Productivity growth, technological progress and efficiencychanges in vietnamese high tech industries

UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES HO CHI MINH CITY THE HAGUE VIETNAM THE NETHERLANDS VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS PRODUCTIVITY GROWTH, TECHNOLOGICAL PROGRESS AND EFFICIENCY CHANGES IN VIETNAMESE HIGH-TECH INDUSTRIES BY DAO HOANG BINH THIEN MASTER OF ARTS IN DEVELOPMENT ECONOMICS HO CHI MINH CITY, January 2015 UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES HO CHI MINH CITY VIETNAM THE HAGUE THE NETHERLANDS VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS PRODUCTIVITY GROWTH, TECHNOLOGICAL PROGRESS AND EFFICIENCY CHANGES IN VIETNAMESE HIGH-TECH INDUSTRIES A thesis submitted in partial fulfilment of the requirements for the degree of MASTER OF ARTS IN DEVELOPMENT ECONOMICS By DAO HOANG BINH THIEN Academic Supervisor: Dr TRUONG DANG THUY HO CHI MINH CITY, January 2015 ABSTRACT Recently, Vietnamese high-tech industries have been receiving attention from both the government, foreign companies, as well as the private sector due to the notable figures of export values (Ministry of Trade and Industry [MoIT] & United Nations Industrial Development Organization [UNIDO], 2011) This thesis attempts to estimate the productivity growth of Vietnamese high-tech manufacturers and its sources of growth Stochastic Production Frontier (SPF) approach is applied to the 2000-2012 panel dataset of Vietnamese high-tech manufactures, which are divided in sub-industries Total Factor Productivity (TFP) is then measured and decomposed to three sources, namely Technological progress (TP), Technical efficiency changes (TEC), and Scale change effects (SCE) Three different technical inefficiency effects models are also applied to investigate the determinants of technical efficiency The empirical results show considerable controversy in both signs and magnitudes of TFP and its components, TE and its determinants across models However, in general, maximum likelihood estimates show that TFP is not the main source of output increase Furthermore, the productivity and efficiency of Vietnamese high-tech manufacturers are unlikely to change largely over time Nevertheless, there are differences of technical inefficiency effects across regions, sub-industries, firm sizes, and type of ownerships Keywords: Vietnam, High-tech, manufacturing, productivity, Technological progress, Technical efficiency, Scale change effects TFP, ACKNOWLEDGEMENT I have taken efforts in this thesis However, it would not have been completed without supports of many individuals and organizations I would like to express my appreciation to all of them I would like to give special thanks to my academic supervisor, Dr Truong Dang Thuy, whose comments and encouragement helped me to write this thesis Furthermore, I would also like to acknowledge the Scientific Committee and the staff of Vietnam-Netherlands Programme for their guidance and support as well as for providing necessary information regarding the thesis Lastly, my thanks also go to my family and my classmates for their precious support which help me completing this thesis TABLE OF CONTENTS ABSTRACT iii ACKNOWLEDGEMENT iv LIST OF FIGURES viii LIST OF TABLES viii LIST OF APPENDICES ix ABBREVIATIONS x CHAPTER INTRODUCTION 1.1 Problem statement 1.2 Research objectives and hypotheses 1.3 Scope of study 1.4 Structure of thesis CHAPTER LITERATURE REVIEW 2.1 Concepts 2.1.1 Total factor productivity (TFP) 2.1.2 Technical change or Technological progress (TP) .8 2.1.3 Technical efficiency (TE) and Technical efficiency change (TEC) 2.1.4 Scale economies and Scale change effects (SCE) 2.1.5 Allocative efficiency (AE) 11 2.2 Approaches to measure and decompose TFP growth 13 2.2.1 Primal or dual approach with production, cost, or profit function .13 2.2.2 Stochastic and deterministic approaches 14 2.2.3 Parametric and non-parametric methods 14 2.3 A review of alternative Stochastic Production Frontier (SPF) models 15 2.3.1 Time-invariant models 16 2.3.2 Time-varying models 17 2.3.3 Exogenous inefficiency determinants 19 2.3.4 TFP growth decomposition 22 CHAPTER OVERVIEW OF VIETNAMESE HIGH-TECHNOLOGY MANUFACTURING SECTOR 25 3.1 High-technology (HT) 25 3.2 Overview of Vietnamese HT manufacturing sector 26 CHAPTER METHODOLOGY 29 4.1 Empirical models 29 4.2 Functional form 30 4.3 Estimation method 34 4.4 Hypotheses and testing 34 4.5 Variable measurement 34 4.5.1 Variables in the frontier model 35 4.5.2 Determinants of Technical inefficiency 36 4.6 Data source and filter process 39 CHAPTER EMPIRICAL RESULTS 40 5.1 Data description 40 5.2 Maximum likelihood estimates 43 5.3 Results of hypothesis testing 47 5.4 Results of TFP decomposition 49 CHAPTER CONCLUSIONS 54 6.1 Findings 54 6.2 Policy implications 55 6.3 Limitations and future research 55 REFERENCES 57 APPENDICES 64 LIST OF FIGURES Figure 1: Value added of HT manufacturing industries of the world and selected regions during 1997–2012 (in billions of current dollars) Figure 2: High-tech exports of Vietnam & other countries in Asia (1997-2012) .3 Figure 3: Production frontier, Technological progress, Technical efficiency, and optimal Scale of production 10 Figure 4: Technical efficiency and Allocative efficiency 12 Figure 5: World exports & value-added of HT manufacturing sector (2001-2012) 27 Figure 6: Exports of Vietnamese HT manufacturing sub-industries 28 Figure 7: Proportions of HT firms operating in five sub-industries .41 Figure 8: Percentage of HT firms divided by regions 41 Figure 9: Number of firms of different sizes, during 2000-2012 42 Figure 10: Change of HT WFOEs and SOEs during 2000-2012 42 Figure 11: Kernel density of TE (3 models BC92, BC95, and HL94) 43 Figure 12: List of major obstacles chosen by Vietnamese manufacturing firms (in 2009) 50 LIST OF TABLES Table 1: Contribution of Vietnamese HT in value added of manufacturing sector during 2000–2012 (in percentage) 27 Table 2: Some main characteristics of three models 33 Table 3: Criterion to divide HT firms into three kind of sizes 36 Table 4: Definition and measurement of all variables in the study 38 Table 5: Descriptive statistics of production function variables 40 Table 6: Descriptive statistics of TI effects mean variables 40 Table 7: Maximum Likelihood estimates of translog production frontier 45 Table 8: Maximum Likelihood estimates of technical inefficiency effects model (Model BC95 and Model HL94) 46 Table 9: LR Tests of hypotheses 48 Table 10: TFP & its decomposition in five HT sub-industries (model HL94) 49 Table 11: TFP change & its sources of change over time (model HL94) .51 Table 12: Growth rate of production inputs across HT sub-industries 52 Table 13: Returns to scale across HT sub-industries during 2000-2012 52 viii LIST OF APPENDICES Appendix 1: HT manufacturing industries in International and Vietnamese Standard Industrial Classification 64 Appendix 2: Provinces and Cities of Vietnam divided by regions 65 ABBREVIATIONS AE Allocative efficiency AEC Allocative efficiency change CRS Constant returns to scale DEA Data envelopment analysis DRS Decreasing returns to scale GSO General Statistics Office HT High-technology IRS Increasing returns to scale LR Likelihood-ratio LS Least Squares MFP Multi-factor Productivity ML Maximum likelihood MLDV Maximum Likelihood Dummy Variable OLS Ordinary Least Squares PIM Perpetual Inventory Method SCE Scale change effects SF Stochastic frontiers SFA Stochastic Frontier Analysis SOE State-owned enterprises SPF Stochastic Production Frontier TE Technical efficiency TEC Technical efficiency change TFP Total Factor Productivity TI Technical inefficiency TP Technological progress VEC Vietnam Enterprise Census VND Vietnam Dong WFOE Wholly foreign owned enterprises One other reason for progressive output growth in spite of regressive TFP growth is cheap labor Primal approach, which is adopted in this thesis, does not account for the costs of labors, whereas low wages are the incentives for HT firm managers setting up factory in Vietnam to exploit the source of cheap labors More labors can be hired, then outputs can keep growing while the wages paid may not grow as fast as output growth rate However, those effects of low wages are not captured by the SPF adopted in this research In other words, the effects of economic efficiency were ignored, resulting in the regressive TFP growth Notably, year 2008 and 2012 showed the strange estimates of SCE, TEC, and TFP, which can be the results from statistic mistakes in data collection Except for those years, other years of the period indicated rather small changes in TFP and its compositions: around -0.1% to 3.4% (see Table 11) Table 11: TFP change & its sources of change over time (model HL94) Year 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2001-2012 TP -0.003 -0.003 -0.001 -0.001 -0.001 -0.006 -0.000 0.000 -0.000 -0.019 -0.007 -0.016 -0.005 SCE 0.003 0.016 0.018 0.011 0.008 -0.000 0.001 0.282 -0.001 0.003 0.003 0.024 0.008 TEC -0.034 0.034 0.021 0.010 -0.014 0.009 0.009 0.652 -0.001 -0.008 0.029 -0.178 -0.017 TFP -0.031 0.031 0.024 0.009 -0.010 -0.000 -0.005 0.763 -0.002 -0.025 -0.003 -0.123 -0.021 Source: Author’s calculation The only bright point in the picture of Vietnamese HT firms’ productivity is the effects of changing scales Those positive estimates are the results of both increasing RTS and growth rate of capital and labors over years and across subindustries (see Table 12 and Table 13) Table 12: Growth rate of production inputs across HT sub-industries Pharmaceuticals Computers Communication equipment Precision instruments Aircrafts Total Growth Rate of Capital 0.235 0.156 0.256 0.237 0.195 0.242 Growth Rate of Labor 0.037 0.106 0.055 0.028 0.047 0.046 Source: Author’s calculation Firms operating in HT sector can still gain advantages by increasing their production scales because RTS is larger than one, implying IRS (see Table 13) Among five sub-industries, Aircraft firms are the ones that can most exploit the scale of economies This is true in reality because aircraft production needs large scale to operate and gain profit Next, Computers and Communication equipment are two sub- industries that have the fastest average rate of changing SCE However, RTS has reduced over time, showing that HT firms nearly reach their optimal scales of production Table 13: Returns to scale across HT sub-industries during 2000-2012 Computers Communication equipment Precision instruments Aircrafts RTS 1.194 1.179 1.173 1.164 1.154 1.142 1.130 1.119 1.111 1.098 1.080 1.067 1.079 1.203 1.171 1.137 1.155 1.142 1.150 1.134 1.123 1.110 1.080 1.070 1.081 1.206 1.197 1.180 1.162 1.147 1.135 1.120 1.111 1.108 1.094 1.077 1.061 1.073 1.206 1.198 1.183 1.170 1.156 1.138 1.118 1.099 1.081 1.068 1.075 1.057 1.076 1.253 1.225 1.188 1.213 1.201 1.184 1.079 1.089 1.202 1.191 1.178 1.164 1.152 1.138 1.125 1.114 1.108 1.094 1.078 1.062 1.076 1.118 1.117 1.108 1.119 1.184 1.113 Year Pharmaceuticals 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2000-2012 Source: Author’s calculation To sum up, there are three conclusions that can be drawn here Firstly, HT firms can still exploit scale of economies if they expand production Secondly, the rate of upgrading technology and improving technical efficiency is rather slow in HT sub-industries Lastly, TFP of Vietnamese HT manufacturing sector does not contributes largely to the increase of output produced as expected CHAPTER CONCLUSIONS 6.1 Findings Stemming from the research questions of whether Vietnam HT firms have high rate of TFP change and what sources of that change are, stochastic production frontier analysis was conducted using panel data of five HT sub-industries located in six regions from Vietnamese Enterprise Census (2000-2012) Afterwards, technical inefficiency effects models were built based on the specifications of Battese and Coelli (1992) – BC92, Battese and Coelli (1995) – BC95, and Huang and Liu (1994) – HL94 Model BC92 was simple to estimate technical inefficiency and draw inference; however, its estimates did not explain the data well Meanwhile, model BC95 omitted important variables so it leads to none of significant coefficients in technical inefficiency effects model Compared with BC95, HL94 is the best model to fit the data of Vietnamese HT sector From the empirical results of model HL94, the findings can be summarized into four main points: First of all, TFP of Vietnamese HT producers only account for a small proportion in the growth of output produced; it even worsened the situation in some years with negative change Secondly, regressive TFP changes were mainly derived from the deterioration of technological progress and the reduction of technical efficiency change Thirdly, only scale expansion have created positive effects on productivity even though they could not offset the downward trend of TFP change Lastly, there have been no HT firms operating at full technical efficiency level with the TE indices around 0.6, indicating that only 60% of potential output level 6.2 Policy implications From estimation results of SPF and TI effects models, mainly from model HL94, this thesis suggest some implications for both policy makers and firm managers First of all, technology progress of HT sector are not as high and quickly changing as in theories, indicating that HT firms are still using outdated technologies In addition, technical efficiency of those firms are also rather low during the period in study Thus, if having difficulty in updating technologies, HT firms can improve productivity by at first adopting best practices of production technology Secondly, estimates of RTS show that HT manufacturing industries can expand production and still exploit scale of economies, especially firms operating in Aircrafts Thirdly, model HL94 show evidence that there is a heterogeneity across HT firms Therefore, when making development policies, it should be taken in consideration that the effects of exogenous determinants on efficiency are different across regions, sub- industries, firm sizes, and firm ownerships Lastly, it seems that there is a bias in the effects of inputs used on technical efficiency In other words, knowledge and information of firms in using labor and capital are unbalanced so training or knowledge diffusion can somehow fill in that knowledge gap 6.3 Limitations and future research Like any other empirical studies, this thesis cannot avoid some limitations in analysis One of them comes from the nature of the dataset, namely Vietnamese Enterprise Census conducted by GSO The information contained in this dataset is virtually from income statements and balance sheets of firms, which may be different from reality because firms could modify the data to avoid tax duties or other contributions to the State The analysis in the thesis is also bound by assumptions and specifications from the stochastic production frontier model As mentioned in the literature review, 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