1

The Impact of Credit Crunch on Enterprise Financing in Emerging

Markets Does Firm Size Matter

Julia Korostelevaa Natalia Isachenkovab and Yulia Rodionovac

a Dr Julia Korosteleva Lecturer in Business Economics Department of Social Science School of Slavonic and East European Studies University College London 16 Taviton Street London WC1H 0BW UK tel + 44(0) 20 7679 7590 e-mail jkorostelevauclacuk (corresponding author)

b Dr Natalia Isachenkova Faculty of Business and Law Kingston University London Kingston

Hill Kingston upon Thames Surrey KT2 7LB United Kingdom tel +44(0) 20 8547 8206 Fax +44(0) 20 8547 7026 e-mail nisachenkovakingstonacuk

c Dr Yulia Rodionova Senior Lecturer in Finance Department of Accounting and Finance

Leicester Business School De Montfort University The Gateway Leicester LE1 9BH UK tel +44 (0) 11 6257 6098 e-mail yrodionovadmuacuk

This draft 30 January 2012

Abstract

Using panel data on 21867 firms from the 2002-2009 Business Environment and

Enterprise Performance Surveys (BEEPS) we examine how firm-level characteristics and

economy-wide institutional settings influence firmsrsquo perceptions of financial constraints and

their choices of investment finance The data enables a perspective on the effects of the

global financial crisis that in 2008 hit hard the emerging markets of Europe and Central Asia

Our analysis of relative percentages of types of investment finance used by the small and

medium-sized firms (SMEs) in the region vis-agrave-vis the financing mix of large firms points to

a greater flexibility of the SMEs in responding to a sharp credit supply shift smaller firms are

able to respond by increasing relative percentages of alternative financing sources such as

trade credit and external equity As evidenced by the BEEPS data in the midst of the global

credit crunch differences between small and large firms in the degree to which firms say

they are constrained are largely eliminated Tests confirm that it is switching to trade credit at

a time of crisis that can soften financing constraints In particular the relative percentage of

trade credit in the financing mix appears to pick up a significant difference in perceived

financing constraints across the size categories and positively affects the propensity of SMEs

to declare themselves as less financially constrained

Keywords financing constraints SMEsrsquo financing choices trade credit crisis

Acknowledgements We are enormously grateful to David Roodman for his invaluable

advice on the technical part of the project We also thank Mike Adams David Crowther John

Holland Stas Kolenikov Fred Mear Tomek Mickiewicz Ivan Shaliastovich Oleh Tsyvinski

and other participants at the BEROC 2010 International Economics Conference in Minsk

2

BAFA 2011 Conference at Aston Business School and BAFA North 2011 at University of

Salford for useful comments and suggestions The usual caveat applies Yulia Rodionova

gratefully acknowledges funding from the De Montfort University ECR Scheme

1 Introduction

Finance availability and cost have been cited as one of the major constraints for

small and medium-sized enterprises (Beck et al 2005 2006 2008) Given the small scale

of their projects and higher risk associated with the higher asymmetry in information arising

from small and medium-sized businessesrsquo (SMEs) lack of accounting records and credible

reputation financial institutions find it costly to monitor small businesses even if

technological progress particularly in part of the risk scoring techniques have enabled the

banking sector to handle the SMEsrsquo finance better than in the past (de la Torre et al 2008)

A large body of literature documents that financial constraints hinder SMEsrsquo growth

and development (Klapper et al 2002 Pissarides et al 2003 Beck et al 2005

Gorodnichenko and Schnitzer 2010) More specifically Gorodnichenko and Schnitzer

(2010) propose the theoretical model showing that financial constraints reduce the ability of

domestically owned firms to innovate and export with further adverse implications for

productivity growth in the economy Their empirical results based on the 2002-2005

Business Enterprise Environment and Performance Survey data conform to their theoretical

propositions implying that policymakers should focus on addressing the problem of financial

market frictions to enhance productivity at both micro and macro levels

Financial constraints may get particularly severe in the period of crisis with small and

medium-sized businesses expected to suffer disproportionally more than their larger

business counterparts given the overall financial contraction in the domestic economies (as

suggested by the financial accelerator theory of real business cycles) and the inability of

smaller-sized firms to draw upon the international financial markets The 2007-2009 global

credit crunch that severely affected international payments and trade credit hit hard across all

the transition countries especially the exports and production in Eastern Europe (Calderon

and Didier 2009 Didier et al 2011) In this paper we analyse the perceptions of financial

constraints of SMEs and the SMEsrsquo choice of investment finance for the transition economies

over the period of 2002-2009 focusing in particular on the effects of the crisis for SMEs

financing vis-agrave-vis large firms More specifically using the 2002-2009 Business Environment

and Enterprise Performance Survey (BEEPS) data of 21867 firms in Emerging Markets of

Europe and Central Asia we undertake a panel data study to investigate how various firm

characteristics and institutional settings affect firmsrsquo perceptions of financial constraints We

further analyse the implications of the 2007-2009 financial crisis for SMEsrsquo financing choices

3

Our study also links the BEEPS measure of financing constraints with relative changes in the

composition of investment finance In particular we examine whether an increase in the

relative percentage of alternative sources of finance such as trade credit has an impact on

the degree of financing constraints

More specifically we first look at the effect of our variables of interest on the firmsrsquo

perceptions of access to finance in a probit model We find that SMEs though more

financially constrained in general are less so during the crisis so that their perceptions of the

financial constraints do not significantly differ from those of larger firms We further

investigate their financing choices and our findings suggest that the reduction in the degree

of perceived financial constraints between small and large firms may be attributed to SMEs

being more flexible in the choice of the sources of financing such as trade credit and ownerrsquos

contribution This finding sheds new light on the role of SMEs vs large firms as channels of

propagating of monetary and real shocks during a recession

Our work is organised as follows Section Two discusses the peculiarities of firm

financing in transition economies with a specific focus on small businesses Section Three

discusses theoretical and empirical issues pertaining to the determinants of smaller

businessesrsquo financing including in the context of financial crisis Based on that we postulate

our hypotheses Section Four describes the data and the methodology Empirical results

follow in Section Five Finally Section Six presents conclusions and policy implications

2 The stylised facts about SME financing in Transition Economies

To launch and operate new ventures entrepreneurs require financial resources that can

either come from their own savings or are external borrowed in formal and informal financial

markets or raised through issuance of equity shares Empirical studies on SME financing

show that smaller businesses typically rely predominantly on their own equity and informal

finance (primarily family and friendsrsquo funds and investment of other individuals comprising

business angels) and exhibit a moderately low level of formal external financing (Bates

1997 Ravid and Spiegel 1997 Huyghebaert 2001 Bygrave 2003)

The situation with SME finance in transition economies is more complex given that

neither of these sources was widely available in the early stage of transition (Estrin and

Mickiewicz 2010) Although individuals were allowed to deposit their savings in the state

savings banks the accumulation of wealth was low Furthermore the savings that individuals

kept with the state savings bank were eroded by hyperinflation at the start of transition For

these reasons internal finance and funds from family and friends were relatively scarce at the

start of transition and were likely to play less prominent role than in non-transition countries

and in the period of crisis even more so given high sensibility of individualsrsquo savings to

external shocks

4

The required funding was also difficult to raise via bank borrowing given the

underdeveloped and inefficient financial system inherited from the planned economy where

the role of finance was passive for finance served as a monetary counterpart of planning

directives Despite the emergence of new private banks the competition in the banking

sector across the region remained low which can partly be explained by the capital

weakness of new banks making the market very segmented The dominance of state-owned

or (partly) privatised commercial banks made the banking environment very concentrated

with these banks expressing preference for large state-owned or privatised enterprises at the

cost of discouraging new entrants (Rostowski 1995 Berglof and Bolton 2002) A number of

newly established banks did not have enough experience in private sector lending

(Pissarides 1998) and in the situation of a great economic uncertainty preferred occupying

some niches to riskier lending to the real sector in particular to SMEs Such niches for

example included foreign currency transactions short-term lending on the inter-bank market

and operations with governmental securities (Korosteleva and Lawson 2010) Other new

banks so-called lsquopocket banksrsquo were mainly established by privatised larger enterprises to

serve the purpose of financing their own activities bringing to the surface the problem of

connected lending Given all these peculiarities of banksrsquo establishment at the start of

transition small de novo firms were severely restricted in their access to the formal credit

market The situation was aggravated further by the credit crunch that was a result of

macroeconomic stabilisation measures taken by transition governments to curb inflation

High nominal interest rates were a far larger problem for new ventures which typically face

an initial period of negative profitability1

The progress in reforming the financial sector was slow This is confirmed by the EBRD

annual transition indicators measuring the progress in reforms They include (1) the banking

reform and interest rate liberalisation and (2) the securities market and non-bank financial

institutions For those two the average scores for the region reached only 24 and 21

respectively on the scale from 1 (little progress) to 43 (developed market economies

standards) the decade after the transition began In 2009 only the Central and Eastern

European countries (CEECs) which joined the EU scored as high as 4 in both areas of

financial institutional reforms with Latvia Lithuania Slovakia Slovenia Bulgaria and

Romania still being one score down in the area of securities markets The latter three

countries also scored lower than their CEE counterparts in the area of banking sector reform

Some CIS countries such as Belarus Turkmenistan and Uzbekistan viewed as the laggards

in transition still have rankings as low as 1 (Turkmenistan) and 2 (Azerbaijan

1 Pissarides (1998) argues that SMEs often reinforce banksrsquo perceptions of them being unreliable borrowers given frequent under-reporting of profits due to tax avoidance purposes or failure to register ownership of assets prompting lenders to penalise SMEs by charging them higher premium

5

BelarusKyrgyzstan Tajikistan and Uzbekistan) in both areas of the financial institutional

reforms Overall after the years of the financial sector reform the majority of transition

economies still have rather shallow domestic credit systems (Figure 1) and relatively

underdeveloped capital markets with market capitalisation ratio varying from as low as 16

per cent of GDP in Kyrgyzstan and Armenia2 to as high as 40-50 per cent in Croatia amp

Kazakhstan respectively in 2009 with Montenegro and Russia standing out compared with

the rest of the region3

Figures 1 amp 2 to be inserted here

A number of empirical studies further confirm that financial constraints in transition

economies constitute one of the main obstacles for start-up entry and growth (Pissarides

1998 1999 2001 Pissarides et al 2003 Klapper et al 2002) Pissarides (2001) concludes

that lack of access to finance is more binding for SMEs than larger businesses with the

severity of this constraint being stronger in South-East Europe compared to other transition

economies including the Commonwealth of Independent States (CIS) In their study of SME

growth in Russia and Bulgaria Pissarides et al (2003) find that financial constraints hamper

SME growth and that SMEs resort to the use of internal funds to overcome constraints on

external finance This is similar to Johnsonrsquos et al (2002) findings suggesting that internal

finance can substitute for external finance (see also Lizal and Svejnar (2002) for similar

conclusions) Pissarides et al (2003) also show that financial constraints affect SMEs more

than barriers related to property rights issues Drawing on the data on 15 Eastern European

countries Klapper et al (2002) show that financial constraints affect SMEs longer-term ability

to grow Finally Gorodnichenko and Schnitzer (2010) show that financial constraints restrain

the ability of domestically-owned firms to innovate and export thus inhibiting productivity

growth They also argue that this negative effect is magnified due to financial constraints

forcing export and innovation activities to become substitutes whereas they are commonly

found to be complements

We complement these studies with the most recent empirical evidence on the

determinants of SMEsrsquo perception of financial constrains in transition economies which

comes from the 2002-09 BEEPS dataset The BEEPS self-reported measure of financing

constraints unites in one termed lsquoaccess to financersquo metric both quantity and price

constraints In the surveys firms were directly asked to indicate the extent to which access to

2 In fact it goes as low as 02 per cent of GDP in Uzbekistan in 2005 following the World Development Indicators data with no data reported for subsequent years 3 Montenegro and Russia emerge as outliers given their far higher ratios of market capitalisation These are 104 and 70 per cent respectively and they are far above of some West European countriesrsquo ratios including Germany and comparable to the ones in China and USA

6

finance was an obstacle to their operations and the averages for the individual countries in

the dataset are shown in Figure 3 With exception of Bosnia and Uzbekistan4 SMEs in all

transition economies are more financially constrained than larger firms although as our

empirical results show (see Section 5) the difference in perception of financial constraints

has been largely eliminated between smaller and larger firms during the recent global

financial crisis

Figure 3 to be inserted here

It has previously been argued that a low reliance on outside financing scarce use of

equity finance5 and low level of inter-firm trade financing is a common feature of small firms

across the transition region of Europe and Central Asia (Klapper et al 2002 Pissarides

1998 2001) Furthermore Klapperrsquos et al (2002) find almost no use of long-term debt

attributing this to the underdevelopment of the banking sector weak collateral law and poor

credit information registries Their evidence also shows virtually zero reliance of SMEs

across the 15 Eastern European countries on trade credit with the exception of Hungary and

to a lesser extent of the Czech Republic Poland and Romania They explain this by

insufficiency of partner firmsrsquo internal funds or their inability to access external borrowings to

become able to finance extension of trade credit Low reliance on trade credit may be also

attributed to low foreign presence in some countries of the region as multinationals could

extend trade credit to local firms including SMEs (Klapper et al2002)

Figure 4 shows the relative importance of financing sources used for purchase of fixed

assets by SMEs in the transition economies The data underlying this figure are the relative

percentages of the financing sources firms used in the year preceding a BEEPS survey year

in the BEEPS 2002-2009 surveys The surveys group financing sources into the following six

types internal funds or retained earnings ownersrsquo contribution or issued new equity shares

[funds] borrowed from private banks [funds] borrowed from state-owned banks purchases

on credit from suppliers and advances from customers and other (moneylenders friends

relatives non-banking financial institutions) Figure 4 suggests that SMEs in the transition

economies tend to largely rely on their internal funds or retained profits in funding their

investment Only about 23 per cent of small and medium-sized firms rely on borrowing from

private banks Trade credit and equity finance occupy similar shares in funding SMErsquos

investment decisions and account for the mere 9 per cent of total purchase of fixed assets

4 In Bosnia amp Uzbekistan larger firms are marginally more constrained than smaller ones (at 10 percent level of significance) 5 Small firms may also decide to limit their issuance of outside equity to avoid reduction in control of their firms (Scherr et al1990 and Hamilton and Fox 1998 cited in Klapper et al 2002)

7

According to Cull (2007) trade credit can be seen as substitute for loans for private firmsrsquo

trading partners that are shut out of financial credit market Other sources include borrowing

from informal money lenders and family and these emerge as the third important source of

funding SMEsrsquo investment after internal funds and bank credit We expect the informal

finance to be mostly comprised of equity provided by family and friends as funding obtained

from informal private money lenders was overly expensive with the premium standing at least

20 percentage points above that charged by local intermediaries (Pissarides 1998)

Figure 4 to be inserted here

In conclusion we note that the number of studies of the financing decisions of small

and medium-sized enterprises in emerging markets and in particular in the former centrally

planned economies or previously heavily regulated economies such as India has been rather

limited (see eg Nivorozhkin 2005 Delcoure 2007 Crnigoj 2007 Chakraborty 2008

Girma et al 2008 Li et al 2009 Correa et al 2010 Love and Zaidi 2010) We contribute to

this literature by analysing for SMEs in these countries the determinants of the following five

financing options retained earnings private loan (loan finance from private banks) trade

credit private equity (ownersrsquo equity) and informal finance In this study the phrase lsquoinformal

financersquo is an umbrella term that helps condense in one category funds from moneylenders

friends relatives non-banking financial institutions Our results allow us to shed more light

on whether and how the theories of financing choices apply to transition countries in the

credit crunch environment

The following section discusses theories pertaining to small firm financing and how this

may be affected by a financial crisis

3 Small Firm Financing and the Effect of Crisis Theoretical Considerations and

Hypotheses

31 Theoretical arguments

When analysing financing choices of SMEs we first turn to the two cornerstone

theories of explaining leverage the trade-off theory and the pecking order hypothesis (POH)

While the former states that firms may prefer debt to equity in the presence of corporate tax

subject to the costs of potential financial distress stemming from borrowing large amounts

(Modigliani and Miller 1958) the latter suggests that the firms first finance their investment

out of retained earnings as this is the cheapest and the most readily available alternative

then out of debt and lastly via issuing equity which is seen as the most expensive option to

8

the firm (Arnold 2008) More recent literature on firm financing started to look closer at and

emphasize the importance of other sources such as trade credit especially for the small and

medium firms using mostly the data on developed economies For instance Berger amp Udell

(1998) stress the importance of trade credit to the short-term financing of small firms Bevan

and Danbolt (2002) estimate that trade credit account for 62 per cent of total liabilities of UK

firms

The role of trade credit has been seen by some researchers as a substitute of bank

lending for liquidity-constrained firms (Cull 2007) such as SMEs One of the benefits of trade

credit compared to the bank lending is that it allows to partly get around the information

asymmetry problem between the lender and the borrowing SME as business partners would

have more information about the ability of the borrower to repay and about such reputation of

the borrower in the industry Meltzer (1960) Nielsen (2002) and Petersen and Rajan (1997)

argue that trade credit may also provide a means of alternative financing under the tight

monetary conditions such as credit crunches when financial institutions are less able or

willing to provide loans to SMEs In support of this hypothesis Atanasova and Wilson (2003

2004) and Mateut et al (2006) find that under tight monetary conditions firms tend to

substitute bank loans with trade credit However the findings in Bernanke and Gertler (1995)

and Gertler and Gilchrist (1993) do not agree with this hypothesis In line with these authors

Taketa and Udell (2007) using a sample of Japanese SMEs after the crisis years find that

bank lending and trade credit are complements rather than substitutes Love and Zaidi

(2010) report that the use of trade credit by East Asian firms has declined after the 1998

financial crisis together with the use of bank loans Finally interesting enough there is

some empirical evidence which suggests that in the context of transition economies there

may be a higher reliance of SMEs on trade credit in the period of crisis More specifically

focusing on the panel of 1686 firms in Bulgaria Hungary Latvia Lithuania Romania and

Turkey in 2007 and 2009 Klapper and Randall (2010) find that during periods of contractions

in bank credit buyers might depend more on trade credit (although primarily to be used for

short-term financing) that may be particularly true for small firms This provides some support

for the hypothesis that the two sources of finance namely bank loans and trade credit in the

context of transition and emerging economies can be seen as substitutes in period of crisis

Another source of firm financing that has recently received increased attention is

private equity Private equity consists of investments by private individual investors or firms

(business angels investments funds) as well as business ownersrsquo contributions to their

equity The lsquobusiness angelsrsquo type of private equity is currently on the rise in the developed

countries as well as emerging markets such as India Brazil China Malaysia However

ownersrsquo contribution is a far more widespread type of private equity in countries under

consideration Generally SMEs are prone to various types of business and financial risks

9

and it would be very important for them to try and hedge against these risks Zou and Adams

(2008) look at the effect of property insurance on the public firmsrsquo borrowing capacity in

China while Matthews and Scott (1995) in the US and Herbane (2011) in the UK investigate

the types of risk management used by the SMEs The findings point to a rather limited use by

the small and medium-sized enterprises of the risk management assessment and hedging

techniques

In the emerging markets of the post-Soviet bloc the use of risk management techniques

such as hedging with financial derivatives is virtually non-existent However an informal risk

management practice of accumulating cash out of profits and also of using informal lending

from family and friends to serve as a cushion in the times of financial distress as protection

against possible bankruptcy and as an instrument of insurance against risks has been one

way of accounting for the risky nature of SMEs in these countries Secondly many SMEs

sometimes use bankruptcy when they find themselves in the situation of financial distress

and then open a new firm without losing much of their personal assets (Radygin et al 2005)

These SMEs are oftentimes are registered as belonging to a relative or the SMEs could be

registered as founded by an artificially created third party with no links to the actual ownerrsquos

personal assets Recently banks in the new emerging economies such as Russia started a

practice of compulsory purchase of loan insurance if the SME is to take a loan from the bank

This serves as a risk insurance mechanism to a certain extent at the same time however

increasing the cost of bank financing However more recently this practice has attracted the

attention of the Federal Antimonopoly Service that ruled that there is evidence of collusion

between banks and insurance companies Overall we could conclude that the use of risk

management practices is very narrow and of a rather informal nature

The next sub-section explores in greater detail the institutional context of financing in the

situation of economic crisis

Empirical studies on small firm financing in the years of crisis are primarily motivated by

the informational asymmetries theories One of the most important contributions in the study

of the role of SMEs during business cycle has been the real business cycle (RBC) theory

(Bernanke and Gertler 1995 Bernanke Gertler amp Gilchrist 1998) The argument put forward

by the RBC theory is that SMEs face tighter liquidity constraints in terms of external financing

due to higher informational asymmetries associated with their activities the low value of

their assets to serve as collateral the high cost of monitoring small businesses given a small

scale of their investment projects and subsequently the unwillingness of banks to lend to

SMEs

During economic slowdowns when small businesses are even more in need of external

finance bank lending to them diminishes even further which tends to propagate the crisis if

the SMEs then go out of business (see for example Tornell and Westermann 2005) At the

10

same time as larger firms use more finance and tend to rely more on external funding they

may be hit harder by financial contraction in the situation of global crises when international

financial markets dry up so preventing larger firms from drawing upon them when required

They are also less flexible and it is more costly for them to restructure and downsize when

they are hit with external shocks Furthermore while SMEs tend to be more flexible in relying

on other sources of finance including trade credit contributed equity and informal finance

the financial structure of larger firms generally tends to be less diversified with a preference

often given to retained profits and bank finance following the pecking order theory Taken

together we may argue that both supply and demand for finance is more affected for larger

firms in the situation of external shocks

Based on the discussion presented in Sections 2 and 31 we further discuss three main

groups of factors which are likely to affect firmsrsquo perception of financial constraints and their

financing choice strategy These are as follows (1) firm size in general and in the period of

crisis (2) other firm- and industry-specific characteristics including foreign ownership export

orientation firmsrsquo social capital and the degree of competition and its pressure on the firm to

develop a new product and (3) country-level institutional parameters including the degree of

protection of property rights and the development of the financial sector

32 Size of the enterprise and the effect of crisis

With regards to the effect of firm size based on the general discussion in the literature

(see sections 2-31) we expect SMEs to be more financially constrained in their access to

external lending and respectively more reliant on internal funds This is due to insufficient

information that the bank can obtain about a particular SME as well as due to a potentially

lower size of collateral However this lower reliance of SMEs on external debt can potentially

be a source of flexibility during the crisis when formal financial markets dry up and when

even large well-established firms have difficulty obtaining bank credit Furthermore following

Atanasova and Wilson (2003 2004) Mateut et al (2006) and Klapper and Randall (2010) we

expect that under tight monetary conditions SMEs in transition economies are more likely to

switch to alternative forms of financing such as trade credit We also hypothesize that SMEs

are more likely to rely on ownersrsquo contributed equity which they tend to accumulate in good

times as part of their risk management strategy to use it as a cushion in the times of financial

distress In summary we expect the difference between the SMEs and large firms in their

reliance on bank finance to diminish during the crisis years and second SMEs to be more

flexible and rely more on other sources of finance such as trade credit and private equity in

the period of financial contractions

11

33 Firm- and industry- level factors

As far as the firm-level and industry-level variables are concerned we expect the

following results first the level of social capital of a firm as proxied by the inverse of the time

spent dealing with government regulations to indicate possible established connections with

public officials can positively affect its access to trade credit Next the industry-level

pressure on a firm from competitors to develop a new product may increase the firmrsquos

chances of obtaining a bank loan as the bank may perceive the firmrsquos operations as more

diversified and less risky (Isachenkova et al 2011) We also expect foreign competition and

the pressure it exerts on a firm innovation capability to play less important role for firm

financing decisions as SMEs are more likely to operate in market niches and they are

unlikely to compete with multinational enterprises In contrast we expect a pressure

originated from customers on a firm to innovate to increase a firmrsquos probability to rely more

on external sources of funding This may be attributed to the fact that a firm does not only

differentiate itself from other firms further with developing a new product but also assures a

demand for this product by responding to the needs of its existing customers The

guaranteed demand for a new product would be one of the most crucial factors taken into

account by bank managers or potential investors in decision-making concerning project

financing Thirdly international product certification may play a similar role with regards to

bank loans increasing the access to external funds Fourth we investigate the effect on the

choice of financing of the firm age with a square term Generally older firms may have

easier access to bank loans as more information is available about them to the lender (Beck

et al 2006 Canton et al 2010) however due to the particulars of the transition period

sometimes older firms may be less economically viable and unable to get a loan therefore

the sign of this coefficient is uncertain here Lastly we also look at the firmrsquos export

orientation which is expected to increase the reliance on bank lending and its ownership

type where we single out foreign and domestic private firms In the case of foreign firms

they are less likely to use private loans and rely instead on retained earnings and intra-

company funds transfers in the case of MNCs

34 Institutional environment

The impact of institutional variables on the financing choices of firms has been of the

utmost interest to economists and policy-makers during the period of transition (see for

example Stijn and Tzioumis 2006 Mitra et al 2008 see also Commander and Svejnar

(2009) for an in-depth and comprehensive analysis of the impact of various business

environment factors on firm performance using BEEPS 2002 - 2005 panel) In our analysis

12

we concentrate on two institutional factors the degree of protection of property rights and the

size of the formal financial sector which have been claimed to be of key importance for firmsrsquo

financing decisions (see Korosteleva and Mickiewicz (2011) for overview of the related

literature) As far as the property rights protection is concerned it is found to play crucial role

for firm growth and access to external finance (Aidis et al 2008 2010 Korosteleva and

Mickiewicz 2011 Estrin Korosteleva and Mickiewicz 2011) In the environment with weak

protection of property rights financial contracts are less likely to be concluded leading to the

underdevelopment of finance and credit rationing with small firms to be disproportionally

affected the most (Acemoglu and Johnson 2005) Beck et al (2004) show that in terms of

access to external finance small firms benefit disproportionally from higher levels of property

rights protection Lack of secure property rights may also discourage SMEs from taking full

advantage of opportunities to invest (Johnson et al 2002) In a survey of private small

manufacturing firms in Poland Russia Ukraine Romania and Slovakia Johnson et al

(2002) find that small firms tend to reinvest less of their earnings when they perceive their

property rights insecure They also find that the effect of the property rights system is of more

paramount importance for entrepreneursrsquo decisions to reinvest their earnings than availability

of formal finance Moreover if property rights are well-protected this lessens the extent of

potential threat of being expropriated by raidersbank lenders in an artificial bankruptcy

procedure which has been quite a significant issue for firms in Russia and other FSU states

(Radygin et al 2005 Sprenger 2002) Based on this we expect that strong property rights

are likely to encourage SMEs to use more debt as well as to use their own funds and

retained profits for investing in investment projects

With regards to the size of the formal finance as measured by the share of private

credit to GDP the relationship between financial depth and financial constraints has been

extensively studied (Beck et al 2006 also see for example Love 2003 who employing a

sample of 36 countries finds that financial development affects firmsrsquo investment by

increasing the availability of external finance) Financial intermediaries facilitate the risk

amelioration in the presence of problems created by information and transaction frictions by

developing expertise in risk assessment and in monitoring (Levine 1997 Barth et al 2006

Barth et al 2008) Developed financial institutions are found to be particularly beneficial for

small firms compared to large ones (Barth et al 2006 Beck et al 2005 2006 2008)

Pissarides et al (2003) show that financial constraints affect SMEs even more than

deficiency of the property rights protection Accordingly the size of the formal financial

system is expected to be positively related to the use of bank finance as a better functioning

financial system should help ease up borrowing constraints

4 Data and Methodology

13

41 Sample

To explore the determinants of the financial structure of small businesses we use the

2002-2009 Business Environment and Enterprise Performance Survey (BEEPS) data6 of

21867 firms covering 26 transition economies of Europe and Central Asia (ECA)7

The sample is primarily comprised of small and medium-sized businesses8 which

account for 893 per cent of the sample The sample is representative in terms of industrial

coverage with the majority of SMEs of the sample operating in manufacturing wholesale

and retailing industries

BEEPS dataset provides rich information on firm characteristics investment

behaviour and firmsrsquo perception of business environment including financial constraints

which are of a primary interest for our investigation of the effect of the recent financial crisis

on firmsrsquo perception of financial constraints Potentially we could use other micro-level data

characterising various domains of business environment captured by firmsrsquo perceptions for

investigating the effects of the institutional settings However using these micro-level

indicators as explanatory variables would make our study plagued with a problem of

endogeneity To avoid this we merge our firm-level data with country-level indicators

characterising various institutional domains The country level data were obtained from the

World Development Indicators (World Bank) and Polity IV databases (for further discussion

see below) Finally the BEEPs dataset contains other useful information which allows us to

shed light of the effect of for example social capital as proxied by the indirect measure of

possible connections with the authorities (see below for the definition of the variable) on firm

financing

42 Variable Definition and Measurement

Explanatory variables

6 This data is a joint project of the European Bank for Reconstruction and Development and World Bank The first survey was launched in 1999 The dataset used in the present study is an unbalanced panel covering the years of 2002 2005 2007-2009 7 The sample includes the following countries Albania Armenia Azerbaijan Belarus Bosnia Bulgaria Croatia Czech Republic Estonia FYROM Georgia Hungary Kazakhstan Kyrgyzstan Latvia Lithuania Moldova Montenegro Poland Romania Russia Serbia Slovakia Slovenia Tajikistan and Ukraine We exclude Uzbekistan as an outlier from our sample We also exclude Turkey as it is not classified as a post-communist country undertaking transition from a planned to a market economy 8 We utilize the EU employment criterion to define small and medium-sized businesses More specifically businesses are defined as micro if they employ 9 and less employees small ndash between 10 and 49 medium ndash between 50 and 249 and large ndash over 250 employees Respectively SMEs are defined as firms employing less than 249 firms

14

To test our main hypothesis of the effect of a firm size on firmsrsquo perception of financial

constraints we introduce a dummy variable denoting small and medium-sized business

coded as 1 if firms are classified as small or medium-sized businesses according to the EU

definition based on the employment criterion For robustness of our results we also use a

continuous variable denoting a size of employment as measured by the natural logarithm of

employment9 The obtained results are consistent with the ones using the SME indicators

To capture the effect of the recent financial crisis we introduce a crisis dummy coded

as 1 if the year of survey is equal to 2008 or 200910

We also introduce a number of firm-level controls which include age of firm11 type of

ownership including private and foreign ownership export orientation and whether a firm

has an internationally certified product all equal to 1 if a business has a respectively listed

characteristic and zero otherwise We also examine the effect of various sources of pressure

on firms to innovate ndash the indicators which are considered to be important for firm investment

decisions Respectively the pressure for innovation may stem from domestic competition

foreign competition and customers To capture the effect of a firmrsquos social capital we

introduce an indicator which indirectly may capture some possible connections of a firm with

authorities It is proxied by time spent by each firm on dealing with government regulations

We assume the less time firms spend dealing with government regulations the more likely

they have some established connections with public officials which allow them to avoid

burdensome regulation procedures

In our study we also introduce a number of country-level variables which characterize

the institutional environment in the countries covered by our sample More specifically we

include an indicator of the financial development as measured by the ratio of domestic credit

to private sector to GDP (one year lag to avoid potential endogeneity) obtained from the

World Bank World Development Indicators (World Bank 2011) This measure has been used

in previous studies (Klapper et al 2006) and it is expected to be of a primary importance for

transition economies where firms tend to rely more on bank finance rather than capital

markets We also introduce a measure of property rights protection (a one year lag) proxied

by the indicator of effective constraints imposed on the executive branch of the government

and obtained from Polity IV project12 This measure of property rights protection is

9 These results are not reported here to save some space However they can be obtained from authors upon request 10 Here it is important to note that although the financial crisis has started in 2007 in the USA it spread to transition economies in 2008-2009 11 Some studies find a non-monotonic relationship between age and firm decision-making In this study we introduce a squared term of age along with a age variable to capture this possible non-linearity 12 Available from httpwwwsystemicpeaceorgpolitypolity4htm

15

considered to be superior to other indicators including the index of property rights reported

by the Heritage Foundation ndashWall Street Journal (for further discussion see Acemoglu and

Johnson 2005 Glaeser et al 2004 Estrin Korosteleva and Mickieiwcz 2011)

In the present study we also introduce macroeconomic controls including cyclical

economic performance as measured by the one year lag of the GDP annual growth rate

and the level of economic development as proxied by a set of GDP pc dummies denoting

the five quintiles of its distribution to address the problem of potential multicollinearity with the

measure of financial development

Finally we include industry and country controls in all our specifications Introducing

country dummies into analysis allows to control for cross-country heterogeneity

For further definition of all variables their descriptive statistics and correlation matrix

see Tables 1-2

43 Dependent variables

To investigate the effect of a firmrsquos size on its perception of financial constraints we

construct a dummy variable coded as 1 capturing a major and very severe obstacle for

access to finance and 0 otherwise

The firm financing choices are defined by the five individual dependent variables

associated with tobit financial choice equations in the seemingly unrelated regression

equations model

One important thing to mention here is the inability to distinguish between

owninternal funds and external private equity considered as one of the limitations of the

2002-2009 BEEPS dataset In the period under investigation BEEPS offers two questions

which aim to capture the use of equity The first one centres around retained earnings and

the second one shows ownersrsquo contributions and private equity or issued new equity

Following some theoretical considerations discussed in sections 2 and 3 in the context of

SMEs we expect the second element of equity to be primarily comprised of existing ownersrsquo

new contributions rather than private equity

Thus the indicator of financial choices represents a set of five individual dependent

variables including retained earnings contributed earnings private borrowing informal

finance trade credit with each of them constructed as a share in total financing of SMErsquos

investment decisions (see Table 1)

44 Methods

16

In this study we employ a number of estimators to obtain robust results More

specifically we use a probit model to investigate the effect of a firm size and the recent

financial crisis on firmsrsquo perception of financial constraints The effect of a firm size in the

situation of crisis is captured by the introduction of the interaction term between firm size as

proxied by the SME indicator and a financial crisis dummy

We further employ the seemingly unrelated regression equations model combined

with the tobit approach for studying firmsrsquo financial structure

Probit model of perception of financial constraints

In the probit model the probability of a firmrsquos perception of financial constraints as

major(j = 1) can be written as follows

( ) ( )int ++

++

infinminus

minus===

ijitj uXjitiitit ijitjuXjy uX

βα βαππ 212-

)()(2 21exp|Pr

Where ity is our measure of financial constraints as perceived by firms and itX is a

set of our explanatory variables discussed in detail in sections 3-4 Here it is important to

note that the interaction term in a probit model cannot be interpreted in a similar way as in

linear models and disregarding this may lead to misleading estimates of the interaction

effect which is of crucial importance for our study (Norton Wang and Ai 2004) Respectively

for robustness of our results here we follow the framework suggested by Norton Wang and

Ai (2004) to account for the model nonlinearity The adjusted marginal effects for the

interaction term are reported in the note to Table 313

Simultaneous Model of Financing Choices

As mentioned above we next model the choice of all five financing choices explicitly

We also hypothesise (following Isachenkova et al 2011) that firm financing choices are likely

to be determined jointly A standard way of modelling jointly determined indicators is a

system of equations - SURE ndash seemingly unrelated regression equations where equations

are linked only by their errors (Zellner 1962) We therefore model the five types of sources of

finance (internal funds private bank borrowing informal finance trade credit and private

13 We also run a probit regression for a split sample of (1) SMEs and (2) large firms to check the robustness of our results (based on the interaction term) while addressing a problem of multicollinearity between a crisis variable and its interaction term with a SME variable The correlation coefficient between a crisis variable and its interaction term with a SME variable is equal to 93 This can be attributed by the problem of a sample being overrepresented by SMEs which constitute 90 of all surveyed firms The results remain robust and can be available from authors upon request

17

equity) using a SURE framework within which we specify a set of five tobit regressions with

correlated residuals

We employ the STATA cmp module which allows to it Seemingly Unrelated Regressions

using the simulated likelihood method such as the Geweke Hajivassiliou and Keane (GHK)

algorithm (for further discussion see Roodman 2008) We utilise a tobit equation to model

each individual financial choice of firms because our dependent financing choices variables

are continuous but their range is constrained (censored) with a substantial number of

observations either equal to zero denoting those who do not use the respective source of

finance or to 100 showing the opposite Other observations are positive and may produce

many different outcomes (Verbeek 2000) Each tobit equation uses a set of identical

explanatory variables that proxy factors which could possibly be associated with firmrsquos

financing choices including industry and country dummies

We also considered the bias caused by potential interdependence between the choice of

whether to invest and firmrsquos financing choices We accounted for the potential selection bias

by introducing into the financial choices SURE Tobit equations (second stage outcome

equations14) the inverse Millrsquos ratio calculated based on modelling the choice to invest in

fixed assets (first stage or selection equation) To identify the first stage of the Heckman

selection model we chose a variable which is correlated with the first stage dependent

variable (investment decision) but not with the second ones (financing choices) We used the

rate of capacity utilization as part of our identification strategy Capacity utilization shows the

percentage of capital stock in use the higher is the rate the more likely firms will increase

investment Batyaeva and Aukutsionek (2001) show that the rate of capacity utilization is

higher in the group of investing firms than in the group of non-investing firms in Russia15 We

calculated the inverse Millrsquos ratio based on the above selection equation16 and included it as

a control in the second stage SURE Tobit equations The inverse Millrsquos ratio has only proved

to be statistically significant in the private bank loan equation pointing to the potential

selection bias arising from the possibility that the factors determining the decision to invest

might differ from those determining the use of bank financing in purchasing fixed assets

14 We also attempted to estimate an investment equation jointly with Tobit financial choices equations within the SURE framework using However given the overall complexity of the model we failed to do this We proceeded further with a two-stage approach by estimating an investment probit equation and calculating the inverse Millrsquos ratio that we add into the outcome financial choices equations at the second stage of the analysis to test for the selection bias 15 We performed an independent sample t-test to check whether the rate of capacity utilization is statistically significantly higher for investing firms compared to non-investing firms for our sample The null hypothesis of no difference was rejected at 1 level of significance 16 To economize on space we do not report the results of the investment probit equation but they are available from authorsrsquo upon request

18

Finally In Table 6 we attempt to condition the determinants of financing constraints

declared by SMEs on the relative percentage increase of trade credit in total funds used for

real investment As mentioned above in Section 2 the timings of measuring the composition

of financing sources precede by a year the timings of measuring the perceptions of financing

constraints That feature of the BEEPSrsquo design allays a likely concern about the endogeneity

of the relative proportion of trade credit and enables causal inference We too report in thre

note to Table 4 the adjusted marginal effects for the interaction term of the SME dummy with

the trade credit variable

In the next section we discuss our empirical results

5 Empirical Results

Table 3 reports the results of the probit model with the marginal effects for firmsrsquo

perception of financial constraints while Tables 4-5 summarize the results of SURE tobits for

a more detailed breakdown of five financing choices More specifically Table 4 reports the

results based on the whole sample to give a comparative perspective on SMErsquos financing

strategy vis-a-vis large businesses whereas Table 5 reports the results based on a

subsample of small and medium-sized firms to shed some light on their financing choices in

the period of crisis

Perception of financial constraints

Table 3 shows that generally small and medium-sized enterprises feel more financially

constrained with the coefficient for SME dummy in relation to the large firms being positive

and significant which is consistent with our discussion in sections 2-3 However the

coefficient of the interaction term with the Crisis dummy turns out to be negative and

significant in relation to the perception of financial constraints as a major obstacle and it

tends to outweigh the effect of a SME dummy when we calculate marginal effects The effect

of the interaction terms with the crisis remains robust after we adjust for non-linearity using

the framework proposed by Norton Wang and Ai (2004)17 Overall these results confirm

that small and medium-sized enterprises are much less financially constrained during the

crisis years with their perceptions close to those of the large firms This result is a polar

opposite to that obtained for the SMEs in the UK (Fraser 2009) which finds that not only do

SMEs generally feel more financially constrained but they report to be even more so during

17 We also check the robustness of our results to the potential problem of multicollinearity between a crisis dummy and its interaction term with SME by splitting a sample and testing the same specification separately for SMEs and large firms We also perform another robustness check by breaking a SME dummy into three subsequent dummies namely micro- small- and medium-sized firms The difference in perception of financial constraints gets almost eliminated in the case of small firms and is largely reduced in the case of micro firms whereas it is less so for medium-sized firms

19

the last crisis We could explain this striking difference by the peculiarities of the SMEs

functioning in new emerging economies The lower reliance of SMEs on external debt in

good times (as shown by results which are discussed below) gives SMEs some flexibility

during the crisis when formal financial markets dry up Jointly with overall flexibility to make

necessary cost cuts and to restructure a business this overall lower reliance on external

funding and the use of alternative sources of financing makes SMEs feel less financially

constrained under the crisis as compared to larger firms

We also find that a more developed financial sector as proxied by domestic private

credit as proportion of GDP helps ease up financial constraints This is in line with the

general literature suggesting that better functioning financial intermediaries facilitate the risk

amelioration in the presence of problems created by market frictions (Levine 1997 Barth et

al 2006 Barth et al 2008)

Unfortunately we fail to find any significant effect of the property rights protection on

firmsrsquo perception of financial constraints that may be explained by the fact that the effect of a

more developed financial sector is likely to outweigh the effect of the property rights

protection

Finally we also find that foreign ownership and international product certificate may

reduce firmsrsquo borrowing constraints while any pressure from domestic or foreign competition

so is pressure from the customers to innovate will increase firmrsquos perception of financial

constraints as major given that firms envisage the need to secure external funding for RampD

or any other innovation-related activities

Financing choices for investment in fixed assets

The results in Table 4 indicate that small enterprises tend to rely more on internal funds

and less on bank loans but they are no different from larger firms in respect of using informal

funds trade credit or private equity which is generally consistent with our discussion in

Sections 2 and 3 The results of Table 5 suggest however that under crisis small and

medium-sized firms tend to switch to other sources of finance such as trade credit and

ownerrsquos contributed equity and to respectively reduce the reliance on retained earnings

perhaps because they decrease due to the negative impact of crisis internal funds With

regards to our discussion of SMEsrsquo risk management we note that the use of private equity

(ownerrsquos contribution) during the crisis years increases which could indicate that the ownerrsquos

funds are used as a cushion in the period of financial distress

An interesting insight regarding the use of trade credit emerges for SMEs in our

sample although in non-crisis years small and medium-sized businesses are not significantly

different from larger firms in terms of reliance on trade credit SMEs tend to finance a

significantly higher proportion of their fixed asset investment by trade credit than large firms

20

in the period of crisis While the latter finding is partly in line with some other studies ndash such

as Klapper and Randall (2010) using BEEPS data it is in stark contrast with similar studies

of the UK private firms (Rehman 2011) for which the use of trade credit is found to have

dried up in crisis This could partly be due to the passed legislation in the UK tightening trade

credit regulation as the result of the abuse of trade credit by large firms in relation to small

firms which forced many SMEs out of the market

With regards to the other firm-level characteristics international certification makes the

firm rely more on private bank loans and informal finance (Table 5) while SMEs with foreign

ownership rely less on private debt but more on retained earnings Both results are

consistent with our hypotheses discussed above Export-oriented small and medium-sized

businesses tend to have greater reliance on trade credit and they use less of internal funds

We find a non-monotonic relationship between age and private equity with both younger and

older firms being more reliant on this source of funding We find some fragmentary support

for private domestic SMEs relying more on informal finance while tending to use less trade

credit and private equity (Table 5)

Interestingly our results (Tables 4-5) suggest that firms which lack some social

connections with governmental officials proxied by the higher amount of time spent dealing

with government regulations are more likely to rely on informal finance trade credit and

private equity In turn businesses which are connected to governmental officials use more

retained profits to fund investment in fixed assets This may be attributed to their connections

serving as a guarantee from expropriation of assets by all sort of rent-seeking individuals

akin private contracting to secure property rights protection This result should be interpreted

jointly with the property rights protection results We expected that better property rights

protection is likely to facilitate firmsrsquo access to bank loan but we failed to confirm this

Perhaps regardless some attempts at a constitutional level to prevent arbitrary government

(which is proxied by our measure of property rights) expropriation culture is still deeply

embedded in the society of post-communist countries and it may manifest in different ways

Welter and Smallbone (2011) argue that entrepreneurs in transition economies have learnt

how to respond to institutional deficiencies in particular weak property rights protection For

example some businesses experiencing high growth choose to invest in unrelated

businesses instead of growing their core businesses for the reason they do not want to

become too noticeable to attract too much attention of the wrong sort In our instance having

some connections with officials seems also to serve as protection against arbitrary

government or individual rent-seeking that makes businesses more keen on re-investing their

retained profits (see Johnson et al (2002) on the discussion of how more secure property

rights can make small firms reinvest more of their earnings)

3

Our study also links the BEEPS measure of financing constraints with relative changes in the

composition of investment finance In particular we examine whether an increase in the

relative percentage of alternative sources of finance such as trade credit has an impact on

the degree of financing constraints

More specifically we first look at the effect of our variables of interest on the firmsrsquo

perceptions of access to finance in a probit model We find that SMEs though more

financially constrained in general are less so during the crisis so that their perceptions of the

financial constraints do not significantly differ from those of larger firms We further

investigate their financing choices and our findings suggest that the reduction in the degree

of perceived financial constraints between small and large firms may be attributed to SMEs

being more flexible in the choice of the sources of financing such as trade credit and ownerrsquos

contribution This finding sheds new light on the role of SMEs vs large firms as channels of

propagating of monetary and real shocks during a recession

Our work is organised as follows Section Two discusses the peculiarities of firm

financing in transition economies with a specific focus on small businesses Section Three

discusses theoretical and empirical issues pertaining to the determinants of smaller

businessesrsquo financing including in the context of financial crisis Based on that we postulate

our hypotheses Section Four describes the data and the methodology Empirical results

follow in Section Five Finally Section Six presents conclusions and policy implications

2 The stylised facts about SME financing in Transition Economies

To launch and operate new ventures entrepreneurs require financial resources that can

either come from their own savings or are external borrowed in formal and informal financial

markets or raised through issuance of equity shares Empirical studies on SME financing

show that smaller businesses typically rely predominantly on their own equity and informal

finance (primarily family and friendsrsquo funds and investment of other individuals comprising

business angels) and exhibit a moderately low level of formal external financing (Bates

1997 Ravid and Spiegel 1997 Huyghebaert 2001 Bygrave 2003)

The situation with SME finance in transition economies is more complex given that

neither of these sources was widely available in the early stage of transition (Estrin and

Mickiewicz 2010) Although individuals were allowed to deposit their savings in the state

savings banks the accumulation of wealth was low Furthermore the savings that individuals

kept with the state savings bank were eroded by hyperinflation at the start of transition For

these reasons internal finance and funds from family and friends were relatively scarce at the

start of transition and were likely to play less prominent role than in non-transition countries

and in the period of crisis even more so given high sensibility of individualsrsquo savings to

external shocks

4

The required funding was also difficult to raise via bank borrowing given the

underdeveloped and inefficient financial system inherited from the planned economy where

the role of finance was passive for finance served as a monetary counterpart of planning

directives Despite the emergence of new private banks the competition in the banking

sector across the region remained low which can partly be explained by the capital

weakness of new banks making the market very segmented The dominance of state-owned

or (partly) privatised commercial banks made the banking environment very concentrated

with these banks expressing preference for large state-owned or privatised enterprises at the

cost of discouraging new entrants (Rostowski 1995 Berglof and Bolton 2002) A number of

newly established banks did not have enough experience in private sector lending

(Pissarides 1998) and in the situation of a great economic uncertainty preferred occupying

some niches to riskier lending to the real sector in particular to SMEs Such niches for

example included foreign currency transactions short-term lending on the inter-bank market

and operations with governmental securities (Korosteleva and Lawson 2010) Other new

banks so-called lsquopocket banksrsquo were mainly established by privatised larger enterprises to

serve the purpose of financing their own activities bringing to the surface the problem of

connected lending Given all these peculiarities of banksrsquo establishment at the start of

transition small de novo firms were severely restricted in their access to the formal credit

market The situation was aggravated further by the credit crunch that was a result of

macroeconomic stabilisation measures taken by transition governments to curb inflation

High nominal interest rates were a far larger problem for new ventures which typically face

an initial period of negative profitability1

The progress in reforming the financial sector was slow This is confirmed by the EBRD

annual transition indicators measuring the progress in reforms They include (1) the banking

reform and interest rate liberalisation and (2) the securities market and non-bank financial

institutions For those two the average scores for the region reached only 24 and 21

respectively on the scale from 1 (little progress) to 43 (developed market economies

standards) the decade after the transition began In 2009 only the Central and Eastern

European countries (CEECs) which joined the EU scored as high as 4 in both areas of

financial institutional reforms with Latvia Lithuania Slovakia Slovenia Bulgaria and

Romania still being one score down in the area of securities markets The latter three

countries also scored lower than their CEE counterparts in the area of banking sector reform

Some CIS countries such as Belarus Turkmenistan and Uzbekistan viewed as the laggards

in transition still have rankings as low as 1 (Turkmenistan) and 2 (Azerbaijan

1 Pissarides (1998) argues that SMEs often reinforce banksrsquo perceptions of them being unreliable borrowers given frequent under-reporting of profits due to tax avoidance purposes or failure to register ownership of assets prompting lenders to penalise SMEs by charging them higher premium

5

BelarusKyrgyzstan Tajikistan and Uzbekistan) in both areas of the financial institutional

reforms Overall after the years of the financial sector reform the majority of transition

economies still have rather shallow domestic credit systems (Figure 1) and relatively

underdeveloped capital markets with market capitalisation ratio varying from as low as 16

per cent of GDP in Kyrgyzstan and Armenia2 to as high as 40-50 per cent in Croatia amp

Kazakhstan respectively in 2009 with Montenegro and Russia standing out compared with

the rest of the region3

Figures 1 amp 2 to be inserted here

A number of empirical studies further confirm that financial constraints in transition

economies constitute one of the main obstacles for start-up entry and growth (Pissarides

1998 1999 2001 Pissarides et al 2003 Klapper et al 2002) Pissarides (2001) concludes

that lack of access to finance is more binding for SMEs than larger businesses with the

severity of this constraint being stronger in South-East Europe compared to other transition

economies including the Commonwealth of Independent States (CIS) In their study of SME

growth in Russia and Bulgaria Pissarides et al (2003) find that financial constraints hamper

SME growth and that SMEs resort to the use of internal funds to overcome constraints on

external finance This is similar to Johnsonrsquos et al (2002) findings suggesting that internal

finance can substitute for external finance (see also Lizal and Svejnar (2002) for similar

conclusions) Pissarides et al (2003) also show that financial constraints affect SMEs more

than barriers related to property rights issues Drawing on the data on 15 Eastern European

countries Klapper et al (2002) show that financial constraints affect SMEs longer-term ability

to grow Finally Gorodnichenko and Schnitzer (2010) show that financial constraints restrain

the ability of domestically-owned firms to innovate and export thus inhibiting productivity

growth They also argue that this negative effect is magnified due to financial constraints

forcing export and innovation activities to become substitutes whereas they are commonly

found to be complements

We complement these studies with the most recent empirical evidence on the

determinants of SMEsrsquo perception of financial constrains in transition economies which

comes from the 2002-09 BEEPS dataset The BEEPS self-reported measure of financing

constraints unites in one termed lsquoaccess to financersquo metric both quantity and price

constraints In the surveys firms were directly asked to indicate the extent to which access to

2 In fact it goes as low as 02 per cent of GDP in Uzbekistan in 2005 following the World Development Indicators data with no data reported for subsequent years 3 Montenegro and Russia emerge as outliers given their far higher ratios of market capitalisation These are 104 and 70 per cent respectively and they are far above of some West European countriesrsquo ratios including Germany and comparable to the ones in China and USA

6

finance was an obstacle to their operations and the averages for the individual countries in

the dataset are shown in Figure 3 With exception of Bosnia and Uzbekistan4 SMEs in all

transition economies are more financially constrained than larger firms although as our

empirical results show (see Section 5) the difference in perception of financial constraints

has been largely eliminated between smaller and larger firms during the recent global

financial crisis

Figure 3 to be inserted here

It has previously been argued that a low reliance on outside financing scarce use of

equity finance5 and low level of inter-firm trade financing is a common feature of small firms

across the transition region of Europe and Central Asia (Klapper et al 2002 Pissarides

1998 2001) Furthermore Klapperrsquos et al (2002) find almost no use of long-term debt

attributing this to the underdevelopment of the banking sector weak collateral law and poor

credit information registries Their evidence also shows virtually zero reliance of SMEs

across the 15 Eastern European countries on trade credit with the exception of Hungary and

to a lesser extent of the Czech Republic Poland and Romania They explain this by

insufficiency of partner firmsrsquo internal funds or their inability to access external borrowings to

become able to finance extension of trade credit Low reliance on trade credit may be also

attributed to low foreign presence in some countries of the region as multinationals could

extend trade credit to local firms including SMEs (Klapper et al2002)

Figure 4 shows the relative importance of financing sources used for purchase of fixed

assets by SMEs in the transition economies The data underlying this figure are the relative

percentages of the financing sources firms used in the year preceding a BEEPS survey year

in the BEEPS 2002-2009 surveys The surveys group financing sources into the following six

types internal funds or retained earnings ownersrsquo contribution or issued new equity shares

[funds] borrowed from private banks [funds] borrowed from state-owned banks purchases

on credit from suppliers and advances from customers and other (moneylenders friends

relatives non-banking financial institutions) Figure 4 suggests that SMEs in the transition

economies tend to largely rely on their internal funds or retained profits in funding their

investment Only about 23 per cent of small and medium-sized firms rely on borrowing from

private banks Trade credit and equity finance occupy similar shares in funding SMErsquos

investment decisions and account for the mere 9 per cent of total purchase of fixed assets

4 In Bosnia amp Uzbekistan larger firms are marginally more constrained than smaller ones (at 10 percent level of significance) 5 Small firms may also decide to limit their issuance of outside equity to avoid reduction in control of their firms (Scherr et al1990 and Hamilton and Fox 1998 cited in Klapper et al 2002)

7

According to Cull (2007) trade credit can be seen as substitute for loans for private firmsrsquo

trading partners that are shut out of financial credit market Other sources include borrowing

from informal money lenders and family and these emerge as the third important source of

funding SMEsrsquo investment after internal funds and bank credit We expect the informal

finance to be mostly comprised of equity provided by family and friends as funding obtained

from informal private money lenders was overly expensive with the premium standing at least

20 percentage points above that charged by local intermediaries (Pissarides 1998)

Figure 4 to be inserted here

In conclusion we note that the number of studies of the financing decisions of small

and medium-sized enterprises in emerging markets and in particular in the former centrally

planned economies or previously heavily regulated economies such as India has been rather

limited (see eg Nivorozhkin 2005 Delcoure 2007 Crnigoj 2007 Chakraborty 2008

Girma et al 2008 Li et al 2009 Correa et al 2010 Love and Zaidi 2010) We contribute to

this literature by analysing for SMEs in these countries the determinants of the following five

financing options retained earnings private loan (loan finance from private banks) trade

credit private equity (ownersrsquo equity) and informal finance In this study the phrase lsquoinformal

financersquo is an umbrella term that helps condense in one category funds from moneylenders

friends relatives non-banking financial institutions Our results allow us to shed more light

on whether and how the theories of financing choices apply to transition countries in the

credit crunch environment

The following section discusses theories pertaining to small firm financing and how this

may be affected by a financial crisis

3 Small Firm Financing and the Effect of Crisis Theoretical Considerations and

Hypotheses

31 Theoretical arguments

When analysing financing choices of SMEs we first turn to the two cornerstone

theories of explaining leverage the trade-off theory and the pecking order hypothesis (POH)

While the former states that firms may prefer debt to equity in the presence of corporate tax

subject to the costs of potential financial distress stemming from borrowing large amounts

(Modigliani and Miller 1958) the latter suggests that the firms first finance their investment

out of retained earnings as this is the cheapest and the most readily available alternative

then out of debt and lastly via issuing equity which is seen as the most expensive option to

8

the firm (Arnold 2008) More recent literature on firm financing started to look closer at and

emphasize the importance of other sources such as trade credit especially for the small and

medium firms using mostly the data on developed economies For instance Berger amp Udell

(1998) stress the importance of trade credit to the short-term financing of small firms Bevan

and Danbolt (2002) estimate that trade credit account for 62 per cent of total liabilities of UK

firms

The role of trade credit has been seen by some researchers as a substitute of bank

lending for liquidity-constrained firms (Cull 2007) such as SMEs One of the benefits of trade

credit compared to the bank lending is that it allows to partly get around the information

asymmetry problem between the lender and the borrowing SME as business partners would

have more information about the ability of the borrower to repay and about such reputation of

the borrower in the industry Meltzer (1960) Nielsen (2002) and Petersen and Rajan (1997)

argue that trade credit may also provide a means of alternative financing under the tight

monetary conditions such as credit crunches when financial institutions are less able or

willing to provide loans to SMEs In support of this hypothesis Atanasova and Wilson (2003

2004) and Mateut et al (2006) find that under tight monetary conditions firms tend to

substitute bank loans with trade credit However the findings in Bernanke and Gertler (1995)

and Gertler and Gilchrist (1993) do not agree with this hypothesis In line with these authors

Taketa and Udell (2007) using a sample of Japanese SMEs after the crisis years find that

bank lending and trade credit are complements rather than substitutes Love and Zaidi

(2010) report that the use of trade credit by East Asian firms has declined after the 1998

financial crisis together with the use of bank loans Finally interesting enough there is

some empirical evidence which suggests that in the context of transition economies there

may be a higher reliance of SMEs on trade credit in the period of crisis More specifically

focusing on the panel of 1686 firms in Bulgaria Hungary Latvia Lithuania Romania and

Turkey in 2007 and 2009 Klapper and Randall (2010) find that during periods of contractions

in bank credit buyers might depend more on trade credit (although primarily to be used for

short-term financing) that may be particularly true for small firms This provides some support

for the hypothesis that the two sources of finance namely bank loans and trade credit in the

context of transition and emerging economies can be seen as substitutes in period of crisis

Another source of firm financing that has recently received increased attention is

private equity Private equity consists of investments by private individual investors or firms

(business angels investments funds) as well as business ownersrsquo contributions to their

equity The lsquobusiness angelsrsquo type of private equity is currently on the rise in the developed

countries as well as emerging markets such as India Brazil China Malaysia However

ownersrsquo contribution is a far more widespread type of private equity in countries under

consideration Generally SMEs are prone to various types of business and financial risks

9

and it would be very important for them to try and hedge against these risks Zou and Adams

(2008) look at the effect of property insurance on the public firmsrsquo borrowing capacity in

China while Matthews and Scott (1995) in the US and Herbane (2011) in the UK investigate

the types of risk management used by the SMEs The findings point to a rather limited use by

the small and medium-sized enterprises of the risk management assessment and hedging

techniques

In the emerging markets of the post-Soviet bloc the use of risk management techniques

such as hedging with financial derivatives is virtually non-existent However an informal risk

management practice of accumulating cash out of profits and also of using informal lending

from family and friends to serve as a cushion in the times of financial distress as protection

against possible bankruptcy and as an instrument of insurance against risks has been one

way of accounting for the risky nature of SMEs in these countries Secondly many SMEs

sometimes use bankruptcy when they find themselves in the situation of financial distress

and then open a new firm without losing much of their personal assets (Radygin et al 2005)

These SMEs are oftentimes are registered as belonging to a relative or the SMEs could be

registered as founded by an artificially created third party with no links to the actual ownerrsquos

personal assets Recently banks in the new emerging economies such as Russia started a

practice of compulsory purchase of loan insurance if the SME is to take a loan from the bank

This serves as a risk insurance mechanism to a certain extent at the same time however

increasing the cost of bank financing However more recently this practice has attracted the

attention of the Federal Antimonopoly Service that ruled that there is evidence of collusion

between banks and insurance companies Overall we could conclude that the use of risk

management practices is very narrow and of a rather informal nature

The next sub-section explores in greater detail the institutional context of financing in the

situation of economic crisis

Empirical studies on small firm financing in the years of crisis are primarily motivated by

the informational asymmetries theories One of the most important contributions in the study

of the role of SMEs during business cycle has been the real business cycle (RBC) theory

(Bernanke and Gertler 1995 Bernanke Gertler amp Gilchrist 1998) The argument put forward

by the RBC theory is that SMEs face tighter liquidity constraints in terms of external financing

due to higher informational asymmetries associated with their activities the low value of

their assets to serve as collateral the high cost of monitoring small businesses given a small

scale of their investment projects and subsequently the unwillingness of banks to lend to

SMEs

During economic slowdowns when small businesses are even more in need of external

finance bank lending to them diminishes even further which tends to propagate the crisis if

the SMEs then go out of business (see for example Tornell and Westermann 2005) At the

10

same time as larger firms use more finance and tend to rely more on external funding they

may be hit harder by financial contraction in the situation of global crises when international

financial markets dry up so preventing larger firms from drawing upon them when required

They are also less flexible and it is more costly for them to restructure and downsize when

they are hit with external shocks Furthermore while SMEs tend to be more flexible in relying

on other sources of finance including trade credit contributed equity and informal finance

the financial structure of larger firms generally tends to be less diversified with a preference

often given to retained profits and bank finance following the pecking order theory Taken

together we may argue that both supply and demand for finance is more affected for larger

firms in the situation of external shocks

Based on the discussion presented in Sections 2 and 31 we further discuss three main

groups of factors which are likely to affect firmsrsquo perception of financial constraints and their

financing choice strategy These are as follows (1) firm size in general and in the period of

crisis (2) other firm- and industry-specific characteristics including foreign ownership export

orientation firmsrsquo social capital and the degree of competition and its pressure on the firm to

develop a new product and (3) country-level institutional parameters including the degree of

protection of property rights and the development of the financial sector

32 Size of the enterprise and the effect of crisis

With regards to the effect of firm size based on the general discussion in the literature

(see sections 2-31) we expect SMEs to be more financially constrained in their access to

external lending and respectively more reliant on internal funds This is due to insufficient

information that the bank can obtain about a particular SME as well as due to a potentially

lower size of collateral However this lower reliance of SMEs on external debt can potentially

be a source of flexibility during the crisis when formal financial markets dry up and when

even large well-established firms have difficulty obtaining bank credit Furthermore following

Atanasova and Wilson (2003 2004) Mateut et al (2006) and Klapper and Randall (2010) we

expect that under tight monetary conditions SMEs in transition economies are more likely to

switch to alternative forms of financing such as trade credit We also hypothesize that SMEs

are more likely to rely on ownersrsquo contributed equity which they tend to accumulate in good

times as part of their risk management strategy to use it as a cushion in the times of financial

distress In summary we expect the difference between the SMEs and large firms in their

reliance on bank finance to diminish during the crisis years and second SMEs to be more

flexible and rely more on other sources of finance such as trade credit and private equity in

the period of financial contractions

11

33 Firm- and industry- level factors

As far as the firm-level and industry-level variables are concerned we expect the

following results first the level of social capital of a firm as proxied by the inverse of the time

spent dealing with government regulations to indicate possible established connections with

public officials can positively affect its access to trade credit Next the industry-level

pressure on a firm from competitors to develop a new product may increase the firmrsquos

chances of obtaining a bank loan as the bank may perceive the firmrsquos operations as more

diversified and less risky (Isachenkova et al 2011) We also expect foreign competition and

the pressure it exerts on a firm innovation capability to play less important role for firm

financing decisions as SMEs are more likely to operate in market niches and they are

unlikely to compete with multinational enterprises In contrast we expect a pressure

originated from customers on a firm to innovate to increase a firmrsquos probability to rely more

on external sources of funding This may be attributed to the fact that a firm does not only

differentiate itself from other firms further with developing a new product but also assures a

demand for this product by responding to the needs of its existing customers The

guaranteed demand for a new product would be one of the most crucial factors taken into

account by bank managers or potential investors in decision-making concerning project

financing Thirdly international product certification may play a similar role with regards to

bank loans increasing the access to external funds Fourth we investigate the effect on the

choice of financing of the firm age with a square term Generally older firms may have

easier access to bank loans as more information is available about them to the lender (Beck

et al 2006 Canton et al 2010) however due to the particulars of the transition period

sometimes older firms may be less economically viable and unable to get a loan therefore

the sign of this coefficient is uncertain here Lastly we also look at the firmrsquos export

orientation which is expected to increase the reliance on bank lending and its ownership

type where we single out foreign and domestic private firms In the case of foreign firms

they are less likely to use private loans and rely instead on retained earnings and intra-

company funds transfers in the case of MNCs

34 Institutional environment

The impact of institutional variables on the financing choices of firms has been of the

utmost interest to economists and policy-makers during the period of transition (see for

example Stijn and Tzioumis 2006 Mitra et al 2008 see also Commander and Svejnar

(2009) for an in-depth and comprehensive analysis of the impact of various business

environment factors on firm performance using BEEPS 2002 - 2005 panel) In our analysis

12

we concentrate on two institutional factors the degree of protection of property rights and the

size of the formal financial sector which have been claimed to be of key importance for firmsrsquo

financing decisions (see Korosteleva and Mickiewicz (2011) for overview of the related

literature) As far as the property rights protection is concerned it is found to play crucial role

for firm growth and access to external finance (Aidis et al 2008 2010 Korosteleva and

Mickiewicz 2011 Estrin Korosteleva and Mickiewicz 2011) In the environment with weak

protection of property rights financial contracts are less likely to be concluded leading to the

underdevelopment of finance and credit rationing with small firms to be disproportionally

affected the most (Acemoglu and Johnson 2005) Beck et al (2004) show that in terms of

access to external finance small firms benefit disproportionally from higher levels of property

rights protection Lack of secure property rights may also discourage SMEs from taking full

advantage of opportunities to invest (Johnson et al 2002) In a survey of private small

manufacturing firms in Poland Russia Ukraine Romania and Slovakia Johnson et al

(2002) find that small firms tend to reinvest less of their earnings when they perceive their

property rights insecure They also find that the effect of the property rights system is of more

paramount importance for entrepreneursrsquo decisions to reinvest their earnings than availability

of formal finance Moreover if property rights are well-protected this lessens the extent of

potential threat of being expropriated by raidersbank lenders in an artificial bankruptcy

procedure which has been quite a significant issue for firms in Russia and other FSU states

(Radygin et al 2005 Sprenger 2002) Based on this we expect that strong property rights

are likely to encourage SMEs to use more debt as well as to use their own funds and

retained profits for investing in investment projects

With regards to the size of the formal finance as measured by the share of private

credit to GDP the relationship between financial depth and financial constraints has been

extensively studied (Beck et al 2006 also see for example Love 2003 who employing a

sample of 36 countries finds that financial development affects firmsrsquo investment by

increasing the availability of external finance) Financial intermediaries facilitate the risk

amelioration in the presence of problems created by information and transaction frictions by

developing expertise in risk assessment and in monitoring (Levine 1997 Barth et al 2006

Barth et al 2008) Developed financial institutions are found to be particularly beneficial for

small firms compared to large ones (Barth et al 2006 Beck et al 2005 2006 2008)

Pissarides et al (2003) show that financial constraints affect SMEs even more than

deficiency of the property rights protection Accordingly the size of the formal financial

system is expected to be positively related to the use of bank finance as a better functioning

financial system should help ease up borrowing constraints

4 Data and Methodology

13

41 Sample

To explore the determinants of the financial structure of small businesses we use the

2002-2009 Business Environment and Enterprise Performance Survey (BEEPS) data6 of

21867 firms covering 26 transition economies of Europe and Central Asia (ECA)7

The sample is primarily comprised of small and medium-sized businesses8 which

account for 893 per cent of the sample The sample is representative in terms of industrial

coverage with the majority of SMEs of the sample operating in manufacturing wholesale

and retailing industries

BEEPS dataset provides rich information on firm characteristics investment

behaviour and firmsrsquo perception of business environment including financial constraints

which are of a primary interest for our investigation of the effect of the recent financial crisis

on firmsrsquo perception of financial constraints Potentially we could use other micro-level data

characterising various domains of business environment captured by firmsrsquo perceptions for

investigating the effects of the institutional settings However using these micro-level

indicators as explanatory variables would make our study plagued with a problem of

endogeneity To avoid this we merge our firm-level data with country-level indicators

characterising various institutional domains The country level data were obtained from the

World Development Indicators (World Bank) and Polity IV databases (for further discussion

see below) Finally the BEEPs dataset contains other useful information which allows us to

shed light of the effect of for example social capital as proxied by the indirect measure of

possible connections with the authorities (see below for the definition of the variable) on firm

financing

42 Variable Definition and Measurement

Explanatory variables

6 This data is a joint project of the European Bank for Reconstruction and Development and World Bank The first survey was launched in 1999 The dataset used in the present study is an unbalanced panel covering the years of 2002 2005 2007-2009 7 The sample includes the following countries Albania Armenia Azerbaijan Belarus Bosnia Bulgaria Croatia Czech Republic Estonia FYROM Georgia Hungary Kazakhstan Kyrgyzstan Latvia Lithuania Moldova Montenegro Poland Romania Russia Serbia Slovakia Slovenia Tajikistan and Ukraine We exclude Uzbekistan as an outlier from our sample We also exclude Turkey as it is not classified as a post-communist country undertaking transition from a planned to a market economy 8 We utilize the EU employment criterion to define small and medium-sized businesses More specifically businesses are defined as micro if they employ 9 and less employees small ndash between 10 and 49 medium ndash between 50 and 249 and large ndash over 250 employees Respectively SMEs are defined as firms employing less than 249 firms

14

To test our main hypothesis of the effect of a firm size on firmsrsquo perception of financial

constraints we introduce a dummy variable denoting small and medium-sized business

coded as 1 if firms are classified as small or medium-sized businesses according to the EU

definition based on the employment criterion For robustness of our results we also use a

continuous variable denoting a size of employment as measured by the natural logarithm of

employment9 The obtained results are consistent with the ones using the SME indicators

To capture the effect of the recent financial crisis we introduce a crisis dummy coded

as 1 if the year of survey is equal to 2008 or 200910

We also introduce a number of firm-level controls which include age of firm11 type of

ownership including private and foreign ownership export orientation and whether a firm

has an internationally certified product all equal to 1 if a business has a respectively listed

characteristic and zero otherwise We also examine the effect of various sources of pressure

on firms to innovate ndash the indicators which are considered to be important for firm investment

decisions Respectively the pressure for innovation may stem from domestic competition

foreign competition and customers To capture the effect of a firmrsquos social capital we

introduce an indicator which indirectly may capture some possible connections of a firm with

authorities It is proxied by time spent by each firm on dealing with government regulations

We assume the less time firms spend dealing with government regulations the more likely

they have some established connections with public officials which allow them to avoid

burdensome regulation procedures

In our study we also introduce a number of country-level variables which characterize

the institutional environment in the countries covered by our sample More specifically we

include an indicator of the financial development as measured by the ratio of domestic credit

to private sector to GDP (one year lag to avoid potential endogeneity) obtained from the

World Bank World Development Indicators (World Bank 2011) This measure has been used

in previous studies (Klapper et al 2006) and it is expected to be of a primary importance for

transition economies where firms tend to rely more on bank finance rather than capital

markets We also introduce a measure of property rights protection (a one year lag) proxied

by the indicator of effective constraints imposed on the executive branch of the government

and obtained from Polity IV project12 This measure of property rights protection is

9 These results are not reported here to save some space However they can be obtained from authors upon request 10 Here it is important to note that although the financial crisis has started in 2007 in the USA it spread to transition economies in 2008-2009 11 Some studies find a non-monotonic relationship between age and firm decision-making In this study we introduce a squared term of age along with a age variable to capture this possible non-linearity 12 Available from httpwwwsystemicpeaceorgpolitypolity4htm

15

considered to be superior to other indicators including the index of property rights reported

by the Heritage Foundation ndashWall Street Journal (for further discussion see Acemoglu and

Johnson 2005 Glaeser et al 2004 Estrin Korosteleva and Mickieiwcz 2011)

In the present study we also introduce macroeconomic controls including cyclical

economic performance as measured by the one year lag of the GDP annual growth rate

and the level of economic development as proxied by a set of GDP pc dummies denoting

the five quintiles of its distribution to address the problem of potential multicollinearity with the

measure of financial development

Finally we include industry and country controls in all our specifications Introducing

country dummies into analysis allows to control for cross-country heterogeneity

For further definition of all variables their descriptive statistics and correlation matrix

see Tables 1-2

43 Dependent variables

To investigate the effect of a firmrsquos size on its perception of financial constraints we

construct a dummy variable coded as 1 capturing a major and very severe obstacle for

access to finance and 0 otherwise

The firm financing choices are defined by the five individual dependent variables

associated with tobit financial choice equations in the seemingly unrelated regression

equations model

One important thing to mention here is the inability to distinguish between

owninternal funds and external private equity considered as one of the limitations of the

2002-2009 BEEPS dataset In the period under investigation BEEPS offers two questions

which aim to capture the use of equity The first one centres around retained earnings and

the second one shows ownersrsquo contributions and private equity or issued new equity

Following some theoretical considerations discussed in sections 2 and 3 in the context of

SMEs we expect the second element of equity to be primarily comprised of existing ownersrsquo

new contributions rather than private equity

Thus the indicator of financial choices represents a set of five individual dependent

variables including retained earnings contributed earnings private borrowing informal

finance trade credit with each of them constructed as a share in total financing of SMErsquos

investment decisions (see Table 1)

44 Methods

16

In this study we employ a number of estimators to obtain robust results More

specifically we use a probit model to investigate the effect of a firm size and the recent

financial crisis on firmsrsquo perception of financial constraints The effect of a firm size in the

situation of crisis is captured by the introduction of the interaction term between firm size as

proxied by the SME indicator and a financial crisis dummy

We further employ the seemingly unrelated regression equations model combined

with the tobit approach for studying firmsrsquo financial structure

Probit model of perception of financial constraints

In the probit model the probability of a firmrsquos perception of financial constraints as

major(j = 1) can be written as follows

( ) ( )int ++

++

infinminus

minus===

ijitj uXjitiitit ijitjuXjy uX

βα βαππ 212-

)()(2 21exp|Pr

Where ity is our measure of financial constraints as perceived by firms and itX is a

set of our explanatory variables discussed in detail in sections 3-4 Here it is important to

note that the interaction term in a probit model cannot be interpreted in a similar way as in

linear models and disregarding this may lead to misleading estimates of the interaction

effect which is of crucial importance for our study (Norton Wang and Ai 2004) Respectively

for robustness of our results here we follow the framework suggested by Norton Wang and

Ai (2004) to account for the model nonlinearity The adjusted marginal effects for the

interaction term are reported in the note to Table 313

Simultaneous Model of Financing Choices

As mentioned above we next model the choice of all five financing choices explicitly

We also hypothesise (following Isachenkova et al 2011) that firm financing choices are likely

to be determined jointly A standard way of modelling jointly determined indicators is a

system of equations - SURE ndash seemingly unrelated regression equations where equations

are linked only by their errors (Zellner 1962) We therefore model the five types of sources of

finance (internal funds private bank borrowing informal finance trade credit and private

13 We also run a probit regression for a split sample of (1) SMEs and (2) large firms to check the robustness of our results (based on the interaction term) while addressing a problem of multicollinearity between a crisis variable and its interaction term with a SME variable The correlation coefficient between a crisis variable and its interaction term with a SME variable is equal to 93 This can be attributed by the problem of a sample being overrepresented by SMEs which constitute 90 of all surveyed firms The results remain robust and can be available from authors upon request

17

equity) using a SURE framework within which we specify a set of five tobit regressions with

correlated residuals

We employ the STATA cmp module which allows to it Seemingly Unrelated Regressions

using the simulated likelihood method such as the Geweke Hajivassiliou and Keane (GHK)

algorithm (for further discussion see Roodman 2008) We utilise a tobit equation to model

each individual financial choice of firms because our dependent financing choices variables

are continuous but their range is constrained (censored) with a substantial number of

observations either equal to zero denoting those who do not use the respective source of

finance or to 100 showing the opposite Other observations are positive and may produce

many different outcomes (Verbeek 2000) Each tobit equation uses a set of identical

explanatory variables that proxy factors which could possibly be associated with firmrsquos

financing choices including industry and country dummies

We also considered the bias caused by potential interdependence between the choice of

whether to invest and firmrsquos financing choices We accounted for the potential selection bias

by introducing into the financial choices SURE Tobit equations (second stage outcome

equations14) the inverse Millrsquos ratio calculated based on modelling the choice to invest in

fixed assets (first stage or selection equation) To identify the first stage of the Heckman

selection model we chose a variable which is correlated with the first stage dependent

variable (investment decision) but not with the second ones (financing choices) We used the

rate of capacity utilization as part of our identification strategy Capacity utilization shows the

percentage of capital stock in use the higher is the rate the more likely firms will increase

investment Batyaeva and Aukutsionek (2001) show that the rate of capacity utilization is

higher in the group of investing firms than in the group of non-investing firms in Russia15 We

calculated the inverse Millrsquos ratio based on the above selection equation16 and included it as

a control in the second stage SURE Tobit equations The inverse Millrsquos ratio has only proved

to be statistically significant in the private bank loan equation pointing to the potential

selection bias arising from the possibility that the factors determining the decision to invest

might differ from those determining the use of bank financing in purchasing fixed assets

14 We also attempted to estimate an investment equation jointly with Tobit financial choices equations within the SURE framework using However given the overall complexity of the model we failed to do this We proceeded further with a two-stage approach by estimating an investment probit equation and calculating the inverse Millrsquos ratio that we add into the outcome financial choices equations at the second stage of the analysis to test for the selection bias 15 We performed an independent sample t-test to check whether the rate of capacity utilization is statistically significantly higher for investing firms compared to non-investing firms for our sample The null hypothesis of no difference was rejected at 1 level of significance 16 To economize on space we do not report the results of the investment probit equation but they are available from authorsrsquo upon request

18

Finally In Table 6 we attempt to condition the determinants of financing constraints

declared by SMEs on the relative percentage increase of trade credit in total funds used for

real investment As mentioned above in Section 2 the timings of measuring the composition

of financing sources precede by a year the timings of measuring the perceptions of financing

constraints That feature of the BEEPSrsquo design allays a likely concern about the endogeneity

of the relative proportion of trade credit and enables causal inference We too report in thre

note to Table 4 the adjusted marginal effects for the interaction term of the SME dummy with

the trade credit variable

In the next section we discuss our empirical results

5 Empirical Results

Table 3 reports the results of the probit model with the marginal effects for firmsrsquo

perception of financial constraints while Tables 4-5 summarize the results of SURE tobits for

a more detailed breakdown of five financing choices More specifically Table 4 reports the

results based on the whole sample to give a comparative perspective on SMErsquos financing

strategy vis-a-vis large businesses whereas Table 5 reports the results based on a

subsample of small and medium-sized firms to shed some light on their financing choices in

the period of crisis

Perception of financial constraints

Table 3 shows that generally small and medium-sized enterprises feel more financially

constrained with the coefficient for SME dummy in relation to the large firms being positive

and significant which is consistent with our discussion in sections 2-3 However the

coefficient of the interaction term with the Crisis dummy turns out to be negative and

significant in relation to the perception of financial constraints as a major obstacle and it

tends to outweigh the effect of a SME dummy when we calculate marginal effects The effect

of the interaction terms with the crisis remains robust after we adjust for non-linearity using

the framework proposed by Norton Wang and Ai (2004)17 Overall these results confirm

that small and medium-sized enterprises are much less financially constrained during the

crisis years with their perceptions close to those of the large firms This result is a polar

opposite to that obtained for the SMEs in the UK (Fraser 2009) which finds that not only do

SMEs generally feel more financially constrained but they report to be even more so during

17 We also check the robustness of our results to the potential problem of multicollinearity between a crisis dummy and its interaction term with SME by splitting a sample and testing the same specification separately for SMEs and large firms We also perform another robustness check by breaking a SME dummy into three subsequent dummies namely micro- small- and medium-sized firms The difference in perception of financial constraints gets almost eliminated in the case of small firms and is largely reduced in the case of micro firms whereas it is less so for medium-sized firms

19

the last crisis We could explain this striking difference by the peculiarities of the SMEs

functioning in new emerging economies The lower reliance of SMEs on external debt in

good times (as shown by results which are discussed below) gives SMEs some flexibility

during the crisis when formal financial markets dry up Jointly with overall flexibility to make

necessary cost cuts and to restructure a business this overall lower reliance on external

funding and the use of alternative sources of financing makes SMEs feel less financially

constrained under the crisis as compared to larger firms

We also find that a more developed financial sector as proxied by domestic private

credit as proportion of GDP helps ease up financial constraints This is in line with the

general literature suggesting that better functioning financial intermediaries facilitate the risk

amelioration in the presence of problems created by market frictions (Levine 1997 Barth et

al 2006 Barth et al 2008)

Unfortunately we fail to find any significant effect of the property rights protection on

firmsrsquo perception of financial constraints that may be explained by the fact that the effect of a

more developed financial sector is likely to outweigh the effect of the property rights

protection

Finally we also find that foreign ownership and international product certificate may

reduce firmsrsquo borrowing constraints while any pressure from domestic or foreign competition

so is pressure from the customers to innovate will increase firmrsquos perception of financial

constraints as major given that firms envisage the need to secure external funding for RampD

or any other innovation-related activities

Financing choices for investment in fixed assets

The results in Table 4 indicate that small enterprises tend to rely more on internal funds

and less on bank loans but they are no different from larger firms in respect of using informal

funds trade credit or private equity which is generally consistent with our discussion in

Sections 2 and 3 The results of Table 5 suggest however that under crisis small and

medium-sized firms tend to switch to other sources of finance such as trade credit and

ownerrsquos contributed equity and to respectively reduce the reliance on retained earnings

perhaps because they decrease due to the negative impact of crisis internal funds With

regards to our discussion of SMEsrsquo risk management we note that the use of private equity

(ownerrsquos contribution) during the crisis years increases which could indicate that the ownerrsquos

funds are used as a cushion in the period of financial distress

An interesting insight regarding the use of trade credit emerges for SMEs in our

sample although in non-crisis years small and medium-sized businesses are not significantly

different from larger firms in terms of reliance on trade credit SMEs tend to finance a

significantly higher proportion of their fixed asset investment by trade credit than large firms

20

in the period of crisis While the latter finding is partly in line with some other studies ndash such

as Klapper and Randall (2010) using BEEPS data it is in stark contrast with similar studies

of the UK private firms (Rehman 2011) for which the use of trade credit is found to have

dried up in crisis This could partly be due to the passed legislation in the UK tightening trade

credit regulation as the result of the abuse of trade credit by large firms in relation to small

firms which forced many SMEs out of the market

With regards to the other firm-level characteristics international certification makes the

firm rely more on private bank loans and informal finance (Table 5) while SMEs with foreign

ownership rely less on private debt but more on retained earnings Both results are

consistent with our hypotheses discussed above Export-oriented small and medium-sized

businesses tend to have greater reliance on trade credit and they use less of internal funds

We find a non-monotonic relationship between age and private equity with both younger and

older firms being more reliant on this source of funding We find some fragmentary support

for private domestic SMEs relying more on informal finance while tending to use less trade

credit and private equity (Table 5)

Interestingly our results (Tables 4-5) suggest that firms which lack some social

connections with governmental officials proxied by the higher amount of time spent dealing

with government regulations are more likely to rely on informal finance trade credit and

private equity In turn businesses which are connected to governmental officials use more

retained profits to fund investment in fixed assets This may be attributed to their connections

serving as a guarantee from expropriation of assets by all sort of rent-seeking individuals

akin private contracting to secure property rights protection This result should be interpreted

jointly with the property rights protection results We expected that better property rights

protection is likely to facilitate firmsrsquo access to bank loan but we failed to confirm this

Perhaps regardless some attempts at a constitutional level to prevent arbitrary government

(which is proxied by our measure of property rights) expropriation culture is still deeply

embedded in the society of post-communist countries and it may manifest in different ways

Welter and Smallbone (2011) argue that entrepreneurs in transition economies have learnt

how to respond to institutional deficiencies in particular weak property rights protection For

example some businesses experiencing high growth choose to invest in unrelated

businesses instead of growing their core businesses for the reason they do not want to

become too noticeable to attract too much attention of the wrong sort In our instance having

some connections with officials seems also to serve as protection against arbitrary

government or individual rent-seeking that makes businesses more keen on re-investing their

retained profits (see Johnson et al (2002) on the discussion of how more secure property

rights can make small firms reinvest more of their earnings)

4

The required funding was also difficult to raise via bank borrowing given the

underdeveloped and inefficient financial system inherited from the planned economy where

the role of finance was passive for finance served as a monetary counterpart of planning

directives Despite the emergence of new private banks the competition in the banking

sector across the region remained low which can partly be explained by the capital

weakness of new banks making the market very segmented The dominance of state-owned

or (partly) privatised commercial banks made the banking environment very concentrated

with these banks expressing preference for large state-owned or privatised enterprises at the

cost of discouraging new entrants (Rostowski 1995 Berglof and Bolton 2002) A number of

newly established banks did not have enough experience in private sector lending

(Pissarides 1998) and in the situation of a great economic uncertainty preferred occupying

some niches to riskier lending to the real sector in particular to SMEs Such niches for

example included foreign currency transactions short-term lending on the inter-bank market

and operations with governmental securities (Korosteleva and Lawson 2010) Other new

banks so-called lsquopocket banksrsquo were mainly established by privatised larger enterprises to

serve the purpose of financing their own activities bringing to the surface the problem of

connected lending Given all these peculiarities of banksrsquo establishment at the start of

transition small de novo firms were severely restricted in their access to the formal credit

market The situation was aggravated further by the credit crunch that was a result of

macroeconomic stabilisation measures taken by transition governments to curb inflation

High nominal interest rates were a far larger problem for new ventures which typically face

an initial period of negative profitability1

The progress in reforming the financial sector was slow This is confirmed by the EBRD

annual transition indicators measuring the progress in reforms They include (1) the banking

reform and interest rate liberalisation and (2) the securities market and non-bank financial

institutions For those two the average scores for the region reached only 24 and 21

respectively on the scale from 1 (little progress) to 43 (developed market economies

standards) the decade after the transition began In 2009 only the Central and Eastern

European countries (CEECs) which joined the EU scored as high as 4 in both areas of

financial institutional reforms with Latvia Lithuania Slovakia Slovenia Bulgaria and

Romania still being one score down in the area of securities markets The latter three

countries also scored lower than their CEE counterparts in the area of banking sector reform

Some CIS countries such as Belarus Turkmenistan and Uzbekistan viewed as the laggards

in transition still have rankings as low as 1 (Turkmenistan) and 2 (Azerbaijan

1 Pissarides (1998) argues that SMEs often reinforce banksrsquo perceptions of them being unreliable borrowers given frequent under-reporting of profits due to tax avoidance purposes or failure to register ownership of assets prompting lenders to penalise SMEs by charging them higher premium

5

BelarusKyrgyzstan Tajikistan and Uzbekistan) in both areas of the financial institutional

reforms Overall after the years of the financial sector reform the majority of transition

economies still have rather shallow domestic credit systems (Figure 1) and relatively

underdeveloped capital markets with market capitalisation ratio varying from as low as 16

per cent of GDP in Kyrgyzstan and Armenia2 to as high as 40-50 per cent in Croatia amp

Kazakhstan respectively in 2009 with Montenegro and Russia standing out compared with

the rest of the region3

Figures 1 amp 2 to be inserted here

A number of empirical studies further confirm that financial constraints in transition

economies constitute one of the main obstacles for start-up entry and growth (Pissarides

1998 1999 2001 Pissarides et al 2003 Klapper et al 2002) Pissarides (2001) concludes

that lack of access to finance is more binding for SMEs than larger businesses with the

severity of this constraint being stronger in South-East Europe compared to other transition

economies including the Commonwealth of Independent States (CIS) In their study of SME

growth in Russia and Bulgaria Pissarides et al (2003) find that financial constraints hamper

SME growth and that SMEs resort to the use of internal funds to overcome constraints on

external finance This is similar to Johnsonrsquos et al (2002) findings suggesting that internal

finance can substitute for external finance (see also Lizal and Svejnar (2002) for similar

conclusions) Pissarides et al (2003) also show that financial constraints affect SMEs more

than barriers related to property rights issues Drawing on the data on 15 Eastern European

countries Klapper et al (2002) show that financial constraints affect SMEs longer-term ability

to grow Finally Gorodnichenko and Schnitzer (2010) show that financial constraints restrain

the ability of domestically-owned firms to innovate and export thus inhibiting productivity

growth They also argue that this negative effect is magnified due to financial constraints

forcing export and innovation activities to become substitutes whereas they are commonly

found to be complements

We complement these studies with the most recent empirical evidence on the

determinants of SMEsrsquo perception of financial constrains in transition economies which

comes from the 2002-09 BEEPS dataset The BEEPS self-reported measure of financing

constraints unites in one termed lsquoaccess to financersquo metric both quantity and price

constraints In the surveys firms were directly asked to indicate the extent to which access to

2 In fact it goes as low as 02 per cent of GDP in Uzbekistan in 2005 following the World Development Indicators data with no data reported for subsequent years 3 Montenegro and Russia emerge as outliers given their far higher ratios of market capitalisation These are 104 and 70 per cent respectively and they are far above of some West European countriesrsquo ratios including Germany and comparable to the ones in China and USA

6

finance was an obstacle to their operations and the averages for the individual countries in

the dataset are shown in Figure 3 With exception of Bosnia and Uzbekistan4 SMEs in all

transition economies are more financially constrained than larger firms although as our

empirical results show (see Section 5) the difference in perception of financial constraints

has been largely eliminated between smaller and larger firms during the recent global

financial crisis

Figure 3 to be inserted here

It has previously been argued that a low reliance on outside financing scarce use of

equity finance5 and low level of inter-firm trade financing is a common feature of small firms

across the transition region of Europe and Central Asia (Klapper et al 2002 Pissarides

1998 2001) Furthermore Klapperrsquos et al (2002) find almost no use of long-term debt

attributing this to the underdevelopment of the banking sector weak collateral law and poor

credit information registries Their evidence also shows virtually zero reliance of SMEs

across the 15 Eastern European countries on trade credit with the exception of Hungary and

to a lesser extent of the Czech Republic Poland and Romania They explain this by

insufficiency of partner firmsrsquo internal funds or their inability to access external borrowings to

become able to finance extension of trade credit Low reliance on trade credit may be also

attributed to low foreign presence in some countries of the region as multinationals could

extend trade credit to local firms including SMEs (Klapper et al2002)

Figure 4 shows the relative importance of financing sources used for purchase of fixed

assets by SMEs in the transition economies The data underlying this figure are the relative

percentages of the financing sources firms used in the year preceding a BEEPS survey year

in the BEEPS 2002-2009 surveys The surveys group financing sources into the following six

types internal funds or retained earnings ownersrsquo contribution or issued new equity shares

[funds] borrowed from private banks [funds] borrowed from state-owned banks purchases

on credit from suppliers and advances from customers and other (moneylenders friends

relatives non-banking financial institutions) Figure 4 suggests that SMEs in the transition

economies tend to largely rely on their internal funds or retained profits in funding their

investment Only about 23 per cent of small and medium-sized firms rely on borrowing from

private banks Trade credit and equity finance occupy similar shares in funding SMErsquos

investment decisions and account for the mere 9 per cent of total purchase of fixed assets

4 In Bosnia amp Uzbekistan larger firms are marginally more constrained than smaller ones (at 10 percent level of significance) 5 Small firms may also decide to limit their issuance of outside equity to avoid reduction in control of their firms (Scherr et al1990 and Hamilton and Fox 1998 cited in Klapper et al 2002)

7

According to Cull (2007) trade credit can be seen as substitute for loans for private firmsrsquo

trading partners that are shut out of financial credit market Other sources include borrowing

from informal money lenders and family and these emerge as the third important source of

funding SMEsrsquo investment after internal funds and bank credit We expect the informal

finance to be mostly comprised of equity provided by family and friends as funding obtained

from informal private money lenders was overly expensive with the premium standing at least

20 percentage points above that charged by local intermediaries (Pissarides 1998)

Figure 4 to be inserted here

In conclusion we note that the number of studies of the financing decisions of small

and medium-sized enterprises in emerging markets and in particular in the former centrally

planned economies or previously heavily regulated economies such as India has been rather

limited (see eg Nivorozhkin 2005 Delcoure 2007 Crnigoj 2007 Chakraborty 2008

Girma et al 2008 Li et al 2009 Correa et al 2010 Love and Zaidi 2010) We contribute to

this literature by analysing for SMEs in these countries the determinants of the following five

financing options retained earnings private loan (loan finance from private banks) trade

credit private equity (ownersrsquo equity) and informal finance In this study the phrase lsquoinformal

financersquo is an umbrella term that helps condense in one category funds from moneylenders

friends relatives non-banking financial institutions Our results allow us to shed more light

on whether and how the theories of financing choices apply to transition countries in the

credit crunch environment

The following section discusses theories pertaining to small firm financing and how this

may be affected by a financial crisis

3 Small Firm Financing and the Effect of Crisis Theoretical Considerations and

Hypotheses

31 Theoretical arguments

When analysing financing choices of SMEs we first turn to the two cornerstone

theories of explaining leverage the trade-off theory and the pecking order hypothesis (POH)

While the former states that firms may prefer debt to equity in the presence of corporate tax

subject to the costs of potential financial distress stemming from borrowing large amounts

(Modigliani and Miller 1958) the latter suggests that the firms first finance their investment

out of retained earnings as this is the cheapest and the most readily available alternative

then out of debt and lastly via issuing equity which is seen as the most expensive option to

8

the firm (Arnold 2008) More recent literature on firm financing started to look closer at and

emphasize the importance of other sources such as trade credit especially for the small and

medium firms using mostly the data on developed economies For instance Berger amp Udell

(1998) stress the importance of trade credit to the short-term financing of small firms Bevan

and Danbolt (2002) estimate that trade credit account for 62 per cent of total liabilities of UK

firms

The role of trade credit has been seen by some researchers as a substitute of bank

lending for liquidity-constrained firms (Cull 2007) such as SMEs One of the benefits of trade

credit compared to the bank lending is that it allows to partly get around the information

asymmetry problem between the lender and the borrowing SME as business partners would

have more information about the ability of the borrower to repay and about such reputation of

the borrower in the industry Meltzer (1960) Nielsen (2002) and Petersen and Rajan (1997)

argue that trade credit may also provide a means of alternative financing under the tight

monetary conditions such as credit crunches when financial institutions are less able or

willing to provide loans to SMEs In support of this hypothesis Atanasova and Wilson (2003

2004) and Mateut et al (2006) find that under tight monetary conditions firms tend to

substitute bank loans with trade credit However the findings in Bernanke and Gertler (1995)

and Gertler and Gilchrist (1993) do not agree with this hypothesis In line with these authors

Taketa and Udell (2007) using a sample of Japanese SMEs after the crisis years find that

bank lending and trade credit are complements rather than substitutes Love and Zaidi

(2010) report that the use of trade credit by East Asian firms has declined after the 1998

financial crisis together with the use of bank loans Finally interesting enough there is

some empirical evidence which suggests that in the context of transition economies there

may be a higher reliance of SMEs on trade credit in the period of crisis More specifically

focusing on the panel of 1686 firms in Bulgaria Hungary Latvia Lithuania Romania and

Turkey in 2007 and 2009 Klapper and Randall (2010) find that during periods of contractions

in bank credit buyers might depend more on trade credit (although primarily to be used for

short-term financing) that may be particularly true for small firms This provides some support

for the hypothesis that the two sources of finance namely bank loans and trade credit in the

context of transition and emerging economies can be seen as substitutes in period of crisis

Another source of firm financing that has recently received increased attention is

private equity Private equity consists of investments by private individual investors or firms

(business angels investments funds) as well as business ownersrsquo contributions to their

equity The lsquobusiness angelsrsquo type of private equity is currently on the rise in the developed

countries as well as emerging markets such as India Brazil China Malaysia However

ownersrsquo contribution is a far more widespread type of private equity in countries under

consideration Generally SMEs are prone to various types of business and financial risks

9

and it would be very important for them to try and hedge against these risks Zou and Adams

(2008) look at the effect of property insurance on the public firmsrsquo borrowing capacity in

China while Matthews and Scott (1995) in the US and Herbane (2011) in the UK investigate

the types of risk management used by the SMEs The findings point to a rather limited use by

the small and medium-sized enterprises of the risk management assessment and hedging

techniques

In the emerging markets of the post-Soviet bloc the use of risk management techniques

such as hedging with financial derivatives is virtually non-existent However an informal risk

management practice of accumulating cash out of profits and also of using informal lending

from family and friends to serve as a cushion in the times of financial distress as protection

against possible bankruptcy and as an instrument of insurance against risks has been one

way of accounting for the risky nature of SMEs in these countries Secondly many SMEs

sometimes use bankruptcy when they find themselves in the situation of financial distress

and then open a new firm without losing much of their personal assets (Radygin et al 2005)

These SMEs are oftentimes are registered as belonging to a relative or the SMEs could be

registered as founded by an artificially created third party with no links to the actual ownerrsquos

personal assets Recently banks in the new emerging economies such as Russia started a

practice of compulsory purchase of loan insurance if the SME is to take a loan from the bank

This serves as a risk insurance mechanism to a certain extent at the same time however

increasing the cost of bank financing However more recently this practice has attracted the

attention of the Federal Antimonopoly Service that ruled that there is evidence of collusion

between banks and insurance companies Overall we could conclude that the use of risk

management practices is very narrow and of a rather informal nature

The next sub-section explores in greater detail the institutional context of financing in the

situation of economic crisis

Empirical studies on small firm financing in the years of crisis are primarily motivated by

the informational asymmetries theories One of the most important contributions in the study

of the role of SMEs during business cycle has been the real business cycle (RBC) theory

(Bernanke and Gertler 1995 Bernanke Gertler amp Gilchrist 1998) The argument put forward

by the RBC theory is that SMEs face tighter liquidity constraints in terms of external financing

due to higher informational asymmetries associated with their activities the low value of

their assets to serve as collateral the high cost of monitoring small businesses given a small

scale of their investment projects and subsequently the unwillingness of banks to lend to

SMEs

During economic slowdowns when small businesses are even more in need of external

finance bank lending to them diminishes even further which tends to propagate the crisis if

the SMEs then go out of business (see for example Tornell and Westermann 2005) At the

10

same time as larger firms use more finance and tend to rely more on external funding they

may be hit harder by financial contraction in the situation of global crises when international

financial markets dry up so preventing larger firms from drawing upon them when required

They are also less flexible and it is more costly for them to restructure and downsize when

they are hit with external shocks Furthermore while SMEs tend to be more flexible in relying

on other sources of finance including trade credit contributed equity and informal finance

the financial structure of larger firms generally tends to be less diversified with a preference

often given to retained profits and bank finance following the pecking order theory Taken

together we may argue that both supply and demand for finance is more affected for larger

firms in the situation of external shocks

Based on the discussion presented in Sections 2 and 31 we further discuss three main

groups of factors which are likely to affect firmsrsquo perception of financial constraints and their

financing choice strategy These are as follows (1) firm size in general and in the period of

crisis (2) other firm- and industry-specific characteristics including foreign ownership export

orientation firmsrsquo social capital and the degree of competition and its pressure on the firm to

develop a new product and (3) country-level institutional parameters including the degree of

protection of property rights and the development of the financial sector

32 Size of the enterprise and the effect of crisis

With regards to the effect of firm size based on the general discussion in the literature

(see sections 2-31) we expect SMEs to be more financially constrained in their access to

external lending and respectively more reliant on internal funds This is due to insufficient

information that the bank can obtain about a particular SME as well as due to a potentially

lower size of collateral However this lower reliance of SMEs on external debt can potentially

be a source of flexibility during the crisis when formal financial markets dry up and when

even large well-established firms have difficulty obtaining bank credit Furthermore following

Atanasova and Wilson (2003 2004) Mateut et al (2006) and Klapper and Randall (2010) we

expect that under tight monetary conditions SMEs in transition economies are more likely to

switch to alternative forms of financing such as trade credit We also hypothesize that SMEs

are more likely to rely on ownersrsquo contributed equity which they tend to accumulate in good

times as part of their risk management strategy to use it as a cushion in the times of financial

distress In summary we expect the difference between the SMEs and large firms in their

reliance on bank finance to diminish during the crisis years and second SMEs to be more

flexible and rely more on other sources of finance such as trade credit and private equity in

the period of financial contractions

11

33 Firm- and industry- level factors

As far as the firm-level and industry-level variables are concerned we expect the

following results first the level of social capital of a firm as proxied by the inverse of the time

spent dealing with government regulations to indicate possible established connections with

public officials can positively affect its access to trade credit Next the industry-level

pressure on a firm from competitors to develop a new product may increase the firmrsquos

chances of obtaining a bank loan as the bank may perceive the firmrsquos operations as more

diversified and less risky (Isachenkova et al 2011) We also expect foreign competition and

the pressure it exerts on a firm innovation capability to play less important role for firm

financing decisions as SMEs are more likely to operate in market niches and they are

unlikely to compete with multinational enterprises In contrast we expect a pressure

originated from customers on a firm to innovate to increase a firmrsquos probability to rely more

on external sources of funding This may be attributed to the fact that a firm does not only

differentiate itself from other firms further with developing a new product but also assures a

demand for this product by responding to the needs of its existing customers The

guaranteed demand for a new product would be one of the most crucial factors taken into

account by bank managers or potential investors in decision-making concerning project

financing Thirdly international product certification may play a similar role with regards to

bank loans increasing the access to external funds Fourth we investigate the effect on the

choice of financing of the firm age with a square term Generally older firms may have

easier access to bank loans as more information is available about them to the lender (Beck

et al 2006 Canton et al 2010) however due to the particulars of the transition period

sometimes older firms may be less economically viable and unable to get a loan therefore

the sign of this coefficient is uncertain here Lastly we also look at the firmrsquos export

orientation which is expected to increase the reliance on bank lending and its ownership

type where we single out foreign and domestic private firms In the case of foreign firms

they are less likely to use private loans and rely instead on retained earnings and intra-

company funds transfers in the case of MNCs

34 Institutional environment

The impact of institutional variables on the financing choices of firms has been of the

utmost interest to economists and policy-makers during the period of transition (see for

example Stijn and Tzioumis 2006 Mitra et al 2008 see also Commander and Svejnar

(2009) for an in-depth and comprehensive analysis of the impact of various business

environment factors on firm performance using BEEPS 2002 - 2005 panel) In our analysis

12

we concentrate on two institutional factors the degree of protection of property rights and the

size of the formal financial sector which have been claimed to be of key importance for firmsrsquo

financing decisions (see Korosteleva and Mickiewicz (2011) for overview of the related

literature) As far as the property rights protection is concerned it is found to play crucial role

for firm growth and access to external finance (Aidis et al 2008 2010 Korosteleva and

Mickiewicz 2011 Estrin Korosteleva and Mickiewicz 2011) In the environment with weak

protection of property rights financial contracts are less likely to be concluded leading to the

underdevelopment of finance and credit rationing with small firms to be disproportionally

affected the most (Acemoglu and Johnson 2005) Beck et al (2004) show that in terms of

access to external finance small firms benefit disproportionally from higher levels of property

rights protection Lack of secure property rights may also discourage SMEs from taking full

advantage of opportunities to invest (Johnson et al 2002) In a survey of private small

manufacturing firms in Poland Russia Ukraine Romania and Slovakia Johnson et al

(2002) find that small firms tend to reinvest less of their earnings when they perceive their

property rights insecure They also find that the effect of the property rights system is of more

paramount importance for entrepreneursrsquo decisions to reinvest their earnings than availability

of formal finance Moreover if property rights are well-protected this lessens the extent of

potential threat of being expropriated by raidersbank lenders in an artificial bankruptcy

procedure which has been quite a significant issue for firms in Russia and other FSU states

(Radygin et al 2005 Sprenger 2002) Based on this we expect that strong property rights

are likely to encourage SMEs to use more debt as well as to use their own funds and

retained profits for investing in investment projects

With regards to the size of the formal finance as measured by the share of private

credit to GDP the relationship between financial depth and financial constraints has been

extensively studied (Beck et al 2006 also see for example Love 2003 who employing a

sample of 36 countries finds that financial development affects firmsrsquo investment by

increasing the availability of external finance) Financial intermediaries facilitate the risk

amelioration in the presence of problems created by information and transaction frictions by

developing expertise in risk assessment and in monitoring (Levine 1997 Barth et al 2006

Barth et al 2008) Developed financial institutions are found to be particularly beneficial for

small firms compared to large ones (Barth et al 2006 Beck et al 2005 2006 2008)

Pissarides et al (2003) show that financial constraints affect SMEs even more than

deficiency of the property rights protection Accordingly the size of the formal financial

system is expected to be positively related to the use of bank finance as a better functioning

financial system should help ease up borrowing constraints

4 Data and Methodology

13

41 Sample

To explore the determinants of the financial structure of small businesses we use the

2002-2009 Business Environment and Enterprise Performance Survey (BEEPS) data6 of

21867 firms covering 26 transition economies of Europe and Central Asia (ECA)7

The sample is primarily comprised of small and medium-sized businesses8 which

account for 893 per cent of the sample The sample is representative in terms of industrial

coverage with the majority of SMEs of the sample operating in manufacturing wholesale

and retailing industries

BEEPS dataset provides rich information on firm characteristics investment

behaviour and firmsrsquo perception of business environment including financial constraints

which are of a primary interest for our investigation of the effect of the recent financial crisis

on firmsrsquo perception of financial constraints Potentially we could use other micro-level data

characterising various domains of business environment captured by firmsrsquo perceptions for

investigating the effects of the institutional settings However using these micro-level

indicators as explanatory variables would make our study plagued with a problem of

endogeneity To avoid this we merge our firm-level data with country-level indicators

characterising various institutional domains The country level data were obtained from the

World Development Indicators (World Bank) and Polity IV databases (for further discussion

see below) Finally the BEEPs dataset contains other useful information which allows us to

shed light of the effect of for example social capital as proxied by the indirect measure of

possible connections with the authorities (see below for the definition of the variable) on firm

financing

42 Variable Definition and Measurement

Explanatory variables

6 This data is a joint project of the European Bank for Reconstruction and Development and World Bank The first survey was launched in 1999 The dataset used in the present study is an unbalanced panel covering the years of 2002 2005 2007-2009 7 The sample includes the following countries Albania Armenia Azerbaijan Belarus Bosnia Bulgaria Croatia Czech Republic Estonia FYROM Georgia Hungary Kazakhstan Kyrgyzstan Latvia Lithuania Moldova Montenegro Poland Romania Russia Serbia Slovakia Slovenia Tajikistan and Ukraine We exclude Uzbekistan as an outlier from our sample We also exclude Turkey as it is not classified as a post-communist country undertaking transition from a planned to a market economy 8 We utilize the EU employment criterion to define small and medium-sized businesses More specifically businesses are defined as micro if they employ 9 and less employees small ndash between 10 and 49 medium ndash between 50 and 249 and large ndash over 250 employees Respectively SMEs are defined as firms employing less than 249 firms

14

To test our main hypothesis of the effect of a firm size on firmsrsquo perception of financial

constraints we introduce a dummy variable denoting small and medium-sized business

coded as 1 if firms are classified as small or medium-sized businesses according to the EU

definition based on the employment criterion For robustness of our results we also use a

continuous variable denoting a size of employment as measured by the natural logarithm of

employment9 The obtained results are consistent with the ones using the SME indicators

To capture the effect of the recent financial crisis we introduce a crisis dummy coded

as 1 if the year of survey is equal to 2008 or 200910

We also introduce a number of firm-level controls which include age of firm11 type of

ownership including private and foreign ownership export orientation and whether a firm

has an internationally certified product all equal to 1 if a business has a respectively listed

characteristic and zero otherwise We also examine the effect of various sources of pressure

on firms to innovate ndash the indicators which are considered to be important for firm investment

decisions Respectively the pressure for innovation may stem from domestic competition

foreign competition and customers To capture the effect of a firmrsquos social capital we

introduce an indicator which indirectly may capture some possible connections of a firm with

authorities It is proxied by time spent by each firm on dealing with government regulations

We assume the less time firms spend dealing with government regulations the more likely

they have some established connections with public officials which allow them to avoid

burdensome regulation procedures

In our study we also introduce a number of country-level variables which characterize

the institutional environment in the countries covered by our sample More specifically we

include an indicator of the financial development as measured by the ratio of domestic credit

to private sector to GDP (one year lag to avoid potential endogeneity) obtained from the

World Bank World Development Indicators (World Bank 2011) This measure has been used

in previous studies (Klapper et al 2006) and it is expected to be of a primary importance for

transition economies where firms tend to rely more on bank finance rather than capital

markets We also introduce a measure of property rights protection (a one year lag) proxied

by the indicator of effective constraints imposed on the executive branch of the government

and obtained from Polity IV project12 This measure of property rights protection is

9 These results are not reported here to save some space However they can be obtained from authors upon request 10 Here it is important to note that although the financial crisis has started in 2007 in the USA it spread to transition economies in 2008-2009 11 Some studies find a non-monotonic relationship between age and firm decision-making In this study we introduce a squared term of age along with a age variable to capture this possible non-linearity 12 Available from httpwwwsystemicpeaceorgpolitypolity4htm

15

considered to be superior to other indicators including the index of property rights reported

by the Heritage Foundation ndashWall Street Journal (for further discussion see Acemoglu and

Johnson 2005 Glaeser et al 2004 Estrin Korosteleva and Mickieiwcz 2011)

In the present study we also introduce macroeconomic controls including cyclical

economic performance as measured by the one year lag of the GDP annual growth rate

and the level of economic development as proxied by a set of GDP pc dummies denoting

the five quintiles of its distribution to address the problem of potential multicollinearity with the

measure of financial development

Finally we include industry and country controls in all our specifications Introducing

country dummies into analysis allows to control for cross-country heterogeneity

For further definition of all variables their descriptive statistics and correlation matrix

see Tables 1-2

43 Dependent variables

To investigate the effect of a firmrsquos size on its perception of financial constraints we

construct a dummy variable coded as 1 capturing a major and very severe obstacle for

access to finance and 0 otherwise

The firm financing choices are defined by the five individual dependent variables

associated with tobit financial choice equations in the seemingly unrelated regression

equations model

One important thing to mention here is the inability to distinguish between

owninternal funds and external private equity considered as one of the limitations of the

2002-2009 BEEPS dataset In the period under investigation BEEPS offers two questions

which aim to capture the use of equity The first one centres around retained earnings and

the second one shows ownersrsquo contributions and private equity or issued new equity

Following some theoretical considerations discussed in sections 2 and 3 in the context of

SMEs we expect the second element of equity to be primarily comprised of existing ownersrsquo

new contributions rather than private equity

Thus the indicator of financial choices represents a set of five individual dependent

variables including retained earnings contributed earnings private borrowing informal

finance trade credit with each of them constructed as a share in total financing of SMErsquos

investment decisions (see Table 1)

44 Methods

16

In this study we employ a number of estimators to obtain robust results More

specifically we use a probit model to investigate the effect of a firm size and the recent

financial crisis on firmsrsquo perception of financial constraints The effect of a firm size in the

situation of crisis is captured by the introduction of the interaction term between firm size as

proxied by the SME indicator and a financial crisis dummy

We further employ the seemingly unrelated regression equations model combined

with the tobit approach for studying firmsrsquo financial structure

Probit model of perception of financial constraints

In the probit model the probability of a firmrsquos perception of financial constraints as

major(j = 1) can be written as follows

( ) ( )int ++

++

infinminus

minus===

ijitj uXjitiitit ijitjuXjy uX

βα βαππ 212-

)()(2 21exp|Pr

Where ity is our measure of financial constraints as perceived by firms and itX is a

set of our explanatory variables discussed in detail in sections 3-4 Here it is important to

note that the interaction term in a probit model cannot be interpreted in a similar way as in

linear models and disregarding this may lead to misleading estimates of the interaction

effect which is of crucial importance for our study (Norton Wang and Ai 2004) Respectively

for robustness of our results here we follow the framework suggested by Norton Wang and

Ai (2004) to account for the model nonlinearity The adjusted marginal effects for the

interaction term are reported in the note to Table 313

Simultaneous Model of Financing Choices

As mentioned above we next model the choice of all five financing choices explicitly

We also hypothesise (following Isachenkova et al 2011) that firm financing choices are likely

to be determined jointly A standard way of modelling jointly determined indicators is a

system of equations - SURE ndash seemingly unrelated regression equations where equations

are linked only by their errors (Zellner 1962) We therefore model the five types of sources of

finance (internal funds private bank borrowing informal finance trade credit and private

13 We also run a probit regression for a split sample of (1) SMEs and (2) large firms to check the robustness of our results (based on the interaction term) while addressing a problem of multicollinearity between a crisis variable and its interaction term with a SME variable The correlation coefficient between a crisis variable and its interaction term with a SME variable is equal to 93 This can be attributed by the problem of a sample being overrepresented by SMEs which constitute 90 of all surveyed firms The results remain robust and can be available from authors upon request

17

equity) using a SURE framework within which we specify a set of five tobit regressions with

correlated residuals

We employ the STATA cmp module which allows to it Seemingly Unrelated Regressions

using the simulated likelihood method such as the Geweke Hajivassiliou and Keane (GHK)

algorithm (for further discussion see Roodman 2008) We utilise a tobit equation to model

each individual financial choice of firms because our dependent financing choices variables

are continuous but their range is constrained (censored) with a substantial number of

observations either equal to zero denoting those who do not use the respective source of

finance or to 100 showing the opposite Other observations are positive and may produce

many different outcomes (Verbeek 2000) Each tobit equation uses a set of identical

explanatory variables that proxy factors which could possibly be associated with firmrsquos

financing choices including industry and country dummies

We also considered the bias caused by potential interdependence between the choice of

whether to invest and firmrsquos financing choices We accounted for the potential selection bias

by introducing into the financial choices SURE Tobit equations (second stage outcome

equations14) the inverse Millrsquos ratio calculated based on modelling the choice to invest in

fixed assets (first stage or selection equation) To identify the first stage of the Heckman

selection model we chose a variable which is correlated with the first stage dependent

variable (investment decision) but not with the second ones (financing choices) We used the

rate of capacity utilization as part of our identification strategy Capacity utilization shows the

percentage of capital stock in use the higher is the rate the more likely firms will increase

investment Batyaeva and Aukutsionek (2001) show that the rate of capacity utilization is

higher in the group of investing firms than in the group of non-investing firms in Russia15 We

calculated the inverse Millrsquos ratio based on the above selection equation16 and included it as

a control in the second stage SURE Tobit equations The inverse Millrsquos ratio has only proved

to be statistically significant in the private bank loan equation pointing to the potential

selection bias arising from the possibility that the factors determining the decision to invest

might differ from those determining the use of bank financing in purchasing fixed assets

14 We also attempted to estimate an investment equation jointly with Tobit financial choices equations within the SURE framework using However given the overall complexity of the model we failed to do this We proceeded further with a two-stage approach by estimating an investment probit equation and calculating the inverse Millrsquos ratio that we add into the outcome financial choices equations at the second stage of the analysis to test for the selection bias 15 We performed an independent sample t-test to check whether the rate of capacity utilization is statistically significantly higher for investing firms compared to non-investing firms for our sample The null hypothesis of no difference was rejected at 1 level of significance 16 To economize on space we do not report the results of the investment probit equation but they are available from authorsrsquo upon request

18

Finally In Table 6 we attempt to condition the determinants of financing constraints

declared by SMEs on the relative percentage increase of trade credit in total funds used for

real investment As mentioned above in Section 2 the timings of measuring the composition

of financing sources precede by a year the timings of measuring the perceptions of financing

constraints That feature of the BEEPSrsquo design allays a likely concern about the endogeneity

of the relative proportion of trade credit and enables causal inference We too report in thre

note to Table 4 the adjusted marginal effects for the interaction term of the SME dummy with

the trade credit variable

In the next section we discuss our empirical results

5 Empirical Results

Table 3 reports the results of the probit model with the marginal effects for firmsrsquo

perception of financial constraints while Tables 4-5 summarize the results of SURE tobits for

a more detailed breakdown of five financing choices More specifically Table 4 reports the

results based on the whole sample to give a comparative perspective on SMErsquos financing

strategy vis-a-vis large businesses whereas Table 5 reports the results based on a

subsample of small and medium-sized firms to shed some light on their financing choices in

the period of crisis

Perception of financial constraints

Table 3 shows that generally small and medium-sized enterprises feel more financially

constrained with the coefficient for SME dummy in relation to the large firms being positive

and significant which is consistent with our discussion in sections 2-3 However the

coefficient of the interaction term with the Crisis dummy turns out to be negative and

significant in relation to the perception of financial constraints as a major obstacle and it

tends to outweigh the effect of a SME dummy when we calculate marginal effects The effect

of the interaction terms with the crisis remains robust after we adjust for non-linearity using

the framework proposed by Norton Wang and Ai (2004)17 Overall these results confirm

that small and medium-sized enterprises are much less financially constrained during the

crisis years with their perceptions close to those of the large firms This result is a polar

opposite to that obtained for the SMEs in the UK (Fraser 2009) which finds that not only do

SMEs generally feel more financially constrained but they report to be even more so during

17 We also check the robustness of our results to the potential problem of multicollinearity between a crisis dummy and its interaction term with SME by splitting a sample and testing the same specification separately for SMEs and large firms We also perform another robustness check by breaking a SME dummy into three subsequent dummies namely micro- small- and medium-sized firms The difference in perception of financial constraints gets almost eliminated in the case of small firms and is largely reduced in the case of micro firms whereas it is less so for medium-sized firms

19

the last crisis We could explain this striking difference by the peculiarities of the SMEs

functioning in new emerging economies The lower reliance of SMEs on external debt in

good times (as shown by results which are discussed below) gives SMEs some flexibility

during the crisis when formal financial markets dry up Jointly with overall flexibility to make

necessary cost cuts and to restructure a business this overall lower reliance on external

funding and the use of alternative sources of financing makes SMEs feel less financially

constrained under the crisis as compared to larger firms

We also find that a more developed financial sector as proxied by domestic private

credit as proportion of GDP helps ease up financial constraints This is in line with the

general literature suggesting that better functioning financial intermediaries facilitate the risk

amelioration in the presence of problems created by market frictions (Levine 1997 Barth et

al 2006 Barth et al 2008)

Unfortunately we fail to find any significant effect of the property rights protection on

firmsrsquo perception of financial constraints that may be explained by the fact that the effect of a

more developed financial sector is likely to outweigh the effect of the property rights

protection

Finally we also find that foreign ownership and international product certificate may

reduce firmsrsquo borrowing constraints while any pressure from domestic or foreign competition

so is pressure from the customers to innovate will increase firmrsquos perception of financial

constraints as major given that firms envisage the need to secure external funding for RampD

or any other innovation-related activities

Financing choices for investment in fixed assets

The results in Table 4 indicate that small enterprises tend to rely more on internal funds

and less on bank loans but they are no different from larger firms in respect of using informal

funds trade credit or private equity which is generally consistent with our discussion in

Sections 2 and 3 The results of Table 5 suggest however that under crisis small and

medium-sized firms tend to switch to other sources of finance such as trade credit and

ownerrsquos contributed equity and to respectively reduce the reliance on retained earnings

perhaps because they decrease due to the negative impact of crisis internal funds With

regards to our discussion of SMEsrsquo risk management we note that the use of private equity

(ownerrsquos contribution) during the crisis years increases which could indicate that the ownerrsquos

funds are used as a cushion in the period of financial distress

An interesting insight regarding the use of trade credit emerges for SMEs in our

sample although in non-crisis years small and medium-sized businesses are not significantly

different from larger firms in terms of reliance on trade credit SMEs tend to finance a

significantly higher proportion of their fixed asset investment by trade credit than large firms

20

in the period of crisis While the latter finding is partly in line with some other studies ndash such

as Klapper and Randall (2010) using BEEPS data it is in stark contrast with similar studies

of the UK private firms (Rehman 2011) for which the use of trade credit is found to have

dried up in crisis This could partly be due to the passed legislation in the UK tightening trade

credit regulation as the result of the abuse of trade credit by large firms in relation to small

firms which forced many SMEs out of the market

With regards to the other firm-level characteristics international certification makes the

firm rely more on private bank loans and informal finance (Table 5) while SMEs with foreign

ownership rely less on private debt but more on retained earnings Both results are

consistent with our hypotheses discussed above Export-oriented small and medium-sized

businesses tend to have greater reliance on trade credit and they use less of internal funds

We find a non-monotonic relationship between age and private equity with both younger and

older firms being more reliant on this source of funding We find some fragmentary support

for private domestic SMEs relying more on informal finance while tending to use less trade

credit and private equity (Table 5)

Interestingly our results (Tables 4-5) suggest that firms which lack some social

connections with governmental officials proxied by the higher amount of time spent dealing

with government regulations are more likely to rely on informal finance trade credit and

private equity In turn businesses which are connected to governmental officials use more

retained profits to fund investment in fixed assets This may be attributed to their connections

serving as a guarantee from expropriation of assets by all sort of rent-seeking individuals

akin private contracting to secure property rights protection This result should be interpreted

jointly with the property rights protection results We expected that better property rights

protection is likely to facilitate firmsrsquo access to bank loan but we failed to confirm this

Perhaps regardless some attempts at a constitutional level to prevent arbitrary government

(which is proxied by our measure of property rights) expropriation culture is still deeply

embedded in the society of post-communist countries and it may manifest in different ways

Welter and Smallbone (2011) argue that entrepreneurs in transition economies have learnt

how to respond to institutional deficiencies in particular weak property rights protection For

example some businesses experiencing high growth choose to invest in unrelated

businesses instead of growing their core businesses for the reason they do not want to

become too noticeable to attract too much attention of the wrong sort In our instance having

some connections with officials seems also to serve as protection against arbitrary

government or individual rent-seeking that makes businesses more keen on re-investing their

retained profits (see Johnson et al (2002) on the discussion of how more secure property

rights can make small firms reinvest more of their earnings)

5

BelarusKyrgyzstan Tajikistan and Uzbekistan) in both areas of the financial institutional

reforms Overall after the years of the financial sector reform the majority of transition

economies still have rather shallow domestic credit systems (Figure 1) and relatively

underdeveloped capital markets with market capitalisation ratio varying from as low as 16

per cent of GDP in Kyrgyzstan and Armenia2 to as high as 40-50 per cent in Croatia amp

Kazakhstan respectively in 2009 with Montenegro and Russia standing out compared with

the rest of the region3

Figures 1 amp 2 to be inserted here

A number of empirical studies further confirm that financial constraints in transition

economies constitute one of the main obstacles for start-up entry and growth (Pissarides

1998 1999 2001 Pissarides et al 2003 Klapper et al 2002) Pissarides (2001) concludes

that lack of access to finance is more binding for SMEs than larger businesses with the

severity of this constraint being stronger in South-East Europe compared to other transition

economies including the Commonwealth of Independent States (CIS) In their study of SME

growth in Russia and Bulgaria Pissarides et al (2003) find that financial constraints hamper

SME growth and that SMEs resort to the use of internal funds to overcome constraints on

external finance This is similar to Johnsonrsquos et al (2002) findings suggesting that internal

finance can substitute for external finance (see also Lizal and Svejnar (2002) for similar

conclusions) Pissarides et al (2003) also show that financial constraints affect SMEs more

than barriers related to property rights issues Drawing on the data on 15 Eastern European

countries Klapper et al (2002) show that financial constraints affect SMEs longer-term ability

to grow Finally Gorodnichenko and Schnitzer (2010) show that financial constraints restrain

the ability of domestically-owned firms to innovate and export thus inhibiting productivity

growth They also argue that this negative effect is magnified due to financial constraints

forcing export and innovation activities to become substitutes whereas they are commonly

found to be complements

We complement these studies with the most recent empirical evidence on the

determinants of SMEsrsquo perception of financial constrains in transition economies which

comes from the 2002-09 BEEPS dataset The BEEPS self-reported measure of financing

constraints unites in one termed lsquoaccess to financersquo metric both quantity and price

constraints In the surveys firms were directly asked to indicate the extent to which access to

2 In fact it goes as low as 02 per cent of GDP in Uzbekistan in 2005 following the World Development Indicators data with no data reported for subsequent years 3 Montenegro and Russia emerge as outliers given their far higher ratios of market capitalisation These are 104 and 70 per cent respectively and they are far above of some West European countriesrsquo ratios including Germany and comparable to the ones in China and USA

6

finance was an obstacle to their operations and the averages for the individual countries in

the dataset are shown in Figure 3 With exception of Bosnia and Uzbekistan4 SMEs in all

transition economies are more financially constrained than larger firms although as our

empirical results show (see Section 5) the difference in perception of financial constraints

has been largely eliminated between smaller and larger firms during the recent global

financial crisis

Figure 3 to be inserted here

It has previously been argued that a low reliance on outside financing scarce use of

equity finance5 and low level of inter-firm trade financing is a common feature of small firms

across the transition region of Europe and Central Asia (Klapper et al 2002 Pissarides

1998 2001) Furthermore Klapperrsquos et al (2002) find almost no use of long-term debt

attributing this to the underdevelopment of the banking sector weak collateral law and poor

credit information registries Their evidence also shows virtually zero reliance of SMEs

across the 15 Eastern European countries on trade credit with the exception of Hungary and

to a lesser extent of the Czech Republic Poland and Romania They explain this by

insufficiency of partner firmsrsquo internal funds or their inability to access external borrowings to

become able to finance extension of trade credit Low reliance on trade credit may be also

attributed to low foreign presence in some countries of the region as multinationals could

extend trade credit to local firms including SMEs (Klapper et al2002)

Figure 4 shows the relative importance of financing sources used for purchase of fixed

assets by SMEs in the transition economies The data underlying this figure are the relative

percentages of the financing sources firms used in the year preceding a BEEPS survey year

in the BEEPS 2002-2009 surveys The surveys group financing sources into the following six

types internal funds or retained earnings ownersrsquo contribution or issued new equity shares

[funds] borrowed from private banks [funds] borrowed from state-owned banks purchases

on credit from suppliers and advances from customers and other (moneylenders friends

relatives non-banking financial institutions) Figure 4 suggests that SMEs in the transition

economies tend to largely rely on their internal funds or retained profits in funding their

investment Only about 23 per cent of small and medium-sized firms rely on borrowing from

private banks Trade credit and equity finance occupy similar shares in funding SMErsquos

investment decisions and account for the mere 9 per cent of total purchase of fixed assets

4 In Bosnia amp Uzbekistan larger firms are marginally more constrained than smaller ones (at 10 percent level of significance) 5 Small firms may also decide to limit their issuance of outside equity to avoid reduction in control of their firms (Scherr et al1990 and Hamilton and Fox 1998 cited in Klapper et al 2002)

7

According to Cull (2007) trade credit can be seen as substitute for loans for private firmsrsquo

trading partners that are shut out of financial credit market Other sources include borrowing

from informal money lenders and family and these emerge as the third important source of

funding SMEsrsquo investment after internal funds and bank credit We expect the informal

finance to be mostly comprised of equity provided by family and friends as funding obtained

from informal private money lenders was overly expensive with the premium standing at least

20 percentage points above that charged by local intermediaries (Pissarides 1998)

Figure 4 to be inserted here

In conclusion we note that the number of studies of the financing decisions of small

and medium-sized enterprises in emerging markets and in particular in the former centrally

planned economies or previously heavily regulated economies such as India has been rather

limited (see eg Nivorozhkin 2005 Delcoure 2007 Crnigoj 2007 Chakraborty 2008

Girma et al 2008 Li et al 2009 Correa et al 2010 Love and Zaidi 2010) We contribute to

this literature by analysing for SMEs in these countries the determinants of the following five

financing options retained earnings private loan (loan finance from private banks) trade

credit private equity (ownersrsquo equity) and informal finance In this study the phrase lsquoinformal

financersquo is an umbrella term that helps condense in one category funds from moneylenders

friends relatives non-banking financial institutions Our results allow us to shed more light

on whether and how the theories of financing choices apply to transition countries in the

credit crunch environment

The following section discusses theories pertaining to small firm financing and how this

may be affected by a financial crisis

3 Small Firm Financing and the Effect of Crisis Theoretical Considerations and

Hypotheses

31 Theoretical arguments

When analysing financing choices of SMEs we first turn to the two cornerstone

theories of explaining leverage the trade-off theory and the pecking order hypothesis (POH)

While the former states that firms may prefer debt to equity in the presence of corporate tax

subject to the costs of potential financial distress stemming from borrowing large amounts

(Modigliani and Miller 1958) the latter suggests that the firms first finance their investment

out of retained earnings as this is the cheapest and the most readily available alternative

then out of debt and lastly via issuing equity which is seen as the most expensive option to

8

the firm (Arnold 2008) More recent literature on firm financing started to look closer at and

emphasize the importance of other sources such as trade credit especially for the small and

medium firms using mostly the data on developed economies For instance Berger amp Udell

(1998) stress the importance of trade credit to the short-term financing of small firms Bevan

and Danbolt (2002) estimate that trade credit account for 62 per cent of total liabilities of UK

firms

The role of trade credit has been seen by some researchers as a substitute of bank

lending for liquidity-constrained firms (Cull 2007) such as SMEs One of the benefits of trade

credit compared to the bank lending is that it allows to partly get around the information

asymmetry problem between the lender and the borrowing SME as business partners would

have more information about the ability of the borrower to repay and about such reputation of

the borrower in the industry Meltzer (1960) Nielsen (2002) and Petersen and Rajan (1997)

argue that trade credit may also provide a means of alternative financing under the tight

monetary conditions such as credit crunches when financial institutions are less able or

willing to provide loans to SMEs In support of this hypothesis Atanasova and Wilson (2003

2004) and Mateut et al (2006) find that under tight monetary conditions firms tend to

substitute bank loans with trade credit However the findings in Bernanke and Gertler (1995)

and Gertler and Gilchrist (1993) do not agree with this hypothesis In line with these authors

Taketa and Udell (2007) using a sample of Japanese SMEs after the crisis years find that

bank lending and trade credit are complements rather than substitutes Love and Zaidi

(2010) report that the use of trade credit by East Asian firms has declined after the 1998

financial crisis together with the use of bank loans Finally interesting enough there is

some empirical evidence which suggests that in the context of transition economies there

may be a higher reliance of SMEs on trade credit in the period of crisis More specifically

focusing on the panel of 1686 firms in Bulgaria Hungary Latvia Lithuania Romania and

Turkey in 2007 and 2009 Klapper and Randall (2010) find that during periods of contractions

in bank credit buyers might depend more on trade credit (although primarily to be used for

short-term financing) that may be particularly true for small firms This provides some support

for the hypothesis that the two sources of finance namely bank loans and trade credit in the

context of transition and emerging economies can be seen as substitutes in period of crisis

Another source of firm financing that has recently received increased attention is

private equity Private equity consists of investments by private individual investors or firms

(business angels investments funds) as well as business ownersrsquo contributions to their

equity The lsquobusiness angelsrsquo type of private equity is currently on the rise in the developed

countries as well as emerging markets such as India Brazil China Malaysia However

ownersrsquo contribution is a far more widespread type of private equity in countries under

consideration Generally SMEs are prone to various types of business and financial risks

9

and it would be very important for them to try and hedge against these risks Zou and Adams

(2008) look at the effect of property insurance on the public firmsrsquo borrowing capacity in

China while Matthews and Scott (1995) in the US and Herbane (2011) in the UK investigate

the types of risk management used by the SMEs The findings point to a rather limited use by

the small and medium-sized enterprises of the risk management assessment and hedging

techniques

In the emerging markets of the post-Soviet bloc the use of risk management techniques

such as hedging with financial derivatives is virtually non-existent However an informal risk

management practice of accumulating cash out of profits and also of using informal lending

from family and friends to serve as a cushion in the times of financial distress as protection

against possible bankruptcy and as an instrument of insurance against risks has been one

way of accounting for the risky nature of SMEs in these countries Secondly many SMEs

sometimes use bankruptcy when they find themselves in the situation of financial distress

and then open a new firm without losing much of their personal assets (Radygin et al 2005)

These SMEs are oftentimes are registered as belonging to a relative or the SMEs could be

registered as founded by an artificially created third party with no links to the actual ownerrsquos

personal assets Recently banks in the new emerging economies such as Russia started a

practice of compulsory purchase of loan insurance if the SME is to take a loan from the bank

This serves as a risk insurance mechanism to a certain extent at the same time however

increasing the cost of bank financing However more recently this practice has attracted the

attention of the Federal Antimonopoly Service that ruled that there is evidence of collusion

between banks and insurance companies Overall we could conclude that the use of risk

management practices is very narrow and of a rather informal nature

The next sub-section explores in greater detail the institutional context of financing in the

situation of economic crisis

Empirical studies on small firm financing in the years of crisis are primarily motivated by

the informational asymmetries theories One of the most important contributions in the study

of the role of SMEs during business cycle has been the real business cycle (RBC) theory

(Bernanke and Gertler 1995 Bernanke Gertler amp Gilchrist 1998) The argument put forward

by the RBC theory is that SMEs face tighter liquidity constraints in terms of external financing

due to higher informational asymmetries associated with their activities the low value of

their assets to serve as collateral the high cost of monitoring small businesses given a small

scale of their investment projects and subsequently the unwillingness of banks to lend to

SMEs

During economic slowdowns when small businesses are even more in need of external

finance bank lending to them diminishes even further which tends to propagate the crisis if

the SMEs then go out of business (see for example Tornell and Westermann 2005) At the

10

same time as larger firms use more finance and tend to rely more on external funding they

may be hit harder by financial contraction in the situation of global crises when international

financial markets dry up so preventing larger firms from drawing upon them when required

They are also less flexible and it is more costly for them to restructure and downsize when

they are hit with external shocks Furthermore while SMEs tend to be more flexible in relying

on other sources of finance including trade credit contributed equity and informal finance

the financial structure of larger firms generally tends to be less diversified with a preference

often given to retained profits and bank finance following the pecking order theory Taken

together we may argue that both supply and demand for finance is more affected for larger

firms in the situation of external shocks

Based on the discussion presented in Sections 2 and 31 we further discuss three main

groups of factors which are likely to affect firmsrsquo perception of financial constraints and their

financing choice strategy These are as follows (1) firm size in general and in the period of

crisis (2) other firm- and industry-specific characteristics including foreign ownership export

orientation firmsrsquo social capital and the degree of competition and its pressure on the firm to

develop a new product and (3) country-level institutional parameters including the degree of

protection of property rights and the development of the financial sector

32 Size of the enterprise and the effect of crisis

With regards to the effect of firm size based on the general discussion in the literature

(see sections 2-31) we expect SMEs to be more financially constrained in their access to

external lending and respectively more reliant on internal funds This is due to insufficient

information that the bank can obtain about a particular SME as well as due to a potentially

lower size of collateral However this lower reliance of SMEs on external debt can potentially

be a source of flexibility during the crisis when formal financial markets dry up and when

even large well-established firms have difficulty obtaining bank credit Furthermore following

Atanasova and Wilson (2003 2004) Mateut et al (2006) and Klapper and Randall (2010) we

expect that under tight monetary conditions SMEs in transition economies are more likely to

switch to alternative forms of financing such as trade credit We also hypothesize that SMEs

are more likely to rely on ownersrsquo contributed equity which they tend to accumulate in good

times as part of their risk management strategy to use it as a cushion in the times of financial

distress In summary we expect the difference between the SMEs and large firms in their

reliance on bank finance to diminish during the crisis years and second SMEs to be more

flexible and rely more on other sources of finance such as trade credit and private equity in

the period of financial contractions

11

33 Firm- and industry- level factors

As far as the firm-level and industry-level variables are concerned we expect the

following results first the level of social capital of a firm as proxied by the inverse of the time

spent dealing with government regulations to indicate possible established connections with

public officials can positively affect its access to trade credit Next the industry-level

pressure on a firm from competitors to develop a new product may increase the firmrsquos

chances of obtaining a bank loan as the bank may perceive the firmrsquos operations as more

diversified and less risky (Isachenkova et al 2011) We also expect foreign competition and

the pressure it exerts on a firm innovation capability to play less important role for firm

financing decisions as SMEs are more likely to operate in market niches and they are

unlikely to compete with multinational enterprises In contrast we expect a pressure

originated from customers on a firm to innovate to increase a firmrsquos probability to rely more

on external sources of funding This may be attributed to the fact that a firm does not only

differentiate itself from other firms further with developing a new product but also assures a

demand for this product by responding to the needs of its existing customers The

guaranteed demand for a new product would be one of the most crucial factors taken into

account by bank managers or potential investors in decision-making concerning project

financing Thirdly international product certification may play a similar role with regards to

bank loans increasing the access to external funds Fourth we investigate the effect on the

choice of financing of the firm age with a square term Generally older firms may have

easier access to bank loans as more information is available about them to the lender (Beck

et al 2006 Canton et al 2010) however due to the particulars of the transition period

sometimes older firms may be less economically viable and unable to get a loan therefore

the sign of this coefficient is uncertain here Lastly we also look at the firmrsquos export

orientation which is expected to increase the reliance on bank lending and its ownership

type where we single out foreign and domestic private firms In the case of foreign firms

they are less likely to use private loans and rely instead on retained earnings and intra-

company funds transfers in the case of MNCs

34 Institutional environment

The impact of institutional variables on the financing choices of firms has been of the

utmost interest to economists and policy-makers during the period of transition (see for

example Stijn and Tzioumis 2006 Mitra et al 2008 see also Commander and Svejnar

(2009) for an in-depth and comprehensive analysis of the impact of various business

environment factors on firm performance using BEEPS 2002 - 2005 panel) In our analysis

12

we concentrate on two institutional factors the degree of protection of property rights and the

size of the formal financial sector which have been claimed to be of key importance for firmsrsquo

financing decisions (see Korosteleva and Mickiewicz (2011) for overview of the related

literature) As far as the property rights protection is concerned it is found to play crucial role

for firm growth and access to external finance (Aidis et al 2008 2010 Korosteleva and

Mickiewicz 2011 Estrin Korosteleva and Mickiewicz 2011) In the environment with weak

protection of property rights financial contracts are less likely to be concluded leading to the

underdevelopment of finance and credit rationing with small firms to be disproportionally

affected the most (Acemoglu and Johnson 2005) Beck et al (2004) show that in terms of

access to external finance small firms benefit disproportionally from higher levels of property

rights protection Lack of secure property rights may also discourage SMEs from taking full

advantage of opportunities to invest (Johnson et al 2002) In a survey of private small

manufacturing firms in Poland Russia Ukraine Romania and Slovakia Johnson et al

(2002) find that small firms tend to reinvest less of their earnings when they perceive their

property rights insecure They also find that the effect of the property rights system is of more

paramount importance for entrepreneursrsquo decisions to reinvest their earnings than availability

of formal finance Moreover if property rights are well-protected this lessens the extent of

potential threat of being expropriated by raidersbank lenders in an artificial bankruptcy

procedure which has been quite a significant issue for firms in Russia and other FSU states

(Radygin et al 2005 Sprenger 2002) Based on this we expect that strong property rights

are likely to encourage SMEs to use more debt as well as to use their own funds and

retained profits for investing in investment projects

With regards to the size of the formal finance as measured by the share of private

credit to GDP the relationship between financial depth and financial constraints has been

extensively studied (Beck et al 2006 also see for example Love 2003 who employing a

sample of 36 countries finds that financial development affects firmsrsquo investment by

increasing the availability of external finance) Financial intermediaries facilitate the risk

amelioration in the presence of problems created by information and transaction frictions by

developing expertise in risk assessment and in monitoring (Levine 1997 Barth et al 2006

Barth et al 2008) Developed financial institutions are found to be particularly beneficial for

small firms compared to large ones (Barth et al 2006 Beck et al 2005 2006 2008)

Pissarides et al (2003) show that financial constraints affect SMEs even more than

deficiency of the property rights protection Accordingly the size of the formal financial

system is expected to be positively related to the use of bank finance as a better functioning

financial system should help ease up borrowing constraints

4 Data and Methodology

13

41 Sample

To explore the determinants of the financial structure of small businesses we use the

2002-2009 Business Environment and Enterprise Performance Survey (BEEPS) data6 of

21867 firms covering 26 transition economies of Europe and Central Asia (ECA)7

The sample is primarily comprised of small and medium-sized businesses8 which

account for 893 per cent of the sample The sample is representative in terms of industrial

coverage with the majority of SMEs of the sample operating in manufacturing wholesale

and retailing industries

BEEPS dataset provides rich information on firm characteristics investment

behaviour and firmsrsquo perception of business environment including financial constraints

which are of a primary interest for our investigation of the effect of the recent financial crisis

on firmsrsquo perception of financial constraints Potentially we could use other micro-level data

characterising various domains of business environment captured by firmsrsquo perceptions for

investigating the effects of the institutional settings However using these micro-level

indicators as explanatory variables would make our study plagued with a problem of

endogeneity To avoid this we merge our firm-level data with country-level indicators

characterising various institutional domains The country level data were obtained from the

World Development Indicators (World Bank) and Polity IV databases (for further discussion

see below) Finally the BEEPs dataset contains other useful information which allows us to

shed light of the effect of for example social capital as proxied by the indirect measure of

possible connections with the authorities (see below for the definition of the variable) on firm

financing

42 Variable Definition and Measurement

Explanatory variables

6 This data is a joint project of the European Bank for Reconstruction and Development and World Bank The first survey was launched in 1999 The dataset used in the present study is an unbalanced panel covering the years of 2002 2005 2007-2009 7 The sample includes the following countries Albania Armenia Azerbaijan Belarus Bosnia Bulgaria Croatia Czech Republic Estonia FYROM Georgia Hungary Kazakhstan Kyrgyzstan Latvia Lithuania Moldova Montenegro Poland Romania Russia Serbia Slovakia Slovenia Tajikistan and Ukraine We exclude Uzbekistan as an outlier from our sample We also exclude Turkey as it is not classified as a post-communist country undertaking transition from a planned to a market economy 8 We utilize the EU employment criterion to define small and medium-sized businesses More specifically businesses are defined as micro if they employ 9 and less employees small ndash between 10 and 49 medium ndash between 50 and 249 and large ndash over 250 employees Respectively SMEs are defined as firms employing less than 249 firms

14

To test our main hypothesis of the effect of a firm size on firmsrsquo perception of financial

constraints we introduce a dummy variable denoting small and medium-sized business

coded as 1 if firms are classified as small or medium-sized businesses according to the EU

definition based on the employment criterion For robustness of our results we also use a

continuous variable denoting a size of employment as measured by the natural logarithm of

employment9 The obtained results are consistent with the ones using the SME indicators

To capture the effect of the recent financial crisis we introduce a crisis dummy coded

as 1 if the year of survey is equal to 2008 or 200910

We also introduce a number of firm-level controls which include age of firm11 type of

ownership including private and foreign ownership export orientation and whether a firm

has an internationally certified product all equal to 1 if a business has a respectively listed

characteristic and zero otherwise We also examine the effect of various sources of pressure

on firms to innovate ndash the indicators which are considered to be important for firm investment

decisions Respectively the pressure for innovation may stem from domestic competition

foreign competition and customers To capture the effect of a firmrsquos social capital we

introduce an indicator which indirectly may capture some possible connections of a firm with

authorities It is proxied by time spent by each firm on dealing with government regulations

We assume the less time firms spend dealing with government regulations the more likely

they have some established connections with public officials which allow them to avoid

burdensome regulation procedures

In our study we also introduce a number of country-level variables which characterize

the institutional environment in the countries covered by our sample More specifically we

include an indicator of the financial development as measured by the ratio of domestic credit

to private sector to GDP (one year lag to avoid potential endogeneity) obtained from the

World Bank World Development Indicators (World Bank 2011) This measure has been used

in previous studies (Klapper et al 2006) and it is expected to be of a primary importance for

transition economies where firms tend to rely more on bank finance rather than capital

markets We also introduce a measure of property rights protection (a one year lag) proxied

by the indicator of effective constraints imposed on the executive branch of the government

and obtained from Polity IV project12 This measure of property rights protection is

9 These results are not reported here to save some space However they can be obtained from authors upon request 10 Here it is important to note that although the financial crisis has started in 2007 in the USA it spread to transition economies in 2008-2009 11 Some studies find a non-monotonic relationship between age and firm decision-making In this study we introduce a squared term of age along with a age variable to capture this possible non-linearity 12 Available from httpwwwsystemicpeaceorgpolitypolity4htm

15

considered to be superior to other indicators including the index of property rights reported

by the Heritage Foundation ndashWall Street Journal (for further discussion see Acemoglu and

Johnson 2005 Glaeser et al 2004 Estrin Korosteleva and Mickieiwcz 2011)

In the present study we also introduce macroeconomic controls including cyclical

economic performance as measured by the one year lag of the GDP annual growth rate

and the level of economic development as proxied by a set of GDP pc dummies denoting

the five quintiles of its distribution to address the problem of potential multicollinearity with the

measure of financial development

Finally we include industry and country controls in all our specifications Introducing

country dummies into analysis allows to control for cross-country heterogeneity

For further definition of all variables their descriptive statistics and correlation matrix

see Tables 1-2

43 Dependent variables

To investigate the effect of a firmrsquos size on its perception of financial constraints we

construct a dummy variable coded as 1 capturing a major and very severe obstacle for

access to finance and 0 otherwise

The firm financing choices are defined by the five individual dependent variables

associated with tobit financial choice equations in the seemingly unrelated regression

equations model

One important thing to mention here is the inability to distinguish between

owninternal funds and external private equity considered as one of the limitations of the

2002-2009 BEEPS dataset In the period under investigation BEEPS offers two questions

which aim to capture the use of equity The first one centres around retained earnings and

the second one shows ownersrsquo contributions and private equity or issued new equity

Following some theoretical considerations discussed in sections 2 and 3 in the context of

SMEs we expect the second element of equity to be primarily comprised of existing ownersrsquo

new contributions rather than private equity

Thus the indicator of financial choices represents a set of five individual dependent

variables including retained earnings contributed earnings private borrowing informal

finance trade credit with each of them constructed as a share in total financing of SMErsquos

investment decisions (see Table 1)

44 Methods

16

In this study we employ a number of estimators to obtain robust results More

specifically we use a probit model to investigate the effect of a firm size and the recent

financial crisis on firmsrsquo perception of financial constraints The effect of a firm size in the

situation of crisis is captured by the introduction of the interaction term between firm size as

proxied by the SME indicator and a financial crisis dummy

We further employ the seemingly unrelated regression equations model combined

with the tobit approach for studying firmsrsquo financial structure

Probit model of perception of financial constraints

In the probit model the probability of a firmrsquos perception of financial constraints as

major(j = 1) can be written as follows

( ) ( )int ++

++

infinminus

minus===

ijitj uXjitiitit ijitjuXjy uX

βα βαππ 212-

)()(2 21exp|Pr

Where ity is our measure of financial constraints as perceived by firms and itX is a

set of our explanatory variables discussed in detail in sections 3-4 Here it is important to

note that the interaction term in a probit model cannot be interpreted in a similar way as in

linear models and disregarding this may lead to misleading estimates of the interaction

effect which is of crucial importance for our study (Norton Wang and Ai 2004) Respectively

for robustness of our results here we follow the framework suggested by Norton Wang and

Ai (2004) to account for the model nonlinearity The adjusted marginal effects for the

interaction term are reported in the note to Table 313

Simultaneous Model of Financing Choices

As mentioned above we next model the choice of all five financing choices explicitly

We also hypothesise (following Isachenkova et al 2011) that firm financing choices are likely

to be determined jointly A standard way of modelling jointly determined indicators is a

system of equations - SURE ndash seemingly unrelated regression equations where equations

are linked only by their errors (Zellner 1962) We therefore model the five types of sources of

finance (internal funds private bank borrowing informal finance trade credit and private

13 We also run a probit regression for a split sample of (1) SMEs and (2) large firms to check the robustness of our results (based on the interaction term) while addressing a problem of multicollinearity between a crisis variable and its interaction term with a SME variable The correlation coefficient between a crisis variable and its interaction term with a SME variable is equal to 93 This can be attributed by the problem of a sample being overrepresented by SMEs which constitute 90 of all surveyed firms The results remain robust and can be available from authors upon request

17

equity) using a SURE framework within which we specify a set of five tobit regressions with

correlated residuals

We employ the STATA cmp module which allows to it Seemingly Unrelated Regressions

using the simulated likelihood method such as the Geweke Hajivassiliou and Keane (GHK)

algorithm (for further discussion see Roodman 2008) We utilise a tobit equation to model

each individual financial choice of firms because our dependent financing choices variables

are continuous but their range is constrained (censored) with a substantial number of

observations either equal to zero denoting those who do not use the respective source of

finance or to 100 showing the opposite Other observations are positive and may produce

many different outcomes (Verbeek 2000) Each tobit equation uses a set of identical

explanatory variables that proxy factors which could possibly be associated with firmrsquos

financing choices including industry and country dummies

We also considered the bias caused by potential interdependence between the choice of

whether to invest and firmrsquos financing choices We accounted for the potential selection bias

by introducing into the financial choices SURE Tobit equations (second stage outcome

equations14) the inverse Millrsquos ratio calculated based on modelling the choice to invest in

fixed assets (first stage or selection equation) To identify the first stage of the Heckman

selection model we chose a variable which is correlated with the first stage dependent

variable (investment decision) but not with the second ones (financing choices) We used the

rate of capacity utilization as part of our identification strategy Capacity utilization shows the

percentage of capital stock in use the higher is the rate the more likely firms will increase

investment Batyaeva and Aukutsionek (2001) show that the rate of capacity utilization is

higher in the group of investing firms than in the group of non-investing firms in Russia15 We

calculated the inverse Millrsquos ratio based on the above selection equation16 and included it as

a control in the second stage SURE Tobit equations The inverse Millrsquos ratio has only proved

to be statistically significant in the private bank loan equation pointing to the potential

selection bias arising from the possibility that the factors determining the decision to invest

might differ from those determining the use of bank financing in purchasing fixed assets

14 We also attempted to estimate an investment equation jointly with Tobit financial choices equations within the SURE framework using However given the overall complexity of the model we failed to do this We proceeded further with a two-stage approach by estimating an investment probit equation and calculating the inverse Millrsquos ratio that we add into the outcome financial choices equations at the second stage of the analysis to test for the selection bias 15 We performed an independent sample t-test to check whether the rate of capacity utilization is statistically significantly higher for investing firms compared to non-investing firms for our sample The null hypothesis of no difference was rejected at 1 level of significance 16 To economize on space we do not report the results of the investment probit equation but they are available from authorsrsquo upon request

18

Finally In Table 6 we attempt to condition the determinants of financing constraints

declared by SMEs on the relative percentage increase of trade credit in total funds used for

real investment As mentioned above in Section 2 the timings of measuring the composition

of financing sources precede by a year the timings of measuring the perceptions of financing

constraints That feature of the BEEPSrsquo design allays a likely concern about the endogeneity

of the relative proportion of trade credit and enables causal inference We too report in thre

note to Table 4 the adjusted marginal effects for the interaction term of the SME dummy with

the trade credit variable

In the next section we discuss our empirical results

5 Empirical Results

Table 3 reports the results of the probit model with the marginal effects for firmsrsquo

perception of financial constraints while Tables 4-5 summarize the results of SURE tobits for

a more detailed breakdown of five financing choices More specifically Table 4 reports the

results based on the whole sample to give a comparative perspective on SMErsquos financing

strategy vis-a-vis large businesses whereas Table 5 reports the results based on a

subsample of small and medium-sized firms to shed some light on their financing choices in

the period of crisis

Perception of financial constraints

Table 3 shows that generally small and medium-sized enterprises feel more financially

constrained with the coefficient for SME dummy in relation to the large firms being positive

and significant which is consistent with our discussion in sections 2-3 However the

coefficient of the interaction term with the Crisis dummy turns out to be negative and

significant in relation to the perception of financial constraints as a major obstacle and it

tends to outweigh the effect of a SME dummy when we calculate marginal effects The effect

of the interaction terms with the crisis remains robust after we adjust for non-linearity using

the framework proposed by Norton Wang and Ai (2004)17 Overall these results confirm

that small and medium-sized enterprises are much less financially constrained during the

crisis years with their perceptions close to those of the large firms This result is a polar

opposite to that obtained for the SMEs in the UK (Fraser 2009) which finds that not only do

SMEs generally feel more financially constrained but they report to be even more so during

17 We also check the robustness of our results to the potential problem of multicollinearity between a crisis dummy and its interaction term with SME by splitting a sample and testing the same specification separately for SMEs and large firms We also perform another robustness check by breaking a SME dummy into three subsequent dummies namely micro- small- and medium-sized firms The difference in perception of financial constraints gets almost eliminated in the case of small firms and is largely reduced in the case of micro firms whereas it is less so for medium-sized firms

19

the last crisis We could explain this striking difference by the peculiarities of the SMEs

functioning in new emerging economies The lower reliance of SMEs on external debt in

good times (as shown by results which are discussed below) gives SMEs some flexibility

during the crisis when formal financial markets dry up Jointly with overall flexibility to make

necessary cost cuts and to restructure a business this overall lower reliance on external

funding and the use of alternative sources of financing makes SMEs feel less financially

constrained under the crisis as compared to larger firms

We also find that a more developed financial sector as proxied by domestic private

credit as proportion of GDP helps ease up financial constraints This is in line with the

general literature suggesting that better functioning financial intermediaries facilitate the risk

amelioration in the presence of problems created by market frictions (Levine 1997 Barth et

al 2006 Barth et al 2008)

Unfortunately we fail to find any significant effect of the property rights protection on

firmsrsquo perception of financial constraints that may be explained by the fact that the effect of a

more developed financial sector is likely to outweigh the effect of the property rights

protection

Finally we also find that foreign ownership and international product certificate may

reduce firmsrsquo borrowing constraints while any pressure from domestic or foreign competition

so is pressure from the customers to innovate will increase firmrsquos perception of financial

constraints as major given that firms envisage the need to secure external funding for RampD

or any other innovation-related activities

Financing choices for investment in fixed assets

The results in Table 4 indicate that small enterprises tend to rely more on internal funds

and less on bank loans but they are no different from larger firms in respect of using informal

funds trade credit or private equity which is generally consistent with our discussion in

Sections 2 and 3 The results of Table 5 suggest however that under crisis small and

medium-sized firms tend to switch to other sources of finance such as trade credit and

ownerrsquos contributed equity and to respectively reduce the reliance on retained earnings

perhaps because they decrease due to the negative impact of crisis internal funds With

regards to our discussion of SMEsrsquo risk management we note that the use of private equity

(ownerrsquos contribution) during the crisis years increases which could indicate that the ownerrsquos

funds are used as a cushion in the period of financial distress

An interesting insight regarding the use of trade credit emerges for SMEs in our

sample although in non-crisis years small and medium-sized businesses are not significantly

different from larger firms in terms of reliance on trade credit SMEs tend to finance a

significantly higher proportion of their fixed asset investment by trade credit than large firms

20

in the period of crisis While the latter finding is partly in line with some other studies ndash such

as Klapper and Randall (2010) using BEEPS data it is in stark contrast with similar studies

of the UK private firms (Rehman 2011) for which the use of trade credit is found to have

dried up in crisis This could partly be due to the passed legislation in the UK tightening trade

credit regulation as the result of the abuse of trade credit by large firms in relation to small

firms which forced many SMEs out of the market

With regards to the other firm-level characteristics international certification makes the

firm rely more on private bank loans and informal finance (Table 5) while SMEs with foreign

ownership rely less on private debt but more on retained earnings Both results are

consistent with our hypotheses discussed above Export-oriented small and medium-sized

businesses tend to have greater reliance on trade credit and they use less of internal funds

We find a non-monotonic relationship between age and private equity with both younger and

older firms being more reliant on this source of funding We find some fragmentary support

for private domestic SMEs relying more on informal finance while tending to use less trade

credit and private equity (Table 5)

Interestingly our results (Tables 4-5) suggest that firms which lack some social

connections with governmental officials proxied by the higher amount of time spent dealing

with government regulations are more likely to rely on informal finance trade credit and

private equity In turn businesses which are connected to governmental officials use more

retained profits to fund investment in fixed assets This may be attributed to their connections

serving as a guarantee from expropriation of assets by all sort of rent-seeking individuals

akin private contracting to secure property rights protection This result should be interpreted

jointly with the property rights protection results We expected that better property rights

protection is likely to facilitate firmsrsquo access to bank loan but we failed to confirm this

Perhaps regardless some attempts at a constitutional level to prevent arbitrary government

(which is proxied by our measure of property rights) expropriation culture is still deeply

embedded in the society of post-communist countries and it may manifest in different ways

Welter and Smallbone (2011) argue that entrepreneurs in transition economies have learnt

how to respond to institutional deficiencies in particular weak property rights protection For

example some businesses experiencing high growth choose to invest in unrelated

businesses instead of growing their core businesses for the reason they do not want to

become too noticeable to attract too much attention of the wrong sort In our instance having

some connections with officials seems also to serve as protection against arbitrary

government or individual rent-seeking that makes businesses more keen on re-investing their

retained profits (see Johnson et al (2002) on the discussion of how more secure property

rights can make small firms reinvest more of their earnings)

6

finance was an obstacle to their operations and the averages for the individual countries in

the dataset are shown in Figure 3 With exception of Bosnia and Uzbekistan4 SMEs in all

transition economies are more financially constrained than larger firms although as our

empirical results show (see Section 5) the difference in perception of financial constraints

has been largely eliminated between smaller and larger firms during the recent global

financial crisis

Figure 3 to be inserted here

It has previously been argued that a low reliance on outside financing scarce use of

equity finance5 and low level of inter-firm trade financing is a common feature of small firms

across the transition region of Europe and Central Asia (Klapper et al 2002 Pissarides

1998 2001) Furthermore Klapperrsquos et al (2002) find almost no use of long-term debt

attributing this to the underdevelopment of the banking sector weak collateral law and poor

credit information registries Their evidence also shows virtually zero reliance of SMEs

across the 15 Eastern European countries on trade credit with the exception of Hungary and

to a lesser extent of the Czech Republic Poland and Romania They explain this by

insufficiency of partner firmsrsquo internal funds or their inability to access external borrowings to

become able to finance extension of trade credit Low reliance on trade credit may be also

attributed to low foreign presence in some countries of the region as multinationals could

extend trade credit to local firms including SMEs (Klapper et al2002)

Figure 4 shows the relative importance of financing sources used for purchase of fixed

assets by SMEs in the transition economies The data underlying this figure are the relative

percentages of the financing sources firms used in the year preceding a BEEPS survey year

in the BEEPS 2002-2009 surveys The surveys group financing sources into the following six

types internal funds or retained earnings ownersrsquo contribution or issued new equity shares

[funds] borrowed from private banks [funds] borrowed from state-owned banks purchases

on credit from suppliers and advances from customers and other (moneylenders friends

relatives non-banking financial institutions) Figure 4 suggests that SMEs in the transition

economies tend to largely rely on their internal funds or retained profits in funding their

investment Only about 23 per cent of small and medium-sized firms rely on borrowing from

private banks Trade credit and equity finance occupy similar shares in funding SMErsquos

investment decisions and account for the mere 9 per cent of total purchase of fixed assets

4 In Bosnia amp Uzbekistan larger firms are marginally more constrained than smaller ones (at 10 percent level of significance) 5 Small firms may also decide to limit their issuance of outside equity to avoid reduction in control of their firms (Scherr et al1990 and Hamilton and Fox 1998 cited in Klapper et al 2002)

7

According to Cull (2007) trade credit can be seen as substitute for loans for private firmsrsquo

trading partners that are shut out of financial credit market Other sources include borrowing

from informal money lenders and family and these emerge as the third important source of

funding SMEsrsquo investment after internal funds and bank credit We expect the informal

finance to be mostly comprised of equity provided by family and friends as funding obtained

from informal private money lenders was overly expensive with the premium standing at least

20 percentage points above that charged by local intermediaries (Pissarides 1998)

Figure 4 to be inserted here

In conclusion we note that the number of studies of the financing decisions of small

and medium-sized enterprises in emerging markets and in particular in the former centrally

planned economies or previously heavily regulated economies such as India has been rather

limited (see eg Nivorozhkin 2005 Delcoure 2007 Crnigoj 2007 Chakraborty 2008

Girma et al 2008 Li et al 2009 Correa et al 2010 Love and Zaidi 2010) We contribute to

this literature by analysing for SMEs in these countries the determinants of the following five

financing options retained earnings private loan (loan finance from private banks) trade

credit private equity (ownersrsquo equity) and informal finance In this study the phrase lsquoinformal

financersquo is an umbrella term that helps condense in one category funds from moneylenders

friends relatives non-banking financial institutions Our results allow us to shed more light

on whether and how the theories of financing choices apply to transition countries in the

credit crunch environment

The following section discusses theories pertaining to small firm financing and how this

may be affected by a financial crisis

3 Small Firm Financing and the Effect of Crisis Theoretical Considerations and

Hypotheses

31 Theoretical arguments

When analysing financing choices of SMEs we first turn to the two cornerstone

theories of explaining leverage the trade-off theory and the pecking order hypothesis (POH)

While the former states that firms may prefer debt to equity in the presence of corporate tax

subject to the costs of potential financial distress stemming from borrowing large amounts

(Modigliani and Miller 1958) the latter suggests that the firms first finance their investment

out of retained earnings as this is the cheapest and the most readily available alternative

then out of debt and lastly via issuing equity which is seen as the most expensive option to

8

the firm (Arnold 2008) More recent literature on firm financing started to look closer at and

emphasize the importance of other sources such as trade credit especially for the small and

medium firms using mostly the data on developed economies For instance Berger amp Udell

(1998) stress the importance of trade credit to the short-term financing of small firms Bevan

and Danbolt (2002) estimate that trade credit account for 62 per cent of total liabilities of UK

firms

The role of trade credit has been seen by some researchers as a substitute of bank

lending for liquidity-constrained firms (Cull 2007) such as SMEs One of the benefits of trade

credit compared to the bank lending is that it allows to partly get around the information

asymmetry problem between the lender and the borrowing SME as business partners would

have more information about the ability of the borrower to repay and about such reputation of

the borrower in the industry Meltzer (1960) Nielsen (2002) and Petersen and Rajan (1997)

argue that trade credit may also provide a means of alternative financing under the tight

monetary conditions such as credit crunches when financial institutions are less able or

willing to provide loans to SMEs In support of this hypothesis Atanasova and Wilson (2003

2004) and Mateut et al (2006) find that under tight monetary conditions firms tend to

substitute bank loans with trade credit However the findings in Bernanke and Gertler (1995)

and Gertler and Gilchrist (1993) do not agree with this hypothesis In line with these authors

Taketa and Udell (2007) using a sample of Japanese SMEs after the crisis years find that

bank lending and trade credit are complements rather than substitutes Love and Zaidi

(2010) report that the use of trade credit by East Asian firms has declined after the 1998

financial crisis together with the use of bank loans Finally interesting enough there is

some empirical evidence which suggests that in the context of transition economies there

may be a higher reliance of SMEs on trade credit in the period of crisis More specifically

focusing on the panel of 1686 firms in Bulgaria Hungary Latvia Lithuania Romania and

Turkey in 2007 and 2009 Klapper and Randall (2010) find that during periods of contractions

in bank credit buyers might depend more on trade credit (although primarily to be used for

short-term financing) that may be particularly true for small firms This provides some support

for the hypothesis that the two sources of finance namely bank loans and trade credit in the

context of transition and emerging economies can be seen as substitutes in period of crisis

Another source of firm financing that has recently received increased attention is

private equity Private equity consists of investments by private individual investors or firms

(business angels investments funds) as well as business ownersrsquo contributions to their

equity The lsquobusiness angelsrsquo type of private equity is currently on the rise in the developed

countries as well as emerging markets such as India Brazil China Malaysia However

ownersrsquo contribution is a far more widespread type of private equity in countries under

consideration Generally SMEs are prone to various types of business and financial risks

9

and it would be very important for them to try and hedge against these risks Zou and Adams

(2008) look at the effect of property insurance on the public firmsrsquo borrowing capacity in

China while Matthews and Scott (1995) in the US and Herbane (2011) in the UK investigate

the types of risk management used by the SMEs The findings point to a rather limited use by

the small and medium-sized enterprises of the risk management assessment and hedging

techniques

In the emerging markets of the post-Soviet bloc the use of risk management techniques

such as hedging with financial derivatives is virtually non-existent However an informal risk

management practice of accumulating cash out of profits and also of using informal lending

from family and friends to serve as a cushion in the times of financial distress as protection

against possible bankruptcy and as an instrument of insurance against risks has been one

way of accounting for the risky nature of SMEs in these countries Secondly many SMEs

sometimes use bankruptcy when they find themselves in the situation of financial distress

and then open a new firm without losing much of their personal assets (Radygin et al 2005)

These SMEs are oftentimes are registered as belonging to a relative or the SMEs could be

registered as founded by an artificially created third party with no links to the actual ownerrsquos

personal assets Recently banks in the new emerging economies such as Russia started a

practice of compulsory purchase of loan insurance if the SME is to take a loan from the bank

This serves as a risk insurance mechanism to a certain extent at the same time however

increasing the cost of bank financing However more recently this practice has attracted the

attention of the Federal Antimonopoly Service that ruled that there is evidence of collusion

between banks and insurance companies Overall we could conclude that the use of risk

management practices is very narrow and of a rather informal nature

The next sub-section explores in greater detail the institutional context of financing in the

situation of economic crisis

Empirical studies on small firm financing in the years of crisis are primarily motivated by

the informational asymmetries theories One of the most important contributions in the study

of the role of SMEs during business cycle has been the real business cycle (RBC) theory

(Bernanke and Gertler 1995 Bernanke Gertler amp Gilchrist 1998) The argument put forward

by the RBC theory is that SMEs face tighter liquidity constraints in terms of external financing

due to higher informational asymmetries associated with their activities the low value of

their assets to serve as collateral the high cost of monitoring small businesses given a small

scale of their investment projects and subsequently the unwillingness of banks to lend to

SMEs

During economic slowdowns when small businesses are even more in need of external

finance bank lending to them diminishes even further which tends to propagate the crisis if

the SMEs then go out of business (see for example Tornell and Westermann 2005) At the

10

same time as larger firms use more finance and tend to rely more on external funding they

may be hit harder by financial contraction in the situation of global crises when international

financial markets dry up so preventing larger firms from drawing upon them when required

They are also less flexible and it is more costly for them to restructure and downsize when

they are hit with external shocks Furthermore while SMEs tend to be more flexible in relying

on other sources of finance including trade credit contributed equity and informal finance

the financial structure of larger firms generally tends to be less diversified with a preference

often given to retained profits and bank finance following the pecking order theory Taken

together we may argue that both supply and demand for finance is more affected for larger

firms in the situation of external shocks

Based on the discussion presented in Sections 2 and 31 we further discuss three main

groups of factors which are likely to affect firmsrsquo perception of financial constraints and their

financing choice strategy These are as follows (1) firm size in general and in the period of

crisis (2) other firm- and industry-specific characteristics including foreign ownership export

orientation firmsrsquo social capital and the degree of competition and its pressure on the firm to

develop a new product and (3) country-level institutional parameters including the degree of

protection of property rights and the development of the financial sector

32 Size of the enterprise and the effect of crisis

With regards to the effect of firm size based on the general discussion in the literature

(see sections 2-31) we expect SMEs to be more financially constrained in their access to

external lending and respectively more reliant on internal funds This is due to insufficient

information that the bank can obtain about a particular SME as well as due to a potentially

lower size of collateral However this lower reliance of SMEs on external debt can potentially

be a source of flexibility during the crisis when formal financial markets dry up and when

even large well-established firms have difficulty obtaining bank credit Furthermore following

Atanasova and Wilson (2003 2004) Mateut et al (2006) and Klapper and Randall (2010) we

expect that under tight monetary conditions SMEs in transition economies are more likely to

switch to alternative forms of financing such as trade credit We also hypothesize that SMEs

are more likely to rely on ownersrsquo contributed equity which they tend to accumulate in good

times as part of their risk management strategy to use it as a cushion in the times of financial

distress In summary we expect the difference between the SMEs and large firms in their

reliance on bank finance to diminish during the crisis years and second SMEs to be more

flexible and rely more on other sources of finance such as trade credit and private equity in

the period of financial contractions

11

33 Firm- and industry- level factors

As far as the firm-level and industry-level variables are concerned we expect the

following results first the level of social capital of a firm as proxied by the inverse of the time

spent dealing with government regulations to indicate possible established connections with

public officials can positively affect its access to trade credit Next the industry-level

pressure on a firm from competitors to develop a new product may increase the firmrsquos

chances of obtaining a bank loan as the bank may perceive the firmrsquos operations as more

diversified and less risky (Isachenkova et al 2011) We also expect foreign competition and

the pressure it exerts on a firm innovation capability to play less important role for firm

financing decisions as SMEs are more likely to operate in market niches and they are

unlikely to compete with multinational enterprises In contrast we expect a pressure

originated from customers on a firm to innovate to increase a firmrsquos probability to rely more

on external sources of funding This may be attributed to the fact that a firm does not only

differentiate itself from other firms further with developing a new product but also assures a

demand for this product by responding to the needs of its existing customers The

guaranteed demand for a new product would be one of the most crucial factors taken into

account by bank managers or potential investors in decision-making concerning project

financing Thirdly international product certification may play a similar role with regards to

bank loans increasing the access to external funds Fourth we investigate the effect on the

choice of financing of the firm age with a square term Generally older firms may have

easier access to bank loans as more information is available about them to the lender (Beck

et al 2006 Canton et al 2010) however due to the particulars of the transition period

sometimes older firms may be less economically viable and unable to get a loan therefore

the sign of this coefficient is uncertain here Lastly we also look at the firmrsquos export

orientation which is expected to increase the reliance on bank lending and its ownership

type where we single out foreign and domestic private firms In the case of foreign firms

they are less likely to use private loans and rely instead on retained earnings and intra-

company funds transfers in the case of MNCs

34 Institutional environment

The impact of institutional variables on the financing choices of firms has been of the

utmost interest to economists and policy-makers during the period of transition (see for

example Stijn and Tzioumis 2006 Mitra et al 2008 see also Commander and Svejnar

(2009) for an in-depth and comprehensive analysis of the impact of various business

environment factors on firm performance using BEEPS 2002 - 2005 panel) In our analysis

12

we concentrate on two institutional factors the degree of protection of property rights and the

size of the formal financial sector which have been claimed to be of key importance for firmsrsquo

financing decisions (see Korosteleva and Mickiewicz (2011) for overview of the related

literature) As far as the property rights protection is concerned it is found to play crucial role

for firm growth and access to external finance (Aidis et al 2008 2010 Korosteleva and

Mickiewicz 2011 Estrin Korosteleva and Mickiewicz 2011) In the environment with weak

protection of property rights financial contracts are less likely to be concluded leading to the

underdevelopment of finance and credit rationing with small firms to be disproportionally

affected the most (Acemoglu and Johnson 2005) Beck et al (2004) show that in terms of

access to external finance small firms benefit disproportionally from higher levels of property

rights protection Lack of secure property rights may also discourage SMEs from taking full

advantage of opportunities to invest (Johnson et al 2002) In a survey of private small

manufacturing firms in Poland Russia Ukraine Romania and Slovakia Johnson et al

(2002) find that small firms tend to reinvest less of their earnings when they perceive their

property rights insecure They also find that the effect of the property rights system is of more

paramount importance for entrepreneursrsquo decisions to reinvest their earnings than availability

of formal finance Moreover if property rights are well-protected this lessens the extent of

potential threat of being expropriated by raidersbank lenders in an artificial bankruptcy

procedure which has been quite a significant issue for firms in Russia and other FSU states

(Radygin et al 2005 Sprenger 2002) Based on this we expect that strong property rights

are likely to encourage SMEs to use more debt as well as to use their own funds and

retained profits for investing in investment projects

With regards to the size of the formal finance as measured by the share of private

credit to GDP the relationship between financial depth and financial constraints has been

extensively studied (Beck et al 2006 also see for example Love 2003 who employing a

sample of 36 countries finds that financial development affects firmsrsquo investment by

increasing the availability of external finance) Financial intermediaries facilitate the risk

amelioration in the presence of problems created by information and transaction frictions by

developing expertise in risk assessment and in monitoring (Levine 1997 Barth et al 2006

Barth et al 2008) Developed financial institutions are found to be particularly beneficial for

small firms compared to large ones (Barth et al 2006 Beck et al 2005 2006 2008)

Pissarides et al (2003) show that financial constraints affect SMEs even more than

deficiency of the property rights protection Accordingly the size of the formal financial

system is expected to be positively related to the use of bank finance as a better functioning

financial system should help ease up borrowing constraints

4 Data and Methodology

13

41 Sample

To explore the determinants of the financial structure of small businesses we use the

2002-2009 Business Environment and Enterprise Performance Survey (BEEPS) data6 of

21867 firms covering 26 transition economies of Europe and Central Asia (ECA)7

The sample is primarily comprised of small and medium-sized businesses8 which

account for 893 per cent of the sample The sample is representative in terms of industrial

coverage with the majority of SMEs of the sample operating in manufacturing wholesale

and retailing industries

BEEPS dataset provides rich information on firm characteristics investment

behaviour and firmsrsquo perception of business environment including financial constraints

which are of a primary interest for our investigation of the effect of the recent financial crisis

on firmsrsquo perception of financial constraints Potentially we could use other micro-level data

characterising various domains of business environment captured by firmsrsquo perceptions for

investigating the effects of the institutional settings However using these micro-level

indicators as explanatory variables would make our study plagued with a problem of

endogeneity To avoid this we merge our firm-level data with country-level indicators

characterising various institutional domains The country level data were obtained from the

World Development Indicators (World Bank) and Polity IV databases (for further discussion

see below) Finally the BEEPs dataset contains other useful information which allows us to

shed light of the effect of for example social capital as proxied by the indirect measure of

possible connections with the authorities (see below for the definition of the variable) on firm

financing

42 Variable Definition and Measurement

Explanatory variables

6 This data is a joint project of the European Bank for Reconstruction and Development and World Bank The first survey was launched in 1999 The dataset used in the present study is an unbalanced panel covering the years of 2002 2005 2007-2009 7 The sample includes the following countries Albania Armenia Azerbaijan Belarus Bosnia Bulgaria Croatia Czech Republic Estonia FYROM Georgia Hungary Kazakhstan Kyrgyzstan Latvia Lithuania Moldova Montenegro Poland Romania Russia Serbia Slovakia Slovenia Tajikistan and Ukraine We exclude Uzbekistan as an outlier from our sample We also exclude Turkey as it is not classified as a post-communist country undertaking transition from a planned to a market economy 8 We utilize the EU employment criterion to define small and medium-sized businesses More specifically businesses are defined as micro if they employ 9 and less employees small ndash between 10 and 49 medium ndash between 50 and 249 and large ndash over 250 employees Respectively SMEs are defined as firms employing less than 249 firms

14

To test our main hypothesis of the effect of a firm size on firmsrsquo perception of financial

constraints we introduce a dummy variable denoting small and medium-sized business

coded as 1 if firms are classified as small or medium-sized businesses according to the EU

definition based on the employment criterion For robustness of our results we also use a

continuous variable denoting a size of employment as measured by the natural logarithm of

employment9 The obtained results are consistent with the ones using the SME indicators

To capture the effect of the recent financial crisis we introduce a crisis dummy coded

as 1 if the year of survey is equal to 2008 or 200910

We also introduce a number of firm-level controls which include age of firm11 type of

ownership including private and foreign ownership export orientation and whether a firm

has an internationally certified product all equal to 1 if a business has a respectively listed

characteristic and zero otherwise We also examine the effect of various sources of pressure

on firms to innovate ndash the indicators which are considered to be important for firm investment

decisions Respectively the pressure for innovation may stem from domestic competition

foreign competition and customers To capture the effect of a firmrsquos social capital we

introduce an indicator which indirectly may capture some possible connections of a firm with

authorities It is proxied by time spent by each firm on dealing with government regulations

We assume the less time firms spend dealing with government regulations the more likely

they have some established connections with public officials which allow them to avoid

burdensome regulation procedures

In our study we also introduce a number of country-level variables which characterize

the institutional environment in the countries covered by our sample More specifically we

include an indicator of the financial development as measured by the ratio of domestic credit

to private sector to GDP (one year lag to avoid potential endogeneity) obtained from the

World Bank World Development Indicators (World Bank 2011) This measure has been used

in previous studies (Klapper et al 2006) and it is expected to be of a primary importance for

transition economies where firms tend to rely more on bank finance rather than capital

markets We also introduce a measure of property rights protection (a one year lag) proxied

by the indicator of effective constraints imposed on the executive branch of the government

and obtained from Polity IV project12 This measure of property rights protection is

9 These results are not reported here to save some space However they can be obtained from authors upon request 10 Here it is important to note that although the financial crisis has started in 2007 in the USA it spread to transition economies in 2008-2009 11 Some studies find a non-monotonic relationship between age and firm decision-making In this study we introduce a squared term of age along with a age variable to capture this possible non-linearity 12 Available from httpwwwsystemicpeaceorgpolitypolity4htm

15

considered to be superior to other indicators including the index of property rights reported

by the Heritage Foundation ndashWall Street Journal (for further discussion see Acemoglu and

Johnson 2005 Glaeser et al 2004 Estrin Korosteleva and Mickieiwcz 2011)

In the present study we also introduce macroeconomic controls including cyclical

economic performance as measured by the one year lag of the GDP annual growth rate

and the level of economic development as proxied by a set of GDP pc dummies denoting

the five quintiles of its distribution to address the problem of potential multicollinearity with the

measure of financial development

Finally we include industry and country controls in all our specifications Introducing

country dummies into analysis allows to control for cross-country heterogeneity

For further definition of all variables their descriptive statistics and correlation matrix

see Tables 1-2

43 Dependent variables

To investigate the effect of a firmrsquos size on its perception of financial constraints we

construct a dummy variable coded as 1 capturing a major and very severe obstacle for

access to finance and 0 otherwise

The firm financing choices are defined by the five individual dependent variables

associated with tobit financial choice equations in the seemingly unrelated regression

equations model

One important thing to mention here is the inability to distinguish between

owninternal funds and external private equity considered as one of the limitations of the

2002-2009 BEEPS dataset In the period under investigation BEEPS offers two questions

which aim to capture the use of equity The first one centres around retained earnings and

the second one shows ownersrsquo contributions and private equity or issued new equity

Following some theoretical considerations discussed in sections 2 and 3 in the context of

SMEs we expect the second element of equity to be primarily comprised of existing ownersrsquo

new contributions rather than private equity

Thus the indicator of financial choices represents a set of five individual dependent

variables including retained earnings contributed earnings private borrowing informal

finance trade credit with each of them constructed as a share in total financing of SMErsquos

investment decisions (see Table 1)

44 Methods

16

In this study we employ a number of estimators to obtain robust results More

specifically we use a probit model to investigate the effect of a firm size and the recent

financial crisis on firmsrsquo perception of financial constraints The effect of a firm size in the

situation of crisis is captured by the introduction of the interaction term between firm size as

proxied by the SME indicator and a financial crisis dummy

We further employ the seemingly unrelated regression equations model combined

with the tobit approach for studying firmsrsquo financial structure

Probit model of perception of financial constraints

In the probit model the probability of a firmrsquos perception of financial constraints as

major(j = 1) can be written as follows

( ) ( )int ++

++

infinminus

minus===

ijitj uXjitiitit ijitjuXjy uX

βα βαππ 212-

)()(2 21exp|Pr

Where ity is our measure of financial constraints as perceived by firms and itX is a

set of our explanatory variables discussed in detail in sections 3-4 Here it is important to

note that the interaction term in a probit model cannot be interpreted in a similar way as in

linear models and disregarding this may lead to misleading estimates of the interaction

effect which is of crucial importance for our study (Norton Wang and Ai 2004) Respectively

for robustness of our results here we follow the framework suggested by Norton Wang and

Ai (2004) to account for the model nonlinearity The adjusted marginal effects for the

interaction term are reported in the note to Table 313

Simultaneous Model of Financing Choices

As mentioned above we next model the choice of all five financing choices explicitly

We also hypothesise (following Isachenkova et al 2011) that firm financing choices are likely

to be determined jointly A standard way of modelling jointly determined indicators is a

system of equations - SURE ndash seemingly unrelated regression equations where equations

are linked only by their errors (Zellner 1962) We therefore model the five types of sources of

finance (internal funds private bank borrowing informal finance trade credit and private

13 We also run a probit regression for a split sample of (1) SMEs and (2) large firms to check the robustness of our results (based on the interaction term) while addressing a problem of multicollinearity between a crisis variable and its interaction term with a SME variable The correlation coefficient between a crisis variable and its interaction term with a SME variable is equal to 93 This can be attributed by the problem of a sample being overrepresented by SMEs which constitute 90 of all surveyed firms The results remain robust and can be available from authors upon request

17

equity) using a SURE framework within which we specify a set of five tobit regressions with

correlated residuals

We employ the STATA cmp module which allows to it Seemingly Unrelated Regressions

using the simulated likelihood method such as the Geweke Hajivassiliou and Keane (GHK)

algorithm (for further discussion see Roodman 2008) We utilise a tobit equation to model

each individual financial choice of firms because our dependent financing choices variables

are continuous but their range is constrained (censored) with a substantial number of

observations either equal to zero denoting those who do not use the respective source of

finance or to 100 showing the opposite Other observations are positive and may produce

many different outcomes (Verbeek 2000) Each tobit equation uses a set of identical

explanatory variables that proxy factors which could possibly be associated with firmrsquos

financing choices including industry and country dummies

We also considered the bias caused by potential interdependence between the choice of

whether to invest and firmrsquos financing choices We accounted for the potential selection bias

by introducing into the financial choices SURE Tobit equations (second stage outcome

equations14) the inverse Millrsquos ratio calculated based on modelling the choice to invest in

fixed assets (first stage or selection equation) To identify the first stage of the Heckman

selection model we chose a variable which is correlated with the first stage dependent

variable (investment decision) but not with the second ones (financing choices) We used the

rate of capacity utilization as part of our identification strategy Capacity utilization shows the

percentage of capital stock in use the higher is the rate the more likely firms will increase

investment Batyaeva and Aukutsionek (2001) show that the rate of capacity utilization is

higher in the group of investing firms than in the group of non-investing firms in Russia15 We

calculated the inverse Millrsquos ratio based on the above selection equation16 and included it as

a control in the second stage SURE Tobit equations The inverse Millrsquos ratio has only proved

to be statistically significant in the private bank loan equation pointing to the potential

selection bias arising from the possibility that the factors determining the decision to invest

might differ from those determining the use of bank financing in purchasing fixed assets

14 We also attempted to estimate an investment equation jointly with Tobit financial choices equations within the SURE framework using However given the overall complexity of the model we failed to do this We proceeded further with a two-stage approach by estimating an investment probit equation and calculating the inverse Millrsquos ratio that we add into the outcome financial choices equations at the second stage of the analysis to test for the selection bias 15 We performed an independent sample t-test to check whether the rate of capacity utilization is statistically significantly higher for investing firms compared to non-investing firms for our sample The null hypothesis of no difference was rejected at 1 level of significance 16 To economize on space we do not report the results of the investment probit equation but they are available from authorsrsquo upon request

18

Finally In Table 6 we attempt to condition the determinants of financing constraints

declared by SMEs on the relative percentage increase of trade credit in total funds used for

real investment As mentioned above in Section 2 the timings of measuring the composition

of financing sources precede by a year the timings of measuring the perceptions of financing

constraints That feature of the BEEPSrsquo design allays a likely concern about the endogeneity

of the relative proportion of trade credit and enables causal inference We too report in thre

note to Table 4 the adjusted marginal effects for the interaction term of the SME dummy with

the trade credit variable

In the next section we discuss our empirical results

5 Empirical Results

Table 3 reports the results of the probit model with the marginal effects for firmsrsquo

perception of financial constraints while Tables 4-5 summarize the results of SURE tobits for

a more detailed breakdown of five financing choices More specifically Table 4 reports the

results based on the whole sample to give a comparative perspective on SMErsquos financing

strategy vis-a-vis large businesses whereas Table 5 reports the results based on a

subsample of small and medium-sized firms to shed some light on their financing choices in

the period of crisis

Perception of financial constraints

Table 3 shows that generally small and medium-sized enterprises feel more financially

constrained with the coefficient for SME dummy in relation to the large firms being positive

and significant which is consistent with our discussion in sections 2-3 However the

coefficient of the interaction term with the Crisis dummy turns out to be negative and

significant in relation to the perception of financial constraints as a major obstacle and it

tends to outweigh the effect of a SME dummy when we calculate marginal effects The effect

of the interaction terms with the crisis remains robust after we adjust for non-linearity using

the framework proposed by Norton Wang and Ai (2004)17 Overall these results confirm

that small and medium-sized enterprises are much less financially constrained during the

crisis years with their perceptions close to those of the large firms This result is a polar

opposite to that obtained for the SMEs in the UK (Fraser 2009) which finds that not only do

SMEs generally feel more financially constrained but they report to be even more so during

17 We also check the robustness of our results to the potential problem of multicollinearity between a crisis dummy and its interaction term with SME by splitting a sample and testing the same specification separately for SMEs and large firms We also perform another robustness check by breaking a SME dummy into three subsequent dummies namely micro- small- and medium-sized firms The difference in perception of financial constraints gets almost eliminated in the case of small firms and is largely reduced in the case of micro firms whereas it is less so for medium-sized firms

19

the last crisis We could explain this striking difference by the peculiarities of the SMEs

functioning in new emerging economies The lower reliance of SMEs on external debt in

good times (as shown by results which are discussed below) gives SMEs some flexibility

during the crisis when formal financial markets dry up Jointly with overall flexibility to make

necessary cost cuts and to restructure a business this overall lower reliance on external

funding and the use of alternative sources of financing makes SMEs feel less financially

constrained under the crisis as compared to larger firms

We also find that a more developed financial sector as proxied by domestic private

credit as proportion of GDP helps ease up financial constraints This is in line with the

general literature suggesting that better functioning financial intermediaries facilitate the risk

amelioration in the presence of problems created by market frictions (Levine 1997 Barth et

al 2006 Barth et al 2008)

Unfortunately we fail to find any significant effect of the property rights protection on

firmsrsquo perception of financial constraints that may be explained by the fact that the effect of a

more developed financial sector is likely to outweigh the effect of the property rights

protection

Finally we also find that foreign ownership and international product certificate may

reduce firmsrsquo borrowing constraints while any pressure from domestic or foreign competition

so is pressure from the customers to innovate will increase firmrsquos perception of financial

constraints as major given that firms envisage the need to secure external funding for RampD

or any other innovation-related activities

Financing choices for investment in fixed assets

The results in Table 4 indicate that small enterprises tend to rely more on internal funds

and less on bank loans but they are no different from larger firms in respect of using informal

funds trade credit or private equity which is generally consistent with our discussion in

Sections 2 and 3 The results of Table 5 suggest however that under crisis small and

medium-sized firms tend to switch to other sources of finance such as trade credit and

ownerrsquos contributed equity and to respectively reduce the reliance on retained earnings

perhaps because they decrease due to the negative impact of crisis internal funds With

regards to our discussion of SMEsrsquo risk management we note that the use of private equity

(ownerrsquos contribution) during the crisis years increases which could indicate that the ownerrsquos

funds are used as a cushion in the period of financial distress

An interesting insight regarding the use of trade credit emerges for SMEs in our

sample although in non-crisis years small and medium-sized businesses are not significantly

different from larger firms in terms of reliance on trade credit SMEs tend to finance a

significantly higher proportion of their fixed asset investment by trade credit than large firms

20

in the period of crisis While the latter finding is partly in line with some other studies ndash such

as Klapper and Randall (2010) using BEEPS data it is in stark contrast with similar studies

of the UK private firms (Rehman 2011) for which the use of trade credit is found to have

dried up in crisis This could partly be due to the passed legislation in the UK tightening trade

credit regulation as the result of the abuse of trade credit by large firms in relation to small

firms which forced many SMEs out of the market

With regards to the other firm-level characteristics international certification makes the

firm rely more on private bank loans and informal finance (Table 5) while SMEs with foreign

ownership rely less on private debt but more on retained earnings Both results are

consistent with our hypotheses discussed above Export-oriented small and medium-sized

businesses tend to have greater reliance on trade credit and they use less of internal funds

We find a non-monotonic relationship between age and private equity with both younger and

older firms being more reliant on this source of funding We find some fragmentary support

for private domestic SMEs relying more on informal finance while tending to use less trade

credit and private equity (Table 5)

Interestingly our results (Tables 4-5) suggest that firms which lack some social

connections with governmental officials proxied by the higher amount of time spent dealing

with government regulations are more likely to rely on informal finance trade credit and

private equity In turn businesses which are connected to governmental officials use more

retained profits to fund investment in fixed assets This may be attributed to their connections

serving as a guarantee from expropriation of assets by all sort of rent-seeking individuals

akin private contracting to secure property rights protection This result should be interpreted

jointly with the property rights protection results We expected that better property rights

protection is likely to facilitate firmsrsquo access to bank loan but we failed to confirm this

Perhaps regardless some attempts at a constitutional level to prevent arbitrary government

(which is proxied by our measure of property rights) expropriation culture is still deeply

embedded in the society of post-communist countries and it may manifest in different ways

Welter and Smallbone (2011) argue that entrepreneurs in transition economies have learnt

how to respond to institutional deficiencies in particular weak property rights protection For

example some businesses experiencing high growth choose to invest in unrelated

businesses instead of growing their core businesses for the reason they do not want to

become too noticeable to attract too much attention of the wrong sort In our instance having

some connections with officials seems also to serve as protection against arbitrary

government or individual rent-seeking that makes businesses more keen on re-investing their

retained profits (see Johnson et al (2002) on the discussion of how more secure property

rights can make small firms reinvest more of their earnings)

7

According to Cull (2007) trade credit can be seen as substitute for loans for private firmsrsquo

trading partners that are shut out of financial credit market Other sources include borrowing

from informal money lenders and family and these emerge as the third important source of

funding SMEsrsquo investment after internal funds and bank credit We expect the informal

finance to be mostly comprised of equity provided by family and friends as funding obtained

from informal private money lenders was overly expensive with the premium standing at least

20 percentage points above that charged by local intermediaries (Pissarides 1998)

Figure 4 to be inserted here

In conclusion we note that the number of studies of the financing decisions of small

and medium-sized enterprises in emerging markets and in particular in the former centrally

planned economies or previously heavily regulated economies such as India has been rather

limited (see eg Nivorozhkin 2005 Delcoure 2007 Crnigoj 2007 Chakraborty 2008

Girma et al 2008 Li et al 2009 Correa et al 2010 Love and Zaidi 2010) We contribute to

this literature by analysing for SMEs in these countries the determinants of the following five

financing options retained earnings private loan (loan finance from private banks) trade

credit private equity (ownersrsquo equity) and informal finance In this study the phrase lsquoinformal

financersquo is an umbrella term that helps condense in one category funds from moneylenders

friends relatives non-banking financial institutions Our results allow us to shed more light

on whether and how the theories of financing choices apply to transition countries in the

credit crunch environment

The following section discusses theories pertaining to small firm financing and how this

may be affected by a financial crisis

3 Small Firm Financing and the Effect of Crisis Theoretical Considerations and

Hypotheses

31 Theoretical arguments

When analysing financing choices of SMEs we first turn to the two cornerstone

theories of explaining leverage the trade-off theory and the pecking order hypothesis (POH)

While the former states that firms may prefer debt to equity in the presence of corporate tax

subject to the costs of potential financial distress stemming from borrowing large amounts

(Modigliani and Miller 1958) the latter suggests that the firms first finance their investment

out of retained earnings as this is the cheapest and the most readily available alternative

then out of debt and lastly via issuing equity which is seen as the most expensive option to

8

the firm (Arnold 2008) More recent literature on firm financing started to look closer at and

emphasize the importance of other sources such as trade credit especially for the small and

medium firms using mostly the data on developed economies For instance Berger amp Udell

(1998) stress the importance of trade credit to the short-term financing of small firms Bevan

and Danbolt (2002) estimate that trade credit account for 62 per cent of total liabilities of UK

firms

The role of trade credit has been seen by some researchers as a substitute of bank

lending for liquidity-constrained firms (Cull 2007) such as SMEs One of the benefits of trade

credit compared to the bank lending is that it allows to partly get around the information

asymmetry problem between the lender and the borrowing SME as business partners would

have more information about the ability of the borrower to repay and about such reputation of

the borrower in the industry Meltzer (1960) Nielsen (2002) and Petersen and Rajan (1997)

argue that trade credit may also provide a means of alternative financing under the tight

monetary conditions such as credit crunches when financial institutions are less able or

willing to provide loans to SMEs In support of this hypothesis Atanasova and Wilson (2003

2004) and Mateut et al (2006) find that under tight monetary conditions firms tend to

substitute bank loans with trade credit However the findings in Bernanke and Gertler (1995)

and Gertler and Gilchrist (1993) do not agree with this hypothesis In line with these authors

Taketa and Udell (2007) using a sample of Japanese SMEs after the crisis years find that

bank lending and trade credit are complements rather than substitutes Love and Zaidi

(2010) report that the use of trade credit by East Asian firms has declined after the 1998

financial crisis together with the use of bank loans Finally interesting enough there is

some empirical evidence which suggests that in the context of transition economies there

may be a higher reliance of SMEs on trade credit in the period of crisis More specifically

focusing on the panel of 1686 firms in Bulgaria Hungary Latvia Lithuania Romania and

Turkey in 2007 and 2009 Klapper and Randall (2010) find that during periods of contractions

in bank credit buyers might depend more on trade credit (although primarily to be used for

short-term financing) that may be particularly true for small firms This provides some support

for the hypothesis that the two sources of finance namely bank loans and trade credit in the

context of transition and emerging economies can be seen as substitutes in period of crisis

Another source of firm financing that has recently received increased attention is

private equity Private equity consists of investments by private individual investors or firms

(business angels investments funds) as well as business ownersrsquo contributions to their

equity The lsquobusiness angelsrsquo type of private equity is currently on the rise in the developed

countries as well as emerging markets such as India Brazil China Malaysia However

ownersrsquo contribution is a far more widespread type of private equity in countries under

consideration Generally SMEs are prone to various types of business and financial risks

9

and it would be very important for them to try and hedge against these risks Zou and Adams

(2008) look at the effect of property insurance on the public firmsrsquo borrowing capacity in

China while Matthews and Scott (1995) in the US and Herbane (2011) in the UK investigate

the types of risk management used by the SMEs The findings point to a rather limited use by

the small and medium-sized enterprises of the risk management assessment and hedging

techniques

In the emerging markets of the post-Soviet bloc the use of risk management techniques

such as hedging with financial derivatives is virtually non-existent However an informal risk

management practice of accumulating cash out of profits and also of using informal lending

from family and friends to serve as a cushion in the times of financial distress as protection

against possible bankruptcy and as an instrument of insurance against risks has been one

way of accounting for the risky nature of SMEs in these countries Secondly many SMEs

sometimes use bankruptcy when they find themselves in the situation of financial distress

and then open a new firm without losing much of their personal assets (Radygin et al 2005)

These SMEs are oftentimes are registered as belonging to a relative or the SMEs could be

registered as founded by an artificially created third party with no links to the actual ownerrsquos

personal assets Recently banks in the new emerging economies such as Russia started a

practice of compulsory purchase of loan insurance if the SME is to take a loan from the bank

This serves as a risk insurance mechanism to a certain extent at the same time however

increasing the cost of bank financing However more recently this practice has attracted the

attention of the Federal Antimonopoly Service that ruled that there is evidence of collusion

between banks and insurance companies Overall we could conclude that the use of risk

management practices is very narrow and of a rather informal nature

The next sub-section explores in greater detail the institutional context of financing in the

situation of economic crisis

Empirical studies on small firm financing in the years of crisis are primarily motivated by

the informational asymmetries theories One of the most important contributions in the study

of the role of SMEs during business cycle has been the real business cycle (RBC) theory

(Bernanke and Gertler 1995 Bernanke Gertler amp Gilchrist 1998) The argument put forward

by the RBC theory is that SMEs face tighter liquidity constraints in terms of external financing

due to higher informational asymmetries associated with their activities the low value of

their assets to serve as collateral the high cost of monitoring small businesses given a small

scale of their investment projects and subsequently the unwillingness of banks to lend to

SMEs

During economic slowdowns when small businesses are even more in need of external

finance bank lending to them diminishes even further which tends to propagate the crisis if

the SMEs then go out of business (see for example Tornell and Westermann 2005) At the

10

same time as larger firms use more finance and tend to rely more on external funding they

may be hit harder by financial contraction in the situation of global crises when international

financial markets dry up so preventing larger firms from drawing upon them when required

They are also less flexible and it is more costly for them to restructure and downsize when

they are hit with external shocks Furthermore while SMEs tend to be more flexible in relying

on other sources of finance including trade credit contributed equity and informal finance

the financial structure of larger firms generally tends to be less diversified with a preference

often given to retained profits and bank finance following the pecking order theory Taken

together we may argue that both supply and demand for finance is more affected for larger

firms in the situation of external shocks

Based on the discussion presented in Sections 2 and 31 we further discuss three main

groups of factors which are likely to affect firmsrsquo perception of financial constraints and their

financing choice strategy These are as follows (1) firm size in general and in the period of

crisis (2) other firm- and industry-specific characteristics including foreign ownership export

orientation firmsrsquo social capital and the degree of competition and its pressure on the firm to

develop a new product and (3) country-level institutional parameters including the degree of

protection of property rights and the development of the financial sector

32 Size of the enterprise and the effect of crisis

With regards to the effect of firm size based on the general discussion in the literature

(see sections 2-31) we expect SMEs to be more financially constrained in their access to

external lending and respectively more reliant on internal funds This is due to insufficient

information that the bank can obtain about a particular SME as well as due to a potentially

lower size of collateral However this lower reliance of SMEs on external debt can potentially

be a source of flexibility during the crisis when formal financial markets dry up and when

even large well-established firms have difficulty obtaining bank credit Furthermore following

Atanasova and Wilson (2003 2004) Mateut et al (2006) and Klapper and Randall (2010) we

expect that under tight monetary conditions SMEs in transition economies are more likely to

switch to alternative forms of financing such as trade credit We also hypothesize that SMEs

are more likely to rely on ownersrsquo contributed equity which they tend to accumulate in good

times as part of their risk management strategy to use it as a cushion in the times of financial

distress In summary we expect the difference between the SMEs and large firms in their

reliance on bank finance to diminish during the crisis years and second SMEs to be more

flexible and rely more on other sources of finance such as trade credit and private equity in

the period of financial contractions

11

33 Firm- and industry- level factors

As far as the firm-level and industry-level variables are concerned we expect the

following results first the level of social capital of a firm as proxied by the inverse of the time

spent dealing with government regulations to indicate possible established connections with

public officials can positively affect its access to trade credit Next the industry-level

pressure on a firm from competitors to develop a new product may increase the firmrsquos

chances of obtaining a bank loan as the bank may perceive the firmrsquos operations as more

diversified and less risky (Isachenkova et al 2011) We also expect foreign competition and

the pressure it exerts on a firm innovation capability to play less important role for firm

financing decisions as SMEs are more likely to operate in market niches and they are

unlikely to compete with multinational enterprises In contrast we expect a pressure

originated from customers on a firm to innovate to increase a firmrsquos probability to rely more

on external sources of funding This may be attributed to the fact that a firm does not only

differentiate itself from other firms further with developing a new product but also assures a

demand for this product by responding to the needs of its existing customers The

guaranteed demand for a new product would be one of the most crucial factors taken into

account by bank managers or potential investors in decision-making concerning project

financing Thirdly international product certification may play a similar role with regards to

bank loans increasing the access to external funds Fourth we investigate the effect on the

choice of financing of the firm age with a square term Generally older firms may have

easier access to bank loans as more information is available about them to the lender (Beck

et al 2006 Canton et al 2010) however due to the particulars of the transition period

sometimes older firms may be less economically viable and unable to get a loan therefore

the sign of this coefficient is uncertain here Lastly we also look at the firmrsquos export

orientation which is expected to increase the reliance on bank lending and its ownership

type where we single out foreign and domestic private firms In the case of foreign firms

they are less likely to use private loans and rely instead on retained earnings and intra-

company funds transfers in the case of MNCs

34 Institutional environment

The impact of institutional variables on the financing choices of firms has been of the

utmost interest to economists and policy-makers during the period of transition (see for

example Stijn and Tzioumis 2006 Mitra et al 2008 see also Commander and Svejnar

(2009) for an in-depth and comprehensive analysis of the impact of various business

environment factors on firm performance using BEEPS 2002 - 2005 panel) In our analysis

12

we concentrate on two institutional factors the degree of protection of property rights and the

size of the formal financial sector which have been claimed to be of key importance for firmsrsquo

financing decisions (see Korosteleva and Mickiewicz (2011) for overview of the related

literature) As far as the property rights protection is concerned it is found to play crucial role

for firm growth and access to external finance (Aidis et al 2008 2010 Korosteleva and

Mickiewicz 2011 Estrin Korosteleva and Mickiewicz 2011) In the environment with weak

protection of property rights financial contracts are less likely to be concluded leading to the

underdevelopment of finance and credit rationing with small firms to be disproportionally

affected the most (Acemoglu and Johnson 2005) Beck et al (2004) show that in terms of

access to external finance small firms benefit disproportionally from higher levels of property

rights protection Lack of secure property rights may also discourage SMEs from taking full

advantage of opportunities to invest (Johnson et al 2002) In a survey of private small

manufacturing firms in Poland Russia Ukraine Romania and Slovakia Johnson et al

(2002) find that small firms tend to reinvest less of their earnings when they perceive their

property rights insecure They also find that the effect of the property rights system is of more

paramount importance for entrepreneursrsquo decisions to reinvest their earnings than availability

of formal finance Moreover if property rights are well-protected this lessens the extent of

potential threat of being expropriated by raidersbank lenders in an artificial bankruptcy

procedure which has been quite a significant issue for firms in Russia and other FSU states

(Radygin et al 2005 Sprenger 2002) Based on this we expect that strong property rights

are likely to encourage SMEs to use more debt as well as to use their own funds and

retained profits for investing in investment projects

With regards to the size of the formal finance as measured by the share of private

credit to GDP the relationship between financial depth and financial constraints has been

extensively studied (Beck et al 2006 also see for example Love 2003 who employing a

sample of 36 countries finds that financial development affects firmsrsquo investment by

increasing the availability of external finance) Financial intermediaries facilitate the risk

amelioration in the presence of problems created by information and transaction frictions by

developing expertise in risk assessment and in monitoring (Levine 1997 Barth et al 2006

Barth et al 2008) Developed financial institutions are found to be particularly beneficial for

small firms compared to large ones (Barth et al 2006 Beck et al 2005 2006 2008)

Pissarides et al (2003) show that financial constraints affect SMEs even more than

deficiency of the property rights protection Accordingly the size of the formal financial

system is expected to be positively related to the use of bank finance as a better functioning

financial system should help ease up borrowing constraints

4 Data and Methodology

13

41 Sample

To explore the determinants of the financial structure of small businesses we use the

2002-2009 Business Environment and Enterprise Performance Survey (BEEPS) data6 of

21867 firms covering 26 transition economies of Europe and Central Asia (ECA)7

The sample is primarily comprised of small and medium-sized businesses8 which

account for 893 per cent of the sample The sample is representative in terms of industrial

coverage with the majority of SMEs of the sample operating in manufacturing wholesale

and retailing industries

BEEPS dataset provides rich information on firm characteristics investment

behaviour and firmsrsquo perception of business environment including financial constraints

which are of a primary interest for our investigation of the effect of the recent financial crisis

on firmsrsquo perception of financial constraints Potentially we could use other micro-level data

characterising various domains of business environment captured by firmsrsquo perceptions for

investigating the effects of the institutional settings However using these micro-level

indicators as explanatory variables would make our study plagued with a problem of

endogeneity To avoid this we merge our firm-level data with country-level indicators

characterising various institutional domains The country level data were obtained from the

World Development Indicators (World Bank) and Polity IV databases (for further discussion

see below) Finally the BEEPs dataset contains other useful information which allows us to

shed light of the effect of for example social capital as proxied by the indirect measure of

possible connections with the authorities (see below for the definition of the variable) on firm

financing

42 Variable Definition and Measurement

Explanatory variables

6 This data is a joint project of the European Bank for Reconstruction and Development and World Bank The first survey was launched in 1999 The dataset used in the present study is an unbalanced panel covering the years of 2002 2005 2007-2009 7 The sample includes the following countries Albania Armenia Azerbaijan Belarus Bosnia Bulgaria Croatia Czech Republic Estonia FYROM Georgia Hungary Kazakhstan Kyrgyzstan Latvia Lithuania Moldova Montenegro Poland Romania Russia Serbia Slovakia Slovenia Tajikistan and Ukraine We exclude Uzbekistan as an outlier from our sample We also exclude Turkey as it is not classified as a post-communist country undertaking transition from a planned to a market economy 8 We utilize the EU employment criterion to define small and medium-sized businesses More specifically businesses are defined as micro if they employ 9 and less employees small ndash between 10 and 49 medium ndash between 50 and 249 and large ndash over 250 employees Respectively SMEs are defined as firms employing less than 249 firms

14

To test our main hypothesis of the effect of a firm size on firmsrsquo perception of financial

constraints we introduce a dummy variable denoting small and medium-sized business

coded as 1 if firms are classified as small or medium-sized businesses according to the EU

definition based on the employment criterion For robustness of our results we also use a

continuous variable denoting a size of employment as measured by the natural logarithm of

employment9 The obtained results are consistent with the ones using the SME indicators

To capture the effect of the recent financial crisis we introduce a crisis dummy coded

as 1 if the year of survey is equal to 2008 or 200910

We also introduce a number of firm-level controls which include age of firm11 type of

ownership including private and foreign ownership export orientation and whether a firm

has an internationally certified product all equal to 1 if a business has a respectively listed

characteristic and zero otherwise We also examine the effect of various sources of pressure

on firms to innovate ndash the indicators which are considered to be important for firm investment

decisions Respectively the pressure for innovation may stem from domestic competition

foreign competition and customers To capture the effect of a firmrsquos social capital we

introduce an indicator which indirectly may capture some possible connections of a firm with

authorities It is proxied by time spent by each firm on dealing with government regulations

We assume the less time firms spend dealing with government regulations the more likely

they have some established connections with public officials which allow them to avoid

burdensome regulation procedures

In our study we also introduce a number of country-level variables which characterize

the institutional environment in the countries covered by our sample More specifically we

include an indicator of the financial development as measured by the ratio of domestic credit

to private sector to GDP (one year lag to avoid potential endogeneity) obtained from the

World Bank World Development Indicators (World Bank 2011) This measure has been used

in previous studies (Klapper et al 2006) and it is expected to be of a primary importance for

transition economies where firms tend to rely more on bank finance rather than capital

markets We also introduce a measure of property rights protection (a one year lag) proxied

by the indicator of effective constraints imposed on the executive branch of the government

and obtained from Polity IV project12 This measure of property rights protection is

9 These results are not reported here to save some space However they can be obtained from authors upon request 10 Here it is important to note that although the financial crisis has started in 2007 in the USA it spread to transition economies in 2008-2009 11 Some studies find a non-monotonic relationship between age and firm decision-making In this study we introduce a squared term of age along with a age variable to capture this possible non-linearity 12 Available from httpwwwsystemicpeaceorgpolitypolity4htm

15

considered to be superior to other indicators including the index of property rights reported

by the Heritage Foundation ndashWall Street Journal (for further discussion see Acemoglu and

Johnson 2005 Glaeser et al 2004 Estrin Korosteleva and Mickieiwcz 2011)

In the present study we also introduce macroeconomic controls including cyclical

economic performance as measured by the one year lag of the GDP annual growth rate

and the level of economic development as proxied by a set of GDP pc dummies denoting

the five quintiles of its distribution to address the problem of potential multicollinearity with the

measure of financial development

Finally we include industry and country controls in all our specifications Introducing

country dummies into analysis allows to control for cross-country heterogeneity

For further definition of all variables their descriptive statistics and correlation matrix

see Tables 1-2

43 Dependent variables

To investigate the effect of a firmrsquos size on its perception of financial constraints we

construct a dummy variable coded as 1 capturing a major and very severe obstacle for

access to finance and 0 otherwise

The firm financing choices are defined by the five individual dependent variables

associated with tobit financial choice equations in the seemingly unrelated regression

equations model

One important thing to mention here is the inability to distinguish between

owninternal funds and external private equity considered as one of the limitations of the

2002-2009 BEEPS dataset In the period under investigation BEEPS offers two questions

which aim to capture the use of equity The first one centres around retained earnings and

the second one shows ownersrsquo contributions and private equity or issued new equity

Following some theoretical considerations discussed in sections 2 and 3 in the context of

SMEs we expect the second element of equity to be primarily comprised of existing ownersrsquo

new contributions rather than private equity

Thus the indicator of financial choices represents a set of five individual dependent

variables including retained earnings contributed earnings private borrowing informal

finance trade credit with each of them constructed as a share in total financing of SMErsquos

investment decisions (see Table 1)

44 Methods

16

In this study we employ a number of estimators to obtain robust results More

specifically we use a probit model to investigate the effect of a firm size and the recent

financial crisis on firmsrsquo perception of financial constraints The effect of a firm size in the

situation of crisis is captured by the introduction of the interaction term between firm size as

proxied by the SME indicator and a financial crisis dummy

We further employ the seemingly unrelated regression equations model combined

with the tobit approach for studying firmsrsquo financial structure

Probit model of perception of financial constraints

In the probit model the probability of a firmrsquos perception of financial constraints as

major(j = 1) can be written as follows

( ) ( )int ++

++

infinminus

minus===

ijitj uXjitiitit ijitjuXjy uX

βα βαππ 212-

)()(2 21exp|Pr

Where ity is our measure of financial constraints as perceived by firms and itX is a

set of our explanatory variables discussed in detail in sections 3-4 Here it is important to

note that the interaction term in a probit model cannot be interpreted in a similar way as in

linear models and disregarding this may lead to misleading estimates of the interaction

effect which is of crucial importance for our study (Norton Wang and Ai 2004) Respectively

for robustness of our results here we follow the framework suggested by Norton Wang and

Ai (2004) to account for the model nonlinearity The adjusted marginal effects for the

interaction term are reported in the note to Table 313

Simultaneous Model of Financing Choices

As mentioned above we next model the choice of all five financing choices explicitly

We also hypothesise (following Isachenkova et al 2011) that firm financing choices are likely

to be determined jointly A standard way of modelling jointly determined indicators is a

system of equations - SURE ndash seemingly unrelated regression equations where equations

are linked only by their errors (Zellner 1962) We therefore model the five types of sources of

finance (internal funds private bank borrowing informal finance trade credit and private

13 We also run a probit regression for a split sample of (1) SMEs and (2) large firms to check the robustness of our results (based on the interaction term) while addressing a problem of multicollinearity between a crisis variable and its interaction term with a SME variable The correlation coefficient between a crisis variable and its interaction term with a SME variable is equal to 93 This can be attributed by the problem of a sample being overrepresented by SMEs which constitute 90 of all surveyed firms The results remain robust and can be available from authors upon request

17

equity) using a SURE framework within which we specify a set of five tobit regressions with

correlated residuals

We employ the STATA cmp module which allows to it Seemingly Unrelated Regressions

using the simulated likelihood method such as the Geweke Hajivassiliou and Keane (GHK)

algorithm (for further discussion see Roodman 2008) We utilise a tobit equation to model

each individual financial choice of firms because our dependent financing choices variables

are continuous but their range is constrained (censored) with a substantial number of

observations either equal to zero denoting those who do not use the respective source of

finance or to 100 showing the opposite Other observations are positive and may produce

many different outcomes (Verbeek 2000) Each tobit equation uses a set of identical

explanatory variables that proxy factors which could possibly be associated with firmrsquos

financing choices including industry and country dummies

We also considered the bias caused by potential interdependence between the choice of

whether to invest and firmrsquos financing choices We accounted for the potential selection bias

by introducing into the financial choices SURE Tobit equations (second stage outcome

equations14) the inverse Millrsquos ratio calculated based on modelling the choice to invest in

fixed assets (first stage or selection equation) To identify the first stage of the Heckman

selection model we chose a variable which is correlated with the first stage dependent

variable (investment decision) but not with the second ones (financing choices) We used the

rate of capacity utilization as part of our identification strategy Capacity utilization shows the

percentage of capital stock in use the higher is the rate the more likely firms will increase

investment Batyaeva and Aukutsionek (2001) show that the rate of capacity utilization is

higher in the group of investing firms than in the group of non-investing firms in Russia15 We

calculated the inverse Millrsquos ratio based on the above selection equation16 and included it as

a control in the second stage SURE Tobit equations The inverse Millrsquos ratio has only proved

to be statistically significant in the private bank loan equation pointing to the potential

selection bias arising from the possibility that the factors determining the decision to invest

might differ from those determining the use of bank financing in purchasing fixed assets

14 We also attempted to estimate an investment equation jointly with Tobit financial choices equations within the SURE framework using However given the overall complexity of the model we failed to do this We proceeded further with a two-stage approach by estimating an investment probit equation and calculating the inverse Millrsquos ratio that we add into the outcome financial choices equations at the second stage of the analysis to test for the selection bias 15 We performed an independent sample t-test to check whether the rate of capacity utilization is statistically significantly higher for investing firms compared to non-investing firms for our sample The null hypothesis of no difference was rejected at 1 level of significance 16 To economize on space we do not report the results of the investment probit equation but they are available from authorsrsquo upon request

18

Finally In Table 6 we attempt to condition the determinants of financing constraints

declared by SMEs on the relative percentage increase of trade credit in total funds used for

real investment As mentioned above in Section 2 the timings of measuring the composition

of financing sources precede by a year the timings of measuring the perceptions of financing

constraints That feature of the BEEPSrsquo design allays a likely concern about the endogeneity

of the relative proportion of trade credit and enables causal inference We too report in thre

note to Table 4 the adjusted marginal effects for the interaction term of the SME dummy with

the trade credit variable

In the next section we discuss our empirical results

5 Empirical Results

Table 3 reports the results of the probit model with the marginal effects for firmsrsquo

perception of financial constraints while Tables 4-5 summarize the results of SURE tobits for

a more detailed breakdown of five financing choices More specifically Table 4 reports the

results based on the whole sample to give a comparative perspective on SMErsquos financing

strategy vis-a-vis large businesses whereas Table 5 reports the results based on a

subsample of small and medium-sized firms to shed some light on their financing choices in

the period of crisis

Perception of financial constraints

Table 3 shows that generally small and medium-sized enterprises feel more financially

constrained with the coefficient for SME dummy in relation to the large firms being positive

and significant which is consistent with our discussion in sections 2-3 However the

coefficient of the interaction term with the Crisis dummy turns out to be negative and

significant in relation to the perception of financial constraints as a major obstacle and it

tends to outweigh the effect of a SME dummy when we calculate marginal effects The effect

of the interaction terms with the crisis remains robust after we adjust for non-linearity using

the framework proposed by Norton Wang and Ai (2004)17 Overall these results confirm

that small and medium-sized enterprises are much less financially constrained during the

crisis years with their perceptions close to those of the large firms This result is a polar

opposite to that obtained for the SMEs in the UK (Fraser 2009) which finds that not only do

SMEs generally feel more financially constrained but they report to be even more so during

17 We also check the robustness of our results to the potential problem of multicollinearity between a crisis dummy and its interaction term with SME by splitting a sample and testing the same specification separately for SMEs and large firms We also perform another robustness check by breaking a SME dummy into three subsequent dummies namely micro- small- and medium-sized firms The difference in perception of financial constraints gets almost eliminated in the case of small firms and is largely reduced in the case of micro firms whereas it is less so for medium-sized firms

19

the last crisis We could explain this striking difference by the peculiarities of the SMEs

functioning in new emerging economies The lower reliance of SMEs on external debt in

good times (as shown by results which are discussed below) gives SMEs some flexibility

during the crisis when formal financial markets dry up Jointly with overall flexibility to make

necessary cost cuts and to restructure a business this overall lower reliance on external

funding and the use of alternative sources of financing makes SMEs feel less financially

constrained under the crisis as compared to larger firms

We also find that a more developed financial sector as proxied by domestic private

credit as proportion of GDP helps ease up financial constraints This is in line with the

general literature suggesting that better functioning financial intermediaries facilitate the risk

amelioration in the presence of problems created by market frictions (Levine 1997 Barth et

al 2006 Barth et al 2008)

Unfortunately we fail to find any significant effect of the property rights protection on

firmsrsquo perception of financial constraints that may be explained by the fact that the effect of a

more developed financial sector is likely to outweigh the effect of the property rights

protection

Finally we also find that foreign ownership and international product certificate may

reduce firmsrsquo borrowing constraints while any pressure from domestic or foreign competition

so is pressure from the customers to innovate will increase firmrsquos perception of financial

constraints as major given that firms envisage the need to secure external funding for RampD

or any other innovation-related activities

Financing choices for investment in fixed assets

The results in Table 4 indicate that small enterprises tend to rely more on internal funds

and less on bank loans but they are no different from larger firms in respect of using informal

funds trade credit or private equity which is generally consistent with our discussion in

Sections 2 and 3 The results of Table 5 suggest however that under crisis small and

medium-sized firms tend to switch to other sources of finance such as trade credit and

ownerrsquos contributed equity and to respectively reduce the reliance on retained earnings

perhaps because they decrease due to the negative impact of crisis internal funds With

regards to our discussion of SMEsrsquo risk management we note that the use of private equity

(ownerrsquos contribution) during the crisis years increases which could indicate that the ownerrsquos

funds are used as a cushion in the period of financial distress

An interesting insight regarding the use of trade credit emerges for SMEs in our

sample although in non-crisis years small and medium-sized businesses are not significantly

different from larger firms in terms of reliance on trade credit SMEs tend to finance a

significantly higher proportion of their fixed asset investment by trade credit than large firms

20

in the period of crisis While the latter finding is partly in line with some other studies ndash such

as Klapper and Randall (2010) using BEEPS data it is in stark contrast with similar studies

of the UK private firms (Rehman 2011) for which the use of trade credit is found to have

dried up in crisis This could partly be due to the passed legislation in the UK tightening trade

credit regulation as the result of the abuse of trade credit by large firms in relation to small

firms which forced many SMEs out of the market

With regards to the other firm-level characteristics international certification makes the

firm rely more on private bank loans and informal finance (Table 5) while SMEs with foreign

ownership rely less on private debt but more on retained earnings Both results are

consistent with our hypotheses discussed above Export-oriented small and medium-sized

businesses tend to have greater reliance on trade credit and they use less of internal funds

We find a non-monotonic relationship between age and private equity with both younger and

older firms being more reliant on this source of funding We find some fragmentary support

for private domestic SMEs relying more on informal finance while tending to use less trade

credit and private equity (Table 5)

Interestingly our results (Tables 4-5) suggest that firms which lack some social

connections with governmental officials proxied by the higher amount of time spent dealing

with government regulations are more likely to rely on informal finance trade credit and

private equity In turn businesses which are connected to governmental officials use more

retained profits to fund investment in fixed assets This may be attributed to their connections

serving as a guarantee from expropriation of assets by all sort of rent-seeking individuals

akin private contracting to secure property rights protection This result should be interpreted

jointly with the property rights protection results We expected that better property rights

protection is likely to facilitate firmsrsquo access to bank loan but we failed to confirm this

Perhaps regardless some attempts at a constitutional level to prevent arbitrary government

(which is proxied by our measure of property rights) expropriation culture is still deeply

embedded in the society of post-communist countries and it may manifest in different ways

Welter and Smallbone (2011) argue that entrepreneurs in transition economies have learnt

how to respond to institutional deficiencies in particular weak property rights protection For

example some businesses experiencing high growth choose to invest in unrelated

businesses instead of growing their core businesses for the reason they do not want to

become too noticeable to attract too much attention of the wrong sort In our instance having

some connections with officials seems also to serve as protection against arbitrary

government or individual rent-seeking that makes businesses more keen on re-investing their

retained profits (see Johnson et al (2002) on the discussion of how more secure property

rights can make small firms reinvest more of their earnings)

8

the firm (Arnold 2008) More recent literature on firm financing started to look closer at and

emphasize the importance of other sources such as trade credit especially for the small and

medium firms using mostly the data on developed economies For instance Berger amp Udell

(1998) stress the importance of trade credit to the short-term financing of small firms Bevan

and Danbolt (2002) estimate that trade credit account for 62 per cent of total liabilities of UK

firms

The role of trade credit has been seen by some researchers as a substitute of bank

lending for liquidity-constrained firms (Cull 2007) such as SMEs One of the benefits of trade

credit compared to the bank lending is that it allows to partly get around the information

asymmetry problem between the lender and the borrowing SME as business partners would

have more information about the ability of the borrower to repay and about such reputation of

the borrower in the industry Meltzer (1960) Nielsen (2002) and Petersen and Rajan (1997)

argue that trade credit may also provide a means of alternative financing under the tight

monetary conditions such as credit crunches when financial institutions are less able or

willing to provide loans to SMEs In support of this hypothesis Atanasova and Wilson (2003

2004) and Mateut et al (2006) find that under tight monetary conditions firms tend to

substitute bank loans with trade credit However the findings in Bernanke and Gertler (1995)

and Gertler and Gilchrist (1993) do not agree with this hypothesis In line with these authors

Taketa and Udell (2007) using a sample of Japanese SMEs after the crisis years find that

bank lending and trade credit are complements rather than substitutes Love and Zaidi

(2010) report that the use of trade credit by East Asian firms has declined after the 1998

financial crisis together with the use of bank loans Finally interesting enough there is

some empirical evidence which suggests that in the context of transition economies there

may be a higher reliance of SMEs on trade credit in the period of crisis More specifically

focusing on the panel of 1686 firms in Bulgaria Hungary Latvia Lithuania Romania and

Turkey in 2007 and 2009 Klapper and Randall (2010) find that during periods of contractions

in bank credit buyers might depend more on trade credit (although primarily to be used for

short-term financing) that may be particularly true for small firms This provides some support

for the hypothesis that the two sources of finance namely bank loans and trade credit in the

context of transition and emerging economies can be seen as substitutes in period of crisis

Another source of firm financing that has recently received increased attention is

private equity Private equity consists of investments by private individual investors or firms

(business angels investments funds) as well as business ownersrsquo contributions to their

equity The lsquobusiness angelsrsquo type of private equity is currently on the rise in the developed

countries as well as emerging markets such as India Brazil China Malaysia However

ownersrsquo contribution is a far more widespread type of private equity in countries under

consideration Generally SMEs are prone to various types of business and financial risks

9

and it would be very important for them to try and hedge against these risks Zou and Adams

(2008) look at the effect of property insurance on the public firmsrsquo borrowing capacity in

China while Matthews and Scott (1995) in the US and Herbane (2011) in the UK investigate

the types of risk management used by the SMEs The findings point to a rather limited use by

the small and medium-sized enterprises of the risk management assessment and hedging

techniques

In the emerging markets of the post-Soviet bloc the use of risk management techniques

such as hedging with financial derivatives is virtually non-existent However an informal risk

management practice of accumulating cash out of profits and also of using informal lending

from family and friends to serve as a cushion in the times of financial distress as protection

against possible bankruptcy and as an instrument of insurance against risks has been one

way of accounting for the risky nature of SMEs in these countries Secondly many SMEs

sometimes use bankruptcy when they find themselves in the situation of financial distress

and then open a new firm without losing much of their personal assets (Radygin et al 2005)

These SMEs are oftentimes are registered as belonging to a relative or the SMEs could be

registered as founded by an artificially created third party with no links to the actual ownerrsquos

personal assets Recently banks in the new emerging economies such as Russia started a

practice of compulsory purchase of loan insurance if the SME is to take a loan from the bank

This serves as a risk insurance mechanism to a certain extent at the same time however

increasing the cost of bank financing However more recently this practice has attracted the

attention of the Federal Antimonopoly Service that ruled that there is evidence of collusion

between banks and insurance companies Overall we could conclude that the use of risk

management practices is very narrow and of a rather informal nature

The next sub-section explores in greater detail the institutional context of financing in the

situation of economic crisis

Empirical studies on small firm financing in the years of crisis are primarily motivated by

the informational asymmetries theories One of the most important contributions in the study

of the role of SMEs during business cycle has been the real business cycle (RBC) theory

(Bernanke and Gertler 1995 Bernanke Gertler amp Gilchrist 1998) The argument put forward

by the RBC theory is that SMEs face tighter liquidity constraints in terms of external financing

due to higher informational asymmetries associated with their activities the low value of

their assets to serve as collateral the high cost of monitoring small businesses given a small

scale of their investment projects and subsequently the unwillingness of banks to lend to

SMEs

During economic slowdowns when small businesses are even more in need of external

finance bank lending to them diminishes even further which tends to propagate the crisis if

the SMEs then go out of business (see for example Tornell and Westermann 2005) At the

10

same time as larger firms use more finance and tend to rely more on external funding they

may be hit harder by financial contraction in the situation of global crises when international

financial markets dry up so preventing larger firms from drawing upon them when required

They are also less flexible and it is more costly for them to restructure and downsize when

they are hit with external shocks Furthermore while SMEs tend to be more flexible in relying

on other sources of finance including trade credit contributed equity and informal finance

the financial structure of larger firms generally tends to be less diversified with a preference

often given to retained profits and bank finance following the pecking order theory Taken

together we may argue that both supply and demand for finance is more affected for larger

firms in the situation of external shocks

Based on the discussion presented in Sections 2 and 31 we further discuss three main

groups of factors which are likely to affect firmsrsquo perception of financial constraints and their

financing choice strategy These are as follows (1) firm size in general and in the period of

crisis (2) other firm- and industry-specific characteristics including foreign ownership export

orientation firmsrsquo social capital and the degree of competition and its pressure on the firm to

develop a new product and (3) country-level institutional parameters including the degree of

protection of property rights and the development of the financial sector

32 Size of the enterprise and the effect of crisis

With regards to the effect of firm size based on the general discussion in the literature

(see sections 2-31) we expect SMEs to be more financially constrained in their access to

external lending and respectively more reliant on internal funds This is due to insufficient

information that the bank can obtain about a particular SME as well as due to a potentially

lower size of collateral However this lower reliance of SMEs on external debt can potentially

be a source of flexibility during the crisis when formal financial markets dry up and when

even large well-established firms have difficulty obtaining bank credit Furthermore following

Atanasova and Wilson (2003 2004) Mateut et al (2006) and Klapper and Randall (2010) we

expect that under tight monetary conditions SMEs in transition economies are more likely to

switch to alternative forms of financing such as trade credit We also hypothesize that SMEs

are more likely to rely on ownersrsquo contributed equity which they tend to accumulate in good

times as part of their risk management strategy to use it as a cushion in the times of financial

distress In summary we expect the difference between the SMEs and large firms in their

reliance on bank finance to diminish during the crisis years and second SMEs to be more

flexible and rely more on other sources of finance such as trade credit and private equity in

the period of financial contractions

11

33 Firm- and industry- level factors

As far as the firm-level and industry-level variables are concerned we expect the

following results first the level of social capital of a firm as proxied by the inverse of the time

spent dealing with government regulations to indicate possible established connections with

public officials can positively affect its access to trade credit Next the industry-level

pressure on a firm from competitors to develop a new product may increase the firmrsquos

chances of obtaining a bank loan as the bank may perceive the firmrsquos operations as more

diversified and less risky (Isachenkova et al 2011) We also expect foreign competition and

the pressure it exerts on a firm innovation capability to play less important role for firm

financing decisions as SMEs are more likely to operate in market niches and they are

unlikely to compete with multinational enterprises In contrast we expect a pressure

originated from customers on a firm to innovate to increase a firmrsquos probability to rely more

on external sources of funding This may be attributed to the fact that a firm does not only

differentiate itself from other firms further with developing a new product but also assures a

demand for this product by responding to the needs of its existing customers The

guaranteed demand for a new product would be one of the most crucial factors taken into

account by bank managers or potential investors in decision-making concerning project

financing Thirdly international product certification may play a similar role with regards to

bank loans increasing the access to external funds Fourth we investigate the effect on the

choice of financing of the firm age with a square term Generally older firms may have

easier access to bank loans as more information is available about them to the lender (Beck

et al 2006 Canton et al 2010) however due to the particulars of the transition period

sometimes older firms may be less economically viable and unable to get a loan therefore

the sign of this coefficient is uncertain here Lastly we also look at the firmrsquos export

orientation which is expected to increase the reliance on bank lending and its ownership

type where we single out foreign and domestic private firms In the case of foreign firms

they are less likely to use private loans and rely instead on retained earnings and intra-

company funds transfers in the case of MNCs

34 Institutional environment

The impact of institutional variables on the financing choices of firms has been of the

utmost interest to economists and policy-makers during the period of transition (see for

example Stijn and Tzioumis 2006 Mitra et al 2008 see also Commander and Svejnar

(2009) for an in-depth and comprehensive analysis of the impact of various business

environment factors on firm performance using BEEPS 2002 - 2005 panel) In our analysis

12

we concentrate on two institutional factors the degree of protection of property rights and the

size of the formal financial sector which have been claimed to be of key importance for firmsrsquo

financing decisions (see Korosteleva and Mickiewicz (2011) for overview of the related

literature) As far as the property rights protection is concerned it is found to play crucial role

for firm growth and access to external finance (Aidis et al 2008 2010 Korosteleva and

Mickiewicz 2011 Estrin Korosteleva and Mickiewicz 2011) In the environment with weak

protection of property rights financial contracts are less likely to be concluded leading to the

underdevelopment of finance and credit rationing with small firms to be disproportionally

affected the most (Acemoglu and Johnson 2005) Beck et al (2004) show that in terms of

access to external finance small firms benefit disproportionally from higher levels of property

rights protection Lack of secure property rights may also discourage SMEs from taking full

advantage of opportunities to invest (Johnson et al 2002) In a survey of private small

manufacturing firms in Poland Russia Ukraine Romania and Slovakia Johnson et al

(2002) find that small firms tend to reinvest less of their earnings when they perceive their

property rights insecure They also find that the effect of the property rights system is of more

paramount importance for entrepreneursrsquo decisions to reinvest their earnings than availability

of formal finance Moreover if property rights are well-protected this lessens the extent of

potential threat of being expropriated by raidersbank lenders in an artificial bankruptcy

procedure which has been quite a significant issue for firms in Russia and other FSU states

(Radygin et al 2005 Sprenger 2002) Based on this we expect that strong property rights

are likely to encourage SMEs to use more debt as well as to use their own funds and

retained profits for investing in investment projects

With regards to the size of the formal finance as measured by the share of private

credit to GDP the relationship between financial depth and financial constraints has been

extensively studied (Beck et al 2006 also see for example Love 2003 who employing a

sample of 36 countries finds that financial development affects firmsrsquo investment by

increasing the availability of external finance) Financial intermediaries facilitate the risk

amelioration in the presence of problems created by information and transaction frictions by

developing expertise in risk assessment and in monitoring (Levine 1997 Barth et al 2006

Barth et al 2008) Developed financial institutions are found to be particularly beneficial for

small firms compared to large ones (Barth et al 2006 Beck et al 2005 2006 2008)

Pissarides et al (2003) show that financial constraints affect SMEs even more than

deficiency of the property rights protection Accordingly the size of the formal financial

system is expected to be positively related to the use of bank finance as a better functioning

financial system should help ease up borrowing constraints

4 Data and Methodology

13

41 Sample

To explore the determinants of the financial structure of small businesses we use the

2002-2009 Business Environment and Enterprise Performance Survey (BEEPS) data6 of

21867 firms covering 26 transition economies of Europe and Central Asia (ECA)7

The sample is primarily comprised of small and medium-sized businesses8 which

account for 893 per cent of the sample The sample is representative in terms of industrial

coverage with the majority of SMEs of the sample operating in manufacturing wholesale

and retailing industries

BEEPS dataset provides rich information on firm characteristics investment

behaviour and firmsrsquo perception of business environment including financial constraints

which are of a primary interest for our investigation of the effect of the recent financial crisis

on firmsrsquo perception of financial constraints Potentially we could use other micro-level data

characterising various domains of business environment captured by firmsrsquo perceptions for

investigating the effects of the institutional settings However using these micro-level

indicators as explanatory variables would make our study plagued with a problem of

endogeneity To avoid this we merge our firm-level data with country-level indicators

characterising various institutional domains The country level data were obtained from the

World Development Indicators (World Bank) and Polity IV databases (for further discussion

see below) Finally the BEEPs dataset contains other useful information which allows us to

shed light of the effect of for example social capital as proxied by the indirect measure of

possible connections with the authorities (see below for the definition of the variable) on firm

financing

42 Variable Definition and Measurement

Explanatory variables

6 This data is a joint project of the European Bank for Reconstruction and Development and World Bank The first survey was launched in 1999 The dataset used in the present study is an unbalanced panel covering the years of 2002 2005 2007-2009 7 The sample includes the following countries Albania Armenia Azerbaijan Belarus Bosnia Bulgaria Croatia Czech Republic Estonia FYROM Georgia Hungary Kazakhstan Kyrgyzstan Latvia Lithuania Moldova Montenegro Poland Romania Russia Serbia Slovakia Slovenia Tajikistan and Ukraine We exclude Uzbekistan as an outlier from our sample We also exclude Turkey as it is not classified as a post-communist country undertaking transition from a planned to a market economy 8 We utilize the EU employment criterion to define small and medium-sized businesses More specifically businesses are defined as micro if they employ 9 and less employees small ndash between 10 and 49 medium ndash between 50 and 249 and large ndash over 250 employees Respectively SMEs are defined as firms employing less than 249 firms

14

To test our main hypothesis of the effect of a firm size on firmsrsquo perception of financial

constraints we introduce a dummy variable denoting small and medium-sized business

coded as 1 if firms are classified as small or medium-sized businesses according to the EU

definition based on the employment criterion For robustness of our results we also use a

continuous variable denoting a size of employment as measured by the natural logarithm of

employment9 The obtained results are consistent with the ones using the SME indicators

To capture the effect of the recent financial crisis we introduce a crisis dummy coded

as 1 if the year of survey is equal to 2008 or 200910

We also introduce a number of firm-level controls which include age of firm11 type of

ownership including private and foreign ownership export orientation and whether a firm

has an internationally certified product all equal to 1 if a business has a respectively listed

characteristic and zero otherwise We also examine the effect of various sources of pressure

on firms to innovate ndash the indicators which are considered to be important for firm investment

decisions Respectively the pressure for innovation may stem from domestic competition

foreign competition and customers To capture the effect of a firmrsquos social capital we

introduce an indicator which indirectly may capture some possible connections of a firm with

authorities It is proxied by time spent by each firm on dealing with government regulations

We assume the less time firms spend dealing with government regulations the more likely

they have some established connections with public officials which allow them to avoid

burdensome regulation procedures

In our study we also introduce a number of country-level variables which characterize

the institutional environment in the countries covered by our sample More specifically we

include an indicator of the financial development as measured by the ratio of domestic credit

to private sector to GDP (one year lag to avoid potential endogeneity) obtained from the

World Bank World Development Indicators (World Bank 2011) This measure has been used

in previous studies (Klapper et al 2006) and it is expected to be of a primary importance for

transition economies where firms tend to rely more on bank finance rather than capital

markets We also introduce a measure of property rights protection (a one year lag) proxied

by the indicator of effective constraints imposed on the executive branch of the government

and obtained from Polity IV project12 This measure of property rights protection is

9 These results are not reported here to save some space However they can be obtained from authors upon request 10 Here it is important to note that although the financial crisis has started in 2007 in the USA it spread to transition economies in 2008-2009 11 Some studies find a non-monotonic relationship between age and firm decision-making In this study we introduce a squared term of age along with a age variable to capture this possible non-linearity 12 Available from httpwwwsystemicpeaceorgpolitypolity4htm

15

considered to be superior to other indicators including the index of property rights reported

by the Heritage Foundation ndashWall Street Journal (for further discussion see Acemoglu and

Johnson 2005 Glaeser et al 2004 Estrin Korosteleva and Mickieiwcz 2011)

In the present study we also introduce macroeconomic controls including cyclical

economic performance as measured by the one year lag of the GDP annual growth rate

and the level of economic development as proxied by a set of GDP pc dummies denoting

the five quintiles of its distribution to address the problem of potential multicollinearity with the

measure of financial development

Finally we include industry and country controls in all our specifications Introducing

country dummies into analysis allows to control for cross-country heterogeneity

For further definition of all variables their descriptive statistics and correlation matrix

see Tables 1-2

43 Dependent variables

To investigate the effect of a firmrsquos size on its perception of financial constraints we

construct a dummy variable coded as 1 capturing a major and very severe obstacle for

access to finance and 0 otherwise

The firm financing choices are defined by the five individual dependent variables

associated with tobit financial choice equations in the seemingly unrelated regression

equations model

One important thing to mention here is the inability to distinguish between

owninternal funds and external private equity considered as one of the limitations of the

2002-2009 BEEPS dataset In the period under investigation BEEPS offers two questions

which aim to capture the use of equity The first one centres around retained earnings and

the second one shows ownersrsquo contributions and private equity or issued new equity

Following some theoretical considerations discussed in sections 2 and 3 in the context of

SMEs we expect the second element of equity to be primarily comprised of existing ownersrsquo

new contributions rather than private equity

Thus the indicator of financial choices represents a set of five individual dependent

variables including retained earnings contributed earnings private borrowing informal

finance trade credit with each of them constructed as a share in total financing of SMErsquos

investment decisions (see Table 1)

44 Methods

16

In this study we employ a number of estimators to obtain robust results More

specifically we use a probit model to investigate the effect of a firm size and the recent

financial crisis on firmsrsquo perception of financial constraints The effect of a firm size in the

situation of crisis is captured by the introduction of the interaction term between firm size as

proxied by the SME indicator and a financial crisis dummy

We further employ the seemingly unrelated regression equations model combined

with the tobit approach for studying firmsrsquo financial structure

Probit model of perception of financial constraints

In the probit model the probability of a firmrsquos perception of financial constraints as

major(j = 1) can be written as follows

( ) ( )int ++

++

infinminus

minus===

ijitj uXjitiitit ijitjuXjy uX

βα βαππ 212-

)()(2 21exp|Pr

Where ity is our measure of financial constraints as perceived by firms and itX is a

set of our explanatory variables discussed in detail in sections 3-4 Here it is important to

note that the interaction term in a probit model cannot be interpreted in a similar way as in

linear models and disregarding this may lead to misleading estimates of the interaction

effect which is of crucial importance for our study (Norton Wang and Ai 2004) Respectively

for robustness of our results here we follow the framework suggested by Norton Wang and

Ai (2004) to account for the model nonlinearity The adjusted marginal effects for the

interaction term are reported in the note to Table 313

Simultaneous Model of Financing Choices

As mentioned above we next model the choice of all five financing choices explicitly

We also hypothesise (following Isachenkova et al 2011) that firm financing choices are likely

to be determined jointly A standard way of modelling jointly determined indicators is a

system of equations - SURE ndash seemingly unrelated regression equations where equations

are linked only by their errors (Zellner 1962) We therefore model the five types of sources of

finance (internal funds private bank borrowing informal finance trade credit and private

13 We also run a probit regression for a split sample of (1) SMEs and (2) large firms to check the robustness of our results (based on the interaction term) while addressing a problem of multicollinearity between a crisis variable and its interaction term with a SME variable The correlation coefficient between a crisis variable and its interaction term with a SME variable is equal to 93 This can be attributed by the problem of a sample being overrepresented by SMEs which constitute 90 of all surveyed firms The results remain robust and can be available from authors upon request

17

equity) using a SURE framework within which we specify a set of five tobit regressions with

correlated residuals

We employ the STATA cmp module which allows to it Seemingly Unrelated Regressions

using the simulated likelihood method such as the Geweke Hajivassiliou and Keane (GHK)

algorithm (for further discussion see Roodman 2008) We utilise a tobit equation to model

each individual financial choice of firms because our dependent financing choices variables

are continuous but their range is constrained (censored) with a substantial number of

observations either equal to zero denoting those who do not use the respective source of

finance or to 100 showing the opposite Other observations are positive and may produce

many different outcomes (Verbeek 2000) Each tobit equation uses a set of identical

explanatory variables that proxy factors which could possibly be associated with firmrsquos

financing choices including industry and country dummies

We also considered the bias caused by potential interdependence between the choice of

whether to invest and firmrsquos financing choices We accounted for the potential selection bias

by introducing into the financial choices SURE Tobit equations (second stage outcome

equations14) the inverse Millrsquos ratio calculated based on modelling the choice to invest in

fixed assets (first stage or selection equation) To identify the first stage of the Heckman

selection model we chose a variable which is correlated with the first stage dependent

variable (investment decision) but not with the second ones (financing choices) We used the

rate of capacity utilization as part of our identification strategy Capacity utilization shows the

percentage of capital stock in use the higher is the rate the more likely firms will increase

investment Batyaeva and Aukutsionek (2001) show that the rate of capacity utilization is

higher in the group of investing firms than in the group of non-investing firms in Russia15 We

calculated the inverse Millrsquos ratio based on the above selection equation16 and included it as

a control in the second stage SURE Tobit equations The inverse Millrsquos ratio has only proved

to be statistically significant in the private bank loan equation pointing to the potential

selection bias arising from the possibility that the factors determining the decision to invest

might differ from those determining the use of bank financing in purchasing fixed assets

14 We also attempted to estimate an investment equation jointly with Tobit financial choices equations within the SURE framework using However given the overall complexity of the model we failed to do this We proceeded further with a two-stage approach by estimating an investment probit equation and calculating the inverse Millrsquos ratio that we add into the outcome financial choices equations at the second stage of the analysis to test for the selection bias 15 We performed an independent sample t-test to check whether the rate of capacity utilization is statistically significantly higher for investing firms compared to non-investing firms for our sample The null hypothesis of no difference was rejected at 1 level of significance 16 To economize on space we do not report the results of the investment probit equation but they are available from authorsrsquo upon request

18

Finally In Table 6 we attempt to condition the determinants of financing constraints

declared by SMEs on the relative percentage increase of trade credit in total funds used for

real investment As mentioned above in Section 2 the timings of measuring the composition

of financing sources precede by a year the timings of measuring the perceptions of financing

constraints That feature of the BEEPSrsquo design allays a likely concern about the endogeneity

of the relative proportion of trade credit and enables causal inference We too report in thre

note to Table 4 the adjusted marginal effects for the interaction term of the SME dummy with

the trade credit variable

In the next section we discuss our empirical results

5 Empirical Results

Table 3 reports the results of the probit model with the marginal effects for firmsrsquo

perception of financial constraints while Tables 4-5 summarize the results of SURE tobits for

a more detailed breakdown of five financing choices More specifically Table 4 reports the

results based on the whole sample to give a comparative perspective on SMErsquos financing

strategy vis-a-vis large businesses whereas Table 5 reports the results based on a

subsample of small and medium-sized firms to shed some light on their financing choices in

the period of crisis

Perception of financial constraints

Table 3 shows that generally small and medium-sized enterprises feel more financially

constrained with the coefficient for SME dummy in relation to the large firms being positive

and significant which is consistent with our discussion in sections 2-3 However the

coefficient of the interaction term with the Crisis dummy turns out to be negative and

significant in relation to the perception of financial constraints as a major obstacle and it

tends to outweigh the effect of a SME dummy when we calculate marginal effects The effect

of the interaction terms with the crisis remains robust after we adjust for non-linearity using

the framework proposed by Norton Wang and Ai (2004)17 Overall these results confirm

that small and medium-sized enterprises are much less financially constrained during the

crisis years with their perceptions close to those of the large firms This result is a polar

opposite to that obtained for the SMEs in the UK (Fraser 2009) which finds that not only do

SMEs generally feel more financially constrained but they report to be even more so during

17 We also check the robustness of our results to the potential problem of multicollinearity between a crisis dummy and its interaction term with SME by splitting a sample and testing the same specification separately for SMEs and large firms We also perform another robustness check by breaking a SME dummy into three subsequent dummies namely micro- small- and medium-sized firms The difference in perception of financial constraints gets almost eliminated in the case of small firms and is largely reduced in the case of micro firms whereas it is less so for medium-sized firms

19

the last crisis We could explain this striking difference by the peculiarities of the SMEs

functioning in new emerging economies The lower reliance of SMEs on external debt in

good times (as shown by results which are discussed below) gives SMEs some flexibility

during the crisis when formal financial markets dry up Jointly with overall flexibility to make

necessary cost cuts and to restructure a business this overall lower reliance on external

funding and the use of alternative sources of financing makes SMEs feel less financially

constrained under the crisis as compared to larger firms

We also find that a more developed financial sector as proxied by domestic private

credit as proportion of GDP helps ease up financial constraints This is in line with the

general literature suggesting that better functioning financial intermediaries facilitate the risk

amelioration in the presence of problems created by market frictions (Levine 1997 Barth et

al 2006 Barth et al 2008)

Unfortunately we fail to find any significant effect of the property rights protection on

firmsrsquo perception of financial constraints that may be explained by the fact that the effect of a

more developed financial sector is likely to outweigh the effect of the property rights

protection

Finally we also find that foreign ownership and international product certificate may

reduce firmsrsquo borrowing constraints while any pressure from domestic or foreign competition

so is pressure from the customers to innovate will increase firmrsquos perception of financial

constraints as major given that firms envisage the need to secure external funding for RampD

or any other innovation-related activities

Financing choices for investment in fixed assets

The results in Table 4 indicate that small enterprises tend to rely more on internal funds

and less on bank loans but they are no different from larger firms in respect of using informal

funds trade credit or private equity which is generally consistent with our discussion in

Sections 2 and 3 The results of Table 5 suggest however that under crisis small and

medium-sized firms tend to switch to other sources of finance such as trade credit and

ownerrsquos contributed equity and to respectively reduce the reliance on retained earnings

perhaps because they decrease due to the negative impact of crisis internal funds With

regards to our discussion of SMEsrsquo risk management we note that the use of private equity

(ownerrsquos contribution) during the crisis years increases which could indicate that the ownerrsquos

funds are used as a cushion in the period of financial distress

An interesting insight regarding the use of trade credit emerges for SMEs in our

sample although in non-crisis years small and medium-sized businesses are not significantly

different from larger firms in terms of reliance on trade credit SMEs tend to finance a

significantly higher proportion of their fixed asset investment by trade credit than large firms

20

in the period of crisis While the latter finding is partly in line with some other studies ndash such

as Klapper and Randall (2010) using BEEPS data it is in stark contrast with similar studies

of the UK private firms (Rehman 2011) for which the use of trade credit is found to have

dried up in crisis This could partly be due to the passed legislation in the UK tightening trade

credit regulation as the result of the abuse of trade credit by large firms in relation to small

firms which forced many SMEs out of the market

With regards to the other firm-level characteristics international certification makes the

firm rely more on private bank loans and informal finance (Table 5) while SMEs with foreign

ownership rely less on private debt but more on retained earnings Both results are

consistent with our hypotheses discussed above Export-oriented small and medium-sized

businesses tend to have greater reliance on trade credit and they use less of internal funds

We find a non-monotonic relationship between age and private equity with both younger and

older firms being more reliant on this source of funding We find some fragmentary support

for private domestic SMEs relying more on informal finance while tending to use less trade

credit and private equity (Table 5)

Interestingly our results (Tables 4-5) suggest that firms which lack some social

connections with governmental officials proxied by the higher amount of time spent dealing

with government regulations are more likely to rely on informal finance trade credit and

private equity In turn businesses which are connected to governmental officials use more

retained profits to fund investment in fixed assets This may be attributed to their connections

serving as a guarantee from expropriation of assets by all sort of rent-seeking individuals

akin private contracting to secure property rights protection This result should be interpreted

jointly with the property rights protection results We expected that better property rights

protection is likely to facilitate firmsrsquo access to bank loan but we failed to confirm this

Perhaps regardless some attempts at a constitutional level to prevent arbitrary government

(which is proxied by our measure of property rights) expropriation culture is still deeply

embedded in the society of post-communist countries and it may manifest in different ways

Welter and Smallbone (2011) argue that entrepreneurs in transition economies have learnt

how to respond to institutional deficiencies in particular weak property rights protection For

example some businesses experiencing high growth choose to invest in unrelated

businesses instead of growing their core businesses for the reason they do not want to

become too noticeable to attract too much attention of the wrong sort In our instance having

some connections with officials seems also to serve as protection against arbitrary

government or individual rent-seeking that makes businesses more keen on re-investing their

retained profits (see Johnson et al (2002) on the discussion of how more secure property

rights can make small firms reinvest more of their earnings)

9

and it would be very important for them to try and hedge against these risks Zou and Adams

(2008) look at the effect of property insurance on the public firmsrsquo borrowing capacity in

China while Matthews and Scott (1995) in the US and Herbane (2011) in the UK investigate

the types of risk management used by the SMEs The findings point to a rather limited use by

the small and medium-sized enterprises of the risk management assessment and hedging

techniques

In the emerging markets of the post-Soviet bloc the use of risk management techniques

such as hedging with financial derivatives is virtually non-existent However an informal risk

management practice of accumulating cash out of profits and also of using informal lending

from family and friends to serve as a cushion in the times of financial distress as protection

against possible bankruptcy and as an instrument of insurance against risks has been one

way of accounting for the risky nature of SMEs in these countries Secondly many SMEs

sometimes use bankruptcy when they find themselves in the situation of financial distress

and then open a new firm without losing much of their personal assets (Radygin et al 2005)

These SMEs are oftentimes are registered as belonging to a relative or the SMEs could be

registered as founded by an artificially created third party with no links to the actual ownerrsquos

personal assets Recently banks in the new emerging economies such as Russia started a

practice of compulsory purchase of loan insurance if the SME is to take a loan from the bank

This serves as a risk insurance mechanism to a certain extent at the same time however

increasing the cost of bank financing However more recently this practice has attracted the

attention of the Federal Antimonopoly Service that ruled that there is evidence of collusion

between banks and insurance companies Overall we could conclude that the use of risk

management practices is very narrow and of a rather informal nature

The next sub-section explores in greater detail the institutional context of financing in the

situation of economic crisis

Empirical studies on small firm financing in the years of crisis are primarily motivated by

the informational asymmetries theories One of the most important contributions in the study

of the role of SMEs during business cycle has been the real business cycle (RBC) theory

(Bernanke and Gertler 1995 Bernanke Gertler amp Gilchrist 1998) The argument put forward

by the RBC theory is that SMEs face tighter liquidity constraints in terms of external financing

due to higher informational asymmetries associated with their activities the low value of

their assets to serve as collateral the high cost of monitoring small businesses given a small

scale of their investment projects and subsequently the unwillingness of banks to lend to

SMEs

During economic slowdowns when small businesses are even more in need of external

finance bank lending to them diminishes even further which tends to propagate the crisis if

the SMEs then go out of business (see for example Tornell and Westermann 2005) At the

10

same time as larger firms use more finance and tend to rely more on external funding they

may be hit harder by financial contraction in the situation of global crises when international

financial markets dry up so preventing larger firms from drawing upon them when required

They are also less flexible and it is more costly for them to restructure and downsize when

they are hit with external shocks Furthermore while SMEs tend to be more flexible in relying

on other sources of finance including trade credit contributed equity and informal finance

the financial structure of larger firms generally tends to be less diversified with a preference

often given to retained profits and bank finance following the pecking order theory Taken

together we may argue that both supply and demand for finance is more affected for larger

firms in the situation of external shocks

Based on the discussion presented in Sections 2 and 31 we further discuss three main

groups of factors which are likely to affect firmsrsquo perception of financial constraints and their

financing choice strategy These are as follows (1) firm size in general and in the period of

crisis (2) other firm- and industry-specific characteristics including foreign ownership export

orientation firmsrsquo social capital and the degree of competition and its pressure on the firm to

develop a new product and (3) country-level institutional parameters including the degree of

protection of property rights and the development of the financial sector

32 Size of the enterprise and the effect of crisis

With regards to the effect of firm size based on the general discussion in the literature

(see sections 2-31) we expect SMEs to be more financially constrained in their access to

external lending and respectively more reliant on internal funds This is due to insufficient

information that the bank can obtain about a particular SME as well as due to a potentially

lower size of collateral However this lower reliance of SMEs on external debt can potentially

be a source of flexibility during the crisis when formal financial markets dry up and when

even large well-established firms have difficulty obtaining bank credit Furthermore following

Atanasova and Wilson (2003 2004) Mateut et al (2006) and Klapper and Randall (2010) we

expect that under tight monetary conditions SMEs in transition economies are more likely to

switch to alternative forms of financing such as trade credit We also hypothesize that SMEs

are more likely to rely on ownersrsquo contributed equity which they tend to accumulate in good

times as part of their risk management strategy to use it as a cushion in the times of financial

distress In summary we expect the difference between the SMEs and large firms in their

reliance on bank finance to diminish during the crisis years and second SMEs to be more

flexible and rely more on other sources of finance such as trade credit and private equity in

the period of financial contractions

11

33 Firm- and industry- level factors

As far as the firm-level and industry-level variables are concerned we expect the

following results first the level of social capital of a firm as proxied by the inverse of the time

spent dealing with government regulations to indicate possible established connections with

public officials can positively affect its access to trade credit Next the industry-level

pressure on a firm from competitors to develop a new product may increase the firmrsquos

chances of obtaining a bank loan as the bank may perceive the firmrsquos operations as more

diversified and less risky (Isachenkova et al 2011) We also expect foreign competition and

the pressure it exerts on a firm innovation capability to play less important role for firm

financing decisions as SMEs are more likely to operate in market niches and they are

unlikely to compete with multinational enterprises In contrast we expect a pressure

originated from customers on a firm to innovate to increase a firmrsquos probability to rely more

on external sources of funding This may be attributed to the fact that a firm does not only

differentiate itself from other firms further with developing a new product but also assures a

demand for this product by responding to the needs of its existing customers The

guaranteed demand for a new product would be one of the most crucial factors taken into

account by bank managers or potential investors in decision-making concerning project

financing Thirdly international product certification may play a similar role with regards to

bank loans increasing the access to external funds Fourth we investigate the effect on the

choice of financing of the firm age with a square term Generally older firms may have

easier access to bank loans as more information is available about them to the lender (Beck

et al 2006 Canton et al 2010) however due to the particulars of the transition period

sometimes older firms may be less economically viable and unable to get a loan therefore

the sign of this coefficient is uncertain here Lastly we also look at the firmrsquos export

orientation which is expected to increase the reliance on bank lending and its ownership

type where we single out foreign and domestic private firms In the case of foreign firms

they are less likely to use private loans and rely instead on retained earnings and intra-

company funds transfers in the case of MNCs

34 Institutional environment

The impact of institutional variables on the financing choices of firms has been of the

utmost interest to economists and policy-makers during the period of transition (see for

example Stijn and Tzioumis 2006 Mitra et al 2008 see also Commander and Svejnar

(2009) for an in-depth and comprehensive analysis of the impact of various business

environment factors on firm performance using BEEPS 2002 - 2005 panel) In our analysis

12

we concentrate on two institutional factors the degree of protection of property rights and the

size of the formal financial sector which have been claimed to be of key importance for firmsrsquo

financing decisions (see Korosteleva and Mickiewicz (2011) for overview of the related

literature) As far as the property rights protection is concerned it is found to play crucial role

for firm growth and access to external finance (Aidis et al 2008 2010 Korosteleva and

Mickiewicz 2011 Estrin Korosteleva and Mickiewicz 2011) In the environment with weak

protection of property rights financial contracts are less likely to be concluded leading to the

underdevelopment of finance and credit rationing with small firms to be disproportionally

affected the most (Acemoglu and Johnson 2005) Beck et al (2004) show that in terms of

access to external finance small firms benefit disproportionally from higher levels of property

rights protection Lack of secure property rights may also discourage SMEs from taking full

advantage of opportunities to invest (Johnson et al 2002) In a survey of private small

manufacturing firms in Poland Russia Ukraine Romania and Slovakia Johnson et al

(2002) find that small firms tend to reinvest less of their earnings when they perceive their

property rights insecure They also find that the effect of the property rights system is of more

paramount importance for entrepreneursrsquo decisions to reinvest their earnings than availability

of formal finance Moreover if property rights are well-protected this lessens the extent of

potential threat of being expropriated by raidersbank lenders in an artificial bankruptcy

procedure which has been quite a significant issue for firms in Russia and other FSU states

(Radygin et al 2005 Sprenger 2002) Based on this we expect that strong property rights

are likely to encourage SMEs to use more debt as well as to use their own funds and

retained profits for investing in investment projects

With regards to the size of the formal finance as measured by the share of private

credit to GDP the relationship between financial depth and financial constraints has been

extensively studied (Beck et al 2006 also see for example Love 2003 who employing a

sample of 36 countries finds that financial development affects firmsrsquo investment by

increasing the availability of external finance) Financial intermediaries facilitate the risk

amelioration in the presence of problems created by information and transaction frictions by

developing expertise in risk assessment and in monitoring (Levine 1997 Barth et al 2006

Barth et al 2008) Developed financial institutions are found to be particularly beneficial for

small firms compared to large ones (Barth et al 2006 Beck et al 2005 2006 2008)

Pissarides et al (2003) show that financial constraints affect SMEs even more than

deficiency of the property rights protection Accordingly the size of the formal financial

system is expected to be positively related to the use of bank finance as a better functioning

financial system should help ease up borrowing constraints

4 Data and Methodology

13

41 Sample

To explore the determinants of the financial structure of small businesses we use the

2002-2009 Business Environment and Enterprise Performance Survey (BEEPS) data6 of

21867 firms covering 26 transition economies of Europe and Central Asia (ECA)7

The sample is primarily comprised of small and medium-sized businesses8 which

account for 893 per cent of the sample The sample is representative in terms of industrial

coverage with the majority of SMEs of the sample operating in manufacturing wholesale

and retailing industries

BEEPS dataset provides rich information on firm characteristics investment

behaviour and firmsrsquo perception of business environment including financial constraints

which are of a primary interest for our investigation of the effect of the recent financial crisis

on firmsrsquo perception of financial constraints Potentially we could use other micro-level data

characterising various domains of business environment captured by firmsrsquo perceptions for

investigating the effects of the institutional settings However using these micro-level

indicators as explanatory variables would make our study plagued with a problem of

endogeneity To avoid this we merge our firm-level data with country-level indicators

characterising various institutional domains The country level data were obtained from the

World Development Indicators (World Bank) and Polity IV databases (for further discussion

see below) Finally the BEEPs dataset contains other useful information which allows us to

shed light of the effect of for example social capital as proxied by the indirect measure of

possible connections with the authorities (see below for the definition of the variable) on firm

financing

42 Variable Definition and Measurement

Explanatory variables

6 This data is a joint project of the European Bank for Reconstruction and Development and World Bank The first survey was launched in 1999 The dataset used in the present study is an unbalanced panel covering the years of 2002 2005 2007-2009 7 The sample includes the following countries Albania Armenia Azerbaijan Belarus Bosnia Bulgaria Croatia Czech Republic Estonia FYROM Georgia Hungary Kazakhstan Kyrgyzstan Latvia Lithuania Moldova Montenegro Poland Romania Russia Serbia Slovakia Slovenia Tajikistan and Ukraine We exclude Uzbekistan as an outlier from our sample We also exclude Turkey as it is not classified as a post-communist country undertaking transition from a planned to a market economy 8 We utilize the EU employment criterion to define small and medium-sized businesses More specifically businesses are defined as micro if they employ 9 and less employees small ndash between 10 and 49 medium ndash between 50 and 249 and large ndash over 250 employees Respectively SMEs are defined as firms employing less than 249 firms

14

To test our main hypothesis of the effect of a firm size on firmsrsquo perception of financial

constraints we introduce a dummy variable denoting small and medium-sized business

coded as 1 if firms are classified as small or medium-sized businesses according to the EU

definition based on the employment criterion For robustness of our results we also use a

continuous variable denoting a size of employment as measured by the natural logarithm of

employment9 The obtained results are consistent with the ones using the SME indicators

To capture the effect of the recent financial crisis we introduce a crisis dummy coded

as 1 if the year of survey is equal to 2008 or 200910

We also introduce a number of firm-level controls which include age of firm11 type of

ownership including private and foreign ownership export orientation and whether a firm

has an internationally certified product all equal to 1 if a business has a respectively listed

characteristic and zero otherwise We also examine the effect of various sources of pressure

on firms to innovate ndash the indicators which are considered to be important for firm investment

decisions Respectively the pressure for innovation may stem from domestic competition

foreign competition and customers To capture the effect of a firmrsquos social capital we

introduce an indicator which indirectly may capture some possible connections of a firm with

authorities It is proxied by time spent by each firm on dealing with government regulations

We assume the less time firms spend dealing with government regulations the more likely

they have some established connections with public officials which allow them to avoid

burdensome regulation procedures

In our study we also introduce a number of country-level variables which characterize

the institutional environment in the countries covered by our sample More specifically we

include an indicator of the financial development as measured by the ratio of domestic credit

to private sector to GDP (one year lag to avoid potential endogeneity) obtained from the

World Bank World Development Indicators (World Bank 2011) This measure has been used

in previous studies (Klapper et al 2006) and it is expected to be of a primary importance for

transition economies where firms tend to rely more on bank finance rather than capital

markets We also introduce a measure of property rights protection (a one year lag) proxied

by the indicator of effective constraints imposed on the executive branch of the government

and obtained from Polity IV project12 This measure of property rights protection is

9 These results are not reported here to save some space However they can be obtained from authors upon request 10 Here it is important to note that although the financial crisis has started in 2007 in the USA it spread to transition economies in 2008-2009 11 Some studies find a non-monotonic relationship between age and firm decision-making In this study we introduce a squared term of age along with a age variable to capture this possible non-linearity 12 Available from httpwwwsystemicpeaceorgpolitypolity4htm

15

considered to be superior to other indicators including the index of property rights reported

by the Heritage Foundation ndashWall Street Journal (for further discussion see Acemoglu and

Johnson 2005 Glaeser et al 2004 Estrin Korosteleva and Mickieiwcz 2011)

In the present study we also introduce macroeconomic controls including cyclical

economic performance as measured by the one year lag of the GDP annual growth rate

and the level of economic development as proxied by a set of GDP pc dummies denoting

the five quintiles of its distribution to address the problem of potential multicollinearity with the

measure of financial development

Finally we include industry and country controls in all our specifications Introducing

country dummies into analysis allows to control for cross-country heterogeneity

For further definition of all variables their descriptive statistics and correlation matrix

see Tables 1-2

43 Dependent variables

To investigate the effect of a firmrsquos size on its perception of financial constraints we

construct a dummy variable coded as 1 capturing a major and very severe obstacle for

access to finance and 0 otherwise

The firm financing choices are defined by the five individual dependent variables

associated with tobit financial choice equations in the seemingly unrelated regression

equations model

One important thing to mention here is the inability to distinguish between

owninternal funds and external private equity considered as one of the limitations of the

2002-2009 BEEPS dataset In the period under investigation BEEPS offers two questions

which aim to capture the use of equity The first one centres around retained earnings and

the second one shows ownersrsquo contributions and private equity or issued new equity

Following some theoretical considerations discussed in sections 2 and 3 in the context of

SMEs we expect the second element of equity to be primarily comprised of existing ownersrsquo

new contributions rather than private equity

Thus the indicator of financial choices represents a set of five individual dependent

variables including retained earnings contributed earnings private borrowing informal

finance trade credit with each of them constructed as a share in total financing of SMErsquos

investment decisions (see Table 1)

44 Methods

16

In this study we employ a number of estimators to obtain robust results More

specifically we use a probit model to investigate the effect of a firm size and the recent

financial crisis on firmsrsquo perception of financial constraints The effect of a firm size in the

situation of crisis is captured by the introduction of the interaction term between firm size as

proxied by the SME indicator and a financial crisis dummy

We further employ the seemingly unrelated regression equations model combined

with the tobit approach for studying firmsrsquo financial structure

Probit model of perception of financial constraints

In the probit model the probability of a firmrsquos perception of financial constraints as

major(j = 1) can be written as follows

( ) ( )int ++

++

infinminus

minus===

ijitj uXjitiitit ijitjuXjy uX

βα βαππ 212-

)()(2 21exp|Pr

Where ity is our measure of financial constraints as perceived by firms and itX is a

set of our explanatory variables discussed in detail in sections 3-4 Here it is important to

note that the interaction term in a probit model cannot be interpreted in a similar way as in

linear models and disregarding this may lead to misleading estimates of the interaction

effect which is of crucial importance for our study (Norton Wang and Ai 2004) Respectively

for robustness of our results here we follow the framework suggested by Norton Wang and

Ai (2004) to account for the model nonlinearity The adjusted marginal effects for the

interaction term are reported in the note to Table 313

Simultaneous Model of Financing Choices

As mentioned above we next model the choice of all five financing choices explicitly

We also hypothesise (following Isachenkova et al 2011) that firm financing choices are likely

to be determined jointly A standard way of modelling jointly determined indicators is a

system of equations - SURE ndash seemingly unrelated regression equations where equations

are linked only by their errors (Zellner 1962) We therefore model the five types of sources of

finance (internal funds private bank borrowing informal finance trade credit and private

13 We also run a probit regression for a split sample of (1) SMEs and (2) large firms to check the robustness of our results (based on the interaction term) while addressing a problem of multicollinearity between a crisis variable and its interaction term with a SME variable The correlation coefficient between a crisis variable and its interaction term with a SME variable is equal to 93 This can be attributed by the problem of a sample being overrepresented by SMEs which constitute 90 of all surveyed firms The results remain robust and can be available from authors upon request

17

equity) using a SURE framework within which we specify a set of five tobit regressions with

correlated residuals

We employ the STATA cmp module which allows to it Seemingly Unrelated Regressions

using the simulated likelihood method such as the Geweke Hajivassiliou and Keane (GHK)

algorithm (for further discussion see Roodman 2008) We utilise a tobit equation to model

each individual financial choice of firms because our dependent financing choices variables

are continuous but their range is constrained (censored) with a substantial number of

observations either equal to zero denoting those who do not use the respective source of

finance or to 100 showing the opposite Other observations are positive and may produce

many different outcomes (Verbeek 2000) Each tobit equation uses a set of identical

explanatory variables that proxy factors which could possibly be associated with firmrsquos

financing choices including industry and country dummies

We also considered the bias caused by potential interdependence between the choice of

whether to invest and firmrsquos financing choices We accounted for the potential selection bias

by introducing into the financial choices SURE Tobit equations (second stage outcome

equations14) the inverse Millrsquos ratio calculated based on modelling the choice to invest in

fixed assets (first stage or selection equation) To identify the first stage of the Heckman

selection model we chose a variable which is correlated with the first stage dependent

variable (investment decision) but not with the second ones (financing choices) We used the

rate of capacity utilization as part of our identification strategy Capacity utilization shows the

percentage of capital stock in use the higher is the rate the more likely firms will increase

investment Batyaeva and Aukutsionek (2001) show that the rate of capacity utilization is

higher in the group of investing firms than in the group of non-investing firms in Russia15 We

calculated the inverse Millrsquos ratio based on the above selection equation16 and included it as

a control in the second stage SURE Tobit equations The inverse Millrsquos ratio has only proved

to be statistically significant in the private bank loan equation pointing to the potential

selection bias arising from the possibility that the factors determining the decision to invest

might differ from those determining the use of bank financing in purchasing fixed assets

14 We also attempted to estimate an investment equation jointly with Tobit financial choices equations within the SURE framework using However given the overall complexity of the model we failed to do this We proceeded further with a two-stage approach by estimating an investment probit equation and calculating the inverse Millrsquos ratio that we add into the outcome financial choices equations at the second stage of the analysis to test for the selection bias 15 We performed an independent sample t-test to check whether the rate of capacity utilization is statistically significantly higher for investing firms compared to non-investing firms for our sample The null hypothesis of no difference was rejected at 1 level of significance 16 To economize on space we do not report the results of the investment probit equation but they are available from authorsrsquo upon request

18

Finally In Table 6 we attempt to condition the determinants of financing constraints

declared by SMEs on the relative percentage increase of trade credit in total funds used for

real investment As mentioned above in Section 2 the timings of measuring the composition

of financing sources precede by a year the timings of measuring the perceptions of financing

constraints That feature of the BEEPSrsquo design allays a likely concern about the endogeneity

of the relative proportion of trade credit and enables causal inference We too report in thre

note to Table 4 the adjusted marginal effects for the interaction term of the SME dummy with

the trade credit variable

In the next section we discuss our empirical results

5 Empirical Results

Table 3 reports the results of the probit model with the marginal effects for firmsrsquo

perception of financial constraints while Tables 4-5 summarize the results of SURE tobits for

a more detailed breakdown of five financing choices More specifically Table 4 reports the

results based on the whole sample to give a comparative perspective on SMErsquos financing

strategy vis-a-vis large businesses whereas Table 5 reports the results based on a

subsample of small and medium-sized firms to shed some light on their financing choices in

the period of crisis

Perception of financial constraints

Table 3 shows that generally small and medium-sized enterprises feel more financially

constrained with the coefficient for SME dummy in relation to the large firms being positive

and significant which is consistent with our discussion in sections 2-3 However the

coefficient of the interaction term with the Crisis dummy turns out to be negative and

significant in relation to the perception of financial constraints as a major obstacle and it

tends to outweigh the effect of a SME dummy when we calculate marginal effects The effect

of the interaction terms with the crisis remains robust after we adjust for non-linearity using

the framework proposed by Norton Wang and Ai (2004)17 Overall these results confirm

that small and medium-sized enterprises are much less financially constrained during the

crisis years with their perceptions close to those of the large firms This result is a polar

opposite to that obtained for the SMEs in the UK (Fraser 2009) which finds that not only do

SMEs generally feel more financially constrained but they report to be even more so during

17 We also check the robustness of our results to the potential problem of multicollinearity between a crisis dummy and its interaction term with SME by splitting a sample and testing the same specification separately for SMEs and large firms We also perform another robustness check by breaking a SME dummy into three subsequent dummies namely micro- small- and medium-sized firms The difference in perception of financial constraints gets almost eliminated in the case of small firms and is largely reduced in the case of micro firms whereas it is less so for medium-sized firms

19

the last crisis We could explain this striking difference by the peculiarities of the SMEs

functioning in new emerging economies The lower reliance of SMEs on external debt in

good times (as shown by results which are discussed below) gives SMEs some flexibility

during the crisis when formal financial markets dry up Jointly with overall flexibility to make

necessary cost cuts and to restructure a business this overall lower reliance on external

funding and the use of alternative sources of financing makes SMEs feel less financially

constrained under the crisis as compared to larger firms

We also find that a more developed financial sector as proxied by domestic private

credit as proportion of GDP helps ease up financial constraints This is in line with the

general literature suggesting that better functioning financial intermediaries facilitate the risk

amelioration in the presence of problems created by market frictions (Levine 1997 Barth et

al 2006 Barth et al 2008)

Unfortunately we fail to find any significant effect of the property rights protection on

firmsrsquo perception of financial constraints that may be explained by the fact that the effect of a

more developed financial sector is likely to outweigh the effect of the property rights

protection

Finally we also find that foreign ownership and international product certificate may

reduce firmsrsquo borrowing constraints while any pressure from domestic or foreign competition

so is pressure from the customers to innovate will increase firmrsquos perception of financial

constraints as major given that firms envisage the need to secure external funding for RampD

or any other innovation-related activities

Financing choices for investment in fixed assets

The results in Table 4 indicate that small enterprises tend to rely more on internal funds

and less on bank loans but they are no different from larger firms in respect of using informal

funds trade credit or private equity which is generally consistent with our discussion in

Sections 2 and 3 The results of Table 5 suggest however that under crisis small and

medium-sized firms tend to switch to other sources of finance such as trade credit and

ownerrsquos contributed equity and to respectively reduce the reliance on retained earnings

perhaps because they decrease due to the negative impact of crisis internal funds With

regards to our discussion of SMEsrsquo risk management we note that the use of private equity

(ownerrsquos contribution) during the crisis years increases which could indicate that the ownerrsquos

funds are used as a cushion in the period of financial distress

An interesting insight regarding the use of trade credit emerges for SMEs in our

sample although in non-crisis years small and medium-sized businesses are not significantly

different from larger firms in terms of reliance on trade credit SMEs tend to finance a

significantly higher proportion of their fixed asset investment by trade credit than large firms

20

in the period of crisis While the latter finding is partly in line with some other studies ndash such

as Klapper and Randall (2010) using BEEPS data it is in stark contrast with similar studies

of the UK private firms (Rehman 2011) for which the use of trade credit is found to have

dried up in crisis This could partly be due to the passed legislation in the UK tightening trade

credit regulation as the result of the abuse of trade credit by large firms in relation to small

firms which forced many SMEs out of the market

With regards to the other firm-level characteristics international certification makes the

firm rely more on private bank loans and informal finance (Table 5) while SMEs with foreign

ownership rely less on private debt but more on retained earnings Both results are

consistent with our hypotheses discussed above Export-oriented small and medium-sized

businesses tend to have greater reliance on trade credit and they use less of internal funds

We find a non-monotonic relationship between age and private equity with both younger and

older firms being more reliant on this source of funding We find some fragmentary support

for private domestic SMEs relying more on informal finance while tending to use less trade

credit and private equity (Table 5)

Interestingly our results (Tables 4-5) suggest that firms which lack some social

connections with governmental officials proxied by the higher amount of time spent dealing

with government regulations are more likely to rely on informal finance trade credit and

private equity In turn businesses which are connected to governmental officials use more

retained profits to fund investment in fixed assets This may be attributed to their connections

serving as a guarantee from expropriation of assets by all sort of rent-seeking individuals

akin private contracting to secure property rights protection This result should be interpreted

jointly with the property rights protection results We expected that better property rights

protection is likely to facilitate firmsrsquo access to bank loan but we failed to confirm this

Perhaps regardless some attempts at a constitutional level to prevent arbitrary government

(which is proxied by our measure of property rights) expropriation culture is still deeply

embedded in the society of post-communist countries and it may manifest in different ways

Welter and Smallbone (2011) argue that entrepreneurs in transition economies have learnt

how to respond to institutional deficiencies in particular weak property rights protection For

example some businesses experiencing high growth choose to invest in unrelated

businesses instead of growing their core businesses for the reason they do not want to

become too noticeable to attract too much attention of the wrong sort In our instance having

some connections with officials seems also to serve as protection against arbitrary

government or individual rent-seeking that makes businesses more keen on re-investing their

retained profits (see Johnson et al (2002) on the discussion of how more secure property

rights can make small firms reinvest more of their earnings)

10

same time as larger firms use more finance and tend to rely more on external funding they

may be hit harder by financial contraction in the situation of global crises when international

financial markets dry up so preventing larger firms from drawing upon them when required

They are also less flexible and it is more costly for them to restructure and downsize when

they are hit with external shocks Furthermore while SMEs tend to be more flexible in relying

on other sources of finance including trade credit contributed equity and informal finance

the financial structure of larger firms generally tends to be less diversified with a preference

often given to retained profits and bank finance following the pecking order theory Taken

together we may argue that both supply and demand for finance is more affected for larger

firms in the situation of external shocks

Based on the discussion presented in Sections 2 and 31 we further discuss three main

groups of factors which are likely to affect firmsrsquo perception of financial constraints and their

financing choice strategy These are as follows (1) firm size in general and in the period of

crisis (2) other firm- and industry-specific characteristics including foreign ownership export

orientation firmsrsquo social capital and the degree of competition and its pressure on the firm to

develop a new product and (3) country-level institutional parameters including the degree of

protection of property rights and the development of the financial sector

32 Size of the enterprise and the effect of crisis

With regards to the effect of firm size based on the general discussion in the literature

(see sections 2-31) we expect SMEs to be more financially constrained in their access to

external lending and respectively more reliant on internal funds This is due to insufficient

information that the bank can obtain about a particular SME as well as due to a potentially

lower size of collateral However this lower reliance of SMEs on external debt can potentially

be a source of flexibility during the crisis when formal financial markets dry up and when

even large well-established firms have difficulty obtaining bank credit Furthermore following

Atanasova and Wilson (2003 2004) Mateut et al (2006) and Klapper and Randall (2010) we

expect that under tight monetary conditions SMEs in transition economies are more likely to

switch to alternative forms of financing such as trade credit We also hypothesize that SMEs

are more likely to rely on ownersrsquo contributed equity which they tend to accumulate in good

times as part of their risk management strategy to use it as a cushion in the times of financial

distress In summary we expect the difference between the SMEs and large firms in their

reliance on bank finance to diminish during the crisis years and second SMEs to be more

flexible and rely more on other sources of finance such as trade credit and private equity in

the period of financial contractions

11

33 Firm- and industry- level factors

As far as the firm-level and industry-level variables are concerned we expect the

following results first the level of social capital of a firm as proxied by the inverse of the time

spent dealing with government regulations to indicate possible established connections with

public officials can positively affect its access to trade credit Next the industry-level

pressure on a firm from competitors to develop a new product may increase the firmrsquos

chances of obtaining a bank loan as the bank may perceive the firmrsquos operations as more

diversified and less risky (Isachenkova et al 2011) We also expect foreign competition and

the pressure it exerts on a firm innovation capability to play less important role for firm

financing decisions as SMEs are more likely to operate in market niches and they are

unlikely to compete with multinational enterprises In contrast we expect a pressure

originated from customers on a firm to innovate to increase a firmrsquos probability to rely more

on external sources of funding This may be attributed to the fact that a firm does not only

differentiate itself from other firms further with developing a new product but also assures a

demand for this product by responding to the needs of its existing customers The

guaranteed demand for a new product would be one of the most crucial factors taken into

account by bank managers or potential investors in decision-making concerning project

financing Thirdly international product certification may play a similar role with regards to

bank loans increasing the access to external funds Fourth we investigate the effect on the

choice of financing of the firm age with a square term Generally older firms may have

easier access to bank loans as more information is available about them to the lender (Beck

et al 2006 Canton et al 2010) however due to the particulars of the transition period

sometimes older firms may be less economically viable and unable to get a loan therefore

the sign of this coefficient is uncertain here Lastly we also look at the firmrsquos export

orientation which is expected to increase the reliance on bank lending and its ownership

type where we single out foreign and domestic private firms In the case of foreign firms

they are less likely to use private loans and rely instead on retained earnings and intra-

company funds transfers in the case of MNCs

34 Institutional environment

The impact of institutional variables on the financing choices of firms has been of the

utmost interest to economists and policy-makers during the period of transition (see for

example Stijn and Tzioumis 2006 Mitra et al 2008 see also Commander and Svejnar

(2009) for an in-depth and comprehensive analysis of the impact of various business

environment factors on firm performance using BEEPS 2002 - 2005 panel) In our analysis

12

we concentrate on two institutional factors the degree of protection of property rights and the

size of the formal financial sector which have been claimed to be of key importance for firmsrsquo

financing decisions (see Korosteleva and Mickiewicz (2011) for overview of the related

literature) As far as the property rights protection is concerned it is found to play crucial role

for firm growth and access to external finance (Aidis et al 2008 2010 Korosteleva and

Mickiewicz 2011 Estrin Korosteleva and Mickiewicz 2011) In the environment with weak

protection of property rights financial contracts are less likely to be concluded leading to the

underdevelopment of finance and credit rationing with small firms to be disproportionally

affected the most (Acemoglu and Johnson 2005) Beck et al (2004) show that in terms of

access to external finance small firms benefit disproportionally from higher levels of property

rights protection Lack of secure property rights may also discourage SMEs from taking full

advantage of opportunities to invest (Johnson et al 2002) In a survey of private small

manufacturing firms in Poland Russia Ukraine Romania and Slovakia Johnson et al

(2002) find that small firms tend to reinvest less of their earnings when they perceive their

property rights insecure They also find that the effect of the property rights system is of more

paramount importance for entrepreneursrsquo decisions to reinvest their earnings than availability

of formal finance Moreover if property rights are well-protected this lessens the extent of

potential threat of being expropriated by raidersbank lenders in an artificial bankruptcy

procedure which has been quite a significant issue for firms in Russia and other FSU states

(Radygin et al 2005 Sprenger 2002) Based on this we expect that strong property rights

are likely to encourage SMEs to use more debt as well as to use their own funds and

retained profits for investing in investment projects

With regards to the size of the formal finance as measured by the share of private

credit to GDP the relationship between financial depth and financial constraints has been

extensively studied (Beck et al 2006 also see for example Love 2003 who employing a

sample of 36 countries finds that financial development affects firmsrsquo investment by

increasing the availability of external finance) Financial intermediaries facilitate the risk

amelioration in the presence of problems created by information and transaction frictions by

developing expertise in risk assessment and in monitoring (Levine 1997 Barth et al 2006

Barth et al 2008) Developed financial institutions are found to be particularly beneficial for

small firms compared to large ones (Barth et al 2006 Beck et al 2005 2006 2008)

Pissarides et al (2003) show that financial constraints affect SMEs even more than

deficiency of the property rights protection Accordingly the size of the formal financial

system is expected to be positively related to the use of bank finance as a better functioning

financial system should help ease up borrowing constraints

4 Data and Methodology

13

41 Sample

To explore the determinants of the financial structure of small businesses we use the

2002-2009 Business Environment and Enterprise Performance Survey (BEEPS) data6 of

21867 firms covering 26 transition economies of Europe and Central Asia (ECA)7

The sample is primarily comprised of small and medium-sized businesses8 which

account for 893 per cent of the sample The sample is representative in terms of industrial

coverage with the majority of SMEs of the sample operating in manufacturing wholesale

and retailing industries

BEEPS dataset provides rich information on firm characteristics investment

behaviour and firmsrsquo perception of business environment including financial constraints

which are of a primary interest for our investigation of the effect of the recent financial crisis

on firmsrsquo perception of financial constraints Potentially we could use other micro-level data

characterising various domains of business environment captured by firmsrsquo perceptions for

investigating the effects of the institutional settings However using these micro-level

indicators as explanatory variables would make our study plagued with a problem of

endogeneity To avoid this we merge our firm-level data with country-level indicators

characterising various institutional domains The country level data were obtained from the

World Development Indicators (World Bank) and Polity IV databases (for further discussion

see below) Finally the BEEPs dataset contains other useful information which allows us to

shed light of the effect of for example social capital as proxied by the indirect measure of

possible connections with the authorities (see below for the definition of the variable) on firm

financing

42 Variable Definition and Measurement

Explanatory variables

6 This data is a joint project of the European Bank for Reconstruction and Development and World Bank The first survey was launched in 1999 The dataset used in the present study is an unbalanced panel covering the years of 2002 2005 2007-2009 7 The sample includes the following countries Albania Armenia Azerbaijan Belarus Bosnia Bulgaria Croatia Czech Republic Estonia FYROM Georgia Hungary Kazakhstan Kyrgyzstan Latvia Lithuania Moldova Montenegro Poland Romania Russia Serbia Slovakia Slovenia Tajikistan and Ukraine We exclude Uzbekistan as an outlier from our sample We also exclude Turkey as it is not classified as a post-communist country undertaking transition from a planned to a market economy 8 We utilize the EU employment criterion to define small and medium-sized businesses More specifically businesses are defined as micro if they employ 9 and less employees small ndash between 10 and 49 medium ndash between 50 and 249 and large ndash over 250 employees Respectively SMEs are defined as firms employing less than 249 firms

14

To test our main hypothesis of the effect of a firm size on firmsrsquo perception of financial

constraints we introduce a dummy variable denoting small and medium-sized business

coded as 1 if firms are classified as small or medium-sized businesses according to the EU

definition based on the employment criterion For robustness of our results we also use a

continuous variable denoting a size of employment as measured by the natural logarithm of

employment9 The obtained results are consistent with the ones using the SME indicators

To capture the effect of the recent financial crisis we introduce a crisis dummy coded

as 1 if the year of survey is equal to 2008 or 200910

We also introduce a number of firm-level controls which include age of firm11 type of

ownership including private and foreign ownership export orientation and whether a firm

has an internationally certified product all equal to 1 if a business has a respectively listed

characteristic and zero otherwise We also examine the effect of various sources of pressure

on firms to innovate ndash the indicators which are considered to be important for firm investment

decisions Respectively the pressure for innovation may stem from domestic competition

foreign competition and customers To capture the effect of a firmrsquos social capital we

introduce an indicator which indirectly may capture some possible connections of a firm with

authorities It is proxied by time spent by each firm on dealing with government regulations

We assume the less time firms spend dealing with government regulations the more likely

they have some established connections with public officials which allow them to avoid

burdensome regulation procedures

In our study we also introduce a number of country-level variables which characterize

the institutional environment in the countries covered by our sample More specifically we

include an indicator of the financial development as measured by the ratio of domestic credit

to private sector to GDP (one year lag to avoid potential endogeneity) obtained from the

World Bank World Development Indicators (World Bank 2011) This measure has been used

in previous studies (Klapper et al 2006) and it is expected to be of a primary importance for

transition economies where firms tend to rely more on bank finance rather than capital

markets We also introduce a measure of property rights protection (a one year lag) proxied

by the indicator of effective constraints imposed on the executive branch of the government

and obtained from Polity IV project12 This measure of property rights protection is

9 These results are not reported here to save some space However they can be obtained from authors upon request 10 Here it is important to note that although the financial crisis has started in 2007 in the USA it spread to transition economies in 2008-2009 11 Some studies find a non-monotonic relationship between age and firm decision-making In this study we introduce a squared term of age along with a age variable to capture this possible non-linearity 12 Available from httpwwwsystemicpeaceorgpolitypolity4htm

15

considered to be superior to other indicators including the index of property rights reported

by the Heritage Foundation ndashWall Street Journal (for further discussion see Acemoglu and

Johnson 2005 Glaeser et al 2004 Estrin Korosteleva and Mickieiwcz 2011)

In the present study we also introduce macroeconomic controls including cyclical

economic performance as measured by the one year lag of the GDP annual growth rate

and the level of economic development as proxied by a set of GDP pc dummies denoting

the five quintiles of its distribution to address the problem of potential multicollinearity with the

measure of financial development

Finally we include industry and country controls in all our specifications Introducing

country dummies into analysis allows to control for cross-country heterogeneity

For further definition of all variables their descriptive statistics and correlation matrix

see Tables 1-2

43 Dependent variables

To investigate the effect of a firmrsquos size on its perception of financial constraints we

construct a dummy variable coded as 1 capturing a major and very severe obstacle for

access to finance and 0 otherwise

The firm financing choices are defined by the five individual dependent variables

associated with tobit financial choice equations in the seemingly unrelated regression

equations model

One important thing to mention here is the inability to distinguish between

owninternal funds and external private equity considered as one of the limitations of the

2002-2009 BEEPS dataset In the period under investigation BEEPS offers two questions

which aim to capture the use of equity The first one centres around retained earnings and

the second one shows ownersrsquo contributions and private equity or issued new equity

Following some theoretical considerations discussed in sections 2 and 3 in the context of

SMEs we expect the second element of equity to be primarily comprised of existing ownersrsquo

new contributions rather than private equity

Thus the indicator of financial choices represents a set of five individual dependent

variables including retained earnings contributed earnings private borrowing informal

finance trade credit with each of them constructed as a share in total financing of SMErsquos

investment decisions (see Table 1)

44 Methods

16

In this study we employ a number of estimators to obtain robust results More

specifically we use a probit model to investigate the effect of a firm size and the recent

financial crisis on firmsrsquo perception of financial constraints The effect of a firm size in the

situation of crisis is captured by the introduction of the interaction term between firm size as

proxied by the SME indicator and a financial crisis dummy

We further employ the seemingly unrelated regression equations model combined

with the tobit approach for studying firmsrsquo financial structure

Probit model of perception of financial constraints

In the probit model the probability of a firmrsquos perception of financial constraints as

major(j = 1) can be written as follows

( ) ( )int ++

++

infinminus

minus===

ijitj uXjitiitit ijitjuXjy uX

βα βαππ 212-

)()(2 21exp|Pr

Where ity is our measure of financial constraints as perceived by firms and itX is a

set of our explanatory variables discussed in detail in sections 3-4 Here it is important to

note that the interaction term in a probit model cannot be interpreted in a similar way as in

linear models and disregarding this may lead to misleading estimates of the interaction

effect which is of crucial importance for our study (Norton Wang and Ai 2004) Respectively

for robustness of our results here we follow the framework suggested by Norton Wang and

Ai (2004) to account for the model nonlinearity The adjusted marginal effects for the

interaction term are reported in the note to Table 313

Simultaneous Model of Financing Choices

As mentioned above we next model the choice of all five financing choices explicitly

We also hypothesise (following Isachenkova et al 2011) that firm financing choices are likely

to be determined jointly A standard way of modelling jointly determined indicators is a

system of equations - SURE ndash seemingly unrelated regression equations where equations

are linked only by their errors (Zellner 1962) We therefore model the five types of sources of

finance (internal funds private bank borrowing informal finance trade credit and private

13 We also run a probit regression for a split sample of (1) SMEs and (2) large firms to check the robustness of our results (based on the interaction term) while addressing a problem of multicollinearity between a crisis variable and its interaction term with a SME variable The correlation coefficient between a crisis variable and its interaction term with a SME variable is equal to 93 This can be attributed by the problem of a sample being overrepresented by SMEs which constitute 90 of all surveyed firms The results remain robust and can be available from authors upon request

17

equity) using a SURE framework within which we specify a set of five tobit regressions with

correlated residuals

We employ the STATA cmp module which allows to it Seemingly Unrelated Regressions

using the simulated likelihood method such as the Geweke Hajivassiliou and Keane (GHK)

algorithm (for further discussion see Roodman 2008) We utilise a tobit equation to model

each individual financial choice of firms because our dependent financing choices variables

are continuous but their range is constrained (censored) with a substantial number of

observations either equal to zero denoting those who do not use the respective source of

finance or to 100 showing the opposite Other observations are positive and may produce

many different outcomes (Verbeek 2000) Each tobit equation uses a set of identical

explanatory variables that proxy factors which could possibly be associated with firmrsquos

financing choices including industry and country dummies

We also considered the bias caused by potential interdependence between the choice of

whether to invest and firmrsquos financing choices We accounted for the potential selection bias

by introducing into the financial choices SURE Tobit equations (second stage outcome

equations14) the inverse Millrsquos ratio calculated based on modelling the choice to invest in

fixed assets (first stage or selection equation) To identify the first stage of the Heckman

selection model we chose a variable which is correlated with the first stage dependent

variable (investment decision) but not with the second ones (financing choices) We used the

rate of capacity utilization as part of our identification strategy Capacity utilization shows the

percentage of capital stock in use the higher is the rate the more likely firms will increase

investment Batyaeva and Aukutsionek (2001) show that the rate of capacity utilization is

higher in the group of investing firms than in the group of non-investing firms in Russia15 We

calculated the inverse Millrsquos ratio based on the above selection equation16 and included it as

a control in the second stage SURE Tobit equations The inverse Millrsquos ratio has only proved

to be statistically significant in the private bank loan equation pointing to the potential

selection bias arising from the possibility that the factors determining the decision to invest

might differ from those determining the use of bank financing in purchasing fixed assets

14 We also attempted to estimate an investment equation jointly with Tobit financial choices equations within the SURE framework using However given the overall complexity of the model we failed to do this We proceeded further with a two-stage approach by estimating an investment probit equation and calculating the inverse Millrsquos ratio that we add into the outcome financial choices equations at the second stage of the analysis to test for the selection bias 15 We performed an independent sample t-test to check whether the rate of capacity utilization is statistically significantly higher for investing firms compared to non-investing firms for our sample The null hypothesis of no difference was rejected at 1 level of significance 16 To economize on space we do not report the results of the investment probit equation but they are available from authorsrsquo upon request

18

Finally In Table 6 we attempt to condition the determinants of financing constraints

declared by SMEs on the relative percentage increase of trade credit in total funds used for

real investment As mentioned above in Section 2 the timings of measuring the composition

of financing sources precede by a year the timings of measuring the perceptions of financing

constraints That feature of the BEEPSrsquo design allays a likely concern about the endogeneity

of the relative proportion of trade credit and enables causal inference We too report in thre

note to Table 4 the adjusted marginal effects for the interaction term of the SME dummy with

the trade credit variable

In the next section we discuss our empirical results

5 Empirical Results

Table 3 reports the results of the probit model with the marginal effects for firmsrsquo

perception of financial constraints while Tables 4-5 summarize the results of SURE tobits for

a more detailed breakdown of five financing choices More specifically Table 4 reports the

results based on the whole sample to give a comparative perspective on SMErsquos financing

strategy vis-a-vis large businesses whereas Table 5 reports the results based on a

subsample of small and medium-sized firms to shed some light on their financing choices in

the period of crisis

Perception of financial constraints

Table 3 shows that generally small and medium-sized enterprises feel more financially

constrained with the coefficient for SME dummy in relation to the large firms being positive

and significant which is consistent with our discussion in sections 2-3 However the

coefficient of the interaction term with the Crisis dummy turns out to be negative and

significant in relation to the perception of financial constraints as a major obstacle and it

tends to outweigh the effect of a SME dummy when we calculate marginal effects The effect

of the interaction terms with the crisis remains robust after we adjust for non-linearity using

the framework proposed by Norton Wang and Ai (2004)17 Overall these results confirm

that small and medium-sized enterprises are much less financially constrained during the

crisis years with their perceptions close to those of the large firms This result is a polar

opposite to that obtained for the SMEs in the UK (Fraser 2009) which finds that not only do

SMEs generally feel more financially constrained but they report to be even more so during

17 We also check the robustness of our results to the potential problem of multicollinearity between a crisis dummy and its interaction term with SME by splitting a sample and testing the same specification separately for SMEs and large firms We also perform another robustness check by breaking a SME dummy into three subsequent dummies namely micro- small- and medium-sized firms The difference in perception of financial constraints gets almost eliminated in the case of small firms and is largely reduced in the case of micro firms whereas it is less so for medium-sized firms

19

the last crisis We could explain this striking difference by the peculiarities of the SMEs

functioning in new emerging economies The lower reliance of SMEs on external debt in

good times (as shown by results which are discussed below) gives SMEs some flexibility

during the crisis when formal financial markets dry up Jointly with overall flexibility to make

necessary cost cuts and to restructure a business this overall lower reliance on external

funding and the use of alternative sources of financing makes SMEs feel less financially

constrained under the crisis as compared to larger firms

We also find that a more developed financial sector as proxied by domestic private

credit as proportion of GDP helps ease up financial constraints This is in line with the

general literature suggesting that better functioning financial intermediaries facilitate the risk

amelioration in the presence of problems created by market frictions (Levine 1997 Barth et

al 2006 Barth et al 2008)

Unfortunately we fail to find any significant effect of the property rights protection on

firmsrsquo perception of financial constraints that may be explained by the fact that the effect of a

more developed financial sector is likely to outweigh the effect of the property rights

protection

Finally we also find that foreign ownership and international product certificate may

reduce firmsrsquo borrowing constraints while any pressure from domestic or foreign competition

so is pressure from the customers to innovate will increase firmrsquos perception of financial

constraints as major given that firms envisage the need to secure external funding for RampD

or any other innovation-related activities

Financing choices for investment in fixed assets

The results in Table 4 indicate that small enterprises tend to rely more on internal funds

and less on bank loans but they are no different from larger firms in respect of using informal

funds trade credit or private equity which is generally consistent with our discussion in

Sections 2 and 3 The results of Table 5 suggest however that under crisis small and

medium-sized firms tend to switch to other sources of finance such as trade credit and

ownerrsquos contributed equity and to respectively reduce the reliance on retained earnings

perhaps because they decrease due to the negative impact of crisis internal funds With

regards to our discussion of SMEsrsquo risk management we note that the use of private equity

(ownerrsquos contribution) during the crisis years increases which could indicate that the ownerrsquos

funds are used as a cushion in the period of financial distress

An interesting insight regarding the use of trade credit emerges for SMEs in our

sample although in non-crisis years small and medium-sized businesses are not significantly

different from larger firms in terms of reliance on trade credit SMEs tend to finance a

significantly higher proportion of their fixed asset investment by trade credit than large firms

20

in the period of crisis While the latter finding is partly in line with some other studies ndash such

as Klapper and Randall (2010) using BEEPS data it is in stark contrast with similar studies

of the UK private firms (Rehman 2011) for which the use of trade credit is found to have

dried up in crisis This could partly be due to the passed legislation in the UK tightening trade

credit regulation as the result of the abuse of trade credit by large firms in relation to small

firms which forced many SMEs out of the market

With regards to the other firm-level characteristics international certification makes the

firm rely more on private bank loans and informal finance (Table 5) while SMEs with foreign

ownership rely less on private debt but more on retained earnings Both results are

consistent with our hypotheses discussed above Export-oriented small and medium-sized

businesses tend to have greater reliance on trade credit and they use less of internal funds

We find a non-monotonic relationship between age and private equity with both younger and

older firms being more reliant on this source of funding We find some fragmentary support

for private domestic SMEs relying more on informal finance while tending to use less trade

credit and private equity (Table 5)

Interestingly our results (Tables 4-5) suggest that firms which lack some social

connections with governmental officials proxied by the higher amount of time spent dealing

with government regulations are more likely to rely on informal finance trade credit and

private equity In turn businesses which are connected to governmental officials use more

retained profits to fund investment in fixed assets This may be attributed to their connections

serving as a guarantee from expropriation of assets by all sort of rent-seeking individuals

akin private contracting to secure property rights protection This result should be interpreted

jointly with the property rights protection results We expected that better property rights

protection is likely to facilitate firmsrsquo access to bank loan but we failed to confirm this

Perhaps regardless some attempts at a constitutional level to prevent arbitrary government

(which is proxied by our measure of property rights) expropriation culture is still deeply

embedded in the society of post-communist countries and it may manifest in different ways

Welter and Smallbone (2011) argue that entrepreneurs in transition economies have learnt

how to respond to institutional deficiencies in particular weak property rights protection For

example some businesses experiencing high growth choose to invest in unrelated

businesses instead of growing their core businesses for the reason they do not want to

become too noticeable to attract too much attention of the wrong sort In our instance having

some connections with officials seems also to serve as protection against arbitrary

government or individual rent-seeking that makes businesses more keen on re-investing their

retained profits (see Johnson et al (2002) on the discussion of how more secure property

rights can make small firms reinvest more of their earnings)

11

33 Firm- and industry- level factors

As far as the firm-level and industry-level variables are concerned we expect the

following results first the level of social capital of a firm as proxied by the inverse of the time

spent dealing with government regulations to indicate possible established connections with

public officials can positively affect its access to trade credit Next the industry-level

pressure on a firm from competitors to develop a new product may increase the firmrsquos

chances of obtaining a bank loan as the bank may perceive the firmrsquos operations as more

diversified and less risky (Isachenkova et al 2011) We also expect foreign competition and

the pressure it exerts on a firm innovation capability to play less important role for firm

financing decisions as SMEs are more likely to operate in market niches and they are

unlikely to compete with multinational enterprises In contrast we expect a pressure

originated from customers on a firm to innovate to increase a firmrsquos probability to rely more

on external sources of funding This may be attributed to the fact that a firm does not only

differentiate itself from other firms further with developing a new product but also assures a

demand for this product by responding to the needs of its existing customers The

guaranteed demand for a new product would be one of the most crucial factors taken into

account by bank managers or potential investors in decision-making concerning project

financing Thirdly international product certification may play a similar role with regards to

bank loans increasing the access to external funds Fourth we investigate the effect on the

choice of financing of the firm age with a square term Generally older firms may have

easier access to bank loans as more information is available about them to the lender (Beck

et al 2006 Canton et al 2010) however due to the particulars of the transition period

sometimes older firms may be less economically viable and unable to get a loan therefore

the sign of this coefficient is uncertain here Lastly we also look at the firmrsquos export

orientation which is expected to increase the reliance on bank lending and its ownership

type where we single out foreign and domestic private firms In the case of foreign firms

they are less likely to use private loans and rely instead on retained earnings and intra-

company funds transfers in the case of MNCs

34 Institutional environment

The impact of institutional variables on the financing choices of firms has been of the

utmost interest to economists and policy-makers during the period of transition (see for

example Stijn and Tzioumis 2006 Mitra et al 2008 see also Commander and Svejnar

(2009) for an in-depth and comprehensive analysis of the impact of various business

environment factors on firm performance using BEEPS 2002 - 2005 panel) In our analysis

12

we concentrate on two institutional factors the degree of protection of property rights and the

size of the formal financial sector which have been claimed to be of key importance for firmsrsquo

financing decisions (see Korosteleva and Mickiewicz (2011) for overview of the related

literature) As far as the property rights protection is concerned it is found to play crucial role

for firm growth and access to external finance (Aidis et al 2008 2010 Korosteleva and

Mickiewicz 2011 Estrin Korosteleva and Mickiewicz 2011) In the environment with weak

protection of property rights financial contracts are less likely to be concluded leading to the

underdevelopment of finance and credit rationing with small firms to be disproportionally

affected the most (Acemoglu and Johnson 2005) Beck et al (2004) show that in terms of

access to external finance small firms benefit disproportionally from higher levels of property

rights protection Lack of secure property rights may also discourage SMEs from taking full

advantage of opportunities to invest (Johnson et al 2002) In a survey of private small

manufacturing firms in Poland Russia Ukraine Romania and Slovakia Johnson et al

(2002) find that small firms tend to reinvest less of their earnings when they perceive their

property rights insecure They also find that the effect of the property rights system is of more

paramount importance for entrepreneursrsquo decisions to reinvest their earnings than availability

of formal finance Moreover if property rights are well-protected this lessens the extent of

potential threat of being expropriated by raidersbank lenders in an artificial bankruptcy

procedure which has been quite a significant issue for firms in Russia and other FSU states

(Radygin et al 2005 Sprenger 2002) Based on this we expect that strong property rights

are likely to encourage SMEs to use more debt as well as to use their own funds and

retained profits for investing in investment projects

With regards to the size of the formal finance as measured by the share of private

credit to GDP the relationship between financial depth and financial constraints has been

extensively studied (Beck et al 2006 also see for example Love 2003 who employing a

sample of 36 countries finds that financial development affects firmsrsquo investment by

increasing the availability of external finance) Financial intermediaries facilitate the risk

amelioration in the presence of problems created by information and transaction frictions by

developing expertise in risk assessment and in monitoring (Levine 1997 Barth et al 2006

Barth et al 2008) Developed financial institutions are found to be particularly beneficial for

small firms compared to large ones (Barth et al 2006 Beck et al 2005 2006 2008)

Pissarides et al (2003) show that financial constraints affect SMEs even more than

deficiency of the property rights protection Accordingly the size of the formal financial

system is expected to be positively related to the use of bank finance as a better functioning

financial system should help ease up borrowing constraints

4 Data and Methodology

13

41 Sample

To explore the determinants of the financial structure of small businesses we use the

2002-2009 Business Environment and Enterprise Performance Survey (BEEPS) data6 of

21867 firms covering 26 transition economies of Europe and Central Asia (ECA)7

The sample is primarily comprised of small and medium-sized businesses8 which

account for 893 per cent of the sample The sample is representative in terms of industrial

coverage with the majority of SMEs of the sample operating in manufacturing wholesale

and retailing industries

BEEPS dataset provides rich information on firm characteristics investment

behaviour and firmsrsquo perception of business environment including financial constraints

which are of a primary interest for our investigation of the effect of the recent financial crisis

on firmsrsquo perception of financial constraints Potentially we could use other micro-level data

characterising various domains of business environment captured by firmsrsquo perceptions for

investigating the effects of the institutional settings However using these micro-level

indicators as explanatory variables would make our study plagued with a problem of

endogeneity To avoid this we merge our firm-level data with country-level indicators

characterising various institutional domains The country level data were obtained from the

World Development Indicators (World Bank) and Polity IV databases (for further discussion

see below) Finally the BEEPs dataset contains other useful information which allows us to

shed light of the effect of for example social capital as proxied by the indirect measure of

possible connections with the authorities (see below for the definition of the variable) on firm

financing

42 Variable Definition and Measurement

Explanatory variables

6 This data is a joint project of the European Bank for Reconstruction and Development and World Bank The first survey was launched in 1999 The dataset used in the present study is an unbalanced panel covering the years of 2002 2005 2007-2009 7 The sample includes the following countries Albania Armenia Azerbaijan Belarus Bosnia Bulgaria Croatia Czech Republic Estonia FYROM Georgia Hungary Kazakhstan Kyrgyzstan Latvia Lithuania Moldova Montenegro Poland Romania Russia Serbia Slovakia Slovenia Tajikistan and Ukraine We exclude Uzbekistan as an outlier from our sample We also exclude Turkey as it is not classified as a post-communist country undertaking transition from a planned to a market economy 8 We utilize the EU employment criterion to define small and medium-sized businesses More specifically businesses are defined as micro if they employ 9 and less employees small ndash between 10 and 49 medium ndash between 50 and 249 and large ndash over 250 employees Respectively SMEs are defined as firms employing less than 249 firms

14

To test our main hypothesis of the effect of a firm size on firmsrsquo perception of financial

constraints we introduce a dummy variable denoting small and medium-sized business

coded as 1 if firms are classified as small or medium-sized businesses according to the EU

definition based on the employment criterion For robustness of our results we also use a

continuous variable denoting a size of employment as measured by the natural logarithm of

employment9 The obtained results are consistent with the ones using the SME indicators

To capture the effect of the recent financial crisis we introduce a crisis dummy coded

as 1 if the year of survey is equal to 2008 or 200910

We also introduce a number of firm-level controls which include age of firm11 type of

ownership including private and foreign ownership export orientation and whether a firm

has an internationally certified product all equal to 1 if a business has a respectively listed

characteristic and zero otherwise We also examine the effect of various sources of pressure

on firms to innovate ndash the indicators which are considered to be important for firm investment

decisions Respectively the pressure for innovation may stem from domestic competition

foreign competition and customers To capture the effect of a firmrsquos social capital we

introduce an indicator which indirectly may capture some possible connections of a firm with

authorities It is proxied by time spent by each firm on dealing with government regulations

We assume the less time firms spend dealing with government regulations the more likely

they have some established connections with public officials which allow them to avoid

burdensome regulation procedures

In our study we also introduce a number of country-level variables which characterize

the institutional environment in the countries covered by our sample More specifically we

include an indicator of the financial development as measured by the ratio of domestic credit

to private sector to GDP (one year lag to avoid potential endogeneity) obtained from the

World Bank World Development Indicators (World Bank 2011) This measure has been used

in previous studies (Klapper et al 2006) and it is expected to be of a primary importance for

transition economies where firms tend to rely more on bank finance rather than capital

markets We also introduce a measure of property rights protection (a one year lag) proxied

by the indicator of effective constraints imposed on the executive branch of the government

and obtained from Polity IV project12 This measure of property rights protection is

9 These results are not reported here to save some space However they can be obtained from authors upon request 10 Here it is important to note that although the financial crisis has started in 2007 in the USA it spread to transition economies in 2008-2009 11 Some studies find a non-monotonic relationship between age and firm decision-making In this study we introduce a squared term of age along with a age variable to capture this possible non-linearity 12 Available from httpwwwsystemicpeaceorgpolitypolity4htm

15

considered to be superior to other indicators including the index of property rights reported

by the Heritage Foundation ndashWall Street Journal (for further discussion see Acemoglu and

Johnson 2005 Glaeser et al 2004 Estrin Korosteleva and Mickieiwcz 2011)

In the present study we also introduce macroeconomic controls including cyclical

economic performance as measured by the one year lag of the GDP annual growth rate

and the level of economic development as proxied by a set of GDP pc dummies denoting

the five quintiles of its distribution to address the problem of potential multicollinearity with the

measure of financial development

Finally we include industry and country controls in all our specifications Introducing

country dummies into analysis allows to control for cross-country heterogeneity

For further definition of all variables their descriptive statistics and correlation matrix

see Tables 1-2

43 Dependent variables

To investigate the effect of a firmrsquos size on its perception of financial constraints we

construct a dummy variable coded as 1 capturing a major and very severe obstacle for

access to finance and 0 otherwise

The firm financing choices are defined by the five individual dependent variables

associated with tobit financial choice equations in the seemingly unrelated regression

equations model

One important thing to mention here is the inability to distinguish between

owninternal funds and external private equity considered as one of the limitations of the

2002-2009 BEEPS dataset In the period under investigation BEEPS offers two questions

which aim to capture the use of equity The first one centres around retained earnings and

the second one shows ownersrsquo contributions and private equity or issued new equity

Following some theoretical considerations discussed in sections 2 and 3 in the context of

SMEs we expect the second element of equity to be primarily comprised of existing ownersrsquo

new contributions rather than private equity

Thus the indicator of financial choices represents a set of five individual dependent

variables including retained earnings contributed earnings private borrowing informal

finance trade credit with each of them constructed as a share in total financing of SMErsquos

investment decisions (see Table 1)

44 Methods

16

In this study we employ a number of estimators to obtain robust results More

specifically we use a probit model to investigate the effect of a firm size and the recent

financial crisis on firmsrsquo perception of financial constraints The effect of a firm size in the

situation of crisis is captured by the introduction of the interaction term between firm size as

proxied by the SME indicator and a financial crisis dummy

We further employ the seemingly unrelated regression equations model combined

with the tobit approach for studying firmsrsquo financial structure

Probit model of perception of financial constraints

In the probit model the probability of a firmrsquos perception of financial constraints as

major(j = 1) can be written as follows

( ) ( )int ++

++

infinminus

minus===

ijitj uXjitiitit ijitjuXjy uX

βα βαππ 212-

)()(2 21exp|Pr

Where ity is our measure of financial constraints as perceived by firms and itX is a

set of our explanatory variables discussed in detail in sections 3-4 Here it is important to

note that the interaction term in a probit model cannot be interpreted in a similar way as in

linear models and disregarding this may lead to misleading estimates of the interaction

effect which is of crucial importance for our study (Norton Wang and Ai 2004) Respectively

for robustness of our results here we follow the framework suggested by Norton Wang and

Ai (2004) to account for the model nonlinearity The adjusted marginal effects for the

interaction term are reported in the note to Table 313

Simultaneous Model of Financing Choices

As mentioned above we next model the choice of all five financing choices explicitly

We also hypothesise (following Isachenkova et al 2011) that firm financing choices are likely

to be determined jointly A standard way of modelling jointly determined indicators is a

system of equations - SURE ndash seemingly unrelated regression equations where equations

are linked only by their errors (Zellner 1962) We therefore model the five types of sources of

finance (internal funds private bank borrowing informal finance trade credit and private

13 We also run a probit regression for a split sample of (1) SMEs and (2) large firms to check the robustness of our results (based on the interaction term) while addressing a problem of multicollinearity between a crisis variable and its interaction term with a SME variable The correlation coefficient between a crisis variable and its interaction term with a SME variable is equal to 93 This can be attributed by the problem of a sample being overrepresented by SMEs which constitute 90 of all surveyed firms The results remain robust and can be available from authors upon request

17

equity) using a SURE framework within which we specify a set of five tobit regressions with

correlated residuals

We employ the STATA cmp module which allows to it Seemingly Unrelated Regressions

using the simulated likelihood method such as the Geweke Hajivassiliou and Keane (GHK)

algorithm (for further discussion see Roodman 2008) We utilise a tobit equation to model

each individual financial choice of firms because our dependent financing choices variables

are continuous but their range is constrained (censored) with a substantial number of

observations either equal to zero denoting those who do not use the respective source of

finance or to 100 showing the opposite Other observations are positive and may produce

many different outcomes (Verbeek 2000) Each tobit equation uses a set of identical

explanatory variables that proxy factors which could possibly be associated with firmrsquos

financing choices including industry and country dummies

We also considered the bias caused by potential interdependence between the choice of

whether to invest and firmrsquos financing choices We accounted for the potential selection bias

by introducing into the financial choices SURE Tobit equations (second stage outcome

equations14) the inverse Millrsquos ratio calculated based on modelling the choice to invest in

fixed assets (first stage or selection equation) To identify the first stage of the Heckman

selection model we chose a variable which is correlated with the first stage dependent

variable (investment decision) but not with the second ones (financing choices) We used the

rate of capacity utilization as part of our identification strategy Capacity utilization shows the

percentage of capital stock in use the higher is the rate the more likely firms will increase

investment Batyaeva and Aukutsionek (2001) show that the rate of capacity utilization is

higher in the group of investing firms than in the group of non-investing firms in Russia15 We

calculated the inverse Millrsquos ratio based on the above selection equation16 and included it as

a control in the second stage SURE Tobit equations The inverse Millrsquos ratio has only proved

to be statistically significant in the private bank loan equation pointing to the potential

selection bias arising from the possibility that the factors determining the decision to invest

might differ from those determining the use of bank financing in purchasing fixed assets

14 We also attempted to estimate an investment equation jointly with Tobit financial choices equations within the SURE framework using However given the overall complexity of the model we failed to do this We proceeded further with a two-stage approach by estimating an investment probit equation and calculating the inverse Millrsquos ratio that we add into the outcome financial choices equations at the second stage of the analysis to test for the selection bias 15 We performed an independent sample t-test to check whether the rate of capacity utilization is statistically significantly higher for investing firms compared to non-investing firms for our sample The null hypothesis of no difference was rejected at 1 level of significance 16 To economize on space we do not report the results of the investment probit equation but they are available from authorsrsquo upon request

18

Finally In Table 6 we attempt to condition the determinants of financing constraints

declared by SMEs on the relative percentage increase of trade credit in total funds used for

real investment As mentioned above in Section 2 the timings of measuring the composition

of financing sources precede by a year the timings of measuring the perceptions of financing

constraints That feature of the BEEPSrsquo design allays a likely concern about the endogeneity

of the relative proportion of trade credit and enables causal inference We too report in thre

note to Table 4 the adjusted marginal effects for the interaction term of the SME dummy with

the trade credit variable

In the next section we discuss our empirical results

5 Empirical Results

Table 3 reports the results of the probit model with the marginal effects for firmsrsquo

perception of financial constraints while Tables 4-5 summarize the results of SURE tobits for

a more detailed breakdown of five financing choices More specifically Table 4 reports the

results based on the whole sample to give a comparative perspective on SMErsquos financing

strategy vis-a-vis large businesses whereas Table 5 reports the results based on a

subsample of small and medium-sized firms to shed some light on their financing choices in

the period of crisis

Perception of financial constraints

Table 3 shows that generally small and medium-sized enterprises feel more financially

constrained with the coefficient for SME dummy in relation to the large firms being positive

and significant which is consistent with our discussion in sections 2-3 However the

coefficient of the interaction term with the Crisis dummy turns out to be negative and

significant in relation to the perception of financial constraints as a major obstacle and it

tends to outweigh the effect of a SME dummy when we calculate marginal effects The effect

of the interaction terms with the crisis remains robust after we adjust for non-linearity using

the framework proposed by Norton Wang and Ai (2004)17 Overall these results confirm

that small and medium-sized enterprises are much less financially constrained during the

crisis years with their perceptions close to those of the large firms This result is a polar

opposite to that obtained for the SMEs in the UK (Fraser 2009) which finds that not only do

SMEs generally feel more financially constrained but they report to be even more so during

17 We also check the robustness of our results to the potential problem of multicollinearity between a crisis dummy and its interaction term with SME by splitting a sample and testing the same specification separately for SMEs and large firms We also perform another robustness check by breaking a SME dummy into three subsequent dummies namely micro- small- and medium-sized firms The difference in perception of financial constraints gets almost eliminated in the case of small firms and is largely reduced in the case of micro firms whereas it is less so for medium-sized firms

19

the last crisis We could explain this striking difference by the peculiarities of the SMEs

functioning in new emerging economies The lower reliance of SMEs on external debt in

good times (as shown by results which are discussed below) gives SMEs some flexibility

during the crisis when formal financial markets dry up Jointly with overall flexibility to make

necessary cost cuts and to restructure a business this overall lower reliance on external

funding and the use of alternative sources of financing makes SMEs feel less financially

constrained under the crisis as compared to larger firms

We also find that a more developed financial sector as proxied by domestic private

credit as proportion of GDP helps ease up financial constraints This is in line with the

general literature suggesting that better functioning financial intermediaries facilitate the risk

amelioration in the presence of problems created by market frictions (Levine 1997 Barth et

al 2006 Barth et al 2008)

Unfortunately we fail to find any significant effect of the property rights protection on

firmsrsquo perception of financial constraints that may be explained by the fact that the effect of a

more developed financial sector is likely to outweigh the effect of the property rights

protection

Finally we also find that foreign ownership and international product certificate may

reduce firmsrsquo borrowing constraints while any pressure from domestic or foreign competition

so is pressure from the customers to innovate will increase firmrsquos perception of financial

constraints as major given that firms envisage the need to secure external funding for RampD

or any other innovation-related activities

Financing choices for investment in fixed assets

The results in Table 4 indicate that small enterprises tend to rely more on internal funds

and less on bank loans but they are no different from larger firms in respect of using informal

funds trade credit or private equity which is generally consistent with our discussion in

Sections 2 and 3 The results of Table 5 suggest however that under crisis small and

medium-sized firms tend to switch to other sources of finance such as trade credit and

ownerrsquos contributed equity and to respectively reduce the reliance on retained earnings

perhaps because they decrease due to the negative impact of crisis internal funds With

regards to our discussion of SMEsrsquo risk management we note that the use of private equity

(ownerrsquos contribution) during the crisis years increases which could indicate that the ownerrsquos

funds are used as a cushion in the period of financial distress

An interesting insight regarding the use of trade credit emerges for SMEs in our

sample although in non-crisis years small and medium-sized businesses are not significantly

different from larger firms in terms of reliance on trade credit SMEs tend to finance a

significantly higher proportion of their fixed asset investment by trade credit than large firms

20

in the period of crisis While the latter finding is partly in line with some other studies ndash such

as Klapper and Randall (2010) using BEEPS data it is in stark contrast with similar studies

of the UK private firms (Rehman 2011) for which the use of trade credit is found to have

dried up in crisis This could partly be due to the passed legislation in the UK tightening trade

credit regulation as the result of the abuse of trade credit by large firms in relation to small

firms which forced many SMEs out of the market

With regards to the other firm-level characteristics international certification makes the

firm rely more on private bank loans and informal finance (Table 5) while SMEs with foreign

ownership rely less on private debt but more on retained earnings Both results are

consistent with our hypotheses discussed above Export-oriented small and medium-sized

businesses tend to have greater reliance on trade credit and they use less of internal funds

We find a non-monotonic relationship between age and private equity with both younger and

older firms being more reliant on this source of funding We find some fragmentary support

for private domestic SMEs relying more on informal finance while tending to use less trade

credit and private equity (Table 5)

Interestingly our results (Tables 4-5) suggest that firms which lack some social

connections with governmental officials proxied by the higher amount of time spent dealing

with government regulations are more likely to rely on informal finance trade credit and

private equity In turn businesses which are connected to governmental officials use more

retained profits to fund investment in fixed assets This may be attributed to their connections

serving as a guarantee from expropriation of assets by all sort of rent-seeking individuals

akin private contracting to secure property rights protection This result should be interpreted

jointly with the property rights protection results We expected that better property rights

protection is likely to facilitate firmsrsquo access to bank loan but we failed to confirm this

Perhaps regardless some attempts at a constitutional level to prevent arbitrary government

(which is proxied by our measure of property rights) expropriation culture is still deeply

embedded in the society of post-communist countries and it may manifest in different ways

Welter and Smallbone (2011) argue that entrepreneurs in transition economies have learnt

how to respond to institutional deficiencies in particular weak property rights protection For

example some businesses experiencing high growth choose to invest in unrelated

businesses instead of growing their core businesses for the reason they do not want to

become too noticeable to attract too much attention of the wrong sort In our instance having

some connections with officials seems also to serve as protection against arbitrary

government or individual rent-seeking that makes businesses more keen on re-investing their

retained profits (see Johnson et al (2002) on the discussion of how more secure property

rights can make small firms reinvest more of their earnings)

12

we concentrate on two institutional factors the degree of protection of property rights and the

size of the formal financial sector which have been claimed to be of key importance for firmsrsquo

financing decisions (see Korosteleva and Mickiewicz (2011) for overview of the related

literature) As far as the property rights protection is concerned it is found to play crucial role

for firm growth and access to external finance (Aidis et al 2008 2010 Korosteleva and

Mickiewicz 2011 Estrin Korosteleva and Mickiewicz 2011) In the environment with weak

protection of property rights financial contracts are less likely to be concluded leading to the

underdevelopment of finance and credit rationing with small firms to be disproportionally

affected the most (Acemoglu and Johnson 2005) Beck et al (2004) show that in terms of

access to external finance small firms benefit disproportionally from higher levels of property

rights protection Lack of secure property rights may also discourage SMEs from taking full

advantage of opportunities to invest (Johnson et al 2002) In a survey of private small

manufacturing firms in Poland Russia Ukraine Romania and Slovakia Johnson et al

(2002) find that small firms tend to reinvest less of their earnings when they perceive their

property rights insecure They also find that the effect of the property rights system is of more

paramount importance for entrepreneursrsquo decisions to reinvest their earnings than availability

of formal finance Moreover if property rights are well-protected this lessens the extent of

potential threat of being expropriated by raidersbank lenders in an artificial bankruptcy

procedure which has been quite a significant issue for firms in Russia and other FSU states

(Radygin et al 2005 Sprenger 2002) Based on this we expect that strong property rights

are likely to encourage SMEs to use more debt as well as to use their own funds and

retained profits for investing in investment projects

With regards to the size of the formal finance as measured by the share of private

credit to GDP the relationship between financial depth and financial constraints has been

extensively studied (Beck et al 2006 also see for example Love 2003 who employing a

sample of 36 countries finds that financial development affects firmsrsquo investment by

increasing the availability of external finance) Financial intermediaries facilitate the risk

amelioration in the presence of problems created by information and transaction frictions by

developing expertise in risk assessment and in monitoring (Levine 1997 Barth et al 2006

Barth et al 2008) Developed financial institutions are found to be particularly beneficial for

small firms compared to large ones (Barth et al 2006 Beck et al 2005 2006 2008)

Pissarides et al (2003) show that financial constraints affect SMEs even more than

deficiency of the property rights protection Accordingly the size of the formal financial

system is expected to be positively related to the use of bank finance as a better functioning

financial system should help ease up borrowing constraints

4 Data and Methodology

13

41 Sample

To explore the determinants of the financial structure of small businesses we use the

2002-2009 Business Environment and Enterprise Performance Survey (BEEPS) data6 of

21867 firms covering 26 transition economies of Europe and Central Asia (ECA)7

The sample is primarily comprised of small and medium-sized businesses8 which

account for 893 per cent of the sample The sample is representative in terms of industrial

coverage with the majority of SMEs of the sample operating in manufacturing wholesale

and retailing industries

BEEPS dataset provides rich information on firm characteristics investment

behaviour and firmsrsquo perception of business environment including financial constraints

which are of a primary interest for our investigation of the effect of the recent financial crisis

on firmsrsquo perception of financial constraints Potentially we could use other micro-level data

characterising various domains of business environment captured by firmsrsquo perceptions for

investigating the effects of the institutional settings However using these micro-level

indicators as explanatory variables would make our study plagued with a problem of

endogeneity To avoid this we merge our firm-level data with country-level indicators

characterising various institutional domains The country level data were obtained from the

World Development Indicators (World Bank) and Polity IV databases (for further discussion

see below) Finally the BEEPs dataset contains other useful information which allows us to

shed light of the effect of for example social capital as proxied by the indirect measure of

possible connections with the authorities (see below for the definition of the variable) on firm

financing

42 Variable Definition and Measurement

Explanatory variables

6 This data is a joint project of the European Bank for Reconstruction and Development and World Bank The first survey was launched in 1999 The dataset used in the present study is an unbalanced panel covering the years of 2002 2005 2007-2009 7 The sample includes the following countries Albania Armenia Azerbaijan Belarus Bosnia Bulgaria Croatia Czech Republic Estonia FYROM Georgia Hungary Kazakhstan Kyrgyzstan Latvia Lithuania Moldova Montenegro Poland Romania Russia Serbia Slovakia Slovenia Tajikistan and Ukraine We exclude Uzbekistan as an outlier from our sample We also exclude Turkey as it is not classified as a post-communist country undertaking transition from a planned to a market economy 8 We utilize the EU employment criterion to define small and medium-sized businesses More specifically businesses are defined as micro if they employ 9 and less employees small ndash between 10 and 49 medium ndash between 50 and 249 and large ndash over 250 employees Respectively SMEs are defined as firms employing less than 249 firms

14

To test our main hypothesis of the effect of a firm size on firmsrsquo perception of financial

constraints we introduce a dummy variable denoting small and medium-sized business

coded as 1 if firms are classified as small or medium-sized businesses according to the EU

definition based on the employment criterion For robustness of our results we also use a

continuous variable denoting a size of employment as measured by the natural logarithm of

employment9 The obtained results are consistent with the ones using the SME indicators

To capture the effect of the recent financial crisis we introduce a crisis dummy coded

as 1 if the year of survey is equal to 2008 or 200910

We also introduce a number of firm-level controls which include age of firm11 type of

ownership including private and foreign ownership export orientation and whether a firm

has an internationally certified product all equal to 1 if a business has a respectively listed

characteristic and zero otherwise We also examine the effect of various sources of pressure

on firms to innovate ndash the indicators which are considered to be important for firm investment

decisions Respectively the pressure for innovation may stem from domestic competition

foreign competition and customers To capture the effect of a firmrsquos social capital we

introduce an indicator which indirectly may capture some possible connections of a firm with

authorities It is proxied by time spent by each firm on dealing with government regulations

We assume the less time firms spend dealing with government regulations the more likely

they have some established connections with public officials which allow them to avoid

burdensome regulation procedures

In our study we also introduce a number of country-level variables which characterize

the institutional environment in the countries covered by our sample More specifically we

include an indicator of the financial development as measured by the ratio of domestic credit

to private sector to GDP (one year lag to avoid potential endogeneity) obtained from the

World Bank World Development Indicators (World Bank 2011) This measure has been used

in previous studies (Klapper et al 2006) and it is expected to be of a primary importance for

transition economies where firms tend to rely more on bank finance rather than capital

markets We also introduce a measure of property rights protection (a one year lag) proxied

by the indicator of effective constraints imposed on the executive branch of the government

and obtained from Polity IV project12 This measure of property rights protection is

9 These results are not reported here to save some space However they can be obtained from authors upon request 10 Here it is important to note that although the financial crisis has started in 2007 in the USA it spread to transition economies in 2008-2009 11 Some studies find a non-monotonic relationship between age and firm decision-making In this study we introduce a squared term of age along with a age variable to capture this possible non-linearity 12 Available from httpwwwsystemicpeaceorgpolitypolity4htm

15

considered to be superior to other indicators including the index of property rights reported

by the Heritage Foundation ndashWall Street Journal (for further discussion see Acemoglu and

Johnson 2005 Glaeser et al 2004 Estrin Korosteleva and Mickieiwcz 2011)

In the present study we also introduce macroeconomic controls including cyclical

economic performance as measured by the one year lag of the GDP annual growth rate

and the level of economic development as proxied by a set of GDP pc dummies denoting

the five quintiles of its distribution to address the problem of potential multicollinearity with the

measure of financial development

Finally we include industry and country controls in all our specifications Introducing

country dummies into analysis allows to control for cross-country heterogeneity

For further definition of all variables their descriptive statistics and correlation matrix

see Tables 1-2

43 Dependent variables

To investigate the effect of a firmrsquos size on its perception of financial constraints we

construct a dummy variable coded as 1 capturing a major and very severe obstacle for

access to finance and 0 otherwise

The firm financing choices are defined by the five individual dependent variables

associated with tobit financial choice equations in the seemingly unrelated regression

equations model

One important thing to mention here is the inability to distinguish between

owninternal funds and external private equity considered as one of the limitations of the

2002-2009 BEEPS dataset In the period under investigation BEEPS offers two questions

which aim to capture the use of equity The first one centres around retained earnings and

the second one shows ownersrsquo contributions and private equity or issued new equity

Following some theoretical considerations discussed in sections 2 and 3 in the context of

SMEs we expect the second element of equity to be primarily comprised of existing ownersrsquo

new contributions rather than private equity

Thus the indicator of financial choices represents a set of five individual dependent

variables including retained earnings contributed earnings private borrowing informal

finance trade credit with each of them constructed as a share in total financing of SMErsquos

investment decisions (see Table 1)

44 Methods

16

In this study we employ a number of estimators to obtain robust results More

specifically we use a probit model to investigate the effect of a firm size and the recent

financial crisis on firmsrsquo perception of financial constraints The effect of a firm size in the

situation of crisis is captured by the introduction of the interaction term between firm size as

proxied by the SME indicator and a financial crisis dummy

We further employ the seemingly unrelated regression equations model combined

with the tobit approach for studying firmsrsquo financial structure

Probit model of perception of financial constraints

In the probit model the probability of a firmrsquos perception of financial constraints as

major(j = 1) can be written as follows

( ) ( )int ++

++

infinminus

minus===

ijitj uXjitiitit ijitjuXjy uX

βα βαππ 212-

)()(2 21exp|Pr

Where ity is our measure of financial constraints as perceived by firms and itX is a

set of our explanatory variables discussed in detail in sections 3-4 Here it is important to

note that the interaction term in a probit model cannot be interpreted in a similar way as in

linear models and disregarding this may lead to misleading estimates of the interaction

effect which is of crucial importance for our study (Norton Wang and Ai 2004) Respectively

for robustness of our results here we follow the framework suggested by Norton Wang and

Ai (2004) to account for the model nonlinearity The adjusted marginal effects for the

interaction term are reported in the note to Table 313

Simultaneous Model of Financing Choices

As mentioned above we next model the choice of all five financing choices explicitly

We also hypothesise (following Isachenkova et al 2011) that firm financing choices are likely

to be determined jointly A standard way of modelling jointly determined indicators is a

system of equations - SURE ndash seemingly unrelated regression equations where equations

are linked only by their errors (Zellner 1962) We therefore model the five types of sources of

finance (internal funds private bank borrowing informal finance trade credit and private

13 We also run a probit regression for a split sample of (1) SMEs and (2) large firms to check the robustness of our results (based on the interaction term) while addressing a problem of multicollinearity between a crisis variable and its interaction term with a SME variable The correlation coefficient between a crisis variable and its interaction term with a SME variable is equal to 93 This can be attributed by the problem of a sample being overrepresented by SMEs which constitute 90 of all surveyed firms The results remain robust and can be available from authors upon request

17

equity) using a SURE framework within which we specify a set of five tobit regressions with

correlated residuals

We employ the STATA cmp module which allows to it Seemingly Unrelated Regressions

using the simulated likelihood method such as the Geweke Hajivassiliou and Keane (GHK)

algorithm (for further discussion see Roodman 2008) We utilise a tobit equation to model

each individual financial choice of firms because our dependent financing choices variables

are continuous but their range is constrained (censored) with a substantial number of

observations either equal to zero denoting those who do not use the respective source of

finance or to 100 showing the opposite Other observations are positive and may produce

many different outcomes (Verbeek 2000) Each tobit equation uses a set of identical

explanatory variables that proxy factors which could possibly be associated with firmrsquos

financing choices including industry and country dummies

We also considered the bias caused by potential interdependence between the choice of

whether to invest and firmrsquos financing choices We accounted for the potential selection bias

by introducing into the financial choices SURE Tobit equations (second stage outcome

equations14) the inverse Millrsquos ratio calculated based on modelling the choice to invest in

fixed assets (first stage or selection equation) To identify the first stage of the Heckman

selection model we chose a variable which is correlated with the first stage dependent

variable (investment decision) but not with the second ones (financing choices) We used the

rate of capacity utilization as part of our identification strategy Capacity utilization shows the

percentage of capital stock in use the higher is the rate the more likely firms will increase

investment Batyaeva and Aukutsionek (2001) show that the rate of capacity utilization is

higher in the group of investing firms than in the group of non-investing firms in Russia15 We

calculated the inverse Millrsquos ratio based on the above selection equation16 and included it as

a control in the second stage SURE Tobit equations The inverse Millrsquos ratio has only proved

to be statistically significant in the private bank loan equation pointing to the potential

selection bias arising from the possibility that the factors determining the decision to invest

might differ from those determining the use of bank financing in purchasing fixed assets

14 We also attempted to estimate an investment equation jointly with Tobit financial choices equations within the SURE framework using However given the overall complexity of the model we failed to do this We proceeded further with a two-stage approach by estimating an investment probit equation and calculating the inverse Millrsquos ratio that we add into the outcome financial choices equations at the second stage of the analysis to test for the selection bias 15 We performed an independent sample t-test to check whether the rate of capacity utilization is statistically significantly higher for investing firms compared to non-investing firms for our sample The null hypothesis of no difference was rejected at 1 level of significance 16 To economize on space we do not report the results of the investment probit equation but they are available from authorsrsquo upon request

18

Finally In Table 6 we attempt to condition the determinants of financing constraints

declared by SMEs on the relative percentage increase of trade credit in total funds used for

real investment As mentioned above in Section 2 the timings of measuring the composition

of financing sources precede by a year the timings of measuring the perceptions of financing

constraints That feature of the BEEPSrsquo design allays a likely concern about the endogeneity

of the relative proportion of trade credit and enables causal inference We too report in thre

note to Table 4 the adjusted marginal effects for the interaction term of the SME dummy with

the trade credit variable

In the next section we discuss our empirical results

5 Empirical Results

Table 3 reports the results of the probit model with the marginal effects for firmsrsquo

perception of financial constraints while Tables 4-5 summarize the results of SURE tobits for

a more detailed breakdown of five financing choices More specifically Table 4 reports the

results based on the whole sample to give a comparative perspective on SMErsquos financing

strategy vis-a-vis large businesses whereas Table 5 reports the results based on a

subsample of small and medium-sized firms to shed some light on their financing choices in

the period of crisis

Perception of financial constraints

Table 3 shows that generally small and medium-sized enterprises feel more financially

constrained with the coefficient for SME dummy in relation to the large firms being positive

and significant which is consistent with our discussion in sections 2-3 However the

coefficient of the interaction term with the Crisis dummy turns out to be negative and

significant in relation to the perception of financial constraints as a major obstacle and it

tends to outweigh the effect of a SME dummy when we calculate marginal effects The effect

of the interaction terms with the crisis remains robust after we adjust for non-linearity using

the framework proposed by Norton Wang and Ai (2004)17 Overall these results confirm

that small and medium-sized enterprises are much less financially constrained during the

crisis years with their perceptions close to those of the large firms This result is a polar

opposite to that obtained for the SMEs in the UK (Fraser 2009) which finds that not only do

SMEs generally feel more financially constrained but they report to be even more so during

17 We also check the robustness of our results to the potential problem of multicollinearity between a crisis dummy and its interaction term with SME by splitting a sample and testing the same specification separately for SMEs and large firms We also perform another robustness check by breaking a SME dummy into three subsequent dummies namely micro- small- and medium-sized firms The difference in perception of financial constraints gets almost eliminated in the case of small firms and is largely reduced in the case of micro firms whereas it is less so for medium-sized firms

19

the last crisis We could explain this striking difference by the peculiarities of the SMEs

functioning in new emerging economies The lower reliance of SMEs on external debt in

good times (as shown by results which are discussed below) gives SMEs some flexibility

during the crisis when formal financial markets dry up Jointly with overall flexibility to make

necessary cost cuts and to restructure a business this overall lower reliance on external

funding and the use of alternative sources of financing makes SMEs feel less financially

constrained under the crisis as compared to larger firms

We also find that a more developed financial sector as proxied by domestic private

credit as proportion of GDP helps ease up financial constraints This is in line with the

general literature suggesting that better functioning financial intermediaries facilitate the risk

amelioration in the presence of problems created by market frictions (Levine 1997 Barth et

al 2006 Barth et al 2008)

Unfortunately we fail to find any significant effect of the property rights protection on

firmsrsquo perception of financial constraints that may be explained by the fact that the effect of a

more developed financial sector is likely to outweigh the effect of the property rights

protection

Finally we also find that foreign ownership and international product certificate may

reduce firmsrsquo borrowing constraints while any pressure from domestic or foreign competition

so is pressure from the customers to innovate will increase firmrsquos perception of financial

constraints as major given that firms envisage the need to secure external funding for RampD

or any other innovation-related activities

Financing choices for investment in fixed assets

The results in Table 4 indicate that small enterprises tend to rely more on internal funds

and less on bank loans but they are no different from larger firms in respect of using informal

funds trade credit or private equity which is generally consistent with our discussion in

Sections 2 and 3 The results of Table 5 suggest however that under crisis small and

medium-sized firms tend to switch to other sources of finance such as trade credit and

ownerrsquos contributed equity and to respectively reduce the reliance on retained earnings

perhaps because they decrease due to the negative impact of crisis internal funds With

regards to our discussion of SMEsrsquo risk management we note that the use of private equity

(ownerrsquos contribution) during the crisis years increases which could indicate that the ownerrsquos

funds are used as a cushion in the period of financial distress

An interesting insight regarding the use of trade credit emerges for SMEs in our

sample although in non-crisis years small and medium-sized businesses are not significantly

different from larger firms in terms of reliance on trade credit SMEs tend to finance a

significantly higher proportion of their fixed asset investment by trade credit than large firms

20

in the period of crisis While the latter finding is partly in line with some other studies ndash such

as Klapper and Randall (2010) using BEEPS data it is in stark contrast with similar studies

of the UK private firms (Rehman 2011) for which the use of trade credit is found to have

dried up in crisis This could partly be due to the passed legislation in the UK tightening trade

credit regulation as the result of the abuse of trade credit by large firms in relation to small

firms which forced many SMEs out of the market

With regards to the other firm-level characteristics international certification makes the

firm rely more on private bank loans and informal finance (Table 5) while SMEs with foreign

ownership rely less on private debt but more on retained earnings Both results are

consistent with our hypotheses discussed above Export-oriented small and medium-sized

businesses tend to have greater reliance on trade credit and they use less of internal funds

We find a non-monotonic relationship between age and private equity with both younger and

older firms being more reliant on this source of funding We find some fragmentary support

for private domestic SMEs relying more on informal finance while tending to use less trade

credit and private equity (Table 5)

Interestingly our results (Tables 4-5) suggest that firms which lack some social

connections with governmental officials proxied by the higher amount of time spent dealing

with government regulations are more likely to rely on informal finance trade credit and

private equity In turn businesses which are connected to governmental officials use more

retained profits to fund investment in fixed assets This may be attributed to their connections

serving as a guarantee from expropriation of assets by all sort of rent-seeking individuals

akin private contracting to secure property rights protection This result should be interpreted

jointly with the property rights protection results We expected that better property rights

protection is likely to facilitate firmsrsquo access to bank loan but we failed to confirm this

Perhaps regardless some attempts at a constitutional level to prevent arbitrary government

(which is proxied by our measure of property rights) expropriation culture is still deeply

embedded in the society of post-communist countries and it may manifest in different ways

Welter and Smallbone (2011) argue that entrepreneurs in transition economies have learnt

how to respond to institutional deficiencies in particular weak property rights protection For

example some businesses experiencing high growth choose to invest in unrelated

businesses instead of growing their core businesses for the reason they do not want to

become too noticeable to attract too much attention of the wrong sort In our instance having

some connections with officials seems also to serve as protection against arbitrary

government or individual rent-seeking that makes businesses more keen on re-investing their

retained profits (see Johnson et al (2002) on the discussion of how more secure property

rights can make small firms reinvest more of their earnings)

13

41 Sample

To explore the determinants of the financial structure of small businesses we use the

2002-2009 Business Environment and Enterprise Performance Survey (BEEPS) data6 of

21867 firms covering 26 transition economies of Europe and Central Asia (ECA)7

The sample is primarily comprised of small and medium-sized businesses8 which

account for 893 per cent of the sample The sample is representative in terms of industrial

coverage with the majority of SMEs of the sample operating in manufacturing wholesale

and retailing industries

BEEPS dataset provides rich information on firm characteristics investment

behaviour and firmsrsquo perception of business environment including financial constraints

which are of a primary interest for our investigation of the effect of the recent financial crisis

on firmsrsquo perception of financial constraints Potentially we could use other micro-level data

characterising various domains of business environment captured by firmsrsquo perceptions for

investigating the effects of the institutional settings However using these micro-level

indicators as explanatory variables would make our study plagued with a problem of

endogeneity To avoid this we merge our firm-level data with country-level indicators

characterising various institutional domains The country level data were obtained from the

World Development Indicators (World Bank) and Polity IV databases (for further discussion

see below) Finally the BEEPs dataset contains other useful information which allows us to

shed light of the effect of for example social capital as proxied by the indirect measure of

possible connections with the authorities (see below for the definition of the variable) on firm

financing

42 Variable Definition and Measurement

Explanatory variables

6 This data is a joint project of the European Bank for Reconstruction and Development and World Bank The first survey was launched in 1999 The dataset used in the present study is an unbalanced panel covering the years of 2002 2005 2007-2009 7 The sample includes the following countries Albania Armenia Azerbaijan Belarus Bosnia Bulgaria Croatia Czech Republic Estonia FYROM Georgia Hungary Kazakhstan Kyrgyzstan Latvia Lithuania Moldova Montenegro Poland Romania Russia Serbia Slovakia Slovenia Tajikistan and Ukraine We exclude Uzbekistan as an outlier from our sample We also exclude Turkey as it is not classified as a post-communist country undertaking transition from a planned to a market economy 8 We utilize the EU employment criterion to define small and medium-sized businesses More specifically businesses are defined as micro if they employ 9 and less employees small ndash between 10 and 49 medium ndash between 50 and 249 and large ndash over 250 employees Respectively SMEs are defined as firms employing less than 249 firms

14

To test our main hypothesis of the effect of a firm size on firmsrsquo perception of financial

constraints we introduce a dummy variable denoting small and medium-sized business

coded as 1 if firms are classified as small or medium-sized businesses according to the EU

definition based on the employment criterion For robustness of our results we also use a

continuous variable denoting a size of employment as measured by the natural logarithm of

employment9 The obtained results are consistent with the ones using the SME indicators

To capture the effect of the recent financial crisis we introduce a crisis dummy coded

as 1 if the year of survey is equal to 2008 or 200910

We also introduce a number of firm-level controls which include age of firm11 type of

ownership including private and foreign ownership export orientation and whether a firm

has an internationally certified product all equal to 1 if a business has a respectively listed

characteristic and zero otherwise We also examine the effect of various sources of pressure

on firms to innovate ndash the indicators which are considered to be important for firm investment

decisions Respectively the pressure for innovation may stem from domestic competition

foreign competition and customers To capture the effect of a firmrsquos social capital we

introduce an indicator which indirectly may capture some possible connections of a firm with

authorities It is proxied by time spent by each firm on dealing with government regulations

We assume the less time firms spend dealing with government regulations the more likely

they have some established connections with public officials which allow them to avoid

burdensome regulation procedures

In our study we also introduce a number of country-level variables which characterize

the institutional environment in the countries covered by our sample More specifically we

include an indicator of the financial development as measured by the ratio of domestic credit

to private sector to GDP (one year lag to avoid potential endogeneity) obtained from the

World Bank World Development Indicators (World Bank 2011) This measure has been used

in previous studies (Klapper et al 2006) and it is expected to be of a primary importance for

transition economies where firms tend to rely more on bank finance rather than capital

markets We also introduce a measure of property rights protection (a one year lag) proxied

by the indicator of effective constraints imposed on the executive branch of the government

and obtained from Polity IV project12 This measure of property rights protection is

9 These results are not reported here to save some space However they can be obtained from authors upon request 10 Here it is important to note that although the financial crisis has started in 2007 in the USA it spread to transition economies in 2008-2009 11 Some studies find a non-monotonic relationship between age and firm decision-making In this study we introduce a squared term of age along with a age variable to capture this possible non-linearity 12 Available from httpwwwsystemicpeaceorgpolitypolity4htm

15

considered to be superior to other indicators including the index of property rights reported

by the Heritage Foundation ndashWall Street Journal (for further discussion see Acemoglu and

Johnson 2005 Glaeser et al 2004 Estrin Korosteleva and Mickieiwcz 2011)

In the present study we also introduce macroeconomic controls including cyclical

economic performance as measured by the one year lag of the GDP annual growth rate

and the level of economic development as proxied by a set of GDP pc dummies denoting

the five quintiles of its distribution to address the problem of potential multicollinearity with the

measure of financial development

Finally we include industry and country controls in all our specifications Introducing

country dummies into analysis allows to control for cross-country heterogeneity

For further definition of all variables their descriptive statistics and correlation matrix

see Tables 1-2

43 Dependent variables

To investigate the effect of a firmrsquos size on its perception of financial constraints we

construct a dummy variable coded as 1 capturing a major and very severe obstacle for

access to finance and 0 otherwise

The firm financing choices are defined by the five individual dependent variables

associated with tobit financial choice equations in the seemingly unrelated regression

equations model

One important thing to mention here is the inability to distinguish between

owninternal funds and external private equity considered as one of the limitations of the

2002-2009 BEEPS dataset In the period under investigation BEEPS offers two questions

which aim to capture the use of equity The first one centres around retained earnings and

the second one shows ownersrsquo contributions and private equity or issued new equity

Following some theoretical considerations discussed in sections 2 and 3 in the context of

SMEs we expect the second element of equity to be primarily comprised of existing ownersrsquo

new contributions rather than private equity

Thus the indicator of financial choices represents a set of five individual dependent

variables including retained earnings contributed earnings private borrowing informal

finance trade credit with each of them constructed as a share in total financing of SMErsquos

investment decisions (see Table 1)

44 Methods

16

In this study we employ a number of estimators to obtain robust results More

specifically we use a probit model to investigate the effect of a firm size and the recent

financial crisis on firmsrsquo perception of financial constraints The effect of a firm size in the

situation of crisis is captured by the introduction of the interaction term between firm size as

proxied by the SME indicator and a financial crisis dummy

We further employ the seemingly unrelated regression equations model combined

with the tobit approach for studying firmsrsquo financial structure

Probit model of perception of financial constraints

In the probit model the probability of a firmrsquos perception of financial constraints as

major(j = 1) can be written as follows

( ) ( )int ++

++

infinminus

minus===

ijitj uXjitiitit ijitjuXjy uX

βα βαππ 212-

)()(2 21exp|Pr

Where ity is our measure of financial constraints as perceived by firms and itX is a

set of our explanatory variables discussed in detail in sections 3-4 Here it is important to

note that the interaction term in a probit model cannot be interpreted in a similar way as in

linear models and disregarding this may lead to misleading estimates of the interaction

effect which is of crucial importance for our study (Norton Wang and Ai 2004) Respectively

for robustness of our results here we follow the framework suggested by Norton Wang and

Ai (2004) to account for the model nonlinearity The adjusted marginal effects for the

interaction term are reported in the note to Table 313

Simultaneous Model of Financing Choices

As mentioned above we next model the choice of all five financing choices explicitly

We also hypothesise (following Isachenkova et al 2011) that firm financing choices are likely

to be determined jointly A standard way of modelling jointly determined indicators is a

system of equations - SURE ndash seemingly unrelated regression equations where equations

are linked only by their errors (Zellner 1962) We therefore model the five types of sources of

finance (internal funds private bank borrowing informal finance trade credit and private

13 We also run a probit regression for a split sample of (1) SMEs and (2) large firms to check the robustness of our results (based on the interaction term) while addressing a problem of multicollinearity between a crisis variable and its interaction term with a SME variable The correlation coefficient between a crisis variable and its interaction term with a SME variable is equal to 93 This can be attributed by the problem of a sample being overrepresented by SMEs which constitute 90 of all surveyed firms The results remain robust and can be available from authors upon request

17

equity) using a SURE framework within which we specify a set of five tobit regressions with

correlated residuals

We employ the STATA cmp module which allows to it Seemingly Unrelated Regressions

using the simulated likelihood method such as the Geweke Hajivassiliou and Keane (GHK)

algorithm (for further discussion see Roodman 2008) We utilise a tobit equation to model

each individual financial choice of firms because our dependent financing choices variables

are continuous but their range is constrained (censored) with a substantial number of

observations either equal to zero denoting those who do not use the respective source of

finance or to 100 showing the opposite Other observations are positive and may produce

many different outcomes (Verbeek 2000) Each tobit equation uses a set of identical

explanatory variables that proxy factors which could possibly be associated with firmrsquos

financing choices including industry and country dummies

We also considered the bias caused by potential interdependence between the choice of

whether to invest and firmrsquos financing choices We accounted for the potential selection bias

by introducing into the financial choices SURE Tobit equations (second stage outcome

equations14) the inverse Millrsquos ratio calculated based on modelling the choice to invest in

fixed assets (first stage or selection equation) To identify the first stage of the Heckman

selection model we chose a variable which is correlated with the first stage dependent

variable (investment decision) but not with the second ones (financing choices) We used the

rate of capacity utilization as part of our identification strategy Capacity utilization shows the

percentage of capital stock in use the higher is the rate the more likely firms will increase

investment Batyaeva and Aukutsionek (2001) show that the rate of capacity utilization is

higher in the group of investing firms than in the group of non-investing firms in Russia15 We

calculated the inverse Millrsquos ratio based on the above selection equation16 and included it as

a control in the second stage SURE Tobit equations The inverse Millrsquos ratio has only proved

to be statistically significant in the private bank loan equation pointing to the potential

selection bias arising from the possibility that the factors determining the decision to invest

might differ from those determining the use of bank financing in purchasing fixed assets

14 We also attempted to estimate an investment equation jointly with Tobit financial choices equations within the SURE framework using However given the overall complexity of the model we failed to do this We proceeded further with a two-stage approach by estimating an investment probit equation and calculating the inverse Millrsquos ratio that we add into the outcome financial choices equations at the second stage of the analysis to test for the selection bias 15 We performed an independent sample t-test to check whether the rate of capacity utilization is statistically significantly higher for investing firms compared to non-investing firms for our sample The null hypothesis of no difference was rejected at 1 level of significance 16 To economize on space we do not report the results of the investment probit equation but they are available from authorsrsquo upon request

18

Finally In Table 6 we attempt to condition the determinants of financing constraints

declared by SMEs on the relative percentage increase of trade credit in total funds used for

real investment As mentioned above in Section 2 the timings of measuring the composition

of financing sources precede by a year the timings of measuring the perceptions of financing

constraints That feature of the BEEPSrsquo design allays a likely concern about the endogeneity

of the relative proportion of trade credit and enables causal inference We too report in thre

note to Table 4 the adjusted marginal effects for the interaction term of the SME dummy with

the trade credit variable

In the next section we discuss our empirical results

5 Empirical Results

Table 3 reports the results of the probit model with the marginal effects for firmsrsquo

perception of financial constraints while Tables 4-5 summarize the results of SURE tobits for

a more detailed breakdown of five financing choices More specifically Table 4 reports the

results based on the whole sample to give a comparative perspective on SMErsquos financing

strategy vis-a-vis large businesses whereas Table 5 reports the results based on a

subsample of small and medium-sized firms to shed some light on their financing choices in

the period of crisis

Perception of financial constraints

Table 3 shows that generally small and medium-sized enterprises feel more financially

constrained with the coefficient for SME dummy in relation to the large firms being positive

and significant which is consistent with our discussion in sections 2-3 However the

coefficient of the interaction term with the Crisis dummy turns out to be negative and

significant in relation to the perception of financial constraints as a major obstacle and it

tends to outweigh the effect of a SME dummy when we calculate marginal effects The effect

of the interaction terms with the crisis remains robust after we adjust for non-linearity using

the framework proposed by Norton Wang and Ai (2004)17 Overall these results confirm

that small and medium-sized enterprises are much less financially constrained during the

crisis years with their perceptions close to those of the large firms This result is a polar

opposite to that obtained for the SMEs in the UK (Fraser 2009) which finds that not only do

SMEs generally feel more financially constrained but they report to be even more so during

17 We also check the robustness of our results to the potential problem of multicollinearity between a crisis dummy and its interaction term with SME by splitting a sample and testing the same specification separately for SMEs and large firms We also perform another robustness check by breaking a SME dummy into three subsequent dummies namely micro- small- and medium-sized firms The difference in perception of financial constraints gets almost eliminated in the case of small firms and is largely reduced in the case of micro firms whereas it is less so for medium-sized firms

19

the last crisis We could explain this striking difference by the peculiarities of the SMEs

functioning in new emerging economies The lower reliance of SMEs on external debt in

good times (as shown by results which are discussed below) gives SMEs some flexibility

during the crisis when formal financial markets dry up Jointly with overall flexibility to make

necessary cost cuts and to restructure a business this overall lower reliance on external

funding and the use of alternative sources of financing makes SMEs feel less financially

constrained under the crisis as compared to larger firms

We also find that a more developed financial sector as proxied by domestic private

credit as proportion of GDP helps ease up financial constraints This is in line with the

general literature suggesting that better functioning financial intermediaries facilitate the risk

amelioration in the presence of problems created by market frictions (Levine 1997 Barth et

al 2006 Barth et al 2008)

Unfortunately we fail to find any significant effect of the property rights protection on

firmsrsquo perception of financial constraints that may be explained by the fact that the effect of a

more developed financial sector is likely to outweigh the effect of the property rights

protection

Finally we also find that foreign ownership and international product certificate may

reduce firmsrsquo borrowing constraints while any pressure from domestic or foreign competition

so is pressure from the customers to innovate will increase firmrsquos perception of financial

constraints as major given that firms envisage the need to secure external funding for RampD

or any other innovation-related activities

Financing choices for investment in fixed assets

The results in Table 4 indicate that small enterprises tend to rely more on internal funds

and less on bank loans but they are no different from larger firms in respect of using informal

funds trade credit or private equity which is generally consistent with our discussion in

Sections 2 and 3 The results of Table 5 suggest however that under crisis small and

medium-sized firms tend to switch to other sources of finance such as trade credit and

ownerrsquos contributed equity and to respectively reduce the reliance on retained earnings

perhaps because they decrease due to the negative impact of crisis internal funds With

regards to our discussion of SMEsrsquo risk management we note that the use of private equity

(ownerrsquos contribution) during the crisis years increases which could indicate that the ownerrsquos

funds are used as a cushion in the period of financial distress

An interesting insight regarding the use of trade credit emerges for SMEs in our

sample although in non-crisis years small and medium-sized businesses are not significantly

different from larger firms in terms of reliance on trade credit SMEs tend to finance a

significantly higher proportion of their fixed asset investment by trade credit than large firms

20

in the period of crisis While the latter finding is partly in line with some other studies ndash such

as Klapper and Randall (2010) using BEEPS data it is in stark contrast with similar studies

of the UK private firms (Rehman 2011) for which the use of trade credit is found to have

dried up in crisis This could partly be due to the passed legislation in the UK tightening trade

credit regulation as the result of the abuse of trade credit by large firms in relation to small

firms which forced many SMEs out of the market

With regards to the other firm-level characteristics international certification makes the

firm rely more on private bank loans and informal finance (Table 5) while SMEs with foreign

ownership rely less on private debt but more on retained earnings Both results are

consistent with our hypotheses discussed above Export-oriented small and medium-sized

businesses tend to have greater reliance on trade credit and they use less of internal funds

We find a non-monotonic relationship between age and private equity with both younger and

older firms being more reliant on this source of funding We find some fragmentary support

for private domestic SMEs relying more on informal finance while tending to use less trade

credit and private equity (Table 5)

Interestingly our results (Tables 4-5) suggest that firms which lack some social

connections with governmental officials proxied by the higher amount of time spent dealing

with government regulations are more likely to rely on informal finance trade credit and

private equity In turn businesses which are connected to governmental officials use more

retained profits to fund investment in fixed assets This may be attributed to their connections

serving as a guarantee from expropriation of assets by all sort of rent-seeking individuals

akin private contracting to secure property rights protection This result should be interpreted

jointly with the property rights protection results We expected that better property rights

protection is likely to facilitate firmsrsquo access to bank loan but we failed to confirm this

Perhaps regardless some attempts at a constitutional level to prevent arbitrary government

(which is proxied by our measure of property rights) expropriation culture is still deeply

embedded in the society of post-communist countries and it may manifest in different ways

Welter and Smallbone (2011) argue that entrepreneurs in transition economies have learnt

how to respond to institutional deficiencies in particular weak property rights protection For

example some businesses experiencing high growth choose to invest in unrelated

businesses instead of growing their core businesses for the reason they do not want to

become too noticeable to attract too much attention of the wrong sort In our instance having

some connections with officials seems also to serve as protection against arbitrary

government or individual rent-seeking that makes businesses more keen on re-investing their

retained profits (see Johnson et al (2002) on the discussion of how more secure property

rights can make small firms reinvest more of their earnings)

14

To test our main hypothesis of the effect of a firm size on firmsrsquo perception of financial

constraints we introduce a dummy variable denoting small and medium-sized business

coded as 1 if firms are classified as small or medium-sized businesses according to the EU

definition based on the employment criterion For robustness of our results we also use a

continuous variable denoting a size of employment as measured by the natural logarithm of

employment9 The obtained results are consistent with the ones using the SME indicators

To capture the effect of the recent financial crisis we introduce a crisis dummy coded

as 1 if the year of survey is equal to 2008 or 200910

We also introduce a number of firm-level controls which include age of firm11 type of

ownership including private and foreign ownership export orientation and whether a firm

has an internationally certified product all equal to 1 if a business has a respectively listed

characteristic and zero otherwise We also examine the effect of various sources of pressure

on firms to innovate ndash the indicators which are considered to be important for firm investment

decisions Respectively the pressure for innovation may stem from domestic competition

foreign competition and customers To capture the effect of a firmrsquos social capital we

introduce an indicator which indirectly may capture some possible connections of a firm with

authorities It is proxied by time spent by each firm on dealing with government regulations

We assume the less time firms spend dealing with government regulations the more likely

they have some established connections with public officials which allow them to avoid

burdensome regulation procedures

In our study we also introduce a number of country-level variables which characterize

the institutional environment in the countries covered by our sample More specifically we

include an indicator of the financial development as measured by the ratio of domestic credit

to private sector to GDP (one year lag to avoid potential endogeneity) obtained from the

World Bank World Development Indicators (World Bank 2011) This measure has been used

in previous studies (Klapper et al 2006) and it is expected to be of a primary importance for

transition economies where firms tend to rely more on bank finance rather than capital

markets We also introduce a measure of property rights protection (a one year lag) proxied

by the indicator of effective constraints imposed on the executive branch of the government

and obtained from Polity IV project12 This measure of property rights protection is

9 These results are not reported here to save some space However they can be obtained from authors upon request 10 Here it is important to note that although the financial crisis has started in 2007 in the USA it spread to transition economies in 2008-2009 11 Some studies find a non-monotonic relationship between age and firm decision-making In this study we introduce a squared term of age along with a age variable to capture this possible non-linearity 12 Available from httpwwwsystemicpeaceorgpolitypolity4htm

15

considered to be superior to other indicators including the index of property rights reported

by the Heritage Foundation ndashWall Street Journal (for further discussion see Acemoglu and

Johnson 2005 Glaeser et al 2004 Estrin Korosteleva and Mickieiwcz 2011)

In the present study we also introduce macroeconomic controls including cyclical

economic performance as measured by the one year lag of the GDP annual growth rate

and the level of economic development as proxied by a set of GDP pc dummies denoting

the five quintiles of its distribution to address the problem of potential multicollinearity with the

measure of financial development

Finally we include industry and country controls in all our specifications Introducing

country dummies into analysis allows to control for cross-country heterogeneity

For further definition of all variables their descriptive statistics and correlation matrix

see Tables 1-2

43 Dependent variables

To investigate the effect of a firmrsquos size on its perception of financial constraints we

construct a dummy variable coded as 1 capturing a major and very severe obstacle for

access to finance and 0 otherwise

The firm financing choices are defined by the five individual dependent variables

associated with tobit financial choice equations in the seemingly unrelated regression

equations model

One important thing to mention here is the inability to distinguish between

owninternal funds and external private equity considered as one of the limitations of the

2002-2009 BEEPS dataset In the period under investigation BEEPS offers two questions

which aim to capture the use of equity The first one centres around retained earnings and

the second one shows ownersrsquo contributions and private equity or issued new equity

Following some theoretical considerations discussed in sections 2 and 3 in the context of

SMEs we expect the second element of equity to be primarily comprised of existing ownersrsquo

new contributions rather than private equity

Thus the indicator of financial choices represents a set of five individual dependent

variables including retained earnings contributed earnings private borrowing informal

finance trade credit with each of them constructed as a share in total financing of SMErsquos

investment decisions (see Table 1)

44 Methods

16

In this study we employ a number of estimators to obtain robust results More

specifically we use a probit model to investigate the effect of a firm size and the recent

financial crisis on firmsrsquo perception of financial constraints The effect of a firm size in the

situation of crisis is captured by the introduction of the interaction term between firm size as

proxied by the SME indicator and a financial crisis dummy

We further employ the seemingly unrelated regression equations model combined

with the tobit approach for studying firmsrsquo financial structure

Probit model of perception of financial constraints

In the probit model the probability of a firmrsquos perception of financial constraints as

major(j = 1) can be written as follows

( ) ( )int ++

++

infinminus

minus===

ijitj uXjitiitit ijitjuXjy uX

βα βαππ 212-

)()(2 21exp|Pr

Where ity is our measure of financial constraints as perceived by firms and itX is a

set of our explanatory variables discussed in detail in sections 3-4 Here it is important to

note that the interaction term in a probit model cannot be interpreted in a similar way as in

linear models and disregarding this may lead to misleading estimates of the interaction

effect which is of crucial importance for our study (Norton Wang and Ai 2004) Respectively

for robustness of our results here we follow the framework suggested by Norton Wang and

Ai (2004) to account for the model nonlinearity The adjusted marginal effects for the

interaction term are reported in the note to Table 313

Simultaneous Model of Financing Choices

As mentioned above we next model the choice of all five financing choices explicitly

We also hypothesise (following Isachenkova et al 2011) that firm financing choices are likely

to be determined jointly A standard way of modelling jointly determined indicators is a

system of equations - SURE ndash seemingly unrelated regression equations where equations

are linked only by their errors (Zellner 1962) We therefore model the five types of sources of

finance (internal funds private bank borrowing informal finance trade credit and private

13 We also run a probit regression for a split sample of (1) SMEs and (2) large firms to check the robustness of our results (based on the interaction term) while addressing a problem of multicollinearity between a crisis variable and its interaction term with a SME variable The correlation coefficient between a crisis variable and its interaction term with a SME variable is equal to 93 This can be attributed by the problem of a sample being overrepresented by SMEs which constitute 90 of all surveyed firms The results remain robust and can be available from authors upon request

17

equity) using a SURE framework within which we specify a set of five tobit regressions with

correlated residuals

We employ the STATA cmp module which allows to it Seemingly Unrelated Regressions

using the simulated likelihood method such as the Geweke Hajivassiliou and Keane (GHK)

algorithm (for further discussion see Roodman 2008) We utilise a tobit equation to model

each individual financial choice of firms because our dependent financing choices variables

are continuous but their range is constrained (censored) with a substantial number of

observations either equal to zero denoting those who do not use the respective source of

finance or to 100 showing the opposite Other observations are positive and may produce

many different outcomes (Verbeek 2000) Each tobit equation uses a set of identical

explanatory variables that proxy factors which could possibly be associated with firmrsquos

financing choices including industry and country dummies

We also considered the bias caused by potential interdependence between the choice of

whether to invest and firmrsquos financing choices We accounted for the potential selection bias

by introducing into the financial choices SURE Tobit equations (second stage outcome

equations14) the inverse Millrsquos ratio calculated based on modelling the choice to invest in

fixed assets (first stage or selection equation) To identify the first stage of the Heckman

selection model we chose a variable which is correlated with the first stage dependent

variable (investment decision) but not with the second ones (financing choices) We used the

rate of capacity utilization as part of our identification strategy Capacity utilization shows the

percentage of capital stock in use the higher is the rate the more likely firms will increase

investment Batyaeva and Aukutsionek (2001) show that the rate of capacity utilization is

higher in the group of investing firms than in the group of non-investing firms in Russia15 We

calculated the inverse Millrsquos ratio based on the above selection equation16 and included it as

a control in the second stage SURE Tobit equations The inverse Millrsquos ratio has only proved

to be statistically significant in the private bank loan equation pointing to the potential

selection bias arising from the possibility that the factors determining the decision to invest

might differ from those determining the use of bank financing in purchasing fixed assets

14 We also attempted to estimate an investment equation jointly with Tobit financial choices equations within the SURE framework using However given the overall complexity of the model we failed to do this We proceeded further with a two-stage approach by estimating an investment probit equation and calculating the inverse Millrsquos ratio that we add into the outcome financial choices equations at the second stage of the analysis to test for the selection bias 15 We performed an independent sample t-test to check whether the rate of capacity utilization is statistically significantly higher for investing firms compared to non-investing firms for our sample The null hypothesis of no difference was rejected at 1 level of significance 16 To economize on space we do not report the results of the investment probit equation but they are available from authorsrsquo upon request

18

Finally In Table 6 we attempt to condition the determinants of financing constraints

declared by SMEs on the relative percentage increase of trade credit in total funds used for

real investment As mentioned above in Section 2 the timings of measuring the composition

of financing sources precede by a year the timings of measuring the perceptions of financing

constraints That feature of the BEEPSrsquo design allays a likely concern about the endogeneity

of the relative proportion of trade credit and enables causal inference We too report in thre

note to Table 4 the adjusted marginal effects for the interaction term of the SME dummy with

the trade credit variable

In the next section we discuss our empirical results

5 Empirical Results

Table 3 reports the results of the probit model with the marginal effects for firmsrsquo

perception of financial constraints while Tables 4-5 summarize the results of SURE tobits for

a more detailed breakdown of five financing choices More specifically Table 4 reports the

results based on the whole sample to give a comparative perspective on SMErsquos financing

strategy vis-a-vis large businesses whereas Table 5 reports the results based on a

subsample of small and medium-sized firms to shed some light on their financing choices in

the period of crisis

Perception of financial constraints

Table 3 shows that generally small and medium-sized enterprises feel more financially

constrained with the coefficient for SME dummy in relation to the large firms being positive

and significant which is consistent with our discussion in sections 2-3 However the

coefficient of the interaction term with the Crisis dummy turns out to be negative and

significant in relation to the perception of financial constraints as a major obstacle and it

tends to outweigh the effect of a SME dummy when we calculate marginal effects The effect

of the interaction terms with the crisis remains robust after we adjust for non-linearity using

the framework proposed by Norton Wang and Ai (2004)17 Overall these results confirm

that small and medium-sized enterprises are much less financially constrained during the

crisis years with their perceptions close to those of the large firms This result is a polar

opposite to that obtained for the SMEs in the UK (Fraser 2009) which finds that not only do

SMEs generally feel more financially constrained but they report to be even more so during

17 We also check the robustness of our results to the potential problem of multicollinearity between a crisis dummy and its interaction term with SME by splitting a sample and testing the same specification separately for SMEs and large firms We also perform another robustness check by breaking a SME dummy into three subsequent dummies namely micro- small- and medium-sized firms The difference in perception of financial constraints gets almost eliminated in the case of small firms and is largely reduced in the case of micro firms whereas it is less so for medium-sized firms

19

the last crisis We could explain this striking difference by the peculiarities of the SMEs

functioning in new emerging economies The lower reliance of SMEs on external debt in

good times (as shown by results which are discussed below) gives SMEs some flexibility

during the crisis when formal financial markets dry up Jointly with overall flexibility to make

necessary cost cuts and to restructure a business this overall lower reliance on external

funding and the use of alternative sources of financing makes SMEs feel less financially

constrained under the crisis as compared to larger firms

We also find that a more developed financial sector as proxied by domestic private

credit as proportion of GDP helps ease up financial constraints This is in line with the

general literature suggesting that better functioning financial intermediaries facilitate the risk

amelioration in the presence of problems created by market frictions (Levine 1997 Barth et

al 2006 Barth et al 2008)

Unfortunately we fail to find any significant effect of the property rights protection on

firmsrsquo perception of financial constraints that may be explained by the fact that the effect of a

more developed financial sector is likely to outweigh the effect of the property rights

protection

Finally we also find that foreign ownership and international product certificate may

reduce firmsrsquo borrowing constraints while any pressure from domestic or foreign competition

so is pressure from the customers to innovate will increase firmrsquos perception of financial

constraints as major given that firms envisage the need to secure external funding for RampD

or any other innovation-related activities

Financing choices for investment in fixed assets

The results in Table 4 indicate that small enterprises tend to rely more on internal funds

and less on bank loans but they are no different from larger firms in respect of using informal

funds trade credit or private equity which is generally consistent with our discussion in

Sections 2 and 3 The results of Table 5 suggest however that under crisis small and

medium-sized firms tend to switch to other sources of finance such as trade credit and

ownerrsquos contributed equity and to respectively reduce the reliance on retained earnings

perhaps because they decrease due to the negative impact of crisis internal funds With

regards to our discussion of SMEsrsquo risk management we note that the use of private equity

(ownerrsquos contribution) during the crisis years increases which could indicate that the ownerrsquos

funds are used as a cushion in the period of financial distress

An interesting insight regarding the use of trade credit emerges for SMEs in our

sample although in non-crisis years small and medium-sized businesses are not significantly

different from larger firms in terms of reliance on trade credit SMEs tend to finance a

significantly higher proportion of their fixed asset investment by trade credit than large firms

20

in the period of crisis While the latter finding is partly in line with some other studies ndash such

as Klapper and Randall (2010) using BEEPS data it is in stark contrast with similar studies

of the UK private firms (Rehman 2011) for which the use of trade credit is found to have

dried up in crisis This could partly be due to the passed legislation in the UK tightening trade

credit regulation as the result of the abuse of trade credit by large firms in relation to small

firms which forced many SMEs out of the market

With regards to the other firm-level characteristics international certification makes the

firm rely more on private bank loans and informal finance (Table 5) while SMEs with foreign

ownership rely less on private debt but more on retained earnings Both results are

consistent with our hypotheses discussed above Export-oriented small and medium-sized

businesses tend to have greater reliance on trade credit and they use less of internal funds

We find a non-monotonic relationship between age and private equity with both younger and

older firms being more reliant on this source of funding We find some fragmentary support

for private domestic SMEs relying more on informal finance while tending to use less trade

credit and private equity (Table 5)

Interestingly our results (Tables 4-5) suggest that firms which lack some social

connections with governmental officials proxied by the higher amount of time spent dealing

with government regulations are more likely to rely on informal finance trade credit and

private equity In turn businesses which are connected to governmental officials use more

retained profits to fund investment in fixed assets This may be attributed to their connections

serving as a guarantee from expropriation of assets by all sort of rent-seeking individuals

akin private contracting to secure property rights protection This result should be interpreted

jointly with the property rights protection results We expected that better property rights

protection is likely to facilitate firmsrsquo access to bank loan but we failed to confirm this

Perhaps regardless some attempts at a constitutional level to prevent arbitrary government

(which is proxied by our measure of property rights) expropriation culture is still deeply

embedded in the society of post-communist countries and it may manifest in different ways

Welter and Smallbone (2011) argue that entrepreneurs in transition economies have learnt

how to respond to institutional deficiencies in particular weak property rights protection For

example some businesses experiencing high growth choose to invest in unrelated

businesses instead of growing their core businesses for the reason they do not want to

become too noticeable to attract too much attention of the wrong sort In our instance having

some connections with officials seems also to serve as protection against arbitrary

government or individual rent-seeking that makes businesses more keen on re-investing their

retained profits (see Johnson et al (2002) on the discussion of how more secure property

rights can make small firms reinvest more of their earnings)

15

considered to be superior to other indicators including the index of property rights reported

by the Heritage Foundation ndashWall Street Journal (for further discussion see Acemoglu and

Johnson 2005 Glaeser et al 2004 Estrin Korosteleva and Mickieiwcz 2011)

In the present study we also introduce macroeconomic controls including cyclical

economic performance as measured by the one year lag of the GDP annual growth rate

and the level of economic development as proxied by a set of GDP pc dummies denoting

the five quintiles of its distribution to address the problem of potential multicollinearity with the

measure of financial development

Finally we include industry and country controls in all our specifications Introducing

country dummies into analysis allows to control for cross-country heterogeneity

For further definition of all variables their descriptive statistics and correlation matrix

see Tables 1-2

43 Dependent variables

To investigate the effect of a firmrsquos size on its perception of financial constraints we

construct a dummy variable coded as 1 capturing a major and very severe obstacle for

access to finance and 0 otherwise

The firm financing choices are defined by the five individual dependent variables

associated with tobit financial choice equations in the seemingly unrelated regression

equations model

One important thing to mention here is the inability to distinguish between

owninternal funds and external private equity considered as one of the limitations of the

2002-2009 BEEPS dataset In the period under investigation BEEPS offers two questions

which aim to capture the use of equity The first one centres around retained earnings and

the second one shows ownersrsquo contributions and private equity or issued new equity

Following some theoretical considerations discussed in sections 2 and 3 in the context of

SMEs we expect the second element of equity to be primarily comprised of existing ownersrsquo

new contributions rather than private equity

Thus the indicator of financial choices represents a set of five individual dependent

variables including retained earnings contributed earnings private borrowing informal

finance trade credit with each of them constructed as a share in total financing of SMErsquos

investment decisions (see Table 1)

44 Methods

16

In this study we employ a number of estimators to obtain robust results More

specifically we use a probit model to investigate the effect of a firm size and the recent

financial crisis on firmsrsquo perception of financial constraints The effect of a firm size in the

situation of crisis is captured by the introduction of the interaction term between firm size as

proxied by the SME indicator and a financial crisis dummy

We further employ the seemingly unrelated regression equations model combined

with the tobit approach for studying firmsrsquo financial structure

Probit model of perception of financial constraints

In the probit model the probability of a firmrsquos perception of financial constraints as

major(j = 1) can be written as follows

( ) ( )int ++

++

infinminus

minus===

ijitj uXjitiitit ijitjuXjy uX

βα βαππ 212-

)()(2 21exp|Pr

Where ity is our measure of financial constraints as perceived by firms and itX is a

set of our explanatory variables discussed in detail in sections 3-4 Here it is important to

note that the interaction term in a probit model cannot be interpreted in a similar way as in

linear models and disregarding this may lead to misleading estimates of the interaction

effect which is of crucial importance for our study (Norton Wang and Ai 2004) Respectively

for robustness of our results here we follow the framework suggested by Norton Wang and

Ai (2004) to account for the model nonlinearity The adjusted marginal effects for the

interaction term are reported in the note to Table 313

Simultaneous Model of Financing Choices

As mentioned above we next model the choice of all five financing choices explicitly

We also hypothesise (following Isachenkova et al 2011) that firm financing choices are likely

to be determined jointly A standard way of modelling jointly determined indicators is a

system of equations - SURE ndash seemingly unrelated regression equations where equations

are linked only by their errors (Zellner 1962) We therefore model the five types of sources of

finance (internal funds private bank borrowing informal finance trade credit and private

13 We also run a probit regression for a split sample of (1) SMEs and (2) large firms to check the robustness of our results (based on the interaction term) while addressing a problem of multicollinearity between a crisis variable and its interaction term with a SME variable The correlation coefficient between a crisis variable and its interaction term with a SME variable is equal to 93 This can be attributed by the problem of a sample being overrepresented by SMEs which constitute 90 of all surveyed firms The results remain robust and can be available from authors upon request

17

equity) using a SURE framework within which we specify a set of five tobit regressions with

correlated residuals

We employ the STATA cmp module which allows to it Seemingly Unrelated Regressions

using the simulated likelihood method such as the Geweke Hajivassiliou and Keane (GHK)

algorithm (for further discussion see Roodman 2008) We utilise a tobit equation to model

each individual financial choice of firms because our dependent financing choices variables

are continuous but their range is constrained (censored) with a substantial number of

observations either equal to zero denoting those who do not use the respective source of

finance or to 100 showing the opposite Other observations are positive and may produce

many different outcomes (Verbeek 2000) Each tobit equation uses a set of identical

explanatory variables that proxy factors which could possibly be associated with firmrsquos

financing choices including industry and country dummies

We also considered the bias caused by potential interdependence between the choice of

whether to invest and firmrsquos financing choices We accounted for the potential selection bias

by introducing into the financial choices SURE Tobit equations (second stage outcome

equations14) the inverse Millrsquos ratio calculated based on modelling the choice to invest in

fixed assets (first stage or selection equation) To identify the first stage of the Heckman

selection model we chose a variable which is correlated with the first stage dependent

variable (investment decision) but not with the second ones (financing choices) We used the

rate of capacity utilization as part of our identification strategy Capacity utilization shows the

percentage of capital stock in use the higher is the rate the more likely firms will increase

investment Batyaeva and Aukutsionek (2001) show that the rate of capacity utilization is

higher in the group of investing firms than in the group of non-investing firms in Russia15 We

calculated the inverse Millrsquos ratio based on the above selection equation16 and included it as

a control in the second stage SURE Tobit equations The inverse Millrsquos ratio has only proved

to be statistically significant in the private bank loan equation pointing to the potential

selection bias arising from the possibility that the factors determining the decision to invest

might differ from those determining the use of bank financing in purchasing fixed assets

14 We also attempted to estimate an investment equation jointly with Tobit financial choices equations within the SURE framework using However given the overall complexity of the model we failed to do this We proceeded further with a two-stage approach by estimating an investment probit equation and calculating the inverse Millrsquos ratio that we add into the outcome financial choices equations at the second stage of the analysis to test for the selection bias 15 We performed an independent sample t-test to check whether the rate of capacity utilization is statistically significantly higher for investing firms compared to non-investing firms for our sample The null hypothesis of no difference was rejected at 1 level of significance 16 To economize on space we do not report the results of the investment probit equation but they are available from authorsrsquo upon request

18

Finally In Table 6 we attempt to condition the determinants of financing constraints

declared by SMEs on the relative percentage increase of trade credit in total funds used for

real investment As mentioned above in Section 2 the timings of measuring the composition

of financing sources precede by a year the timings of measuring the perceptions of financing

constraints That feature of the BEEPSrsquo design allays a likely concern about the endogeneity

of the relative proportion of trade credit and enables causal inference We too report in thre

note to Table 4 the adjusted marginal effects for the interaction term of the SME dummy with

the trade credit variable

In the next section we discuss our empirical results

5 Empirical Results

Table 3 reports the results of the probit model with the marginal effects for firmsrsquo

perception of financial constraints while Tables 4-5 summarize the results of SURE tobits for

a more detailed breakdown of five financing choices More specifically Table 4 reports the

results based on the whole sample to give a comparative perspective on SMErsquos financing

strategy vis-a-vis large businesses whereas Table 5 reports the results based on a

subsample of small and medium-sized firms to shed some light on their financing choices in

the period of crisis

Perception of financial constraints

Table 3 shows that generally small and medium-sized enterprises feel more financially

constrained with the coefficient for SME dummy in relation to the large firms being positive

and significant which is consistent with our discussion in sections 2-3 However the

coefficient of the interaction term with the Crisis dummy turns out to be negative and

significant in relation to the perception of financial constraints as a major obstacle and it

tends to outweigh the effect of a SME dummy when we calculate marginal effects The effect

of the interaction terms with the crisis remains robust after we adjust for non-linearity using

the framework proposed by Norton Wang and Ai (2004)17 Overall these results confirm

that small and medium-sized enterprises are much less financially constrained during the

crisis years with their perceptions close to those of the large firms This result is a polar

opposite to that obtained for the SMEs in the UK (Fraser 2009) which finds that not only do

SMEs generally feel more financially constrained but they report to be even more so during

17 We also check the robustness of our results to the potential problem of multicollinearity between a crisis dummy and its interaction term with SME by splitting a sample and testing the same specification separately for SMEs and large firms We also perform another robustness check by breaking a SME dummy into three subsequent dummies namely micro- small- and medium-sized firms The difference in perception of financial constraints gets almost eliminated in the case of small firms and is largely reduced in the case of micro firms whereas it is less so for medium-sized firms

19

the last crisis We could explain this striking difference by the peculiarities of the SMEs

functioning in new emerging economies The lower reliance of SMEs on external debt in

good times (as shown by results which are discussed below) gives SMEs some flexibility

during the crisis when formal financial markets dry up Jointly with overall flexibility to make

necessary cost cuts and to restructure a business this overall lower reliance on external

funding and the use of alternative sources of financing makes SMEs feel less financially

constrained under the crisis as compared to larger firms

We also find that a more developed financial sector as proxied by domestic private

credit as proportion of GDP helps ease up financial constraints This is in line with the

general literature suggesting that better functioning financial intermediaries facilitate the risk

amelioration in the presence of problems created by market frictions (Levine 1997 Barth et

al 2006 Barth et al 2008)

Unfortunately we fail to find any significant effect of the property rights protection on

firmsrsquo perception of financial constraints that may be explained by the fact that the effect of a

more developed financial sector is likely to outweigh the effect of the property rights

protection

Finally we also find that foreign ownership and international product certificate may

reduce firmsrsquo borrowing constraints while any pressure from domestic or foreign competition

so is pressure from the customers to innovate will increase firmrsquos perception of financial

constraints as major given that firms envisage the need to secure external funding for RampD

or any other innovation-related activities

Financing choices for investment in fixed assets

The results in Table 4 indicate that small enterprises tend to rely more on internal funds

and less on bank loans but they are no different from larger firms in respect of using informal

funds trade credit or private equity which is generally consistent with our discussion in

Sections 2 and 3 The results of Table 5 suggest however that under crisis small and

medium-sized firms tend to switch to other sources of finance such as trade credit and

ownerrsquos contributed equity and to respectively reduce the reliance on retained earnings

perhaps because they decrease due to the negative impact of crisis internal funds With

regards to our discussion of SMEsrsquo risk management we note that the use of private equity

(ownerrsquos contribution) during the crisis years increases which could indicate that the ownerrsquos

funds are used as a cushion in the period of financial distress

An interesting insight regarding the use of trade credit emerges for SMEs in our

sample although in non-crisis years small and medium-sized businesses are not significantly

different from larger firms in terms of reliance on trade credit SMEs tend to finance a

significantly higher proportion of their fixed asset investment by trade credit than large firms

20

in the period of crisis While the latter finding is partly in line with some other studies ndash such

as Klapper and Randall (2010) using BEEPS data it is in stark contrast with similar studies

of the UK private firms (Rehman 2011) for which the use of trade credit is found to have

dried up in crisis This could partly be due to the passed legislation in the UK tightening trade

credit regulation as the result of the abuse of trade credit by large firms in relation to small

firms which forced many SMEs out of the market

With regards to the other firm-level characteristics international certification makes the

firm rely more on private bank loans and informal finance (Table 5) while SMEs with foreign

ownership rely less on private debt but more on retained earnings Both results are

consistent with our hypotheses discussed above Export-oriented small and medium-sized

businesses tend to have greater reliance on trade credit and they use less of internal funds

We find a non-monotonic relationship between age and private equity with both younger and

older firms being more reliant on this source of funding We find some fragmentary support

for private domestic SMEs relying more on informal finance while tending to use less trade

credit and private equity (Table 5)

Interestingly our results (Tables 4-5) suggest that firms which lack some social

connections with governmental officials proxied by the higher amount of time spent dealing

with government regulations are more likely to rely on informal finance trade credit and

private equity In turn businesses which are connected to governmental officials use more

retained profits to fund investment in fixed assets This may be attributed to their connections

serving as a guarantee from expropriation of assets by all sort of rent-seeking individuals

akin private contracting to secure property rights protection This result should be interpreted

jointly with the property rights protection results We expected that better property rights

protection is likely to facilitate firmsrsquo access to bank loan but we failed to confirm this

Perhaps regardless some attempts at a constitutional level to prevent arbitrary government

(which is proxied by our measure of property rights) expropriation culture is still deeply

embedded in the society of post-communist countries and it may manifest in different ways

Welter and Smallbone (2011) argue that entrepreneurs in transition economies have learnt

how to respond to institutional deficiencies in particular weak property rights protection For

example some businesses experiencing high growth choose to invest in unrelated

businesses instead of growing their core businesses for the reason they do not want to

become too noticeable to attract too much attention of the wrong sort In our instance having

some connections with officials seems also to serve as protection against arbitrary

government or individual rent-seeking that makes businesses more keen on re-investing their

retained profits (see Johnson et al (2002) on the discussion of how more secure property

rights can make small firms reinvest more of their earnings)

16

In this study we employ a number of estimators to obtain robust results More

specifically we use a probit model to investigate the effect of a firm size and the recent

financial crisis on firmsrsquo perception of financial constraints The effect of a firm size in the

situation of crisis is captured by the introduction of the interaction term between firm size as

proxied by the SME indicator and a financial crisis dummy

We further employ the seemingly unrelated regression equations model combined

with the tobit approach for studying firmsrsquo financial structure

Probit model of perception of financial constraints

In the probit model the probability of a firmrsquos perception of financial constraints as

major(j = 1) can be written as follows

( ) ( )int ++

++

infinminus

minus===

ijitj uXjitiitit ijitjuXjy uX

βα βαππ 212-

)()(2 21exp|Pr

Where ity is our measure of financial constraints as perceived by firms and itX is a

set of our explanatory variables discussed in detail in sections 3-4 Here it is important to

note that the interaction term in a probit model cannot be interpreted in a similar way as in

linear models and disregarding this may lead to misleading estimates of the interaction

effect which is of crucial importance for our study (Norton Wang and Ai 2004) Respectively

for robustness of our results here we follow the framework suggested by Norton Wang and

Ai (2004) to account for the model nonlinearity The adjusted marginal effects for the

interaction term are reported in the note to Table 313

Simultaneous Model of Financing Choices

As mentioned above we next model the choice of all five financing choices explicitly

We also hypothesise (following Isachenkova et al 2011) that firm financing choices are likely

to be determined jointly A standard way of modelling jointly determined indicators is a

system of equations - SURE ndash seemingly unrelated regression equations where equations

are linked only by their errors (Zellner 1962) We therefore model the five types of sources of

finance (internal funds private bank borrowing informal finance trade credit and private

13 We also run a probit regression for a split sample of (1) SMEs and (2) large firms to check the robustness of our results (based on the interaction term) while addressing a problem of multicollinearity between a crisis variable and its interaction term with a SME variable The correlation coefficient between a crisis variable and its interaction term with a SME variable is equal to 93 This can be attributed by the problem of a sample being overrepresented by SMEs which constitute 90 of all surveyed firms The results remain robust and can be available from authors upon request

17

equity) using a SURE framework within which we specify a set of five tobit regressions with

correlated residuals

We employ the STATA cmp module which allows to it Seemingly Unrelated Regressions

using the simulated likelihood method such as the Geweke Hajivassiliou and Keane (GHK)

algorithm (for further discussion see Roodman 2008) We utilise a tobit equation to model

each individual financial choice of firms because our dependent financing choices variables

are continuous but their range is constrained (censored) with a substantial number of

observations either equal to zero denoting those who do not use the respective source of

finance or to 100 showing the opposite Other observations are positive and may produce

many different outcomes (Verbeek 2000) Each tobit equation uses a set of identical

explanatory variables that proxy factors which could possibly be associated with firmrsquos

financing choices including industry and country dummies

We also considered the bias caused by potential interdependence between the choice of

whether to invest and firmrsquos financing choices We accounted for the potential selection bias

by introducing into the financial choices SURE Tobit equations (second stage outcome

equations14) the inverse Millrsquos ratio calculated based on modelling the choice to invest in

fixed assets (first stage or selection equation) To identify the first stage of the Heckman

selection model we chose a variable which is correlated with the first stage dependent

variable (investment decision) but not with the second ones (financing choices) We used the

rate of capacity utilization as part of our identification strategy Capacity utilization shows the

percentage of capital stock in use the higher is the rate the more likely firms will increase

investment Batyaeva and Aukutsionek (2001) show that the rate of capacity utilization is

higher in the group of investing firms than in the group of non-investing firms in Russia15 We

calculated the inverse Millrsquos ratio based on the above selection equation16 and included it as

a control in the second stage SURE Tobit equations The inverse Millrsquos ratio has only proved

to be statistically significant in the private bank loan equation pointing to the potential

selection bias arising from the possibility that the factors determining the decision to invest

might differ from those determining the use of bank financing in purchasing fixed assets

14 We also attempted to estimate an investment equation jointly with Tobit financial choices equations within the SURE framework using However given the overall complexity of the model we failed to do this We proceeded further with a two-stage approach by estimating an investment probit equation and calculating the inverse Millrsquos ratio that we add into the outcome financial choices equations at the second stage of the analysis to test for the selection bias 15 We performed an independent sample t-test to check whether the rate of capacity utilization is statistically significantly higher for investing firms compared to non-investing firms for our sample The null hypothesis of no difference was rejected at 1 level of significance 16 To economize on space we do not report the results of the investment probit equation but they are available from authorsrsquo upon request

18

Finally In Table 6 we attempt to condition the determinants of financing constraints

declared by SMEs on the relative percentage increase of trade credit in total funds used for

real investment As mentioned above in Section 2 the timings of measuring the composition

of financing sources precede by a year the timings of measuring the perceptions of financing

constraints That feature of the BEEPSrsquo design allays a likely concern about the endogeneity

of the relative proportion of trade credit and enables causal inference We too report in thre

note to Table 4 the adjusted marginal effects for the interaction term of the SME dummy with

the trade credit variable

In the next section we discuss our empirical results

5 Empirical Results

Table 3 reports the results of the probit model with the marginal effects for firmsrsquo

perception of financial constraints while Tables 4-5 summarize the results of SURE tobits for

a more detailed breakdown of five financing choices More specifically Table 4 reports the

results based on the whole sample to give a comparative perspective on SMErsquos financing

strategy vis-a-vis large businesses whereas Table 5 reports the results based on a

subsample of small and medium-sized firms to shed some light on their financing choices in

the period of crisis

Perception of financial constraints

Table 3 shows that generally small and medium-sized enterprises feel more financially

constrained with the coefficient for SME dummy in relation to the large firms being positive

and significant which is consistent with our discussion in sections 2-3 However the

coefficient of the interaction term with the Crisis dummy turns out to be negative and

significant in relation to the perception of financial constraints as a major obstacle and it

tends to outweigh the effect of a SME dummy when we calculate marginal effects The effect

of the interaction terms with the crisis remains robust after we adjust for non-linearity using

the framework proposed by Norton Wang and Ai (2004)17 Overall these results confirm

that small and medium-sized enterprises are much less financially constrained during the

crisis years with their perceptions close to those of the large firms This result is a polar

opposite to that obtained for the SMEs in the UK (Fraser 2009) which finds that not only do

SMEs generally feel more financially constrained but they report to be even more so during

17 We also check the robustness of our results to the potential problem of multicollinearity between a crisis dummy and its interaction term with SME by splitting a sample and testing the same specification separately for SMEs and large firms We also perform another robustness check by breaking a SME dummy into three subsequent dummies namely micro- small- and medium-sized firms The difference in perception of financial constraints gets almost eliminated in the case of small firms and is largely reduced in the case of micro firms whereas it is less so for medium-sized firms

19

the last crisis We could explain this striking difference by the peculiarities of the SMEs

functioning in new emerging economies The lower reliance of SMEs on external debt in

good times (as shown by results which are discussed below) gives SMEs some flexibility

during the crisis when formal financial markets dry up Jointly with overall flexibility to make

necessary cost cuts and to restructure a business this overall lower reliance on external

funding and the use of alternative sources of financing makes SMEs feel less financially

constrained under the crisis as compared to larger firms

We also find that a more developed financial sector as proxied by domestic private

credit as proportion of GDP helps ease up financial constraints This is in line with the

general literature suggesting that better functioning financial intermediaries facilitate the risk

amelioration in the presence of problems created by market frictions (Levine 1997 Barth et

al 2006 Barth et al 2008)

Unfortunately we fail to find any significant effect of the property rights protection on

firmsrsquo perception of financial constraints that may be explained by the fact that the effect of a

more developed financial sector is likely to outweigh the effect of the property rights

protection

Finally we also find that foreign ownership and international product certificate may

reduce firmsrsquo borrowing constraints while any pressure from domestic or foreign competition

so is pressure from the customers to innovate will increase firmrsquos perception of financial

constraints as major given that firms envisage the need to secure external funding for RampD

or any other innovation-related activities

Financing choices for investment in fixed assets

The results in Table 4 indicate that small enterprises tend to rely more on internal funds

and less on bank loans but they are no different from larger firms in respect of using informal

funds trade credit or private equity which is generally consistent with our discussion in

Sections 2 and 3 The results of Table 5 suggest however that under crisis small and

medium-sized firms tend to switch to other sources of finance such as trade credit and

ownerrsquos contributed equity and to respectively reduce the reliance on retained earnings

perhaps because they decrease due to the negative impact of crisis internal funds With

regards to our discussion of SMEsrsquo risk management we note that the use of private equity

(ownerrsquos contribution) during the crisis years increases which could indicate that the ownerrsquos

funds are used as a cushion in the period of financial distress

An interesting insight regarding the use of trade credit emerges for SMEs in our

sample although in non-crisis years small and medium-sized businesses are not significantly

different from larger firms in terms of reliance on trade credit SMEs tend to finance a

significantly higher proportion of their fixed asset investment by trade credit than large firms

20

in the period of crisis While the latter finding is partly in line with some other studies ndash such

as Klapper and Randall (2010) using BEEPS data it is in stark contrast with similar studies

of the UK private firms (Rehman 2011) for which the use of trade credit is found to have

dried up in crisis This could partly be due to the passed legislation in the UK tightening trade

credit regulation as the result of the abuse of trade credit by large firms in relation to small

firms which forced many SMEs out of the market

With regards to the other firm-level characteristics international certification makes the

firm rely more on private bank loans and informal finance (Table 5) while SMEs with foreign

ownership rely less on private debt but more on retained earnings Both results are

consistent with our hypotheses discussed above Export-oriented small and medium-sized

businesses tend to have greater reliance on trade credit and they use less of internal funds

We find a non-monotonic relationship between age and private equity with both younger and

older firms being more reliant on this source of funding We find some fragmentary support

for private domestic SMEs relying more on informal finance while tending to use less trade

credit and private equity (Table 5)

Interestingly our results (Tables 4-5) suggest that firms which lack some social

connections with governmental officials proxied by the higher amount of time spent dealing

with government regulations are more likely to rely on informal finance trade credit and

private equity In turn businesses which are connected to governmental officials use more

retained profits to fund investment in fixed assets This may be attributed to their connections

serving as a guarantee from expropriation of assets by all sort of rent-seeking individuals

akin private contracting to secure property rights protection This result should be interpreted

jointly with the property rights protection results We expected that better property rights

protection is likely to facilitate firmsrsquo access to bank loan but we failed to confirm this

Perhaps regardless some attempts at a constitutional level to prevent arbitrary government

(which is proxied by our measure of property rights) expropriation culture is still deeply

embedded in the society of post-communist countries and it may manifest in different ways

Welter and Smallbone (2011) argue that entrepreneurs in transition economies have learnt

how to respond to institutional deficiencies in particular weak property rights protection For

example some businesses experiencing high growth choose to invest in unrelated

businesses instead of growing their core businesses for the reason they do not want to

become too noticeable to attract too much attention of the wrong sort In our instance having

some connections with officials seems also to serve as protection against arbitrary

government or individual rent-seeking that makes businesses more keen on re-investing their

retained profits (see Johnson et al (2002) on the discussion of how more secure property

rights can make small firms reinvest more of their earnings)

17

equity) using a SURE framework within which we specify a set of five tobit regressions with

correlated residuals

We employ the STATA cmp module which allows to it Seemingly Unrelated Regressions

using the simulated likelihood method such as the Geweke Hajivassiliou and Keane (GHK)

algorithm (for further discussion see Roodman 2008) We utilise a tobit equation to model

each individual financial choice of firms because our dependent financing choices variables

are continuous but their range is constrained (censored) with a substantial number of

observations either equal to zero denoting those who do not use the respective source of

finance or to 100 showing the opposite Other observations are positive and may produce

many different outcomes (Verbeek 2000) Each tobit equation uses a set of identical

explanatory variables that proxy factors which could possibly be associated with firmrsquos

financing choices including industry and country dummies

We also considered the bias caused by potential interdependence between the choice of

whether to invest and firmrsquos financing choices We accounted for the potential selection bias

by introducing into the financial choices SURE Tobit equations (second stage outcome

equations14) the inverse Millrsquos ratio calculated based on modelling the choice to invest in

fixed assets (first stage or selection equation) To identify the first stage of the Heckman

selection model we chose a variable which is correlated with the first stage dependent

variable (investment decision) but not with the second ones (financing choices) We used the

rate of capacity utilization as part of our identification strategy Capacity utilization shows the

percentage of capital stock in use the higher is the rate the more likely firms will increase

investment Batyaeva and Aukutsionek (2001) show that the rate of capacity utilization is

higher in the group of investing firms than in the group of non-investing firms in Russia15 We

calculated the inverse Millrsquos ratio based on the above selection equation16 and included it as

a control in the second stage SURE Tobit equations The inverse Millrsquos ratio has only proved

to be statistically significant in the private bank loan equation pointing to the potential

selection bias arising from the possibility that the factors determining the decision to invest

might differ from those determining the use of bank financing in purchasing fixed assets

14 We also attempted to estimate an investment equation jointly with Tobit financial choices equations within the SURE framework using However given the overall complexity of the model we failed to do this We proceeded further with a two-stage approach by estimating an investment probit equation and calculating the inverse Millrsquos ratio that we add into the outcome financial choices equations at the second stage of the analysis to test for the selection bias 15 We performed an independent sample t-test to check whether the rate of capacity utilization is statistically significantly higher for investing firms compared to non-investing firms for our sample The null hypothesis of no difference was rejected at 1 level of significance 16 To economize on space we do not report the results of the investment probit equation but they are available from authorsrsquo upon request

18

Finally In Table 6 we attempt to condition the determinants of financing constraints

declared by SMEs on the relative percentage increase of trade credit in total funds used for

real investment As mentioned above in Section 2 the timings of measuring the composition

of financing sources precede by a year the timings of measuring the perceptions of financing

constraints That feature of the BEEPSrsquo design allays a likely concern about the endogeneity

of the relative proportion of trade credit and enables causal inference We too report in thre

note to Table 4 the adjusted marginal effects for the interaction term of the SME dummy with

the trade credit variable

In the next section we discuss our empirical results

5 Empirical Results

Table 3 reports the results of the probit model with the marginal effects for firmsrsquo

perception of financial constraints while Tables 4-5 summarize the results of SURE tobits for

a more detailed breakdown of five financing choices More specifically Table 4 reports the

results based on the whole sample to give a comparative perspective on SMErsquos financing

strategy vis-a-vis large businesses whereas Table 5 reports the results based on a

subsample of small and medium-sized firms to shed some light on their financing choices in

the period of crisis

Perception of financial constraints

Table 3 shows that generally small and medium-sized enterprises feel more financially

constrained with the coefficient for SME dummy in relation to the large firms being positive

and significant which is consistent with our discussion in sections 2-3 However the

coefficient of the interaction term with the Crisis dummy turns out to be negative and

significant in relation to the perception of financial constraints as a major obstacle and it

tends to outweigh the effect of a SME dummy when we calculate marginal effects The effect

of the interaction terms with the crisis remains robust after we adjust for non-linearity using

the framework proposed by Norton Wang and Ai (2004)17 Overall these results confirm

that small and medium-sized enterprises are much less financially constrained during the

crisis years with their perceptions close to those of the large firms This result is a polar

opposite to that obtained for the SMEs in the UK (Fraser 2009) which finds that not only do

SMEs generally feel more financially constrained but they report to be even more so during

17 We also check the robustness of our results to the potential problem of multicollinearity between a crisis dummy and its interaction term with SME by splitting a sample and testing the same specification separately for SMEs and large firms We also perform another robustness check by breaking a SME dummy into three subsequent dummies namely micro- small- and medium-sized firms The difference in perception of financial constraints gets almost eliminated in the case of small firms and is largely reduced in the case of micro firms whereas it is less so for medium-sized firms

19

the last crisis We could explain this striking difference by the peculiarities of the SMEs

functioning in new emerging economies The lower reliance of SMEs on external debt in

good times (as shown by results which are discussed below) gives SMEs some flexibility

during the crisis when formal financial markets dry up Jointly with overall flexibility to make

necessary cost cuts and to restructure a business this overall lower reliance on external

funding and the use of alternative sources of financing makes SMEs feel less financially

constrained under the crisis as compared to larger firms

We also find that a more developed financial sector as proxied by domestic private

credit as proportion of GDP helps ease up financial constraints This is in line with the

general literature suggesting that better functioning financial intermediaries facilitate the risk

amelioration in the presence of problems created by market frictions (Levine 1997 Barth et

al 2006 Barth et al 2008)

Unfortunately we fail to find any significant effect of the property rights protection on

firmsrsquo perception of financial constraints that may be explained by the fact that the effect of a

more developed financial sector is likely to outweigh the effect of the property rights

protection

Finally we also find that foreign ownership and international product certificate may

reduce firmsrsquo borrowing constraints while any pressure from domestic or foreign competition

so is pressure from the customers to innovate will increase firmrsquos perception of financial

constraints as major given that firms envisage the need to secure external funding for RampD

or any other innovation-related activities

Financing choices for investment in fixed assets

The results in Table 4 indicate that small enterprises tend to rely more on internal funds

and less on bank loans but they are no different from larger firms in respect of using informal

funds trade credit or private equity which is generally consistent with our discussion in

Sections 2 and 3 The results of Table 5 suggest however that under crisis small and

medium-sized firms tend to switch to other sources of finance such as trade credit and

ownerrsquos contributed equity and to respectively reduce the reliance on retained earnings

perhaps because they decrease due to the negative impact of crisis internal funds With

regards to our discussion of SMEsrsquo risk management we note that the use of private equity

(ownerrsquos contribution) during the crisis years increases which could indicate that the ownerrsquos

funds are used as a cushion in the period of financial distress

An interesting insight regarding the use of trade credit emerges for SMEs in our

sample although in non-crisis years small and medium-sized businesses are not significantly

different from larger firms in terms of reliance on trade credit SMEs tend to finance a

significantly higher proportion of their fixed asset investment by trade credit than large firms

20

in the period of crisis While the latter finding is partly in line with some other studies ndash such

as Klapper and Randall (2010) using BEEPS data it is in stark contrast with similar studies

of the UK private firms (Rehman 2011) for which the use of trade credit is found to have

dried up in crisis This could partly be due to the passed legislation in the UK tightening trade

credit regulation as the result of the abuse of trade credit by large firms in relation to small

firms which forced many SMEs out of the market

With regards to the other firm-level characteristics international certification makes the

firm rely more on private bank loans and informal finance (Table 5) while SMEs with foreign

ownership rely less on private debt but more on retained earnings Both results are

consistent with our hypotheses discussed above Export-oriented small and medium-sized

businesses tend to have greater reliance on trade credit and they use less of internal funds

We find a non-monotonic relationship between age and private equity with both younger and

older firms being more reliant on this source of funding We find some fragmentary support

for private domestic SMEs relying more on informal finance while tending to use less trade

credit and private equity (Table 5)

Interestingly our results (Tables 4-5) suggest that firms which lack some social

connections with governmental officials proxied by the higher amount of time spent dealing

with government regulations are more likely to rely on informal finance trade credit and

private equity In turn businesses which are connected to governmental officials use more

retained profits to fund investment in fixed assets This may be attributed to their connections

serving as a guarantee from expropriation of assets by all sort of rent-seeking individuals

akin private contracting to secure property rights protection This result should be interpreted

jointly with the property rights protection results We expected that better property rights

protection is likely to facilitate firmsrsquo access to bank loan but we failed to confirm this

Perhaps regardless some attempts at a constitutional level to prevent arbitrary government

(which is proxied by our measure of property rights) expropriation culture is still deeply

embedded in the society of post-communist countries and it may manifest in different ways

Welter and Smallbone (2011) argue that entrepreneurs in transition economies have learnt

how to respond to institutional deficiencies in particular weak property rights protection For

example some businesses experiencing high growth choose to invest in unrelated

businesses instead of growing their core businesses for the reason they do not want to

become too noticeable to attract too much attention of the wrong sort In our instance having

some connections with officials seems also to serve as protection against arbitrary

government or individual rent-seeking that makes businesses more keen on re-investing their

retained profits (see Johnson et al (2002) on the discussion of how more secure property

rights can make small firms reinvest more of their earnings)

18

Finally In Table 6 we attempt to condition the determinants of financing constraints

declared by SMEs on the relative percentage increase of trade credit in total funds used for

real investment As mentioned above in Section 2 the timings of measuring the composition

of financing sources precede by a year the timings of measuring the perceptions of financing

constraints That feature of the BEEPSrsquo design allays a likely concern about the endogeneity

of the relative proportion of trade credit and enables causal inference We too report in thre

note to Table 4 the adjusted marginal effects for the interaction term of the SME dummy with

the trade credit variable

In the next section we discuss our empirical results

5 Empirical Results

Table 3 reports the results of the probit model with the marginal effects for firmsrsquo

perception of financial constraints while Tables 4-5 summarize the results of SURE tobits for

a more detailed breakdown of five financing choices More specifically Table 4 reports the

results based on the whole sample to give a comparative perspective on SMErsquos financing

strategy vis-a-vis large businesses whereas Table 5 reports the results based on a

subsample of small and medium-sized firms to shed some light on their financing choices in

the period of crisis

Perception of financial constraints

Table 3 shows that generally small and medium-sized enterprises feel more financially

constrained with the coefficient for SME dummy in relation to the large firms being positive

and significant which is consistent with our discussion in sections 2-3 However the

coefficient of the interaction term with the Crisis dummy turns out to be negative and

significant in relation to the perception of financial constraints as a major obstacle and it

tends to outweigh the effect of a SME dummy when we calculate marginal effects The effect

of the interaction terms with the crisis remains robust after we adjust for non-linearity using

the framework proposed by Norton Wang and Ai (2004)17 Overall these results confirm

that small and medium-sized enterprises are much less financially constrained during the

crisis years with their perceptions close to those of the large firms This result is a polar

opposite to that obtained for the SMEs in the UK (Fraser 2009) which finds that not only do

SMEs generally feel more financially constrained but they report to be even more so during

17 We also check the robustness of our results to the potential problem of multicollinearity between a crisis dummy and its interaction term with SME by splitting a sample and testing the same specification separately for SMEs and large firms We also perform another robustness check by breaking a SME dummy into three subsequent dummies namely micro- small- and medium-sized firms The difference in perception of financial constraints gets almost eliminated in the case of small firms and is largely reduced in the case of micro firms whereas it is less so for medium-sized firms

19

the last crisis We could explain this striking difference by the peculiarities of the SMEs

functioning in new emerging economies The lower reliance of SMEs on external debt in

good times (as shown by results which are discussed below) gives SMEs some flexibility

during the crisis when formal financial markets dry up Jointly with overall flexibility to make

necessary cost cuts and to restructure a business this overall lower reliance on external

funding and the use of alternative sources of financing makes SMEs feel less financially

constrained under the crisis as compared to larger firms

We also find that a more developed financial sector as proxied by domestic private

credit as proportion of GDP helps ease up financial constraints This is in line with the

general literature suggesting that better functioning financial intermediaries facilitate the risk

amelioration in the presence of problems created by market frictions (Levine 1997 Barth et

al 2006 Barth et al 2008)

Unfortunately we fail to find any significant effect of the property rights protection on

firmsrsquo perception of financial constraints that may be explained by the fact that the effect of a

more developed financial sector is likely to outweigh the effect of the property rights

protection

Finally we also find that foreign ownership and international product certificate may

reduce firmsrsquo borrowing constraints while any pressure from domestic or foreign competition

so is pressure from the customers to innovate will increase firmrsquos perception of financial

constraints as major given that firms envisage the need to secure external funding for RampD

or any other innovation-related activities

Financing choices for investment in fixed assets

The results in Table 4 indicate that small enterprises tend to rely more on internal funds

and less on bank loans but they are no different from larger firms in respect of using informal

funds trade credit or private equity which is generally consistent with our discussion in

Sections 2 and 3 The results of Table 5 suggest however that under crisis small and

medium-sized firms tend to switch to other sources of finance such as trade credit and

ownerrsquos contributed equity and to respectively reduce the reliance on retained earnings

perhaps because they decrease due to the negative impact of crisis internal funds With

regards to our discussion of SMEsrsquo risk management we note that the use of private equity

(ownerrsquos contribution) during the crisis years increases which could indicate that the ownerrsquos

funds are used as a cushion in the period of financial distress

An interesting insight regarding the use of trade credit emerges for SMEs in our

sample although in non-crisis years small and medium-sized businesses are not significantly

different from larger firms in terms of reliance on trade credit SMEs tend to finance a

significantly higher proportion of their fixed asset investment by trade credit than large firms

20

in the period of crisis While the latter finding is partly in line with some other studies ndash such

as Klapper and Randall (2010) using BEEPS data it is in stark contrast with similar studies

of the UK private firms (Rehman 2011) for which the use of trade credit is found to have

dried up in crisis This could partly be due to the passed legislation in the UK tightening trade

credit regulation as the result of the abuse of trade credit by large firms in relation to small

firms which forced many SMEs out of the market

With regards to the other firm-level characteristics international certification makes the

firm rely more on private bank loans and informal finance (Table 5) while SMEs with foreign

ownership rely less on private debt but more on retained earnings Both results are

consistent with our hypotheses discussed above Export-oriented small and medium-sized

businesses tend to have greater reliance on trade credit and they use less of internal funds

We find a non-monotonic relationship between age and private equity with both younger and

older firms being more reliant on this source of funding We find some fragmentary support

for private domestic SMEs relying more on informal finance while tending to use less trade

credit and private equity (Table 5)

Interestingly our results (Tables 4-5) suggest that firms which lack some social

connections with governmental officials proxied by the higher amount of time spent dealing

with government regulations are more likely to rely on informal finance trade credit and

private equity In turn businesses which are connected to governmental officials use more

retained profits to fund investment in fixed assets This may be attributed to their connections

serving as a guarantee from expropriation of assets by all sort of rent-seeking individuals

akin private contracting to secure property rights protection This result should be interpreted

jointly with the property rights protection results We expected that better property rights

protection is likely to facilitate firmsrsquo access to bank loan but we failed to confirm this

Perhaps regardless some attempts at a constitutional level to prevent arbitrary government

(which is proxied by our measure of property rights) expropriation culture is still deeply

embedded in the society of post-communist countries and it may manifest in different ways

Welter and Smallbone (2011) argue that entrepreneurs in transition economies have learnt

how to respond to institutional deficiencies in particular weak property rights protection For

example some businesses experiencing high growth choose to invest in unrelated

businesses instead of growing their core businesses for the reason they do not want to

become too noticeable to attract too much attention of the wrong sort In our instance having

some connections with officials seems also to serve as protection against arbitrary

government or individual rent-seeking that makes businesses more keen on re-investing their

retained profits (see Johnson et al (2002) on the discussion of how more secure property

rights can make small firms reinvest more of their earnings)

19

the last crisis We could explain this striking difference by the peculiarities of the SMEs

functioning in new emerging economies The lower reliance of SMEs on external debt in

good times (as shown by results which are discussed below) gives SMEs some flexibility

during the crisis when formal financial markets dry up Jointly with overall flexibility to make

necessary cost cuts and to restructure a business this overall lower reliance on external

funding and the use of alternative sources of financing makes SMEs feel less financially

constrained under the crisis as compared to larger firms

We also find that a more developed financial sector as proxied by domestic private

credit as proportion of GDP helps ease up financial constraints This is in line with the

general literature suggesting that better functioning financial intermediaries facilitate the risk

amelioration in the presence of problems created by market frictions (Levine 1997 Barth et

al 2006 Barth et al 2008)

Unfortunately we fail to find any significant effect of the property rights protection on

firmsrsquo perception of financial constraints that may be explained by the fact that the effect of a

more developed financial sector is likely to outweigh the effect of the property rights

protection

Finally we also find that foreign ownership and international product certificate may

reduce firmsrsquo borrowing constraints while any pressure from domestic or foreign competition

so is pressure from the customers to innovate will increase firmrsquos perception of financial

constraints as major given that firms envisage the need to secure external funding for RampD

or any other innovation-related activities

Financing choices for investment in fixed assets

The results in Table 4 indicate that small enterprises tend to rely more on internal funds

and less on bank loans but they are no different from larger firms in respect of using informal

funds trade credit or private equity which is generally consistent with our discussion in

Sections 2 and 3 The results of Table 5 suggest however that under crisis small and

medium-sized firms tend to switch to other sources of finance such as trade credit and

ownerrsquos contributed equity and to respectively reduce the reliance on retained earnings

perhaps because they decrease due to the negative impact of crisis internal funds With

regards to our discussion of SMEsrsquo risk management we note that the use of private equity

(ownerrsquos contribution) during the crisis years increases which could indicate that the ownerrsquos

funds are used as a cushion in the period of financial distress

An interesting insight regarding the use of trade credit emerges for SMEs in our

sample although in non-crisis years small and medium-sized businesses are not significantly

different from larger firms in terms of reliance on trade credit SMEs tend to finance a

significantly higher proportion of their fixed asset investment by trade credit than large firms

20

in the period of crisis While the latter finding is partly in line with some other studies ndash such

as Klapper and Randall (2010) using BEEPS data it is in stark contrast with similar studies

of the UK private firms (Rehman 2011) for which the use of trade credit is found to have

dried up in crisis This could partly be due to the passed legislation in the UK tightening trade

credit regulation as the result of the abuse of trade credit by large firms in relation to small

firms which forced many SMEs out of the market

With regards to the other firm-level characteristics international certification makes the

firm rely more on private bank loans and informal finance (Table 5) while SMEs with foreign

ownership rely less on private debt but more on retained earnings Both results are

consistent with our hypotheses discussed above Export-oriented small and medium-sized

businesses tend to have greater reliance on trade credit and they use less of internal funds

We find a non-monotonic relationship between age and private equity with both younger and

older firms being more reliant on this source of funding We find some fragmentary support

for private domestic SMEs relying more on informal finance while tending to use less trade

credit and private equity (Table 5)

Interestingly our results (Tables 4-5) suggest that firms which lack some social

connections with governmental officials proxied by the higher amount of time spent dealing

with government regulations are more likely to rely on informal finance trade credit and

private equity In turn businesses which are connected to governmental officials use more

retained profits to fund investment in fixed assets This may be attributed to their connections

serving as a guarantee from expropriation of assets by all sort of rent-seeking individuals

akin private contracting to secure property rights protection This result should be interpreted

jointly with the property rights protection results We expected that better property rights

protection is likely to facilitate firmsrsquo access to bank loan but we failed to confirm this

Perhaps regardless some attempts at a constitutional level to prevent arbitrary government

(which is proxied by our measure of property rights) expropriation culture is still deeply

embedded in the society of post-communist countries and it may manifest in different ways

Welter and Smallbone (2011) argue that entrepreneurs in transition economies have learnt

how to respond to institutional deficiencies in particular weak property rights protection For

example some businesses experiencing high growth choose to invest in unrelated

businesses instead of growing their core businesses for the reason they do not want to

become too noticeable to attract too much attention of the wrong sort In our instance having

some connections with officials seems also to serve as protection against arbitrary

government or individual rent-seeking that makes businesses more keen on re-investing their

retained profits (see Johnson et al (2002) on the discussion of how more secure property

rights can make small firms reinvest more of their earnings)

20

in the period of crisis While the latter finding is partly in line with some other studies ndash such

as Klapper and Randall (2010) using BEEPS data it is in stark contrast with similar studies

of the UK private firms (Rehman 2011) for which the use of trade credit is found to have

dried up in crisis This could partly be due to the passed legislation in the UK tightening trade

credit regulation as the result of the abuse of trade credit by large firms in relation to small

firms which forced many SMEs out of the market

With regards to the other firm-level characteristics international certification makes the

firm rely more on private bank loans and informal finance (Table 5) while SMEs with foreign

ownership rely less on private debt but more on retained earnings Both results are

consistent with our hypotheses discussed above Export-oriented small and medium-sized

businesses tend to have greater reliance on trade credit and they use less of internal funds

We find a non-monotonic relationship between age and private equity with both younger and

older firms being more reliant on this source of funding We find some fragmentary support

for private domestic SMEs relying more on informal finance while tending to use less trade

credit and private equity (Table 5)

Interestingly our results (Tables 4-5) suggest that firms which lack some social

connections with governmental officials proxied by the higher amount of time spent dealing

with government regulations are more likely to rely on informal finance trade credit and

private equity In turn businesses which are connected to governmental officials use more

retained profits to fund investment in fixed assets This may be attributed to their connections

serving as a guarantee from expropriation of assets by all sort of rent-seeking individuals

akin private contracting to secure property rights protection This result should be interpreted

jointly with the property rights protection results We expected that better property rights

protection is likely to facilitate firmsrsquo access to bank loan but we failed to confirm this

Perhaps regardless some attempts at a constitutional level to prevent arbitrary government

(which is proxied by our measure of property rights) expropriation culture is still deeply

embedded in the society of post-communist countries and it may manifest in different ways

Welter and Smallbone (2011) argue that entrepreneurs in transition economies have learnt

how to respond to institutional deficiencies in particular weak property rights protection For

example some businesses experiencing high growth choose to invest in unrelated

businesses instead of growing their core businesses for the reason they do not want to

become too noticeable to attract too much attention of the wrong sort In our instance having

some connections with officials seems also to serve as protection against arbitrary

government or individual rent-seeking that makes businesses more keen on re-investing their

retained profits (see Johnson et al (2002) on the discussion of how more secure property

rights can make small firms reinvest more of their earnings)

21

Pressure from domestic competition and customers on a firm to develop a new

product which may be a characteristic of oligopolistic or monopolistic competition structure

makes a firm more likely to rely more on bank finance

Interestingly we find the use of outsourcing by SMEs (Table 5) strongly and robustly

significant in explaining access to external funding

Our results show that SMEs in countries with low GDP per capita (the first three

quartiles up to the level of USD 10468 at ppp) tend to rely more on internal funds and less

on bank finance

We also investigate whether an increase in the relative percentage of trade credit in the

financing mix affects small firmsrsquo perceptions of financing constraints To this end we

estimate a probit model that conditions on relative share of trade credit and includes an

interaction term for the SME dummy and trade credit Reported in Table 6 this model

confirms that during a crisis flexibility in switching to alternative sources of finance such as

trade credit could be a possible determinant of perceptions of financing constraints In

particular the increase in a relative percentage of trade credit in the firmrsquos financing mix

picks up a significant difference in financing constraints across the size categories and

positively affects the propensity of SMEs to declare themselves as less financially

constrained

Overall our findings regarding firm- and industry-specific characteristics and the impact

of the institutional variables in all three specifications are generally consistent with the

hypotheses and literature discussed in Sections 2 and 3 with some exceptions which we will

summarise in the next section

22

6 Conclusions

Our key results may be summarized as follows

Consistent with the literature smaller businesses generally feel more financially

constrained in accessing external funding given the small scale of their investment projects

inability to provide good collateral and higher risk implying that financial institutions find it

costly to monitor small businesses

However in the situation of crisis as exemplified by the recent financial crisis which in

the 2008-09 spread to the transition economies the difference in perception of financial

constraints between smaller and larger firms is largely eliminated Our analysis suggests that

SMEs are more flexible in that they also rely on other sources of finance such as trade credit

and ownersrsquo contributed equity which may make them more flexible than large firms during

the years of crisis Furthermore smaller firms overall require less finance given the small

scale of their projects So they may be hit less by financial contraction compared to larger

firms the financial position of which is particularly undermined in the situation of global crises

when international financial markets dry up thus preventing larger firms from drawing upon

them when required Smaller firms are also more flexible and it is less costly for them to

restructure and downsize when they are hit with external shocks

Our second set of results relate to the firm characteristics Consistent with the literature

firmrsquos export orientation increases the reliance on trade credit and reduces the reliance on

internal funds while foreign ownership diminishes the reliance on bank lending Foreign firms

tend to rely more on retained earnings and intra-company fundsrsquo transfers in the case of

multinational businesses In our empirical study we also find that international product

certification increases the access to private loans and informal funding Our results also

suggest that social capital in the form of connections with officials is used by SMEs to

overcome deficiency of the property rights system and facilitate reinvestment of earnings by

small businesses

Finally our third set of the results is related to the role financial institutional

arrangements play for firm perception of financial constraints and financing decisions With

the development of the financial institutions the transactions costs of financial intermediation

may decrease reducing the cost of finance and increasing its availability Indeed we find that

a higher share of private credit to GDP is associated with firms relying more on private credit

in financing their investment decisions We also show that a size of the formal credit market

plays more prominent role in firmsrsquo perception of financial constraints

Our findings have some policy implications Overall a more developed financial sector

can mitigate market frictions to make bank finance more accessible by SMEs in good times

and to provide some incentives for small businesses to reinvest their earnings This may also

facilitate accumulation of cash by owner-managers which can be used as a cushion in bad

23

times However in the situation of external shocks and financial contraction the authorities

should focus on promoting trade credit that is seen as substitute for bank loans in bad times

References

Acemoglu D and S Johnson 2005 Unbundling Institutions Journal of Political Economy

113 943-995

Aidis R S Estrin and T Mickiewicz 2008 Institutions and Entrepreneurship Development in

Russia A Comparative Perspective Journal of Business Venturing 23(6)656-672

Aidis R Estrin S Mickiewicz T 2010 Size matters entrepreneurial entry and

government Small Business Economics DOI 101007s11187-010-9299-y

Arnold G 2008 Corporate Financial Management 4th Edition Prentice Hall

Atanasova and Wilson 2003 Bank Borrowing Constraints and the Demand for Trade Credit

Evidence from Panel Data Managerial and Decision Economics Special Issue The

Economics of Credit Management 24 (6-7) 503ndash514

Atanasova and Wilson 2004 Disequilibrium in the UK corporate loan market Journal of

Banking amp Finance 28 (March) 595-614

Barth J G Caprio and R Levine 2006 Rethinking Bank Regulation Till Angels Govern

Cambridge University Press New York

Barth J G Caprio and R Levine 2008 Bank Regulations Are Changing For Better or

Worse Working Paper Series 4646 World Bank Washington DC

Bates T 1997 Financial Business Creation The Case of Chinese and Korean Immigrant

Entrepreneurs Journal of Business Venturing 12109-124

Batyaeva A and S Aukutsionek (2001) Investment and Non-Investment in the Russian

Industry Journal of East-West Business 6(4) 5-22

Beck T and A de la Torre 2006 The basic analytics of access to financial services World

Bank Research Paper

Beck T A Demirguumlccedil-Kunt and V Maksimovic 2004 Financing patterns around the world

Are small firms different World Bank working paper

Beck T A Demirguumlccedil-Kunt and V Maksimovic (2005) ldquoFinancial and Legal Constraints to

Growth Does the Firm Size Matterrdquo The Journal of Finance Vol LX No1 February

2005

Beck T A Demirguumlccedil-Kunt L Laeven and V Maksimovic (2006) ldquoThe Determinants of

Financing Obstaclesrdquo The Journal of International Money and Finance 25 pp932-952

Beck T A Demirguumlccedil-Kunt and V Maksimovic 2008 ldquoFinancial Patterns Around the World

Are Small Firms Differentrdquo Journal of Financial Economics 89(3) 467-487

Berger A amp G Udell 1998 The Economics of Small Business Finance The Role of

22

6 Conclusions

Our key results may be summarized as follows

Consistent with the literature smaller businesses generally feel more financially

constrained in accessing external funding given the small scale of their investment projects

inability to provide good collateral and higher risk implying that financial institutions find it

costly to monitor small businesses

However in the situation of crisis as exemplified by the recent financial crisis which in

the 2008-09 spread to the transition economies the difference in perception of financial

constraints between smaller and larger firms is largely eliminated Our analysis suggests that

SMEs are more flexible in that they also rely on other sources of finance such as trade credit

and ownersrsquo contributed equity which may make them more flexible than large firms during

the years of crisis Furthermore smaller firms overall require less finance given the small

scale of their projects So they may be hit less by financial contraction compared to larger

firms the financial position of which is particularly undermined in the situation of global crises

when international financial markets dry up thus preventing larger firms from drawing upon

them when required Smaller firms are also more flexible and it is less costly for them to

restructure and downsize when they are hit with external shocks

Our second set of results relate to the firm characteristics Consistent with the literature

firmrsquos export orientation increases the reliance on trade credit and reduces the reliance on

internal funds while foreign ownership diminishes the reliance on bank lending Foreign firms

tend to rely more on retained earnings and intra-company fundsrsquo transfers in the case of

multinational businesses In our empirical study we also find that international product

certification increases the access to private loans and informal funding Our results also

suggest that social capital in the form of connections with officials is used by SMEs to

overcome deficiency of the property rights system and facilitate reinvestment of earnings by

small businesses

Finally our third set of the results is related to the role financial institutional

arrangements play for firm perception of financial constraints and financing decisions With

the development of the financial institutions the transactions costs of financial intermediation

may decrease reducing the cost of finance and increasing its availability Indeed we find that

a higher share of private credit to GDP is associated with firms relying more on private credit

in financing their investment decisions We also show that a size of the formal credit market

plays more prominent role in firmsrsquo perception of financial constraints

Our findings have some policy implications Overall a more developed financial sector

can mitigate market frictions to make bank finance more accessible by SMEs in good times

and to provide some incentives for small businesses to reinvest their earnings This may also

facilitate accumulation of cash by owner-managers which can be used as a cushion in bad

23

times However in the situation of external shocks and financial contraction the authorities

should focus on promoting trade credit that is seen as substitute for bank loans in bad times

References

Acemoglu D and S Johnson 2005 Unbundling Institutions Journal of Political Economy

113 943-995

Aidis R S Estrin and T Mickiewicz 2008 Institutions and Entrepreneurship Development in

Russia A Comparative Perspective Journal of Business Venturing 23(6)656-672

Aidis R Estrin S Mickiewicz T 2010 Size matters entrepreneurial entry and

government Small Business Economics DOI 101007s11187-010-9299-y

Arnold G 2008 Corporate Financial Management 4th Edition Prentice Hall

Atanasova and Wilson 2003 Bank Borrowing Constraints and the Demand for Trade Credit

Evidence from Panel Data Managerial and Decision Economics Special Issue The

Economics of Credit Management 24 (6-7) 503ndash514

Atanasova and Wilson 2004 Disequilibrium in the UK corporate loan market Journal of

Banking amp Finance 28 (March) 595-614

Barth J G Caprio and R Levine 2006 Rethinking Bank Regulation Till Angels Govern

Cambridge University Press New York

Barth J G Caprio and R Levine 2008 Bank Regulations Are Changing For Better or

Worse Working Paper Series 4646 World Bank Washington DC

Bates T 1997 Financial Business Creation The Case of Chinese and Korean Immigrant

Entrepreneurs Journal of Business Venturing 12109-124

Batyaeva A and S Aukutsionek (2001) Investment and Non-Investment in the Russian

Industry Journal of East-West Business 6(4) 5-22

Beck T and A de la Torre 2006 The basic analytics of access to financial services World

Bank Research Paper

Beck T A Demirguumlccedil-Kunt and V Maksimovic 2004 Financing patterns around the world

Are small firms different World Bank working paper

Beck T A Demirguumlccedil-Kunt and V Maksimovic (2005) ldquoFinancial and Legal Constraints to

Growth Does the Firm Size Matterrdquo The Journal of Finance Vol LX No1 February

2005

Beck T A Demirguumlccedil-Kunt L Laeven and V Maksimovic (2006) ldquoThe Determinants of

Financing Obstaclesrdquo The Journal of International Money and Finance 25 pp932-952

Beck T A Demirguumlccedil-Kunt and V Maksimovic 2008 ldquoFinancial Patterns Around the World

Are Small Firms Differentrdquo Journal of Financial Economics 89(3) 467-487

Berger A amp G Udell 1998 The Economics of Small Business Finance The Role of

23

times However in the situation of external shocks and financial contraction the authorities

should focus on promoting trade credit that is seen as substitute for bank loans in bad times

References

Acemoglu D and S Johnson 2005 Unbundling Institutions Journal of Political Economy

113 943-995

Aidis R S Estrin and T Mickiewicz 2008 Institutions and Entrepreneurship Development in

Russia A Comparative Perspective Journal of Business Venturing 23(6)656-672

Aidis R Estrin S Mickiewicz T 2010 Size matters entrepreneurial entry and

government Small Business Economics DOI 101007s11187-010-9299-y

Arnold G 2008 Corporate Financial Management 4th Edition Prentice Hall

Atanasova and Wilson 2003 Bank Borrowing Constraints and the Demand for Trade Credit

Evidence from Panel Data Managerial and Decision Economics Special Issue The

Economics of Credit Management 24 (6-7) 503ndash514

Atanasova and Wilson 2004 Disequilibrium in the UK corporate loan market Journal of

Banking amp Finance 28 (March) 595-614

Barth J G Caprio and R Levine 2006 Rethinking Bank Regulation Till Angels Govern

Cambridge University Press New York

Barth J G Caprio and R Levine 2008 Bank Regulations Are Changing For Better or

Worse Working Paper Series 4646 World Bank Washington DC

Bates T 1997 Financial Business Creation The Case of Chinese and Korean Immigrant

Entrepreneurs Journal of Business Venturing 12109-124

Batyaeva A and S Aukutsionek (2001) Investment and Non-Investment in the Russian

Industry Journal of East-West Business 6(4) 5-22

Beck T and A de la Torre 2006 The basic analytics of access to financial services World

Bank Research Paper

Beck T A Demirguumlccedil-Kunt and V Maksimovic 2004 Financing patterns around the world

Are small firms different World Bank working paper

Beck T A Demirguumlccedil-Kunt and V Maksimovic (2005) ldquoFinancial and Legal Constraints to

Growth Does the Firm Size Matterrdquo The Journal of Finance Vol LX No1 February

2005

Beck T A Demirguumlccedil-Kunt L Laeven and V Maksimovic (2006) ldquoThe Determinants of

Financing Obstaclesrdquo The Journal of International Money and Finance 25 pp932-952

Beck T A Demirguumlccedil-Kunt and V Maksimovic 2008 ldquoFinancial Patterns Around the World

Are Small Firms Differentrdquo Journal of Financial Economics 89(3) 467-487

Berger A amp G Udell 1998 The Economics of Small Business Finance The Role of

24

Private Equity and Debt Markets in the Financial Growth Cycle Journal of Banking

and Finance 22 613ndash73

Berglof E and Bolton P 2002 The great divide and beyond financial architecture in

transition Journal of Economic Perspectives 16 (1 Winter) pp 77-100

Bernanke B S amp M Gertler 1995 Inside the Black Box The Credit Channel of Monetary

Policy Transmission NBER Working Papers 5146 National Bureau of Economic Research

Inc

Bernanke B M Gertler amp S Gilchrist 1998 The Financial Accelerator in a Quantitative

Business Cycle Framework in Taylor J amp M Woodford (ed) 1999 Handbook of

Macroeconomics Elsevier 1(1)

Bevan A and J Danbolt 2002 Capital structure and its determinants in the UK - a

decompositional analysis Applied Financial Economics 12(3) 159-170

Bygrave W 2003 Financing Entrepreneurs and their Ventures In P Reynolds W Bygrave

and E Autio eds Global Entrepreneurship Monitor 2003 Global Report Kansas City

Kauffman Center for Entrepreneurial Leadership at the Ewing Mario Kauffman Foundation

Calderon C Didier T 2009 Severity Of The Crisis And Its Transmission Channels World Bank LAC Research Report CantonE I Grilo J Monteagudo and P van der Zwan 2010 Investigating the Perceptions

of Credit Constraints in the European Union Erasmus Research Institute of Management

Report

Chakraborty I 2008 Capital Structure in Emerging Stock Market The Case of India

Research in International Business and Finance doi101016jribaf201002001

Chang C Lee A amp Lee C 2009 Determinants of Capital Structure Choice A Structural

Equation Modeling Approach Quarterly Journal of Economics and Finance 49 197-213

Commander SJ amp J Svejnar 2011 Business Environment Exports Ownership and Firm

Performance Review of Economics and Statistics 931 309-337

Correa PG Fernandes AM amp Uregian C 2010 Technology Adoption and the Investment

Climate Firm-Level Evidence for Eastern Europe and Central Asia The World

Bank Economic Review 24 121-147

Crnigoj M 2007 Risk Averse Insiders with Specific Objective Function and Capital

Structure Mimeo

Cull R and L C Xu 2007 Formal Finance and Trade Credit during Chinarsquos Transition

World Bank Policy Research Working Paper 4204

De La Torre AM Peria and S Schmukler 2008 Bank Involvement with SMEs Beyond

Relationship Lending Working Paper Series 4649 World Bank Washington DC

Delcoure N 2007 The Determinants of Capital Structure in Transitional Economies

25

International Review of Economics and Finance 16 400-415

Didier T Hevia C and Schmukler SL 2011 How Resilient Were Emerging Economies to the Global Crisis World Bank Policy Research Working Paper No 5637

Estrin S and T Mickiewicz 2010 Entrepreneurship in Transition Economies The Role of

Institutions Forthcoming in edited volume by M Minitti at Oxford UP

Estrin S J Korostelva and T Mickiewicz 2011 Which Institutions Encourage Entrepreneurs

to Create Larger Firms IZA Discussion Paper 5481 available from

httpftpizaorgdp5481pdf

Ge Y and J Qiu 2007 Financial Development Bank Discrimination and Trade Credit

Journal of Banking amp Finance 31 513ndash530

Gertler M and S Gilchrist 1993 The Role of Credit Market Imperfections in the Monetary

Transmission Mechanism Arguments and Evidence The Scandinavian Journal of

Economics 95(1) (Mar 1993) 43-64

Girma S Gong Y amp Gorg H 2008 Foreign Direct Investment Access to Finance and

Innovation Activity in Chinese Enterprises The World Bank Economic Review 22 367-382

Glaeser E R La Porta F Lopez-de-Silanes and A Shleifer Do Institutions Cause

Growth NBER Working Paper Series 10568 2004

Gorodnichenko Y and M Schnitzer 2010 Financial constraints and innovation Why poor

countries donrsquot catch up NBER working papers 15792 National Bureau of Economic

Research Inc

Fraser S 2009 Small Firms in the Credit Crisis Evidence from the UK Survey of SME Finances Economic and Social Research Council Report Available at httpwww2warwickacukfacsocwbsresearchcsmeresearchlatestsmall_firms_in_the_credit_crisis_v3-oct09pdf Herbane B 2011 Small business research Time for a crisis-based view International Small

Business Journal 28(1)43ndash64

Huyghebaert N 2001 The Capital Structure of the Business Start-ups Determinants of

Initial Capital Structure Review of Banking and Finance 284-88

Isachenkova N J Korosteleva and Y Rodionova 2011 Financing Choices A Study of

Entrepreneurial Firms in High-tech Industries CSESCE Working Paper No Centre for

the Study of Economic and Social Change in Europe UCL London

Johnson S J McMillan and C Woodruff 2002 Property Rights and Finance The American

Economic Review 92 (5)1335-1356

Klapper L V Sarria-Allende and V Sulla 2002 Small- and Medium-Size Enterprise

Financing in Eastern Europe World Bank Policy Research Working Paper 2933

26

Klapper L F and Randall D 2010 ldquoThe Impact of the Financial Crisis on Supply-Chain

Financingrdquo World Bank Group Enterprise note No 13Korosteleva J and Mickiewicz T

2011 Startup finance in the age of globalisation Emerging Markets Finance and Trade

47(3) 23-49

Korosteleva J and C Lawson (2010) The Belarusian Case of Transition Whither Financial

Repression Post-Communist Economies Vol 22(1)

Levine R 1997 Financial Development and Economic Growth Views and Agenda Journal

of Economic Literature 35 (June) 688-726

Li K Yue H amp Zhao L 2009 Ownership Institutions and Capital Structure Evidence

From China Journal of Comparative Economics 37 471-490

Lizal L and J Svejnar 2002 Investment credit rationing and the soft budget constraint

evidence from Czech panel data Review of Economics and Statistics 84(2) 353-370

Love I 2003 Financial development and financing constraints International evidence from

the structural investment model Review of Financial Studies 16(3) pp 765-79

Love I and R Zaidi 2010 Trade Credit Bank Credit and Financial Crisis International

Review of Finance 10(1) 125-147 March

Mateut S S Bougheas and P Mizen 2006 Trade credit bank lending and monetary

policy transmission European Economic Review 50(3) 603-629

Matthews C H and S G Scott1995 Uncertainty and Planning in Small and

Entrepreneurial Firms An Empirical Assessment Journal of Small Business management

23(4) 34-52

Meltzer A H 1960 Mercantile Credit Monetary Policy and Size of Firms The Review of

Economics and Statistics 42 (4 ) (Nov 1960) 429-437

Mitra P amp Muravyev A amp M Schaffer 2008 Convergence in Institutions and Market

Outcomes Cross-Country and Time-Series Evidence from the BEEPS Surveys in Transition

Economies IZA Discussion Papers 3863 Institute for the Study of Labor (IZA)

Modigliani F and MH Miller 1958 The Cost of Capital Corporation Finance and the

Theory of Investment American Economic Review 48(3) pp 261-97

Nielsen J H 2002 Trade Credit and the Bank Lending Channel Journal of Money Credit

and Banking 34 226-253

Nivorozhkin E 2005 Financing Choices of Firms in EU Accession Countries Emerging

Markets Review 6 138-169

Norton E Wang H and C Ai 2004 Computing Interaction Effects in Logit and Probit

Models The Stata Journal 4(2) 103-116

Petersen M A and R G Rajan 1997 Trade Credit Theory and Evidence Review of

Financial Studies 10 661ndash691

27

Pissarides F 1998 Is Lack of Funds the Main Obstacle to Growth EBRD Working Paper

No 33

Pissarides F 1999 Is Lack of Funds the Main Obstacle to Growth EBRDrsquos Experience with

Small- and Medium-sized Businesses in Central and Eastern Europe Journal of Business

Venturing 14 519-539

Pissarides F 2001 Financial Structure to Promote Private Sector Development in South-

Eastern Europe EBRD Working Paper No 64

Pissarides F M Singer and J Svejnar 2003 Objectives and Constraints of Entrepreneurs

Evidence from Small and Medium Size Enterprises in Russia and Bulgaria Journal of

Comparative Economics 31 503-531

Radygin A D A E Gontmakher M G Kuzyk I V Mezheraup H Swain Yu V

Simachiov N A Shmeleva and R M Entov 2005 The institution of Bankruptcy

Development Problems Areas of Reforming Consortium for Economic Policy Research and

Advice Moscow 2005

Ravid S and M Spiegel 1997 Optimal Financing Contracts for a Start-up with Unlimited

Operating Discretion Journal of Financial and Quantitative Analysis 32 269-86

Rostowski J ed 1995 Banking reform in Central Europe and the Soviet Union Budapest

Central University Press

Rehman Shafiq 2011 The Effect of Financial Crisis on the Behaviour of Trade Credit A

Study of the UK Private Firms BAFA Northern Area Group Annual Conference 6th

Septmeber 2011

Roodman D 2009 Estimating Fully Observed Recursive Mixed-Process Models with cmp CGD Working Paper 168 Washington DC Center for Global Development Sprenger C 2002 ldquoOwnership and Corporate Governance in Russian Industry a Surveyrdquo

EBRD Working Paper No70

Stijn Claessens and Konstantinos Tzioumis 2006 Measuring firmsrsquo access to finance

World Bank Working Paper

Taketa G and K Udell 2007 Lending Channels and Financial Shocks The Case of Small

and Medium-Sized Enterprise Trade Credit and the Japanese Banking Crisis Monetary and

Economic Studies Institute for Monetary and Economic Studies Bank of Japan 25(2) 1- 44

November

Tornell A and F Westermann 2005 Boom-Bust Cycles and Financial Liberalization

Cambridge MA MIT Press

Verbeek M (2000) A Guide to Modern Econometrics John Wiley amp Sons New York

28

Welter F and D Smallbone 2011 Institutional Perspective on Entrepreneurial Behaviour in

Challenging Environments Journal of Small Business Management 49(1) 107-125

World Bank (2011) World Development Indicators (edition September 2011) ESDS

International University of Manchester DOI httpdxdoiorg105257wbwdi2011-09

Zellner A 1962 An efficient method of estimating seemingly unrelated regression equations

and tests for aggregation bias Journal of the American Statistical Association 57 348ndash368

Zou H and Adams 2008 Debt Capacity Cost of Debt and Corporate Insurance Journal of

Financial and Quantitative Analysis 43 433-466

28

Welter F and D Smallbone 2011 Institutional Perspective on Entrepreneurial Behaviour in

Challenging Environments Journal of Small Business Management 49(1) 107-125

World Bank (2011) World Development Indicators (edition September 2011) ESDS

International University of Manchester DOI httpdxdoiorg105257wbwdi2011-09

Zellner A 1962 An efficient method of estimating seemingly unrelated regression equations

and tests for aggregation bias Journal of the American Statistical Association 57 348ndash368

Zou H and Adams 2008 Debt Capacity Cost of Debt and Corporate Insurance Journal of

Financial and Quantitative Analysis 43 433-466

29

Figure 1 Domestic Credit to Private Sector (as of GDP) in Transition Economies and

Comparator Countries selectively 1991-2010

Source World Bank (2011) Figure 2 Market Capitalisation (as of GDP) in Transition Economies and

Comparator Countries selectively 1991-2010

000

5000

10000

15000

20000

25000

1991 1993 1995 1998 2001 2004 2007 2008 2009 2010

China Czech Rep Estonia Germany Hungary Kazakhstan

Lithuania Poland Russian Federation Slovenia United States

30

Source World Bank (2011) Source World Bank (2011)

000

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

1991 1993 1995 1998 2001 2004 2007 2008 2009 2010

China Czech Rep Estonia Germany Hungary KazakhstanLithuania Poland Russian Federation Slovenia United States

Figure 3 Percentage of SMEsobstacle in operating business 2002

Source Authorsrsquo calculations based on BEEPS 2002access to of finance (incl its availability and cost) is No ObstaModerate Obstacle a Major Obstacle a Very Severe Obstacle to the current operations of their firms The figure shows only percentage of firms which find access to finance as both a major and very severe obstacle Please note firmemployment criterion in accordance with Eurostat criteria micro firm sized - 10-49 employees mediumand over SMEs are respectively def

Percentage of SMEs vs Large firms that perceive access to finance as a major obstacle in operating business 2002-2009

Source Authorsrsquo calculations based on BEEPS 2002-09 Respondents were asked whether access to of finance (incl its availability and cost) is No Obstacle a Minor Obstacle a Moderate Obstacle a Major Obstacle a Very Severe Obstacle to the current operations of their firms The figure shows only percentage of firms which find access to finance as both a major and very severe obstacle Please note firms were classified by size on the basis of employment criterion in accordance with Eurostat criteria micro firm -

49 employees medium-sized - 50- 249 employees and large and over SMEs are respectively defined as employing less than 250 employees

31

vs Large firms that perceive access to finance as a major

09 Respondents were asked whether cle a Minor Obstacle a

Moderate Obstacle a Major Obstacle a Very Severe Obstacle to the current operations of their firms The figure shows only percentage of firms which find access to finance as both a

s were classified by size on the basis of - 0-9 employees small-

249 employees and large - 250 employees ined as employing less than 250 employees

Figure 4 Sources of financing SMEsrsquo investments

Source Authorsrsquo calculations based on BEEPS 2002estimate the proportion of their firmsrsquo total purchase of fixed assets thathe previous year from each of the sources listed on the diagram

Figure 4 Sources of financing SMEsrsquo investments

Source Authorsrsquo calculations based on BEEPS 2002-09 Respondents were asked to estimate the proportion of their firmsrsquo total purchase of fixed assets thathe previous year from each of the sources listed on the diagram

32

09 Respondents were asked to estimate the proportion of their firmsrsquo total purchase of fixed assets that was financed over

33

Table 1 Descriptive statistics and definitions of variables

Variable Definition Mean SD No of obs EXPLANATORY variables Institutional variables and macroeconomic controls Property rights (t-1)

Polity IV lsquoExecutive Constraintsrsquo scores from 1=rdquounlimited authorityrdquo to 7=rdquoexecutive parityrdquo higher value denotes less arbitrariness

572 175 21867

Domestic credit as a of GDP (t-1)

Ratio of credit to private sector to GDP (WB WDI April 2009)

3211 1878 21477

GDP per capita (t-1)

GDP per capita at purchasing power parity constant at 2005 $USD (WB WDI April 2009)

99472 543073 21867

GDP growth (t-1)

Annual GDP growth rate (WB WDI April 2009) 629 324 21867

Firm and industry-level characteristics Small amp medium-sized firms

1=small firms with a number of employees being gt=1 and lt250 0 otherwise

893 309 21835

Crisis 1=2008 amp 2009 0 otherwise 26 44 21867 Age Age of firm in 2008 or in 2009 years 2084 10268 21859 Age squared Age squared - - 21859 International product certification

1=firm in a process of applying or it has an international product certificate 0 otherwise

35 76 21766

Foreign ownership Percent owned by foreign individuals companies or organisations

982 2746 21469

Export orientation Percent of sales exported directly or indirectly 1137 2577 21828 Privately owned from inception

1=firm is private from inception 75 43 18767

Time spent on dealing with government regulations

Percent of time spent on dealing with government regulations

843 1348 20701

Pressure to innovate originates from domestic competition

1=Yes 0 otherwise 283 103 20186

Pressure to innovate originates from foreign competition

1=Yes 0 otherwise 208 114 19707

Pressure to innovate originates from customers

1=Yes 0 otherwise 29 104 20093

DEPENDENT variables Probit model Perception of financial constraints

1=firm perceives financial constraints as major or very severe 0 otherwise

22 42 20934

SURE tobit model Retained profits Retained profits as a of firm financing of fixed

assets 6692 4039 14491

34

Private loan Private loan as a of firm financing of fixed assets

1268 2763 13246

Trade credit Trade credit as a of firm financing of fixed assets

367 1483 14267

Privatecontributed equity

Privatecontributed equity as a of firm financing of fixed assets

415 1768 14257

Informal funding Money from family friends and other money lenders as a of firm financing of fixed assets

998 2551 13279

Source BEEPS 2002-2009 unless specified otherwise

35

Table 2 Correlation Matrix for the dependent and macro-level variables

Variables

Percep

of

financial

const-s

Retaine

d profits

Private

loan

Inform

al

finance

Trade

credit

Private

equity

SME

Crisis

Property

rights

Dom

estic

credit

GDP pc

ppp

GDP

grow

th

Perception

of financial

constraints

1

Retained

profits

-008

1

Private loan

003

-053

1

Inform

al

finance

004

-047

-012

1

Trade credit

003

-029

-004

-005

1

Private

equity

003

-033

-006

-007

-003

1

SME

003

005

-006

-001

-002

002

1

Crisis

009

-012

015

-016

012

011

002

1

Property

rights (t-1)

000

-013

010

005

-002

004

001

-005

1

Dom

estic

credit (t-1)

0002

-016

017

-008

006

009

001

052

043

1

GDP pc ppp

(t-1)

-002

-013

006

0002

002

004

-001

19

046

064

1

GDP growth

(t-1)

-001

011

-008

-0001

-002

-001

001

-017

044

-050

-055

1

Source BEEPS 2002-2009 W

B W

DI A

pr 2009 Polity IV

36

Table 3 Perception of Financial Constraints probit estimation results and marginal effects Dependent variable Perception of financial constraints as a major obstacle

probit results probit marginal effects

Coef Robust Std Err

Coef Robust Std Err

Small and Medium-sized enterprises 0203 0058 0052 0014 Crisis 0890 0126 0301 0047 Small and Medium-sized_x_Crisis -0273 0113 -0069 0026 International Product Certification -0057 0020 -0016 0005 Privately owned from inception 0012 0036 0003 0010 Time spent on dealing with government regulations 0005 0001 0001 00003 Pressure to innovate originates from domestic competition 0071 0015 0020 0004 Pressure to innovate originates from foreign competition 0078 0016 0022 0004 Pressure to innovate originates from customers 0048 0013 0013 0004 Foreign Ownership -0005 0001 -0001 00001 Export orientation -00001 0001 -0000018 00002 Age -0001 0001 -00002853 00003 Age squared x 10-07 497 525 137 145 Domestic Credit as of GDP (t-1) -0009 0003 -0003 0001 Property Rights (t-1) 0028 0058 0008 0016 GDP growth (t-1) -0023 0008 -0006 0002 Outsourced product 0024 0043 0007 0012 GDP per capita ppp (t-1) Quartile1 0257 0210 0075 0065 GDP per capita ppp (t-1) Quartile 2 0338 0160 0100 0050 GDP per capita ppp (t-1) Quartile 3 0091 0123 0026 0036 GDP per capita ppp (t-1) Quartile 4 0180 0079 0052 0023 Constant -2094 433 na na Industrial controls Yes Yes Yes Yes Country controls Yes Yes Yes Yes Number of obs 12807 12807 Pseudo R2 00673 00673 Source BEEPS 2002-2009 WB WDI Apr 2009 Polity IV Note significance levels - 1 - 5 - 10 For the interaction term of SME and crisis the marginal effect is different from the one reported in the table above After controlling for non-linearity following Norton et al 2004 the coefficient of the interaction term at mean is equal to -0074 standard error is equal to 0038 and z statistic is equal to -190 indicating significance at 001 level

37

Table 4 SURE Tobits results for Firmsrsquo Financing Choices (based on whole sample)

Dependent variable Retained profits

Private Loan

Informal Finance

Trade Credit

Private Equity

Explanatory variables Coef Coef Coef Coef Coef

Crisis -1468 14429 -34767 4368 73231 (348) (6410) (7329) (9464) (11454)

SME 430 -13399 -1525 -3524 -4729 (1879) (3438) (3489) (5247) (7219) International Product Certification -0697 4192 4165 1884 -0852

(0720) (1306) (1311) (2107) (2728) Privately owned from inception 0866 2911 5778 -8569 -4307

(1276) (2541) (2486) (3825) (4811) Time spent on dealing with government regulations -0133 -0018 0323 0246 0346 (0042) (0081) (0076) (0112) (0134) Pressure to innovate originates from domestic competition -128 3166 3024 2552 -2404

(0522) (1052) (1029) (1644) (199) Pressure to innovate originates from foreign competition -0499 0746 2258 0056 845 (0463) (114) (1131) (1745) (2195) Pressure to innovate originates from customers -952 2428 138 2339 3297

(0581) (0915) (0864) (141) (1762) Foreign Ownership 0050 -0094 -0045 -0013 -0003

(0017) (0033) (0032) (0050) (0064) Export orientation -0072 0118 0026 0153 -0035

(0022) (004) (004) (0063) (0080) Age 0042 -0039 -0127 -005 -028

(0037) (007) (0074) (0109) (0149)

Age squared x 10-04 -0204 0246 0453 213 143

(0189) (035) (0367) (539) (070) Domestic credit as of GDP (t-1) 0445 0516 -0976 -0840 -1578 (0120) (0230) (0227) (0349) (0457) Property Rights (t-1) -818 7486 -6239 -741 -22129

(244) (5232) (5211) (7244) (10025) GDP growth (t-1) 0149 1198 -0923 -0623 2098

(0335) (0615) (0669) (906) (119)

30

Source World Bank (2011) Source World Bank (2011)

000

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

1991 1993 1995 1998 2001 2004 2007 2008 2009 2010

China Czech Rep Estonia Germany Hungary KazakhstanLithuania Poland Russian Federation Slovenia United States

Figure 3 Percentage of SMEsobstacle in operating business 2002

Source Authorsrsquo calculations based on BEEPS 2002access to of finance (incl its availability and cost) is No ObstaModerate Obstacle a Major Obstacle a Very Severe Obstacle to the current operations of their firms The figure shows only percentage of firms which find access to finance as both a major and very severe obstacle Please note firmemployment criterion in accordance with Eurostat criteria micro firm sized - 10-49 employees mediumand over SMEs are respectively def

Percentage of SMEs vs Large firms that perceive access to finance as a major obstacle in operating business 2002-2009

Source Authorsrsquo calculations based on BEEPS 2002-09 Respondents were asked whether access to of finance (incl its availability and cost) is No Obstacle a Minor Obstacle a Moderate Obstacle a Major Obstacle a Very Severe Obstacle to the current operations of their firms The figure shows only percentage of firms which find access to finance as both a major and very severe obstacle Please note firms were classified by size on the basis of employment criterion in accordance with Eurostat criteria micro firm -

49 employees medium-sized - 50- 249 employees and large and over SMEs are respectively defined as employing less than 250 employees

31

vs Large firms that perceive access to finance as a major

09 Respondents were asked whether cle a Minor Obstacle a

Moderate Obstacle a Major Obstacle a Very Severe Obstacle to the current operations of their firms The figure shows only percentage of firms which find access to finance as both a

s were classified by size on the basis of - 0-9 employees small-

249 employees and large - 250 employees ined as employing less than 250 employees

Figure 4 Sources of financing SMEsrsquo investments

Source Authorsrsquo calculations based on BEEPS 2002estimate the proportion of their firmsrsquo total purchase of fixed assets thathe previous year from each of the sources listed on the diagram

Figure 4 Sources of financing SMEsrsquo investments

Source Authorsrsquo calculations based on BEEPS 2002-09 Respondents were asked to estimate the proportion of their firmsrsquo total purchase of fixed assets thathe previous year from each of the sources listed on the diagram

32

09 Respondents were asked to estimate the proportion of their firmsrsquo total purchase of fixed assets that was financed over

33

Table 1 Descriptive statistics and definitions of variables

Variable Definition Mean SD No of obs EXPLANATORY variables Institutional variables and macroeconomic controls Property rights (t-1)

Polity IV lsquoExecutive Constraintsrsquo scores from 1=rdquounlimited authorityrdquo to 7=rdquoexecutive parityrdquo higher value denotes less arbitrariness

572 175 21867

Domestic credit as a of GDP (t-1)

Ratio of credit to private sector to GDP (WB WDI April 2009)

3211 1878 21477

GDP per capita (t-1)

GDP per capita at purchasing power parity constant at 2005 $USD (WB WDI April 2009)

99472 543073 21867

GDP growth (t-1)

Annual GDP growth rate (WB WDI April 2009) 629 324 21867

Firm and industry-level characteristics Small amp medium-sized firms

1=small firms with a number of employees being gt=1 and lt250 0 otherwise

893 309 21835

Crisis 1=2008 amp 2009 0 otherwise 26 44 21867 Age Age of firm in 2008 or in 2009 years 2084 10268 21859 Age squared Age squared - - 21859 International product certification

1=firm in a process of applying or it has an international product certificate 0 otherwise

35 76 21766

Foreign ownership Percent owned by foreign individuals companies or organisations

982 2746 21469

Export orientation Percent of sales exported directly or indirectly 1137 2577 21828 Privately owned from inception

1=firm is private from inception 75 43 18767

Time spent on dealing with government regulations

Percent of time spent on dealing with government regulations

843 1348 20701

Pressure to innovate originates from domestic competition

1=Yes 0 otherwise 283 103 20186

Pressure to innovate originates from foreign competition

1=Yes 0 otherwise 208 114 19707

Pressure to innovate originates from customers

1=Yes 0 otherwise 29 104 20093

DEPENDENT variables Probit model Perception of financial constraints

1=firm perceives financial constraints as major or very severe 0 otherwise

22 42 20934

SURE tobit model Retained profits Retained profits as a of firm financing of fixed

assets 6692 4039 14491

34

Private loan Private loan as a of firm financing of fixed assets

1268 2763 13246

Trade credit Trade credit as a of firm financing of fixed assets

367 1483 14267

Privatecontributed equity

Privatecontributed equity as a of firm financing of fixed assets

415 1768 14257

Informal funding Money from family friends and other money lenders as a of firm financing of fixed assets

998 2551 13279

Source BEEPS 2002-2009 unless specified otherwise

35

Table 2 Correlation Matrix for the dependent and macro-level variables

Variables

Percep

of

financial

const-s

Retaine

d profits

Private

loan

Inform

al

finance

Trade

credit

Private

equity

SME

Crisis

Property

rights

Dom

estic

credit

GDP pc

ppp

GDP

grow

th

Perception

of financial

constraints

1

Retained

profits

-008

1

Private loan

003

-053

1

Inform

al

finance

004

-047

-012

1

Trade credit

003

-029

-004

-005

1

Private

equity

003

-033

-006

-007

-003

1

SME

003

005

-006

-001

-002

002

1

Crisis

009

-012

015

-016

012

011

002

1

Property

rights (t-1)

000

-013

010

005

-002

004

001

-005

1

Dom

estic

credit (t-1)

0002

-016

017

-008

006

009

001

052

043

1

GDP pc ppp

(t-1)

-002

-013

006

0002

002

004

-001

19

046

064

1

GDP growth

(t-1)

-001

011

-008

-0001

-002

-001

001

-017

044

-050

-055

1

Source BEEPS 2002-2009 W

B W

DI A

pr 2009 Polity IV

36

Table 3 Perception of Financial Constraints probit estimation results and marginal effects Dependent variable Perception of financial constraints as a major obstacle

probit results probit marginal effects

Coef Robust Std Err

Coef Robust Std Err

Small and Medium-sized enterprises 0203 0058 0052 0014 Crisis 0890 0126 0301 0047 Small and Medium-sized_x_Crisis -0273 0113 -0069 0026 International Product Certification -0057 0020 -0016 0005 Privately owned from inception 0012 0036 0003 0010 Time spent on dealing with government regulations 0005 0001 0001 00003 Pressure to innovate originates from domestic competition 0071 0015 0020 0004 Pressure to innovate originates from foreign competition 0078 0016 0022 0004 Pressure to innovate originates from customers 0048 0013 0013 0004 Foreign Ownership -0005 0001 -0001 00001 Export orientation -00001 0001 -0000018 00002 Age -0001 0001 -00002853 00003 Age squared x 10-07 497 525 137 145 Domestic Credit as of GDP (t-1) -0009 0003 -0003 0001 Property Rights (t-1) 0028 0058 0008 0016 GDP growth (t-1) -0023 0008 -0006 0002 Outsourced product 0024 0043 0007 0012 GDP per capita ppp (t-1) Quartile1 0257 0210 0075 0065 GDP per capita ppp (t-1) Quartile 2 0338 0160 0100 0050 GDP per capita ppp (t-1) Quartile 3 0091 0123 0026 0036 GDP per capita ppp (t-1) Quartile 4 0180 0079 0052 0023 Constant -2094 433 na na Industrial controls Yes Yes Yes Yes Country controls Yes Yes Yes Yes Number of obs 12807 12807 Pseudo R2 00673 00673 Source BEEPS 2002-2009 WB WDI Apr 2009 Polity IV Note significance levels - 1 - 5 - 10 For the interaction term of SME and crisis the marginal effect is different from the one reported in the table above After controlling for non-linearity following Norton et al 2004 the coefficient of the interaction term at mean is equal to -0074 standard error is equal to 0038 and z statistic is equal to -190 indicating significance at 001 level

37

Table 4 SURE Tobits results for Firmsrsquo Financing Choices (based on whole sample)

Dependent variable Retained profits

Private Loan

Informal Finance

Trade Credit

Private Equity

Explanatory variables Coef Coef Coef Coef Coef

Crisis -1468 14429 -34767 4368 73231 (348) (6410) (7329) (9464) (11454)

SME 430 -13399 -1525 -3524 -4729 (1879) (3438) (3489) (5247) (7219) International Product Certification -0697 4192 4165 1884 -0852

(0720) (1306) (1311) (2107) (2728) Privately owned from inception 0866 2911 5778 -8569 -4307

(1276) (2541) (2486) (3825) (4811) Time spent on dealing with government regulations -0133 -0018 0323 0246 0346 (0042) (0081) (0076) (0112) (0134) Pressure to innovate originates from domestic competition -128 3166 3024 2552 -2404

(0522) (1052) (1029) (1644) (199) Pressure to innovate originates from foreign competition -0499 0746 2258 0056 845 (0463) (114) (1131) (1745) (2195) Pressure to innovate originates from customers -952 2428 138 2339 3297

(0581) (0915) (0864) (141) (1762) Foreign Ownership 0050 -0094 -0045 -0013 -0003

(0017) (0033) (0032) (0050) (0064) Export orientation -0072 0118 0026 0153 -0035

(0022) (004) (004) (0063) (0080) Age 0042 -0039 -0127 -005 -028

(0037) (007) (0074) (0109) (0149)

Age squared x 10-04 -0204 0246 0453 213 143

(0189) (035) (0367) (539) (070) Domestic credit as of GDP (t-1) 0445 0516 -0976 -0840 -1578 (0120) (0230) (0227) (0349) (0457) Property Rights (t-1) -818 7486 -6239 -741 -22129

(244) (5232) (5211) (7244) (10025) GDP growth (t-1) 0149 1198 -0923 -0623 2098

(0335) (0615) (0669) (906) (119)

Figure 3 Percentage of SMEsobstacle in operating business 2002

Source Authorsrsquo calculations based on BEEPS 2002access to of finance (incl its availability and cost) is No ObstaModerate Obstacle a Major Obstacle a Very Severe Obstacle to the current operations of their firms The figure shows only percentage of firms which find access to finance as both a major and very severe obstacle Please note firmemployment criterion in accordance with Eurostat criteria micro firm sized - 10-49 employees mediumand over SMEs are respectively def

Percentage of SMEs vs Large firms that perceive access to finance as a major obstacle in operating business 2002-2009

Source Authorsrsquo calculations based on BEEPS 2002-09 Respondents were asked whether access to of finance (incl its availability and cost) is No Obstacle a Minor Obstacle a Moderate Obstacle a Major Obstacle a Very Severe Obstacle to the current operations of their firms The figure shows only percentage of firms which find access to finance as both a major and very severe obstacle Please note firms were classified by size on the basis of employment criterion in accordance with Eurostat criteria micro firm -

49 employees medium-sized - 50- 249 employees and large and over SMEs are respectively defined as employing less than 250 employees

31

vs Large firms that perceive access to finance as a major

09 Respondents were asked whether cle a Minor Obstacle a

Moderate Obstacle a Major Obstacle a Very Severe Obstacle to the current operations of their firms The figure shows only percentage of firms which find access to finance as both a

s were classified by size on the basis of - 0-9 employees small-

249 employees and large - 250 employees ined as employing less than 250 employees

Figure 4 Sources of financing SMEsrsquo investments

Source Authorsrsquo calculations based on BEEPS 2002estimate the proportion of their firmsrsquo total purchase of fixed assets thathe previous year from each of the sources listed on the diagram

Figure 4 Sources of financing SMEsrsquo investments

Source Authorsrsquo calculations based on BEEPS 2002-09 Respondents were asked to estimate the proportion of their firmsrsquo total purchase of fixed assets thathe previous year from each of the sources listed on the diagram

32

09 Respondents were asked to estimate the proportion of their firmsrsquo total purchase of fixed assets that was financed over

33

Table 1 Descriptive statistics and definitions of variables

Variable Definition Mean SD No of obs EXPLANATORY variables Institutional variables and macroeconomic controls Property rights (t-1)

Polity IV lsquoExecutive Constraintsrsquo scores from 1=rdquounlimited authorityrdquo to 7=rdquoexecutive parityrdquo higher value denotes less arbitrariness

572 175 21867

Domestic credit as a of GDP (t-1)

Ratio of credit to private sector to GDP (WB WDI April 2009)

3211 1878 21477

GDP per capita (t-1)

GDP per capita at purchasing power parity constant at 2005 $USD (WB WDI April 2009)

99472 543073 21867

GDP growth (t-1)

Annual GDP growth rate (WB WDI April 2009) 629 324 21867

Firm and industry-level characteristics Small amp medium-sized firms

1=small firms with a number of employees being gt=1 and lt250 0 otherwise

893 309 21835

Crisis 1=2008 amp 2009 0 otherwise 26 44 21867 Age Age of firm in 2008 or in 2009 years 2084 10268 21859 Age squared Age squared - - 21859 International product certification

1=firm in a process of applying or it has an international product certificate 0 otherwise

35 76 21766

Foreign ownership Percent owned by foreign individuals companies or organisations

982 2746 21469

Export orientation Percent of sales exported directly or indirectly 1137 2577 21828 Privately owned from inception

1=firm is private from inception 75 43 18767

Time spent on dealing with government regulations

Percent of time spent on dealing with government regulations

843 1348 20701

Pressure to innovate originates from domestic competition

1=Yes 0 otherwise 283 103 20186

Pressure to innovate originates from foreign competition

1=Yes 0 otherwise 208 114 19707

Pressure to innovate originates from customers

1=Yes 0 otherwise 29 104 20093

DEPENDENT variables Probit model Perception of financial constraints

1=firm perceives financial constraints as major or very severe 0 otherwise

22 42 20934

SURE tobit model Retained profits Retained profits as a of firm financing of fixed

assets 6692 4039 14491

34

Private loan Private loan as a of firm financing of fixed assets

1268 2763 13246

Trade credit Trade credit as a of firm financing of fixed assets

367 1483 14267

Privatecontributed equity

Privatecontributed equity as a of firm financing of fixed assets

415 1768 14257

Informal funding Money from family friends and other money lenders as a of firm financing of fixed assets

998 2551 13279

Source BEEPS 2002-2009 unless specified otherwise

35

Table 2 Correlation Matrix for the dependent and macro-level variables

Variables

Percep

of

financial

const-s

Retaine

d profits

Private

loan

Inform

al

finance

Trade

credit

Private

equity

SME

Crisis

Property

rights

Dom

estic

credit

GDP pc

ppp

GDP

grow

th

Perception

of financial

constraints

1

Retained

profits

-008

1

Private loan

003

-053

1

Inform

al

finance

004

-047

-012

1

Trade credit

003

-029

-004

-005

1

Private

equity

003

-033

-006

-007

-003

1

SME

003

005

-006

-001

-002

002

1

Crisis

009

-012

015

-016

012

011

002

1

Property

rights (t-1)

000

-013

010

005

-002

004

001

-005

1

Dom

estic

credit (t-1)

0002

-016

017

-008

006

009

001

052

043

1

GDP pc ppp

(t-1)

-002

-013

006

0002

002

004

-001

19

046

064

1

GDP growth

(t-1)

-001

011

-008

-0001

-002

-001

001

-017

044

-050

-055

1

Source BEEPS 2002-2009 W

B W

DI A

pr 2009 Polity IV

36

Table 3 Perception of Financial Constraints probit estimation results and marginal effects Dependent variable Perception of financial constraints as a major obstacle

probit results probit marginal effects

Coef Robust Std Err

Coef Robust Std Err

Small and Medium-sized enterprises 0203 0058 0052 0014 Crisis 0890 0126 0301 0047 Small and Medium-sized_x_Crisis -0273 0113 -0069 0026 International Product Certification -0057 0020 -0016 0005 Privately owned from inception 0012 0036 0003 0010 Time spent on dealing with government regulations 0005 0001 0001 00003 Pressure to innovate originates from domestic competition 0071 0015 0020 0004 Pressure to innovate originates from foreign competition 0078 0016 0022 0004 Pressure to innovate originates from customers 0048 0013 0013 0004 Foreign Ownership -0005 0001 -0001 00001 Export orientation -00001 0001 -0000018 00002 Age -0001 0001 -00002853 00003 Age squared x 10-07 497 525 137 145 Domestic Credit as of GDP (t-1) -0009 0003 -0003 0001 Property Rights (t-1) 0028 0058 0008 0016 GDP growth (t-1) -0023 0008 -0006 0002 Outsourced product 0024 0043 0007 0012 GDP per capita ppp (t-1) Quartile1 0257 0210 0075 0065 GDP per capita ppp (t-1) Quartile 2 0338 0160 0100 0050 GDP per capita ppp (t-1) Quartile 3 0091 0123 0026 0036 GDP per capita ppp (t-1) Quartile 4 0180 0079 0052 0023 Constant -2094 433 na na Industrial controls Yes Yes Yes Yes Country controls Yes Yes Yes Yes Number of obs 12807 12807 Pseudo R2 00673 00673 Source BEEPS 2002-2009 WB WDI Apr 2009 Polity IV Note significance levels - 1 - 5 - 10 For the interaction term of SME and crisis the marginal effect is different from the one reported in the table above After controlling for non-linearity following Norton et al 2004 the coefficient of the interaction term at mean is equal to -0074 standard error is equal to 0038 and z statistic is equal to -190 indicating significance at 001 level

37

Table 4 SURE Tobits results for Firmsrsquo Financing Choices (based on whole sample)

Dependent variable Retained profits

Private Loan

Informal Finance

Trade Credit

Private Equity

Explanatory variables Coef Coef Coef Coef Coef

Crisis -1468 14429 -34767 4368 73231 (348) (6410) (7329) (9464) (11454)

SME 430 -13399 -1525 -3524 -4729 (1879) (3438) (3489) (5247) (7219) International Product Certification -0697 4192 4165 1884 -0852

(0720) (1306) (1311) (2107) (2728) Privately owned from inception 0866 2911 5778 -8569 -4307

(1276) (2541) (2486) (3825) (4811) Time spent on dealing with government regulations -0133 -0018 0323 0246 0346 (0042) (0081) (0076) (0112) (0134) Pressure to innovate originates from domestic competition -128 3166 3024 2552 -2404

(0522) (1052) (1029) (1644) (199) Pressure to innovate originates from foreign competition -0499 0746 2258 0056 845 (0463) (114) (1131) (1745) (2195) Pressure to innovate originates from customers -952 2428 138 2339 3297

(0581) (0915) (0864) (141) (1762) Foreign Ownership 0050 -0094 -0045 -0013 -0003

(0017) (0033) (0032) (0050) (0064) Export orientation -0072 0118 0026 0153 -0035

(0022) (004) (004) (0063) (0080) Age 0042 -0039 -0127 -005 -028

(0037) (007) (0074) (0109) (0149)

Age squared x 10-04 -0204 0246 0453 213 143

(0189) (035) (0367) (539) (070) Domestic credit as of GDP (t-1) 0445 0516 -0976 -0840 -1578 (0120) (0230) (0227) (0349) (0457) Property Rights (t-1) -818 7486 -6239 -741 -22129

(244) (5232) (5211) (7244) (10025) GDP growth (t-1) 0149 1198 -0923 -0623 2098

(0335) (0615) (0669) (906) (119)

Figure 4 Sources of financing SMEsrsquo investments

Source Authorsrsquo calculations based on BEEPS 2002estimate the proportion of their firmsrsquo total purchase of fixed assets thathe previous year from each of the sources listed on the diagram

Figure 4 Sources of financing SMEsrsquo investments

Source Authorsrsquo calculations based on BEEPS 2002-09 Respondents were asked to estimate the proportion of their firmsrsquo total purchase of fixed assets thathe previous year from each of the sources listed on the diagram

32

09 Respondents were asked to estimate the proportion of their firmsrsquo total purchase of fixed assets that was financed over

33

Table 1 Descriptive statistics and definitions of variables

Variable Definition Mean SD No of obs EXPLANATORY variables Institutional variables and macroeconomic controls Property rights (t-1)

Polity IV lsquoExecutive Constraintsrsquo scores from 1=rdquounlimited authorityrdquo to 7=rdquoexecutive parityrdquo higher value denotes less arbitrariness

572 175 21867

Domestic credit as a of GDP (t-1)

Ratio of credit to private sector to GDP (WB WDI April 2009)

3211 1878 21477

GDP per capita (t-1)

GDP per capita at purchasing power parity constant at 2005 $USD (WB WDI April 2009)

99472 543073 21867

GDP growth (t-1)

Annual GDP growth rate (WB WDI April 2009) 629 324 21867

Firm and industry-level characteristics Small amp medium-sized firms

1=small firms with a number of employees being gt=1 and lt250 0 otherwise

893 309 21835

Crisis 1=2008 amp 2009 0 otherwise 26 44 21867 Age Age of firm in 2008 or in 2009 years 2084 10268 21859 Age squared Age squared - - 21859 International product certification

1=firm in a process of applying or it has an international product certificate 0 otherwise

35 76 21766

Foreign ownership Percent owned by foreign individuals companies or organisations

982 2746 21469

Export orientation Percent of sales exported directly or indirectly 1137 2577 21828 Privately owned from inception

1=firm is private from inception 75 43 18767

Time spent on dealing with government regulations

Percent of time spent on dealing with government regulations

843 1348 20701

Pressure to innovate originates from domestic competition

1=Yes 0 otherwise 283 103 20186

Pressure to innovate originates from foreign competition

1=Yes 0 otherwise 208 114 19707

Pressure to innovate originates from customers

1=Yes 0 otherwise 29 104 20093

DEPENDENT variables Probit model Perception of financial constraints

1=firm perceives financial constraints as major or very severe 0 otherwise

22 42 20934

SURE tobit model Retained profits Retained profits as a of firm financing of fixed

assets 6692 4039 14491

34

Private loan Private loan as a of firm financing of fixed assets

1268 2763 13246

Trade credit Trade credit as a of firm financing of fixed assets

367 1483 14267

Privatecontributed equity

Privatecontributed equity as a of firm financing of fixed assets

415 1768 14257

Informal funding Money from family friends and other money lenders as a of firm financing of fixed assets

998 2551 13279

Source BEEPS 2002-2009 unless specified otherwise

35

Table 2 Correlation Matrix for the dependent and macro-level variables

Variables

Percep

of

financial

const-s

Retaine

d profits

Private

loan

Inform

al

finance

Trade

credit

Private

equity

SME

Crisis

Property

rights

Dom

estic

credit

GDP pc

ppp

GDP

grow

th

Perception

of financial

constraints

1

Retained

profits

-008

1

Private loan

003

-053

1

Inform

al

finance

004

-047

-012

1

Trade credit

003

-029

-004

-005

1

Private

equity

003

-033

-006

-007

-003

1

SME

003

005

-006

-001

-002

002

1

Crisis

009

-012

015

-016

012

011

002

1

Property

rights (t-1)

000

-013

010

005

-002

004

001

-005

1

Dom

estic

credit (t-1)

0002

-016

017

-008

006

009

001

052

043

1

GDP pc ppp

(t-1)

-002

-013

006

0002

002

004

-001

19

046

064

1

GDP growth

(t-1)

-001

011

-008

-0001

-002

-001

001

-017

044

-050

-055

1

Source BEEPS 2002-2009 W

B W

DI A

pr 2009 Polity IV

36

Table 3 Perception of Financial Constraints probit estimation results and marginal effects Dependent variable Perception of financial constraints as a major obstacle

probit results probit marginal effects

Coef Robust Std Err

Coef Robust Std Err

Small and Medium-sized enterprises 0203 0058 0052 0014 Crisis 0890 0126 0301 0047 Small and Medium-sized_x_Crisis -0273 0113 -0069 0026 International Product Certification -0057 0020 -0016 0005 Privately owned from inception 0012 0036 0003 0010 Time spent on dealing with government regulations 0005 0001 0001 00003 Pressure to innovate originates from domestic competition 0071 0015 0020 0004 Pressure to innovate originates from foreign competition 0078 0016 0022 0004 Pressure to innovate originates from customers 0048 0013 0013 0004 Foreign Ownership -0005 0001 -0001 00001 Export orientation -00001 0001 -0000018 00002 Age -0001 0001 -00002853 00003 Age squared x 10-07 497 525 137 145 Domestic Credit as of GDP (t-1) -0009 0003 -0003 0001 Property Rights (t-1) 0028 0058 0008 0016 GDP growth (t-1) -0023 0008 -0006 0002 Outsourced product 0024 0043 0007 0012 GDP per capita ppp (t-1) Quartile1 0257 0210 0075 0065 GDP per capita ppp (t-1) Quartile 2 0338 0160 0100 0050 GDP per capita ppp (t-1) Quartile 3 0091 0123 0026 0036 GDP per capita ppp (t-1) Quartile 4 0180 0079 0052 0023 Constant -2094 433 na na Industrial controls Yes Yes Yes Yes Country controls Yes Yes Yes Yes Number of obs 12807 12807 Pseudo R2 00673 00673 Source BEEPS 2002-2009 WB WDI Apr 2009 Polity IV Note significance levels - 1 - 5 - 10 For the interaction term of SME and crisis the marginal effect is different from the one reported in the table above After controlling for non-linearity following Norton et al 2004 the coefficient of the interaction term at mean is equal to -0074 standard error is equal to 0038 and z statistic is equal to -190 indicating significance at 001 level

37

Table 4 SURE Tobits results for Firmsrsquo Financing Choices (based on whole sample)

Dependent variable Retained profits

Private Loan

Informal Finance

Trade Credit

Private Equity

Explanatory variables Coef Coef Coef Coef Coef

Crisis -1468 14429 -34767 4368 73231 (348) (6410) (7329) (9464) (11454)

SME 430 -13399 -1525 -3524 -4729 (1879) (3438) (3489) (5247) (7219) International Product Certification -0697 4192 4165 1884 -0852

(0720) (1306) (1311) (2107) (2728) Privately owned from inception 0866 2911 5778 -8569 -4307

(1276) (2541) (2486) (3825) (4811) Time spent on dealing with government regulations -0133 -0018 0323 0246 0346 (0042) (0081) (0076) (0112) (0134) Pressure to innovate originates from domestic competition -128 3166 3024 2552 -2404

(0522) (1052) (1029) (1644) (199) Pressure to innovate originates from foreign competition -0499 0746 2258 0056 845 (0463) (114) (1131) (1745) (2195) Pressure to innovate originates from customers -952 2428 138 2339 3297

(0581) (0915) (0864) (141) (1762) Foreign Ownership 0050 -0094 -0045 -0013 -0003

(0017) (0033) (0032) (0050) (0064) Export orientation -0072 0118 0026 0153 -0035

(0022) (004) (004) (0063) (0080) Age 0042 -0039 -0127 -005 -028

(0037) (007) (0074) (0109) (0149)

Age squared x 10-04 -0204 0246 0453 213 143

(0189) (035) (0367) (539) (070) Domestic credit as of GDP (t-1) 0445 0516 -0976 -0840 -1578 (0120) (0230) (0227) (0349) (0457) Property Rights (t-1) -818 7486 -6239 -741 -22129

(244) (5232) (5211) (7244) (10025) GDP growth (t-1) 0149 1198 -0923 -0623 2098

(0335) (0615) (0669) (906) (119)

33

Table 1 Descriptive statistics and definitions of variables

Variable Definition Mean SD No of obs EXPLANATORY variables Institutional variables and macroeconomic controls Property rights (t-1)

Polity IV lsquoExecutive Constraintsrsquo scores from 1=rdquounlimited authorityrdquo to 7=rdquoexecutive parityrdquo higher value denotes less arbitrariness

572 175 21867

Domestic credit as a of GDP (t-1)

Ratio of credit to private sector to GDP (WB WDI April 2009)

3211 1878 21477

GDP per capita (t-1)

GDP per capita at purchasing power parity constant at 2005 $USD (WB WDI April 2009)

99472 543073 21867

GDP growth (t-1)

Annual GDP growth rate (WB WDI April 2009) 629 324 21867

Firm and industry-level characteristics Small amp medium-sized firms

1=small firms with a number of employees being gt=1 and lt250 0 otherwise

893 309 21835

Crisis 1=2008 amp 2009 0 otherwise 26 44 21867 Age Age of firm in 2008 or in 2009 years 2084 10268 21859 Age squared Age squared - - 21859 International product certification

1=firm in a process of applying or it has an international product certificate 0 otherwise

35 76 21766

Foreign ownership Percent owned by foreign individuals companies or organisations

982 2746 21469

Export orientation Percent of sales exported directly or indirectly 1137 2577 21828 Privately owned from inception

1=firm is private from inception 75 43 18767

Time spent on dealing with government regulations

Percent of time spent on dealing with government regulations

843 1348 20701

Pressure to innovate originates from domestic competition

1=Yes 0 otherwise 283 103 20186

Pressure to innovate originates from foreign competition

1=Yes 0 otherwise 208 114 19707

Pressure to innovate originates from customers

1=Yes 0 otherwise 29 104 20093

DEPENDENT variables Probit model Perception of financial constraints

1=firm perceives financial constraints as major or very severe 0 otherwise

22 42 20934

SURE tobit model Retained profits Retained profits as a of firm financing of fixed

assets 6692 4039 14491

34

Private loan Private loan as a of firm financing of fixed assets

1268 2763 13246

Trade credit Trade credit as a of firm financing of fixed assets

367 1483 14267

Privatecontributed equity

Privatecontributed equity as a of firm financing of fixed assets

415 1768 14257

Informal funding Money from family friends and other money lenders as a of firm financing of fixed assets

998 2551 13279

Source BEEPS 2002-2009 unless specified otherwise

35

Table 2 Correlation Matrix for the dependent and macro-level variables

Variables

Percep

of

financial

const-s

Retaine

d profits

Private

loan

Inform

al

finance

Trade

credit

Private

equity

SME

Crisis

Property

rights

Dom

estic

credit

GDP pc

ppp

GDP

grow

th

Perception

of financial

constraints

1

Retained

profits

-008

1

Private loan

003

-053

1

Inform

al

finance

004

-047

-012

1

Trade credit

003

-029

-004

-005

1

Private

equity

003

-033

-006

-007

-003

1

SME

003

005

-006

-001

-002

002

1

Crisis

009

-012

015

-016

012

011

002

1

Property

rights (t-1)

000

-013

010

005

-002

004

001

-005

1

Dom

estic

credit (t-1)

0002

-016

017

-008

006

009

001

052

043

1

GDP pc ppp

(t-1)

-002

-013

006

0002

002

004

-001

19

046

064

1

GDP growth

(t-1)

-001

011

-008

-0001

-002

-001

001

-017

044

-050

-055

1

Source BEEPS 2002-2009 W

B W

DI A

pr 2009 Polity IV

36

Table 3 Perception of Financial Constraints probit estimation results and marginal effects Dependent variable Perception of financial constraints as a major obstacle

probit results probit marginal effects

Coef Robust Std Err

Coef Robust Std Err

Small and Medium-sized enterprises 0203 0058 0052 0014 Crisis 0890 0126 0301 0047 Small and Medium-sized_x_Crisis -0273 0113 -0069 0026 International Product Certification -0057 0020 -0016 0005 Privately owned from inception 0012 0036 0003 0010 Time spent on dealing with government regulations 0005 0001 0001 00003 Pressure to innovate originates from domestic competition 0071 0015 0020 0004 Pressure to innovate originates from foreign competition 0078 0016 0022 0004 Pressure to innovate originates from customers 0048 0013 0013 0004 Foreign Ownership -0005 0001 -0001 00001 Export orientation -00001 0001 -0000018 00002 Age -0001 0001 -00002853 00003 Age squared x 10-07 497 525 137 145 Domestic Credit as of GDP (t-1) -0009 0003 -0003 0001 Property Rights (t-1) 0028 0058 0008 0016 GDP growth (t-1) -0023 0008 -0006 0002 Outsourced product 0024 0043 0007 0012 GDP per capita ppp (t-1) Quartile1 0257 0210 0075 0065 GDP per capita ppp (t-1) Quartile 2 0338 0160 0100 0050 GDP per capita ppp (t-1) Quartile 3 0091 0123 0026 0036 GDP per capita ppp (t-1) Quartile 4 0180 0079 0052 0023 Constant -2094 433 na na Industrial controls Yes Yes Yes Yes Country controls Yes Yes Yes Yes Number of obs 12807 12807 Pseudo R2 00673 00673 Source BEEPS 2002-2009 WB WDI Apr 2009 Polity IV Note significance levels - 1 - 5 - 10 For the interaction term of SME and crisis the marginal effect is different from the one reported in the table above After controlling for non-linearity following Norton et al 2004 the coefficient of the interaction term at mean is equal to -0074 standard error is equal to 0038 and z statistic is equal to -190 indicating significance at 001 level

37

Table 4 SURE Tobits results for Firmsrsquo Financing Choices (based on whole sample)

Dependent variable Retained profits

Private Loan

Informal Finance

Trade Credit

Private Equity

Explanatory variables Coef Coef Coef Coef Coef

Crisis -1468 14429 -34767 4368 73231 (348) (6410) (7329) (9464) (11454)

SME 430 -13399 -1525 -3524 -4729 (1879) (3438) (3489) (5247) (7219) International Product Certification -0697 4192 4165 1884 -0852

(0720) (1306) (1311) (2107) (2728) Privately owned from inception 0866 2911 5778 -8569 -4307

(1276) (2541) (2486) (3825) (4811) Time spent on dealing with government regulations -0133 -0018 0323 0246 0346 (0042) (0081) (0076) (0112) (0134) Pressure to innovate originates from domestic competition -128 3166 3024 2552 -2404

(0522) (1052) (1029) (1644) (199) Pressure to innovate originates from foreign competition -0499 0746 2258 0056 845 (0463) (114) (1131) (1745) (2195) Pressure to innovate originates from customers -952 2428 138 2339 3297

(0581) (0915) (0864) (141) (1762) Foreign Ownership 0050 -0094 -0045 -0013 -0003

(0017) (0033) (0032) (0050) (0064) Export orientation -0072 0118 0026 0153 -0035

(0022) (004) (004) (0063) (0080) Age 0042 -0039 -0127 -005 -028

(0037) (007) (0074) (0109) (0149)

Age squared x 10-04 -0204 0246 0453 213 143

(0189) (035) (0367) (539) (070) Domestic credit as of GDP (t-1) 0445 0516 -0976 -0840 -1578 (0120) (0230) (0227) (0349) (0457) Property Rights (t-1) -818 7486 -6239 -741 -22129

(244) (5232) (5211) (7244) (10025) GDP growth (t-1) 0149 1198 -0923 -0623 2098

(0335) (0615) (0669) (906) (119)

34

Private loan Private loan as a of firm financing of fixed assets

1268 2763 13246

Trade credit Trade credit as a of firm financing of fixed assets

367 1483 14267

Privatecontributed equity

Privatecontributed equity as a of firm financing of fixed assets

415 1768 14257

Informal funding Money from family friends and other money lenders as a of firm financing of fixed assets

998 2551 13279

Source BEEPS 2002-2009 unless specified otherwise

35

Table 2 Correlation Matrix for the dependent and macro-level variables

Variables

Percep

of

financial

const-s

Retaine

d profits

Private

loan

Inform

al

finance

Trade

credit

Private

equity

SME

Crisis

Property

rights

Dom

estic

credit

GDP pc

ppp

GDP

grow

th

Perception

of financial

constraints

1

Retained

profits

-008

1

Private loan

003

-053

1

Inform

al

finance

004

-047

-012

1

Trade credit

003

-029

-004

-005

1

Private

equity

003

-033

-006

-007

-003

1

SME

003

005

-006

-001

-002

002

1

Crisis

009

-012

015

-016

012

011

002

1

Property

rights (t-1)

000

-013

010

005

-002

004

001

-005

1

Dom

estic

credit (t-1)

0002

-016

017

-008

006

009

001

052

043

1

GDP pc ppp

(t-1)

-002

-013

006

0002

002

004

-001

19

046

064

1

GDP growth

(t-1)

-001

011

-008

-0001

-002

-001

001

-017

044

-050

-055

1

Source BEEPS 2002-2009 W

B W

DI A

pr 2009 Polity IV

36

Table 3 Perception of Financial Constraints probit estimation results and marginal effects Dependent variable Perception of financial constraints as a major obstacle

probit results probit marginal effects

Coef Robust Std Err

Coef Robust Std Err

Small and Medium-sized enterprises 0203 0058 0052 0014 Crisis 0890 0126 0301 0047 Small and Medium-sized_x_Crisis -0273 0113 -0069 0026 International Product Certification -0057 0020 -0016 0005 Privately owned from inception 0012 0036 0003 0010 Time spent on dealing with government regulations 0005 0001 0001 00003 Pressure to innovate originates from domestic competition 0071 0015 0020 0004 Pressure to innovate originates from foreign competition 0078 0016 0022 0004 Pressure to innovate originates from customers 0048 0013 0013 0004 Foreign Ownership -0005 0001 -0001 00001 Export orientation -00001 0001 -0000018 00002 Age -0001 0001 -00002853 00003 Age squared x 10-07 497 525 137 145 Domestic Credit as of GDP (t-1) -0009 0003 -0003 0001 Property Rights (t-1) 0028 0058 0008 0016 GDP growth (t-1) -0023 0008 -0006 0002 Outsourced product 0024 0043 0007 0012 GDP per capita ppp (t-1) Quartile1 0257 0210 0075 0065 GDP per capita ppp (t-1) Quartile 2 0338 0160 0100 0050 GDP per capita ppp (t-1) Quartile 3 0091 0123 0026 0036 GDP per capita ppp (t-1) Quartile 4 0180 0079 0052 0023 Constant -2094 433 na na Industrial controls Yes Yes Yes Yes Country controls Yes Yes Yes Yes Number of obs 12807 12807 Pseudo R2 00673 00673 Source BEEPS 2002-2009 WB WDI Apr 2009 Polity IV Note significance levels - 1 - 5 - 10 For the interaction term of SME and crisis the marginal effect is different from the one reported in the table above After controlling for non-linearity following Norton et al 2004 the coefficient of the interaction term at mean is equal to -0074 standard error is equal to 0038 and z statistic is equal to -190 indicating significance at 001 level

37

Table 4 SURE Tobits results for Firmsrsquo Financing Choices (based on whole sample)

Dependent variable Retained profits

Private Loan

Informal Finance

Trade Credit

Private Equity

Explanatory variables Coef Coef Coef Coef Coef

Crisis -1468 14429 -34767 4368 73231 (348) (6410) (7329) (9464) (11454)

SME 430 -13399 -1525 -3524 -4729 (1879) (3438) (3489) (5247) (7219) International Product Certification -0697 4192 4165 1884 -0852

(0720) (1306) (1311) (2107) (2728) Privately owned from inception 0866 2911 5778 -8569 -4307

(1276) (2541) (2486) (3825) (4811) Time spent on dealing with government regulations -0133 -0018 0323 0246 0346 (0042) (0081) (0076) (0112) (0134) Pressure to innovate originates from domestic competition -128 3166 3024 2552 -2404

(0522) (1052) (1029) (1644) (199) Pressure to innovate originates from foreign competition -0499 0746 2258 0056 845 (0463) (114) (1131) (1745) (2195) Pressure to innovate originates from customers -952 2428 138 2339 3297

(0581) (0915) (0864) (141) (1762) Foreign Ownership 0050 -0094 -0045 -0013 -0003

(0017) (0033) (0032) (0050) (0064) Export orientation -0072 0118 0026 0153 -0035

(0022) (004) (004) (0063) (0080) Age 0042 -0039 -0127 -005 -028

(0037) (007) (0074) (0109) (0149)

Age squared x 10-04 -0204 0246 0453 213 143

(0189) (035) (0367) (539) (070) Domestic credit as of GDP (t-1) 0445 0516 -0976 -0840 -1578 (0120) (0230) (0227) (0349) (0457) Property Rights (t-1) -818 7486 -6239 -741 -22129

(244) (5232) (5211) (7244) (10025) GDP growth (t-1) 0149 1198 -0923 -0623 2098

(0335) (0615) (0669) (906) (119)

35

Table 2 Correlation Matrix for the dependent and macro-level variables

Variables

Percep

of

financial

const-s

Retaine

d profits

Private

loan

Inform

al

finance

Trade

credit

Private

equity

SME

Crisis

Property

rights

Dom

estic

credit

GDP pc

ppp

GDP

grow

th

Perception

of financial

constraints

1

Retained

profits

-008

1

Private loan

003

-053

1

Inform

al

finance

004

-047

-012

1

Trade credit

003

-029

-004

-005

1

Private

equity

003

-033

-006

-007

-003

1

SME

003

005

-006

-001

-002

002

1

Crisis

009

-012

015

-016

012

011

002

1

Property

rights (t-1)

000

-013

010

005

-002

004

001

-005

1

Dom

estic

credit (t-1)

0002

-016

017

-008

006

009

001

052

043

1

GDP pc ppp

(t-1)

-002

-013

006

0002

002

004

-001

19

046

064

1

GDP growth

(t-1)

-001

011

-008

-0001

-002

-001

001

-017

044

-050

-055

1

Source BEEPS 2002-2009 W

B W

DI A

pr 2009 Polity IV

36

Table 3 Perception of Financial Constraints probit estimation results and marginal effects Dependent variable Perception of financial constraints as a major obstacle

probit results probit marginal effects

Coef Robust Std Err

Coef Robust Std Err

Small and Medium-sized enterprises 0203 0058 0052 0014 Crisis 0890 0126 0301 0047 Small and Medium-sized_x_Crisis -0273 0113 -0069 0026 International Product Certification -0057 0020 -0016 0005 Privately owned from inception 0012 0036 0003 0010 Time spent on dealing with government regulations 0005 0001 0001 00003 Pressure to innovate originates from domestic competition 0071 0015 0020 0004 Pressure to innovate originates from foreign competition 0078 0016 0022 0004 Pressure to innovate originates from customers 0048 0013 0013 0004 Foreign Ownership -0005 0001 -0001 00001 Export orientation -00001 0001 -0000018 00002 Age -0001 0001 -00002853 00003 Age squared x 10-07 497 525 137 145 Domestic Credit as of GDP (t-1) -0009 0003 -0003 0001 Property Rights (t-1) 0028 0058 0008 0016 GDP growth (t-1) -0023 0008 -0006 0002 Outsourced product 0024 0043 0007 0012 GDP per capita ppp (t-1) Quartile1 0257 0210 0075 0065 GDP per capita ppp (t-1) Quartile 2 0338 0160 0100 0050 GDP per capita ppp (t-1) Quartile 3 0091 0123 0026 0036 GDP per capita ppp (t-1) Quartile 4 0180 0079 0052 0023 Constant -2094 433 na na Industrial controls Yes Yes Yes Yes Country controls Yes Yes Yes Yes Number of obs 12807 12807 Pseudo R2 00673 00673 Source BEEPS 2002-2009 WB WDI Apr 2009 Polity IV Note significance levels - 1 - 5 - 10 For the interaction term of SME and crisis the marginal effect is different from the one reported in the table above After controlling for non-linearity following Norton et al 2004 the coefficient of the interaction term at mean is equal to -0074 standard error is equal to 0038 and z statistic is equal to -190 indicating significance at 001 level

37

Table 4 SURE Tobits results for Firmsrsquo Financing Choices (based on whole sample)

Dependent variable Retained profits

Private Loan

Informal Finance

Trade Credit

Private Equity

Explanatory variables Coef Coef Coef Coef Coef

Crisis -1468 14429 -34767 4368 73231 (348) (6410) (7329) (9464) (11454)

SME 430 -13399 -1525 -3524 -4729 (1879) (3438) (3489) (5247) (7219) International Product Certification -0697 4192 4165 1884 -0852

(0720) (1306) (1311) (2107) (2728) Privately owned from inception 0866 2911 5778 -8569 -4307

(1276) (2541) (2486) (3825) (4811) Time spent on dealing with government regulations -0133 -0018 0323 0246 0346 (0042) (0081) (0076) (0112) (0134) Pressure to innovate originates from domestic competition -128 3166 3024 2552 -2404

(0522) (1052) (1029) (1644) (199) Pressure to innovate originates from foreign competition -0499 0746 2258 0056 845 (0463) (114) (1131) (1745) (2195) Pressure to innovate originates from customers -952 2428 138 2339 3297

(0581) (0915) (0864) (141) (1762) Foreign Ownership 0050 -0094 -0045 -0013 -0003

(0017) (0033) (0032) (0050) (0064) Export orientation -0072 0118 0026 0153 -0035

(0022) (004) (004) (0063) (0080) Age 0042 -0039 -0127 -005 -028

(0037) (007) (0074) (0109) (0149)

Age squared x 10-04 -0204 0246 0453 213 143

(0189) (035) (0367) (539) (070) Domestic credit as of GDP (t-1) 0445 0516 -0976 -0840 -1578 (0120) (0230) (0227) (0349) (0457) Property Rights (t-1) -818 7486 -6239 -741 -22129

(244) (5232) (5211) (7244) (10025) GDP growth (t-1) 0149 1198 -0923 -0623 2098

(0335) (0615) (0669) (906) (119)

36

Table 3 Perception of Financial Constraints probit estimation results and marginal effects Dependent variable Perception of financial constraints as a major obstacle

probit results probit marginal effects

Coef Robust Std Err

Coef Robust Std Err

Small and Medium-sized enterprises 0203 0058 0052 0014 Crisis 0890 0126 0301 0047 Small and Medium-sized_x_Crisis -0273 0113 -0069 0026 International Product Certification -0057 0020 -0016 0005 Privately owned from inception 0012 0036 0003 0010 Time spent on dealing with government regulations 0005 0001 0001 00003 Pressure to innovate originates from domestic competition 0071 0015 0020 0004 Pressure to innovate originates from foreign competition 0078 0016 0022 0004 Pressure to innovate originates from customers 0048 0013 0013 0004 Foreign Ownership -0005 0001 -0001 00001 Export orientation -00001 0001 -0000018 00002 Age -0001 0001 -00002853 00003 Age squared x 10-07 497 525 137 145 Domestic Credit as of GDP (t-1) -0009 0003 -0003 0001 Property Rights (t-1) 0028 0058 0008 0016 GDP growth (t-1) -0023 0008 -0006 0002 Outsourced product 0024 0043 0007 0012 GDP per capita ppp (t-1) Quartile1 0257 0210 0075 0065 GDP per capita ppp (t-1) Quartile 2 0338 0160 0100 0050 GDP per capita ppp (t-1) Quartile 3 0091 0123 0026 0036 GDP per capita ppp (t-1) Quartile 4 0180 0079 0052 0023 Constant -2094 433 na na Industrial controls Yes Yes Yes Yes Country controls Yes Yes Yes Yes Number of obs 12807 12807 Pseudo R2 00673 00673 Source BEEPS 2002-2009 WB WDI Apr 2009 Polity IV Note significance levels - 1 - 5 - 10 For the interaction term of SME and crisis the marginal effect is different from the one reported in the table above After controlling for non-linearity following Norton et al 2004 the coefficient of the interaction term at mean is equal to -0074 standard error is equal to 0038 and z statistic is equal to -190 indicating significance at 001 level

37

Table 4 SURE Tobits results for Firmsrsquo Financing Choices (based on whole sample)

Dependent variable Retained profits

Private Loan

Informal Finance

Trade Credit

Private Equity

Explanatory variables Coef Coef Coef Coef Coef

Crisis -1468 14429 -34767 4368 73231 (348) (6410) (7329) (9464) (11454)

SME 430 -13399 -1525 -3524 -4729 (1879) (3438) (3489) (5247) (7219) International Product Certification -0697 4192 4165 1884 -0852

(0720) (1306) (1311) (2107) (2728) Privately owned from inception 0866 2911 5778 -8569 -4307

(1276) (2541) (2486) (3825) (4811) Time spent on dealing with government regulations -0133 -0018 0323 0246 0346 (0042) (0081) (0076) (0112) (0134) Pressure to innovate originates from domestic competition -128 3166 3024 2552 -2404

(0522) (1052) (1029) (1644) (199) Pressure to innovate originates from foreign competition -0499 0746 2258 0056 845 (0463) (114) (1131) (1745) (2195) Pressure to innovate originates from customers -952 2428 138 2339 3297

(0581) (0915) (0864) (141) (1762) Foreign Ownership 0050 -0094 -0045 -0013 -0003

(0017) (0033) (0032) (0050) (0064) Export orientation -0072 0118 0026 0153 -0035

(0022) (004) (004) (0063) (0080) Age 0042 -0039 -0127 -005 -028

(0037) (007) (0074) (0109) (0149)

Age squared x 10-04 -0204 0246 0453 213 143

(0189) (035) (0367) (539) (070) Domestic credit as of GDP (t-1) 0445 0516 -0976 -0840 -1578 (0120) (0230) (0227) (0349) (0457) Property Rights (t-1) -818 7486 -6239 -741 -22129

(244) (5232) (5211) (7244) (10025) GDP growth (t-1) 0149 1198 -0923 -0623 2098

(0335) (0615) (0669) (906) (119)

37

Table 4 SURE Tobits results for Firmsrsquo Financing Choices (based on whole sample)

Dependent variable Retained profits

Private Loan

Informal Finance

Trade Credit

Private Equity

Explanatory variables Coef Coef Coef Coef Coef

Crisis -1468 14429 -34767 4368 73231 (348) (6410) (7329) (9464) (11454)

SME 430 -13399 -1525 -3524 -4729 (1879) (3438) (3489) (5247) (7219) International Product Certification -0697 4192 4165 1884 -0852

(0720) (1306) (1311) (2107) (2728) Privately owned from inception 0866 2911 5778 -8569 -4307

(1276) (2541) (2486) (3825) (4811) Time spent on dealing with government regulations -0133 -0018 0323 0246 0346 (0042) (0081) (0076) (0112) (0134) Pressure to innovate originates from domestic competition -128 3166 3024 2552 -2404

(0522) (1052) (1029) (1644) (199) Pressure to innovate originates from foreign competition -0499 0746 2258 0056 845 (0463) (114) (1131) (1745) (2195) Pressure to innovate originates from customers -952 2428 138 2339 3297

(0581) (0915) (0864) (141) (1762) Foreign Ownership 0050 -0094 -0045 -0013 -0003

(0017) (0033) (0032) (0050) (0064) Export orientation -0072 0118 0026 0153 -0035

(0022) (004) (004) (0063) (0080) Age 0042 -0039 -0127 -005 -028

(0037) (007) (0074) (0109) (0149)

Age squared x 10-04 -0204 0246 0453 213 143

(0189) (035) (0367) (539) (070) Domestic credit as of GDP (t-1) 0445 0516 -0976 -0840 -1578 (0120) (0230) (0227) (0349) (0457) Property Rights (t-1) -818 7486 -6239 -741 -22129

(244) (5232) (5211) (7244) (10025) GDP growth (t-1) 0149 1198 -0923 -0623 2098

(0335) (0615) (0669) (906) (119)

38

Table 4 Continued

Retained Earnings

Private Loan

Informal Finance

Trade Credit

Private Equity

Outsourced product -7147 7026 11302 9187 11968 (1169) (3037) (3019) (4686) (568)

GDP per capita ppp (t-1) Quartile1 17667 -18847 22746 -38628 -47309

(8296) (16383) (16249) (24715) (32176) GDP per capita ppp (t-1) Quartile2 10075 -1298 -6898 -32957 -36702

(6165) (12290) (11932) (18809) (24136) GDP per capita ppp (t-1) Quartile3 8281 -4884 -6021 -9496 -32234

(4419) (8778) (8145) (13732) (18344) GDP per capita ppp (t-1) Quartile4 1199 -4721 -1553 -12905 6665

(2956) (5524) (4898) (9622) (8691) Inverse Millrsquos Ratio -2526 -32549 19162 -1537 2926

(7875) (14726) (17288) (20594) (2637) Constant 7042 -85070 -64477 -77818 -3173

(1783) (38276) (37321) (5456) (75304) Industrial controls Yes Yes Yes Yes Yes

Country controls Yes Yes Yes Yes Yes

Number of obs 9005 9005 9005 9005 9005 Wald Chi-sq (52) 78042 78042 78042 78042 78042 Prob gt Chi-sq 00000 00000 00000 00000 00000

Source BEEPS 2002-2009 WB WDI Apr 2009 Polity IV Note Significance levels - 1 - 5 - 10

39

Table 5 SURE Tobits results for Financing Choices of Small and Medium-sized Firms

Dependent variable Retained profits

Private Loan

Informal Finance

Trade Credit

Private Equity

Explanatory variables Coef Coef Coef Coef Coef

Crisis -15875 11558 -30270 50053 72067 (3854) (7397) (8228) (10934) (12854)

International Product Certification -0897 3652 3306 2970 -0394

(0826) (1596) (1544) (2534) (3324) Privately owned from inception 0678 2027 4834 -8865 -9052

(1383) (2861) (2731) (4364) (5115) Time spent on dealing with government regulations -0144 -0041 0308 0263 0315 (0045) (0091) (0083) (0125) (0152) Pressure to innovate originates from domestic competition -1294 3967 2409 2881 -2953

(0556) (1162) (1099) (1808) (2122) Pressure to innovate originates from foreign competition -0948 -0675 1751 0208 1492 (0623) (1257) (1219) (1934) (2367) Pressure to innovate originates from customers 0003 2036 0963 1832 2653

(0491) (0998) (0911) (1548) (1893) Foreign Ownership 0049 -0115 -0065 -0012 -0012

(0019) (0039) (0037) (0059) (0076) Export orientation -0071 0136 0035 0159 -0003

(0024) (0046) (0043) (0073) (0090) Age 0029 0012 -0145 0032 -0389

(0047) (0093) (0097) (0149) (0200)

Age squared x 10-04 -02 01 06 -10 20

(02) (05) (05) (10) (10) Domestic credit as of GDP (t-1) 0476 0728 -0946 -0776 -1807 (0134) (0271) (0253) (0399) (0518) Property Rights (t-1) -2254 6503 -10385 4784 -15872

(2647) (5838) (5694) (8174) (10977) GDP growth (t-1) 0207 1151 -0849 -0168 1528

(0376) (0721) (0753) (1057) (1366) Outsourced product -7865 7619 10726 9504 11758

(1832) (3442) (3341) (5316) (6493) GDP per capita ppp (t-1) Quartile1 20894 -32368 20890 -35076 -39491

(8815) (18206) (17397) (27311) (34101)

40

Table 5 Continued

Retained Earnings

Private Loan

Informal Finance

Trade Credit

Private Equity

GDP per capita ppp (t-1) Quartile2 13296 -10201 -6731 -28589 -34508

(6551) (13612) (12684) (20675) (25398) GDP per capita ppp (t-1) Quartile3 10309 -10280 -5077 -8055 -29137

(4696) (9796) (8705) (15030) (19279) GDP per capita ppp (t-1) Quartile4 2053 -6537 -2848 -16115 11719

(3151) (6156) (5304) (10614) (9173) Inverse Millrsquos Ratio -1450 -45525 5380 -18916 42778

(9105) (18097) (20333) (24781) (32181) Constant 77698 -77491 -29969 -115744 -58162

(19289) (42941) (41124) (61743) (80918) Industrial controls Yes Yes Yes Yes Yes

Country controls Yes Yes Yes Yes Yes

Number of obs 8072 8072 8072 8072 8072

Wald Chi-sq (51) 71481 71481 71481 71481 71481

Prob gt Chi-sq 00000 00000 00000 00000 00000

Source BEEPS 2002-2009 WB WDI Apr 2009 Polity IV Note Significance levels - 1 - 5 - 10

41

Table 6 The Impact of Use of Trade Credit for Real Investmentplusmn on Perceptions of Financial Constraints probit marginal effects

Dependent variable Perception of financial constraints as a major obstacle

probit marginal effects Coef Robust Std

Err

Small and Medium-sized enterprises 00548 00143 Crisis 02149 00338 Use of Trade Credit for Real Investment 00025 00008 Small and Medium-sized_x_Use of Trade Credit for Real Investment -00024 00009 International Product Certification -00077 00062 Privately owned from inception 00134 00118 Time spent on dealing with government regulations 00012 00003

Pressure to innovate originates from domestic competition 00221 00051

Pressure to innovate originates from foreign competition 00109 00042

Pressure to innovate originates from customers 00205 00053 Foreign Ownership -00010 00002 Export orientation -00001 00002 Age -00005 00003 Age squared x 10-07 00000002 00000002

Domestic Credit as of GDP (t-1) -00023 00009 Property Rights (t-1) -00145 00208 GDP growth (t-1) -00081 00025 Outsourced product 00071 00138 GDP per capita ppp (t-1) Quartile1 00399 00758 GDP per capita ppp (t-1) Quartile 2 00679 00602 GDP per capita ppp (t-1) Quartile 3 00131 00413 GDP per capita ppp (t-1) Quartile 4 00457 00263 Constant na na Industrial controls Yes Yes

Country controls Yes Yes

Number of obs 8760

Pseudo R2 00684

Source BEEPS 2002-2009 WB WDI Apr 2009 Polity IV Note significance levels - 1 - 5 - 10 For the interaction term of the SME dummy and Use of Trade Credit for Real Investment the marginal effect is different from the one reported in the table above After controlling for non-linearity following Norton et al 2004 the coefficient of the interaction term at the mean is equal to -0001975 standard error is equal to 0000782 and z statistic is equal to -24852 indicating significance at the 001 level

plusmn The Use of Trade Credit variable is given by the relative percentage of purchases of fixed assets on credit from suppliers and advances from customers

• Introduction
• 2 The stylised facts about SME financing in Transition Economies

39

Table 5 SURE Tobits results for Financing Choices of Small and Medium-sized Firms

Dependent variable Retained profits

Private Loan

Informal Finance

Trade Credit

Private Equity

Explanatory variables Coef Coef Coef Coef Coef

Crisis -15875 11558 -30270 50053 72067 (3854) (7397) (8228) (10934) (12854)

International Product Certification -0897 3652 3306 2970 -0394

(0826) (1596) (1544) (2534) (3324) Privately owned from inception 0678 2027 4834 -8865 -9052

(1383) (2861) (2731) (4364) (5115) Time spent on dealing with government regulations -0144 -0041 0308 0263 0315 (0045) (0091) (0083) (0125) (0152) Pressure to innovate originates from domestic competition -1294 3967 2409 2881 -2953

(0556) (1162) (1099) (1808) (2122) Pressure to innovate originates from foreign competition -0948 -0675 1751 0208 1492 (0623) (1257) (1219) (1934) (2367) Pressure to innovate originates from customers 0003 2036 0963 1832 2653

(0491) (0998) (0911) (1548) (1893) Foreign Ownership 0049 -0115 -0065 -0012 -0012

(0019) (0039) (0037) (0059) (0076) Export orientation -0071 0136 0035 0159 -0003

(0024) (0046) (0043) (0073) (0090) Age 0029 0012 -0145 0032 -0389

(0047) (0093) (0097) (0149) (0200)

Age squared x 10-04 -02 01 06 -10 20

(02) (05) (05) (10) (10) Domestic credit as of GDP (t-1) 0476 0728 -0946 -0776 -1807 (0134) (0271) (0253) (0399) (0518) Property Rights (t-1) -2254 6503 -10385 4784 -15872

(2647) (5838) (5694) (8174) (10977) GDP growth (t-1) 0207 1151 -0849 -0168 1528

(0376) (0721) (0753) (1057) (1366) Outsourced product -7865 7619 10726 9504 11758

(1832) (3442) (3341) (5316) (6493) GDP per capita ppp (t-1) Quartile1 20894 -32368 20890 -35076 -39491

(8815) (18206) (17397) (27311) (34101)

40

Table 5 Continued

Retained Earnings

Private Loan

Informal Finance

Trade Credit

Private Equity

GDP per capita ppp (t-1) Quartile2 13296 -10201 -6731 -28589 -34508

(6551) (13612) (12684) (20675) (25398) GDP per capita ppp (t-1) Quartile3 10309 -10280 -5077 -8055 -29137

(4696) (9796) (8705) (15030) (19279) GDP per capita ppp (t-1) Quartile4 2053 -6537 -2848 -16115 11719

(3151) (6156) (5304) (10614) (9173) Inverse Millrsquos Ratio -1450 -45525 5380 -18916 42778

(9105) (18097) (20333) (24781) (32181) Constant 77698 -77491 -29969 -115744 -58162

(19289) (42941) (41124) (61743) (80918) Industrial controls Yes Yes Yes Yes Yes

Country controls Yes Yes Yes Yes Yes

Number of obs 8072 8072 8072 8072 8072

Wald Chi-sq (51) 71481 71481 71481 71481 71481

Prob gt Chi-sq 00000 00000 00000 00000 00000

Source BEEPS 2002-2009 WB WDI Apr 2009 Polity IV Note Significance levels - 1 - 5 - 10

41

Table 6 The Impact of Use of Trade Credit for Real Investmentplusmn on Perceptions of Financial Constraints probit marginal effects

Dependent variable Perception of financial constraints as a major obstacle

probit marginal effects Coef Robust Std

Err

Small and Medium-sized enterprises 00548 00143 Crisis 02149 00338 Use of Trade Credit for Real Investment 00025 00008 Small and Medium-sized_x_Use of Trade Credit for Real Investment -00024 00009 International Product Certification -00077 00062 Privately owned from inception 00134 00118 Time spent on dealing with government regulations 00012 00003

Pressure to innovate originates from domestic competition 00221 00051

Pressure to innovate originates from foreign competition 00109 00042

Pressure to innovate originates from customers 00205 00053 Foreign Ownership -00010 00002 Export orientation -00001 00002 Age -00005 00003 Age squared x 10-07 00000002 00000002

Domestic Credit as of GDP (t-1) -00023 00009 Property Rights (t-1) -00145 00208 GDP growth (t-1) -00081 00025 Outsourced product 00071 00138 GDP per capita ppp (t-1) Quartile1 00399 00758 GDP per capita ppp (t-1) Quartile 2 00679 00602 GDP per capita ppp (t-1) Quartile 3 00131 00413 GDP per capita ppp (t-1) Quartile 4 00457 00263 Constant na na Industrial controls Yes Yes

Country controls Yes Yes

Number of obs 8760

Pseudo R2 00684

Source BEEPS 2002-2009 WB WDI Apr 2009 Polity IV Note significance levels - 1 - 5 - 10 For the interaction term of the SME dummy and Use of Trade Credit for Real Investment the marginal effect is different from the one reported in the table above After controlling for non-linearity following Norton et al 2004 the coefficient of the interaction term at the mean is equal to -0001975 standard error is equal to 0000782 and z statistic is equal to -24852 indicating significance at the 001 level

plusmn The Use of Trade Credit variable is given by the relative percentage of purchases of fixed assets on credit from suppliers and advances from customers

• Introduction
• 2 The stylised facts about SME financing in Transition Economies

40

Table 5 Continued

Retained Earnings

Private Loan

Informal Finance

Trade Credit

Private Equity

GDP per capita ppp (t-1) Quartile2 13296 -10201 -6731 -28589 -34508

(6551) (13612) (12684) (20675) (25398) GDP per capita ppp (t-1) Quartile3 10309 -10280 -5077 -8055 -29137

(4696) (9796) (8705) (15030) (19279) GDP per capita ppp (t-1) Quartile4 2053 -6537 -2848 -16115 11719

(3151) (6156) (5304) (10614) (9173) Inverse Millrsquos Ratio -1450 -45525 5380 -18916 42778

(9105) (18097) (20333) (24781) (32181) Constant 77698 -77491 -29969 -115744 -58162

(19289) (42941) (41124) (61743) (80918) Industrial controls Yes Yes Yes Yes Yes

Country controls Yes Yes Yes Yes Yes

Number of obs 8072 8072 8072 8072 8072

Wald Chi-sq (51) 71481 71481 71481 71481 71481

Prob gt Chi-sq 00000 00000 00000 00000 00000

Source BEEPS 2002-2009 WB WDI Apr 2009 Polity IV Note Significance levels - 1 - 5 - 10

41

Table 6 The Impact of Use of Trade Credit for Real Investmentplusmn on Perceptions of Financial Constraints probit marginal effects

Dependent variable Perception of financial constraints as a major obstacle

probit marginal effects Coef Robust Std

Err

Small and Medium-sized enterprises 00548 00143 Crisis 02149 00338 Use of Trade Credit for Real Investment 00025 00008 Small and Medium-sized_x_Use of Trade Credit for Real Investment -00024 00009 International Product Certification -00077 00062 Privately owned from inception 00134 00118 Time spent on dealing with government regulations 00012 00003

Pressure to innovate originates from domestic competition 00221 00051

Pressure to innovate originates from foreign competition 00109 00042

Pressure to innovate originates from customers 00205 00053 Foreign Ownership -00010 00002 Export orientation -00001 00002 Age -00005 00003 Age squared x 10-07 00000002 00000002

Domestic Credit as of GDP (t-1) -00023 00009 Property Rights (t-1) -00145 00208 GDP growth (t-1) -00081 00025 Outsourced product 00071 00138 GDP per capita ppp (t-1) Quartile1 00399 00758 GDP per capita ppp (t-1) Quartile 2 00679 00602 GDP per capita ppp (t-1) Quartile 3 00131 00413 GDP per capita ppp (t-1) Quartile 4 00457 00263 Constant na na Industrial controls Yes Yes

Country controls Yes Yes

Number of obs 8760

Pseudo R2 00684

Source BEEPS 2002-2009 WB WDI Apr 2009 Polity IV Note significance levels - 1 - 5 - 10 For the interaction term of the SME dummy and Use of Trade Credit for Real Investment the marginal effect is different from the one reported in the table above After controlling for non-linearity following Norton et al 2004 the coefficient of the interaction term at the mean is equal to -0001975 standard error is equal to 0000782 and z statistic is equal to -24852 indicating significance at the 001 level

plusmn The Use of Trade Credit variable is given by the relative percentage of purchases of fixed assets on credit from suppliers and advances from customers

• Introduction
• 2 The stylised facts about SME financing in Transition Economies

41

Table 6 The Impact of Use of Trade Credit for Real Investmentplusmn on Perceptions of Financial Constraints probit marginal effects

Dependent variable Perception of financial constraints as a major obstacle

probit marginal effects Coef Robust Std

Err

Small and Medium-sized enterprises 00548 00143 Crisis 02149 00338 Use of Trade Credit for Real Investment 00025 00008 Small and Medium-sized_x_Use of Trade Credit for Real Investment -00024 00009 International Product Certification -00077 00062 Privately owned from inception 00134 00118 Time spent on dealing with government regulations 00012 00003

Pressure to innovate originates from domestic competition 00221 00051

Pressure to innovate originates from foreign competition 00109 00042

Pressure to innovate originates from customers 00205 00053 Foreign Ownership -00010 00002 Export orientation -00001 00002 Age -00005 00003 Age squared x 10-07 00000002 00000002

Domestic Credit as of GDP (t-1) -00023 00009 Property Rights (t-1) -00145 00208 GDP growth (t-1) -00081 00025 Outsourced product 00071 00138 GDP per capita ppp (t-1) Quartile1 00399 00758 GDP per capita ppp (t-1) Quartile 2 00679 00602 GDP per capita ppp (t-1) Quartile 3 00131 00413 GDP per capita ppp (t-1) Quartile 4 00457 00263 Constant na na Industrial controls Yes Yes

Country controls Yes Yes

Number of obs 8760

Pseudo R2 00684

Source BEEPS 2002-2009 WB WDI Apr 2009 Polity IV Note significance levels - 1 - 5 - 10 For the interaction term of the SME dummy and Use of Trade Credit for Real Investment the marginal effect is different from the one reported in the table above After controlling for non-linearity following Norton et al 2004 the coefficient of the interaction term at the mean is equal to -0001975 standard error is equal to 0000782 and z statistic is equal to -24852 indicating significance at the 001 level

plusmn The Use of Trade Credit variable is given by the relative percentage of purchases of fixed assets on credit from suppliers and advances from customers

• Introduction
• 2 The stylised facts about SME financing in Transition Economies