measuring the investment gap and its financing

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Measuring the Investment Gap and its Financing Requirements for Irish SMEs

DATE08/03/2018

VENUEDoF Conference

AUTHORSConor O’Toole, Martina Lawless, Rachel Slaymaker

This research is being completed under the joint ESRI/Department of Finance research programme on Banking.

www.esri.ie @ESRIDublin #ESRIevents #ESRIpublications@ESRIDublin #ESRIevents #ESRIpublications www.esri.ie2 12 March 2018

Introduction

• Since the financial crisis, investment in fixed assets globally has been subdued

• Ireland has been no exception and previous research highlights credit access as a limiting factor

• However, no research has looked at whether an “investment gap” exists specifically in Ireland

• Low investment is not in itself evidence of an investment gap

• This paper asks the question:• Is there an investment gap in Ireland for SMEs?• If so, to what extent do financial factors explain any

gap?


Characterising Investment Phases


Aggregate Investment in Ireland

Modified Investment - Four Quarter Rolling Sum

0

10000

20000

30000

40000

50000

60000

OverallConstructionOther

€mn


Aggregate Investment in Ireland

Modified Investment - Four Quarter Rolling Sum

0

10000

20000

30000

40000

50000

60000

OverallConstructionOther

Sufficient?

€mn

Too much? Too little? Hmm?


Modelling the Investment Gap

Investment = f(Measure of Fundamentals, Controls)

Gap = Actual - Predicted Investment

Investment = f(Measure of Fundamentals, Financial Factors, Cost of Credit, Controls)


Data and Micro Data Method

• Use DoF Credit Demand Survey

• Contains information on financing factors

• Includes a variable measuring fixed asset investment

• Data includes financial factors as well as measures of firm performance (turnover growth, employment growth, profitability)

• Provides a source of data to estimate investment equations with financial factors


Some Summary Statistics

Share of Companies Investing Share of Companies Investing by Size

• Some slowdown in investment evident in 2016• Mainly driven by larger SMEs• Evident across all sectors and age groups


More Summary Statistics

Total Investment Investment by Sector

• Some slowdown in investment evident in 2016• Mainly driven by larger SMEs• Evident across all sectors and age groups

0

1.00e+07

2.00e+07

3.00e+07

4.00e+07

5.00e+07

Eu

ros

2013

2014

2015

2016

Construction Manufacturing

Wholesale & Retail Professional & Scientific

Other


Modelling the Gap

• First task, modelling the gap:• Estimate an equation with “fundamental factors”• Get model based predictions• Calculate gap

• We use a model that is “two staged”1. Stage 1: Does a firm invest?2. Stage 2: Level of investment

• Fundamental factors include:• Size, age, loan default, turnover growth, employment

growth, exporting, profitability, local economic conditions (NUTS3 level unemployment rates), time factors


Estimates of the Gap

Actual Average Investment and Model Prediction

Investment Gap (Actual – Predicted)


Methodologies to Estimate the Impact of Financial Market Imperfections

Key Question – To what extent are financial market imperfections impacting investment gap?

• Use three different methods to assess

Method Overview Description

Method 1 Model Based Append financial factors to baseline specification and

compare difference in predicted values

Method 2 EIF Ex Ante

Guidelines

Apply the loan-financing gap estimation methodology

from the EIF Ex-Ante Guidelines

Method 3 External Financing

Shares

Use the share of investment funding by external finance

from other countries or historical data for Ireland


Model Based Financial Factors

Factor Financial Channel Measurement Intuition

Interest rate Cost of financing Higher interest rates should lower investment

Credit access Applications for

finance and their

success

We split the sample into borrowers who had

successfully applied for credit, rejected borrowers,

discouraged borrowers and those that did not apply.

Investment should be higher for successful applicants.

Lending conditions Access to, demand

for, finance

We include a variable for whether or not firms believe

the banks are lending. If this lowers credit demand, it

should have a negative association with investment.

No collateral

posted

Access to finance We distinguish between those firms who applied for

financing and posted specific collateral and all other

firms as a proxy for the collateral channel.

Debt to turnover

ratio

Debt overhang This indicator reflects the degree to which debt

sustainability impacts investment.

Total debt Indebtedness This measure of free collateral can capture the extent

to which firms can provide collateral to access external

financing.


Summary of Financial Frictions Shares

2014 2015 2016

Method 1: Model Based Median (Preferred) 9% 10% 17%

Method 2: EIF Method 17% 15% 18%

Method 3a: External Financing Share - EU 12% 12% 12%

• Findings from all models summarised below• Figures present the share of the investment gap explained by

financing frictions• Further detail available in the technical paper


Illustration for Whole Economy

Provide an illustration of national magnitude • Given current data on capital formation, it is very challenging to understand

national domestic firm investment

• Nearly impossible to triangulate our SME survey investment figure

• We provide an illustrative example

• Method uses CSO data to “scale up” the survey to provide a national figure

• Use 2014, 2015 Business Demography Data from CSO to get a scaling factor for each sector/size class and apply these scales

• Large health warning associated with this illustration• National statistics do not provide an accurate SME investment figure for indigenous

companies

• Multinational activity in national sources induces very large volatility which makes benchmarking nearly impossible

• Trend in our data has a 63 per cent correlation coefficient with capital acquisitions in the manufacturing of food and beverages sector


Aggregated Figures

All €mn 2014 2015 2016

Sample Investment 402 331 254

Aggregated Investment 4,036 3,964 3,063

Gap (Share) -49% -41% -34%

Predicted Aggregate 6,009 5,602 4,110

Gap Level 1,973 1,638 1,046

Modified GFCF (Nominal) 31,731 39,726 44,893

Gap as % of Modified GFCF 6% 4% 2%

Share of Gap Explained by Finance

Method 1 9% 10% 17%

Method 2 17% 15% 18%

Method 3 12% 12% 12%

Financing Value of Gap

Method 1 181 168 180

Method 2 337 250 192

Method 3a 236 196 125


Conclusions and Policy Implications

A number of findings emerge:• Clear evidence that actual investment is below what would be expected given

how companies are currently performing• The magnitude of this “investment gap” is economically meaningful and is

estimated to be just over 30 per cent in 2016 relative to SMEs actual investment• Using three different methodologies, we estimate that financial factors explain

between 12 per cent and 18 per cent of the investment gap in 2016. • More specifically, we find investment is negatively related to the interest rate,

lowered by credit rationing and borrower discouragement and increased where firms have been able to post tangible collateral

• In 2016, illustrative example suggests gap is 2 per cent of Modified GFCF• Would be great to get an SME investment figure from CSO to benchmarkPolicy implications:

• Policies to reduce cost of credit warranted and can provide additionality to investment activity

• Clear link to collateral availability so that policy instruments targeted at improving collateral available through risk sharing or other guarantee schemes could be worthwhile and help boost investment.


APPENDIX


Investment Fundamentals Regression

(1) Investment probability (2) Ln(Investment level)

(margins)

Size-small 0.139*** 1.055***

(0.009) (0.085)

Size-medium 0.328*** 2.200***

(0.013) (0.095)

Default -0.033 -0.252

(0.020) (0.175)

Age 0.000 0.005***

(0.000) (0.001)

Turnover change 0.002*** 0.005**

(0.000) (0.002)

Employee change 0.002*** 0.009***

(0.000) (0.003)

Export 0.120*** 0.365***

(0.012) (0.067)

Profitability- profit 0.070*** 0.215***

(0.010) (0.076)

Profitability- loss 0.003 0.075

(0.013) (0.112)

Unemployment -0.022*** 0.001

(0.006) (0.039)

Wave dummies Yes Yes

Region dummies Yes Yes

Sector dummies Yes Yes

N 12,149 12,149


Financial Factors in Model

(1) (2)

Investment Decision (Yes, No) Investment Level (in

Logs)

No collateral posted -0.016 -0.281***

(0.018) (0.100)

Credit access - rejected -0.070*** 0.156

(0.023) (0.140)

Credit access - discouraged borrower -0.071*** -0.337**

(0.022) (0.167)

Credit access – did not apply -0.065*** -0.189**

(0.013) (0.075)

Tight lending conditions -0.028*** -0.056

(0.010) (0.070)

DTI lag -0.022*** 0.044

(0.009) (0.052)

lnD lag 0.005*** 0.014***

(0.001) (0.005)

Interest rate -0.005*** -0.006

(0.002) (0.011)

Wave dummies Yes Yes

Region dummies Yes Yes

Sector dummies Yes Yes

Fundamental Factors Yes Yes

N 11,144 11,144

measuring the investment gap and its financing

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