Technical efficiency of poultry farms in vietnam non parametric and parametric approaches

VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS TECHNICAL EFFICIENCY OF POULTRY FARMS IN VIETNAM NON-PARAMETRIC AND PARAMETRIC APPROACHES BY NGUYỄN THỊ NGỌC LINH MASTER OF ARTS IN DEVELOPMENT ECONOMICS HO CHI MINH CITY, DECEMBER 2013 VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS TECHNICAL EFFICIENCY OF POULTRY FARMS IN VIETNAM NON-PARAMETRIC AND PARAMETRIC APPROACHES A thesis submitted in partial fulfilment of the requirements for the degree of MASTER OF ARTS IN DEVELOPMENT ECONOMICS BY NGUYỄN THỊ NGỌC LINH Academic Supervisor: DR TRƢƠNG ĐĂNG THỤY Ho Chi Minh City, December 2013 DECLARATION This is to certify that the thesis entitle “Technical efficiency of Vietnam poultry farms: non-parametric and parametric approaches”, which is submitted by me in partial fulfillment of the requirement for the degree of Master of Art in Development Economic to Vietnam – The Netherlands Programme The thesis comprises only my original work and due supervision and acknowledgement have been made in the text to all materials used Nguyễn Thị Ngọc Linh i ACKNOWLEDGEMENT My appreciation firstly goes to my supervisor, Dr Trƣơng Đăng Thụy, who has made a great effort to support me in this thesis His profound comments have been helpful not only in completing this study but also in improving my knowledge in doing the research I would like to thank my family, especially my mother I would not complete this thesis, as well as study in this program, without their scarification, encouragement and important support For the love and expectation of my family, which motivate my effort to complete this master degree, my mere expression of gratitude here have never been sufficient I am very proud to attend this program I am grateful to all lectures in Vietnam – Netherlands Programme for their dedicated instruction and all the courses during the period I studied at the program Besides, I would like to thank all the academic and technical staffs of the Vietnam – Netherlands Programme for supporting me during that time Moreover, I received the enormous encouragement from my classmates and workmates, especially my special friend who has supported me a lot in the writing process I am very grateful for everything that all of you gave me ii ABBREVIATION AE Allocative efficiency BCC DEA model as study of Banker, Charnes and Cooper CCR DEA model as study of Charnes, Cooper and Rhodes CRS Constant returns to scale DEA Data Envelopment Analysis DMU Decision making unit DPF Deterministic Production Function FAO Food and Agriculture Organization GSO General Statistic Office ML Maximum likelihood MLE Maximum likelihood estimate OLS Ordinary Least Square PDF Probability density function SFM Stochastic Frontier Model TE Technical efficiency VHLSS Vietnam Household Living Standards Survey VND Vietnam Dong VRS Variable returns to scale iii ABSTRACT This study attempts to estimate the technical efficiency as well as determine the factorial effects of technical efficiency level of Vietnam poultry farms under semiindustrial system and traditional system Then, this study employs a two-stage analysis with a household-level dataset in whole country In particular, the first stage estimates technical efficiency level of poultry farms under both systems through non-parametric and parametric approaches, which were represented by Data Envelopment Analysis and Stochastic Frontier Analysis, respectively In the second stage, sources of efficiency will be determined by Tobit regression and least square regression with householdspecific characteristics which represent for human capital in qualitative dimension A sample of 3,356 households in VHLSS 2010 is utilized to analyze the broiler poultry production in Vietnam, wherein 820 poultry farms under semi-industrial system and 2,536 poultry farms under traditional system The results from the first stage show that the average technical efficiency which was obtained from SFM is higher than that in DEA; and the TE scores in SFA exhibit the variability lower than TE scores in DEA Moreover, from the analysis in the second stage, it is can be stated that education level of farmer has significantly effects on the TE differential among poultry farms in the positive way Finally, the results also show that TE scores of poultry farms under both systems located in the Southeast are higher than other agro-ecological regions Keywords: poultry household, data envelopment analysis, stochastic frontier model, technical efficiency, human capital iv TABLE OF CONTENTS CHAPTER 1: INTRODUCTION 1.1 Problem Statements 1.2 Research Objectives 1.3 Research Organization CHAPTER 2: LITERATURE REVIEW 2.1 Basic concepts of efficiency 2.2 Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) 2.2.1 Data Envelopment Analysis (DEA) .10 2.2.2 Stochastic Frontier Model approach (SFM) 12 2.2.2.1 The Production frontier 12 i Deterministic Production Frontier 12 ii Stochastic Production Frontier 13 2.2.2.2 Estimation method 15 i Modified Ordinary Least Squares (MOLS) 15 ii Maximum likelihood Estimation (MLE) 16 2.2.2.3 Measurement of Efficiency 17 2.2.3 Comparison between DEA and SFM approaches .17 2.3 Empirical studies 19 2.3.1 Measurement of technical efficiency of poultry subsector 19 2.3.2 DEA and SFM approaches on measurement of technical efficiency of agriculture sector 22 2.3.3 Impact of human capital on agriculture productivity 24 CHAPTER 3: OVER VIEW OF POULTRY FARMS IN VIETNAM 27 3.1 General characteristics of poultry production in Vietnam 27 3.2 Poultry production system in Vietnam 29 i Traditional extensive household poultry production (non-intensive system) 31 ii Semi-industrial commercial poultry production (semi-intensive) 32 iii Industrial poultry production (intensive system) .32 v CHAPTER 4: DATA DESCRIPTIONS AND RESEARCH METHODOLOGY 34 4.1 Data Description 34 4.1.1 Data Source 34 4.1.2 Data Descriptions 34 4.2 Method, Model specification and Variables definition .36 4.2.1 The first stage: Measurement of Technical efficiency 36 4.2.1.1 Measurement of Technical efficiency using Data Envelopment Analysis 36 4.2.1.2 Measurement of Technical efficiency using Stochastic Frontier Model 38 i Production function specification 39 ii Estimation method specification 40 4.2.1.3 Variables Description for the first stage 41 4.2.1.4 Hypothesis testing 44 i Functional form specification test 45 ii Estimating method specification test 45 4.2.2 The second stage: Factorial decomposition of Technical efficiency 46 4.2.2.1 The Technical efficiency model 46 4.2.2.2 Variables description for the second stage 49 4.2.3 Research Hypotheses 53 CHAPTER 5: EMPIRICAL RESULTS AND DISSCUSION .54 5.1 The first stage: The estimation of the Technical efficiency scores .54 5.1.1 Testing null hypotheses for SFM approach in the first stage .54 i The Production Functional form specification test 55 ii The model specification test 57 5.1.2 Discussion on results obtained from the first stage 58 5.1.2.1 Comparing the Technical efficiency scores in SFM and DEA approaches 58 5.1.2.2 The distribution of technical efficiency scores in SFM and DEA approaches 60 5.1.2.3 Technical efficiency varies between agro-ecological regions .63 vi 5.2 The second stage: The determinants of Technical efficiency 65 5.2.1 Testing the significant of coefficients simultaneously for regressions 65 5.2.2 Discussion on the results obtained from the second stage 66 5.2.2.1 The effects of human capital on technical efficiency scores 67 5.2.2.2 The difference of technical efficiency scores between various agroecological regions 69 CHAPTER 6: CONCLUSION AND POLICY IMPLICATION 70 6.1 Concluding remarks 71 6.2 Policy implications .72 6.3 Limitations of study and recommendations for future research 73 REFERENCES .74 Appendix 1: Matrix of correlation between variables in Stochastic frontier production function of semi-industrial poultry farms .78 Appendix 2: Matrix of correlation between variables in Stochastic frontier production function of traditional poultry farms 78 Appendix 3: Matrix of correlation between variables in technical efficiency model of semi-industrial poultry farms .79 Appendix 4: Matrix of correlation between variables in technical efficiency model of traditional poultry farms .79 Appendix 5: OLS regression of technical efficiency model of traditional poultry farms 80 Appendix 6: Testing heteroskedasticity for OLS regression of technical efficiency model of traditional poultry farms 80 Appendix 7: Testing heteroskedasticity for OLS-robust regression of technical efficiency model of traditional poultry farms .81 Appendix 8: Summary of Empirical Studies at measuring technical efficiency of poultry sector 82 Appendix 9: Summary empirical studies of comparison DEA and SFM approaches at measuring the technical efficiency .84 vii LIST OF TABLES Table 4-1: Summary statistic of broiler poultry productivity of farms between regions and within systems 35 Table 4-2: Summary statistic of Input and Output variables for Poultry farms under semi-industrial system and traditional system 42 Table 4-3: Statistical description of determinant factors of technical efficiency level 52 Table 5-1: Maximum-likelihood estimates of the Cobb-Douglas and Translog stochastic production frontier models 56 Table 5-2: Tests hypotheses of the production function specification 58 Table 5-3: Summarizing the technical efficiency scores 59 Table 5-4: The technical efficiency distribution in SFM and DEA-BCC 61 Table 5-5: Technical efficiency scores among agro-ecological regions 63 Table 5-6: The factorial effects on technical efficiency scores from SFM and DEABCC 66 LIST OF FIGURES Figure 2-1: Technical efficiency and Allocative Efficiency Figure 2-2: Stochastic Production Frontier 14 Figure 3-1: Growth rate of livestock and poultry with base year of 1990 27 Figure 3-2: Annual growth rate of number of poultry with base year of 1990 28 Figure 3-3: Poultry density of Vietnam in 2006 29 Figure 3-4: Average number of birds per household in 2001 29 Figure 3-5: Regional Characteristics of poultry-holding household in 2002 30 Figure 3-6: Proportion of total chicken in three production systems in 2006 and 2009 in Vietnam 33 Figure 5-1: The distribution of TE scores of semi-industrial and traditional systems from SFM and DEA approaches 62 Figure 5-2: Technical efficiency scores between agro-ecological regions 64 viii of Vietnam Although education level trivially influences on the TE level of semi-industrial poultry farms, investing in rural education is also recommended to facilitate the adaptation of new technology as well as new breeds of poultry because it leads to the enhancement of the TE level of poultry farms Finally, the result shows that the agricultural training program seems inefficient However, the technical support program for farmers is necessary to adapt new technology for poultry and for agriculture sector in general Hence, policy makers should consider improving the quality of these programs 6.3 Limitations of study and recommendations for future research Although this study could provide some implications above, it still has several limitations as follows Firstly, in the analysis of the first stage and the second stage, the production function and technical efficiency function could not take all socio-economic factors into account due to the lack of data Some missing variables should be corrected in further studies to achieve better results Secondly, the breed of poultry should also be considered because breed of poultry is an important factor to determine productivity of farms The local poultry breeds are less productivity than those which were imported from abroad, while traditional poultry farms tend to raise poultry with local breeds However, the data not have information for the breeds of poultry that farmers raised under both systems This problem could be considered in later research, then, the results will be more consistent Finally, this study does not provide a complete comparison in all aspects of production efficiency; it focuses only in pure technical efficiency These problems are expected to be solved in the future studies In conclusion, although this study still faces some limitations, it is expected to make significant contribution to the empirical study on measuring technical efficiency of poultry sector in Vietnam Furthermore, this study also expects to contribute to the interesting research methodology which employs two alternative methods including non-parametric and parametric approaches to measure technical efficiency in agriculture sector 73 REFERENCES Afriat, S N (1972) Efficiency estimation of production functions International Economic Review, 13(3), 568-598 Aigner, D J., & Chu, S F (1968) On estimating the industry production function The American Economic Review, 58(4), 826-839 Aigner, D J., Lovell, C A L., & Schmidt, P (1977) Formulation and estimation of stochastic frontier 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Point Q and Q’ lie on the SS’ curve; hence, these points are technical efficiency points while point P indicates the technical inefficiency point The distance QP indicates for amount of waste input