The influence of institutional quality of firm size and number of non state firm at province level in vietnam

UNIVERSISTY OF ECONOMICS HO CHI MINH CITY VIET NAM INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS VIET NAM – NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS THE INFLUENCE OF INSTITUTIONAL QUALITY ON FIRM SIZE AND NUMBER OF NON – STATE FIRMS AT PROVINCE LEVEL IN VIETNAM By TRINH MINH HAN MASTER OF ARTS IN DEVELOPMENT ECONOMICS HO CHI MINH, November 2017 UNIVERSISTY OF ECONOMICS HO CHI MINH CITY VIET NAM INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS VIET NAM – NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS THE INFLUENCE OF INSTITUTIONAL QUALITY ON FIRM SIZE AND NUMBER OF NON – STATE FIRM AT PROVINCE LEVEL IN VIETNAM A thesis submitted in partial fulfillment of the requirements for the degree of MASTER OF ARTS IN DEVELOPMENT ECONOMICS By TRINH MINH HAN Academic Supervisor: Dr TRUONG DANG THUY HO CHI MINH, November 2017 ABSTRACT The relationship between institutions and firm size is now well established This paper investigates the influences of the institutional quality of local government on firm size and number of non – state firms by using the panel data of 52 provinces in Vietnam from the period 2009 to 2013 We use a unique dataset and ranking of provincial governance institutions from Vietnam as measure of the institutional quality We deal with the endogeneity issue by using the distance from the 17th parallel as the instrument for the institutions variable Interestingly, we find no evidences to clarify the relationship between the institutional quality, firm size and number of non – state firms at province level in Vietnam Keywords: institutions, the PCI, average firm size, number of non – state firms ACKNOWLEDGEMENT With completely heart and soul, I would like to manifest my most sincere gratitude to my supervisor Dr Truong Dang Thuy There is nothing more valuable than his instructions and advice since I was lost in the final stage to finish this program His spirit and responsibility is definitely the most memorable and impressive for me even when I am no longer a student of VNP After all, Dr Thuy, I would like to say that thank you so much In addition, I thank my family, friends, VNP officers so much for supporting me to complete this program ii TABLE OF CONTENTS ABSTRACT II ACKNOWLEDGEMENT II TABLE OF CONTENTS III ABBREVIATIONS V LIST OF FIGURES VI LIST OF TABLES VII CHAPTER ONE: INTRODUCTION 1.1 PROBLEM STATEMENT 1.2 SCOPE AND OBJECTIVE OF RESEARCH 1.3 RESEARCH HYPOTHESES 1.4 THESIS STRUCTURE CHAPTER TWO: LITERATURE REVIEW 2.1 THE RELATIONSHIP BETWEEN INSTITIONS AND FIRM SIZE 2.2 THE FIRM SIZE AND THE EMPLOYEE – WEIGHTED AVERAGE FIRM SIZE 2.3 HOW TO MEASURE INSTITIONAL QUALITY 10 2.4 OTHER STATE VARIABLES 12 2.5 THE RELATIONSHIP BETWEEN INSTITUTIONS AND NUMBER OF FIRMS 13 CHAPTER THREE: METHODOLOGY AND DATA 16 3.1 DATA SOURCES AND CHARACTERISTICS 16 3.1.1 DATA SOURCES 16 3.1.2 EMPLOYEE – WEIGHTED AVERAGE FIRM SIZE and NUMBER OF FIRMS 16 3.1.3 MEASURE OF INSTITUTIONS 18 3.1.4 OTHER CONTROL VARIABLES 21 3.2 ENDOGENEITY ISSUE 21 3.3 MODEL SPECIFICATION 23 CHAPTER FOUR: RESEARCHING RESULT 26 4.1 STATISTIC ANALYSIS 26 iii 4.1.1 DESCRIPTIVE STATISTICS 26 4.1.2 BIVARIATE ANALYSIS 29 4.2 RESULT 34 CHAPTER FIVE: CONCLUSION 39 5.1 CONCLUSION 39 5.2 LIMITATION 40 5.3 SUGGESTION FOR FUTURE RESEARCHES 40 REFERENCES 41 APPENDICES 44 iv ABBREVIATIONS AFS Average firm size EWAS Employee – weighted average firm size FE Fixed effects GDP Gross Domestic Product GSO General Statistics Office IV Instrumental variable Max Maximum Min Minimum Obs Observation OLS Ordinary least squares PCI Provincial Competitiveness Index RE Random effects Std Dev Standard deviation VCCI Vietnam Chamber of Commerce and Industry v LIST OF FIGURES Figure 1: Scatter plot of the effect of PCI, Market size, GDP per capita, Schooling on Employee – weighted average firm size 30 Figure 2: Scatter plot of the effect of PCI, Market size, GDP per capita, Schooling on average firm size 31 Figure 3: Scatter plot of the effect of PCI, Market size, GDP per capita, Schooling on number of non – state firms 32 Figure 4: Scatter plot of the effect of Distance, Market size, GDP per capita and Schooling on PCI index 33 vi LIST OF TABLES Table 1: Descriptive statistics 26 Table 2: Correlation of variables 29 Table 3: What determines firm size? 34 Table 4: What determines firm size? (using IV) 36 Table 5: What determines number of non – state firms? 37 Table A 1: List of Vietnamese provinces 44 Table A 2: Data sources and definition of variables 45 Table A 3: Top five leading provinces of PCI Ranking from 2009 to 2013 47 vii CHAPTER ONE: INTRODUCTION 1.1 PROBLEM STATEMENT A firm always has to deal with issues such as the mobilization of resources for investment, the administration of performance, the resolution of conflicts among different parties, and these ones should be accomplished internally However, the legal system could influence on those problems, and as a result, the optimal size of firms might also reply on the development of institutions in each country In various studies that exploit either cross – country variation or single country variation have investigated the influences of institutional quality on firm size Kumar, Rajan, and Zingales (henceforth KRZ) (2001) concluded that higher efficient legal systems lead to larger firm sizes across thirteen European countries, the effect are stronger for industries where physical assets are less important In Mexico, Laeven and Woodruff (2007) found that the positive relationship between average firm size and judicial efficiency, this link is more prevalent for proprietorships than for corporations Beck et al (2006) had similar result when they used firm – level data on the largest industrial firms in forty - four countries Based on those previous researches, this paper will investigate the relationship between the local governance and entrepreneurs in Vietnam Interestingly, this country has a homogenous political system and government structure, but economic performances is substantially different among provinces (VNCI – VCCI, 2005) Vietnam is a nation with more than ninety million persons, a developing country organized into sixty - three provinces By launching the renovation reforms (Doi moi) in 1986, Vietnam’s GDP per capita increases from around 100$ to over 2000$ by the end of 2014 within a quarter of a century, and the poverty rate diminishes from 50% in the early 1990s to 3% in 2015 (World bank, 2015) The story may continue to follow the positive direction, but unfortunately, it does not In recent years, Vietnamese economics has revealed many troubles: the public debt is too high, the population aging, the polluted environment, the exhausted natural resources, Four trend lines from figure indicate for the positive correlations of PCI, market size, gdp per capita and schooling on number of non – state firms, especially the one between market size and number of non – state firms The last figure, the link between variables in the first stage regression of instrument variable approach is displayed: Figure 4: Scatter plot of the effect of Distance, Market size, GDP per capita and Schooling on PCI index Interestingly, the trend line between the distance and the PCI idicates the negative correlation 33 4.2 RESULT Using panel – data models, the tables below illustrate the effect of determinants such as institutions, market size, gdp per capita, schooling (human capital) on firm size and number of non – state firms at province level in Vietnam from 2009 to 2013 The details are reported as below: Table 3: What determines firm size? AFS EWAS (1)OLS (2)FE (3)RE (4)OLS (5)FE (6)RE LogPCI 0.739**(0.302) 0.051 (0.107) 0.139 (0.119) 0.601**(0.240) -0.054 (0.115) -0.010 (0.106) LogMarketsize 0.084**(0.040) -1.576***(0.501) 0.132 (0.096) 0.118***(0.027) -0.561 (0.756) 0.100 (0.070) LogGdppercapita 0.038 (0.044) -0.173 (0.106) -0.268***(0.079) 0.141***(0.040) 0.159 (0.145) 0.118 (0.076) Schooling -0.243 (0.471) 0.401 (0.539) 0.005 (0.536) -0.236 (0.347) 1.072*(0.559) 0.656 (0.508) R-squared 0.060 0.030 0.0007 0.164 0.056 0.124 260 260 260 260 260 260 Obs Note: robust standard errors are reported in parentheses *, **, *** denote significance at the 10%, 5% and 1% of statistical significance respectively In table 3, we present regression running results to investigate the influences of determinants on firm size We use average firm size captured by the total employment over total number of firms and employee – weighted average firm size as dependent variable In which, model (1), (2), (3) use average firm size, and model (4), (5), (6) use employee- 34 weighted average firm size The OLS method is applied in model (1), (4), the fixed effect is used in model (2), (5), and model (3), (6) run with random effects Remarkably, the outcomes not meet our expectations The main variable – log of PCI index – has no significant in models using fixed effects and random effects, even though in OLS model, this one has significant and positive sign The coefficient of log of market size in model (2), and the coefficient of log gdp per capita in model (3) have significant at % level when we use average firm size as dependent variable, but, those ones become insignificant in models using employee-weighted average firm size The coefficient of schooling or human capital in fixed effects model running with average firm size has no significant, while that one running employee – weighted average firm size has significant at 10 % level In addition, the R – squared in models using average firm size is very low In general, we are not able to conclude anything from the outcomes of table In the following table, we continue to investigate the influences of institutions variable and other control variables on firm size by using the instrument variable approach 35 Table 4: What determines firm size? (using IV) AFS 1st Stage EWAS 2st Stage LogPCI 1st Stage 2st Stage -1.842 (4.973) -0.119 (2.728) LogMarketsize 0.013 (0.050) 0.159 (0.151) 0.017 (0.038) 0.101 (0.090) LogGdppercapita 0.001 (0.031) -0.272***(0.084) 0.008 (0.030) 0.118**(0.057) Schooling -0.480**(0.234) -0.893 (2.338) -0.465**(0.226) 0.623 (1.227) Distance -0.00005 (0.00009) R-squared Obs -0.00005 (0.00007) 0.022 260 0.116 260 Note: standard errors are reported in parentheses *, **, *** denote significance at the 10%, 5% and 1% of statistical significance respectively In table 4, the distance from the 17th parallel is used as the instrument for institutions variable – log of PCI The first stage and second stage regression is reported respectively There are no evidences to state about the influences of the main variable – log of PCI – on firm size from both of two regressions, whether the dependent variable is average firm size or employee – weighted average firm size The only coefficient has significant is log of gdp per capita, and this one turn from negative sign in model using average firm size to positive sign in model using employee – weighted average firm size 36 Table 5: What determines number of non – state firms? Non IV (4)IV 1st Stage 2st Stage (1)OLS (2)FE (3)RE LogPCI -0.067 (0.140) -0.018 (0.045) -0.031 (0.048) LogMarketsize 0.480***(0.016) 0.961***(0.171) 0.491***(0.046) 0.008 (0.058) 0.451 (0.293) LogGdppercapita 0.193***(0.029) 0.357***(0.031) 0.363***(0.024) -0.001 (0.032) 0.389**(0.158) Schooling 2.314***(0.142) -0.485**(0.237) 2.740 (4.938) 0.215 (0.167) 0.618***(0.184) Distance 4.668 (10.340) 0.00005 (0.00001) R-squared Obs 0.896 0.825 0.849 260 260 260 0.583 260 Note: standard errors are reported in parentheses with IV model, robust standard errors are reported in parentheses with non IV model *, **, *** denote significance at the 10%, 5% and 1% of statistical significance respectively Table presents the outcome of regression running to investigate the influences of institutions variable and other control variables such as market size, gdp per capita and schooling Model (1), (2), (3) uses OLS, Fixed effects and Random effects without instrument variable, respectively Model (4) reports two stages of regression running with the distance from the 17th parallel as the instrument for log of PCI Interestingly, the coefficient of institutions has no significant at all models with or without instrument variable Gdp per captia has significant and positive sign in all models, 37 though the significant level in model using instrument variables is lower than that in other models Market size has significant at % level and positive sign in models running without instrument, but in instrument variable model this one has no significant The R – squared in model (4) is much lower than that in rest models To sum up, we not find the impact of main variable – PCI index – on the number of non – state firms, even though we have used panel – data models and instrument variable approach 38 CHAPTER FIVE: CONCLUSION This section briefly summarizes what occurred and what achieved in the process investigating the influences of institutions variables and other control variables on firm size and number of non – state firms 5.1 CONCLUSION By using the Provincial Competitive Index – the PCI index as a measure of the administrations quality of 52 local governments, combining with the employee weighted average firm size, suggested by Davis and Henrekson (1997), as a measure of the dependent variables, this paper presents the main purpose investigating the influences of institutional quality on firm size and the number of non – state firm In addition, we set other variables to control firm size and number of non – state firms The first one is market size measured by the municipal population, the second one is gdp per capita, and the last one we use the percentage of trained employed at 15 years of age and above by province named schooling variable We deal with the endogeneity issue by using the instrument for institutions variable The distance from the central province to the 17th parallel is used to instrument for PCI index variable The argument behind the instrument is that the smaller gap to that line indicates the higher damage from the war, as a consequence, this thing influences on the quality of local government Summing up, this paper finds no evidences to clarify the relationship between the provincial institutions quality, firm size and number of non – state firms Business environment plays an important role to spur economic performance, improving the institutional quality at local government, policy makers are able to solve one of growth constraints at Vietnam Although the findings from this paper are not strong enough to convince policy makers to eliminate constraints of business environment, the strategic objectives of Vietnam government will not achieve if they not perform 39 5.2 LIMITATION This section lists some limitations of this study Firstly, the database of this one lacks of the presence of some provinces (11 provinces not be observed in this research) Moreover, the source of province data was only gathered from the Provincial Statistic Yearbook of each province Hence, there is still not an assessment agency responsible for the quality of this data Secondly, the instrument of this one – the distance from the central of province to the 17th parallel – is not good one, when using it, the coefficient of the major variable does not appear as the expectations 5.3 SUGGESTION FOR FUTURE RESEARCHES From the limitation of the instrument in this paper, the further studies should seek additional instruments to investigate deeper the causation relationship between the institutions and the firm size In addition, the PCI dataset contains many valuable elements such as: “informal charges, legal institutions, entry costs …”, by breakdown this one, these following researches could investigate deeper the influences of institutions on firm size distribution Finally, the future researches should gather the data of Vietnam provinces as much as possible 40 REFERENCES Acemoglu, D., Johnson, S., & Mitton, T (2009) Determinants of 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Land access and tenure security; Transparency; Time costs of regulatory compliance; Informal charges; Proactivity of the provincial government; Business support services; Labor training; and Legal 45 institutions Sub-indices are constructed for each of these components and then combined to provide an overall indication of the quality of economic governance The sub-indices include both perception-based and concrete indicators The questionnaire was designed to have name and position of respondent usually by the own-business experience That made to increase confident for this survey (For full details of the construction of the PCI, see www.pcivietnam.org) The informal charge is one of nine indicators of this data It was surveyed regard on bribery during business registration and licensing 46 APPENDIX 4: PCI RANKING (TOP) PCI 2009 Da Nang Binh Duong Lao Cai Dong Thap Vinh Long Vinh Phuc 75.96 74.01 70.47 68.54 67.24 66.65 PCI 2010 Da Nang Lao Cai Dong Thap Tra Vinh Binh Duong Bac Ninh 69.77 67.95 67.22 65.80 65.72 64.48 PCI 2011 Lao Cai Bac Ninh Long An Dong Thap Da Nang BRVT Table A 3: Top five leading provinces of PCI Ranking from 2009 to 2013 47 73.53 67.27 67.12 67.06 66.98 66.13 PCI 2012 Dong Thap An Giang Lao Cao Binh Dinh Vinh Long Kien Giang 63.79 63.42 63.08 63.06 62.97 62.96 PCI 2013 Da Nang Thua Thien Hue Kien Giang Quang Ninh Dong Thap Ben Tre 66.45 65.56 63.55 63.51 63.35 62.78 ... investigates the influences of the institutional quality of local government on firm size and number of non – state firms by using the panel data of 52 provinces in Vietnam from the period 2009... first one includes the data at province level: the number of firms, the number of plants, the number of employees and the distribution of rims and plants by size bins Based on this dataset, they computed... as the instrument for the institutions variable Interestingly, we find no evidences to clarify the relationship between the institutional quality, firm size and number of non – state firms at province