(Luận văn thạc sĩ) technical efficiency of vietnam rice farms a stochastic frontier production approach

UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM ·- INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS VIETNAM- NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS TECHNICAL EFFICIENCY OF VIETNAM RICE FARMS A STOCHASTIC FRONTIER PRODUCTION APPROACH By NGUYEN THANH DONG TRINH NGUYEN MASTER OF ARTS IN DEVELOPMENT ECONOMICS Ho Chi Minh, December 2011 UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS VIETNAM- NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS TECHNICAL EFFICIENCY OF VIETNAM RICE FARMS A STOCHASTIC FRONTIER PRODUCTION APPROACH A thesis submitted in partial fulfilment of the requirements for the degree of MASTER OF ARTS IN DEVELOPMENT ECONOMICS By NGUYEN THANH DONG TRINH NGUYEN Academic Supervisors DR NGUYEN TRONG HOAI DR PHAM LE THONG Ho Chi Minh, December 2011 CERTIFICATION "I certificate that the substance of the thesis has not already been submitted for any degree and is not currently submitted for any other degree I certify that to the best of my knowledge and help received in preparing the thesis and all sources used have been acknowledged in the thesis." Signature Nguyen Thanh Dong Trinh Nguyen Date: ACKNOWLEDGMENTS Firstly, I would like to say thank you to Dr Nguyen Trong Hoai and Dr Pham Le Thong - my academic supervisors, for their devoted recommendation Without their precious advice and instruction, I could not complete this thesis By the way, I am very proud to attend this program Every teacher sets an example of hard working for me and other students to follow And I will never forget the support from all employees of the program Their enthusiastic and friendly attitude makes me feel comfortable to study and research Moreover, I received the enormous and continue encouragement from my closed friends and my family, especially my mother Their loves have given me more strength and belief to overcome difficulties during the studying I am very grateful for everything that all of you gave me How can I pay your debt of gratitude! Nguyen Thanh Dong Trinh Nguyen ii ABSTRACT The research investigates the technical efficiency level and determinants of rice production in Vietnam The analysis employs the Vietnam Household Living Standard Survey 2008 data set and stochastic production frontier approach The mean technical efficiency level is 80% Credit approach, land policy, and experience are not significant elements of technical efficiency models while the irrigation, promotion program, education and gender of household head are significant ones Key words: technical efficiency, rice production, stochastic production frontier 111 TABLE OF CONTENT CERTIFICATION i ACKNOWLEDGMENTS ii ABSTRACT iii TABLE OF CONTENT iv LIST OF FIGURES vi LIST OF TABLES vi LIST OF ABBREVIATION vii CHAPTER I INTRODUCTION 1.1 Problem Statements 1.2 Research Objectives 1.3 Research Questions and Hypotheses 1.4 Research Methodology 1.6 Thesis Structure CHAPTER II LITERATURE REVIEW ON TECHNICAL EFFICIENCY AND CONCEPTUAL FRAMEWORK 2.1 Key Concepts 2.1.1 Technical Efficiency 2.1.2 Production Frontier 2.1.3 Stochastic Production Frontier I 2.2 Approaches to Measure Technical Efficiency 11 2.2.1 Data Envelopment Analysis 11 2.2.2 Stochastic Frontier Analysis 12 2.3 Stochastic Frontier Analysis Framework 12 2.3.1 Stochastic Frontier Model 12 2.3.2 Estimation method 14 2.4 Empirical Studies 15 2.5 Conceptual Framework 25 CHAPTER III RESEARCH METHODOLOGY FOR TECHNICAL EFFICIENCY AT THE FAMRS LEVEL 31 3.1 Data Source 31 3.2 Models Specification and Variables Definition 31 IV 2.1 Stochastic Frontier Production Function 31 3.2.2 Efficiency Model: 38 CHAPTER IV RESULTS AND DISCUSSION 45 4.1 Results of Data Analysis 45 4.1.1 Stochastic Frontier Production Function 45 4.1.2 Efficiency Model 49 4.2 Results Discussion 52 4.2.1 Discussion on Determinants of Stochastic Frontier Production Function 52 4.2.2 Discussion on Determinants of Technical Efficiency 54 CHAPTER V CONCLUSION AND RECOMMENDATION 60 5.1 Conclusion 60 5.2 Policy recommendation 61 5.3 Research limitation and further studies 63 REFERENCE 64 APPENDIX 69 v LIST OF FIGURES Figure 2.1: Technical Efficiency Figure 2.2: Production Frontier I Figure 2.3: The Stochastic Frontier Production Function 11 Figure 2.4: Conceptual Framework 26 Figure 4.1: Distribution of Technical Efficiency 56 LIST OF TABLES Table 2.1: Summary of Empirical Studies 22 Table 3.1 : Definition of Variables in Stochastic Frontier Production Function32 Table 3.2: Definition of Variables in Technical Efficiency Model 38 Table 4.1: Statistical Summary of Variables in Frontier Model 45 Table 4.2: Maximum Likelihood Estimation of Stochastic Frontier Production Function 46 Table 4.3: Statistical Summary ofVariables in Efficiency Model 49 Table 4.4: OLS -Robust Model of Technical Efficiency Determinants 51 Table 4.5: Statistical Summary of Technical Efficiency Level 55 Table 4.6: Distribution of Technical Efficiency 55 vi LIST OF ABBREVIATION COLS Corrected Ordinary Least Squares DEA Data Envelopment Analysis FAOSTAT Food and Agriculture Organization of the United NationsStatistics Division GDP Gross Domestic Production GOY government of Vietnam GSO General Statistics Office of Vietnam IPCC International Panel of Climate Change MLE Maximum Likelihood Estimation MOLS Modified Ordinary Least Squares OLS Ordinary Least Squares SBV State Bank of Vietnam TE Technical Efficiency USDA US Department of Agriculture VHLSS Vietnam Household Living Standard Survey VND Unit Currency of Vietnam- Vietnam Dong vii CHAPTER I INTRODUCTION 1.1 Problem Statements • Agriculture is an important sector in Vietnam economy Agriculture accounts for I8.2% of the country's gross domestic product in 2009 In 2008, agricultural export accounts for I2.3% of total export value of the country In 2009, the proportion of labor force in agriculture, forestry and fishery sector is 62.9% Rural population proportion was around 7I% (FAOSTAT, 20IO) and rural labor force made up 58.5 %of the total labor force (GSO, 20I 0) Rice is one of the most important crops in agricultural production with the highest cultivating area of food production Rice production is ranked at the fifth in the world Rice yield contributes 90% food production, and is related to 80% labor force of Vietnam In 20 I 0, domestic rice production of whole country was about 40 million tons from 7,500 thousands hectares of cultivated area with average yield of over tons/ha (GSO, 20IO) Vietnam annual per capita of rice consumption is very high, I69 kg/person/year (Laillou et al, 20 I 0), producing about I ,59 I calorie intake - 60% in 2007 (Timmer, 20 I 0) Rice has been a Vietnam's principal agricultural export and a great source of foreign exchange Value of exported rice accounts about 20% of agricultural and forestry products Vietnam has exported rice to I20 countries and its share in global market is about 20%, ranked at the second in the world (USDA, 20 I I) In 20 I 0, Vietnam has exported 6.88 million tons of rice worth US$3.23 billion In comparison with the year 2009, the quantity was increased I5.4 percent and the value was increased 21.2 percent (GSO, 20IO) 5.3 Research limitation and further studies The limitation of secondary data does not allow author to investigate some other aspects of rice production But with VHLSS 2008 - a large and intensive data set, we can have a broad view about efficiency of Vietnam rice production Surprisingly, Mekong River Delta has no significant advantage of technical efficiency although this region receives most favorable conditions from the nature It raises an issue for further study to find out the reasons and overcome trouble to improve efficiency of this region 63 REFERENCE Afriat S.N ( 1972 ), "Efficiency estimation of production functions··, Intemational Economic Review Vo.l3, No.3, 568-598 in Porcelli F (2009), "Measurement of Technical Efficiency A Brief Survey on Parametric and Non-Parametric Techniques Aigner D.J., C.A.K Lovell, and P Schmidt (1977), "Formulation and Estimation of Stochastic Frontier Production Function Models"', Journal of Econometrics 6, 21-37 Aigner D.J and S.F Chu (1968), "On estimating the industry production function", American Economic Review 58,826-839 in Aigner D.J., Lovell, C.A.K and Schmidt, P (I 977), "Formulation and Estimation of Stochastic Frontier Production Function Models" Journal of Econometrics 6, 21-37 AI-Hassan S (2008), "Technical Efficiency of Rice Farmers in Northern Ghana", AERC Research Paper 178, African Economic Research Consortium, Nairobi Am or T.B C Muller (201 0) "Application of Stochastic Production Frontier in the Estimation of Technical Efficiency of Irrigated Agriculture in Tunisia'', Agricultural Journal Vol.5, No.2, 50-56 Battese G.E (1991 ), "Frontier Production Functions and Technical Efficiency: A Survey Empirical Applications in Agricultural Economics", JSSN 157-0188 ISBN 85834 936 I ~l Battese G.E., and T.J Coelli (1995), "A Mode/for Technical Inefficiency Effects in a Stochastic Frontier Production for Panel Data··, Empirical Economics 20, 325-332 in Khan A., F.A Huda, and A Alam (2010), "Farm Household Technical Efficiency: A Study on Rice Producers in Selected Areay qf' Jam a/pur District in Bangladesh", European Journal of Social Sciences Vol.14, No.2 Battese G.E and G.S Corra (1977), "Estimation of a production frontier model: with application to the pastoral =one of Eastern Australia" Australian Journal of Agricultural Economics, 21, 169179 in Kompas T (2002), "Market Reform Productivity and Efficiency in l"ietnamese Rice Production IDEC Working Paper, Crawford School of Economics and Government, Australian National University Brazdik F (2006) "Non-parametric analysis ofteclmical efficiency: Factors qffecting efficiency ~l West Java rice farms" Working paper series (ISSN 1211-3298), Electronic Version Charnes A., W.W Cooper, E Rhodes ( 1978), "Measuring the efficiency of decision making units", European Journal of Operational Research, 2(4), 429-444 in F Brazdik (2006), "Non-Parametric Analysis of Technical Efficiency: Factors "1flecting Efficiency of West Java Rice Farms", ISSN 1211-3298 Coelli T.J (1993), "Finite sample properties ~l stochastic frontier estimators and associated test statistics", ISSN 157-0188, ISBN I 86389 0947 Coelli T.J., and G.E Battese ( 1996), "ldent(fication of factors which influence the technical inefficiency of Indian farmers", Australian Journal of Agricultural Economics, Vol 40, No 2, I 03128 in Khan A., F.A Huda and A Alam (2010) "Farm Household Technical ~fficiency: Stud_v 64 on Rice Producers in Selected Areas qf Jama/pur District in Bangladesh", European Journal of Social Sciences- Vol 14, No.2 Coelli T.J., P.D.S., and G.E Battese tl998), "An Introduction to Efficiency and Productivity Analysis", Kluwer Academic Publishers, Boston in Khan A., F.A Huda, and A Alam (2010), "Farm Household Technical Efficiency: A Study on Rice Producers in Selected Areas of Jamalpur District in Bangladesh" European Journal of Social Sciences- Vol 14, No.2 Msuya E.E, S Hisano, T Nariu (2008), "Explaining Productivity Variation among ,'·)maller A1ai=e Farmers in Tan=ania", XII World Congress of Rural Sociology of the International Rural Sociology Association, Goyang Korea 2008 Ellis ( 1993 ), "Peasant Economics 2nd edition", Cambridge University Press in S AI-Hassan (2008), "Technical Efficiency qf Rice Farmers in Northern Ghana", AERC Research Paper 178 African Economic Research Consortium, Nairobi April 2008 Chirwa E.C (2003), "Sources of Technical Efficiency among Smallholder Mai=e Farmers in Southern Malm1'i", Wadonda Consult Working Paper WC/01/03 FAOST AT (2009), Statistical Yearbook 2009 FAOSTAT (2010), Statistical Yearbook 2010 Farrell M.J (1957), "The Measurement qf Productive E,f.ficiency·•, Journal of the Royal Statistical Society Vol.l20, No.3, 253-290 in Hien N.T.M., T Kawaguchi and N Suzuki (2003), "A Study on Technical E;Yficiency qf Rice Production in Afekong Delta Vietnam by Stochastic Frontier Analysis" J Fac Agr Kyushu Univ., Vol 48, No.l-2, 325-357 Gabrielsen A ( 1975 ) "On estimating efficient production functions", Chr Michelsen Institute, Department of Humanities and Social Science, Working Paper No.A-35 in Porcelli F (2009), "Measurement of Technical Efficiency A Brief Survey on Parametric and Non-Parametric Techniques", General Statistical Office (2009), "Statistical Yearbook qf Vietnam" Statistical Publishing House General Statistical Office (2009), "The 2009 VN Population and Housing Census - Completed Results" General Statistical Office (20 10), "Statistical Yearbook of Vietnam", Statistical Publishing House Government Information Gateway (2009), "Resolution on National Food 5iecurity- No.: 63NQCP" Greene W.H (1980), "Maximum likelihood estimation qfeconometric.frontierfunctions" Journal ofEconometrics 13,27-56 Gujarati D.N (2003), "Basic Econometrics·· ISBN 0-07-112342-3 Hien N.T.M., T Kawaguchi and N Suzuki (2003), "A S"tudy on Technical ~fficiency of Rice Production in Alekong Delta · · · Vietnam by Stochastic Frontier Analysis" Journal of the Faculty of Agriculture, Kyushu University Vol.48, No.l-2, 325-357 65 Horrace W.C., P Schmidt (1996), "Confidence Statements for Efficiency Estimates from Stochastic Frontier Models" Journal of Productivity Analysis, Vol.7, 257-282 in Brazdik, F (2006), "NonParametric Analysis of Technical E;(ficiency: Factors /~fleeting E;f}iciency of West Java Rice Farms", ISSN 1211-3298 Huy H.T (2009), "Technical E;[ficiency of Rice Producing Households in Mekong Delta of Vietnam", MPRA Paper No 30610, posted 03 May 2011 I 12:48, online at http://mpra.ub.unimuenchen.de/3061 0/ Idiong I.C (2007), "Estimation of Farm Level Technical Efficiency in Small-scale Swamp Rice Production in Cross River State of Nigeria: A Stochastic Frontier Approach", World Journal of Agricultural Sciences Vol.3 No.5 653-658 Raphael 1.0 (2008) ''Technical E;(ficiency of Cassava Farmers in South Eastern Nigeria: Stochastic Frontier Approach" Agricultural Journal Vol.3, No.2, 152-156, 2008 ISSN: 1816-9155 IPCC (2007), "The Fourth Assessment Report", Intergovernmental Panel on Climate Change Johansson H (2005), "Technical, Allocative and Economic Efficiency in Swedish DaiiJ' Farms: The Data Envelopment Analysis versus The Stochastic Frontier Approach", Poster background paper prepared for presentation at the XI International Congress of the European Association of Agricultural Economists (EAAE) Copenhagen, Denmark, August 24-27, 2005 Jondrow J C.A.K Lovell, I.S Materov, and P Schmidt (1982), "On the Estimation of Technical Inefficiency in the Stochastic Frontier Production Function Model", Journal of Econometrics Vol.19, 233-238 Kalirajan K.P., and R.T Shand ( 1985 ), "Types of Education and Agricultural Productivity: A Quantitative Analysis of Tamil Nadu Rice Farming", Journal of Development Studies, Vol.21 No.2, 232-43 KBR (2009), "TA4903-VIE JVater Sector Review Project_ Final Report", prepared by Kellogg Brown & Root Pty Ltd South Australia Khai H.V., M Yabe (2009), "Agricultural Policy Impacts in So.vbean Productive }.,fficiency in the Mekong Delta qf VietNam", Annual Conference of The Agricultural Economics Society of Japan, Tsukuba University, Tsukuba, Japan, March 28-30 Khan A., F.A Huda, and A Alam (2010), "Farm Household Technical Efficiency: A Study on Rice Producers in Selected Areas qf Jamalpur District in Bangladesh", European Journal of Social Sciences Vol.l4, No.2 • Kompas T (2002) "A1arket Reform, Productivity and }.,fficiency in Vietnamese Rice Production" IDEC Working Paper Crawford School of Economics and Government, Australian National University Kompas T., C.T Nhu, N.Q Ha, and N.T.M Hoa (2009) "Productivity Net Returns and E;(ficiency: Land and Market Reform in Vietnamese Rice Production", International and 66 Development Economics Working Papers, !DEC 09-02, Crawford School of Economics and Government Koc M.G., and Parlakay (2011 ), ''Determinants of Technical Efficiency in Second Crop Mai=e Growing Farms in Turkey: A Case Study for the East Mediterranean in Turkey'', Asian Journal of Animal and Veterinary Advances Vol.6, No.5, 488-498 Kumbhaker S.C, and C.A.K Lovell (2000) "Stochastic Frontier Analysis" in Hien N.T.M., T Kawaguchi and N Suzuki (2003), "A Study on Technical Efficiency of Rice Production in The Ale kong Delta - Vietnam hy Stochastic Frontier Analysis" Journal of the Faculty of Agriculture, Kyushu University, Vol.48, No.l-2, 325-357 Laillou A., S Muthayya, S Prigge, and L Scott (2010), "Country Assessment for Rice F ort(fication in Vietnam", Rice Fortification Resource Group, July 8-15, 2010 Meeusen W., and J V.D Broeck ( 1977), "Efficiency Estimation from Cobb-Douglas Production Function with Composed Error", International Economic Review 8, 435-444 in Jondrow J., Lovell, C.A.K., I.S Materov, and P Schmidt (1982), "On the Estimation of Technical Ine_fficiency in The Stochastic Frontier Production Function Alode/", Journal of Econometrics, Vol.J 9, 233-238 Ohajianya D.O, P.C Obasi, and J.S Orebiyi (2006), "Technical Inefficiency and Its Determinants in Food Crops Production in Imo State, Nigeria", Journal of Agriculture and Social Research (JASR) Vol 6, No.2, 2006 Onoja A.O M.K Imbrahim and A.I Achike (2008), "Econometric Analysis q(Credit and Farm Resource Technical E:!ficiencies' Determinants in Cassava Farms in Kogi State Nigeria: A Diagnostic and Stochastic Frontier Approach" Edited Conference Proceedings ofthe lOth Annual National Conference of Nigerian Association of Agricultural Economists (NAAE), October 7th to 1Oth, University of Abuja Porcelli F (2009), "Measurement of Technical Efficiency A Brief Survey on Parametric and NonParametric Techniques", available at this website address: http:/!docs google com/viewer?a=v&q=cache: pS09o B lzfXY J: www2 warwick ac uk/fac/soc/econo mics/stafflphd students/porcelli/porcelli dea sfm.pdf+porcelli+ 2009+efficiency&hl=vi&gl=vn&pi d=bl&srcid=A DGEESiMRkAFvgKzBs4Xba3bl4vs1NdwHV GBk9627n Vc V12uMG LeaLcngxSOA n3y8obxdPnziuBRkEoi3ZIGiwYNOJJgqjteiVOg4taHhWQmAtGgLHBdQNLaplFwDCFr-20nN 4V4-d&sig=AHIEtbOu A 1-Ax8MDufBJDWbbOtuydXcPQ, retrieved on May 24th, 2011 Richmond J (1974), "Estimating the efficiency of production", International Economic Review Vo.l3, No.2, 515-521 in Porcelli F (2009), "Measurement of Technical Efficiency A Brief Survey on Parametric and Non-Parametric Techniques" Rios A.R., and G.E Shively (2004), "Farm Si=e and Non-Parametric Efficiency Measurement for Coffee in Vietnam", Selected Paper prepared for presentations at the American Agricultural Economics Association Annual Meeting, Province, Rhode Island, July 24-27, 2005 State Bank of Vietnam (2009), "State Bank of Vietnam- Annual Report 2009" Sharma K.R., and Leung P.S ( 1998), "Technical Efficiency of Carp Production in l'iepal: An Application of Stochastic Frontier Production Function Approach", Aquaculture Economics and Management 2, 129-140 in Khan A., F.A Huda, A Alam (2010), "Farm Household Technical 67 Efficiency: A Study on Rice Producers in Selected Areas qf Jamalpur District in Bangladesh" European Journal of Social Sciences- Vol.l4, No.2 Sigh S (2007), "A S'tudy on Technical Efficiency qf Wheat Cultivation in Haryana ·· Agricultural Economics Research Review Vol 20 January-June 2007, 127-136 Stevenson R.E ( 1980), "Likelihood functions for generali=ed stochastic frontier estimations", Journal of Econometrics Vo.l3, No.I, 58-66 in Porcelli F (2009), "Measurement of Technical Efficiency A BriefSurvey on Parametric and Non-Parametric Techniques" Tijani A.A (2006), "Ana~vsis of the technical efficiency of rice farms in Jjesha Land of Osun State, Nigeria", Agrekon, Vol.45, No.2 Timmer C.P (20 I0), "The Changing Role of Rice in Asia's Food \'ecurity ", ADB Sustainable Development Working Paper, No.15, September 20 I USDA (20 11 ), "Grain: World Markets and Trade", Foreign Agricultural Service Circular Series FG 10-11, October 2011 Winsten, C B (1957), "Discussion on lvfr Farrell's Paper", Journal of the Royal Statistical Society Series A (120), 282- 284 in Porcelli F (2009), "Measurement of Technical Efficiency A Brief Survey on Parametric and Non-Parametric Techniques" • 68 APPENDIX APPENDIX A: MATRIX OF CORRELATION BETWEEN VARIABLES IN STOCHASTIC FRONTIER PRODUCTION FUNCTION lnFLA lnFLA lnHLA lnARFA lnFSEED lnBSEED lnFERT lnHERB lniNSECT lnCAPITAL lnHIRED_MACIDNE lnHIRED CATILE In FUEL lnHLA lnARFA lnFSEED lnBSEED lnFER.T In In lnHIRED lnHIRED lnHERB INSECT CAPITAL MACHINE CATTLE lnFUEL 1.00 -0.15 1.00 O.o7 0.46 0.20 0.43 0.31 0.43 0.38 -0.07 0.34 0.07 0.24 0.05 0.06 -0.03 -0.09 -0.10 0.27 -0.19 -0.04 -0.01 1.00 0.45 0.77 0.56 0.55 0.54 0.18 0.36 -0.02 0.42 1.00 0.32 0.12 0.24 0.15 0.12 0.07 -0.01 0.23 1.00 0.50 0.51 0.49 0.17 0.34 0.01 0.35 69 1.00 0.46 0.67 0.06 0.47 -0.01 0.30 1.00 0.54 0.00 0.42 0.07 0.30 1.00 -0.07 0.50 0.02 0.31 1.00 -0.28 -0.14 0.22 1.00 -0.07 0.12 1.00 -0.02 1.00 - - APPENDIX B: STOCHASTIC FRONTIER PRODUCTION FUNCTION Stoc Frontier normaVhalf-normal model Log likelihood Nwnber ofobs Wald chi2(12) Prob > chi2 363 4,691 98,534 0.00 Coef StdErr z 0.003 0.004 0.9 0.001 0.005 4.0 0.837 0.006 132.8 -0.004 0.001 -2.7 0.014 0.004 3.1 0.091 0.004 25.0 0.028 0.002 11.9 0.010 0.002 5.0 0.009 0.002 5.6 0.015 0.001 10.9 0.007 0.001 4.4 -0.002 0.001 -2.0 0.113 0.046 2.5 0.319 0.006 0.118 0.004 Likelihood-ratio test ofsigrna_u=O: clubar2(01) = 4.4e+02Prob>=clubar2 = loY lnFLA lnlllA lnAREA lnFSEED loB SEED lnFERT loiN SECT lnHERB lnFUEL lnHIRED MACHINE lnHIRED CATTLE lnCAPITAL - cons sigrna_u sigrna2 70 P>lzl 0.39 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.05 0.01 0.000 APPENDIX C: WALD TESTS FOR THE SIGNIFICANCE INDIVIDUAL VARIABLES IN STOCHASTIC FRONTIER MODEL Ho: ~7 = J-Io: ~I= • [lnY]lnFLA = chi2(1) = 0.73 Prob > chi2 = 0.3914 [lnY]lniNSECT = chi2(1) = 141.71 Prob > chi2 = 0.0000 Ho Ho: ~8 = :~2 = [lnY]lnHLA = chi2(1) = 16.25 Prob > chi2 = 0.0001 [InY]lnHERB = chi2(1)= 25.23 Prob > chi2 = 0.0000 Ho: ~3 Ho: ~9 = [InY]lnAREA = chi2(1) =17626.81 Prob > chi2 = 0.0000 [lnY]lnFUEL = chi2(1) = 1.11 Prob > chi2 = 0.0000 Ho: ~4 = Ho: ~10 = = [lnY]lnFSEED = chi2(1) = 7.34 Prob > chi2 = 0.0067 [lnY]InHIRED_MACHINE= chi2(1) = 118.76 Prob > chi2 = 0.0000 Ho: ~5 = 1-Io: ~II= 0 [lnY]InBSEED = chi2(1) = 9.58 Prob > chi2 = 0.0020 [lnY]InHIRED_CATTLE= chi2(1)= 19.57 Prob > chi2 = 0.0000 Ho: ~6 = Ho: ~12 = 0 [lnY]lnFERT = chi2(1) = 626.28 Prob > chi2 = 0.0000 [lnY]InCAPITAL = chi2(1) = 3.83 Prob > chi2 = 0.0504 71 OF APPENDIX D: WALD TEST FOR CONSTANT RETURN TO SCALE Ho: sum of all coefficients = chi2(1) 6.31 Prob > chi2 0.0120 72 APPENDIX E: MA TRlX OF CORRELA TlON BETWEEN VARlABLES IN EFFICIENCY MODEL ~ timeLUR CER RATIO AVE NAIR MC IR MN_IR PPRO CRE SCH SEX AGE EXPERIENCE RRD MRD EXPE RIEN CER timeLUR RATIO AVE NAIR MC IR MN IR PPRO CRE SCH SEX AGE CE RRD MRD 1.00 0.53 -0.01 0.06 0.00 0.03 -0.08 0.00 0.04 -0.01 0.14 0.07 -0.07 0.06 1.00 0.01 0.09 0.04 0.02 -0.08 0.01 0.05 -0.04 0.13 0.06 -0.06 0.14 1.00 -0.11 0.06 -0.08 -0.02 0.13 -0.12 0.05 0.02 -0.02 -0.20 0.37 1.00 -0.68 -0.16 -0.01 -0.04 0.05 -0.01 -0.02 0.02 -0.06 -0.15 1.00 1.00 -0.02 -0.01 0.09 -0.02 -0.01 -0.03 0.15 -0.10 -0.13 -0.12 0.00 0.07 -0.04 0.11 -0.05 0.22 0.28 73 1.00 0.05 -0.16 -0.02 -0.07 0.07 -0.11 -0.09 1.00 -0.06 0.05 -0.07 0.02 -0.16 0.14 1.00 0.18 -0.18 -0.15 0.26 -0.19 1.00 -0.21 -0.12 -0.04 -0.02 1.00 0.29 0.05 0.11 1.00 -0.08 1.00 -0.06 -0.25 1.00 APPENDIX F: VARIANCE INFLATION FACTOR AND TOLERANCE OF VARIABLES IN EFFICIENCY MODEL • Variable MC IR NA_IR MRD CER RATIO timeLUR RRD MN_IR SCH AGE AVE EXPERIENCE SEX PPRO CRE MeanVIF lNIF 0.36 0.41 0.67 0.68 0.70 0.73 0.78 0.80 0.81 0.82 0.87 0.91 0.93 0.95 VIF 2.80 2.42 1.50 1.47 1.43 1.37 1.28 1.25 1.24 1.21 1.15 1.09 1.08 1.06 1.45 ' 74 APPENDIX G: OLS MODEL OF TECHNICAL EFFICIENCY DETERMINANTS Number of obs F(l4, 4674) Prob > F R-squared Adj R-squared RootMSE Linear regression • TElOO timeLUR CER_RATIO AVE NA_IR MC_IR MN_IR CRE PPRO SEX AGE SCH EXPERIENCE RRD MRD cons Coef 0.07 0.57 0.00 7.04 8.30 5.49 0.49 -1.83 0.94 0.00 0.25 0.00 3.20 -0.65 69.14 Std Err 0.03 0.49 0.00 0.57 0.60 1.06 0.42 0.69 0.45 0.01 0.05 0.01 0.42 0.56 0.98 t 2.24 1.17 -1.24 12.38 13.73 5.20 1.15 -2.66 2.11 0.19 4.79 -0.12 7.65 -1.16 70.64 4,689.00 41.80 0.00 0.11 0.11 10.93 P>lt 0.03 0.24 0.21 0.00 0.00 0.00 0.25 0.01 0.04 0.85 0.00 0.91 0.00 0.24 0.00 APPENDIX H: TEST FOR HETEROSKEDASTICITY OF EFFICIENCY MODEL ' • Breusch-Pagan I Cook- Weisberg test for heteroskedasticity Ho: Constant variance Variables: fitted values ofTE1 00 chi2(1) = 668.15 Prob > chi2 = 0.0000 75 APPENDIX 1: OLS - ROBUST MODEL OF TECHNICAL DETERMINA TS Linear regression ' • TElOO time OLD CER RATIO AVE NAIR MC IR MN IR CRE PPRO SEX AGE SCH EXPERIENCE RRD MRD cons Coef 0.07 0.57 0.00 7.04 8.30 5.49 0.49 -1.83 0.94 0.00 0.25 0.00 3.20 -0.65 69.14 Robust Std Err 0.03 0.52 0.00 0.69 0.69 1.02 0.46 0.86 0.45 0.01 0.06 0.01 0.35 0.65 1.19 ' • 76 Number ofobs F( 14, 4674) Prob > F R-squared RootMSE 4689 35.26 0.00 0.11 10.93 t 2.16 1.09 -0.66 10.20 11.96 5.41 1.05 -2.11 2.08 0.18 4.39 -0.12 9.17 -1.00 58.31 P>ltl 0.03 0.28 0.51 0.00 0.00 0.00 0.29 0.04 0.04 0.85 0.00 0.91 0.00 0.32 0.00 EFFICIENCY APPENDIX J: WALD-TEST FOR THE SIGNIFICANCE OF INDIVIDUAL VARIABLES IN TECHNICAL EFFICIENCY MODEL Ho:8,=0 ' [TEIOO]timeOLD = F(l, 4674) = 4.66 Prob > F = 0.031 Ho: 8g = [TElOO]PPRO = F(l, 4674) = 4.47 Prob > F = 0.0346 Ho:82 = [TElOO]CER_RATIO = F(l,4674)= 1.19 Prob > F = 0.2753 Ho:89 = [TEl OO]SEX = F(l, 4674) = 4.31 Prob > F = 0.0379 Ho: 83 = [TEIOO]A VE = F(l, 4674) = 0.44 Prob > F = 0.5083 Ho:8w=O [TEl OO]AGE = F(l, 4674) =0.03 Prob > F = 0.8538 Ho: 84 = [TEl OO]NA_IR = F(l, 4674) = 104.01 Prob > F = 0.000 Ho: 811 = [TElOO]SCH = F(l, 4674) = 19.26 Prob > F = 0.000 Ho:8s = [TE100]MC_IR= F(l, 4674) = 143.1 Prob > F = 0.000 Ho:812=0 [TE100]EXPERIENCE = F(l, 4674) = 0.01 Prob > F = 0.9058 Ho: 86 = [TE100]MN_IR= F(l, 4674) = 29.24 Prob > F = 0.000 Ho:813=0 RRD=O F(l, 4674) = 84.05 Prob > F = 0.000 Ho: 87 = [TElOO]CRE = F(l, 4674) = 1.11 Prob > F = 0.2919 IP·f,14=0 I"()· ,~'!RD = F(l, 4674) = 1.01 Prob > F = 0.3159 77 ... determinants of rice production in Vietnam The analysis employs the Vietnam Household Living Standard Survey 2008 data set and stochastic production frontier approach The mean technical efficiency. .. applies stochastic frontier approach to analysis technical efficiency of rice farming 2.3 Stochastic Frontier Analysis Framework 2.3.1 Stochastic Frontier Model Aigner et a! (1977), Meeusen and Broeck... the total cultivated land in estimating the efficiency model Average of land parcel Kompas (2009) used the average land size of farm in province data to evaluate the impact of land fragmentation