Impact evaluation of microcredit on welfare of the vietnam rural household

INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM VIETNAM -NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS · IMPACT EVALUATION OF MICROCREDIT ON WELFARE OF THE VIETNAM RURAL HOUSEHOLD A thesis submitted in partial fulfilment of the requirements for the degree of MASTER OF ARTS IN DEVELOPMENT ECONOMICS By PHAM TIEN THANH Academic Supervisor: DR PHAM BAO DUONG HO CHI MINH CITY, OCTOBER 2012 DECLARATION I certify that the contents of thesis have been carried out and written by me to the best of my knowledge and with the support in preparing this paper from many different sources I certify that this thesis has not been submitted to any other programs or journals HCMC, October 15th, 2012 PHAM TIEN THANH ACKOWLEDGEMENTS This thesis is impossible to be achieved without the support and assistance of the following people: Firstly, I would like to express my greatest gratitude to Dr Pham Bao Duong, my academic supervisor, who advised and instructed and supported me during the process of this thesis His expertise and his suggestions have provided a good basis for the improvement of my research His enthusiasm and encouraging is also a motivation for me to achieve me thesis I would like to give my special thanks to Prof.Dr Nguyen Trong Hoai, Dean of Vietnam-The Netherlands Programme and Dr Pham Khanh Nam, Academic Director of Vietnam -The Netherlands Programme Their knowledge and enthusiasm has supported me a lot during my thesis writing process This is also a good opportunity to express my appreciation to all the lecturers who equipped me with valuable knowledge during my study at Vietnam -The Netherlands Programme I would also like to appreciate Mr Nguyen Khanh Duy, Lecturer at the Faculty of Development Economics, University of Economics, Ho Chi Minh City His support with data as well as using econometrics software is a great contribution to the completion of my thesis Lastly, I am grateful to my beloved parents who gave moral support and encouraged me to finish my thesis during writing process 11 ABSTRACT This research evaluates the impact of microcredit on the welfare of households living in the Vietnam rural areas, especially the poor The research is analyzed based on a data of the Vietnam household living standard survey (VHLSS) in the year 2008 The difference of the research in comparison with the previous studied about the relationship between microcredit and welfare is the employment of propensity score matching (PSM) method, thus it reflects the impact of microcredit on rural households' living standard better and more precisely The result shows that microcredit will result in better welfare of rural households via a greater increase in the income and consumption per capita per month of the participating households However, the result about the poor rural households showed that microcredit does not result in a higher increase in income of the participants than that of the nonparticipants, but contributes to a greater rise in the consumption The research also showed the determinants on the accessibility to microcredit programs of the households living in rural regions The results found out that the probability of accessing the microcredit sources of the rural households in Vietnam is still low Moreover, the proportionate of accessibility to microcredit of the poor household is even less that of the nonpoor households, which means microcredit programs mistarget the poor households From those results, the research gives policy recommendations to improve microcredit programs in rural areas as well as to support more poor households to access to microcredit sources 111 TABLE OF CONTENT DECLARATION i ACKNOWLEDMENTS ii ABSTRACT iii TABLE OF CONTENT iv LIST OF ABBRIVIA TIONS vi LIST OF TABLES AND FIGURES VII CHAPTER I INTRODUCTION 1.1 Problem Statement ~ 1.2 Objectives of the study 1.3 Research questions 1.4 Organization of the research CHAPTER II LITERARTURE REVIEW Overview of Poverty 2.1.1 Definition 2.1.2 Method of defining poverty 2.2 Overview of Microcredit 2.2.1 Some definitions 2.2.2 Characteristics of Microcredit 2.2.3 Overview of rural credit market in Vietnam 11 2.2.4 Overview of microcredit program in Vietnam 12 2.3 Empirical Study 17 2.3 Impact of micro credit on welfare/ living standard of the rural households 17 2.3.2 Determinants of the accessibility to microcredit programs 24 lV CHAPTER III 30 RESEARCH METHODOLOGY AND DATA DESCRIPTION 30 3.1 Model of determinants of access to credit 30 3.2.Impact Evaluation techniques 34 3.2.1 Some Definition 34 3.2.2 Impact evaluation using PSM technique 34 3.2.3 Impact evaluation using DID technique 38 3.3 Data Description 41 3.3.1 Survey area 41 3.3.2 Data sources • 41 3.3.3 Sample selection 41 CHAPTER IV 44 RESULT 44 4.1 Descriptive Statistics 44 4.2 Determinants on microcredit participation 46 4.3 Impact of microcredit on welfare of rural households using PSM 51 4.4 Impact of microcredit on welfare of the rural poor using PSM 52 4.5 Impact ofmicrocredit on welfare of rural households using DID with fixed effect 55 4.6 Comparison between the results ofPSM and DID method 56 Comparison with previous studies 57 CHAPTER V 59 CONCLUSION, POLICY RECOMMENDATION AND LIMITATION ••• ••••••• 59 5.1 Conclusion 59 5.2 Policy Recommendation 62 5.3 Limitation 64 REFERENCES 65 APPEND IX 63 v LIST OF ABBREVIATIONS GSO General Statistics Office ·····························•··· ··················································'········································· MOLISA Ministry of Labor, Invalids and Social Affairs DO LISA Department of Labor, Invalids and Social Affairs MFis Micro Finance Institutions - Vietnam Bank for Agriculture and Rural Development VBA VBSP WB UN ·······-········ am household living standard survey VHLSS ····················-········· NN Nearest neighbor PSM Propensity Score Matching DD or DID Difference in Difference or Double Difference VI LIST OF TABLES AND FIGURES List of Tables Table 2.1: Poverty Rate in Vietnam Table 2.2: Characteristics ofMicrocredit Programs in Vietnam from 2005 to 2011 12 Table 2.3: Main Characteristics ofthe MFis in 2011 14 Table 2.4: Characteristics ofMicrocredit Programs by VBSP from 2005 to 2011 16 Table2.5: Summary of Some Main Findings about the Impact ofMicrocredit Programs on Welfare/ Living Standards 20 Table 3.1: Table 3.2: Descriptions of the Determinants on Accessibility to Microcredit 31 Variables in the Analysis of the Impact ofMicrocredit using DID 40 Table 3.3: Characteristics of Comparison Groups in 2008 .43 Table 4.1: Impact ofMicrocredit on Income/Consumption ofRural Households using Independent Sample T-Test Methods 44 Table 4.2: Impact of Microcredit on Income/Consumption of the Rural Poor using Independent Sample T-Test Methods 44 Table 4.3: Distribution of Eligibility with respect to Treatment Households .45 Table 4.4: Credit Access with respect to Eligible Households .45 Table 4.5: Probit Estimations of Determinants on Accessibility to Microcredit .47 Table 4.6: Probit Estimation ofModel3 with Marginal Effect 48 Table 4.7: Impact ofMicrocredit on Income ofRural Households using PSM 51 Table 4.8: Impact ofMicrocredit on Consumption ofRural Households using PSM 52 Table 4.9: Impact ofMicrocredit on Income of the Rural Poor using PSM 53 Table 4.10: Sector of Production and Business on Which the Loan was Spent 53 Table 4.11: Reasons of Unchanged or Worse Living Condition 54 Table 4.12: Impact ofMicrocredit on Consumption ofthe Rural Poor using PSM 54 Table 4.13: Impact of Microcredit on Welfare of Rural households using DID with fixed effect 55 Table 4.14: Result Comparison between PSM and DID Method 56 Table 4.15: Results from the Previous Studies 51 VII List of Figures Figure 2.1 : Gross Loan Portfolio of microcredit in Vietnam from 2005 to 2011 13 Figure 2.2 :Characteristics ofMicrocredit Programs by VBSP from 2005 to 2011 15 Figure 2.3 : Determinants on Accessibility to Microcredit and Welfare Indicators 29 Figure 3.1 : Illustration oflmpact Evaluation Using DID Method 39 Vlll CHAPTER I INTRODUCTION The purpose of this chapter is to present chapter introduction of microcredit program as well as scope of the research such research methodology, research data, research objectives, and research questions l.l.Problem Statement Vietnam is considered one of the few countries that has obtained the remarkable achievement in poverty reduction As annual reports by GSO showed, the poverty rate has declined from 37.4 percent in 1998, to 18.1 percent in 2004 to 13.4 percent in 2008 In a report -by GSO (2008), the poverty rate in rural areas (16.1 percent) was higher than that in urban areas (6.7 percent) A large number of farmers in Vietnam are still living in poverty and under poor living standards Moreover, they have difficulties with accessing to credit sources especially, formal credit sources As a result, they mostly borrow from informal sources for financing their production as well as for consumption That results in the fact that they may fall into deeper debt and default debt Therefore, in order to gain the more preeminent achievement of hunger eradication and poverty reduction as well as to help the poor escape from poverty, the Vietnam Government have invested a great number of capital as well as provided financial services to support the rural households, especially the poor in rural areas via credit programs One of the special credit programs that the Government applied the program is microcredit As the definition by Microcredit Summit ( 1997), microcredit program is a program which provides small loans to poor people so that they can generate income to improve their living standard Many countries have applied microcredit programs as a tool of poverty reduction as well as a channel of providing credit to rural households Microcredit has been popularly applied and its impact on welfare or living standard of households has 1.2.4 Marginal Effect of Pro bit Model • Marginal effects after probit y = Pr(credit) (predict) 09857761 variable I dy/dx Std Err z P>lzl ( 95% C.I l X -+ -hgender* I age I age2 I hedu I hmar* I ost*l ethnic* I hhsize I drate I lpc I hval I distance I geofl *I geof2 *I geo2* I rbs*l ca2* I po* I - 0306262 0091425 -.0001125 0044193 0118135 0473607 0243143 0051596 -.0090407 1.06e-07 -3.54e-07 0002262 -.0287043 -.0659635 0437096 -.042231 0020188 -.0177212 026 00357 00003 00199 02473 03206 01759 00443 01013 00000 00000 00073 01756 01816 01914 01856 01932 02118 -1.18 2.56 -3.25 22 0.48 1.48 1.38 1.17 -0.89 0.14 -3 23 0.31 -1.63 -3 63" 28 -2.28 0.10 -0.84 0.239 0.010 0.001 0.026 0.633 0.140 0.167 0.244 0.372 0.885 0.001 0.757 0.102 0.000 0.022 0.023 0.917 403 -.081593 020341 002142 016143 -.00018 -.000045 000517 008322 -.036665 060292 -.015483 110204 -.010162 05879 -.003516 013835 -.028896 010814 -1.3e-06 1.5e-06 -5.7e-07 -1.4e-07 -.001209 001661 -.063121 005713 -.101561 -.0303b6 006202 081217 -.078602 -.00586 -.035841 039878 -.059231 023789 (*) dy/dx is for discrete change of dummy variable from to • 76 794216 50.4116 2743.42 6.47988 816429 054904 801341 4.1404 777072 2295.05 94961.5 7.05692 149204 534367 219195 805532 887678 892707 The impact of microcredit program on welfare of rural households using PSM f 2.1 Estimation of propensity score **************************************************** Algorithm to estimate the propensity score **************************************~************* The treatment is credit =0 : No ; =1 : Yes Freq Percent Cum + - I I 2,096 290 87.85 12.15 87.85 100.00 + - Total I 2,386 100.00 Estimation of the propensity score (sum of wgt is 5.3093e+06) Iteration 0: log pseudolikelihood Iteration 1: log pseudolikelihood Iteration 2: log pseudolikelihood Iteration 3: log pseudolikellhood Iteration 4: log pseudolikelihood -833.18428 -769.26135 -765.72159 -765.6464 -765.64634 Probit regression Log pseudolikelihood Number of obs Wald chi2(18) Prob > chi2 Pseudo R2 = -765.64634 2386 120.10 0.0000 0.0811 Robust credit Coef Std Err z [95% Conf Interval] P>lzl -+ -hgender -.2204426 1450126 -1.52 0.128 -.504662 0637769 0512422 0225119 age 2.28 0.023 0071198 0953646 age2 -.0006241 0002232 -2.80 0.005 -.0010614 -.0001867 0176923 0123278 hedu 44 0.151 -.0064698 0418544 hmar 1465891 1661613 0.88 0.378 -.1790811 4722593 ost 2457945 160846 53 0.126 -.0694579 5610468 ethnic 0786153 1282612 0.61 0.540 -.172772 3300026 0276332 hhsize 0322468 1.17 0.243 -.0219132 0864068 drate -.0619393 0564842 -1.10 0.273 -.1726462 0487677 lpc 3.39e-06 4.05e-06 0.84 402 -4.55e-06 0000113 hval -2.04e-06 6.35e-07 0.001 -3.28e-06 -7.93e-07 -3.21 distance 0039783 - 0050013 0129578 0045815 0.87 0.385 geofl -.170938 1218422 -1.40 0.161 -.4097443 0678682 geof2 -.3183673 1026071 -3.10 0.002 -.5194736 -.1172611 geo2 2445213 1032658 2.37 0.018 0421241 4469186 0925165 0.051 -.3617508 0009072 rbs -.1804218 -1.95 0771773 1152368 0.67 503 -.1486828 3030373 ca2 -.0082208 1123458 -0.07 0.942 -.2284145 211973 po - 9011146 -2.002358 5618691 -3.56 0.000 -3.103601 cons I I I I I I I I I I I I I I I I I I I I Note: the common support option has been selected The region of common support is [.012981, 47304715] i 77 Description of the estimated propensity score in region of common support Estimated propensity score 1% 5% 10% 25% 50% 75% 90% 95% 99% Smallest 012981 0130057 0130107 0130646 Percentiles 015509 0246869 0362468 067725 obs Sum of Wgt .1029042 Largest 4342763 4371411 4579433 4730472 1694928 2392524 2805114 365969 2284 2284 Mean Std Dev .1240969 0793075 Variance skewness Kurtosis 0062897 1.063566 974971 ****************************************************** Step 1: Identification of the optima: number of blocks Use option detail if you want more detailed output ****************************************************** The final number of blocks is This number of blocks ensures that the mean propensity score is not different for treated and controls in each block ********************************************************** Step 2: Test of balancing property of the propensity score Use option detail if you want more detailed output ********************************************************** The balancing property is satisfied This table shows the inferior bound, the number of treated and the number of controls for each block Inferior of block of pscore =0 : No ; =1 : Yes Total -+ + 012981 0833333 125 1666667 3333333 I I I I I 754 547 242 423 28 43 57 50 127 13 I I I I I 797 604 292 550 41 -+ + Total I 1,994 290 I 2,284 Note: the common support option has been selected ******************************************* End of the algorithm to estimate the pscore ******************************************* i • 78 2.2 Impact evaluation of microcredit on welfare 2.2 Impact on log of average income per capita 2.2 !.Nearest Neighbor Matching method Analytical standard errors n treat n contr ATT Std Err t 290 254 0.082 0.034 431 Note: the numbers of treated and controls refer to actual nearest neighbour matches Bootstrapped standard errors n treat n contr ATT Std Err t 290 254 0.082 0.029 2.785 Note: the numbers of treated and controls refer to actual nearest neighbo~r matches 2.2 Radius Matching method Analytical standard errors n treat n contr ATT Std Err t 170 362 0.090 0.038 2.361 Note: the numbers of treated and controls refer to actual matches within radius Bootstrapped standard errors n treat n contr ATT Std Err t 170 362 0.090 0.043 071 Note: the numbers of treated and controls refer to actual matches within radius 2.2 Stratification method Analytical standard errors n treat n contr ATT Std Err 290 1994 0.092 0.028 t 3.325 Bootstrapped standard errors n treat n contr ATT Std Err t 290 1994 0.092 0.028 3.343 79 2.2 Impact on average income per capita 2.2 l.Nearest Neighbor Matching method Analytical standard errors - n treat n contr ATT Std Err t - 290 254 90.331 23.554 3.835 - Note: the numbers of treated and controls refer to actual nearest neighbour matches Bootstrapped standard errors - n treat n contr ATT Std Err t 290 254 90.331 21.763 4.151 - Note: the numbers of treated and controls refer to actual nearest neighbour matches 2.2 2 Radius Matching method Analytical standard errors - n treat n contr ATT Std Err t - 170 362 91.762 27.817 3.299 - Note: the numbers of treated and controls refer to actual matches within radius Bootstrapped standard errors - n treat n contr ATT Std Err t - 170 362 91.762 38.510 383 - Note: the numbers of treated and contro~s refer to actual matches within radius 2.2 Stratification method Analytical standard errors - n treat n contr ATT Std Err t 29 1994 93.915 20.941 4.485 - Bootstrapped standard errors - n treat n contr ATT Std Err t - 29 1994 93.915 22.841 4.112 - i • 80 2.2 Impact on log of average consumption per capita 2.2 Stratification method Analytical standard errors n treat n contr ATT Std Err t 290 254 0.118 0.032 3.634 Note: the numbers of treated and controls refer to actual nearest neighbour matches Bootstrapped standard errors n treat n contr ATT Std Err t 290 254 0.118 03 3.237 Note: the numbers of treated and controls refer to actual nearest neighbour matches 2.2 Stratification method Analytical standard errors n treat n contr ATT Std Err t 170 362 0.130 0.036 3.604 Note: the numbers of treated and controls refer to actual matches within radius Bootstrapped standard errors n treat n contr ATT Std Err t 170 62 0.130 0.041 3.200 Note: the num~ers of treated and controls refer to actual matches within radius 2.2 3 Stratification method ATT estimation with the Stratification method Analytical standard errors n treat n contr ATT Std Err t 290 1994 0.124 025 5.054 Bootstrapped standard errors n treat n contr ATT Std Err 290 1994 0.124 020 i • 81 t 6.299 2.2 Impact on consumption per capita 2.2 l.Nearest Neighbor Matching method Analytical standard errors - n treat n contr ATT Std Err t - 290 254 73.284 18.190 4.029 - Note: the numbers of treated and controls refer to actual nearest neighbour matches Bootstrapped standard errors n treat n contr ATT Std Err t - 290 254 73.284 18.618 3.936 - Note: the numbers of treated and controls refer to actual nearest neighbour matches 2.2 Radius Matching method Analytical standard errors - n treat n contr ATT Std Err t - 170 362 86.793 21.982 3.948 - Note: the numbers of treated and con::rcls refer to actual matches within radius ' Bootstrapped standard errors - n treat n contr ATT Std Err t - 170 362 86.793 29.912 2.902 - Note: the numbers of treated and con::rols refer to actual matches within radius 2.2 Stratification method Analytical standard errors - n treat n contr ATT Std Err t - 290 1994 77.714 14.780 58 - Bootstrapped standard errors - n treat n contr ATT Std Err t - 290 1994 77.714 12.318 6.309 - • 82 The impact of microcredit program on welfare of the rural poor using PSM i • 3.1 Estimation of propensity score **************************************************** Algorithm to estimate the propensity score **************************************************** The treatment is credit =0 : No ; =1 : Yes I I Freq Percent Cum + - I I 241 99 70.88 29.12 70.88 100.00 + - Total I 340 100.00 Estimation of the propensity score (sum of wgt is 7.3806e+05) Iteration 0: log pseudolikelihood Iteration 1: log pseudolikelihood Iteration 2: log pseudolikelihood Iteration 3: log pseudolikelihood Iteration 4: log pseudolikelihood -203.13416 -167.80027 -165.87674 -165.85165 -165.85164 Probit regression Log pseudolikelihood = Number of obs Wald chi2(18) Prob > chi2 Pseudo R2 -165.85164 340 73.11 0.0000 0.1835 -~ Robust credit I Coef Std Err z P>lzl [95% Conf Interval] -+ hgender I 2546174 3139148 0.81 0.417 -.3606443 8698791 age I -.0114784 0398684 -0.29 0.773 -.089619 0666622 age2 I -.0000578 0003734 -0.15 877 -.0007896 000674 hedu I 0738638 0276461 2.67 0.008 0196785 128049 hmar I 0461368 3307367 0.14 0.889 -.6020952 6943687 ost I -.0677631 4929231 -0.14 891 -1.033875 8983484 ethnic I 5703301 2627605 2.17 0.030 0553289 1.085331 hhsize I 1593863 0646162 2.47 0.014 0327409 2860318 drate I -.3689113 1451254 -2.54 011 -.6533518 -.0844708 lpc I 7.26e-06 7.45e-06 0.98 0.329 -7.34e-06 0000219 hval I 5.46e-06 1.97e-06 2.77 0.006 1.59e-06 9.32e-06 distance I 0104119 0081855 1.27 0.203 - 0056313 0264551 geofl I - 1127256 2612711 -0.43 0.666 -.6248075 3993562 geof2 I -.3248203 2335246 -1.39 0.164 -.7825201 1328796 geo2 I 4703378 2255054 2.09 0.037 0283552 9123203 rbs I -.1457987 204928 -0.71 0.477 -.5474502 2558528 ca2 I 2659439 2631803 01 0.312 -.2498801 7817678 po I 8480587 3086781 2.75 0.006 2430609 1.453057 cons I -2.584804 1.08646 -2.38 0.017 -4.714226 -.4553815 Note: the common support option has been selected The region of common support is [.01778183, 90920033] i' 83 Description of the estimated propensity score in region of common support i Estimated propensity score - ~ 1% 5% 10% 25% Percentiles 0200174 0361762 0540576 1257768 50% 75% 90% 95% 99% Smallest 0177818 0179178 0184947 0200174 Obs Sum of Wgt .272886 Largest 824314 8413337 8747703 9092003 4406013 6000481 6742904 824314 330 330 l"'ean Std Dev .3016466 2062667 Variance Skewness Kurtosis 0425459 5873015 565311 ****************************************************** Step 1: Identification of the optimal number of blocks Use option detail if you want more detailed output ****************************************************** The final number of blocks is This number of blocks ensures that the mean propensity score is not different for treated and controls in each block ********************************************************** Step 2: Test of balancing property of the propensity score Use option detail if you want more detailed output ********************************************************** The balancing property is satisfied • This table shows the inferior bound, the number of treated and the number of controls for each block Inferior of block of pscore =0 : No ; =1 Yes Total -+ + 0177818 0833333 125 1666667 3333333 6666667 8333333 I I I I I I I I 52 24 15 67 50 19 3 11 19 28 24 11 I I I I I I I I 55 25 26 86 78 43 14 -+ + Total I 231 99 I 330 Note: the common support option has been selected ******************************************* End of the algorithm to estimate the pscore ******************************************* t • 84 3.2 Impact evaluation of microcredit on welfare using PSM 3.2 Impact on log of average income per capita 3.2 !.Nearest Neighbor Matching method Analytical standard errors - n treat n contr ATT Std Err t - 99 62 0.082 0.061 1.354 - Note: the numbers of treated and controls refer to actualnearest neighbour matches Bootstrapped standard errors - n treat n contr ATT Std Err t - 99 62 0.082 0.054 1.526 - Note: the numbers of treated and controls refer to actual nearest neighbour matches 3.2 Radius Matching method Analytical standard errors - n treat n contr ATT Stc Err t 51 76 0.13 0.064 113 - Note: the numbers of treated and controls refer to actual matches within radius Bootstrapped standard errors - n treat n contr ATT Std Err t - 51 76 13 0.085 1.598 - Note: the numbers of treated and controls refer to actual matches within radius 3.2 Stratification method ATT estimation with the Stratification method Analytical standard errors - n treat n contr ATT Std Err t - 99 231 0.079 - Bootstrapped standard errors - n treat n contr ATT Std Err t - 99 231 0.079 0.057 1.394 i • 85 3.2 Impact on average income per capita I • 3.2 l.Nearest Neighbor Matching method Analytical standard errors - n treat n contr ATT Std Err t - 99 62 51.768 33.760 1.533 - Note: the numbers of treated and controls refer to actual nearest neighbour matches Bootstrapped standard errors - n treat n contr ATT Std Err t - 99 62 51.768 31.258 1.656 -· Note: the numbers of treated and controls refer to actual nearest neighbour matches 3.2 2.Near Radius Matching method Analytical standard errors - n treat n contr ATT Std Err t - 51 • 76 85.586 39.481 2.168 - Note: the numbers of treated and controls refer to actual matches within radius Bootstrapped standard errors • - n treat n contr ATT Std Err t 51 76 85.586 58.900 453 - Note: the numbers of treated and controls refer to actual matches within radius 3.2 3.Near Radius Matching method ATT estimation with the Stratification method Analytical standard errors - n treat n contr ATT Std Err t - 99 231 47.168 - Bootstrapped standard errors n treat n contr ATT Std Err t 99 231 47.168 31.438 500 i ' 86 3.2 Impact on log of average consumption per capita f 3.2 Stratification method Analytical standard errors n treat n contr ATT Sld Err t 99 62 0.129 0.059 2.201 Note: the numbers of treated and controls refer to actual nearest neighbour matches Bootstrapped standard errors n treat n contr ATT Std Err t 99 62 0.129 0.057 2.266 Note: the numbers of treated and controls refer to actual nearest neighbour matches 3.2 Radius Matching method Analytical standard errors , n J:reat n contr ATT Std Err t 51 76 0.199 0.068 2.949 Note: the numbers of treated and controls refer to actualmatches within radius Bootstrapped standard errors n treat n contr ATT Std Err t 51 76 0.199 0.079 2.519 Note: the numbers of treated and controls refer to actual matches within radius 3.2 Stratification method Analytical standard errors n treat n contr ATT 99 231 0.141 Std Err t Bootstrapped standard errors n treat n contr ATT Std Err t 99 231 0.141 0.051 2.754 87 ' - - 3.2 Impact on consumption per capita 3.2 l.Nearest Neighbor Matching method Analytical standard errors n treat n contr ATT Std Err t 99 62 913 28.485 2.314 Note: the numbers of treated and controls refer to actual nearest neighbour matches Bootstrapped standard errors n treat n contr ATT Std Err t 99 62 65.913 27.212 2.422 Note: the numbers of treated and controls refer to actual nearest neighbour matches 3.2.4.2 Radius Matching method Analytical standard errors n treat n contr ATT Std Err t 51 76 98.095 33.093 2.964 't Note: the numbers of treated and controls refer to actual matches within radius Bootstrapped standard errors n treat n contr ATT Std Err t 51 76 98.095 39.301 2.496 Note: the numbers of treated and controls refer to actual matches within radius 3.2 Stratification method ATT estimation with the Stratification method Analytical standard errors n treat n contr ATT 99 231 71 72 Std Err t Bootstrapped standard errors n treat n contr ATT Std Err t 99 231 71.720 20.512 3.496 88 Impact evaluation of microcredit on welfare using DID with Fixed Effect Impact on average income per capita Note: credit08 omitted because of collinearity (*) Fixed-effects (within) regression Group variable: hhid R-sq: 0.0780 0.0070 0.0321 within between overal:i corr(u_i, Xb) 358 179 Obs per group: avg max 2.0 F(2,177) Prob > F = 0.0077 Coef avinc I Number of obs Number of groups Std Err P>ltl t 7.49 0.0008 [95% Conf Interval] -+ year credit08 timecredit I cons I 96.39623 (omitted) 61.06953 475.7151 41.96409 2.30 0.023 13.58189 179.2106 65.71173 22.83438 0.93 20.83 0.354 0.000 -68.60977 430.6524 19.0.7488 520.7778 -+ sigma_u sigma_e I rho I 296.20514 305.5032 48455091 F test that all u_i=C: • (fraction of variance due to u_i) F(178, 177) = 88 Prob > F = 0.0000 4.2 Impact on log of average income per capita Note: credit08 omitted because of collinearity (*) Fixed-effects (within) Group variable: hhid R-sq: within between overall corr(u_i, Xb) = lnavinc I regression Number of obs Number of groups 358 179 0.3235 0.0005 03 Obs per group: mln avg max 2.0 -0.0044 F(2,177) Prob > F Coef Std Err t P>ltl 42.32 0.0000 [95% Conf Interval] -+ year credit08 tlmecredit cons I I I I 2900307 (omitted) 092364 5.977053 04673 6.21 0.000 197811 3822503 0731747 0254277 1.26 235.06 0.209 0.000 -.0520431 5.926872 2367712 6.027233 -+ sigma_u sigma_e I rho I 42302578 34019963 60725805 F test that all u_i=O: (fraction of variance due to u_i) 09 F(178, 177) = 89 Prob > F = 0.0000 4.3 Impact on average consumption per capita Note: credit08 omitted because of collinearity (*) Fixed-effects (within) Group variable: hhid " R-sq: within between overall corr(u_i, Xb) avexp I regression 0.2089 0.0048 0.0880 358 179 Obs per group: avg max 2.0 F(2,177) Prob > F = -0.0162 Coef Number of obs Number of groups Std Err P>ltl t 23.37 0.0000 [95% Conf Interval] -+ year credit08 timecredit I cons I 121.2292 (omitted) 115.1666 382.3017 33.72849 3.59 0.000 54.66751 187.791 52.81557 18.35305 2.18 20.83 0.031 0.000 10.93738 346.0827 219.3959 418.5206 -+ - sigma_u I sigma_e I rho I 230.84967 245.54711 46917808 (fraction of variance due to u_i) - - F test that all u_i=O: F(178, 177) = 1.76 Prob > F = 0.0001 4.4 Impact on log of average consumption per capita Note: credit08 omitted because of collinearity (*) • Fixed-effects (within) Group variable: hhid R-sq: within between overall corr(u_i, Xb) lnavexp I regression 0.5439 0.0051 0.2015 358 179 Obs per group: avg max 2.0 F(2,177) Frob > F = -0.0029 Coef Number of cbs Number of groups Std Err t P>ltl 105.52 0.0000 [95% Conf Interval] -+ year credit08 tirnecredit I cons I 3814157 (omitted) 1451803 5.7923 0399287 9.55 0.000 3026181 4602133 062 5245 0217269 32 266.60 021 0.000 0217908 5.749423 2685698 5.835177 -+ sigrna_u I sigrna_e I rho I 39940252 29068547 65372553 F test that all u_i=O: (fraction of variance due to u_i) F(178, 177) = 77 Prob > F = 0.0000 (*)Note: The credit08 variable (the participation in the program) is omitted because of its perfect correlattion with the other dummy variables (the dummy variable of households generated from using fixed effect model) Therefore, when using DID with fixed-effect regression, we should only consider the pre and post program impact over time (which means the coefficient oftimecredit variable) 90 ... ofMicrocredit on Income ofRural Households using PSM 51 Table 4.8: Impact ofMicrocredit on Consumption ofRural Households using PSM 52 Table 4.9: Impact ofMicrocredit on Income of the Rural. .. Determinants on microcredit participation 46 4.3 Impact of microcredit on welfare of rural households using PSM 51 4.4 Impact of microcredit on welfare of the rural poor using PSM 52 4.5 Impact. .. income of the poorest households than that of the medium-income households in Vietnam rural regions, then this leads to the positive impact on poverty alleviation In a research on the case of the Vietnam