Investment Financing and Financial Development: Evidence ...Investment Financing and Financial...

Introduction Modelling Investment Data and Econometrics Results Conclusions and Policy Implications Annex

Investment Financing and Financial

Development: Evidence from Viet Nam

Conference on Understanding Banks in Emerging Markets

(CEPR, EBRD, EBC, RoF)

Conor M. O’Toole1 Carol Newman 2

1Economic Analysis Division

Economic and Social Research Institute

2Department of Economics

Trinity College Dublin


So many banks in Ha Noi...


1 Introduction

Why Viet Nam?

2 Modelling Investment

Investment Framework

Empirical Model with Financial Development

3 Data and Econometrics

Data

Econometric Methodology

4 Results

Main Results

Additional Findings and Robustness Checks

5 Conclusions and Policy Implications

6 Annex


Extensive literature concerning “Does finance cause growth?”

King & Levine (1993), Honohan and Beck (2007), Beck (2013),

Beck and Levine (2004)

Policy prescriptions for developing economies include measures

to facilitate financial reform and development

Benefits of financial development (Levine, 2005)

Increased and more efficient investment

Better monitoring and corporate governance

Improved risk management

Trade facilitation


RQ :Does financial development reduce firm financing

constraints?

Build on Rajan and Zingales (1998), Love (2003), Love and Zicchino

(2006), Guariglia and Poncet (2008), Beck et al. (2008)

Complementary to research on financial reform and access to

finance

Galindo et al. (2007), Abiad et al. (2008), Haramillo et al. (1996),

Barajas et al. (2000), Gelos and Werner (2002)

Complement work on SMEs and financing constraints in

development

Beck and Demirguc-Kunt (2006a,b), Ayyagari et al (2007),

Beck et al. (2008)


Innovations and contributions of this paper1 Firm level data on non-listed SMEs in industry and

services;

2 Direct data on how firms financed investment;

3 Within country variation in financial development; and

4 Definition of financial development V

(1) Financial depth

(2) State involvement

(3) Market financing


Why Viet Nam?

Fast growing, realigning economy with considerable product and capital market

liberalisation (WTO accession 2007)

Economic Growth Investment

Source: General Statistics Office, Vietnam


Why Viet Nam?

Major changes to financial operating environment evident at macro level

Financial liberalisation Domestic credit to private sector (as % of GDP)

Banking sector concentration Expansion of monetary base

Source: Beck et al. (2000, 2009); Cihak et al. (2013) World Bank WDI; Abiad et al (2010).


Investment Framework

Modelling investment

Neoclassical Q model of finance:

(IK

)it

= α0 +1a

Qi,t−1 + ci + λt + θjt + εit

Accelerator model:

(IK

)it

= β0 + β2∆sit + β3∆sit−1 + ci + λt + θjt + εit

Financing constraints: Cash flow? Cash stock?

Direct measure: IFit =(

IFIF+ExF

)it

(IK

)it

= α + βQQi,t−1 + βIFIFi,t−1 + ci + ηt + λj + εit

A-priori expectations: βQ > 0 βIF > 0


Empirical Model with Financial Development

Financial Development - Decomposed

1 Financial depth

1 Business credit to private sector as percent of industrial output,

FinDepthpt

2 State involvement

1 SOE share of total loans, (LS)pt

2 SOE share of loans to SOE share of output,(

LSGDPS

)pt

3 Market financing of investment

1 % of inv lending by commercial banks to % of inv lending by state,(CLGL

)pt(

IK

)it

= α + βQQi,t−1 + βIFIFi,t−1 + βOFDOFDp,t−1 + φIFOFD (IF ·OFD)p,t−1

+ ci + ηt + λj + ρp + ψpj + εit

A-priori expectationsFinancial depth V φIFOFD < 0

State involvement V φIFOFD > 0

Market financing of investment V φIFOFD < 0


Data

Data

Vietnamese Enterprise Survey (VES) over the period

2002-2008

Data prepared and cleaned under DANIDA funded project

Surveys all firms > 30 employees with a representative

sample of firms < 30 employees

Covers all sectors of the economy V Including industry and

market services

Data includes all 64 rural and urban provinces

Provincial measures of FD aggregated from firm data


Data

Summary Statistics

VARIABLE N Mean St DevIK 43,138 .927 1.489

IF 44,153 .691 .404(CFK

)37,867 .116 .312(

SK

)44,153 4.716 4.651(P

K

)44,153 .076 .405

FinDepth 44,153 .269 .136(LSLT

)44,153 .416 .188(

LSGDPS

)44,153 1.245 .447(

CLGL

)42,817 134.804 228.215

Private 44,153 .784 .411

State 44,153 .128 .334

Joint Venture 44,153 .023 .150

Solely Foreign 44,153 .065 .247

Services 44,153 .388 .487

SME 44,153 .872 .334


Data

Figure: Mean of Provincial Financial Development Indicators

Private business credit to industrial output SOE share of loans

SOE loan share to SOE output share Commercial to state loans

Source: Authors calculation using Vietnamese Enterprise Survey data


Econometric Methodology

A number of important econometric issues are raised

Measuring Q V Panel VAR on firm fundamentalsxit = Axi,t−1 + κi + γt + uit

qit =(c′[I− δA]−1δA

)xit

VAR includes mvpk and CF/K ratio

Estimate using System GMM (Holtz-Eakin et al. (1988))

Further considerationsErrors-in-Variables and endogeneity

Firm level heterogeneity

Spatial and temporal serial correlation in errors

Choosen methodologyDifference GMM (Arellano & Bond (1991)) with Helmert

transformation (Arellano & Bover (1995))

Cluster robust standard errors

Exogeneity condition for instruments:

E(εitXi,t−s) = 0∀s > 1 (1)


Main Results

Table: GMM Investment Equation Estimates - All Firms

Constraint Financial Depth State Involvement Market Financing Overall

Dep VarIit

Ki,t−1(1) (2) (3) (4) (5) (6) (7) (8) (9) 10

Qi,t−1 0.110*** 0.110*** 0.109*** 0.109*** 0.109*** 0.110*** 0.110*** 0.111*** 0.111*** 0.111***

(0.011) (0.011) (0.011) (0.011) (0.011) (0.011) (0.011) (0.012) (0.012) (0.012)

IFi,t−1 0.048*** 0.050*** 0.013 0.046*** 0.025 0.048*** 0.056*** 0.062*** 0.034* 0.026

(0.015) (0.015) (0.017) (0.015) (0.016) (0.015) (0.016) (0.017) (0.018) (0.019)

FinDepthp,t−1 -0.350** -0.364** -0.593***

(0.147) (0.147) (0.158)

IFi,t−1 × FinDepthp,t−1 -0.827*** -0.645***

(0.182) (0.212)

(LS )p,t−1 0.546*** 0.563***

(0.072) (0.072)

IFi,t−1× (LS )p,t−1 0.611***

(0.148)(LS

GDPS

)p,t−1

0.064** 0.069** 0.053

(0.031) (0.031) (0.033)

IFi,t−1×(

LSGDPS

)p,t−1

0.147** 0.223***

(0.062) (0.066)(CLGL

)p,t−1

-0.000 -0.000 0.000

(0.000) (0.000) (0.000)

IFi,t−1 ×(

CLGL

)p,t−1

-0.001*** -0.000**

(0.000) (0.000)

Sargan/Hansen J (p-value) 0.446/0.462 0.457/0.469 0.436/0.449 0.392/0.384 0.364/0.352 0.449/0.463 0.438/0.450 0.804/0.771 0.820/0.791 0.798/0.762

Res AR(2) (p-value) 0.410 0.419 0.428 0.450 0.507 0.399 0.409 0.573 0.553 0.588

n 38,912 38,912 38,912 38,912 38,912 38,912 38,912 35,214 35,214 35,214

* p<0.10, ** p<0.05, *** p<0.01


Main Results

Overall Marginal Effects

∂I∂IF

= 0+(−0.645) ·FinDepth+(0.223) ·(

LS

GDPS

)+(−0.0001)

(CLGL

)

Year Overall Marginal Effect

2002 .051***

2004 .028***

2006 -.008

2008 -.066***

Standard errors calculated using bootstrap methods on MF distribution

* p<0.10, ** p<0.05, *** p<0.01



Test if effects are heterogeneous across firms

Define an indicator variable for:

1. SMEs 2 .Foreign firms 3. Market services

Interact with all main variables

Test for robustness using cash flow - investment

sensitivities and alternative clustering



Table: GMM Investment Equation Estimates - Domestic Firms by Size Category

(1) (2) (3) (4)(IFTF

)t−1

0.023 0.001 0.012 0.016

(0.023) (0.027) (0.024) (0.025)(IFTF

)t−1

× M 0.053* 0.095*** 0.062* 0.056*

(0.031) (0.036) (0.032) (0.034)(IFTF

)t−1

× S 0.019 -0.035 -0.013 0.038

(0.031) (0.037) (0.034) (0.033)(IFTF

)t−1

× FinDeptht−1 -0.073

(0.271)(IFTF

)t−1

× M × FinDeptht−1 0.541

(0.385)(IFTF

)t−1

× S × FinDeptht−1 -1.589***

(0.401)(IFTF

)t−1

×(

LSLT

)t−1

0.091

(0.258)(IFTF

)t−1

×M ×(

LSLT

)t−1

-0.132

(0.360)(IFTF

)t−1

×S ×(

LSLT

)t−1

0.896***

(0.341)(IFTF

)t−1

×(

LSGDPS

)t−1

-0.077

(0.103)(IFTF

)t−1

×M ×(

LSGDPS

)t−1

0.062

(0.140)(IFTF

)t−1

×S ×(

LSGDPS

)t−1

0.353***

(0.136)

Sargan test (p-value) 0.450 0.441 0.358 0.427

Hansens J (p-value) 0.465 0.455 0.346 0.437

Res AR(2) (p-value) 0.415 0.431 0.509 0.418

n 38,912 38,912 38,912 38,912

* p<0.10, ** p<0.05, *** p<0.01



Table: GMM Investment Equation Estimates - Domestic Firms by Size Category

(1) (2) (3) (4) (5) (6)(IFTF

)t−1

0.023 0.001 0.012 0.016 0.024 0.036

(0.023) (0.027) (0.024) (0.025) (0.024) (0.029)(IFTF

)t−1

× M 0.053* 0.095*** 0.062* 0.056* 0.055* 0.066*

(0.031) (0.036) (0.032) (0.034) (0.031) (0.039)(IFTF

)t−1

× S 0.019 -0.035 -0.013 0.038 0.015 -0.038

(0.031) (0.037) (0.034) (0.033) (0.031) (0.040)(IFTF

)t−1

×(

CLGL

)t−1

0.000

(0.000)(IFTF

)t−1

×M ×(

CLGL

)t−1

0.000

(0.000)(IFTF

)t−1

×S ×(

CLGL

)t−1

-0.001***

(0.000)

Sargan test (p-value) 0.594 0.505 0.435 0.473 0.325 0.836

Hansens J (p-value) 0.691 0.532 0.445 0.496 0.390 0.814

Res AR(2) (p-value) 0.401 0.476 0.451 0.372 0.294 0.629

n 38,912 38,912 38,912 38,912 38,283 35,214

* p<0.10, ** p<0.05, *** p<0.01



Effects heterogeneous across firms

SMEs Foreign firms

⇒ FD ⇓ financing constraints for small firms ⇒ No effect of FD, use IF

⇒ No effect for medium firms ⇒ Evidence that FOR and SOEs

don’t compete for finance

Services

⇒ Less constrained

⇒ FD stronger ⇓ financing constraints

⇒ Main beneficiaries



Table: GMM Estimates - All Firms - Q Model(

IK

)t

Constraint Financial Depth State Interventionism Market Financing Overall

Qt−1 0.083*** 0.032*** 0.023** 0.028*** 0.036*** 0.041***

(0.023) (0.010) (0.010) (0.009) (0.013) (0.011)(CFK

)t

0.368*** 0.007 0.180* 0.168 0.185** 0.086

(0.078) (0.103) (0.104) (0.119) (0.093) (0.122)

FinDeptht−1 -0.712*** -1.041***

(0.169) (0.196)(CFK

)t×FinDeptht−1 -2.099* -3.499***

(1.209) (1.076)(LSLT

)t−1

-0.595***

(0.081)(CFK

)t×

(LSLT

)t−1

0.145

(1.210)(LS

GDPS

)t−1

-0.097*** -0.108***

(0.030) (0.034)(CFK

)t×

(LS

GDPS

)t−1

-0.557 1.209***

(0.713) (0.211)(CLGL

)t−1

0.001*** 0.001***

(0.000) (0.000)(CFK

)t×

(CLGL

)t−1

-0.001*** -0.001*

(0.000) (0.000)


Hansens J (p-value) 0.10 0.08 0.20 0.12 0.18 0.76

Res AR(1) (p-value) 0.0 0.0 0.0 0.0 0.0 0.0

Res AR(2) (p-value) 0.73 0.74 0.85 0.99 0.96 0.61

Time/Province/Sector Dummies Yes Yes Yes Yes Yes Yes

Sector-Province Dummies Yes Yes Yes Yes Yes Yes

n 51,871 42,517 52,482 52,482 45,356 38,121

* p<0.10, ** p<0.05, *** p<0.01

All estimates are robust to heteroskedasticity and clustered at the firm level

Instruments are lagged CF/K, sales to capital dated t − 3 and deeper,

as well as lags of variables in main equation where correct


ConclusionsClear evidence that financial development reduces financing constraints in Vietnam

Constraints are:

1 Decreasing in financial depth

2 Increasing in the use of finance by SOEs

3 Decreasing in the degree of loans allocated on market terms

Distributional impacts are evident with small firms and service firms benefiting

Policy ImplicationsVietnam had gradual but progressive opening of capital markets

Policy makers must ensure financial development effects those starved of finance

Mix of more credit and better allocation criteria required

Micro-finance institutions not used in Viet Nam - network of former state lenders

Future ResearchDoes financial development improve the marginal productivity of capital?

Household decisions, access to credit and financial development


Many thanks for your time. Questions, comments,

suggestions.....

Email: [email protected]


DefinitionsFinancial Development V “Ease by which firms with positive

NPV projects can finance investment”

Financing Constraint V “Wedge between internal and

external cost of capital”


Table: GMM Investment Equation Estimates - Solely Foreign Firms FOR ==1

(1) (2) (3) (4) (5) (6)(IFTF

)t−1

0.046*** 0.008 0.022 0.053*** 0.044*** 0.030

(0.016) (0.018) (0.017) (0.016) (0.016) (0.019)(IFTF

)t−1

× FOR 0.040 0.072* 0.055 0.020 0.056 0.089*

(0.037) (0.039) (0.037) (0.045) (0.037) (0.046)(IFTF

)t−1

× FinDeptht−1 -0.852***

(0.191)(IFTF

)t−1

× FOR × FinDeptht−1 0.318

(0.451)(IFTF

)t−1

×(

LSLT

)t−1

0.625***

(0.152)(IFTF

)t−1

×FOR ×(

LSLT

)t−1

-0.139

(0.517)(IFTF

)t−1

×(

LSGDPS

)t−1

0.170***

(0.065)(IFTF

)t−1

×FOR ×(

LSGDPS

)t−1

-0.352**

(0.168)(IFTF

)t−1

×(

CLGL

)t−1

-0.001***

(0.000)(IFTF

)t−1

×FOR ×(

CLGL

)t−1

0.001*

(0.000)


Hansens J (p-value) 0.465 0.455 0.346 0.437 0.353 0.792

Res AR(2) (p-value) 0.415 0.431 0.509 0.418 0.313 0.545

n 38,912 38,912 38,912 38,912 38,283 35,214

* p<0.10, ** p<0.05, *** p<0.01


Table: GMM Investment Equation Estimates - Services Firms - SERV = 1

(1) (2) (3) (4) Overall(IFTF

)t−1

0.043* 0.057** 0.073*** 0.076*** 0.064**

(0.025) (0.024) (0.022) (0.029) (0.030)(IFTF

)t−1

× SERV -0.138*** -0.106** -0.051 -0.163*** -0.159***

(0.047) (0.042) (0.038) (0.049) (0.054)(IFTF

)t−1

× FinDeptht−1 -0.694** -0.534*

(0.291) (0.329)(IFTF

)t−1

× SERV × FinDeptht−1 -1.047** -0.520

(0.510) (0.615)(IFTF

)t−1

×(

LSLT

)t−1

0.299

(0.226)(IFTF

)t−1

×SERV ×(

LSLT

)t−1

0.938**

(0.390)(IFTF

)t−1

×(

LSGDPS

)t−1

0.038 0.099

(0.098) (0.106)(IFTF

)t−1

×SERV ×(

LSGDPS

)t−1

0.300* 0.462***

(0.156) (0.176)(IFTF

)t−1

×(

CLGL

)t−1

-0.000 0.000

(0.000) (0.000)(IFTF

)t−1

×SERV ×(

CLGL

)t−1

-0.002*** -0.002***

(0.001) (0.001)

Sargan test (p-value) 0.314 0.264 0.306 0.752 0.617

Hansens J (p-value) 0.346 0.284 0.345 0.733 0.720

Res AR(2) (p-value) 0.484 0.565 0.417 0.562 0.617

n 29,330 29,330 29,330 29,330 25,759

* p<0.10, ** p<0.05, *** p<0.01


Attrition

Year No of Firms % of Total

2002 22,050 8%

2003 28,588 10%

2004 37,192 13%

2005 45,024 15%

2006 61,560 21%

2007 41,048 14%

2008 57,398 20%

Source: VES


Summary Statistics

VARIABLE N Mean St DevIK 43,138 .927 1.489

IF 44,153 .691 .404(CFK

)37,867 .116 .312(

SK

)44,153 4.716 4.651(P

K

)44,153 .076 .405

FinDepth 44,153 .269 .136(LSLT

)44,153 .416 .188(

LSGDPS

)44,153 1.245 .447(

CLGL

)42,817 134.804 228.215

Private 44,153 .784 .411

State 44,153 .128 .334

Joint Venture 44,153 .023 .150

Solely Foreign 44,153 .065 .247

Services 44,153 .388 .487

SME 44,153 .872 .334


Variable Definitions

Table: Overview of variables in empirical model

Variable Description SourceIK Investment to beginning period capital stock VESSK Total sales to beginning period capital stock VESCFK Net income plus depreciation VES

HHIj The Herfindahl index of revenue concentration (4 digit sector) VES

FinDepth Credit to the private sector as a percentage of output VES

(LS) SOE Share of Outstanding Loans VES(LS

GDPS

)SOE Loans Share relative to SOE Output Share VES(

CLGL

)% of Loans by Commercial Banks to % Loans by Gov Banks VES

FOR Firms with 100% Foreign Ownership VES

JV Joint ventures with foreign companies VES

SERV Market Services Sectors VES

SME Firms less than 250 employees Eurostat


Table: GMM Estimates - All Firms - Simple Accelerator Model(

IK

)t

Constraint Financial Depth State Interventionism Market Financing Overall

(∆yt ) 1.796*** 0.243** 0.192* 0.273** 0.458*** 0.400***

(0.525) (0.096) (0.100) (0.123) (0.171) (0.133)(CFK

)t

0.421*** -0.116 0.245** 0.162 0.230** 0.141

(0.131) (0.163) (0.098) (0.119) (0.089) (0.116)

FinDeptht−1 -0.743*** -0.985***

(0.171) (0.206)(CFK

)t×FinDeptht−1 -6.331*** -3.484***

(1.192) (1.043)(LSLT

)t−1

-0.552***

(0.099)(CFK

)t×

(LSLT

)t−1

0.302

(1.219)(LS

GDPS

)t−1

-0.083** -0.089**

(0.033) (0.036)(CFK

)t×

(LS

GDPS

)t−1

-0.909 1.147***

(0.679) (0.203)(CLGL

)t−1

0.001*** 0.001***

(0.000) (0.000)(CFK

)t×

(CLGL

)t−1

-0.001*** -0.001**

(0.000) (0.000)


Hansens J (p-value) 0.22 0.27 0.11 0.14 0.352

Res AR(1) (p-value) 0.0 0.0 0.0 0.0 0.0 0.0

Res AR(2) (p-value) 0.05 0.68 0.94 0.89 0.507 0.399

Time/Province/Sector Dummies Yes Yes Yes Yes Yes Yes

Sector-Province Dummies Yes Yes Yes Yes Yes Yes

n 92,281 42,441 52,356 52,356 45,250 38,055

* p<0.10, ** p<0.05, *** p<0.01

All estimates are robust to heteroskedasticity and clustered at the firm level

Instruments are lagged CF/K, sales to capital dated t − 3 and deeper,

as well as lags of variables in main equation where correct

Investment Financing and Financial Development: Evidence ...Investment Financing and Financial...

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