Title Page
ABSTRACT
Contents
List of Abbreviations 17
Conversion factors used in this study 19
CHAPTER 1. Introduction 20
1.1. Background 20
1.2. The problem statement 26
1.3. Objectives 29
1.4. The conceptual framework 30
1.5. Justification 32
1.6. Research outline 33
CHAPTER 2. LITERATURE REVIEWS 35
2.1. Overview 35
2.2. Theoretical Literature 35
2.2.1. Theoretical Framework 35
2.2.2. General concept of stochastic frontier analysis (SFA) 40
2.2.3. Advantages of stochastic frontier analysis 42
2.2.4. Empirical review on efficiency measurement with SFA 43
2.3. Theoretical conceptualization of adoption of new agricultural technology 49
2.3.1. Approach to measure farm technology adoption 51
2.3.2. The impact evaluation approaches of agricultural technology 52
2.3.3. Empirical review of ESR model 54
2.4. Agricultural credit and efficiency nexus 58
CHAPTER 3. RICE INDUSTRY IN MYANMAR 61
3.1. General information about Myanmar 61
3.2. Some major changes of agricultural policy in Myanmar 65
3.3. Poverty and agricultural productivity 65
3.4. Resource utilization conditions in agricultural sector 68
3.4.1. Land utilization 68
3.4.2. Irrigation 69
3.4.3. Farm mechanization 69
3.4.4. Varieties 71
3.4.5. Chemical fertilizer 72
3.4.6. Credit 73
3.5. Growth of Rice production in Myanmar 74
3.5.1. Yield, Production and Export of Rice in Myanmar and Neighboring Countries 74
3.5.2. Sown area, Yield, Production and Export of rice in Myanmar (1995-2018) 76
3.5.3. Current situations of rice cultivation in Regions and States of Myanmar (2018-19) 78
3.5.4. Constraints on rice growing in Myanmar 81
CHAPTER 4. Measuring the Efficiency and Determinants of Rice Production in Myanmar: A Translog Stochastic Frontier Approach 84
4.1. Introduction 84
4.2. The conceptual of production efficiencies 86
4.3. Materials and Methods 87
4.3.1. Stochastic Frontier Model 87
4.3.2. Econometric specification 91
4.3.3. Model for inefficiency effects 94
4.3.4. Specification of Hypotheses 95
4.3.5. Data gathering technique 96
4.3.6. Explanations of the data used for measuring the efficiency 98
4.4. Results and Discussions 100
4.4.1. Hypothesis Testing 100
4.4.2. Technical efficiency of rice production 101
4.4.3. Economic efficiency of rice production 104
4.4.4. Frequency distribution of Technical, Allocative and Economic Efficiency for rice production in Myanmar 106
4.4.5. Factors affecting efficiency estimates among rice farmers 110
4.5. Conclusions 114
CHAPTER 5. Determining the influencing factors on adoption decision and its impact on productivity in Myanmar: The case of improved rice varieties 118
5.1. Introduction 118
5.2. History of rice variety introduction to Myanmar 121
5.3. Theoretical framework and empirical strategy 123
5.3.1. Theoretical framework 123
5.3.2. Endogenous switching regression 125
5.3.3. Estimation of average treatment effects 129
5.3.4. Conditional expectations and treatment effects 130
5.3.5. Data 131
5.3.6. Descriptions of variables used 132
5.3.7. Descriptive statistics of variables used 134
5.4. Results and Discussion 138
5.4.1. Determinants of IRVs adoption and Rice Yield 138
5.4.2. Average treatment effect on treated(ATT) of IRVs adoption 144
5.5. Conclusion 145
CHPATER 6. Impact of agricultural microcredit on technical efficiency and rice productivity in Ayeyarwaddy delta region, Myanmar 149
6.1. Introduction 149
6.2. Methodologies 152
6.2.1. Theoretical background 152
6.2.2. The stochastic frontier model 153
6.2.3. Propensity score matching 155
6.2.4. Measuring Technical Efficiency and Probit Models 159
6.3. Data and Summary statistics 162
6.4. Results and discussion 164
6.4.1. Determinants of participation in credit 164
6.4.2. Analysis of the propensity scores 167
6.4.3. Balancing test of matching quality 169
6.4.4. Robustness of results to hidden bias 171
6.4.5. Impact of the participation in credit on rice yield 172
6.4.6. Hypothesis Testing 172
6.4.7. Measuring technical efficiency and its determinants 174
6.4.8. Effect of credit on technical efficiency 177
6.5. Conclusion 179
CHAPTER 7. SUMMARY, CONCLUSION AND POLICY RECOMMENDATION 181
7.1. Summary 181
7.2. Conclusions 186
7.3. Policy implications 189
7.4. Suggestions for further study 192
References 194
초록 219
Table 3.1. Myanmar's socio-economic key indicators 64
Table 3.2. Utilization of Farm Machinery (Number) 70
Table 3.3. Sown area, Yield, Production and Export of Rice for Neighboring Countries and Myanmar (2019) 75
Table 3.4. Sown acre, Yield, Production and Export of Rice in Myanmar (1995-2018) 77
Table 3.5. Sown areas in Region and State of Myanmar (2018-19) 80
Table 4.1. Socio-economic variables of the respondents (2019) 97
Table 4.2. Descriptive statistics of the variables used (2019) 98
Table 4.3. Hypothesis tests for appropriate functional form and statistical assumption 100
Table 4.4. MLE estimates of translog SFA production function for rice cultivation in Myanmar 101
Table 4.5. MLE estimates of translog SFA cost function for rice production in Myanmar 105
Table 4.6. Frequency distribution of efficiency estimates from Stochastic Frontier Model 107
Table 4.7. Determinants of technical, allocative and economic efficiencies in rice cultivation 111
Table 5.1. Expected conditional and average treatment effects 131
Table 5.2. Definition of variables and a priori expectations for improved rice varieties adoption 133
Table 5.3. Summary statistics of outcome and explanatory variables used in estimations 137
Table 5.4. ESR Results of IRVs Adoption and Rice Yield 143
Table 5.5. Average treatment effects of adoption of IRVs on rice outputs 145
Table 6.1. Definition of variables 161
Table 6.2. Summary statistics of the used variables 163
Table 6.3. Probit model estimates of credit participation 165
Table 6.4. Balancing Test of matched sample 170
Table 6.5. Rosenbaum bound test for hidden bias 171
Table 6.6. Impact of credit on rice yield(kg/ac)-PSM 172
Table 6.7. Hypotheses tests for appropriate functional form and statistical assumption 173
Table 6.8. Maximum likelihood estimates of SFA production function and inefficiency model 175
Table 6.9. Technical efficiency distribution of credit users and non-users farmers 177
Figure 1.1. GDP share of Myanmar in 2018-2019 22
Figure 1.2. The conceptual framework of the whole research 31
Figure 2.1. Conceptual framework for efficiency analysis 37
Figure 3.1. Map of Myanmar and Ayeyarwaddy region showing study area (Pathein town) 62
Figure 3.2. Gross Domestic Product (2019) 63
Figure 3.3. Trend in poverty headcount by Union level and residential level 66
Figure 3.4. Land Utilization in 2018-2019 68
Figure 3.5. Trend of rice production in Myanmar (1995-2018) 78
Figure 4.1. Distribution of Technical(TE), Allocative(AE) and Economic(EE) efficiency index of farmers in Myanmar 109
Figure 4.2. Scatter plot for the relationship between farm size and TE, AE and EE[내용없음] 14
Figure 5.1. Sown area, Yield and Production of Rice in Myanmar 119
Figure 6.1. Propensity score distribution and common support 168