(Luận văn) technical efficiency and its determinants , the case of manufacturing firms in vietnam

t to UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS ng hi ep VIETNAM- NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS w n lo ad y th ju TECHNICAL EFFICIENCY AND ITS DETERMINANTS: THE CASE OF MANUFACTURING FIRMS IN VIETNAM yi pl n ua al n va fu A thesis submitted in partial fulfilment of the requirements for the degree of ll m MASTER OF ARTS IN DEVELOPMENT ECONOMICS I~ oi at nh z By z k jm ht vb TRAN VAN KHUE om l.c DR PHAM LE THONG DR NGUYEN TRONG HOAI gm Academic Supervisor: n a Lu n va t re HO CHI MINH CITY, DECEMBER 2011 I I : -~ ~ t to ABBREVIATIONS ng hi w DEA Data Envelopment Analysis E&E Electrical and Electronics FDI Foreign Direct Investment FEM Fixed Effects Model n Allocative Efficiency Change lo ep AEC ad Gross Domestic Product ju yi GSO y th GDP General Statistic Office pl Information and Communication Technology MDE Master of Development Economics POLS Pooled Ordinary Least Squares R&D Research and Develop REM Random Effects Model SEC Scale Economies SEC Scale Efficiency Change SFPF Stochastic Frontier Production Function SMEs Small and Medium Enterprises SOEs State-Owned Enterprises TE Technical Efficiency TEC Technical Efficiency Change TFP Total Factor Productivity TP Technical Progress TT Time Trend n ua al ICT n va ll fu oi m at nh z z k jm ht vb om l.c gm an Lu n va re III TABLE OF CONTENTS t to ng hi ep CHAPTER 1: INTRODUCTION 1.1 The problem statement 1.2 Objectives of the research S w 1.3 Research questions n lo 1.4 Research methodology ad 1.5 Thesis structure y th ju CHAPTER 2: LITERATURE REVIEW yi pl 2.1 Introduction ua al 2.2 Basic Concepts and Theoretical Review n 2.2.1 The Production Function n va 2.2.2 Cobb-Douglas production function fu 2.2.3 Technical Efficiency 11 ll 2.2.4 Technical efficiency measurement 12 m oi 2.2.5 The stochastic frontier production function (SFPF) 13 nh 2.3 Empirical Studies 16 at z 2.3.1 Studies in advanced countries 16 z vb Studies in developing countries 19 k jm ht 2.3.3 Studies in Vietnam 22 2.4 Analytical framework for the research 29 gm l.c CHAPTER 3: RESEARCH METHODOLOGY AND DATA COLLECTION om 3.1 Introduction 31 3.2 Research methodology 31 a Lu 3.2.1 The stochastic frontier model 31 t re IV n 3.3.1 The stochastic frontier model 37 va 3.3 Testing Hypothesis 37 n 3.2.2 The technical efficiency model 34 3.3.2 The technical efficiency model 37 3.4 Data Collection 38 t to ng hi CHAPTER 4: ANALYSIS RESULTS ep 4.1 Sample profile 39 4.2 Technical efficiency 41 w n 4.3 Comparison of technical efficiency 44 lo 4.4 Technical efficiency model 46 ad 4.4.1 Testing for the most appropriate model .46 y th 4.4.2 Testing for heteroskedasticity 47 ju yi 4.4.3 Determinants of technical efficiency pl 4.5 Chapter Summary 50 ua al n CHAPTER 5: CONCLUSIONS, RECOMMENDATION AND LIMITATIONS va 5.1 The conclusions 51 n fu 5.2 The recommendations 54 ll 5.3 Limitations 55 oi m nh REFERENCES 56 at APPENDICES 60 z z k jm ht vb om l.c gm n a Lu n va t re v t to LIST OF TABLES & GRAPHS ng hi ep Table 2.1: Summary of Empirical Studies Table 3.1: Summary ofvariables in the frontier production function w n lo Table 3.2: Summary of variables in the technical efficiency model ad Table 4.1: Descriptive statistics of output, capital and labour of manufacturing firms y th in the period 2000-2004 ju yi Table 4.2: Estimates ofti model and tvd model pl ua al Table 4.3: The statistical tests of some hypothesis n Table 4.4: Summary of technical efficiency between ti model and tvd model va n Table 4.5: Determinants oftechnical efficiency ll fu oi m Graph 4.1: The structure of 1,645 manufacturing firms from other sectors at nh z z k jm ht vb om l.c gm n a Lu n va t re VI t to LIST OF FIGURES ng hi ep Figure 1.1: The share of manufacturing enterprises in all industries ofVietnam w n lo Figure 2.1: Illustration of Technical Efficiency ad ju y th Figure 2.2: Analytical Framework yi pl n ua al n va ll fu oi m at nh z z k jm ht vb om l.c gm n a Lu n va t re VII CHAPTER 1: INTRODUCTION t to 1.1 The problem statement ng hi Since the launch of renovation in 1986, Vietnam has successfully transformed the ep centrally-planned economy into a market economy and made great achievements in social and economic aspects In the period of 2000- 2010, the country's economic w n growth was relatively high and stable at an annual average rate of 7.2% In 2010, lo ad the real GDP was recorded 3.4 times as much as that in 2000; the state budget y th collection was times; and the GDP per capita stood at US$1,168 (GSO, 2011) By ju achieving these, Vietnam has moved from the group of poorest countries to the yi pl group of middle-income countries In addition, Vietnam has been successful in ua al poverty reduction, close to achieving universal primary education, improving n maternal health, reducing child mortality, obtaining much progress in gender n va equality and empowering women, and etc ll fu In contribution to economic and social development, Vietnamese enterprises play a oi m crucial role Business activities of enterprises have made significant progress In 53.2% and in 2007 was over 60% (GSO, 2008) The development of enterprises in at • nh 1995, enterprises contributed about 45.3% of GDP; in 2001 this share increased to z z many different sectors and localities lead to the change of economy's structure vb which reduces the share of agriculture and increases those rates of industry and ht k jm services gm With regards to manufacturing enterprises, they made important contribution to l.c dealing with social matters such as creating more new jobs, increasing income for om employees, contributing more to the state budget, and etc In more details, manufacturing enterprises create 2.203 million jobs, accounting for 47.3% of total an Lu jobs in all enterprises (GSO, 2007) t re has not been completed and needs to be improved comprehensively The shortage n economy in general and the manufacturing sector in particular The infrastructure va However, many weaknesses are found in the process of the development of the of electricity and water which are common may reduce the productivity (Klause et t to al., 2005) So, the efficiency and competitiveness of the economy still is lower than ng its potential hi ep Moreover, the performance of enterprises has different results because of their resource, types of ownership, type and scale of business, location and some other w n reasons Although the business environment has been more transparent and flexible lo for business operation, the business results of each enterprise might not grow ad steadily In general, Vietnam enterprises expose their own features y th ju Firstly, the number of new enterprises especially private companies has grown yi sharply since 2000 when the Enterprise Law carne into effect In three years after pl ua al the issue of the Law, more than 72,600 new private enterprises were established, creating around 1.6 - million new jobs (ClEM, 2004) These figures are very n ll fu of 1998 n va impressive when compared with just 26,000 private enterprises operating by the end oi m Secondly, enterprises located in big cities such as Hanoi; Hochirninh city may enjoy nh many favorable conditions such as ideal geographical location; advantage of at telecommunication, transportation; abundant labor supply with high skill to apply z z new technology in production Consequently, the number of enterprises in these vb cities increases very fast and accounts for about 47% of total number of enterprises ht jm and 45% of total revenue of the whole country (GSO, 2007) On the other hand, k these enterprises are still facing with a lot of problems such as non-synchronous gm infrastructure, un-skilled labor Especially, each enterprise in big cities has to l.c compete fiercely with many other local and domestic companies located at the same om city These problems in association with improper policies might cause the an Lu companies to slowly increase their effectiveness t re and foreign-invested sectors where the former plays a leading role in the economy n mechanism and the state regulations, Vietnam's enterprises include state, private va Thirdly, as a multi-sector market model operating according to the market The government uses the state enterprises as an important tool to stabilize the micro- t to economic environment and market prices of essential commodities such as electricity, ng coal, transport, rice and rubber So, state enterprises have received a lot of support, hi priorities, and subsidies from government Therefore, the performance of state ep enterprises is questioned about the efficiency relative to other sectors in the economy w n For above reasons, some issues need to be clarified such as the performance of firms lo in Vietnam; the production efficiency level of firms located in former Hanoi, ad y th Hochiminh cities and other places; firms of the state, foreign and other sectors; and ju the factors influencing the technical efficiency of firms yi The purpose of this thesis is to identify the above issues And, the manufacturing pl ua al sector is selected to research because of following reasons: The share of manufacturing enterprises in all industries accounts more than 20 percent of all kind n n va of activity (GSO, 2006) However, manufacturing enterprises contribute important oi m and export value (22 percent) ll fu shares of revenue (more than 30 percent), number of employees (about 50 percent) nh The thesis applies a stochastic frontier production model and technical efficiency at model to analyze the technical efficiency of manufacturing firms and try to find the z z determinants that affect firms' technical efficiency k jm ht vb om l.c gm an Lu n va t re Figure 1.1: The share of manufacturing enterprises in all industries of t to Vietnam ng hi 60 ep 50 tn ,-= Q) w ·c 40 n lo ad 30 Employment C'G Export yi 10 ju ';te y th 20 pl al n ua 2000 2001 2002 2003 2004 2005 2006 n va Source: GSO ll fu oi m at nh 1.2 Objectives of the research Basically, this thesis aims at four objectives as follows: z z vb (1) To measure the level of technical efficiency of manufacturing firms in the jm ht period 2000 to 2004 k (2) To compare the difference in technical efficiency between manufacturing gm firms located in former Hanoi and Hochiminh City and those located in other l.c provinces; between firms of state-owned, foreign firms and other firms om (3) To identify factors influencing the technical efficiency of manufacturing an Lu firms n va (4) To suggest appropriate policies for improving technical efficiency of *Note: Former Hanoi: Because the data applied in the thesis from 2000 to 2004 Since August 1, 2008 Hanoi has merged with Hatay province and parts of neighboring of Vinhphuc and Hoabinh provinces t re manufacturing firms • APPENDICES t to APPENDIX 1: Results of summary of all manufacturing firms in the period 2000-2004 ng hi Variable Mean Std Dev Observations Max I Min ep -+ + y w n lo ad 67902.01 257335.4 244018.2 81805.12 19.4 -2127963 8467547 I 5775797 I 2759652 I 1070.73 1027.906 300.2434 -17279.47 49756 I 35192.6 I 14880.53 I 113911.9 109579.7 31166.15 10 10.8 -1081747 3433053 I 2488468 I 1058510 I N N = n = T = I 27921.81 = n = T = I 317.1279 ju y th k overall I between I within I I overall I between I within I I overall I between I within I N = n = T = 15395 3079 15395 3079 15395 3079 yi pl n ua al APPENDIX 2: Results of summary of former Hanoi's manufacturing firms in the period 2000-2004 va Variable I Mean overall I between I within I I overall I between I within I 52505.08 Std Dev Min Observations Max I n -+ + -1656817 I 1503653 I 821746.9 I N 411.7016 401.7696 91.76708 4.2 -1370.177 5549 I 4707.8 I 1121 623 I N 74032.9 71624.63 19016.97 11 53.2 -261905.1 oi 221.6233 at z = 1890 378 n = T = = 1890 378 n = T = I 997436 I 741554.6 I 278628.9 I N z 22747.46 nh = 1890 378 n = T = jm ht vb overall I between I within I 15 47.6 -506259.5 m k 138473.2 129852.5 48464.9 ll fu y k APPENDIX 3: Results of summary ofHochiminh city's manufacturing firms in the period 2000-2004 Mean Std Dev Min Max I l.c gm Variable Observations -+ + 417.1405 k overall between within 37030.51 4748254 I 3822103 I 2081994 I 1637.762 1561.198 497.2594 4 -17179.46 49756 I 35192.6 I 14980.54 I 149262.3 144113.3 39122.1 10 10.8 -1072638 3433053 I 2488468 I 981615.5 I N I N 4165 833 4165 833 n ~ = n = T = I 60 = n = T = N = n = T = 4165 833 re overall between within 153 -1493375 va 274212.4 260324.9 86536.09 an Lu 84749.05 om I overall between within y - APPENDIX 4: Results of summary of other provinces' manufacturing firms in the period 2000-2004 t to ~ ng Variable Mean Std Dev Min Observations Max I hi -+ + ep overall between within 63505.03 267503.3 253709.8 84952.44 19.4 -2132360 8467547 I 5775797 I 2755255 I overall between within 291.855 807.8368 784.9994 191.4162 -4518.945 20028 I 13234.8 I 7085.055 I overall between within 24907.01 101464.9 97229.9 29077.85 13 33.8 -755072.8 2444251 I 1659482 I 1055495 y w I n lo ad k I ju y th N = n = T = 9340 1868 N = n = T = 9340 1868 N = n = T = 9340 1868 yi pl n ua al APPENDIX 5: Results of summary of State's manufacturing firms in the period 2000-2004 I Mean Std Dev Min va Variable Observations Max I I 87121.53 263628.8 253133.2 74074.62 464.1109 885.7782 872.8569 153.2206 -1194.289 30944.01 132021.6 128895.3 28846.73 10 10.8 -813227 ll 11101 I 10288.8 I 3214.111 I N = n = T = 4050 810 3433053 I 2488468 I 975529 I N = n = T = 4050 810 I at z z k jm ht vb overall I between I within I 4050 810 4731648 I 3822103 I 1951564 I nh ~ k N = n = T = 19.4 -952958.9 oi m I overall I between I within I I overall I between I within I fu y n -+ + APPENDIX 6: Results of summary ofF oreign' s manufacturing firms in the period 2000-2004 Mean Std Dev Min Max I Observations l.c I gm Variable y 520.6596 1965.861 1868.639 614.2256 9.2 -17075.94 49756 I 35192.6 I 15084.06 I 81711.16 191266 181725.1 60008.65 147 852.2 -1027957 2724186 I 2024304 I 1112299 I I 61 N = n = T = 3120 624 N = n = T = 3120 624 N = n = T = 3120 624 re 8467547 I 5775797 I 2861449 I n 30 305.8 -2026166 va 461699.2 434221.6 157669.3 n k I 169699 a Lu I overall I between I within I I overall I between I within I I overall I between I within I om -+ + , APPENDIX 7: Results of summary of Other sector's manufacturing firms in the period 2000-2004 t to ng Variable Mean Std Dev Min Max I 49685.92 45528.58 19921.02 28.2 -349597.1 167.5474 495.271 480.9453 118.7329 -3239.253 1004170 I 485267.2 I 615872 I I 11663 I 9510 I 2676.947 6029.695 15868.91 14462.39 6539.36 53.2 -150830.9 Observations hi -+ + ep y w n lo ad k 19823.51 287106 I 213077 I 199135.9 I 11 N = n = T = 8225 1645 N = n = T = 8225 1645 N = n = 8225 1645 T = ju y th overall I between I within I I overall I between I within I I overall I between I within I yi pl ua al n APPENDIX 8: Results of time-invariant inefficiency model of all 3,079 manufacturing firms in the period 2000-2004 n va fu = = 15395 3079 Obs per group: = avg = max = 5 Number of obs Number of groups ll Time-invariant inefficiency model Group variable: i oi m at nh = = 14678.43 0.0000 = Wald chi2(6) Prob > chi2 -17621.917 z Log likelihood z Coef Std Err z vb lny I P>lzl [95% Conf Interval] 51.07 57.27 2.83 3.55 -1.77 3.89 4.61 0.000 0.000 0.005 0.000 0.076 0.000 0.000 4487266 5794184 0470839 0641063 -.160077 0965347 3.774058 484542 6204795 2598884 2224975 0079887 2921029 9.3566 l.c 0091367 010475 0542879 0404067 0428747 0498907 1.424144 4666343 5999489 1534861 1433019 -.0760441 1943188 6.565329 gm I I I I I I I k jm lnk lnl locl loc2 staetp foretp cons ht -+ -+ -1.423711 0202658 0318594 2.87 8.61 28.21 0.004 0.000 0.000 1.296582 13473 836352 6.877425 2141704 9612384 a Lu 4.087004 1744502 8987952 om /mu I /lnsigma2 I /ilgtgamma I -+ -.0241283 0065504 0240005 0044189 1.144228 6976963 7991154 335775 1.238834 7233697 8931957 3530968 n va 1.190591 7107019 8461555 3444359 n sigma2 gamma sigma_u2 sigma_v2 re 62 ~ APPENDIX 9: Results of time-varying decay inefficiency model of all 3,079 manufacturing firms in the period 2000-2004 t to ng hi Number of obs Number of groups = Time variable: t Obs per group: avg max = Wald chi2(6) Frob > chi2 = ep Time-varying decay inefficiency model Group variable: i w -17364.974 = n Log likelihood lo ad lny I Coef Std Err z F>lzl = 15395 3079 5 = = = 13114.67 0.0000 [95% Conf Interval] -+ ju y th lnk lnl locl I loc2 staetp I foretp cons I 0094253 0103161 0552174 0411297 0435719 0511649 2308662 yi 4119543 6064609 1753239 1820449 -.0264891 3529977 6.540999 pl 43.71 58.79 3.18 4.43 -0.61 6.90 28.33 0.000 0.000 0.001 0.000 0.543 0.000 0.000 3934811 5862418 0670997 1014321 -.1118885 2527163 6.08851 4304276 6266801 2835481 2626577 0589103 4532792 6.993489 al -+ ua 3.548445 0204943 1371729 92086 n 220003 0014617 0209798 0328329 16.13 14.02 6.54 28.05 va /mu I /eta /lnsigma2 I /ilgtgamma I 0.000 0.000 0.000 0.000 3.117247 0176294 0960532 8565087 3.979643 0233593 1782926 9852113 0240644 0066875 0240048 0042121 1.100818 7019307 7733245 3183977 ll 1.195175 728141 8674218 3349089 oi m 1.147026 7152173 8203731 3266533 fu I I I I sigma2 gamma sigma_u2 sigma_v2 n -+ at nh z vb - ti model : = 786.63 0.0000 gm 795.88 0.0000 k = jm [ilgtgamma]_cons chi2( 1) = Frob > chi2 = ht ( 1) - tvd model om [ilgtgamma]_cons chi2( 1) Frob > chi2 = l.c ( 1) z APPENDIX 10: Hypothesis test whether y=O an Lu n va t re • 63 APPENDIX 11: Hypothesis test whether the manufacturing sector having constant t to returns to scale ng - ti model: hi ( 1) ep [lny]lnk + [lny]lnl = chi2( 1) 45.22 Frob > chi2 = 0.0000 w - tvd model : n ( 1) lo [lny]lnk + [lny]lnl = chi2 ( 1) 28 Frob > chi2 = 0.0702 ad y th ju APPENDIX 12: Hypothesis test whether ti model nested in tvd model yi pl n ua al Obs 11 (null) BIC AIC df 11 (model) va Model I 513.89 0.0000 LR chi2(1) Frob > chi2 Likelihood-ratio test (Assumption: ti nested in tvd) -+ 15395 15395 -17621.92 -17364.97 35340.25 34836.01 35263.83 34751.95 10 11 ll fu N=Obs used in calculating BIC; see [R] BIC note oi m Note: n ti I tvd I at nh z APPENDIX 13: Hypothesis test whether 11=0 in tvd model z chi2( 1) k jm [eta] cons ht vb ( 1) gm l.c Frob > chi2 196.57 0.0000 om an Lu n va re 64 • APPENDIX 14: Results ofti and tvd models of 378 former Hanoi's manufacturing firms in the period 2000-2004 t to ng - ti model hi ep Time-invariant inefficiency model Group variable: i w n lo ad Log likelihood = y th Coef = Obs per group: avg max = = Std Err 1890 378 5 = = 2106.99 0.0000 [95% Conf Interval] P>lzl z = = Wald chi2(2) Prob > chi2 -1863.4897 lny I Number of obs Number of groups ju -+ -.4208586 7167271 6.020406 0219787 0284312 1.973859 yi lnk I lnl _cons pl 19.15 25.21 3.05 0.000 0.000 0.002 3777812 6610029 2.151713 463936 7724513 9.889098 3.533922 -.0418204 1.084867 n ua /mu /lnsigma2 /ilgtgamma I al -+ -1.972964 0600638 090063 1.79 -0.70 12.05 0.073 0.486 0.000 -.3330163 -.1595434 9083472 7.400861 0759025 1.261388 0576037 0170027 0574433 0088739 852533 7126618 6042145 2248481 ll 959042 747414 7168014 2422406 fu I I I I n sigma2 gamma sigma_u2 sigma_v2 va -+ -1.078857 7792649 8293883 259633 oi m nh - tvd model = 1890 378 Obs per group: = avg = max = 5 at Time-varying decay inefficiency model Group variable: i z Number of obs Number of groups = z Time variable: t Wald chi2(2) Prob > chi2 -1805.1087 Std Err z P>lzl = 1479.90 0.0000 gm Coef = k lny I = jm ht vb Log likelihood [95% Conf Interval] 3234155 7301529 529.6796 0242868 0279339 13.32 26.14 0.000 0.000 2758143 6754035 3710168 7849024 om lnk lnl I cons I l.c -+ + -526.2634 000175 0304769 1.316424 1949713 0000158 0658885 0956989 2699.18 11.09 0.46 13.76 0.000 0.000 0.644 0.000 525.8813 0001441 -.0986622 1.128857 526.6455 0002059 1596159 1.50399 -+ -.0679275 0159547 0683548 008121 9060487 755628 6790168 2020394 • 65 1.17306 8181688 9469626 2338732 re 1.030946 7885861 8129897 2179563 n sigma2 gamma I sigma_u2 I sigma_v2 I va I I I I an Lu /mu /eta /lnsigma2 /ilgtgamma ii APPENDIX 15: Results ofti and tvd models of833 Hochiminh city's manufacturing firms in the period 2000-2004 t to ng ti model: hi ep w n lo ad Log likelihood y th lny I Coef 4165 833 Obs per group: = avg = max = 5 = = 4107.45 0.0000 Wald chi2(2) Prob > chi2 -4066.442 = = = Number of obs Number of groups Time-invariant inefficiency model Group variable: i Std Err z P>lzl [95% Conf Interval] ju -+ -.4350849 583741 6.137818 0143764 0180179 7192152 yi lnk lnl I _cons I pl 30.26 32.40 8.53 0.000 0.000 0.000 4069078 5484265 4.728182 4632621 6190555 7.547453 n 3.124665 -.0557448 1.09398 ua /mu I /lnsigma2 I /ilgtgamma al -+ -.7177722 0407693 0608903 4.35 -1.37 17.97 0.000 0.172 0.000 1.717857 -.1356513 9746366 4.531473 0241616 1.213322 0385588 0114434 0384504 0058525 8731471 7260427 6331515 2257969 ll 9457804 7491303 7085128 2372676 fu I I I I n sigma2 gamma sigma_u2 sigma_v2 va -+ -1.024456 7708863 7838742 2487383 oi m at nh tvd model: = = 4165 833 Obs per group: = avg = max = 5 Number of obs Number of groups z Time-varying decay inefficiency model Group variable: i z Wald chi2(2) Prob > chi2 -3915.1078 Std Err z 3321.41 0.0000 P>lzl [95% Conf Interval] 0.000 0.000 0.000 3319003 5591388 5.850652 l.c Coef = = gm lny I = k Log likelihood jm ht vb Time variable: t -+ -.3609855 5932986 6.444842 0148397 0174288 3031636 24.33 34.04 21.26 3900707 6274584 7.039032 om lnk I lnl I _cons I I I I I 2.644587 0323194 -.1096812 1.169187 2853867 0035119 0430941 063546 9.27 9.20 -2.55 18.40 0.000 0.000 0.011 0.000 2.08524 0254362 -.1941441 1.044639 3.203935 0392026 -.0252184 1.293735 -+ -.8961197 7629981 6837376 2123821 0386175 0114912 0386702 0052841 8235392 7397442 6079454 2020254 66 9750969 7847787 7595298 2227388 t re I I I I n sigma2 gamma sigma_u2 sigma_v2 va /mu /eta /lnsigma2 /i1gtgamma an Lu -+ • APPENDIX 16: Results ofti and tvd models of 1,868 other provinces manufacturing firms in the period 2000-2004 t to ti model: ng hi Time-invariant inefficiency model Group variable: i ep w n lo ad Log likelihood = -11465.588 y th lny I Coef Std Err z Number of obs Number of groups = Obs per group: avg max = = Wald chi2(2) Prob > chi2 = P>lzl = 9340 1868 5 = = 8312.06 0.0000 [95% Conf Interval] ju -+ -.5108214 5792951 6.290339 0116519 0135667 1.2681 yi lnk I lnl I _cons I pl 43.84 42.70 4.96 0.000 0.000 0.000 4879841 5527048 3.804909 5336587 6058854 8.77577 -+ -/mu I /lnsigma2 /ilgtgamma 1.26732 0255523 0413597 al 4.060638 2882112 7978541 ua 1 3.20 11.28 19.29 0.001 0.000 0.000 1.576737 2381296 7167906 6.54454 3382928 8789175 n -+ -.0340878 0088544 0338691 0068258 1.268874 6718999 853458 4008205 n 1.402551 7065979 9862225 4275771 ll fu 1.334039 6895153 9198403 4141988 va sigma2 gamma sigma_u2 sigma_v2 tvd model: oi Number of obs Number of groups at Time-varying decay inefficiency model Group variable: i nh ~ m , = 9340 1868 z Obs per group: avg max z Time variable: t ht vb = Wald chi2(2) Prob > chi2 -11367.285 5 = = = = jm Log likelihood = = 7635.84 0.0000 k Coef Std Err z P>lzl gm lny I [95% Conf Interval] lnk lnl I 0119003 013442 2527411 40.33 43.52 24.02 0.000 0.000 0.000 4566305 558622 5.574759 503279 6113137 6.565486 om _cons 4799547 5849678 6.070122 l.c -+ + -3.488375 0179619 2495572 7894952 2400146 001724 0260966 0423517 14.53 10.42 9.56 18.64 0.000 0.000 0.000 0.000 3.017955 0145829 1984088 7064873 3.958795 021341 3007057 872503 an Lu /mu /eta I /lnsigma2 I /ilgtgamma I 1.283457 6877229 8826628 4007942 0334939 0090955 0333337 0066287 1.219461 6696245 8173299 3878023 ,, 67 1.350812 7052663 9479957 4137862 t re I I I I n sigma2 gamma sigma_u2 sigma_v2 va -+ t APPENDIX 17: Results ofti and tvd models of810 State's manufacturing firms in the period 2000-2004 t to ti model: ng hi ep 4050 810 Number of obs Number of groups Time-invariant inefficiency model Group variable: i 5 Obs per group: avg max w n lo ad Log likelihood = y th lny I Coef 4504.25 0.0000 Wald chi2(2) Prob > chi2 -3722.2865 Std Err z P>lzl [95% Conf Interval] ju -+ -.4139825 7143291 5.555988 014516 0196425 8264937 yi lnk I lnl I cons pl 28.52 36.37 6.72 0.000 0.000 0.000 3855317 6758306 3.93609 4424333 7528276 7.175886 -+ -1 3.235821 -.0890141 1.235721 824795 0432702 0631796 ua al /mu /lnsigma2 /ilgtgamma 3.92 -2.06 19.56 0.000 0.040 0.000 1.619253 -.1738222 1.111891 4.85239 -.0042061 1.359551 n -+ -.039585 0110233 0396614 0051908 8404463 7524815 6310942 1958298 n 9958028 7956867 7865639 2161774 ll fu 9148327 7748183 7088291 2060036 va sigma2 gamma I sigma_u2 sigma_v2 m tvd model: oi r· nh Number of obs Number of groups at Time-varying decay inefficiency model Group variable: i = = 4050 810 z Time variable: t z Obs per group: avg max ht vb = Wald chi2(2) Prob > chi2 -3581.7732 = = = jm Log likelihood 5 = = 3474.06 0.0000 k Coef Std Err z P>lzl gm lny I [95% Conf Interval] 3456468 7429418 9.569684 0151282 0194884 3.254651 22.85 38.12 2.94 0.000 0.000 0.003 315996 7047454 3.190685 3752975 7811383 15.94868 om lnk I lnl I _cons I l.c -+ + -I I I I 6.656491 0124029 -.078794 1.385229 3.223679 0057868 0511712 072335 2.06 2.14 -1.54 19.15 0.039 0.032 0.124 0.000 3381963 0010609 -.1790878 1.243455 12.97479 0237449 0214998 1.527003 an Lu /mu /eta /lnsigma2 /ilgtgamma 9242303 7998295 7392266 1850037 047294 011581 047665 0047297 8360325 7761648 645805 1757337 a 68 1.021733 8215674 8326483 1942737 t re I I I I n sigma2 gamma sigma_u2 sigma_v2 va -+ i APPENDIX 18: Results ofti and tvd models of624 Foreign's manufacturing firms in the period 2000-2004 t to ti model: ng hi ep 3120 624 Number of obs Number of groups Time-invariant inefficiency model Group variable: i Obs per group: avg max w n lo ad Log likelihood = y th Std Err Coef 2530.66 0.0000 Wald chi2(2) Prob > chi2 -3418.7066 lny I 5 [95% Conf Interval] P>lzl z ju -+ -.517498 6886674 3.974811 0219783 0276141 2850278 yi lnk lnl I _cons pl 23.55 24.94 13.95 0.000 0.000 0.000 4744214 6345447 3.416167 5605746 74279 4.533455 -+ -/mu I /lnsigma2 I /ilgtgamma I 2230413 0604187 0874541 ua al 2.191179 2032021 1.103179 9.82 3.36 12.61 2.628332 3216207 1.274586 754026 0847836 9317718 0.000 0.001 0.000 n -+ -1 1.088481 7174346 7747884 287931 1.379361 7815267 1.065288 3226332 ll fu 0740323 0163602 0741083 0088528 n 1.22532 7508552 920038 3052821 va sigma2 gamma I sigma_u2 sigma_v2 oi m • tvd model: nh = = 3120 624 Obs per group: = avg = max = 5 Number of obs Number of groups at Time-varying decay inefficiency model Group variable: i z z Time variable: t Wald chi2(2) Prob > chi2 -3318.35 Coef Std Err z P>lzl = = 2042.62 0.0000 gm lny I = k jm ht vb Log likelihood [95% Conf Interval] 0219915 0262357 2646902 21.86 22.87 17.78 0.000 0.000 0.000 4375849 5487023 4.18627 5237899 6515445 5.223837 om 4806874 6001234 4.705053 l.c lnk lnl I _cons I -+ + -.1620078 0042802 056654 0847781 11.66 10.73 0.87 11.78 0.000 0.000 0.384 0.000 1.571892 0375342 -.0617212 8328632 2.206951 0543125 1603582 1.165187 -+ -1.050555 7308669 7678158 2827391 0595181 0166759 05957 00816 940145 69696 6510608 2667458 a 69 1.173931 762274 8845708 2987324 re I I I I n sigma2 gamma sigma_u2 sigma_v2 va 1.889422 0459233 0493185 9990252 n I I I I a Lu /mu /eta /lnsigma2 /ilgtgamma ~ APPENDIX 19: Results ofti and tvd models of 1,645 other sector's manufacturing firms in the period 2000-2004 t to ti model: ng hi Time-invariant inefficiency model Group variable: i ep w n lo Log likelihood = Number of obs Number of groups = Obs per group: avg max = Wald chi2(2) Prob > chi2 -10170.127 8225 1645 = 5 = = = = 5067.70 0.0000 ad y th lny I Coef Std Err z P>lzl [95% Conf Interval] ju -+ -lnk I lnl _cons 4623057 5466299 6.704487 0133328 0141404 1.088427 yi 1 34.67 38.66 6.16 0.000 0.000 0.000 4361739 5189152 4.571209 4884376 5743446 8.837765 3.931725 2935622 7730087 1.086141 026917 0437251 ua al /mu I /lnsigma2 I /ilgtgamma pl -+ -3.62 10.91 17.68 6.060523 3463185 8587083 1.802927 2408059 6873092 0.000 0.000 0.000 036101 0094482 0357877 0074219 1.272274 6653681 8474657 4090416 1.413853 7023907 987751 438135 ll fu 1.341197 6841714 9176083 4235883 n I I I I va sigma2 gamma sigma_u2 sigma_v2 n -+ m tvd model: oi ~ nh Number of obs Number of groups at Time-varying decay inefficiency model Group variable: i 8225 1645 = = z z Time variable: t Log likelihood Wald chi2(2) Prob > chi2 = -10090.637 Coef Std Err z P>lzl 5 = = = = = 4488.30 0.0000 gm lny I k jm ht vb Obs per group: avg max [95% Conf Interval] 1 4120655 5577144 6.802646 0138538 0140413 3655151 29.74 39.72 18.61 0.000 0.000 0.000 3849125 530194 6.08625 4392185 5852348 7.519043 om l.c lnk lnl _cons -+ + -1 3494309 0020841 0275077 0446684 10.21 8.39 9.47 17.27 0.000 0.000 0.000 0.000 2.883981 0134046 2065487 6839072 4.253725 0215743 314377 8590042 1.29753 6838357 8872977 4102328 0356921 0096575 0354307 0072112 1.229428 6646102 8178548 3960991 • 70 1.369406 7024526 9567405 4243666 re I I I I n sigma2 gamma sigma_u2 sigma_v2 va -+ n 3.568853 0174894 2604628 7714557 a Lu /mu I /eta /lnsigma2 /ilgtgamma :- Appendix 20: Descriptive statistic of efficiency factors t to Std Dev 1540 888.8596 888.9751 1540 2002 414259 414259 2000 2002 2000 233.7034 549.7854 492.5163 244.4477 574124 8148946 -3430.017 11.06301 10.16148 10.06389 1.414259 9.063007 446.5064 444.5529 42.33237 11 -88.36083 1.228521 1.180533 3405397 1 177785 ng -+ + -i hi ep t w n lo k21 ad overall I between I within I I overall I between I within I I overall I between I within I I overall I between I within ju y th age 1 yi overall between within 3.575912 staetp overall between within 2630724 4403157 4403729 foretp overall between within 2026632 4019967 4020489 0 2026632 loc1 overall between within 1227671 3281804 328223 0 1227671 loc2 overall between 2705424 4442545 4443122 0 2705424 n ua n va 024 -854.6141 ll fu 41.7722 21.18007 36.00609 oi m 0 2630724 at nh z N = n = T = 15395 3079 N = n = T = 15395 3079 N = n = T = 15395 307 N = n = T = 15395 3079 N = n = T = 15395 3079 N = n = T = 15395 307 I I 2026632 I I I I 1227671 I I I I N = n = T = 15395 3079 N = n = T = 15395 3079 N = n = 15395 3079 T = z 15395 3079 2705424 om l.c gm liq N = n = T = k 2.577785 15395 3079 jm overall between within N = n = T = ht size within 225.6392 3079 I 3079 I 1540 I I 2004 I 2002 I 2004 I I 16183 I 11528.39 I 12897.89 I I 81 I 79 I 13.06301 I I 6561 I 6243 I 543.6392 I I I I 5.577785 I I 4258.33 I 858.52 I 3403.386 I I I I 2630724 I vb overall between within al ~ age2 pl •' Observations Max I Min Mean Variable an Lu n va re • 71 Appendix 21: Testing OLS vs REM and testing REM vs FEM t to - Testing OLS vs REM ng xttestO hi ep Breusch and Pagan Lagrangian multiplier test for random effects = Xb + u[i] + e[i,t] te[i,t] w n Estimated results: Var lo I sd = sqrt(Var) ad -+ - ju y th I u 856562 • 0858215 5711535 1 690137 2929531 755747 Var(u) yi Test: te e 19437.05 0.0000 pl chi2(1) Prob > chi2 n ua al -Testing REM vs FEM va n hausman fern rem ll fu (B) rem (b-B) sqrt(diag(V_b-V_B)) Difference S.E nh (b) fern oi • m Coefficients 000052 age 0830454 0686352 -.000083 0144102 0008111 z -.0000309 z k21 at -+ -.0008323 -.0010049 0001726 0000565 4227513 5829311 -.1601798 0024743 1iq -.000015 -.0000217 6.69e-06 k jm ht vb age2 size Ho: difference in coefficients not systematic (b-B) I [(V_b-V_B)A(-1)] (b-B) 3996.32 0.0000 n (V_b-V_B is not positive definite) va Prob>chi2 an Lu chi2(5) om Test: inconsistent under Ha, efficient under Ho; obtained from xtreg l.c B gm b = consistent under Ho and Ha; obtained from xtreg t re 72 • • Appendix 22: Test for heteroskedasticity for FEM t to xttest3 ' ng Modified Wald test for groupwise heteroskedasticity hi in fixed effect regression model ep w n lo chi2 (3079) ad Prob>chi2 l.Oe+07 = 0.0000 y th ju Appendix 23: The best model of determinant on technical efficiency yi pl xtreg te k2l age age2 size liq staetp foretp loc1 loc2, fe vce(robust) Fixed-effects (within) regression overall 0.3962 3079 Obs per group: avg 5.0 max ll fu 0.3999 n between va 0.3343 n within 15395 Number of groups ua R-sq: Number of obs al Group variable: i m 0.1986 oi corr(u_i, Xb) F(5,3078) 485.39 Prob > F 0.0000 nh (Std Err adjusted for 3079 clusters in i) at • z Coef Std Err t P>ltl vb te z Robust [95% Conf Interval] -.0000309 000051 -0.61 0.544 0000691 -.0001309 k jm k2l ht -+ -.0830454 0038507 21.57 0.000 07 54 952 0905956 -.0008323 0001051 -7.92 0.000 -.0010383 -.0006263 size 4227513 0117802 35.89 0.000 3996534 4458492 0000529 -0.28 0.777 - 0001187 loc1 (omitted) 1oc2 (omitted) 29295314 rho 9525954 (fraction of variance due to u - i) 73 t re 1.3132341 sigma - e n • • sigma- u va 10.93914 10.78408 274.70 0.000 10.86161 0395404 - cons -+ n a Lu (omitted) om foretp 0000888 l.c -.000015 (omitted) liq staetp gm age age2 Appendix 24: Test determinant on technical efficiency t to testparm k21 age age2 size liq ng hi ep w n k21 =0 2) age =0 3) age2 =0 4) size =0 lo 1) ad 5) liq =0 ju y th F( 5, 3078) = 485.39 yi => pl Prob > F 0.0000 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 re 74