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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
Introduction Modelling Investment Data and Econometrics Results Conclusions and Policy Implications Annex
So many banks in Ha Noi...
Introduction Modelling Investment Data and Econometrics Results Conclusions and Policy Implications Annex
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
Introduction Modelling Investment Data and Econometrics Results Conclusions and Policy Implications 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
Introduction Modelling Investment Data and Econometrics Results Conclusions and Policy Implications Annex
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)
Introduction Modelling Investment Data and Econometrics Results Conclusions and Policy Implications Annex
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
Introduction Modelling Investment Data and Econometrics Results Conclusions and Policy Implications Annex
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
Introduction Modelling Investment Data and Econometrics Results Conclusions and Policy Implications Annex
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).
Introduction Modelling Investment Data and Econometrics Results Conclusions and Policy Implications Annex
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
Introduction Modelling Investment Data and Econometrics Results Conclusions and Policy Implications Annex
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
Introduction Modelling Investment Data and Econometrics Results Conclusions and Policy Implications Annex
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
Introduction Modelling Investment Data and Econometrics Results Conclusions and Policy Implications Annex
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
Introduction Modelling Investment Data and Econometrics Results Conclusions and Policy Implications Annex
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
Introduction Modelling Investment Data and Econometrics Results Conclusions and Policy Implications Annex
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)
Introduction Modelling Investment Data and Econometrics Results Conclusions and Policy Implications Annex
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
Introduction Modelling Investment Data and Econometrics Results Conclusions and Policy Implications Annex
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
Introduction Modelling Investment Data and Econometrics Results Conclusions and Policy Implications Annex
Additional Findings and Robustness Checks
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
Introduction Modelling Investment Data and Econometrics Results Conclusions and Policy Implications Annex
Additional Findings and Robustness Checks
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
Introduction Modelling Investment Data and Econometrics Results Conclusions and Policy Implications Annex
Additional Findings and Robustness Checks
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
Introduction Modelling Investment Data and Econometrics Results Conclusions and Policy Implications Annex
Additional Findings and Robustness Checks
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
Introduction Modelling Investment Data and Econometrics Results Conclusions and Policy Implications Annex
Additional Findings and Robustness Checks
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)
Sargan test (p-value) 0.22 0.10 0.06 0.18 0.41 0.83
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
Introduction Modelling Investment Data and Econometrics Results Conclusions and Policy Implications Annex
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
Introduction Modelling Investment Data and Econometrics Results Conclusions and Policy Implications Annex
Many thanks for your time. Questions, comments,
suggestions.....
Email: [email protected]
Introduction Modelling Investment Data and Econometrics Results Conclusions and Policy Implications Annex
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”
Introduction Modelling Investment Data and Econometrics Results Conclusions and Policy Implications Annex
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)
Sargan test (p-value) 0.450 0.441 0.358 0.427 0.298 0.820
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
Introduction Modelling Investment Data and Econometrics Results Conclusions and Policy Implications Annex
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
Introduction Modelling Investment Data and Econometrics Results Conclusions and Policy Implications Annex
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
Introduction Modelling Investment Data and Econometrics Results Conclusions and Policy Implications Annex
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
Introduction Modelling Investment Data and Econometrics Results Conclusions and Policy Implications Annex
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
Introduction Modelling Investment Data and Econometrics Results Conclusions and Policy Implications Annex
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)
Sargan test (p-value) 0.31 0.25 0.05 0.19 0.364 0.449
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