(Luận văn) determinants of firm exit in vietnam

t to ng hi ERASMUS UNVERSITY ROTTERDAM INSTITUTE OF SOCIAL STUDIES THE NETHERLANDS ep UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM w n lo ad ju y th VIETNAM – THE NETHERLANDS yi PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS pl n ua al n va ll fu DETERMINANTS OF FIRM EXIT IN VIETNAM oi m at nh BY z z k jm ht vb TRAN THI LAM om l.c gm MASTER OF ARTS IN DEVELOPMENT ECONOMICS an Lu n va ey t re Non-VIB th HO CHI MINH CITY, MAY 2017 t to ng hi INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS ep UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM w n lo ad ju y th VIETNAM – THE NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS yi pl n ua al va n DETERMINANTS OF FIRM EXIT IN VIETNAM ll fu m oi A thesis submitted in partial fulfilment of requirements for the degree of nh MASTER OF ARTS IN DEVELOPMENT ECONOMICS at z z k jm TRAN THI LAM ht vb By om l.c gm n va DR TRUONG DANG THUY an Lu Academic Supervisor: ey t re th HO CHI MINH CITY, MAY 2017 Non-VIB t to TABLE OF CONTENTS ng ACKNOWLEDGEMENT hi ep ABSTRACT LIST OF FIGURE AND TABLES w CHAPTER 1: INTRODUCTION n 1.1 Problem Statement lo ad 1.2 Research objectives ju y th 1.3 Research questions 1.4 Scope of research yi pl CHAPTER 2: LITERATURE REVIEW ua al 2.1 Literature Review n 2.1.1 Firm exit behavior va 2.1.2 Determinants of the decision to exit n ll fu 2.2 Review of empirical studies on firm survival/exit 17 oi m 2.2.1 Approaches of analyzing firm exit and survival 17 2.2.2 Emprical analyses of firm survival 18 nh at 2.2.3 Emprical analyses of firm Exit 20 z CHAPTER 3: RESEARCH METHODOLOGY 23 z ht vb 3.1 Conceptual framework and the econometric model 23 jm 3.1.1 Conceptual framework 23 k 3.1.2 Theoretical reviews 24 gm 3.1.3 The econometric model 25 l.c 3.2 Data and variables 27 om CHAPTER 4: RESEARCH RESULT 29 an Lu 4.1 Descriptive Statistic 31 4.2 Regression results 34 va 4.2.1 Bivariate analysis 34 n 4.2.5 Marginal effects 41 Non-VIB th 4.2.4 Results of random-effect logistic regressions……………………………………… …38 ey 4.2.3 Multicollinearty analysis 37 t re 4.2.2 Multivariate analysis 36 t to CHAPTER 5: CONCLUSION…………………………………………………………………… 43 ng 5.1 Conclusion 43 hi ep 5.2 Policy Implications 44 5.3 Thesis limitations and suggestion for further researches 44 w REPERENCE 46 n lo APPENDICES 56 ad ju y th yi pl n ua al n va ll fu oi m at nh z z k jm ht vb om l.c gm an Lu n va ey t re th Non-VIB t to ACKNOWLEDGEMENT ng hi Firstly, I would like to express my sincere gratitude to my advisor Dr TRUONG DANG ep 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 w n lo I would like to express my thanks to my friends in MDE class 19, and 20, especially Duy ad Chinh (class 19), Do Luat (class 20), Duy Lap (class 20), Nguyen Thai Duong (class 20) and one y th special friend who have given their limited time to help me solved the difficulties in the process ju yi I also would like to send love to my family and my close friends for always being beside pl ua al me, spiritually encouraging me and letting me know that I am not alone in all difficult situations n Finally, my special thanks also to my husband and my baby who help me to have a strong n va motivation to finish my thesis ll fu oi m at nh z z k jm ht vb om l.c gm an Lu n va ey t re th Non-VIB 1|Page t to ABSTRACT ng hi This paper examines the determinants of firm exit in Vietnam using SME data from 2005 to ep 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 w n size, age, investment and total gross profit negatively affect firm exit lo ad Keywords: Small and medium enterprise, total asset, firm exit, firm size, firm age, debt leverage, y th investment, total gross profit, random effects logistic regression ju yi pl n ua al n va ll fu oi m at nh z z k jm ht vb om l.c gm an Lu n va ey t re th Non-VIB 2|Page t to LIST OF FIGURE AND TABLES ng hi Figure 1.1: Number of registered enterprises and stop business over period 2007-2015 ep Figure 3.1: Conceptual framework w n Table 3.1: List of surveyed province/city lo ad Table 3.2: Descriptive variables y th ju Table 4.1: Descriptive Statistic yi pl Table 4.2: The number of survey exit firms in each city/province al n ua Table 4.3: Overview of firm exit in Viet Nam n va Table 4.4: Firm exit in province/city ll fu Table 4.5 A comparison between Firm non-exit and Firm exit in term of variables oi at nh Table 4.7: VIF index m Table 4.6: Covariance matrix z Table 4.8 Results of three Random – effect logistic regressions z k jm ht vb Table 4.9 Marginal effect results om l.c gm an Lu n va ey t re th Non-VIB 3|Page t to CHAPTER 1: INTRODUCTION ng hi 1.1 Problem Statement ep The stable development and growth of firms are key factors what influence directly the w socioeconomic development On the other hand, firm’s activities affect almost all respects of n lo economy and society such as rate of unemployment, national budget, activity of trade, and other ad macroeconomic indicators y th ju The role of small and medium enterprises (SMEs) in economic growth has been recognized yi through many studies in the world recently An article by Joshua and Quartey (2010) describes that pl ua al SMEs play important roles to an economic development as creating efficient and productive jobs, n the seeds of large corporations and the fuel maintaining the national machine In advanced n va economies, the number of firms in the SME sector, which has substantial labors, is larger than the ll fu multinational one (Mullineux, 1997) In addition, Feeney and Riding (1997) reveal that oi m 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 intra- nh at regional division of the firm and they also become a countervailing force again the influence of z large-scale corporations There is approximately 91% of the enterprises is Small, Medium and z vb Micro Enterprises (SMMEs) in South Africa (Hassbroeck 1996, Berry et al 2002) They create jm ht about 61% jobs for labor source and also represent for 52%- 57% of GDP (CSS 1998, Ntsika 1999, k Gumede 2000, Berry et al 2002) In additional, Small and medium enterprises also account over countries (UNIDO 1999) om l.c gm 90% of the private business sector and play a crucial role in contributing GDP in most African Viet Nam has changed from a centralized planned economy to a socialist-oriented market an Lu 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 role to play in motivating growth, generating jobs and contributing to poverty reduction The Non-VIB 4|Page th stable until now, especially SMEs sector Small and medium enterprises (SMEs) have an essential ey 2005 and continues to grow at 7.01 percent from 2005 to 2010 The process of developing keeps in t re Vietnam General Statistics Office, Vietnam attains around 7% GDP growth over the period 2000 to n va private ownership sector contributes a vital role for Vietnam economic growth According to t to contribution of SMEs is a major tax resource for Vietnam budget annually Furthermore, according ng to the report of the Vietnam Chamber of Commerce and Industry (VCCI), we have 543,963 hi ep 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 w only contributing significantly to the Gross domestic product (GDP), reducing poverty, enhancing n lo security society, but also creating more than one million new jobs per year ad y th According to Ministry of Science and Technology, there are 692 thousand enterprises ju registered business in the period 2007 – 2015 However, there are too many enterprises not enough yi power to survive in globalized market and international integration and move out of market every pl ua al 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 n va firms) Figure 1.1 shows that the number of firms that ceased operations is increasing in the recent n years ll fu z vb Registration of operations jm ht 50.000,00 z 60.000,00 at 70.000,00 nh 80.000,00 oi 90.000,00 m 100.000,00 40.000,00 k 30.000,00 Stop business gm 20.000,00 2007 2008 2009 2010 2011 2012 2013 2014 2015 om l.c 10.000,00 an Lu Figure 1.1: Number of registered enterprises and stop business over period 2007-2015 va n (Source: Administrative Department of Business Registration - Ministry of Science and Technology) th Non-VIB ey makers to decrease the number of firm stopping business every year t re Therefore, this is a crucial problem requires a reaction from government official and policy 5|Page t to In recently, the determinant impacts the ratio of birth - death enterprises and issue of firm ng survival in the developed countries have been attracting a lot of attention of scholars around the hi ep 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 w progress (Stel et al 2005) Some empirical studies focus on relationship between characteristics of n lo firm, policy, an environment, the process of international trade liberalization and rate of firm exit ad Most of studies focus on the topic of firm exit is conducted at the firm or industry level (Hannan y th and Carroll 1992, Sarkar et al 2006) They study on effect of the determinants on exit probability of ju yi small and medium enterprises (SMEs) Many other empirical studies also reveal that the pl perseverance of small firms has an important role in economic development in a context of al n ua increasing import competition from low-cost nations (Colantone et al 2014) va However, in both the theoretical and practical sides, most of the articles are empirically n carried out on foreign firms in developed countries and studies about survival of enterprise are less fu ll mention in developing countries (Parker 2004) There are a few researches studied directly on exit m oi issue in developing countries, especially in Viet Nam nh at Thus, from the obtained results of this research will contribute to understand deeply about z the determinants influence on firm exit in Viet Nam as practical part They can make policies z 1.2 Research objectives k jm ht vb priority and influence debates on firm’s activity to reduce firm exit gm The main objective of this study is to identify factors influence on the decision of firm exit l.c Using the SME data from 2005 to 2011, this study applies a logit model with the decision to exit as  th developed based on following questions: What factors influence probability of firm exit? Non-VIB ey Medium Enterprise in Vietnam To identify and understand the dimension clearly, the research is t re This research examines how the determinants affect the exit probability of Small and n va 1.3 Research questions an Lu leverage as explanatory variables om the dependent variable and total asset, firm age, total gross profit, firm size, investment and debt 6|Page t to Bernard, Andrew, and J Bradford Jensen 2002 “The Deaths of Manufacturing Plants.” National ng Bureau of Economic Research Working Paper no 9026, NBER, Cambridge, MA hi ep Blanchard, P., Huiban, J.P and Mathieu, C., 2012 The determinants of firm exit in the French food industries Revue d'Etudes en Agriculture et Environnement-Review of agricultural and w n environmental studies, 93(2), pp.193-212 lo ad Bloom, N., M Draca and J Van Reenen (2011), ‘Trade induced technical change? 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Exit and financing in the trucking ey t re th Non-VIB 55 | P a g e t to APPENDICES ng hi Appendix 1: VIF test ep 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 Variable w n lo ad yi 2.03 ju y th Mean VIF pl al 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 = Log likelihood = -2373.3276 Wald chi2(6) Prob > chi2 n va Random-effects logistic regression Group variable: id n ua Appendix 2: Logistic regression with Random effects ll fu oi m at nh 147.03 0.0000 z = = 12 z Std Err .4087775 -1.634255 -.0318761 1347594 0421419 4416987 0559827 9841883 2274575 n 7.59 Prob >= chibar2 = 0.003 ey t re Likelihood-ratio test of rho=0: chibar2(01) = va 659329 116715 0125578 0039483 -.0044603 -.0158523 0000602 9865291 -1.505214 an Lu sigma_u rho -.0004107 -.0043078 -.0206177 -.0221885 -.0001718 -.2783029 -1.876092 om -.8330653 0.066 0.932 0.002 0.000 0.345 0.272 0.000 l.c /lnsig2u 1.84 -0.09 -3.04 -11.77 -0.94 1.10 -17.87 gm 0033084 0021062 0041219 0016164 0000592 3226672 0946135 [95% Conf Interval] k 0060736 -.0001798 -.012539 -.0190204 -.0000558 3541131 -1.690653 P>|z| jm asset size old tgp i lvr _cons z ht Coef vb exit th Non-VIB 56 | P a g e t to ng Appendix 3: The marginal effects for Model hi ep Average marginal effects Model VCE : OIM Number of obs = 7853 w Expression : Linear prediction, predict() dy/dx w.r.t : asset size old tgp i lvr n lo ad y th dy/dx ju 0060736 -.0001798 -.012539 -.0190204 -.0000558 3541131 0033084 0021062 0041219 0016164 0000592 3226672 yi pl z 1.84 -0.09 -3.04 -11.77 -0.94 1.10 n ua al asset size old tgp i lvr Delta-method Std Err 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 n va ll fu Appendix 4: Logistic regression with Random effects of sub-provinces Number of obs Number of groups Random effects u_i ~ Gaussian Obs per group: = avg = max = Integration method: mvaghermite Integration points = Log likelihood Wald chi2(15) Prob > chi2 = = 7853 3602 oi m Random-effects logistic regression Group variable: id at nh 2.2 12 z 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 th 7937456 1706595 251143 6574189 8931813 -.2326058 1055307 7943539 60084 ey prv Phú Thọ Hà Tây Hải Phòng Nghệ An Quảng Nam Khánh Hoà Lâm Đồng TP HCM Long An t re 0135696 0048848 -.0009718 -.0159357 0000686 8975147 n 0006968 -.0032691 -.0176602 -.0222969 -.0001221 -.3697013 va 0.030 0.698 0.029 0.000 0.582 0.414 an Lu 2.17 0.39 -2.19 -11.78 -0.55 0.82 om 0032839 0020801 0042573 0016228 0000487 3232753 l.c 0071332 0008079 -.009316 -.0191163 -.0000268 2639067 Non-VIB [95% Conf Interval] gm asset size old tgp i lvr Likelihood-ratio test of rho=0: chibar2(01) = P>|z| k Coef jm exit ht z 195.70 0.0000 vb Std Err = = z = -2342.6751 5.13 Prob >= chibar2 = 0.012 57 | P a g e t to Appendix 5: The marginal effects for Model ng hi Average marginal effects Model VCE : OIM Number of obs = 7853 ep Expression : Linear prediction, predict() dy/dx w.r.t : asset size old tgp i lvr w n dy/dx lo 0071332 0008079 -.009316 -.0191163 -.0000268 2639067 0032839 0020801 0042573 0016228 0000487 3232753 ad ju y th asset size old tgp i lvr Delta-method Std Err z 2.17 0.39 -2.19 -11.78 -0.55 0.82 P>|z| [95% Conf Interval] 0.030 0.698 0.029 0.000 0.582 0.414 0006968 -.0032691 -.0176602 -.0222969 -.0001221 -.3697013 0135696 0048848 -.0009718 -.0159357 0000686 8975147 yi pl al Number of obs Number of groups = = 7853 3602 Obs per group: = avg = max = 2.2 va Random-effects logistic regression Group variable: id n ua Appendix 6: Logistic regression with Random effects of sub-provinces and time n Random effects u_i ~ Gaussian ll fu Integration points = Log likelihood Wald chi2(18) Prob > chi2 m Integration method: mvaghermite 12 = = 124.19 0.0000 oi = -2055.0387 Coef .0037232 -.0106204 -.0122664 -.0006138 -.0000706 9026934 0035906 0030984 0050264 0010845 0000571 4459556 1.04 -3.43 -2.44 -0.57 -1.24 2.02 z 0.300 0.001 0.015 0.571 0.216 0.043 -.0033143 -.0166931 -.022118 -.0027394 -.0001825 0286365 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 [95% Conf Interval] 0107607 -.0045477 -.0024148 0015119 0000413 1.77675 z z k jm ht vb om l.c gm an Lu n va t re 28.46 Prob >= chibar2 = 0.000 ey Likelihood-ratio test of rho=0: chibar2(01) = P>|z| at Std Err nh exit asset size old tgp i lvr th Non-VIB 58 | P a g e t to Appendix 7: The marginal effects for Model ng hi Average marginal effects Model VCE : OIM Number of obs = 7853 ep Expression : Linear prediction, predict() dy/dx w.r.t : asset size old tgp i lvr w n lo Delta-method Std Err ad 0037232 -.0106204 -.0122664 -.0006138 -.0000706 9026934 0035906 0030984 0050264 0010845 0000571 4459556 z ju y th yi pl asset size old tgp i lvr dy/dx P>|z| 1.04 -3.43 -2.44 -0.57 -1.24 2.02 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 ua al n Appendix 8: SCATTER THE PREDICTED PROBABILITY OF EXIT ON CONTINUOUS va n VARIABLES fu ll Label variable exit "Predicted probability of exit" oi m z at nh Asset z k jm ht vb l.c gm om an Lu 200 400 600 TOTAL ASSET 800 1000 n va ey t re Size th Non-VIB 59 | P a g e ad ju y th lo yi n n ua al n va ll fu oi m at nh z z k jm ht vb an Lu n va ey t re th 60 | P a g e Non-VIB om l.c gm TGP 2000 1500 1000 old 500 pl w ep hi ng t to AGE 2000 1500 1000 SIZE 500 .5 t to hi ep ng w n lo ad y th ju yi 100000 150000 TOTAL GROSS PROFIT 200000 250000 n ua al 50000 pl va INVESTMENT n oi m ll fu nh at z z k jm ht vb gm 20000 80000 an Lu 40000 60000 INVESTMENT - I om l.c n va ey t re th Non-VIB 61 | P a g e .4 w n lo ad ep ju y th hi yi pl ng n ua al t to Lvr n va ll fu oi m at nh z z k jm ht vb om l.c gm an Lu n va ey t re th 62 | P a g e Non-VIB lvr