FARM-LEVEL ECONOMIC IMPACT OF ECOLOGICALLY-BASED RODENT MANAGEMENT IN AN INTENSIVE IRRIGATED RICE SYSTEM: THE CASE STUDY OF RICE FARMING IN THE MEKONG RIVER DELTA, VIETNAM HO NGOC NINH SUBMITTED TO THE FACULTY OF GRADUATE SCHOOL UNIVERSITY OF THE PHILIPPINES LOS BAÑOS IN PARTIAL FULFILLMENT OF THE REQUIREMENT FOR THE DEGREE OF DOCTOR OF PHILOSOPHY (Agricultural Economics) ii APRIL 2013 Trường ðại học Nông nghiệp Hà Nội – Luận án tiến sỹ khoa học Nông nghiệp ……………………… ii BIOGRAPHICAL SKETCH The author was born on September 02, 1982 in Huong Son district, Ha Tinh Province, Vietnam He is the fourth child of Ho Viet Luong and Nguyen Thi Tan He graduated with a Bachelor of Science in Agricultural Economics from Hanoi University of Agriculture, Vietnam in 2005 He has worked as a lecturer at the Department of Quantitative Analysis, Faculty of Economics and Rural Development, Hanoi University of Agriculture (HUA) since 2006 In 2009, he was awarded a scholarship grant funded by the World Bank and Ministry of Education and Training of Vietnam through the Training and Research Improvement Grant Project of HUA (TRIG-HUA), which enabled him to pursue his Master of Science in Agricultural Economics at the Department of Agricultural Economics, College of Economics and Management, University of the Philippines Los Baños (UPLB) His academic performance had been outstanding having obtained an overall average grade of 1.125 from all the graduate courses that he took during the first and second semesters, SY 2009-2010 leading to a Master of Science degree in Agricultural Economics Considering that his overall weighted average grade met the academic requirement for the straight Doctor of Philosophy (PhD) program, he continued to pursue his PhD degree in Agricultural Economics since the first semester of SY 2010-2011 under the TRIG-HUA Scholarship grant In June 2011, the Southeast Asian Regional Center for Graduate Study and Research in Agriculture (SEARCA) granted him a scholarship grant to enable him to continue his straight Ph.D degree in Agricultural Economics at UPLB In March 2012, he was awarded a PhD dissertation research grant by the Irrigated Rice Research Consortium (IRRC) through the Social Sciences Division (SSD), International Rice Research Institute (IRRI) He is happily married to Lai Phuong Thao and blessed with a lovely daughter, Ho Ngoc Phuong HO NGOC NINH Trường ðại học Nông nghiệp Hà Nội – Luận án tiến sỹ khoa học Nông nghiệp ……………………… iii ACKNOWLEDGEMENT I wish to express my since rest gratitude and appreciation to the following people to make the completion of this research work possible: To Dr Corazon T Aragon, my academic advisor and chair of my Advisory Committee and Dr Florencia G Palis, co-major adviser, for their encouragement, invaluable advice, heartfelt guidance, and wholehearted supports to finish the study To Dr Flordeliza A Lantican, Dr Zenaida M Sumalde, and Dr Ma Victoria O Espaldon, members of my Advisory Committee, for their valuable suggestions and constructive comments, and encouragement to improve the quality of this study I would like to extend my gratitude and appreciation to Dr Roderick M Rejesus, for answering my queries related to my research and for providing invaluable advice I also would like to extend my appreciation to Dr Grant R Singleton, Coordinator of IRRC, IRRI, for allowing me to utilize the EBRM Project data and for his invaluable contributions to the development of this research To the staff of the College of Economics and Management (CEM); School of Environmental Science & Management; the UPLB Graduate School; the UPLB Foundation Inc.; the Social Sciences Division (SSD) and the Training Center of IRRI, for their kind help, support and good services To the local authorities and officers at the Plant Protection Subdivision, and the Department of Agriculture and Rural Development in An Giang Province, for their cooperation in providing me the needed information Special thanks also to Ms Truong Thi Ngoc Chi for her help in data collection To the World Bank and the Ministry of Education and Training of Vietnam, and the management and the staff of the TRIG-HUA, for granting full financial support to enable me to pursue my M S degree and partial financial support for my Straight PhD Program To the Southeast Asian Regional Center for Graduate Study and Research in Agriculture (SEARCA), for granting a scholarship to enable me to continue my straight PhD Program, especially to Dr Gil C Saguiguit, Jr., Director and Dr Editha C Cedicol, Head of the Graduate Scholarship Department (GSD) I would like also to express my gratitude to all the staff of GSD for responding to all my scholarship-related requests so graciously To Dr Tran Duc Vien, Rector; Dr Vu Van Liet, Vice-Rector, of Hanoi University of Agriculture; Dr Do Kim Chung, former Dean; Dr Tran Dinh Thao, current Dean; Dr Nguyen Thi Minh Hien, and Dr Nguyen Van Song, Deputies, of the Faculty of Economics and Rural Development; Dr Pham Van Hung, former Head; Dr Nguyen Thi Duong Nga, current Head; and Dr Nguyen Tuan Son, of the Department of Quantitative Analysis, for their logistical and moral encouragement and valuable advice for the pursuit of my Ph.D degree To all my colleagues and professors at the Department of Quantitative Analysis for their encouragement and to those who took over my academic responsibilities during my study leave To Dr Tuong, Dr Vinh and their families, as well as, all my Vietnamese and international friends at UPLB and IRRI, for their understanding, encouragement, and full support during the period of my study; and special thanks to Ms Trina Leah T Mendoza for editing my dissertation manuscript To my dear parents Ho Viet Luong and Nguyen Thi Tan; my dear parents-in-law Lai Huy Binh and Vu Thi Thu Huong; my dear grandmother-in-law Nguyen Thi Chat; my dear uncles and uncles-in-law and their families; my dear brothers, sisters and their families; and my dear brother-in-law, who were sources of my inspiration, for their support, encouragement, patience, understanding, and for taking care of my wife and daughter during the period of my graduate study; and Trường ðại học Nông nghiệp Hà Nội – Luận án tiến sỹ khoa học Nông nghiệp ……………………… iv Finally, to my beloved wife Lai Phuong Thao, and my wonderful daughter, Ho Ngoc Phuong, for their love, patience, sacrifices, support and understanding, to whom this research work is dedicated TABLE OF CONTENTS CHAPTER I II PAGE Title Page i Approval Page ii Biographical Sketch iii Acknowledgement iv Table of Contents v List of Tables ix List of Figures xvii List of Appendix Tables xix List of Appendix Figures xxiii Abstract xxiv INTRODUCTION 1.1 Background of the study 1.2 Statement of the Problem 1.3 Objectives of the Study 10 1.4 Significance of the Study 11 REVIEW OF LITERATURE 12 2.1 Ecologically-Based Rodent Management 12 2.1.1 Empirical Studies Related to the Evolution of EcologicallyBased Rodent Management 12 2.1.2 Empirical Studies on Ecologically-Based Rodent Management in Other Countries 14 2.1.3 Empirical Studies on Ecologically-Based Rodent Management in Vietnam 23 Trường ðại học Nông nghiệp Hà Nội – Luận án tiến sỹ khoa học Nông nghiệp ……………………… v CHAPTER 2.2 Empirical Studies on Impact Assessment of Agricultural Technology Adoption 2.3 Empirical Studies on Technical, Allocative and Economic Efficiency III IV PAGE 30 34 2.3.1 Empirical Studies on Technical, Allocative and Economic Efficiency of Rice Farmers in Other Countries 34 2.3.2 Empirical Studies on Technical, Allocative and Economic Efficiency of Rice Farmers in Vietnam 46 THEORICAL AND CONCEPTUAL FRAMEWORK 53 3.1 Theoretical Framework 53 3.1.1 Concepts and Models for Impact Assessment Using Panel Data 53 3.1.2 Concepts and Models for Estimating Technical, Allocative, Economic Efficiency 68 3.2 Conceptual Framework 77 3.3 Hypotheses of the Study 84 RESEARCH METHODOLOGY 86 4.1 Sampling Design 86 4.1.1 Selection of the Study Area 86 4.1.2 Selection of the Sample Rice Farmer-Respondents 89 4.2 Types of Data and Methods of Data Collection 91 4.3 Methods of Analysis 93 4.3.1 Descriptive and Trend Analysis 93 4.3.2 Cost and Return Analysis 93 4.3.3 Comparison of Means (T-test) 95 4.3.4 Estimation Procedures and Empirical Specification for Impact Assessment Using Panel Data 96 4.3.5 Analysis of Stochastic Production and Efficiency 103 4.4 Limitations of the Study Trường ðại học Nông nghiệp Hà Nội – Luận án tiến sỹ khoa học Nông nghiệp ……………………… 113 vi CHAPTER V PAGE RESULTS AND DISCUSSION 114 5.1 Characteristics of the Sample Rice Farmer-Respondents and Their Rice Farms 114 5.2 Changes in the Rice Farmers’ Attitudes Towards Rodent Management and Their Rodent Management Practices 124 5.2.1 Dissemination of the EBRM Technology in Vietnam 124 5.2.2 Changes in the Rice Farmers’ Knowledge on Rodent Pest Management 129 5.2.3 Changes in the Rice Farmers’ Attitudes and Beliefs Towards Rats and Rat Management 135 5.2.4 Changes in Rodent Control Practices of the Sample Rice Farmers 138 5.3 Comparison of the Mean Levels of Input Use and Paddy Yield Among the Sample Rice Farmer-Respondents 142 5.3.1 Input Use and Yield Comparison of the Sample Rice Farms Across Study Periods 142 5.3.2 Input Use and Yield Comparison between the Treatment and Control Groups 152 5.3.3 Input Use and Yield Comparison Among the Project Sites 157 5.3.4 Input Use and Yield Comparison by Rice Variety 160 5.3.5 Input Use and Yield Comparison between Farm Size Groups 162 5.4 Cost and Return Analysis 164 5.4.1 Change in the Profitability of Rice Production over Time 164 5.4.2 Profitability Comparison between the Treatment and Control Groups 175 5.4.3 Profitability Comparison between Improved and Conventional Varieties 184 Trường ðại học Nông nghiệp Hà Nội – Luận án tiến sỹ khoa học Nông nghiệp ……………………… vii CHAPTER 5.4.4 Profitability Comparison between Farm Size Groups 5.4.5 Profitability Comparison Among Project Sites 188 5.5 Impact of Ecologically-Based Rodent Management on Rice Yield and Income of Its Beneficiaries 190 5.5.1 Propensity Score Matching Results 191 5.5.2 Results of Estimated Average Impacts of the EBRM Technology and Its Components on Rice Yield and Income of the Beneficiaries 197 5.6 Estimated Impact of the EBRM Technology and Its Components on Technical Efficiency of the Beneficiaries 230 5.6.1 Selection of the Most Appropriate Stochastic Frontier Model 231 5.6.2 Factors Affecting Rice Output Per Farm and Determinants of Technical Inefficiency 235 5.6.3 Comparison of Technical Efficiency Levels between EBRM Farmers and Control Farmers 250 5.7 Estimated Impact of the EBRM Technology and Its Components on Allocative and Economic Efficiency VI PAGE 186 258 5.7.1 Allocative Efficiency of the Sample Rice Farmers 259 5.7.2 Economic Efficiency of the Sample Rice Farmers 264 SUMMARY, CONCLUSIONS AND RECOMMENDATIONS 270 6.1 Summary and Conclusions 270 6.2 Policy Recommendations 285 LITERATURE CITED 291 APPENDICES 302 Trường ðại học Nông nghiệp Hà Nội – Luận án tiến sỹ khoa học Nông nghiệp ……………………… viii Trường ðại học Nông nghiệp Hà Nội – Luận án tiến sỹ khoa học Nông nghiệp ……………………… ix 325 Appendix Table 23 MLE of the Cobb-Douglas stochastic production and technical inefficiency functions for Model before and after the implementation of the EBRM Project, using the CA unmatched and kernel matched samples in An Giang Province, Mekong River Delta, Vietnam VARIABLE SYMBOL VARIABLE NAME Frontier Production Function Constant ln A Area ln S Seed ln L Labor ln N Nitrogen ln P Phosphate ln K Potash ln Pest Pesticides Vart Variety dummy CA CA dummy t Time dummy Technical Inefficiency Function Constant Z1 Gender dummy Z2 Household size Knowledge index Z3 Farming experience Z4 Educational attainment Z5 Distance (field-house) Z6 Z7 Membership dummy Z8 Cropping intensity dummy Z9 Farm size dummy Z10 Location dummy Variance Parameter σ2 sigma-squared γ gamma Log-likelihood function LR test of the one-sided error Mean technical efficiency (%) PARAMETER UNMATCHED SAMPLE Std Coefficient Error MATCHED SAMPLE Std Coefficient Error β0 β1 8.062*** 0.916*** 0.127 0.027 8.049*** 0.914*** 0.136 0.029 β2 β3 β4 β5 β6 β7 β8 β9 θ 0.040*** 0.027ns* 0.025*** 0.001ns* 0.002ns* -0.001ns* 0.002ns* 0.102*** 0.061*** 0.016 0.022 0.008 0.002 0.002 0.003 0.005 0.005 0.007 0.041*** 0.030ns* 0.025*** 0.001ns* 0.003ns* -0.001ns* 0.002ns* 0.102*** 0.062*** 0.017 0.023 0.008 0.002 0.002 0.003 0.005 0.005 0.007 δ0 δ1 δ2 δ3 δ4 δ5 δ6 δ7 δ8 δ9 δ10 0.148*** -0.020*** 0.001ns* -0.153*** 0.000ns* -0.002*** 0.009*** -0.020*** -0.021ns* -0.002ns* 0.028*** 0.026 0.011 0.002 0.030 0.000 0.001 0.005 0.009 0.015 0.008 0.008 0.151*** -0.020*** 0.001ns* -0.157*** 0.000ns* -0.002*** 0.008ns* -0.021*** -0.021ns* -0.002ns* 0.028*** 0.027 0.011 0.002 0.030 0.000 0.001 0.006 0.009 0.015 0.008 0.008 0.001*** 0.395*** 691.90 90.86 96.96 0.000 0.187 0.0007*** 0.4361*** 670.57 83.20 96.93 0.0001 0.1821 Note: ***, **, and * indicate statistical significance at 1%, 5% and 10% probability level; and ns denotes insignificance at 10% probability level Trường ðại học Nông nghiệp Hà Nội – Luận án tiến sỹ khoa học Nông nghiệp ……………………… 340 326 Appendix Table 24 MLE of the Cobb-Douglas stochastic production and technical inefficiency functions for Model before and after the implementation of the EBRM Project, using the CA unmatched and kernel matched samples in An Giang Province, Mekong River Delta, Vietnam VARIABLE SYMBOL VARIABLE NAME Frontier Production Function Constant ln A Area ln S Seed ln L Labor ln N Nitrogen ln P Phosphate ln K Potash ln Pest Pesticides Vart Variety dummy t Time dummy Technical Inefficiency Function Constant Gender dummy Z1 Z2 Household size PARAMETER UNMATCHED SAMPLE Std Coefficient Error MATCHED SAMPLE Std Coefficient Error β0 β1 7.763*** 0.842*** 0.096 0.024 8.146*** 0.920*** 0.154 0.032 β2 β3 β4 β5 β6 β7 β8 θ 0.079*** 0.085*** 0.016*** 0.003*** 0.001ns* 0.008*** 0.005ns* 0.081*** 0.008 0.023 0.005 0.001 0.002 0.002 0.008 0.008 0.043*** 0.027ns* 0.022*** 0.000ns* 0.002ns* 0.001ns* 0.004ns* 0.066*** 0.019 0.023 0.010 0.002 0.002 0.004 0.007 0.009 δ0 δ1 0.211*** -0.038*** 0.029 0.012 0.1955*** -0.0145ns* 0.0221 0.0099 δ2 0.002ns* 0.002 -0.0004ns* 0.0016 *** 0.030 *** 0.0214 0.000ns* 0.000 0.0001ns* 0.0002 ns* ns* 0.0008 Z3 Knowledge index δ3 Z4 Farming experience δ4 -0.097 -0.0946 Z5 Educational attainment δ5 0.001 0.001 Z6 Distance (field-house) δ6 0.013*** 0.008 0.0060ns* 0.0060 Z7 Membership dummy δ7 -0.010ns* 0.008 -0.0111ns* 0.0072 0.010 ns* 0.0115 ns* Z8 Cropping intensity dummy Z9 Farm size dummy Z10 Location dummy Z11 CA dummy Variance Parameter σ2 sigma-squared γ gamma Log-likelihood function LR test of the one-sided error Mean technical efficiency (%) δ8 δ9 δ10 δ11 -0.009 ns* -0.0012 -0.0175 *** 0.024 0.041*** -0.139*** 0.010 0.009 0.010 0.0039 0.0232*** -0.2194*** 0.0056 0.0057 0.0300 0.001*** 1.000*** 660.215 313.899 0.000 0.000 0.001*** 0.560*** 676.48 374.52 0.000 0.129 86.61 90.45 Note: ***, **, and * indicate statistical significance at 1%, 5% and 10% probability level; and ns denotes insignificance at 10% probability level Trường ðại học Nông nghiệp Hà Nội – Luận án tiến sỹ khoa học Nông nghiệp ……………………… 341 Appendix Table 25 Hypothesis test to determine the presence of technical inefficiency effects (OLS vs MLE) in the CobbDouglas model before and after the implementation of the EBRM Project, using the CA unmatched and kernel matched samples in An Giang Province, Mekong River Delta, Vietnam FRONTIER TEST PARAMETER RESTRICTIONS LOG-LIKELIHOOD GAMMA t-STAT H0 (OLS) H1 (MLE) LLR TEST STATISTIC DOF χ2 CRITICAL VALUE (at 1%) OUTCOME A Using the unmatched sample (N =302) Model H0: γ = δi = 0.395*** 2.11 646.47 691.90 90.86 11 24.05a Model H0: γ = δi = 1.000*** 3065.41 503.27 660.215 313.90 12 25.55a Reject H0, MLE is adequate Reject H0, MLE is adequate B Using the kernel matched sample (N =294) Model H0: γ = δi = 0.436*** 2.395 628.98 670.57 83.195 11 24.05a Model H0: γ = δi = 0.5605*** 4.360 489.22 676.48 374.516 12 25.55a Reject H0, MLE is adequate Reject H0, MLE is adequate Note: N is total numbers of observations/respondents for two survey periods a Critical values obtained from Kodde and Palm table (1986) Model includes CA dummy variable as an explanatory variable in stochastic production function Model includes CA dummy variable as an explanatory variable in technical inefficiency function 342 327 Trường ðại học Nông nghiệp Hà Nội – Luận án tiến sỹ khoa học Nông nghiệp ……………………… Appendix Table 26 Hypothesis test to determine the most appropriate functional form (Cobb-Douglas vs Translog model) before and after the implementation of the EBRM Project, using the CTBS unmatched and kernel matched samples in An Giang Province, Mekong River Delta, Vietnam FUNCTIONAL FORM TEST PARAMETER RESTRICTIONS LOG-LIKELIHOOD H0 (Cobb-Douglass) A Using the unmatched sample (N =316) H1 (Translog) LLR TEST STATISTIC DOF χ2 CRITICAL VALUE (at 1%) Model H0: All βjk =0 770.69 810.42 79.45 33 54.78 Model H0: All βjk =0 774.01 812.82 77.61 30 50.89 OUTCOME Reject H0, Translog is adequate Reject H0, Translog is adequate B Using the kernel matched sample (N =296) Model H0: All βjk =0 724.68 758.35 67.35 33 54.78 Model H0: All βjk =0 727.22 758.71 62.98 30 50.89 Reject H0, Translog is adequate Reject H0, Translog is adequate Note: N is total numbers of observations/respondents for two survey periods a Critical value obtained from the normal χ2 table Model includes CTBS dummy variable as an explanatory variable in stochastic production function Model includes CTBS dummy variable as an explanatory variable in technical inefficiency function 343 328 Trường ðại học Nông nghiệp Hà Nội – Luận án tiến sỹ khoa học Nông nghiệp ……………………… Trường ðại học Nông nghiệp Hà Nội – Luận án tiến sỹ khoa học Nông nghiệp ……………………… 344 329 Appendix Table 27 MLE of the Cobb-Douglas stochastic production and technical inefficiency functions for Model before and after the implementation of the EBRM Project, using the CTBS unmatched and kernel matched samples in An Giang Province, Mekong River Delta, Vietnam VARIABLE SYMBOL VARIABLE NAME Frontier Production Function Constant ln A Area ln S Seed ln L Labor ln N Nitrogen ln P Phosphate ln K Potash ln Pest Pesticides Vart Variety dummy CTBS CTBS dummy t Time dummy Technical Inefficiency Function Constant Gender dummy Z1 Z2 Household size Knowledge index Z3 Z4 Farming experience Z5 Educational attainment Z6 Distance (field-house) Membership dummy Z7 Z8 Cropping intensity dummy Z9 Farm size dummy Location dummy Z10 Variance Parameter σ2 sigma-squared γ gamma Log-likelihood function LR test of the one-sided error Mean technical efficiency (%) PARAMETER UNMATCHED SAMPLE Std Coefficient Error MATCHED SAMPLE Std Coefficient Error β0 β1 8.057*** 0.917*** 0.114 0.025 8.053*** 0.915*** 0.126 0.027 β2 β3 β4 β5 β6 β7 β8 β9 θ 0.049*** 0.022ns* 0.018*** 0.003ns* 0.002*** 0.000ns* -0.002ns* 0.130*** 0.073*** 0.014 0.019 0.007 0.004 0.001 0.003 0.004 0.005 0.006 0.048*** 0.027ns* 0.017*** 0.002ns* 0.001ns* -0.001ns* -0.001ns* 0.132*** 0.073*** 0.014 0.021 0.007 0.004 0.001 0.003 0.004 0.005 0.007 δ0 δ1 δ2 δ3 δ4 δ5 δ6 δ7 δ8 δ9 δ10 0.082*** 0.000ns* -0.001ns* -0.060*** 0.000ns* -0.003*** -0.001ns* -0.003ns* 0.018*** -0.004ns* 0.030*** 0.017 0.008 0.001 0.019 0.000 0.001 0.004 0.004 0.005 0.005 0.004 0.086*** 0.000ns* -0.001ns* -0.060*** 0.000ns* -0.003*** -0.005ns* -0.004ns* 0.020*** -0.005ns* 0.029*** 0.023 0.007 0.001 0.019 0.000 0.001 0.004 0.006 0.006 0.005 0.004 0.0004*** 0.0024*** 770.69 114.57 96.19 0.000 0.004 0.0004*** 0.0057*** 724.68 107.03 96.66 0.0000 0.1122 Note: ***, **, and * indicate statistical significance at 1%, 5% and 10% probability level; and ns denotes insignificance at 10% probability level Trường ðại học Nông nghiệp Hà Nội – Luận án tiến sỹ khoa học Nông nghiệp ……………………… 345 330 Appendix Table 28 MLE of the Cobb-Douglas stochastic production and technical inefficiency functions for Model before and after the implementation of the EBRM Project, using the CTBS unmatched and kernel matched samples in An Giang Province, Mekong River Delta, Vietnam VARIABLE SYMBOL VARIABLE NAME Frontier Production Function Constant ln A Area ln S Seed ln L Labor ln N Nitrogen ln P Phosphate ln K Potash ln Pest Pesticides Vart Variety dummy t Time dummy Technical Inefficiency Function Constant Gender dummy Z1 Z2 Household size PARAMETER UNMATCHED SAMPLE Std Coefficient Error MATCHED SAMPLE Std Coefficient Error β0 β1 β2 β3 β4 β5 β6 β7 β8 θ 8.159*** 0.914*** 0.056*** 0.022ns* 0.018*** 0.002ns* 0.002*** -0.001ns* -0.002ns* 0.074*** 0.157 0.034 0.021 0.028 0.011 0.007 0.001 0.004 0.005 0.008 8.166*** 0.920*** 0.049*** 0.027ns* 0.017*** 0.002ns* 0.002*** -0.001ns* 0.000ns* 0.073*** 0.124 0.027 0.014 0.020 0.007 0.004 0.001 0.003 0.004 0.007 δ0 δ1 δ2 0.214*** 0.000ns* -0.001ns* 0.022 0.012 0.002 0.204*** -0.002ns* -0.001ns* 0.019 0.007 0.001 Z3 Knowledge index δ3 -0.055*** 0.022 -0.063*** 0.020 Z4 Farming experience δ4 0.000ns* 0.000 0.000ns* 0.000 Z5 Education attainment δ5 -0.003*** 0.001 -0.003*** 0.001 ns* 0.006 -0.005 ns* 0.004 0.007 -0.006ns* 0.005 *** 0.008 *** 0.005 -0.001ns* 0.030*** -0.134*** 0.007 0.006 0.006 0.003ns* 0.030*** -0.142*** 0.006 0.004 0.008 0.0005*** 1.0000*** 774.01 507.24 0.000 0.000 0.000*** 0.729*** 727.22 487.82 0.000 0.143 Z6 Distance (field-house) δ6 -0.001 Z7 Membership dummy δ7 -0.003ns* Z8 Cropping intensity dummy Z9 Farm size dummy Z10 Location dummy Z11 CTBS dummy Variance Parameter σ2 sigma-squared γ gamma Log-likelihood function LR test of the one-sided error Mean technical efficiency (%) δ8 δ9 δ10 δ11 0.016 85.91 0.015 87.61 Note: ***, **, and * indicate statistical significance at 1%, 5% and 10% probability level; and ns denotes insignificance at 10% probability level Trường ðại học Nông nghiệp Hà Nội – Luận án tiến sỹ khoa học Nông nghiệp ……………………… 346 Appendix Table 29 Hypothesis test to determine the presence of technical inefficiency effects (OLS vs MLE) in the CobbDouglas models before and after the implementation of the EBRM Project, using the CTBS unmatched and kernel matched samples in An Giang Province, Mekong River Delta, Vietnam FRONTIER PARAMETER TEST RESTRICTIONS LOG-LIKELIHOOD GAMMA t-STAT H0 (OLS) H1 (MLE) LLR TEST STATISTIC DOF χ2 CRITICTBSL OUTCOME VALUE (at 1%) A Using the unmatched sample (N =316) Model H0: γ = δi = 0.002*** 0.54 713.41 770.69 114.57 11 24.05a Model H0: γ = δi = 1.000*** 8003.34 520.39 774.012 507.24 12 25.55a Reject H0, MLE is adequate Reject H0, MLE is adequate B Using the kernel matched sample (N =296) Model H0: γ = δi = 0.006*** 0.051 671.16 724.68 107.031 11 24.05a Model H0: γ = δi = 0.7294*** 5.109 483.31 727.22 487.820 12 25.55a Reject H0, MLE is adequate Reject H0, MLE is adequate Note: N is total numbers of observations/respondents for two survey periods a Critical values obtained from Kodde and Palm table (1986) Model includes CTBS dummy variable as an explanatory variable in stochastic production function Model includes CTBS dummy variable as an explanatory variable in technical inefficiency function 331 Trường ðại học Nông nghiệp Hà Nội – Luận án tiến sỹ khoa học Nông nghiệp ……………………… 347 Appendix Table 30 Pearson correlation results for the Cobb-Douglas production function for Model 2, 216 rice farmers using the EBRM kernel matched sample, An Giang Province, Mekong River Delta, Vietnam, 2006 and 2009 VARIABLE A S L N P K PEST VART T 1.000 0.984 0.983 0.966 0.913 0.847 0.745 -0.007 -0.067 0.000 0.000 0.000 0.000 0.000 0.000 0.877 0.164 1.000 0.985 0.951 0.893 0.825 0.765 -0.003 -0.149 0.000 0.000 0.000 0.000 0.000 0.950 0.002 1.000 0.951 0.888 0.833 0.746 0.028 -.183 0.000 0.000 0.000 0.000 0.567 0.000 1.000 0.930 0.788 0.700 0.004 -0.1020 0.000 0.000 0.000 0.941 0.035 1.000 0.733 0.588 0.006 -0.049 0.000 0.000 0.899 0.314 1.000 0.633 -0.052 -0.020 0.000 0.280 0.685 1.000 0.006 -0.113 0.908 0.018 1.000 -0.268 For Production Function Analysis: A Pearson Correlation Sig (2-tailed) S L N P K PEST VART T Pearson Correlation 0.984 Sig (2-tailed) 0.000 Pearson Correlation 0.983 0.985 Sig (2-tailed) 0.000 0.000 Pearson Correlation 0.966 0.951 0.951 Sig (2-tailed) 0.000 0.000 0.000 Pearson Correlation 0.913 0.893 0.888 0.930 Sig (2-tailed) 0.000 0.000 0.000 0.000 Pearson Correlation 0.847 0.825 0.833 0.788 0.733 Sig (2-tailed) 0.000 0.000 0.000 0.000 0.000 Pearson Correlation 0.745 0.765 0.746 0.700 0.588 0.633 Sig (2-tailed) 0.000 0.000 0.000 0.000 0.000 0.000 Pearson Correlation -0.007 -0.003 0.028 0.004 0.006 -0.052 0.006 Sig (2-tailed) 0.877 0.950 0.567 0.941 0.899 0.280 0.908 Pearson Correlation -0.067 -0.149 -0.183 -0.102 -0.049 -0.020 -0.113 -0.268 Sig (2-tailed) 0.164 0.002 0.000 0.035 0.314 0.685 0.018 0.000 1.000 348 332 Trường ðại học Nông nghiệp Hà Nội – Luận án tiến sỹ khoa học Nông nghiệp ……………………… 0.000 Appendix Table 30 Continued VARIABLE GENDER HHSIZE KI EXP EDU DISTANCE ASSN CROP FARMSIZE LOCA EBRM 065 002 017 099 063 -.026 -.058 065 018 000 177 964 718 040 188 593 233 175 703 993 -.195 212 -.147 -.025 017 047 168 -.111 -.208 000 000 002 598 728 330 000 021 000 022 098 -.069 037 087 -.093 009 606 648 042 150 439 071 053 848 000 -.217 -.091 046 136 212 -.128 084 000 058 343 005 000 008 081 -.220 180 038 060 -.093 028 000 000 429 210 052 565 -.098 005 005 025 -.096 042 910 920 604 046 -.017 141 091 077 725 003 058 111 012 -.682 272 796 000 000 061 -.069 203 150 -.014 For Technical Inefficiency Analysis: Gender HHSize KI Exp Edu Distance ASSN Crop Farmsize Loca Pearson Correlation Sig (2-tailed) Pearson Correlation 065 Sig (2-tailed) 177 Pearson Correlation 002 -.195 Sig (2-tailed) 964 000 Pearson Correlation 017 212 022 Sig (2-tailed) 718 000 648 Pearson Correlation 099 -.147 098 -.217 Sig (2-tailed) 040 002 042 000 Pearson Correlation 063 -.025 -.069 -.091 -.220 Sig (2-tailed) 188 598 150 058 000 Pearson Correlation -.026 017 037 046 180 -.098 Sig (2-tailed) 593 728 439 343 000 042 Pearson Correlation -.058 047 087 136 038 005 -.017 Sig (2-tailed) 233 330 071 005 429 910 725 Pearson Correlation 065 168 -.093 212 060 005 141 012 Sig (2-tailed) 175 000 053 000 210 920 003 796 Pearson Correlation 018 -.111 009 -.128 -.093 025 091 -.682 061 Sig (2-tailed) 703 021 848 008 052 604 058 000 203 Trường ðại học Nông nghiệp Hà Nội – Luận án tiến sỹ khoa học Nông nghiệp ……………………… 766 349 Pearson Correlation 000 -.208 606 084 028 -.096 077 272 -.069 -.014 Sig (2-tailed) 993 000 000 081 565 046 111 000 150 766 333 EBRM Appendix Table 31 Pearson correlation results for the Cobb-Douglas production function for Model 2, 147 rice farmers using the CA kernel matched sample, An Giang Province, Mekong River Delta, Vietnam, 2006 and 2009 VARIABLE A S L N P K PEST VART T For Production Function Analysis: A Pearson Correlation Sig (2-tailed) S L N P K PEST VART 986 983 967 917 861 755 -.050 -.056 000 000 000 000 000 000 395 338 987 952 891 854 765 -.047 -.136 000 000 000 000 000 423 020 952 890 853 752 -.015 -.176 000 000 000 000 794 002 933 807 711 -.037 -.095 000 000 000 523 106 763 585 -.024 -.039 000 000 685 510 672 -.085 -.053 000 148 366 -.063 -.103 283 077 -.318 Pearson Correlation 986 Sig (2-tailed) 000 Pearson Correlation 983 987 Sig (2-tailed) 000 000 Pearson Correlation 967 952 952 Sig (2-tailed) 000 000 000 Pearson Correlation 917 891 890 933 Sig (2-tailed) 000 000 000 000 Pearson Correlation 861 854 853 807 763 Sig (2-tailed) 000 000 000 000 000 Pearson Correlation 755 765 752 711 585 672 Sig (2-tailed) 000 000 000 000 000 000 -.050 -.047 -.015 -.037 -.024 -.085 -.063 395 423 794 523 685 148 283 Pearson Correlation Sig (2-tailed) Trường ðại học Nông nghiệp Hà Nội – Luận án tiến sỹ khoa học Nông nghiệp ……………………… 000 350 Pearson Correlation Sig (2-tailed) -.056 -.136 -.176 -.095 -.039 -.053 -.103 -.318 338 020 002 106 510 366 077 000 Appendix Table 31 Continued VARIABLE GENDER HHSIZE KI EXP EDU DISTANCE ASSN CROP FARMSIZE LOCA CA For Technical Inefficiency Analysis: Gender HHSize KI Exp Edu Distance ASSN Crop Farmsize Loca Pearson Correlation Sig (2-tailed) 049 018 083 106 005 -.010 013 170 -.048 024 406 754 153 069 937 867 831 004 413 683 Pearson Correlation 049 -.229 265 -.135 -.028 -.007 -.096 208 -.017 -.194 Sig (2-tailed) 406 000 000 021 636 901 099 000 770 001 Pearson Correlation 018 -.229 -.014 139 -.068 034 087 -.097 015 494 Sig (2-tailed) 754 000 805 017 246 561 137 096 800 000 Pearson Correlation 083 265 -.014 -.228 -.125 114 069 274 -.066 059 Sig (2-tailed) 153 000 805 000 032 051 241 000 256 312 Pearson Correlation 106 -.135 139 -.228 -.264 083 163 043 -.188 104 Sig (2-tailed) 069 021 017 000 000 156 005 463 001 075 Pearson Correlation 005 -.028 -.068 -.125 -.264 -.079 -.106 058 127 -.143 Sig (2-tailed) 937 636 246 032 000 176 071 320 030 014 -.010 -.007 034 114 083 -.079 088 123 034 129 Sig (2-tailed) 867 901 561 051 156 176 133 035 566 026 Pearson Correlation 013 -.096 087 069 163 -.106 088 007 -.537 338 Sig (2-tailed) 831 099 137 241 005 071 133 901 000 000 Pearson Correlation 170 208 -.097 274 043 058 123 007 126 -.047 Sig (2-tailed) 004 000 096 000 463 320 035 901 031 423 -.048 -.017 015 -.066 -.188 127 034 -.537 005 Pearson Correlation Pearson Correlation Trường ðại học Nông nghiệp Hà Nội – Luận án tiến sỹ khoa học Nông nghiệp ……………………… 126 351 334 T .413 770 800 256 001 030 566 000 031 935 Pearson Correlation 024 -.194 494 059 104 -.143 129 338 -.047 005 Sig (2-tailed) 683 001 000 312 075 014 026 000 423 935 Appendix Table 32 Pearson correlation results for the Cobb-Douglas production function for Model 2, 148 rice farmers using the CTBS kernel matched sample, An Giang Province, Mekong River Delta, Vietnam, 2006 and 2009 VARIABLE A S L N P K PEST VART T For Production Function Analysis: A Pearson Correlation Sig (2-tailed) S L N P K PEST VART 978 979 938 858 771 727 024 -.085 000 000 000 000 000 000 683 147 975 924 855 744 764 032 -.176 000 000 000 000 000 589 002 931 844 760 719 068 -.221 000 000 000 000 247 000 900 671 637 063 -.140 000 000 000 282 016 530 542 055 -.082 000 000 347 160 561 -.027 -.032 000 642 583 010 -.107 866 066 -.300 Pearson Correlation 978 Sig (2-tailed) 000 Pearson Correlation 979 975 Sig (2-tailed) 000 000 Pearson Correlation 938 924 931 Sig (2-tailed) 000 000 000 Pearson Correlation 858 855 844 900 Sig (2-tailed) 000 000 000 000 Pearson Correlation 771 744 760 671 530 Sig (2-tailed) 000 000 000 000 000 Pearson Correlation 727 764 719 637 542 561 Sig (2-tailed) 000 000 000 000 000 000 Pearson Correlation 024 032 068 063 055 -.027 Trường ðại học Nông nghiệp Hà Nội – Luận án tiến sỹ khoa học Nông nghiệp ……………………… 010 352 335 CA Sig (2-tailed) Sig (2-tailed) T Pearson Correlation 589 247 282 347 642 866 000 -.085 -.176 -.221 -.140 -.082 -.032 -.107 -.300 147 002 000 016 160 583 066 000 336 Sig (2-tailed) 683 Appendix Table 32 Continued VARIABLE GENDER HHSIZE KI EXP EDU DISTANCE ASSN CROP FARMSIZE LOCA CTBS For Technical Inefficiency Analysis: Gender HHSize KI Exp Edu Distance ASSN Crop Farmsize Loca Pearson Correlation Sig (2-tailed) Pearson Correlation 110 Sig (2-tailed) 058 Pearson Correlation 110 -.009 -.042 193 042 -.080 -.083 -.014 006 -.012 058 877 474 001 468 168 157 804 912 844 -.119 216 -.091 -.056 -.055 103 222 -.179 -.166 041 000 118 336 349 078 000 002 004 043 122 -.041 050 096 -.039 049 569 457 036 480 390 099 505 405 000 -.207 -.139 -.061 135 189 -.112 069 000 017 295 020 001 055 238 -.250 277 -.019 102 -.120 -.009 000 000 741 081 039 883 -.106 080 -.100 003 -.046 067 168 087 963 431 -.028 076 108 066 -.009 -.119 877 041 -.042 216 043 Sig (2-tailed) 474 000 457 Pearson Correlation 193 -.091 122 -.207 Sig (2-tailed) 001 118 036 000 Pearson Correlation 042 -.056 -.041 -.139 -.250 Sig (2-tailed) 468 336 480 017 000 -.080 -.055 050 -.061 277 -.106 Sig (2-tailed) Pearson Correlation Pearson Correlation Sig (2-tailed) 168 349 390 295 000 067 -.083 103 096 135 -.019 080 -.028 157 078 099 020 741 168 632 -.014 222 -.039 189 102 -.100 076 -.030 Sig (2-tailed) 804 000 505 001 081 087 192 602 Pearson Correlation 006 -.179 049 -.112 -.120 003 108 -.561 Pearson Correlation Sig (2-tailed) Pearson Correlation Trường ðại học Nông nghiệp Hà Nội – Luận án tiến sỹ khoa học Nông nghiệp ……………………… 632 192 064 257 -.030 -.561 351 602 000 000 098 -.081 093 163 -.015 098 353 Sig (2-tailed) CTBS Pearson Correlation Sig (2-tailed) 912 002 405 055 039 963 064 000 093 800 -.012 -.166 569 069 -.009 -.046 066 351 -.081 -.015 844 004 000 238 883 431 257 000 163 800 337 Trường ðại học Nông nghiệp Hà Nội – Luận án tiến sỹ khoa học Nông nghiệp ……………………… 354 [...]... ABSTRACT HO NGOC NINH University of the Philippines Los Baños, April 2013 Farm- Level Economic Impact of Ecologically -Based Rodent Management in an Intensive Irrigated Rice System: The Case Study of Rice Farming in the Mekong River Delta, Vietnam Major Professor: Dr Corazon T Aragon Using panel data from 221 sample rice farmers in An Giang Province, Mekong River Delta, Vietnam, a comparison of means (t-test)... framework of impact assessment of the EBRM Project in the Mekong River Delta, Vietnam 80 5 Conceptual framework showing the effects of factors on production, technical and economic efficiency in rice production in the Mekong River Delta, Vietnam 83 6 The EBRM Project sites and study area in the Mekong River Delta, Vietnam 88 7 Extension network for the dissemination of the EBRM technology in Vietnam. .. Province, Mekong River Delta, Vietnam 214 53 Estimated mean impact of the EBRM technology on real net farm income of rice farmers using the kernel matched sample, An Giang Province, Mekong River Delta, Vietnam 215 54 Estimated mean impact of community action (CA) on real net farm income of rice farmers using the unmatched sample, An Giang Province, Mekong River Delta, Vietnam 218 55 Estimated mean impact of. .. contaminated food and water, and damaged buildings and other possessions As in other areas of Asia, the rodent problem in Vietnam has increased since the 1970s in rice -based farming systems (Singleton, 2003) The most likely reasons for this are increases in area and intensity of rice production, and asynchronous planting of crops (Singleton and Petch, 1994, and Singleton, 2003) The level of rodent. .. after the implementation of the EBRM Project, 158 rice farmer-respondents in An Giang Province, Mekong River Delta, Vietnam 157 24 Mean levels of input use and paddy yield in the summer-autumn season in the project sites before and after the implementation of the EBRM Project, 221 rice farmer-respondents in An Giang Province, Mekong River Delta, Vietnam 159 25 Mean levels of input use and paddy yield in. .. using the kernel matched sample, An Giang Province, Mekong River Delta, Vietnam 211 51 Estimated mean impact of the EBRM technology on real net farm income of rice farmers using the unmatched sample, An Giang Province, Mekong River Delta, Vietnam 213 52 Estimated mean impact of the EBRM technology on real net farm income of rice farmers using the 1-to-1 nearest neighbor matched sample, An Giang Province,... robustness of EBRM strategies over a range of lowland irrigated rice agro-ecosystems However, this study only focused on the implementation and its economic impact on rice production in the Mekong River Delta, Vietnam 1.2 Statement of the Problem Rice is grown in many areas throughout Vietnam, but the two principal areas are the Red River Delta in northern Vietnam, and the Mekong River Delta in southern Vietnam, ... farmer-respondents in An Giang Province, Mekong River Delta, Vietnam 153 22 Comparison of the mean levels of input use and paddy yield in the summer-autumn season between the control and CA treatment groups before and after the implementation of the EBRM Project, 151 rice farmer-respondents in An Giang Province, Mekong River Delta, Vietnam 155 23 Comparison of the mean levels of input use and paddy yield in the summer-autumn... mean impact of the community trap barrier systems (CTBS) component on real net farm income of rice farmers using the unmatched sample, An Giang Province, Mekong River Delta, Vietnam 223 58 Estimated mean impact of the community trap barrier systems (CTBS) component on real net farm income of rice farmers using the 1-to-1 nearest neighbor matched sample, An Giang Province, Mekong River Delta, Vietnam. .. significance of the differences in the mean levels of input use and paddy yield per hectare between the CA farmers and the control farmers, before and after the implementation of the EBRM Project 305 4 Results of the t-test of means to determine the significance of the differences in the mean levels of input use and paddy yield per hectare between the CTBS farmers and the control farmers, before and after the .. .FARM- LEVEL ECONOMIC IMPACT OF ECOLOGICALLY -BASED RODENT MANAGEMENT IN AN INTENSIVE IRRIGATED RICE SYSTEM: THE CASE STUDY OF RICE FARMING IN THE MEKONG RIVER DELTA, VIETNAM HO NGOC NINH SUBMITTED... NINH University of the Philippines Los Baños, April 2013 Farm- Level Economic Impact of Ecologically -Based Rodent Management in an Intensive Irrigated Rice System: The Case Study of Rice Farming. .. Delta as in other regions in Vietnam, rodent pest damage is one of the main constraints in rice production Rodent pests were a growing problem in the rice agro-ecosystems of the Mekong River Delta,