Graduate Institute of International Development and Applied Economics

The Impact of Lending Rates On SME Growth: The Case of Zambia

Wise Banda

Dissertation prepared in partial fulfilment for the requirements for the Master of Science in

Development Finance

13Th

September, 2016

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Dedication

This dissertation is dedicated to the Zambian people whom although hardworking,

are generally let down by the very educated professionals who are supposed to

safeguard and protect their interests. Although I cannot offer much at this stage, I

am confident that this work piece will encourage boldness and rationality in drafting

policies in our struggle for progress and inspire future policy makers. In completing

this work, it is my hope that patriotism will be restored and decision makers will find

the courage to act with honour to promote the wellbeing and prosperity of Zambians

above all else.

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Acknowledgement

I would like to express my sincere gratitude to The Chevening Scholarships, the UK

government’s Global Scholarship programme funded by Foreign and Commonwealth

Office (FCO) and Partner Organisations for according me the opportunity to pursue

this MSc in Development Finance here in Reading, United Kingdom.

I would also like to thank my supervisor, Dr Srinivasan for his guidance during the

completion of this research work. Completing this academic work would not have

been possible without the unconditional support from my family and friends

throughout this whole programme, words cannot express the gratitude I feel.

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Table of Contents

Dedication ------------------------------------------------------------------------------------- i

Acknowledgement --------------------------------------------------------------------------- ii

Table of Contents --------------------------------------------------------------------------- iii

Table of Figures ----------------------------------------------------------------------------- vi

LIST OF TABLES ------------------------------------------------------------------------------- vii

Abbreviations and Acronyms ------------------------------------------------------------ viii

Abstract -------------------------------------------------------------------------------------- ix

CHAPTER 1 - INTRODUCTION -------------------------------------------------------------- 1

1.1. Background -------------------------------------------------------------------------- 1

1.2. Research Problem ------------------------------------------------------------------- 2

1.3. Research Objectives ----------------------------------------------------------------- 3

1.4. Scope of the Study ------------------------------------------------------------------- 4

1.4.1. Research Strategy -------------------------------------------------------------- 5

1.5. Structure of the Study -------------------------------------------------------------- 5

CHAPTER 2 - LITERATURE REVIEW ------------------------------------------------------- 7

2.1. Introduction -------------------------------------------------------------------------- 7

2.2. Small and Medium Enterprises---------------------------------------------------- 8

2.2.1. The Definition of SMEs -------------------------------------------------------- 9

2.2.2. Sources of Finance ------------------------------------------------------------ 10

2.2.3. SMEs and Growth: Empirical Evidence ------------------------------------ 11

2.3. What Determines SME Growth --------------------------------------------------- 13

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2.3.1. Financial Constraints --------------------------------------------------------- 14

2.4. Interest Rate Theory ---------------------------------------------------------------- 15

2.4.1. Why Policy Makers Normally Increase Interest Rates -------------------- 19

2.5. The Zambian Case ------------------------------------------------------------------ 21

2.5.1. Background --------------------------------------------------------------------- 21

2.5.2. Recent Developments --------------------------------------------------------- 21

2.5.3. Zambian SME Constraints --------------------------------------------------- 22

2.5.4. Performance of SMEs in Zambia -------------------------------------------- 24

2.6. Conclusion --------------------------------------------------------------------------- 28

CHAPTER 3 - METHODOLOGY ------------------------------------------------------------ 30

3.1. Introduction ------------------------------------------------------------------------- 30

3.2. Objectives Review ------------------------------------------------------------------- 30

3.3. Hypothesis Formulation ----------------------------------------------------------- 31

3.3.1. Hypothesis 1 -------------------------------------------------------------------- 31

3.3.2. Hypothesis 2 -------------------------------------------------------------------- 32

3.3.3. Hypothesis 3 -------------------------------------------------------------------- 32

3.4. Nature and Sources of the Data -------------------------------------------------- 33

3.5. Estimation Model Specification --------------------------------------------------- 34

3.6. Selection of Variables -------------------------------------------------------------- 35

3.6.1. Dependent Variable ----------------------------------------------------------- 35

3.6.2. Explanatory Variables -------------------------------------------------------- 36

3.7. Estimation Method ----------------------------------------------------------------- 37

3.8. Limitations --------------------------------------------------------------------------- 39

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3.9. Conclusion --------------------------------------------------------------------------- 40

CHAPTER 4 - RESULTS ANALYSIS AND DISCUSSION --------------------------------- 41

4.1. Introduction ------------------------------------------------------------------------- 41

4.2. Descriptive Statistics --------------------------------------------------------------- 41

4.3. Discussion and Interpretation of the Results ---------------------------------- 47

4.4. Inferences from these Findings --------------------------------------------------- 49

4.5. Lending Rates Across Countries -------------------------------------------------- 49

4.6. Lending Rates and Investment Expenditure ------------------------------------ 51

4.7. Conclusion --------------------------------------------------------------------------- 52

CHAPTER 5 - CONCLUSION AND POLICY IMPLICATIONS ---------------------------- 53

5.1. Summary ---------------------------------------------------------------------------- 53

5.2. Research Conclusions and Limitations of the Findings ----------------------- 55

5.3. Policy Implications------------------------------------------------------------------ 55

5.4. Areas for Further Research ------------------------------------------------------- 57

Bibliography ----------------------------------------------------------------------------------- 59

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Table of Figures

Figure 2-1: Percentage of SMEs Financed by Banks in Sub-Saharan African ----- 10

Figure 2-2: SME growth in Employment ------------------------------------------------- 12

Figure 2-3: Interest Rate Transmission Mechanism------------------------------------ 17

Figure 2-4: Lending Rates Vs Inflation Trends in Zambia ---------------------------- 20

Figure 2-5: Ranking constraints to SME growth in Zambia --------------------------- 23

Figure 2-6: Comparison of Zambian SME Loan Rejections --------------------------- 24

Figure 2-7: Performance of Zambian SMES in Terms of Percentage Growth in Sales

-------------------------------------------------------------------------------------------- 25

Figure 2-8: Number of firms listed on the Lusaka Stock Exchange ------------------ 26

Figure 4-1: Lending rates and Firm Productivity --------------------------------------- 44

Figure 4-2: Productivity and Credit Granted -------------------------------------------- 45

Figure 4-3: Lending Rates and Credit Granted ----------------------------------------- 48

Figure 4-4: Lending Rates Across Countries -------------------------------------------- 50

Figure 4-5: SME Performance ------------------------------------------------------------- 51

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LIST OF TABLES

Table 2-1: Lusaka Stock Exchange Listed Companies --------------------------------- 27

Table 4-1: Summary Statistics------------------------------------------------------------ 42

Table 4-2: Graphical Representation of the Correlation among the Variables ------ 43

Table 4-3: Regression Results ------------------------------------------------------------- 45

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Abbreviations and Acronyms

AfDB

African Development Bank, 8

BOZ

Bank of Zambia, 9

CSO

Central Statistical Office, 32

EU

European Union, 13

IMF

International Monetary Fund, 8, 9, 22, 23, 24, 42, 44

Non-Bank Financial Institutions

NBFI, 21

OLS

Ordinary Least Squares, 32

Small and Medium Enterprises (SMEs)

SMEs, 8

Structural Adjustment Programs (SAPS)

SAPs, 8

Sub-Saharan African

SSA, 10

Zambia Data Portal

ZDP, 32

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Abstract

The business environment in which Small and Medium Enterprises operate plays a

key role in determining their success or closure rates. In trying to make the stabilise

the macroeconomic environment through such targets such as low inflation rates,

stable exchange and growth rates, sustainable debt and balance of payment,

sometimes these policies may result in undesirable outcomes which if undermined

distorts the performance of other actors in the economy in the long run. Of particular

concern is the impact of Lending rate policies on SME growth behaviour. Although

from a policy perspective it is imperative to understand how Lending rates affect a

firm’s ability to access finance and grow, it is astonishing to note that few studies

have been done in this field.

This dissertation aims to bridge this gap and contribute empirical literature on the

impact of lending rates on SME growth decisions, access to credit as well as the role

of electricity supply in firm growth. The study focuses on Zambia and uses the data

generated by the Bank of Zambia, World Bank, Central Statistical Office and the

Zambia Data Portal. Using firm productivity as a measure of SME growth, multiple

linear regressions were run on the data and the study reveals a negative correlation

between high Lending rates and SME growth as well as negative correlation between

Electricity usage and SME productivity. This result draws importance to the financial

policies undertaken by policy makers whose impacts must be assessed in totality. It

also supports the revelations of the World Bank (Enterprise Surveys, 2013) of the

important role of adequate electricity supply in supporting the development of the

SME sector. Furthermore, the study also finds a positive correlation between Credit

Granted to firms and their productivity.

Word Count: 13,484

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CHAPTER 1 - INTRODUCTION

1.1. Background

Ever since the peak of structural adjustment programs in the 1980s and 1990s,

Small and Medium Enterprises (SMEs) in Africa have always been side-lined by

economists and policy makers as drivers of economic growth in preference to large

scale multinational companies. The rationale was that of trickle-down effect, where

the large corporations would inject the much needed capital into the economy, bring

in modern technologies and expertise as well as provide employment for the locals.

As such, many hastily embraced the IMF and World Bank induced Structural

Adjustment Programmes (SAPs) (Mkandawire & Soludo, 2002). Faced with high

national debt levels, high inflation and weak economies, developing countries

implemented Structural Adjustment Programs (SAPS) where they sold large scale

state enterprises to pave way for this foreign inflow of capital, technologies and the

employment that would ensue under economic liberalisation and market oriented

policies. Although some multinational companies did indeed set up subsidiaries in

developing countries, owing to the incentives under SAPs, the trickle down benefits

have not been to the anticipated levels (Mkandawire & Soludo, 2002). In order to

ensure macroeconomic stability, policy makers embarked on liberal policies that were

aimed at curbing inflation, stabilizing exchange rates, debt sustainability and raising

interest rate to attract foreign investment to the capital starved enterprises. However,

although most developing countries saw little improvement in economic performance

and stability since the SAPS, a concern emerged on the unfavourable performance of

the SMEs.

In recent studies, many scholars and policy analysists have realised the importance

of SMEs in economic growth and private sector development (Beck, et al., 2005; Beck,

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2007). To this end, many international development institutions have identified SMEs

as engines of growth and are investing significant efforts in promoting their growth.

As noted by Beck, et al., (2006), the World Bank, AFDB, IMF have changed their

approach to development and now provide financing to SMEs and also support

government policies and programmes that aim at improving the business

environments in which firms operate. Despite the extensive literature on the

challenges in the macroeconomic environment that hampers SME growth, including

that of access to finance, there is little research that explores the link between interest

rates in influencing this environment more especially Lending rates and their impact

on SMEs. Among the noted constraints as argued by Beck et al., (2005), include

access to finance, Taxation, corruption, institutions and regulatory environment,

poor infrastructure and of course the policy environment. Hence this research

focuses on lending rates and how they influence SME’s growth and investment

decisions as well as access to finance in Zambia.

1.2. Research Problem

Ever since the liberalisation of the economy, Zambia has seen significant capital

inflows to various sectors of the economy and has enjoyed impressive economic

growth averaging 7% between 2010 and 2014 (World Bank, 2016; IMF, 2015). In

order to sustain this capital inflow as well as attract major business investments,

policy makers have been implementing policies that try to stabilize the

macroeconomic environment. Among these include curbing inflation to single digit

currently at 7.1% BOZ (2016), stabilising the exchange rate volatility, and

maintaining stable balance of payments position. However, the country has recently

been experiencing declining economic performance. The IMF mission in their recent

consultation visit to the country in 2014 noted that the country has been facing a

deteriorating current account as a result of falling copper prices, Zambia’s major

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export; fiscal imbalances and policy uncertainties causing downward pressure on the

exchange rate and significantly lowering the growth rate from 6.7% in 2013 to 3.7%

in 2014, and an estimated further economic decline to 3% for 2015 (IMF, 2016). In

light of this harsh economic reality, the Bank of Zambia’s implemented tight

monetary policy by hiking the reserve requirements and raising the interest rates.

Although inflation and exchange rate volatility stabilized, this action did not have a

favourable bearing on other players of the economy most notably the Small and

medium enterprises. It is this attempt to address larger problems that in usually

result in economic distortions for other players. Hence the need for this research

which investigates the impact of Lending rates on the growth of Small and Medium

Enterprises.

The Bank of Zambia tightens monetary policy through either raising the reserve

requirement or increasing the policy rate, which is the benchmark lending rate used

by financial institutions (Mbao, et al., 2014). In so doing, the monetary base and

consequently liquidity in circulation is reduced in an attempt to lower aggregate

demand and fight inflation. Large scale enterprises can cope with this development

as their markets and sources of capital are usually across borders, mostly in Europe

and Asia. However, for most SMEs which rely almost entirely on the local market for

both financing and sales, such developments become hostile for them and threaten

their very survival. Little research in this field justifies the need for this dissertation

which explores the impact of Lending rates on SME growth and their ability to access

finance.

1.3. Research Objectives

The aim of this research is to contribute to existing empirical knowledge on the

broader impact of financial policies on other sectors of the economy than the

originally intended targets. In particular, the research examines the impact of high

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lending rates on growth of SMEs and their ability to access financing. In view of this

purpose of the study, the research will try to answer the following questions:

a) What is the impact of Lending rates on SME growth as Measured by

productivity?

b) Do Lending rates also affect the credit granted to firms?

c) How do Zambia’s lending rates fare among similar countries in Sub-

Saharan Africa and the world, do countries with lower lending rates have

more productive SMEs?

d) Does lowering the lending rates improve SME expansion through increased

investments in capital and machinery?

The contributions of this research work are primarily empirical although the findings

to be presented may provide the basis for better modelling of Financial and Economic

Policies for SME growth in the future.

1.4. Scope of the Study

The area of focus of the research is on SMEs in Zambia although for comparative

purposes, other Sub-Saharan African (SSA) countries will be reviewed. This is in

order to get a clear understanding whether the research results are applicable to

countries with similar contexts. The dissertation is centred on SMEs that borrow

from formal financial institutions because flows of credit to firms that do not borrow

from financial institutions is not well documented and such data is not readily

available. However, it is possible that bank interest rates may influence the

availability of credit from other sources such as Non-Bank Financial Institutions

(NBFI), family and friends as well as the terms on which they are offered.

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Additionally, despite many factors that constrain SME growth, the scope of this study

is limited to three namely; Lending rates, Credit Granted by banks and the role

Electricity in SME growth with major focus on lending rates.

1.4.1. Research Strategy

The research employs a case study analysis of Zambia by giving trends, descriptive

indicators and current economic outlook of the country. Based on these

developments, empirical analysis of the impact of interest rates on SME growth in

Zambia will be done using regression analysis. A comparison of the findings with five

other Sub-Saharan African countries will help emphasize the case. This strategy is

useful in understanding how policy differentials among countries is affecting their

business environment, with regards to interest rates and consequently the growth of

the SMEs. Zambia is of particular interest as it normally falls prey to economic shocks

due to its over reliance on large scale enterprises especially in the mining sector and

there have been calls to diversify the economy, thus the SME sector if promoted

provides a lucrative alternative. Hence, this research provides a wealth of knowledge

especially with regards to economic diversification focusing on Small and Medium

Enterprises. The link between interest rates and investments will be explored by

controlling for other determinants using the investment function; 𝑖 = 𝑓(𝑥, 𝑦) .

1.5. Structure of the Study

From this introductory chapter, the remainder of the dissertation is structured as

follows: chapter two will present the Literature review which will highlight the

underlying theoretical and conceptual framework of this research. In this vain, an

extensive review of interest rate theories as well as empirical research on SME growth,

characteristics and other relevant aspects will be presented in order to give direction

and build the research case. The chapter closes by summarising the empirical

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evidence regarding effects of interest rates on investment as well as key determinants

of SME growth. The third chapter details the methodology and tools used to analyse

the data. From the description of the data collection and sampling methods, to

selection of the dependent and independent variables, the chapter continues to

highlight the econometric model and software used.

Consequently, Chapter four will follow and present empirical results and summary

statistics of the analysis. Based on this, a detailed interpretation and discussion of

the findings shall close the chapter. And in concluding the dissertation, Chapter 5

will summarise the research findings and highlight the policy implications for

economists and policy makers.

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CHAPTER 2 - LITERATURE REVIEW

2.1. Introduction

For some time now, the role of SMEs in development have been undermined

especially in developing countries in preference for large scale enterprises. The

various arguments advanced for this are that large scale enterprises especially foreign

ones bring with them the vital capital injections, expertise and technological transfers

while at the same time create employment and present tax benefits for the domestic

economy. As such, many developing countries’ policy makers have been more

concerned about creating a macroeconomic atmosphere which favour such large

scale multinational companies and foreign investments at the expense of the local

industries. Although most of the policies aimed at creating this environment would

benefit all stakeholders at large, some of them have had the effects of undermining

the growth of Small and Medium Enterprises (SMEs). Despite evidence from Beck et

al., (2006) finding no causal relationship between SME growth and economic

development, it does however establish a positive correlation between the two. This

means that, countries that achieve higher levels of economic growth also exhibit a

vibrant SME sector. Besides, evidence is vast from around the world that today’s large

scale enterprises were once SMEs themselves. Of central focus to this paper are

lending rates and how they impact SMEs’ ability to access financing and transform

into large scale enterprises.

This chapter sets the conceptual and theoretical framework for the research by

reviewing empirical studies on the topic. The chapter explores the underlying theories

and empirical studies on interest rates as well as how they impact various aspects of

economic growth. The study proceeds to define the main concepts and discusses the

major debates on lending rates, investments, access to finance and characteristics

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and determinants of SME growth. Thereafter, a detailed study of the relationship

between Lending rates and a firm’s investment decisions shall follow. Furthermore,

the chapter meticulously highlights the relationship between Lending rates and how

they affect a firm’s ability to access finance both from the supply side and demand

side. Empirical evidence from existing literature is presented to support the research.

The rationale here is to draw attention to the link between lending rates and how they

influence a firms’ productivity as well as its ability to access to credit and

consequently make investment decisions. A case study of Zambia shall be presented

outlining the economic and financial reform background as well as an examination

of the interest rate policy and its determinants. By comparing the performance of

SMEs in Zambia with those of other Sub-Saharan countries, the chapter concludes

by building the hypothesis to ascertain the relationship between the two which is

then tested in Chapter 4.

2.2. Small and Medium Enterprises

Small and Medium Enterprises are a vital part of a well-functioning economy.

Developed countries have witnessed exceptional rise of start-ups transform into giant

multinational corporations. From Tech companies such as Microsoft, Apple, Tesla,

social media companies like Facebook, Google, LinkedIn and trading companies like

Amazon, eBay, Alibaba as well as transport and media companies like Virgin, SpaceX,

Tesla and General Motors all were once tiny companies some of which originated in

university dormitories and homes to later became the major growth companies of the

past three decades. Just like advanced countries, developing countries also need to

promote their small and medium enterprises if they are to accelerate their economic

growth. Empirical evidence reveals that SMEs create more than 50% of the total

formal employment and they also generate the highest rates of job creation even

surpassing large corporation, (Ayyagari, et al., 2007; Ayyagari, et al., 2011).

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2.2.1. The Definition of SMEs

The definition of Small and Medium Enterprises varies depending on the target region

and institutions involved. Additionally, different aspects of SMEs are considered

when defining them. Some scholars define SMEs in terms of number of employees,

while others define them in terms of performance measures such as annual turnover

and Balance sheet capital injection. The European Union defines a small and medium

enterprise as a company that employs 250 or fewer employees, or has an annual

turnover of up to €50million and a balance sheet of up to €43 million (European

Union, 2012). Gibson and Vaart (2008) on the other hand defines an SME as “a formal

enterprise with annual turnover, in U.S. dollar terms, of between 10 and 1000 times

the mean per capita gross national income, at purchasing power parity, of the country

in which it operates.” Although the later definition is ideal as it uses annual turnover

to categorise the SMEs, the most former is commonly due to the ready availability of

such data on employment as compared to turnover as most SMEs rarely keep

updated financial information1.

According to Caner (2014), SMEs are characterised by high failure rates, produce

intermediate low value added goods, and are mostly informal and semi-formal

enterprises that usually lack corporate business acumen. Perhaps it is because of

this trait that makes it hard for them to raise financing as 50% of them do not have

access to formal credit (World Bank, 2016). Caner (2014) adds that due to their

informal nature, they normally hire unreported labour and are prone to tax evasion

issues.

1 Most SMEs especially in developing countries operate on a thin line between the formal and informal sectors

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2.2.2. Sources of Finance

Empirical evidence reveals that due to their informal nature and small size SMEs find

it difficult to raise finances from financial institutions (Beck, et al., 2006). In their

infancy, they rely extensively on personal resources as well as that from family

members and informal sources. For capital intensive projects, such large investment

funding can only be accessed from commercial banks especially in developing

countries where capital markets are under developed. According to Mankiw (2016)

financing constraints such as the cost of borrowing, can prevent firms from taking

up profitable investments. Non-Bank Financial Institutions are also influenced as

some of them source their capital directly from banks hence contributing to their

higher interest rates.

Figure 2-1 below presents the percentage of total firms financed by the banks.

Figure 2-1: Percentage of SMEs Financed by Banks in Sub-Saharan African

Source: Enterprise Surveys of the World Bank (2013)

From

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Figure 2-1, it can be seen that a small percentage of SMEs in Sub-Saharan Africa are

financed by Banks, with Mauritius attaining the highest percentage at 30.8% while

the rest of the countries under review recorded financing below 26%. Zambia

recorded an alarming lower percentage attaining only a meagre 6.6% of SMEs

financed by banks.

According to the research by Vaselin (2014), fully financially constrained firms have

no loans because their loan applications were rejected or the firm did not apply for

credit due to harsh credit terms even though they needed it. Other scholars,

(Ayyagari, et al., 2006; Beck, 2007; Beck & Demirguc-Kunt, 2006) suggest that firms

may not apply for credit due to; (1) having enough funds generated from business

operations; (2) harsh conditions from lenders which may include high interest rates,

technical requirements and collateral requirement for credit grants; (3) Or simply that

the firm’s applications were rejected based on strict credit criteria ultimately forcing

them to seek other sources (Vaselin, 2014). Alternatively, many firms seek external

sources of funding such as informal sources like money lenders, family and friends

which are viewed as being more efficient with more flexibility in their lending

approach compared to the big banks ( Cull , et al., 2008)

2.2.3. SMEs and Growth: Empirical Evidence

The debates as to whether growth in Small and medium enterprises leads to overall

economic growth has been well documented. Evidence from Beck (2007) in his cross-

country studies suggests a positive correlation between the two, where countries that

had a larger SME base showed higher or faster growth compared to those that had a

smaller SME base. Although this was the case, the findings do not establish a causal

relationship between SMEs and economic growth. Additionally, SMEs accounted for

a greater share of employment in the private sector of most economies thereby

consolidating their contribution to economic growth (Enterprise Survey, 2013). As

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developing countries begin to attain stronger growth, SMEs begin to play a more

cardinal role in industrial development and restructuring, providing intermediate

goods and services, allowing for increased specialisation and complementing larger

enterprises with inputs and services (Fjose, et al., 2010).

Figure 2-2: SME growth in Employment

Source: Enterprise Surveys of the World Bank (2013)

Figure 2-2 shows the percentage increase in employment created by SMEs. It can be

noted that SMEs have contributed to employment growth with percentages between

10% to 12.2% for the majority of the countries. SMEs in Angola and Gabon appear

to be growing faster than the rest by this measure at 18.7%. Only Zambian SMEs

seem to contribute very minimal to employment creation at only 1.5%.

Despite acknowledging the role of SMEs in providing intermediate goods, Caner

(2014) draws attention to the low value added goods and services they produced as

well as the SMEs’ short life span due to high bankruptcy rates among them. Perhaps

this is the reason why scholars and policy makers had for a long time neglected the

SME sector in preference for large enterprises and multinational corporations as

drivers of growth (McPherson, 1992). According to their arguments, large companies

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bring in the much needed foreign capital, technologies and expertise and would

eventually drive economic growth while sharing the benefits with the local people

through job creation and trickled down effect. A disadvantage of relying too much on

large scale foreign companies however is that, the goods they produce are not

necessarily intended for the local market. This is because they mostly aim to

penetrate international markets and their pricing strategies may ultimately make

them overlook the local markets in preference for lucrative international markets.

Additionally, they create an industrial gap as they do not mostly produce intermediate

or low value goods which may be needed by the local markets in which they are based.

Hence, SMEs emerge to fill up this gap. After realising the volatile nature of large

enterprises especially in this era of increased globalisation and capital mobility, there

have been renewed interest in SME research and development from both scholars

and policy makers in the recent past. SMEs are believed to be the engines of

economic growth but poor institutions, policies, market failures and macroeconomic

instabilities impede their expansion (World Bank, 2016).

2.3. What Determines SME Growth

Recent studies have reinvigorated the importance of SMEs in economic development.

Ayyagari et al. (2007) in their research found that SMEs create more employment

than the large corporations which were initially promoted. Development institutions

such as the World Bank, African Development Bank among others have now

dedicated significant funding and resources to try to promote the SME industry. The

idea is to stimulate the sector as the engine of economic growth given their outreach

potential and magnitude of their impact. The vision is that they would graduate into

large scale multinational enterprises and contribute even further to economic growth.

As noted by McPherson (1992), much of the support to the SME sector is through

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policy reform as well as business skills training to the entrepreneurs in an effort to

make them compete with large scale enterprises.

Macroeconomic instability creates a hostile business environment that undermines

SMEs’ performance. Specific challenges include weak regulatory and contract

enforcement institutions, corruption, costs of doing business as well as financial and

economic policies (Enterprise Surveys, 2013). These challenges have given rise to the

high failure rates of SMEs especially in developing countries where most of them

stagnate or fail completely before their 3rd birthday. Liedholm and Mead (1993) assert

that the economic situation prevailing in a country plays a key role in the emergence

of SMEs. According to their argument, new SME start-ups in developing countries

are more likely to reflect primarily a case of people seeking a way of sustaining

themselves due to economic hardships. On the contrary, in developed countries, new

enterprises arise as a result of a growing demand for goods and services in expanding

sectors. As such, the number of New start-ups varies inversely with the aggregate

level of economic activity in developing countries while the opposite is true for

developed countries.

Many scholars, such as Levine (2005) and Beck et al. (2005) among others

emphasised the context of the macroeconomic environment in which firms operate

as a constraint, one of them being the financial policies. Sound financial policies are

a necessary condition for attaining economic growth as they are usually the key

determinants of the business environment in the economy. From them, exchange

rates, inflation, taxation and interest rates among others are derived. Mwenda and

Mutoti (2011) assert that repressive financial policies affect the business environment

and cause credit rationing thereby influencing savings and investment decisions,

returns on assets and the ability to access finance.

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2.3.1. Financial Constraints

Of all the constraints facing SMEs, access to finance ranks the highest. According to

the World Bank (2016), 50% of SMEs do not have access to finance with the number

rising to 70% when micro-enterprises are considered. This translates to about

$2.6trillion credit gap for both formal and informal SMEs. Research by Beck, et al.

(2008) and Beck et al. (2006) reveals that size plays a key role in determining access

to finance, with smaller firms having more difficulties in accessing finance compared

to larger ones. Evidence from Ayyagari, et al. (2006) finds that financial constraints

limit a firm’s size and growth. Furthermore, due to lending institutions’ preference

for large enterprises, SMEs use less finance from formal sources such as Banks and

rely more on internal sources, supplier credit and informal sources such as money

lenders and family and friends (Ayyagari, et al., 2006; Enterprise Surveys, 2013).

Economic policies, especially financial policies have a significant influence in shaping

the business environment in which firms operate. Financial policies determine

profitability and turnover of both the SMEs and the commercial banks which provide

their financing, through directly affecting the operational costs and margins

respectively. Hence monetary policies of raising interest rates appear to be at the root

of these access to finance challenges.

2.4. Interest Rate Theory

Interest rates have for a long time been considered the key determinants for capital

flows. Neoclassical economic literature emphasizes the negative relationship between

interest rates and capital flows (Mankiw, 2009). Although this may be true in most

cases, there are different aspects of interest rates that are worth noting. These include

the interest rates earned on investments, also called the rates of return; and the

interest rates paid out for renting assets, otherwise known as Lending rates. In some

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literature, they are used interchangeably, although they could be mutually exclusive,

the lender may not necessarily be the borrower.

From the earning perspective (supply side), interest rates represent the returns on

investment made and are considered income. Hence the higher the interest rates, the

higher the returns on investments and consequently more capital inflows. Examples

for such assets which are motivated by high interest rates include equity, capital,

bonds and many others. The higher their yields, the more attractive they become.

This rationale is well explained in the international capital mobility theories (Begg,

2014; Mankiw, 2016).

On the paying side (demand side), interest represents the price of borrowing and is

thus considered as a cost. In this regard, the high lending rates entail high costs of

borrowing and results in lower investment expenditure by the firms. This is the basis

of the investment function which stipulates a negative relationship between interest

rates and investments (Mankiw, 2016).

This background is the basis of credit lending decisions by banks which fall on the

supply side. Firms on other hand fall on the demand side. Bernanke and Gertler

(1995) review lending decisions by banks using balance sheet channel. Bougheas, et

al. (2006) further elaborate on this view by explaining that banks base their lending

decisions on financial performance factors such as profitability, credit history, debt

levels and so on. In most developing countries, Banks are the major providers of

financing due to the undeveloped capital markets. In Sub-Saharan Africa, this is even

more evident as the numbers of firms raising funds through the stock markets are

very minimal compared to developed countries and emerging markets. This argument

is also supported by Kashyap and Stein (1994).

Hence, the tight monetary policies through high interest rates present an adverse

situation compounding the problem of SME growth through access to finance more

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especially on SMEs that rely to a large extent on bank lending for larger capital needs.

Figure 2-3 shows this transmission effect.

Figure 2-3: Interest Rate Transmission Mechanism

Source: Bank of Georgia2

Figure 2-3 it can be noted that in an effort to curb inflation and reduce price levels, an

increase in interest rates reduces the availability of credit on the market.

Furthermore, because the cost of borrowing also increases, firms scale down on

expansionary expenditures and investments and the overall result is a reduction in

aggregate demand and growth. Consequently, SMEs will fail if they are subverted by

bad policies which affect both their operational costs and their ability to take up

expansion opportunities. It is imperative however, to note that repressive financial

policies may not be implemented to sabotage the economy, but may rather be in

2 There are many theories which express the transmission mechanism of high interest rates, however, the one from the (Bank of Georgia, 2010) expresses it in a more simplified version.

18 | P a g e

response to solve an urgent economic condition such as inflation, foreign exchange

volatility or curb capital flight.

On the supply side, monetary policy results in credit rationing by banks through

aggressive pricing of loans to reflect opportunity costs, the risks in balance sheet

information, as well as the costs of borrowing (Bougheas, et al., 2006). Where the

central bank adopts a policy rate, the situation is usually worse as banks adjust their

lending rates by charging a margin on this indicative rate. Brownbridge (1998) in his

analysis of the financial reforms of Zambia reaffirms this and adds that such pricing

leads to adverse selection as most credit worthy firms avoid the high interest loans

leaving only the risky ones thereby impairing the banks’ credit portfolio.

In situations where interest rates are guided by a central bank policy rate system,

Banks normally use this as the indicative rate for the cost of capital and would charge

a margin above or below the policy rate to maximise their earnings. Hence the overall

consequence is the general rise in the lending rates in the economy. The impact is

severe for those SMEs that rely on Bank financing and usually leads to high default

rates due to inability to pay the high interest rates. Non-Bank Financial Institutions

are also influenced by these lending rates as most of them use bank lending rates as

their benchmarks. Hence rates charged by NBFIs are even higher.

In addition to this, the credit available from other sources; family, friends and money

lenders, is usually of small amounts for capital expansion (Cull et al., (2011). All these

scenarios leave little room for raising finances from financial institutions. Hence, the

tight monetary policies through increasing the interest rates present an adverse

situation more especially to SMEs that rely to a larger extent on Bank lending for

larger capital project and investments.

Firms require financing to undertake investments. Mankiw (2016) defines investment

in three categories namely business fixed, residential fixed and inventory investment.

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According to this definition, business fixed investment is where firms grow and

expand by purchasing new structures, equipment and intellectual property products.

Residential investment on the other hand involves purchases of housing while

inventory investment comes about as a result of a firm’s increases in its stock (Ibid).

This research refers to business fixed investment spending. From neoclassical

economic theory, increases in real interest rates leads to a reduction in investment

hence the negative relationship between the two. In order for firms to produce goods

and services, they require capital to purchase land, machinery and equipment as well

as the technologies.

2.4.1. Why Policy Makers Normally Increase Interest Rates

Policy makers around the world have always implemented ambitious policies in their

bid to meet macroeconomic targets. The primary focus has thus been on attaining

positive economic growth rates, stable exchange rates, low unemployment and of

course low inflation rates. It is in trying to stabilize inflation that the link with interest

rates becomes more pronounced. Mankiw (2016) views interest rates as the prices

that link the future with the present. According to this view, central banks raise

interest rates using the Fischer equation and quantity theory of Money. The quantity

theory of money shows that money supply, or the rate of money growth determines

the inflation rate in the economy. Hence, it is usually in response to inflationary

pressures that policy makers base their monetary growth decisions. In doing so, they

actually affect the interest rates as well. Thus if interest rates rise in response to

rising inflation, then the real interest rates, which is the difference between the two,

will also rise.

𝒓 = 𝒊 − 𝝅 (Equation 2-1)

𝑊ℎ𝑒𝑟𝑒 𝑟 = 𝑟𝑒𝑎𝑙 𝑖𝑛𝑡𝑒𝑟𝑒𝑠𝑡 𝑟𝑎𝑡𝑒𝑠, 𝑖 = 𝑛𝑜𝑚𝑖𝑛𝑎𝑙 𝑖𝑛𝑡𝑒𝑟𝑒𝑠𝑡 𝑟𝑎𝑡𝑒 𝑎𝑛𝑑; 𝜋 = 𝑖𝑛𝑓𝑙𝑎𝑡𝑖𝑜𝑛

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Hence through this interaction, the effects of inflation on real and nominal interest

rates can be determined. Understanding this theory is cardinal in analysing how

interest rates and inflation should move. Empirical evidence from the IMF shows a

positive correlation between the two. In the Zambian context, lending rates and

inflation rates have generally been declining steadily since mid-1990s although there

were some up swings between 2008 and 2010, they are still relatively high. Inflation

has generally been contained below 10% since 2007. Figure 2-4 highlights this trend.

Figure 2-4: Lending Rates Vs Inflation Trends in Zambia

Source: Author’s computations using BOZ data

Besides raising the cost of borrowing, lowering domestic investment expenditure due

to the high earnings on savings and adverse selection issues, high interest rates have

more ramifications. As argued by Mankiw (2016), in a worst case scenario, higher

interest rates can reduce economic growth and even trigger a recession as a result of

slowing investments and economic activity (see Figure 2-3).

0.0

20.0

40.0

60.0

80.0

100.0

120.0

140.0

160.0

180.0

200.0

1990 1995 2000 2005 2010 2015 2020

Lending Rates vs Inflation

Interest Annual Inflation

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2.5. The Zambian Case

2.5.1. Background

From independence, Zambia did not have a clear SME policy until 1981 as the

majority of the businesses in the economy where state run. This was largely due to

the import substitution industrialisation policies undertaken by the government. Due

to the commodity and oil crisis of 1975 which saw copper prices tumble and economic

downturn, the government embarked on a new policy to promote SMEs although this

impact was insignificant (Mumbi & Kafula, 2011). It was not until the 1990s when

the new government embarked on massive privatisation campaigns and economic

liberalisation programs which saw the selling of state enterprises, and massive job

downsizing that a significant number of Zambians began indulging in SME activities

due to the resulting unemployment.

Reforms and readjustments continued for another dozen years until the late 2000s

when the country started enjoying a period of sustained economic growth averaging

7% annually. The financial sector reforms, debt cancellation and good copper prices

contributed to an improved balance of payment position and saw the country attain

budget surpluses and accumulate foreign reserves.

2.5.2. Recent Developments

SMEs in Zambia have been performing much lower than their counterparts in Sub-

Saharan Africa and other developing countries. This has been largely attributed to

the unstable macroeconomic environment. Recent macroeconomic developments

showed a number of economic challenges facing the country. According to the IMF

(2016) mission report, a volatile exchange rate resulting from the fall in the copper

prices sent the country’s currency in free fall. This situation has been exacerbated by

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increased borrowing from the international markets which made debt repayments

high and left the country in deficit. Furthermore, the rise in inflation forced central

bank activity on the market through open market operations and raising of interest

rates as they struggled to curb inflation and maintain positive growth which had

taken a dive from a peak of 7% enjoyed in 2008 to 3.4% in 2016 (IMF, 2016). These

increased rates entail a rise in the cost of borrowing. The situation is further worsened

by electricity shortages, budget deficit and increasing debt stock all putting the

country under intense pressure. Likewise, high inflation, and rising interest rates

have made financing conditions very tight. It is forecasted that growth will slump

further to about 3 percent in 2016 less than half of what the country enjoyed between

2008 to 2013 (IMF, 2015; World Bank, 2016).

2.5.3. Zambian SME Constraints

This adverse macroeconomic environment has led to poor overall performance of

Zambian firms. Like SMEs in most developing countries, Zambian SMEs also face

harsh conditions for them to survive and mature into large scale enterprises. Among

the top constraints include access to finance, practices of informal sector and

electricity shortages.

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Figure 2-5: Ranking constraints to SME growth in Zambia

Source: Enterprise Surveys of the World Bank (2013)

Because of the high Lending rates, recently hiked to a record 15.5% (BPR)3 in 2016,

difficult credit terms, only a small proportion of firms in Zambia are financed by

banks (BOZ, 2016). In addition to this, the World Bank Enterprise Survey, reveals a

sharp decline in the percentage of firms seeking financing from banks from 15% in

2007 to 9.9% in 2013 (Enterprise Surveys, 2013). Perhaps this is explained by the

large number of firms whose loan applications got rejected (see

Figure 2-6).

3 Bank of Zambia Policy Rate

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Figure 2-6: Comparison of Zambian SME Loan Rejections

Source: Enterprise Survey of the World Bank (2013)

From

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Figure 2-6, Zambia tops the group in having the highest number of rejected loans for

SMEs at 34.1%. This figure is closely tailed by Sudan at 33.8%. The rest of the Sub-

Saharan African countries ranged between 10.2% and 28% of rejected loans.

2.5.4. Performance of SMEs in Zambia

Similarly, growth of firms in Zambia slowed as annual sales growth slumped to 11%

between 2010 and 2012, to 20% between the period 2005-2007. The performance of

Zambian firms has been below par compared to other SSA countries. In terms of

percentage of annual sales growth, Zambian firms grew at the least pace at 11.4%

while for the rest of Sub-Saharan countries, Sales growth ranged from 17.9% for

Guinea-Bissau, to 66.3% for Angola.

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Figure 2-7: Performance of Zambian SMES in Terms of Percentage Growth in Sales

Source: Enterprise Survey of the World Bank (2013)

In view of the above situation, the study reviewed the stock market to ascertain

whether firms were sourcing their funds from the capital markets or perhaps

expanding and listing there. Just like in many developing countries, the number of

firms raising funds through capital markets is very small compared to developed and

emerging markets (Kashyap and Stein, 1994). Mostly companies that manage to raise

such finances are usually large scale enterprises. However, many firms in Zambia

have failed to expand into large scale ones, and two thirds of the companies listed on

the stock market were originally state run enterprises with only few exceptions having

graduated from SME category into large scale enterprises.

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Figure 2-8: Trends for Number of Firms Listed on the Lusaka Stock Exchange

Source: World Bank (2016)4

As can be observed from

Figure 2-8, the number of listed companies quickly shot up between 2000 and 2002

when they peaked at 30. However, the following years saw a sharp decline to 10

companies in 2003. At 2014, the numbers improved to 20 listed companies although

this is still below the 2002 levels. Ironically, about two thirds of the listed firms are

former state owned parastatals with very few independent local firms making the list.

The rest are multinational firms.

4 The break in trends between 2016 and 2014 is as a result of unavailability of data.

28 | P a g e

Table 2-1: Lusaka Stock Exchange Listed Companies

COMPANY LISTING DATES INDUSTRY5

1.Lafarge Zambia plc 22/05/1995 Manufacturing (g)

2.British American Tobacco (Z) Ltd 15/12/1995 Retail Trading (m)

3. Real Estate Investments Zambia Plc 28/08/1996 Property (m)

4. Zambia Sugar Plc 27/09/1996 Agriculture processing (g)

5. Zambian Breweries Plc 09/06/1997 Manufacturing (g)

6. National Breweries Plc 16/03/1998 Manufacturing (g)

7. Standard Chartered Bank Plc 30/11/1998 Banking (m)

8. ZCCM-Investment Holdings Plc 12/01/2000 Investments (g)

9. Taj Pamodzi Hotels Plc 24/12/2001 Hospitality (m)

10. Puma Energy (Z) Plc 18/06/2002 Oil Marketing (m)

11. Shoprite Holdings Plc 19/02/2003 Retail (m)

12. ZAMEFA Plc 08/09/2004 Manufacturing (g)

13. Zambeef Products Plc 05/04/2005 Agriculture Processing (l)

14. Cavmont Capital Holdings Plc 13/09/2006 Investments (l)

15. AEL Mining Services (Z) Plc 23/10/2006 Mining (m)

16. Investrust Bank Plc 18/06/2007 Banking (l)

17.Copperbelt Energy Corporation Plc 21/01/2008 Energy (l)

5 The Firm ownership history is presented together with the industry where; (m) = Multinational, (g) = Formerly State owned, (l) = Local

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18. Airtel Networks Plc 11/06/2008 Mobile Telecommunication (m)

19. ZANACO plc 27/11/2008 Banking (g)

20. Zambia Bata Shoe Plc 31/03/2009 Manufacturing (m)

21. Prima Reinsurance Plc 30/08/2013 Insurance (l)

22. Madison Financial Services Plc 01/09/2014 Finance (l)

Source: Lusaka Stock Exchange (LUSE, 2016).

From this

Table 2-1, it can be noted that the growth of the listed companies has been slow. The

table asserts the argument that very few SMEs grow to the extent of listing with only

about 27% of locally owned firms reaching this level. Former parastatals which were

privatised form a significant portion at 32% while the multinationals dominate at

41%. Similarly, the percentage of firms in Zambia that export directly or indirectly,

has slumped slightly lower than six years ago. The Enterprise Survey (2013) reveals

that, exporting SMEs dropped from 15% in 2007 to 12% in 2012. And export sales

decreased, from 4% in 2007 to 2% in 2012. All these results seemingly reveal the

characteristics and the macroeconomic environment in which SMEs operate in

Zambia.

2.6. Conclusion

A vast amount of literature including that of Levin (2006) emphasised the importance

of the macroeconomic environment in determining SMEs’ success. Sound financial

policies are a necessary part of this environment for accelerating economic growth

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and SME development. Repressive financial policies such as credit rationing, high

inflation, high interest and high tax rates affect savings, asset returns and the

allocation of credit. Consequently, SMEs fail if they are subverted by poor policies

which affect both their operational costs and their ability to take up expansion

opportunities (Mwenda & Mutoti, 2011).

The deteriorating performance of SMEs in Zambia raises concern over the kind of

macroeconomic environment in which they operate especially the financial policies.

The destitution of SMEs in accessing financial services is having a toll on their

performance. Unsurprisingly, access to credit is the most commonly reported

obstacle by firms in Zambia. As highlighted in this chapter, only a small number of

firms raise their funds from commercial banks. However, in order for them to mature

or commercialise, they require external finance hence the existing lending rate

policies become imperative to their growth and survival.

This chapter has presented the theoretical and conceptual background for the

dissertation. The chapter explored characteristics and nature of Small and Medium

Enterprises as well as determinants and constraints to their growth. Moreover, the

relationship between interest rates, inflation and access to finance has been

highlighted. Using the transmission mechanism, the study highlighted how high

interest rates impede access to credit and consequently SME growth. An overview of

SME macroeconomic developments and performance in Zambia was reviewed. The

next chapter presents the tools and methodologies to be used in determining the

extent to which lending rates affect the performance of Small and Medium

Enterprises (SMEs).

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CHAPTER 3 - METHODOLOGY

3.1. Introduction

This chapter explains the tools and methods used to collect, analyse and present the

data. As argued by Biggam (2011), the methodology is an important component of

research as it validates the research and provides a means for replicating or building

on the study by other researchers using the similar methods thereby authenticating

the research. The primary focus of this study is on the impact of Lending rates on

SME growth although the study also explores the role of Credit Granted and

Electricity supply in influencing that growth. Despite extensive literature

emphasising the importance of SMEs in economic growth, many developing countries

still side-line SMEs in preference for large scale enterprises. Hence, the chapter

formulates and tests the hypotheses in order to answer the research objectives.

It begins by a review of the objectives of this study and formulating the research

hypotheses. Thereafter the Chapter will outline the nature and sources of the data,

specify variables and the estimation method for this research. Finally, this chapter

will present the research limitations and a summary of the main points.

3.2. Objectives Review

In view of the purpose of the study, the following objectives were outlined: -

a) To ascertain the significance of Small and Medium Enterprises in stimulating

sustainable economic growth and development especially for developing countries

like Zambia.

b) To assess the impact of austerity measures namely contractionary fiscal and

monetary policies on the growth and expansion of SMEs.

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c) To identify ways of overcoming the challenges faced by SMEs and policy

implications for inclusive sustainable development for policy makers.

The contributions of this research work are primarily empirical although the findings

to be presented may provide the basis for better modelling of Financial Policies for

SME growth in the future.

3.3. Hypothesis Formulation

Based on neoclassical economic theories as well as empirical evidence for various

literature and given the above objectives, the study formulates the hypothesis to be

tested as below;

3.3.1. Hypothesis 1

Boivin, et al (2010) illustrates that monetary policy targeted at price stability has a

muting effect on economic activity. His findings reveal a correlation between policy

interest rates and economic activity. According to this view, an increase in money

supply leads to a fall in interest, capital outflow, depreciation and an increase in

output. This is an ideal situation for local SMEs to expand and increase their capacity

and increasing exports as the price of local goods become cheaper due to the low

exchange rates. Given the lower interest rates, SMEs are expected to have better

access to finance needed for their growth. On the other hand, contractionary

monetary policy reduces money in circulation, raises interest rates and reduces

output. As such, SMEs are expected to have difficulties to access finance, lower sales

on international markets as their products becomes expensive due to the

appreciation of the exchange rates. Hence, hypothesis 1 is that high lending rates

will reduce Productivity (SME Growth). This is the primary objective that the study

tests.

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3.3.2. Hypothesis 2

As argued by Beck and Demirguc-Kunt (2006), access to credit plays an important

role in SME growth. Although Access to finance on its own depends on other factors,

this study views it in as a consequence of high lending rates. In this regard, it is

observed from the credit supply perspective. As discussed in Chapter 2.4.1,

Contractionary monetary policies reduce money in circulation, increase interest rates

and reduce aggregate demand. Due to the high policy rates on which commercial

banks base their lending decisions, the cost of lending increases. Large firms

normally go unaffected by these changes due to their bargaining power and the size

of their transactions. Smaller firms on the other hand bear the brunt. As the cost of

bowing increases due to the high lending rates, few SMEs are expected to access cred

from banks. Hence, Credit Granted by banks to SMEs presents an ideal way of

measuring the indirect impact of high lending rates on SME growth. Firms need credit

for them to grow and expand. Hence by assessing the productivity of firms when

granted credit, the hypothesis will be tested. Hence, the hypothesis is that SME

productivity increases with credit granted.

3.3.3. Hypothesis 3

As highlighted in the empirical evidence in Chapter 1.2 & Chapter 2.3, the business

atmosphere in which firms operate plays a key role in determining their opportunities

for expansion. The combined financial policy environment and institutional

infrastructure ultimately determines the SMEs ability to enter the industry, grow or

stagnate. In their studies, Liedholm and Mead (1993) found that SME growth varies

inversely with aggregate levels of economic activity which itself is enhanced through

proper infrastructure such as the availability of efficient transport, communication

and electricity services among others. Thus, this study reiterates importance of

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electricity as an explanatory variable to SME growth. Hence, the hypothesis is that

Electricity Supply is positively correlated to Productivity, in testing this, the study

expects to find lower SME growth associated to low electricity availability and high

SME growth associated with periods of high electricity availability.

3.4. Nature and Sources of the Data

This dissertation uses secondary data from the Bank of Zambia (BOZ, 2015), Central

Statistical Office (CSO, 2015), Zambia Data Portal (ZDP, 2015). The approach is both

qualitative and quantitative and uses a desk review method of analysis. Secondary

research is ideal in this case due to the wealth of data gathered by Official institutions

which increases the reliability of the data. The Bank of Zambia (BOZ) publishes daily

and fortnight data on key financial indicators such as Lending rates, Credit Granted,

Exchange rates and many more and is thus the ideal source for collecting trends in

the study’s key variables. The Central Statistical Office (CSO) publishes quarterly

data on employment and economic statistics in Zambia while the Zambia Data Portal

is a comprehensive database for industrial productivity in Zambia as well as key

economic indicators. Hence, the later and former provided data on Electricity and

manufacturing productivity in Zambia. Thus, when considered in totality, all these

sources provide a wealth of information that is adequate to answer the objectives of

this research.

To assess the relationship between Lending rates and SME growth, the study employs

a multiple linear regression model using ordinary least Squares (OLS). This method

is widely used in research to test for correlation between variables. Cross country

comparisons were done through trend analysis where trends among countries were

assessed to determine if there were variations. For this study, SME performance in

Zambia was compared with countries selected from Sub-Saharan Africa. This was in

order to control for the political and economic context of the countries, which is

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similar. The time series data therefore measures changes in SME Productivity due to

variations in Lending Rates, Credit Granted and Electricity Supplied between the

period 1996 to 2015. To run regressions, the data was analysed using the statistical

software STATA, although any other software could be used and should yield similar

results.

3.5. Estimation Model Specification

The research was conducted on SMEs in the manufacturing sector in Zambia and a

comparative analysis of other Sub-Saharan countries. The study employed multiple

regression analysis methods using Ordinary Least Squares (OLS) with time series

data from the Bank of Zambia, Central Statistics Office and Zambia Data Portal.

The aim of this dissertation is to examine the impact of lending rates on the growth

of small and medium enterprises and ascertain whether a causal relation possibly

exists between these variables. In this essence, the hypothesis to be tested is whether

a negative correlation exists between high lending rates and SME growth as measured

by firm productivity. Nonetheless, it is worth noting that there are many other factors

that may affect SME growth other than lending rates. Hence, additional variables

must be included in order to capture the multi-dimensional nature of SMEs growth

and gauge the extent of their influence on it. Although SME growth has been

measured by other variables such as employment, turnover, profitability and many

others, this study adopts a single dimensional measure using productivity as the

indicator that epitomises SME Growth. This measure has been chosen not only

because of availability of data, but most importantly to control for the effects of other

variables that may affect SME growth that are not captured.

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From the previous chapters, the derived hypothesis assumes a direct connection

between lending rates and SME growth hence the need to control for size, age and

ownership.

3.6. Selection of Variables

The variables chosen the purposes of this research are presented in the following

sections.

3.6.1. Dependent Variable

The dependent variable is the variable which is impacted upon by the explanatory

variable. In other words, it is one which varies due to the influence of an independent

variable. For purposes of this study, SME Productivity has been selected to measure

the variation in SME Output caused by the independent variables.

3.6.1.1. Productivity

The dependent variable for this research is Firm Productivity also known as Output

per year. Productivity has been chosen amongst employment, turnover and

profitability, to depict SME growth due to the readily availability of the data as well

as its high responsiveness to changes in economic factors hence making it a great

variable for this study. Data for this variable has been collected from the Central

Statistical Office (CSO) and Zambia Data Portal (ZDP) on the manufacturing SMEs in

Zambia per year. The manufacturing sector has been chosen because it is the sector

that receives the least incentives and subsidies in Zambia hence controls for bias that

may arise due to government intervention policies.

The analysis focuses on how SME Productivity responds to changes in lending rates

there by providing the basis to determine the correlation. Although Productivity is

measured in tonnes, this has been adjusted to index form (1000) in order to make

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the data more comparable to measures of other variables in this study. Therefore,

SME Growth is measured by the dependent variable growth in Productivity, and is

explained by changes Lending rates, Credit Granted to SMEs and Electricity supplied

to firms.

3.6.2. Explanatory Variables

The selected explanatory variables for the research model are Lending rates, Credit

Granted and Electricity availability. These have been chosen because they are the top

constraints that were reported in the Enterprise Surveys (2013) by Zambian

manufacturing firms. Therefore, it was cardinal to understanding exactly how they

influence SME growth.

3.6.2.1. Lending Rates

This is the primary explanatory variable whose impact the study seeks to invest.

Lending rates the interest rates that financial institutions charge to their SME clients

as a cost of borrowing and so presents a valuable measure in checking how it affects

SME growth. The Lending rates in this study are calculated as the average lending

rates composed of the BOZ Policy Rate plus the lending margin charged by the

financial institutions per year. This is because weighted lending rates omit the

lending margin which, although varies across financial institutions, is a key

determinant to SMEs access to Credit as illustrated in Interest Rate Theory 2.4. Although

NBFIs, money lenders and other sources of finance may have their own lending rate

rates, this study focuses on commercial bank lending rates which rely on the policy

rates.

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3.6.2.2. Credit Granted

Credit Granted refers to the amount of loans and other credit facilities granted to the

private sector per year. The rationale is to observe how monetary policies such as

increases in the policy rates and consequently the lending rates impact the amount

of Credit that commercial banks grant to firms. Demonstrating this relationship will

exemplify the robustness of the research model. This will moreover, examine the

assertions that SMEs seek other sources of funding as the cost of borrowing increases

although this is from the supply side (see Chapter 2.3). Access to finance entails how

easy it is to access funding for expansion and growth among SMEs as they take

advantage of new opportunities.

3.6.2.3. Electricity Supplied

As outlined in Chapter 2, Zambia has been facing erratic electricity supply for the

past few years. Despite the demand for electricity surging both domestically and

regionally, the country has made little strides in increasing its electricity generation

capacity. Hence, this variable is intended to measure the economic impact of erratic

electricity supply on the productivity especially of SMEs which rarely afford to use

other alternatives such as mobile power generators and power banks. This ultimately

affects the cost of production hence productivity.

3.7. Estimation Method

This study primarily aims to examine the impact of Lending rates on the growth and

expansion of Small and Medium Enterprises in Zambia. The objective is to determine

the correlation between these variables. As noted by Varian (2010), a model’s power

comes from the elimination of irrelevant details thereby allowing the economist to

concentrate on the critical aspects of the economic reality they seek to understand.

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Thus the chosen model demonstrates the relationship between the policy variables

and SME growth in a simplified way. Previous chapters have highlighted the variables

to be used in the regression model namely Productivity, Lending rates, Credit Granted

and Electricity availability. Hence, the econometric model to be used is as follows:

𝒚𝒊 = 𝜶𝟎 + 𝜷𝟏𝒙𝑖 + ⋯ + 𝜷𝒌𝒙𝒏 + 𝜺𝒊 (Equation 3-1)

Where;

𝒚𝒊 = Measures SME growth in terms of Sales

𝜶𝟎 = The intercept point at which the regression line crosses the 𝑦 𝑎𝑥𝑖𝑠

𝜷𝟏 … 𝜷𝒌= These are coefficient results from the regression using the software STATA

𝒙𝒊….. 𝒙𝒏 = These are the variables to be estimated

𝜺𝒊 = This represents factors that may affect SME growth but are not included I the

model.

The linearity of the variables is determined by the slope and intercept of the variables.

Regression analysis is commonly used to ascertain correlation between two or more

variables. Thus correlation exists if the variables exhibit linearity while the opposite

entails nor known relationship between the variables. Regression analysis therefore,

tries to establish this relationship in order to form grounds to accept or reject the

null hypothesis which assumes no relationship between variables. Fitting in the

selected variables into Equation 3-1, the regression model then becomes:

𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦𝑖 = 𝛼0 − 𝛽1𝐿𝑒𝑛𝑑𝑖𝑛𝑔 𝑅𝑎𝑡𝑒𝑠𝑖 + 𝛽2𝐶𝑟𝑒𝑑𝑖𝑡 𝐺𝑟𝑎𝑛𝑡𝑒𝑑𝑖 + 𝛽3𝐸𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦𝑖 + 𝜀𝑖 (Eq. 3-2)

This Equation 3-2, states that SME productivity depends on the lending rates, Credit

granted and Electricity as well as other factors that have been captured by the error

term 𝜀𝑖 . The signage of the coefficients is important as they reveal the nature of the

40 | P a g e

relationship. In Equation 3-2, lending rates are negatively related to productivity

while credit granted and electricity are positively related to it. The null hypothesis

would thus be:

𝑯𝟎 = No relationship between the explanatory variables and Productivity.

𝑯𝟏 = A correlation between at least one of the explanatory variables and

Productivity exists.

3.8. Limitations

Despite the data have been collected from reputable official sources, limitations exist

to its use. One limitation is that the definition of SMEs differs across countries regions

and aspects. SMEs can be defined in terms of size, turnover, profitability and

employment. Hence the chosen aspect of defining an SME also determines the

number of SMEs that fall under that categorisation. Some firms in Zambian context

could be large enterprises, but when defined in international terms, they would fall

into SMEs. Hence, for purposes of this study, large Enterprise are those that have

managed to penetrate international markets. Thus, those that haven’t are still in their

infancy and are thus considered as SMEs. This is important in order to draw logical

conclusion from the collected data as it is not categorised into large or small

enterprises.

Another is that the productivity data collected is the aggregate data collected for

manufacturing sector in Zambia and does not separately categorise small from larger

enterprises. This may lead to inaccuracies and generalisations in the results.

However, this limitation is eased by the study’s chosen definition of SMES, which

ultimately places majority of Zambian firms in the SME sector due to their capacity.

41 | P a g e

Similarly, credit granted by the commercial banks is the aggregate amount granted

to the private sector. The private sector definition does not separate small firms from

large firms thereby posing a similar challenge as the previous case. Furthermore,

some of the data collected was scanty or missing in some cases. In order to solve this

problem, the mean value and modes were used to fill the missing values.

3.9. Conclusion

This chapter highlighted the tools and methods used to collect and analyse the data.

The chapter elaborated on the sources and nature of the data to be used, the selected

variables and regression models as well as the hypotheses that have been deduced

for testing in the proceeding chapters. As observed by Levine (2006), many theoretical

models predict that a higher level of macroeconomic stability through appropriate

financial policies will induce a faster rate of economic growth, not just an increase in

the level of economic development. It is hypothesized in this study that lower lending

rates would produce similar results. The challenge however is striking a balance

between these two objectives of attaining macroeconomic stability while at the same

time promoting the local private sector. The next chapter presents the results and

discussion of the findings.

42 | P a g e

CHAPTER 4 - RESULTS ANALYSIS AND DISCUSSION

4.1. Introduction

This chapter presents the results of the regressions outlined in the preceding chapter

with respect to impact of Lending rates on Small and Medium Enterprise growth. The

chapter also elaborates how these findings meet the research objectives as outlined

in Chapter 1. It begins by highlighting descriptive statistics on the nature of the data

and outlining key observations. Thereafter the empirical results of the impact of

lending rates and credit granted on SMEs growth as measured by the firm

productivity variable will be presented and discussed.

The research uses productivity macro level data spanning a 15 years’ period from

2000 to 2015 from the Bank of Zambia, Central Statistical Office and Enterprise

Survey. As stipulated earlier in Chapter 3, the econometric model includes three

variables: Lending Rates, Electricity and Credit Granted. The data covers a range of

variables on manufacturing firms in Zambia. To ensure a focused analysis, the study

excludes small scale and artisan mining, as well as primary agricultural companies.

The Chapter concludes by discussing the implications of these results and how they

answer the research objectives.

4.2. Descriptive Statistics

In attempting to answer the main research questions, the study ran a regression to

test the importance of Lending Rates in improving Small and Medium Enterprise

growth by controlling for the effects that may be caused by other variables highlighted

earlier. In order to accept or reject the null hypothesis, this study used significance

43 | P a g e

levels of P < 0.01 and P < 0.05. According to Andren (2007), a P -Value reflects the

likelihood that a given outcome occurred randomly. In this vain the lower the P-Value

given the threshold criteria, the more statistically significant the coefficient is in

explaining variation.

As highlighted in the literature review, Lending rates are expected to have a negative

effect on the growth of SMEs because high Lending rates increase the cost of

borrowing and firms find it challenging to access credit and undertake expansionary

investments to increase productivity. Hence, if it is found in this analysis that higher

Lending rates do indeed reduce SME growth, as measured by their output and

productivity, the 𝜷𝟏 coefficient should be statistically significant and negative.

Table 2 below presents the summary statistics of the variables under investigation.

Table 4-1: Summary Statistics

Source: Author’s calculations6

The major variables in this model are Productivity and Lending rates. In this

summary in Table 4-1, the average productivity is 108.61 with an interval of 83.2

minimum productivity and 140.6457 maximum productivity. The Mean lending rate7

was 41% for the period under review with the minimum recorded Lending Rate of

25% and maximum of 64.8%. Similarly, the average Electricity supplied or consumed

6 Note that Productivity is in index format (1000) and calculations relate to the manufacturing sector only 7 Lending Rates are the Average Lending Rates i.e. (Weighted Lending Base Rate + Lending Margin)

CreditGran~d 15 30.76104 9.453956 17.05696 46.60998

Electricity 15 107.7583 20.20856 76.2 144.0796

LendingRates 15 41.65333 12.98531 25 64.8

Productivity 15 108.6123 18.21915 83.2 140.6457

Variable Obs Mean Std. Dev. Min Max

. summarize Productivity LendingRates Electricity CreditGranted

44 | P a g e

per year ranged between 76.2 and 144.08 with a mean of 107.76; while Credit

Granted ranged between17.06 and 46.61 with a mean value of 30.76 each year.

Based on the regression model established in Chapter 2, Productivity is a function of

Lending Rates (LR), Credit Granted (CG), and Electricity. This is a linear regression

model and is commonly used in research to establish whether a causal relationship

exists among the underlying variables. Furthermore, this model also reveals a

correlation between the variables. Figure 3 shows the linear correlations between

productivity and each of the explanatory variables: Lending rates, Credit Granted and

Electricity.

Table 4-2: Graphical Representation of the Correlation among the Variables

Source: Authors’ computations, output from regression

80

.00

10

0.0

012

0.0

014

0.0

0

Pro

ductivity

80.00 100.00 120.00 140.00Electricity

80

.00

10

0.0

012

0.0

014

0.0

0

Pro

ductivity

10.00 20.00 30.00 40.00 50.00Credit Granted

10

.00

20

.00

30

.00

40

.00

50

.00

Cre

dit G

rante

d

20.00 30.00 40.00 50.00 60.00 70.00Lending Rates

80

.00

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0.0

012

0.0

014

0.0

0

Pro

ductivity

20.00 30.00 40.00 50.00 60.00 70.00Lending Rates

45 | P a g e

Table 4-2 shows the negative correlation between lending rates and productivity. Figure

4-1 goes on to detail this relationship and it can be noted that the relationship between

lending rates and firm productivity is almost perfectly symmetrical. As lending rates

reduce, firm productivity increases proportionately. A fascinating point to note is how

well the lending rates effectively influence productivity with periods of low lending

rates corresponding to high productivity such as 2005 and 2006, 2012, 2014, 2015

and 2016.

Figure 4-1: Lending rates and Firm Productivity

Source: Authors’ computations based on Zambia Data Portal and BOZ

Figure 4-2 on the other hand shows a positive relationship between productivity and

electricity as well as credit granted. This result affirms the access to finance literature

that emphasise the role of credit in promoting SME growth and expansion. From the

graph, firm productivity increased proportionately to the increase in credit granted to

firms by banks. Furthermore, electricity also played a significant role in increasing

productivity will periods of increase electricity consumption correlating with periods

of high productivity.

0.00

50.00

100.00

150.00

200.00

0 2 4 6 8 10 12 14 16 18

Relationship between Lending Rates and SME Productivity

Productivity Lending Rates

46 | P a g e

Figure 4-2: Productivity and Credit Granted

Source: Authors’ computations based on data from Zambia Data Portal and BOZ

After running a multiple regression of the impact of lending rates and other

explanatory variables on SME productivity, Table 3 presents the results.

Table 4-3: Regression Results

0.00

20.00

40.00

60.00

80.00

100.00

120.00

140.00

160.00

0 2 4 6 8 1 0 1 2 1 4 1 6

Total Manufacturing Credit Granted

_cons 64.67494 14.01411 4.61 0.001 33.8301 95.51978

CreditGranted .8683522 .2422789 3.58 0.004 .3350998 1.401605

Electricity .3047864 .1177559 2.59 0.025 .0456074 .5639653

LendingRates -.3749356 .1385824 -2.71 0.020 -.6799534 -.0699178

Productivity Coef. Std. Err. t P>|t| [95% Conf. Interval]

Total 4647.1263 14 331.937593 Root MSE = 4.3735

Adj R-squared = 0.9424

Residual 210.402208 11 19.1274735 R-squared = 0.9547

Model 4436.72409 3 1478.90803 Prob > F = 0.0000

F( 3, 11) = 77.32

Source SS df MS Number of obs = 15

. regress Productivity LendingRates Electricity CreditGranted

47 | P a g e

Source: Output from Author’s Calculations using STATA

The resulting estimates suggest that the independent variables lending rates, credit

granted, and electricity have a profound impact of productivity of SMEs. The results

further assert the negative effect of lending rates and corruption on SMEs

productivity. From this analysis, Lending rates have a significant negative correlation

with productivity at 5% significance level, therefore the null hypothesis is rejected at

the same significance level. The lending rate coefficient of -0.3749 entails that a 1%

increase in lending rates causes productivity to reduce by approximately 37% and

vice versa.

Additionally, Electricity as was anticipated, also showed a strong positive correlation

with productivity at 5% significance level, therefore the null hypothesis is rejected at

the same significance level. Its positive coefficient of 0.304 entails that a 1% fall in

electricity supply to firms culminates into approximately a 30% fall in firm

productivity and vice versa. This supports the assertions of erratic electricity supply

as affecting growth in Zambia as observed by the IMF (2015) mission.

Similarly, Credit Granted to firms by banks has a significant positive correlation with

productivity at 1% significance level and the null hypothesis is thus rejected at the

same level. The positive coefficient of 0.868 implies that a 1% increase in credit

granted increases firm productivity by approximately 86%. Moreover, the R-Squared

produced a good result. Otherwise known as the coefficient of determination, the R-

Squared indicates the proportion of the dependent variable, in this case productivity,

that is explained by the independent variables. In this regard, the R-Squared

demonstrates how well the regression model used in the research fits the data points.

The chosen model gave an R-Squared of 0.9547 and adjusted R-Squared of 0.9424.

48 | P a g e

This entails that about 95.47% of the variations in SME productivity is explained by

the independent variables of this chosen regression model. This demonstrates the

strength of the chosen model. Accordingly, the regression model thus becomes:

𝒚𝑖 = 𝟔𝟒. 𝟔𝟕𝟒𝟗𝟒 − 𝟎. 𝟑𝟕𝟒𝟗𝟑𝟓𝟔𝑳𝑹𝑖 + 𝟎. 𝟑𝟎𝟒𝟕𝟖𝟔𝟒𝑬𝑳𝑖 + 𝟎. 𝟖𝟔𝟖𝟑𝟓𝟐𝟐𝑪𝑮𝑖 + 𝜺𝒊 (Equation 4-1)

Where y is productivity, 𝑳𝑹𝑖 is Lending Rates, 𝑬𝑳𝑖 is Electricity supplied and 𝑪𝑮𝑖 is

Credit Granted and εi is the error term. These empirical studies support research

findings by other scholars have emphasised the importance of access to finance and

the macroeconomic environment in which SMEs operate in supporting their growth

(Ayyagari, et al., 2011; Beck, 2007; Beck & Demirguc-Kunt, 2006). Furthermore, as

highlighted in the (Enterprise Surveys, 2013), among the major growth constraints

faced by SMEs, access to finance and electricity, ranked on top of the others. These

results empirically prove the causal link between lending rates, credit granted and

firm productivity. They also suggest a strong correlation between electricity usage

with firm productivity and growth. In summary, the regression results have

presented strong grounds to reject the null hypothesis and emphatically suggest a

high probability of a causal relationship between lending rates, credit granted,

electricity supply and SME growth in Zambia.

4.3. Discussion and Interpretation of the Results

As affirmed by the extensive literature in Chapter 2, Small and Medium Enterprises

are mostly influenced by factors in the macroeconomic environment in which they

operate. From infrastructure to deliberate policies, all these have a bearing on the

performance of firms, their success or failure. This study has revealed the

excruciating impact that lending rates have on firm growth and consequently that of

the overall economy.

49 | P a g e

Studies by Beck et al (2007) and Ayaggari et al (2006) emphasised the importance of

access to finance on SME growth. Mankiw (2016) presented interest rates theories

that showed the transmission effect of interest rates on overall economic activity

especially with regard to investment expenditures. Thus the negative effect of lending

rates on SME productivity as evidenced by this study agrees with existing empirical

research on SME growth especially with regards to the role of credit. This is because

credit granted is also negatively related to lending rates. Figure 4-3 highlights this

relationship.

Figure 4-3: Lending Rates and Credit Granted

Source: Author’s computations8 based on data from BOZ.

The African Development Bank, World Bank and many other development

institutions have realised the importance of the macroeconomic environment

especially policies and access to finance in supporting SME growth. Hence, they are

now more concerned with policy support interventions and strengthening institutions

that promote SME growth. Moreover, the IMF (2015) in their mission report on

8 Note that the Credit granted is in millions (‘000,000) of Zambian Kwacha

0

10

20

30

40

50

60

70

0 2 4 6 8 10 12 14 16

Credit grants vs Lending Rates

Lending Rates Credit Granted

50 | P a g e

Zambia noted that erratic electricity supply was adversely affecting overall growth. In

fact, erratic electricity supply is one of the major factors that was sighted as a

probable cause of Zambia’s poor economic performance between 2011 to 2015 and

will likely continue to be so for the 2016 – 2017 economic outlook. The findings of

this study are in line with these observations as they showed the positive effect of

electricity supply or usage with overall firm productivity.

4.4. Inferences from these Findings

Of all the above scenarios, the main objective that lending rates affect the growth of

Small and Medium Enterprises holds. Lending rates have also been proved to have a

negative effect on the credit granted by financial institutions. As lending rates

decreased, the amount of credit granted by financial institutions increased (see

Figure 8). This is probably because as lending rates increase, fewer people approach

Banks for credit due to the increased cost of borrowing. However, this argument

would hold more strongly if firms’ borrowings from non-bank financial institution and

other sources of funding increased during the same period, which is beyond the scope

of this study. Access to finance literature by Beck el al. (2008) reveals that very few

SMEs actually borrow from commercial banks and formal financial institutions. The

results in this study reveal more credit being granted to SMEs when lending rates are

lower than when they are higher presents a sensible case.

4.5. Lending Rates Across Countries

In ascertaining how lending rates in Zambia fare compared to other countries, Figure

9 presents the answer to this objective.

51 | P a g e

Figure 4-4: Lending Rates Across Countries

Source: Author’s Calculations using data from Enterprise Survey 2013

From Figure 4-4, a comparison of the trends in average lending rates across developed,

emerging and developing countries between 1996 to 2015 is presented. From this

graph, an appalling revelation emerges. Rich countries have the lowest lending rates

compared to the rest of the world with the United Kingdom leading at 0.5% for the

countries under review. Similarly, emerging countries of India, China, Mexico also

exhibited lower lending rates compared to poorer ones in Sub-Saharan Africa. Middle

income countries which include Botswana, Namibia and South Africa also showed

low interest rates compared to low income countries. In the last segment, developing

countries in Sub-Saharan Africa showed the highest lending rates of over 90% to18%

for Angola, 28% to 17% in Kenya, 19% to 22% for Uganda and 42% to 15% in Zambia

for the period under review. Thus, of all the countries under review, Zambia, Uganda

and Angola revealed the highest lending rates.

0.00

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60.00

80.00

100.00

120.00

Comparison of average Lending Rates across selected countries

1996 - 2001 2002 - 2007 2008 - 2012 2013 - 2015

52 | P a g e

4.6. Lending Rates and Investment Expenditure

The third objective that this dissertation sort to investigate is whether lowering the

lending rates improves SME expansion through increased investments in capital and

machinery. The study compared performance of SMEs across emerging and

developing countries on Sales Growth, Investment Growth and employment growth

for the 2010 – 2015 period with the lending rates data from figure 10. The Firms’

performance is highlighted in Figure 7 below.

Figure 4-5: SME Performance

Source: SME Finance Forum Database

By comparing the rates for both figure 6 and 7, both emerging and developing

countries showed increased investment growth during the period 2007 to 2013. Chile

and Botswana showed higher investment expenditure at around 76.2% for Chile and

67.7% for Botswana and both had low interest rates during this period of between

4% to 9% for both. Similarly, Zambia (34.6%) had more investment growth than

Philippines (28.7%) and India (24.9%), and just about the same growth with Mexico

(35%) although these countries had much lower lending rates than Zambia during

the same period. Same applies to Kenya (43.8%) and Tanzania (40%) while Uganda

-40

-20

0

20

40

60

80

100

Ch

ile

Ind

ia

Ch

ina

Ph

ilip

ines

Mex

ico

Vie

tnam

Bo

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ana

Sou

th A

fric

a

Tan

zan

ia

Ken

ya

Uga

nd

a

An

gola

Nig

eria

Zam

bia

2010 2014 2012 2015 2010 2015 2010 2007 2013 2013 2013 2013 2014 2013

SME Performance across countries

Sales growth Investment Growth Employment Growth

53 | P a g e

and Nigeria had lower investment growth. These results are peculiar and show lack

of correlation and provide an interesting area for future research. Therefore, these

results are inconclusive.

4.7. Conclusion

This chapter has presented the analysis and findings of the study using both the

regression and trend analysis. Using data from the Zambia Data Portal on

manufacturing firms in Zambia, the regression results revealed a significant impact

of lending rates on access to credit and SME productivity. Furthermore, electricity

was also found to positively impact firm productivity. The main findings are

consistent with the existing literature on the topic as highlighted in Chapter 2. Most

assumptions of the research have been substantiated thereby indicating the

suitability of the chosen model for the analysis. In so doing, this Chapter has

adequately addressed the three main objectives the research set out in Chapter 1.

Notwithstanding thereof, the results also revealed some baffling, counter-intuitive

findings which do not seem to fit with the existing literature. Perhaps the foreseen

data limitations and scope of the study could have warranted such results and

affected the definiteness of the model. However, these noted nonconformities do

indeed present an interesting case for future investigations.

54 | P a g e

CHAPTER 5 - CONCLUSION AND POLICY IMPLICATIONS

This chapter concludes the study by summarizing the objectives, main conclusions

as well as policy implications of the results. The chapter also addresses the

limitations of the research and areas of future research. In linking theory and

research, this study submits a compelling case that developing countries’ policy

makers should consider when aiming for overall macroeconomic targets. In so doing,

the fate of the Small and Medium Enterprises which are the building blocks of the

economy can be safeguarded.

5.1. Summary

This dissertation set out to investigate the impact of lending rates on the growth of

small and medium enterprises. The research contributes to existing empirical

knowledge on SME growth and the broader impact of financial policies on other

sectors of the economy than the originally intended targets. Small and medium

enterprises have been identified as engines of growth and building blocks of the bigger

economy. However, the macroeconomic policies implemented by policy makers

especially those of increasing lending rates to tackle inflation and possibly attract

foreign capital have had detrimental effects on the growth of the small and medium

enterprise industry in Zambia. This has negatively affected their ability to access

credit as it raised the cost of borrowing. The situation has been exacerbated by the

erratic supply of electricity which has been the norm in Zambia due to the main hydro

power generation corporations operating below capacity thereby failing to

consistently supply energy to the productive sector, of which the Small and Medium

Enterprises require a good deal of it.

An extensive wealth of literature and empirical research has emerged on SMEs

especially with regards to constraints to their growth as well as their contributions to

55 | P a g e

the economy. In many developing countries development agenda, Small and Medium

enterprise had initially been side-lined in the development with more preference given

to Large Scale multinational companies and state back agricultural industries. As a

result, this created a gap in the processing and other small scale manufacturing

industries to link the two industries. Although small and medium enterprises have

continued to exist for some time, the lack of deliberate policy support to see them

grow and expand into large scale multinational industries had been a case of great

concern.

In this disposition the study sought to examine three objectives. Firstly, it examined

the impact of Lending rates on SME Productivity and how this influences their Access

to finance and consequently their growth. The second objective was to determine how

lending rates in Zambia fare among similar other countries around the world. This

sought to establish the performance of firms in countries with low rates compared to

those with high interest rates. Thirdly, the study examined cases to ascertain whether

countries with lower lending rates saw increased expenditure on investment

expenditure on capital and machinery.

This study used the Ministry of Commerce’s definition of SMEs in order to categorise

enterprises in terms expansion and commercialisation. Using data from the Bank of

Zambia, Central Statistical Office and Zambia Data portal as well as World Bank on

the manufacturing industry, trends in lending rates and productivity have been

established and presented. Additionally, a selection of a range of variables based on

extensive literature review of SME growth and its underlying factors. As observed by

the Enterprise Survey (2015), the significant ones were Electricity, Access to finance,

activities of the informal sector, Tax rates and Tax administration.

56 | P a g e

5.2. Research Conclusions and Limitations of the Findings

The findings from the empirical analysis endorse the hypothesis that high lending

rates have a negative effect on SME growth. Likewise, Electricity supply has also been

proved to have a profound effect of firm productivity in Zambia with high output and

productivity being associated with high electricity usage or availability. The

assumption that lending rates influence the ability access credit have also been

confirmed.

Hence from this dissertation several conclusions can be drawn. The impact of lending

rates on SME growth was estimated using the regression model as the expected

variation in firm Productivity given a change in lending rates. Despite significant and

conclusive results from the regression model, the scanty nature of the data as well

as indices used may have limited the accuracy of the conclusions, although the

assumed errors are not expected to significantly alter the findings.

From the results, it has been revealed that the determinants of SME growth also

interrelate with each other, as was the case with lending rates influencing the mount

of credit granted. It may therefore be assumed or deduced that lending rates also be

interrelated with many of the other factors that affect SME growth. This study has

nonetheless proved the overall assumptions on lending rates and their impact on the

growth of SMEs and thus contributes to existing literature on the subject.

5.3. Policy Implications

Ever since the Structural Adjustment era of the early 1990s, the economic disposition

of Zambia has always favoured large scale foreign businesses over Small and Medium

Enterprises (see Chapter 1 and 2). Even today, the current industrial policies are

tailored towards attracting foreign investment and large companies with little policy

direction deliberately targeted at SMEs. As such, the domestic industrial base

57 | P a g e

propelled by these SMEs has tremendously suffered. The country now has a missing

manufacturing and processing base to support the primary industries, whose output

is supposed to feed into the large scale industries as inputs. From having a strong

industrial base under the deliberate import substitution policies of the 1960s to the

1990s, Zambia today depends on imports even for basic everyday commodities.

Important implications can be drawn from these findings. In undertaking

stabilisation measures such as curbing inflation, exchange rate volatility as well as

regulating the growth of money supply in the economy, policy makers should examine

the impact of such policies in totality especially with regards to the impacts on the

smaller but significant players in the economy such as SMEs. As has been revealed,

policies that affect these players eventually affect the entire economy (Mbao, et al.,

2014). A logical inference for policy making purposes is that financial policies and

conditions need to be adjusted and transformed to suit the industrial base and its

needs in Zambia.

The low growth of the SME sector has been attributed to a number of factors but

access to credit which is hampered by high lending rates as well as erratic electricity

supply has had profound impacts. Although policy makers have been preaching

economic diversification, this cannot be achieved without the full participation of

Small and Medium Enterprises, hence reiterating the need for financial and economic

policies that directly aim to boost their growth. Business incubation programmes, as

are common in East Africa, Financial management training and international trading

literacy program supported by policy makers could go a long way in creating capacity

and exploring cross border opportunities (Mbao, et al., 2014). Likewise, state backed

credit guarantee schemes could help SMEs acquire machinery and equipment for

their production needs.

58 | P a g e

Furthermore, in order attract large enterprises, the country needs to have a vibrant

SME sector that produces products that feed into these corporations otherwise it

would not be a viable investment destination. Deliberate policies such as lower

borrowing costs, tax holidays and other incentives, Multi-facility Economic Zones

could be extended to the SME sector as well to make it more competitive and enable

them to acquire the necessary capital and equipment to boost their output. Providing

a conducive infrastructural environment especially in terms of improving electricity

supply and transport systems would further provide multiplier effects of productivity.

One of the strategies the Asian tigers implemented to surpass emerging African

Countries in the 1970s was that while African nations including Zambia were

abandoning the import substitution policies through privatisation, Asian Tigers

continued with them and sourced foreign capital which boosted their manufacturing

base. Because of this large manufacturing base, they are the favourites to attract

large scale production companies. African countries thus have to invest in their local

manufacturing base and industries if they are to attain meaningful development.

5.4. Areas for Further Research

Although this dissertation has addressed the lending rates impact on SME growth, a

number of areas in the study of SMEs still require further exploring. The study

explored lending rates on SME growth in the context of formal borrowing. However,

most SMEs source their financing from the informal sources such as family, friends

and money lenders and Non-Bank Financial institutions most of whom have different

ways of determining their lending rates. Hence, further research in this direction to

understand how they determine their rates, and to examine whether adverse

conditions of the formal financial institutions cause more SMEs to approach the

informal sources of finance would be an interesting undertaking.

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Furthermore, it would be stimulating to undertake an investigation into actual use

of the financing that SMEs acquire from formal financial institutions to ascertain

whether a policy could be instigated to ease their operations.

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Bibliography

Cull, R., Demirgüç-Kunt , A. & Morduch, J. (2008). Microfinance Meets the Market.

Washington DC: World Bank - Development Research Group.

Andren, T. (2007). Econometics. 1 ed. Frederiksberg : Ventus Publishing ApS.

Ayyagari, M., Beck, T. & Demirguc-Kunt, A. (2007). Small and Medium Enterprises

Across the Globe. Washington DC: The World Bank Development Research Group.

Ayyagari, M., Demirgüç-Kunt, A. & Maksimovic, V. (2006). “How Important Are

Financing Constraints? The Role of Finance in the Business Environment.”

Washington: World Bank Policy Research.

Ayyagari, M., Demirguc-Kunt, A. & Maksimovic, V. (2011). Small vs. Young Firms

Across the World: Contribution to Employment, Job Creation, and Growth.

Washington DC: World Bank.

Bank of Georgia (2010). Monetary Policy Transmission Mechanism. [Online]

Available at: https://www.nbg.gov.ge/index.php?m=541&lng=eng

[Accessed 27 August 2016].

Bank of Zambia (2010). Statistical Report. [Online]

Available at:

http://www.boz.zm/StatisticalReview/Quarterly%20Review%20Report%20-

%20%20Q1%202010%20Tables%20II.pdf

[Accessed 23 August 2016].

Bank of Zambia (2013). Economic Statistics Fortnightly. [Online]

Available at: http://www.boz.zm/Publishing/121/Statistics%20Fortnightly%20-

2013%20Vol.%2020%20No.%2022.pdf

[Accessed 20 August 2016].

61 | P a g e

Beck, T. (2007). Financial Constraints of SMEs: Evidence, Determinats and Solutions.

Washington DC: World Bank.

Beck, T. & Demirguc-Kunt, A. (2006). Small and Medium-Size Enterprises: Access to

Finance as a Growth Constraint. Journal of Banking & Finance, 30(11), pp. 2931-

2943.

Beck, T., Demirguc-Kunt, A. & Levine, R. (2005). SMEs, Growth, and Poverty: Cross-

Country Evidence. Journal of Economic Growth, 10(3), pp. 199-229.

Beck, T., Demirguc-Kunt, A. & Maksimovic, V. (2006). Financial and Legal

Constraints to Firm Growth - Does Size Matter? Washington: World Bank.

Beck, T., Demirgüç-Kunt, A. & Maksimovic, V. (2008). Financing Patterns Around

the World: Are Small Firms Different?. Journal of Financial Economics, 89(3), p. 467–

487.

Begg, D. K. (2014). Economics. 11 ed. New York: Maidenhead : McGraw-Hill.

Bernanke, B. S. & Gertler, M. (1995). Inside the Black Box: The Credit Channel of

Monetary Policy Transmission. NBER Working Paper No. 5146, s.n.

Biggam, J. (2011). Succeeding With Your Master’s Dissertation: A Step-By-Step

Handbook. 1st ed. Berkshire: McGraw-Hill Education.

Boivin, J., Kiley, M. T. & Mishkin, F. S. (2010). How Has the Monetary Transmission

Mechanism Evolved Over Time? Washington D.C., National Bureau of Economic

Research.

Bougheas, S., Mizen, P. & Yalcin, C. (2006). Access to External Finance: Theory and

Evidence on the Impact of Monetary Policy and Firm-Specific Characteristics. Journal

of Banking & Finance, 30(1), pp. 199-227.

62 | P a g e

BOZ (2016). Bank of Zambia. [Online]

Available at:

http://www.boz.zm/Publishing/113/113_Statistics%20Fortnghtly%20-

2016%20Vol%2023%20No.%2017.pdf

[Accessed 15 August 2016].

Brownbridge, M. (1998). Financial Policies and the Banking System in Zambia. In:

Banking in Africa. Asmara: African World Press, Inc, pp. 143 - 160.

Calice, P., Chando, V. M. & Sekioua, S. (2012). Bank Financing to Small and

Medium Enterprises in East Africa: Findings of a Survey in Kenya, Tanzania, Uganda

and Zambia. Tunis: African Development Bank.

Caner, S. (2014). The Role of Small and Medium Size Enterprises in Economic

Development. Moscow, HSE Conference.

Central Statistical Office (2016). National Statistics. [Online]

Available at: http://www.zamstats.gov.zm/

[Accessed 16 June 2016].

Enterprise Surveys (2013). Enterprise Surveys. (http://www.enterprisesurveys.org),

The World Bank.. [Online]

Available at: http://www.enterprisesurveys.org

European Union (2012). What is an SME?. [Online]

Available at: http://ec.europa.eu/growth/smes/business-friendly-

environment/sme-definition_en

[Accessed 18 July 2016].

Fjose, S., Grünfeld, L. A. & Green, C. (2010). SMEs and Growth in Sub-Saharan

Africa: Identifying SME Roles and Obstacles to SME Growth. Oslo: MENON Business

Economics .

63 | P a g e

Gibson, T. & Vaart, H. J. (2008). Defining SMEs: A Less Imperfect Way of Defining

Small and Medium Enterprises in Developing Countries. [Online]

Available at: http://seaf.com/wp-content/uploads/2014/10/Defining-SMEs-

September-20081.pdf

[Accessed 3 August 2016].

IMF (2015). International Monetary Fund. [Online]

Available at: http://www.imf.org/external/pubs/ft/scr/2015/cr15153.pdf

[Accessed 11 August 2016].

IMF (2016). International Monetary Fund. [Online]

Available at: http://www.imf.org/external/np/sec/pr/2016/pr16120.htm

[Accessed 28 August 2016].

Kashyap, A. K. & Stein, J. C. (1994). The Impact of Monetary Policy on Bank Balance

Sheets. Carnegie-Rochester Conference Series on Public Policy , Volume 42, pp. 151-

195.

Levine, R. (2005). Finance and Growth: Theory and Evidence. Handbook of Economic

Growth, 1, Part A(1), pp. 865-934.

Liedholm, C. & Mead, D. C. (1993). “The Structure and Growth of Microenterprise in

Southern and Eastern Africa: Evidence from Recent Surveys.”. Working Paper No.

36.: GEMINI.

LUSE (2016). Lusaka Stock Exchange. [Online]

Available at: http://www.luse.co.zm/

[Accessed 11 August 2016].

Mankiw, G. N. (2016). Macroeconomics. 9th ed. New York: Worth Publishers.

64 | P a g e

Mbao, F. Z., Kapembwa, C., Mooka, O. & Rasmussen, T. a. S. J. (2014).

Determinants of Bank Lending Rates in Zambia: A Balance Sheet Approach. Lusaka:

Bank of Zambia.

McPherson, M. A. (1992). “Growth and Survival of Small Southern African Firms."

Michigan: East Lansing.

McPherson, M. A. (1992). Growth of Micro and Small Enterprises in Southern Africa.

Journal of Development Economics , Volume 48, pp. 253-277.

Mkandawire, T. & Soludo, C. C. (2002). African Voices On Structural Adjustment: A

Companion to Our Continent, Our Future. Ottawa: International Development

Research Centre.

Mumbi, P. C. & Kafula, L. (2011). The Effects of Fiscal Policy on the Conduct and

Transmission Mechanism of Monetary Molicy in Zambia. Lusaka: COMESA

MONETARY INSTITUTE.

Mwenda, A. and Mutoti, N. (2011). Financial Sector Reforms, Bank Performance and

Economic Growth: Evidence from Zambia. African Development Review, 23(1), pp. 60-

74.

Taylor, J. B., Solow, R. M. & Friedman, B. M. (1997). Inflation, Unemployment and

Monetary Policy. 1st ed. London: MIT Press.

Thorsten, B. (2007). Financing Constraints of SMEs in Developing Countries:

Evidence, Determinants and Solutions. [Online]

Available at:

http://siteresources.worldbank.org/DEC/Resources/Financing_Constraints_of_SM

Es.pdf

[Accessed 8 August 2016].

65 | P a g e

Varian, H. R. (2010). Intermediate Microeconomics: A Modern Approach. 8th ed. New

York: W. W. Norton & Company, Inc..

World Bank (2016). Country Overview Zambia. [Online]

Available at: http://www.worldbank.org/en/country/zambia/overview

[Accessed 27 August 2016].

Zambia Data Portal (2016). Industrial Productivity. [Online]

Available at: http://zambia.africadata.org/en/DataAnalysis

[Accessed 26 July 2016].