Determinants of firm exit in vietnam

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UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM ERASMUS UNVERSITY ROTTERDAM INSTITUTE OF SOCIAL STUDIES THE NETHERLANDS VIETNAM – THE NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS DETERMINANTS OF FIRM EXIT IN VIETNAM BY TRAN THI LAM MASTER OF ARTS IN DEVELOPMENT ECONOMICS HO CHI MINH CITY, MAY 2017 Non-VIB UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS VIETNAM – THE NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS DETERMINANTS OF FIRM EXIT IN VIETNAM A thesis submitted in partial fulfilment of requirements for the degree of MASTER OF ARTS IN DEVELOPMENT ECONOMICS By TRAN THI LAM Academic Supervisor: DR TRUONG DANG THUY HO CHI MINH CITY, MAY 2017 Non-VIB TABLE OF CONTENTS ACKNOWLEDGEMENT ABSTRACT LIST OF FIGURE AND TABLES CHAPTER 1: INTRODUCTION 1.1 Problem Statement 1.2 Research objectives 1.3 Research questions 1.4 Scope of research CHAPTER 2: LITERATURE REVIEW 2.1 Literature Review 2.1.1 Firm exit behavior 2.1.2 Determinants of the decision to exit 2.2 Review of empirical studies on firm survival/exit 17 2.2.1 Approaches of analyzing firm exit and survival 17 2.2.2 Emprical analyses of firm survival 18 2.2.3 Emprical analyses of firm Exit 20 CHAPTER 3: RESEARCH METHODOLOGY 23 3.1 Conceptual framework and the econometric model 23 3.1.1 Conceptual framework 23 3.1.2 Theoretical reviews 24 3.1.3 The econometric model 25 3.2 Data and variables 27 CHAPTER 4: RESEARCH RESULT 29 4.1 Descriptive Statistic 31 4.2 Regression results 34 4.2.1 Bivariate analysis 34 4.2.2 Multivariate analysis 36 4.2.3 Multicollinearty analysis 37 4.2.4 Results of random-effect logistic regressions……………………………………… …38 4.2.5 Marginal effects 41 Non-VIB CHAPTER 5: CONCLUSION…………………………………………………………………… 43 5.1 Conclusion 43 5.2 Policy Implications 44 5.3 Thesis limitations and suggestion for further researches 44 REPERENCE 46 APPENDICES 56 Non-VIB ACKNOWLEDGEMENT Firstly, I would like to express my sincere gratitude to my advisor Dr TRUONG DANG THUY for his enthusiastic assistance He has not only several insightful comments based on his immense knowledge helps me to solve all my problems, but also encourages me to finish my thesis I would like to express my thanks to my friends in MDE class 19, and 20, especially Duy Chinh (class 19), Do Luat (class 20), Duy Lap (class 20), Nguyen Thai Duong (class 20) and one special friend who have given their limited time to help me solved the difficulties in the process I also would like to send love to my family and my close friends for always being beside me, spiritually encouraging me and letting me know that I am not alone in all difficult situations Finally, my special thanks also to my husband and my baby who help me to have a strong motivation to finish my thesis Non-VIB 1|Page ABSTRACT This paper examines the determinants of firm exit in Vietnam using SME data from 2005 to 2011 Using panel data from 10 provinces and cities in Vietnam and applying the logistic regression method, this study finds that total asset and leverage have positive impacts on firm exit while the size, age, investment and total gross profit negatively affect firm exit Keywords: Small and medium enterprise, total asset, firm exit, firm size, firm age, debt leverage, investment, total gross profit, random effects logistic regression Non-VIB 2|Page LIST OF FIGURE AND TABLES Figure 1.1: Number of registered enterprises and stop business over period 2007-2015 Figure 3.1: Conceptual framework Table 3.1: List of surveyed province/city Table 3.2: Descriptive variables Table 4.1: Descriptive Statistic Table 4.2: The number of survey exit firms in each city/province Table 4.3: Overview of firm exit in Viet Nam Table 4.4: Firm exit in province/city Table 4.5 A comparison between Firm non-exit and Firm exit in term of variables Table 4.6: Covariance matrix Table 4.7: VIF index Table 4.8 Results of three Random – effect logistic regressions Table 4.9 Marginal effect results Non-VIB 3|Page CHAPTER 1: INTRODUCTION 1.1 Problem Statement The stable development and growth of firms are key factors what influence directly the socioeconomic development On the other hand, firm’s activities affect almost all respects of economy and society such as rate of unemployment, national budget, activity of trade, and other macroeconomic indicators The role of small and medium enterprises (SMEs) in economic growth has been recognized through many studies in the world recently An article by Joshua and Quartey (2010) describes that SMEs play important roles to an economic development as creating efficient and productive jobs, the seeds of large corporations and the fuel maintaining the national machine In advanced economies, the number of firms in the SME sector, which has substantial labors, is larger than the multinational one (Mullineux, 1997) In addition, Feeney and Riding (1997) reveal that governments in most countries have conducted several policies to encourage the development of SMEs Whereas, the growth of SMEs promotes the process of redistribution of both inter and intraregional division of the firm and they also become a countervailing force again the influence of large-scale corporations There is approximately 91% of the enterprises is Small, Medium and Micro Enterprises (SMMEs) in South Africa (Hassbroeck 1996, Berry et al 2002) They create about 61% jobs for labor source and also represent for 52%- 57% of GDP (CSS 1998, Ntsika 1999, Gumede 2000, Berry et al 2002) In additional, Small and medium enterprises also account over 90% of the private business sector and play a crucial role in contributing GDP in most African countries (UNIDO 1999) Viet Nam has changed from a centralized planned economy to a socialist-oriented market economy after “Đổi Mới” reform period since mid-1980 Undergoing a period of formation and development, the Vietnam economy continues to grow and get many substantial achievements A private ownership sector contributes a vital role for Vietnam economic growth According to Vietnam General Statistics Office, Vietnam attains around 7% GDP growth over the period 2000 to 2005 and continues to grow at 7.01 percent from 2005 to 2010 The process of developing keeps in stable until now, especially SMEs sector Small and medium enterprises (SMEs) have an essential role to play in motivating growth, generating jobs and contributing to poverty reduction The Non-VIB 4|Page contribution of SMEs is a major tax resource for Vietnam budget annually Furthermore, according to the report of the Vietnam Chamber of Commerce and Industry (VCCI), we have 543,963 enterprises in 2011, about nearly 513,000 enterprises in 2015, but there is nearly 97 percent of small and medium firm, mainly private businesses The important role of SME is increasing thanks to not only contributing significantly to the Gross domestic product (GDP), reducing poverty, enhancing security society, but also creating more than one million new jobs per year According to Ministry of Science and Technology, there are 692 thousand enterprises registered business in the period 2007 – 2015 However, there are too many enterprises not enough power to survive in globalized market and international integration and move out of market every year According to General Statistics Office of Vietnam, more and more firms exit and stop activity in annual reports (2015: 80,900 firms; 2014: 67,800 firms; 2013: 70,500 firms and 2012: 63,500 firms) Figure 1.1 shows that the number of firms that ceased operations is increasing in the recent years 100.000,00 90.000,00 80.000,00 70.000,00 60.000,00 50.000,00 Registration of operations 40.000,00 Stop business 30.000,00 20.000,00 10.000,00 2007 2008 2009 2010 2011 2012 2013 2014 2015 Figure 1.1: Number of registered enterprises and stop business over period 2007-2015 (Source: Administrative Department of Business Registration - Ministry of Science and Technology) Therefore, this is a crucial problem requires a reaction from government official and policy makers to decrease the number of firm stopping business every year Non-VIB 5|Page In recently, the determinant impacts the ratio of birth - death enterprises and issue of firm survival in the developed countries have been attracting a lot of attention of scholars around the world (Parker 2004, Strotmann 2006) In addition, the issue about entrepreneurial activities, which has mentioned in empirical literatures recently, is a crucial factor affects to speed of economic progress (Stel et al 2005) Some empirical studies focus on relationship between characteristics of firm, policy, an environment, the process of international trade liberalization and rate of firm exit Most of studies focus on the topic of firm exit is conducted at the firm or industry level (Hannan and Carroll 1992, Sarkar et al 2006) They study on effect of the determinants on exit probability of small and medium enterprises (SMEs) Many other empirical studies also reveal that the perseverance of small firms has an important role in economic development in a context of increasing import competition from low-cost nations (Colantone et al 2014) However, in both the theoretical and practical sides, most of the articles are empirically carried out on foreign firms in developed countries and studies about survival of enterprise are less mention in developing countries (Parker 2004) There are a few researches studied directly on exit issue in developing countries, especially in Viet Nam Thus, from the obtained results of this research will contribute to understand deeply about the determinants influence on firm exit in Viet Nam as practical part They can make policies priority and influence debates on firm’s activity to reduce firm exit 1.2 Research objectives The main objective of this study is to identify factors influence on the decision of firm exit Using the SME data from 2005 to 2011, this study applies a logit model with the decision to exit as the dependent variable and total asset, firm age, total gross profit, firm size, investment and debt leverage as explanatory variables 1.3 Research questions This research examines how the determinants affect the exit probability of Small and Medium Enterprise in Vietnam To identify and understand the dimension clearly, the research is developed based on following questions:  What factors influence probability of firm exit? 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Exit and financing in the trucking industry,’ Journal of Finance 53, 905–38 Non-VIB 55 | P a g e APPENDICES Appendix 1: VIF test Variable VIF 1/VIF intercept old aset size i lvr tgp 3.44 3.14 1.85 1.79 1.50 1.28 1.22 0.290879 0.317980 0.539434 0.558102 0.667644 0.780449 0.817761 Mean VIF 2.03 Appendix 2: Logistic regression with Random effects Random-effects logistic regression Group variable: id Number of obs Number of groups = = 7853 3602 Random effects u_i ~ Gaussian Obs per group: = avg = max = 2.2 Integration method: mvaghermite Integration points = 12 Log likelihood = -2373.3276 Wald chi2(6) Prob > chi2 exit Coef Std Err asset size old tgp i lvr _cons 0060736 -.0001798 -.012539 -.0190204 -.0000558 3541131 -1.690653 0033084 0021062 0041219 0016164 0000592 3226672 0946135 /lnsig2u -.8330653 sigma_u rho 659329 116715 z 1.84 -0.09 -3.04 -11.77 -0.94 1.10 -17.87 0.066 0.932 0.002 0.000 0.345 0.272 0.000 147.03 0.0000 [95% Conf Interval] -.0004107 -.0043078 -.0206177 -.0221885 -.0001718 -.2783029 -1.876092 0125578 0039483 -.0044603 -.0158523 0000602 9865291 -1.505214 4087775 -1.634255 -.0318761 1347594 0421419 4416987 0559827 9841883 2274575 Likelihood-ratio test of rho=0: chibar2(01) = Non-VIB P>|z| = = 7.59 Prob >= chibar2 = 0.003 56 | P a g e Appendix 3: The marginal effects for Model Average marginal effects Model VCE : OIM Number of obs = 7853 Expression : Linear prediction, predict() dy/dx w.r.t : asset size old tgp i lvr dy/dx asset size old tgp i lvr Delta-method Std Err .0060736 -.0001798 -.012539 -.0190204 -.0000558 3541131 0033084 0021062 0041219 0016164 0000592 3226672 z 1.84 -0.09 -3.04 -11.77 -0.94 1.10 P>|z| [95% Conf Interval] 0.066 0.932 0.002 0.000 0.345 0.272 -.0004107 -.0043078 -.0206177 -.0221885 -.0001718 -.2783029 0125578 0039483 -.0044603 -.0158523 0000602 9865291 Appendix 4: Logistic regression with Random effects of sub-provinces Random-effects logistic regression Group variable: id Number of obs Number of groups = = 7853 3602 Random effects u_i ~ Gaussian Obs per group: = avg = max = 2.2 Integration method: mvaghermite Integration points = 12 Log likelihood Wald chi2(15) Prob > chi2 = -2342.6751 Std Err z 195.70 0.0000 exit Coef asset size old tgp i lvr 0071332 0008079 -.009316 -.0191163 -.0000268 2639067 0032839 0020801 0042573 0016228 0000487 3232753 2.17 0.39 -2.19 -11.78 -0.55 0.82 0.030 0.698 0.029 0.000 0.582 0.414 0006968 -.0032691 -.0176602 -.0222969 -.0001221 -.3697013 0135696 0048848 -.0009718 -.0159357 0000686 8975147 prv Phú Thọ Hà Tây Hải Phòng Nghệ An Quảng Nam Khánh Hoà Lâm Đồng TP HCM Long An 7937456 1706595 251143 6574189 8931813 -.2326058 1055307 7943539 60084 1921006 190841 2161726 1862634 2052271 3189987 3158617 17712 2251866 4.13 0.89 1.16 3.53 4.35 -0.73 0.33 4.48 2.67 0.000 0.371 0.245 0.000 0.000 0.466 0.738 0.000 0.008 4172354 -.203382 -.1725474 2923494 4909436 -.8578317 -.5135468 447205 1594824 1.170256 5447011 6748335 1.022488 1.295419 39262 7246082 1.141503 1.042198 _cons -2.243187 1816322 -12.35 0.000 -2.599179 -1.887194 /lnsig2u -1.04371 4878387 -1.999856 -.0875638 sigma_u rho 5934187 0966898 1447463 0426083 3679059 0395171 9571627 2178208 Likelihood-ratio test of rho=0: chibar2(01) = Non-VIB P>|z| = = [95% Conf Interval] 5.13 Prob >= chibar2 = 0.012 57 | P a g e Appendix 5: The marginal effects for Model Average marginal effects Model VCE : OIM Number of obs = 7853 Expression : Linear prediction, predict() dy/dx w.r.t : asset size old tgp i lvr dy/dx asset size old tgp i lvr Delta-method Std Err .0071332 0008079 -.009316 -.0191163 -.0000268 2639067 0032839 0020801 0042573 0016228 0000487 3232753 z 2.17 0.39 -2.19 -11.78 -0.55 0.82 P>|z| 0.030 0.698 0.029 0.000 0.582 0.414 [95% Conf Interval] 0006968 -.0032691 -.0176602 -.0222969 -.0001221 -.3697013 0135696 0048848 -.0009718 -.0159357 0000686 8975147 Appendix 6: Logistic regression with Random effects of sub-provinces and time Random-effects logistic regression Group variable: id Number of obs Number of groups = = 7853 3602 Random effects u_i ~ Gaussian Obs per group: = avg = max = 2.2 Integration method: mvaghermite Integration points = 12 Log likelihood Wald chi2(18) Prob > chi2 = -2055.0387 Std Err z 124.19 0.0000 exit Coef asset size old tgp i lvr 0037232 -.0106204 -.0122664 -.0006138 -.0000706 9026934 0035906 0030984 0050264 0010845 0000571 4459556 1.04 -3.43 -2.44 -0.57 -1.24 2.02 0.300 0.001 0.015 0.571 0.216 0.043 -.0033143 -.0166931 -.022118 -.0027394 -.0001825 0286365 0107607 -.0045477 -.0024148 0015119 0000413 1.77675 prv Phú Thọ Hà Tây Hải Phòng Nghệ An Quảng Nam Khánh Hoà Lâm Đồng TP HCM Long An 1.143679 3163788 3977338 7132815 1.310776 -.382788 -.0200515 6446741 8916216 2256335 2170558 2462461 2131411 2449612 3568521 3559286 1993359 2636486 5.07 1.46 1.62 3.35 5.35 -1.07 -0.06 3.23 3.38 0.000 0.145 0.106 0.001 0.000 0.283 0.955 0.001 0.001 7014451 -.1090428 -.0848997 2955326 8306613 -1.082205 -.7176587 2539828 3748797 1.585912 7418003 8803673 1.13103 1.790891 3166293 6775557 1.035365 1.408363 year 2007 2009 2011 -16.33033 5.834139 5.578369 2343.881 1.016017 1.013916 -0.01 5.74 5.50 0.994 0.000 0.000 -4610.252 3.842783 3.59113 4577.591 7.825496 7.565608 _cons -7.870576 1.037529 -7.59 0.000 -9.904097 -5.837056 /lnsig2u 1683684 2497466 -.321126 6578628 sigma_u rho 1.087829 2645448 1358409 0485909 8516642 1806465 1.389483 369821 Likelihood-ratio test of rho=0: chibar2(01) = Non-VIB P>|z| = = [95% Conf Interval] 28.46 Prob >= chibar2 = 0.000 58 | P a g e Appendix 7: The marginal effects for Model Average marginal effects Model VCE : OIM Number of obs = 7853 Expression : Linear prediction, predict() dy/dx w.r.t : asset size old tgp i lvr dy/dx asset size old tgp i lvr 0037232 -.0106204 -.0122664 -.0006138 -.0000706 9026934 Delta-method Std Err .0035906 0030984 0050264 0010845 0000571 4459556 z 1.04 -3.43 -2.44 -0.57 -1.24 2.02 P>|z| 0.300 0.001 0.015 0.571 0.216 0.043 [95% Conf Interval] -.0033143 -.0166931 -.022118 -.0027394 -.0001825 0286365 0107607 -.0045477 -.0024148 0015119 0000413 1.77675 Appendix 8: SCATTER THE PREDICTED PROBABILITY OF EXIT ON CONTINUOUS VARIABLES Label variable exit "Predicted probability of exit" Asset 200 400 600 TOTAL ASSET 800 1000 Size Non-VIB 59 | P a g e .5 0 500 1000 SIZE 1500 2000 AGE 500 1000 old 1500 2000 TGP Non-VIB 60 | P a g e .5 0 50000 100000 150000 TOTAL GROSS PROFIT 200000 250000 INVESTMENT Non-VIB 20000 40000 60000 INVESTMENT - I 80000 61 | P a g e Lvr Non-VIB lvr 62 | P a g e ... OF ECONOMICS HO CHI MINH CITY VIETNAM INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS VIETNAM – THE NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS DETERMINANTS OF FIRM EXIT IN VIETNAM. .. Methodology In my study, I examines the determinants affecting the behavior of a firm to exit or not exit go out the market If the firm just has two options are an exit or not exit, a binary logit... factors influence probability of firm exit? Non-VIB 6|Page 1.4 Scope of research The study will examine the relationship between firm exit and related determinants using the panel data of 2005-2011
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