(Luận văn) productivity growth, technological progress and efficiencychanges in vietnamese high tech industries

UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES HO CHI MINH CITY THE HAGUE t to VIETNAM THE NETHERLANDS ng hi ep VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS w n lo ad ju y th yi pl n ua al n va PRODUCTIVITY GROWTH, TECHNOLOGICAL PROGRESS AND EFFICIENCY CHANGES IN VIETNAMESE HIGH-TECH INDUSTRIES ll fu oi m at nh z z ht vb k jm BY om l.c gm DAO HOANG BINH THIEN n a Lu MASTER OF ARTS IN DEVELOPMENT ECONOMICS n va y te re HO CHI MINH CITY, January 2015 UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES HO CHI MINH CITY THE HAGUE t to VIETNAM THE NETHERLANDS ng hi ep VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS w n lo ad ju y th yi PRODUCTIVITY GROWTH, TECHNOLOGICAL PROGRESS AND EFFICIENCY CHANGES IN VIETNAMESE HIGH-TECH INDUSTRIES pl n ua al n va ll fu oi m nh at A thesis submitted in partial fulfilment of the requirements for the degree of z z MASTER OF ARTS IN DEVELOPMENT ECONOMICS ht vb k jm om l.c DAO HOANG BINH THIEN gm By n a Lu Academic Supervisor: n va Dr TRUONG DANG THUY y te re HO CHI MINH CITY, January 2015 ABSTRACT t to Recently, Vietnamese high-tech industries have been receiving attention from ng both the government, foreign companies, as well as the private sector due to the hi ep notable figures of export values (Ministry of Trade and Industry [MoIT] & United Nations Industrial Development Organization [UNIDO], 2011) This thesis attempts w n to estimate the productivity growth of Vietnamese high-tech manufacturers and its lo ad sources of growth Stochastic Production Frontier (SPF) approach is applied to the ju y th 2000-2012 panel dataset of Vietnamese high-tech manufactures, which are divided in sub-industries Total Factor Productivity (TFP) is then measured and yi pl decomposed to three sources, namely Technological progress (TP), Technical al ua efficiency changes (TEC), and Scale change effects (SCE) Three different technical n inefficiency effects models are also applied to investigate the determinants of va n technical efficiency The empirical results show considerable controversy in both fu ll signs and magnitudes of TFP and its components, TE and its determinants across m oi models However, in general, maximum likelihood estimates show that TFP is not the at nh main source of output increase Furthermore, the productivity and efficiency of z Vietnamese high-tech manufacturers are unlikely to change largely over time z High-tech, manufacturing, productivity, TFP, k Vietnam, jm Keywords: ht sub-industries, firm sizes, and type of ownerships vb Nevertheless, there are differences of technical inefficiency effects across regions, gm Technological progress, Technical efficiency, Scale change effects om l.c n a Lu n va y te re iii ACKNOWLEDGEMENT t to ng hi I have taken efforts in this thesis However, it would not have been completed ep without supports of many individuals and organizations I would like to express my w appreciation to all of them n lo ad I would like to give special thanks to my academic supervisor, Dr Truong ju y th Dang Thuy, whose comments and encouragement helped me to write this thesis yi Furthermore, I would also like to acknowledge the Scientific Committee and pl ua al the staff of Vietnam-Netherlands Programme for their guidance and support as well as for providing necessary information regarding the thesis n va n Lastly, my thanks also go to my family and my classmates for their precious fu ll support which help me completing this thesis oi m at nh z z ht vb k jm om l.c gm n a Lu n va y te re iv TABLE OF CONTENTS ABSTRACT iii t to ng ACKNOWLEDGEMENT iv hi ep LIST OF FIGURES viii LIST OF TABLES viii w n lo LIST OF APPENDICES ix ad ABBREVIATIONS x y th ju CHAPTER INTRODUCTION yi Problem statement 1.2 Research objectives and hypotheses 1.3 Scope of study 1.4 Structure of thesis pl 1.1 n ua al n va ll fu m oi CHAPTER LITERATURE REVIEW nh 2.1 Concepts at Total factor productivity (TFP) 2.1.2 Technical change or Technological progress (TP) 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 z 2.1.1 z ht vb k jm om l.c gm 2.2 Approaches to measure and decompose TFP growth 13 a Lu 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 n 2.2.1 n va y te re 2.3 A review of alternative Stochastic Production Frontier (SPF) models 15 v t to ng hi ep 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 w n MANUFACTURING SECTOR 25 lo ad High-technology (HT) 25 3.2 Overview of Vietnamese HT manufacturing sector 26 ju y th 3.1 yi pl CHAPTER METHODOLOGY 29 al Empirical models 29 4.2 Functional form 30 4.3 Estimation method 34 4.4 Hypotheses and testing 34 4.5 Variable measurement 34 n ua 4.1 n va ll fu oi m at nh Variables in the frontier model 35 4.5.2 Determinants of Technical inefficiency 36 z 4.5.1 z ht vb Data source and filter process 39 k jm 4.6 gm CHAPTER EMPIRICAL RESULTS 40 Data description 40 5.2 Maximum likelihood estimates 43 5.3 Results of hypothesis testing 47 5.4 Results of TFP decomposition 49 om l.c 5.1 n a Lu n va y te re CHAPTER CONCLUSIONS 54 6.1 Findings 54 vi t to 6.2 Policy implications 55 6.3 Limitations and future research 55 ng REFERENCES 57 hi ep APPENDICES 64 w n lo ad ju y th yi pl n ua al n va ll fu oi m at nh z z ht vb k jm om l.c gm n a Lu n va y te re vii LIST OF FIGURES t to Figure 1: Value added of HT manufacturing industries of the world and selected regions during 1997–2012 (in billions of current dollars) ng hi ep Figure 2: High-tech exports of Vietnam & other countries in Asia (1997-2012) Figure 3: Production frontier, Technological progress, Technical efficiency, and optimal Scale of production 10 w n Figure 4: Technical efficiency and Allocative efficiency 12 lo ad 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 ju y th yi Figure 8: Percentage of HT firms divided by regions 41 pl n ua al 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 va n Figure 12: List of major obstacles chosen by Vietnamese manufacturing firms (in 2009) 50 ll fu m oi LIST OF TABLES nh Table 1: Contribution of Vietnamese HT in value added of manufacturing sector at z during 2000–2012 (in percentage) 27 z 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 ht vb jm k 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 om l.c gm a Lu n 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 n y te re viii va Table 13: Returns to scale across HT sub-industries during 2000-2012 52 LIST OF APPENDICES t to Appendix 1: HT manufacturing industries in International and Vietnamese Standard ng Industrial Classification 64 hi ep Appendix 2: Provinces and Cities of Vietnam divided by regions 65 w n lo ad ju y th yi pl n ua al n va ll fu oi m at nh z z ht vb k jm om l.c gm n a Lu n va y te re ix ABBREVIATIONS t to ng hi ep w n lo ad 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 ju y th AE Likelihood-ratio LS Least Squares yi LR pl Maximum likelihood n ML Multi-factor Productivity ua al MFP va n MLDV Maximum Likelihood Dummy Variable fu 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 ll OLS oi m at nh z z ht vb k jm om l.c gm n a Lu n va y te re x Master’s Thesis Dao Hoang Binh Thien VNP19 - 2014 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 t to account for the costs of labors, whereas low wages are the incentives for HT firm ng hi managers setting up factory in Vietnam to exploit the source of cheap labors More ep 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 w n captured by the SPF adopted in this research In other words, the effects of economic lo ad efficiency were ignored, resulting in the regressive TFP growth y th Notably, year 2008 and 2012 showed the strange estimates of SCE, TEC, and ju yi TFP, which can be the results from statistic mistakes in data collection Except for pl those years, other years of the period indicated rather small changes in TFP and its al n ua compositions: around -0.1% to 3.4% (see Table 11) va Table 11: TFP change & its sources of change over time (model HL94) TP SCE TEC TFP -0.003 0.003 -0.034 -0.031 -0.003 0.016 0.034 0.031 -0.001 0.018 0.021 0.024 -0.001 0.011 0.010 0.009 -0.001 0.008 -0.014 -0.010 -0.006 -0.000 0.009 -0.000 -0.000 0.001 0.009 -0.005 0.000 0.282 0.652 0.763 -0.000 -0.001 -0.001 -0.002 -0.019 0.003 -0.008 -0.025 -0.007 0.003 0.029 -0.003 -0.016 0.024 -0.178 -0.123 -0.005 0.008 -0.017 -0.021 n ll fu oi m at nh z z ht vb om l.c gm Source: Author’s calculation k jm Year 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2001-2012 a Lu The only bright point in the picture of Vietnamese HT firms’ productivity is n the effects of changing scales Those positive estimates are the results of both n va increasing RTS and growth rate of capital and labors over years and across sub- y te re industries (see Table 12 and Table 13) 51 Master’s Thesis Dao Hoang Binh Thien VNP19 - 2014 Table 12: Growth rate of production inputs across HT sub-industries t to Pharmaceuticals Computers Communication equipment Precision instruments Aircrafts Total ng hi ep 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 w n Source: Author’s calculation lo ad Firms operating in HT sector can still gain advantages by increasing their y th production scales because RTS is larger than one, implying IRS (see Table 13) ju Among five sub-industries, Aircraft firms are the ones that can most exploit the scale yi pl of economies This is true in reality because aircraft production needs large scale to ua al operate and gain profit Next, Computers and Communication equipment are two sub- n industries that have the fastest average rate of changing SCE However, RTS has va n reduced over time, showing that HT firms nearly reach their optimal scales of fu ll production m oi Table 13: Returns to scale across HT sub-industries during 2000-2012 Precision instruments Aircrafts RTS 1.203 1.171 1.137 1.155 1.142 1.150 1.134 1.123 1.110 1.080 1.070 1.081 1.117 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 1.108 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 1.119 1.253 1.225 1.188 1.213 1.201 1.184 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 1.113 z ht vb k jm n a Lu 1.079 1.089 1.184 om l.c gm 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 1.118 Communication equipment z 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2000-2012 Computers at Pharmaceuticals nh Year va n Source: Author’s calculation rate of upgrading technology and improving technical efficiency is rather slow in HT 52 y firms can still exploit scale of economies if they expand production Secondly, the te re To sum up, there are three conclusions that can be drawn here Firstly, HT Master’s Thesis Dao Hoang Binh Thien VNP19 - 2014 sub-industries Lastly, TFP of Vietnamese HT manufacturing sector does not contributes largely to the increase of output produced as expected t to ng hi ep w n lo ad ju y th yi pl n ua al n va ll fu oi m at nh z z ht vb k jm om l.c gm n a Lu n va y te re 53 Master’s Thesis Dao Hoang Binh Thien VNP19 - 2014 CHAPTER CONCLUSIONS t to 6.1 Findings ng Stemming from the research questions of whether Vietnam HT firms have hi ep 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 w n six regions from Vietnamese Enterprise Census (2000-2012) Afterwards, technical lo ad inefficiency effects models were built based on the specifications of Battese and ju – HL94 y th Coelli (1992) – BC92, Battese and Coelli (1995) – BC95, and Huang and Liu (1994) yi pl Model BC92 was simple to estimate technical inefficiency and draw inference; ua al however, its estimates did not explain the data well Meanwhile, model BC95 omitted n important variables so it leads to none of significant coefficients in technical va n inefficiency effects model Compared with BC95, HL94 is the best model to fit the ll fu data of Vietnamese HT sector m oi From the empirical results of model HL94, the findings can be summarized at nh into four main points: z First of all, TFP of Vietnamese HT producers only account for a small z vb proportion in the growth of output produced; it even worsened the situation in some ht years with negative change jm k Secondly, regressive TFP changes were mainly derived from the deterioration gm of technological progress and the reduction of technical efficiency change om even though they could not offset the downward trend of TFP change l.c Thirdly, only scale expansion have created positive effects on productivity with the TE indices around 0.6, indicating that only 60% of potential output level n a Lu Lastly, there have been no HT firms operating at full technical efficiency level n va y te re 54 Master’s Thesis Dao Hoang Binh Thien 6.2 VNP19 - 2014 Policy implications From estimation results of SPF and TI effects models, mainly from model t to HL94, this thesis suggest some implications for both policy makers and firm ng hi managers First of all, technology progress of HT sector are not as high and quickly ep 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 w n in study Thus, if having difficulty in updating technologies, HT firms can improve lo ad productivity by at first adopting best practices of production technology Secondly, y th estimates of RTS show that HT manufacturing industries can expand production and ju yi still exploit scale of economies, especially firms operating in Aircrafts Thirdly, pl model HL94 show evidence that there is a heterogeneity across HT firms Therefore, al n ua when making development policies, it should be taken in consideration that the va effects of exogenous determinants on efficiency are different across regions, sub- n industries, firm sizes, and firm ownerships Lastly, it seems that there is a bias in the fu ll effects of inputs used on technical efficiency In other words, knowledge and m oi information of firms in using labor and capital are unbalanced so training or nh at knowledge diffusion can somehow fill in that knowledge gap z Limitations and future research z 6.3 vb ht Like any other empirical studies, this thesis cannot avoid some limitations in jm analysis One of them comes from the nature of the dataset, namely Vietnamese k gm Enterprise Census conducted by GSO The information contained in this dataset is l.c virtually from income statements and balance sheets of firms, which may be different om from reality because firms could modify the data to avoid tax duties or other a Lu contributions to the State The analysis in the thesis is also bound by assumptions and n specifications from the stochastic production frontier model As mentioned in the production are large 55 y advantage may lead to misleading results of SPF estimates if price effects on te re the distortions caused by prices or costs of factor inputs and outputs produced This n va literature review, SPF, like any model adopting primal approach, does not determine Master’s Thesis Dao Hoang Binh Thien VNP19 - 2014 From the above weak points, it may be better to improve the estimation results if the quality of data can be enhanced through collecting primary data rather than t to secondary data from GSO Thus, information about prices and costs can also be ng hi obtained then dual approach can be adopted to better describe the production of firms ep in the market economy situation If dual approach cannot be applied somehow, the analysis may be improved by attempting to build other models such as those proposed w n by Greene (2005) then comparing with the estimation in this result as a reference to lo ad make more precise inference ju y th yi pl n ua al n va ll fu oi m at nh z z ht vb k jm om l.c gm n a Lu n va y te 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