(Luận văn) does remittance affect on behaviour of households a case study of 12 rural provinces in vietnam

t to ng UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM hi INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS ep w n lo ad VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS ju y th yi pl n ua al n va DOES REMITTANCE AFFECT ON BEHAVIOUR OF HOUSEHOLDS? A CASE STUDY OF TWELVE RURAL PROVINCES IN VIETNAM ll fu oi m at nh z z jm ht vb BY k NGUYỄN NGÔ PHƯƠNG DIỆP om l.c gm n a Lu MASTER OF ARTS IN DEVELOPMENT ECONOMICS n va y te re th HO CHI MINH CITY, October 2014 t to ng hi ep UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS w n lo ad VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS ju y th yi pl ua al n DOES REMITTANCE AFFECT ON BEHAVIOUR OF HOUSEHOLDS? A CASE STUDY OF TWELVE RURAL PROVINCES IN VIETNAM n va ll fu oi m at nh A thesis submitted in partial fulfilment of the requirements for the degree of z MASTER OF ARTS IN DEVELOPMENT ECONOMICS z k jm ht vb By Dr PHẠM THỊ THU TRÀ n a Lu Academic Supervisor: om l.c gm NGUYỄN NGÔ PHƯƠNG DIỆP n va y te re th HO CHI MINH CITY, October 2014 t to ng DECLARATION hi ep This is to certify that the substance of this thesis entitled “Does remittance w n affected on behaviour of households?: A case study of twelve rural provinces in lo ad Vietnam”, which is submitted by me in fulfillment of requirements for the degree of yi Programme ju y th Master of Art in Development Economic to the Vietnam – The Netherlands pl I certify that to best of my knowledge, any help received in preparing this thesis, al n ua and all sources used, have been acknowledged in this thesis va n Nguyễn Ngô Phương Diệp ll fu oi m at nh z z k jm ht vb om l.c gm n a Lu n va y te re th t to ng ACKNOWLEDGMENT hi ep w First of all, I would like to express my greatest appreciation to my supervisor, n Dr Phạm Thị Thu Trà, for her advices, instructions and comments, patient guidance, as lo ad well as encouragement with all her heart during the time of studying and doing this y th thesis Without her guidance, I could not implement and complete my thesis ju yi I also would like to offer my special thanks to Dr.Phạm Khánh Nam and pl Lecturer Lê Anh Khang for the valuable suggestions and materials that help me to n ua al develop this thesis va In addition, I would like to special thanks to all the lecturers at the Vietnam – n Netherlands Program for their knowledge of all the courses during I studied at the ll fu program m oi Besides my mentors, I would like to thank my friends who are always beside me at nh and support for my thesis z Last, but not least, I am very deeply grateful to my family Without their warm z ht vb encouragement, support, and attention, I would not be possible to complete this k jm dissertation om l.c gm n a Lu n va y te re th t to ng ABBREVIATIONS hi ep Average Treatment Effect’ ATT Average Treatment effect on the Treated BPM Balance of Payment Manual DID Difference in Difference ATE w n lo ad Foreign Direct Investment ju y th FDI FEM yi IMF International Monetary Fund NPISH NonProfit Institutions Serving Household ODA Official Development Assistance OLS Ordinary Least Square PSM Propensity Score Matching TFP Total Factor Productivity USD United States Dollar VHLSS Vietnam Household Living Standard Survey VARHS Vietnam Access to Resources Household Survey WB World Bank pl Fixed-Effect Model n ua al n va ll fu oi m at nh z z k jm ht vb om l.c gm n a Lu n va y te re th t to ng ABSTRACT hi ep During the past decades, remittance becomes a new capital source in developing w countries This capital flow which is increasing every year in the developing countries n lo derived from origins such as exporting labors, or migration from countries with low ad y th income to countries with medium or high income Remittance considered the stable ju capital flow for economic growth to labor exporting countries or countries with huge yi pl migration, helps reducing poverty through increasing income of households Until ua al 1986, in most cases remittance received by households living in Ho Chi Minh city in n Viet Nam, after 1986 remittance inflow is expanded to households living in rural areas va of Viet Nam by labor exporting policy Up to now, remittance is increasing more and n ll fu more, and it is also one of tools to alleviate poverty, and to enhance living condition of oi m Viet Nam households So, the aim of this study will examine the effect of remittance at nh on behaviours of households receiving remittance in rural Vietnam Estimation of this effect based on impact evaluation method and data set of Vietnam Access to Resources z z Household Survey (VARHS) in 2006, 2008, and 2010 This data set was carried out by vb jm ht Institute of Labor and Social Sciences, a subsidiary of Ministry of Labor-Invalids and Social Affairs, in 12 rural provinces in North, Middle and South of Viet Nam such as k gm Ha Tay, Lao Cai, Phu Tho, Lai Chau, Dien Bien, Nghe An, Quang Nam, Khanh Hoa, Dak Lak, Dak Nong, Lam Dong, Long An om l.c n a Lu n va y te re th t to ng TABLE OF CONTENTS hi ep DECLARATION ACKNOWLEDGMENT w n ABBREVIATIONS lo ad ABSTRACT ju y th TABLE OF CONTENTS yi LIST OF TABLES pl LIST OF FIGURES 10 al PROBLEM STATEMENT 11 RESEARCH OBJECTIVE 14 RESEARCH QUESTION 14 SCOPE 14 DATA 16 METHODOLOGY 16 THESIS OUTLINE 16 n ua n va ll fu oi m at nh 1 CHAPTER II - THEORETICAL FRAMEWORK 18 z z RELEVANT CONCEPTS AND BROADER ISSUES OF CONCERN 18 1.1 Remittance 18 2.1.2 Literature of migration and remittances 19 2.1.3 Theory of Remittances 23 2 LITERATURE REVIEW: REMITTANCES, INCOME, SAVINGS, ASSET, INSURANCE AND BORROWING 26 SUMMARY OF LITERATURE REVIEW 33 CONCEPTUAL FRAMEWORK 35 k jm ht vb om l.c gm a Lu CHAPTER III - RESEARCH METHODOLOGY 36 n n va PROPENSITY SCORE MATCHING 36 3.1.1 Assumptions of PSM method 37 3.1.2 Model Specification of Propensity Score Matching 38 3.1.3 Software 44 DIFFERENCE IN DIFFERENCE (DD) METHOD 44 y te re th t to ng hi ep w 3.2.1 Theory 44 3.2.2 Implementing DID 45 3.2.3 Model of this study 46 3.3 COMBINING PSM WITH DID METHODS 50 3.4 DATA 51 n lo CHAPTER IV - EMPIRICAL ANALYSIS 55 ad ju y th DESCRIPTIVE ANALYSIS OF THE SAMPLE 55 EMPIRICAL RESULTS 58 2.1 Propensity score matching (PSM) model 58 2.2 DID model 63 2.3 Combining PSM Method and DID Method 68 yi pl ua al n CHAPTER V - CONCLUSIONS AND RECOMMENDATIONS 72 va CONCLUSIONS 72 LIMITATIONS AND SUGGESTIONS FOR FURTHER RESEARCHES 73 n ll fu 5 oi m REFERENCES 74 at nh APPENIX A REMITTANCES DEFINED IN BALANCE OF PAYMENT OF INTERNATIONAL MONETARY FUND 80 z APPENDIX B QUESTIONNAIRE 84 z vb APPENDIX C PROPENSITY SCORE MATCHING METHOD 91 ht k jm APPENDIX D DIFFERENCE IN DIFFERENCE METHOD 127 om l.c gm APPENDIX E PSM AND DID METHODS 147 n a Lu n va y te re th t to ng LIST OF TABLES hi ep w Table 3.1 Variables of Propensity score Matching 41 n lo Table 3.2 Population in each province 42 ad ju y th Table 3.3 Weight of Population in VARHS 2006, VARHS 2008 and VARHS 2010 42 Table 3.4 Variables of Difference in Difference Method 49 yi pl Table 3.5 DID estimation between treatment group and control group 50 ua al n Table Number of HHs receiving remittance and receiving no remittance 55 va n Table Summary of Households with and without remittance 56 fu ll Table 4.3 Expected sign in PSM Model 57 oi m Table 4.4 Expected sign of variables in DD model 58 nh at Table 4.5 Summary of Average Treatment Effect of on Treated Group 62 z z ht vb Table 4.6 Summary the impacts of remittance by PSM method 63 k jm Table 4.7 Results of DID Method in 2006/2008 66 gm Table 4.8 Results of DID Method in 2008/2010 67 Table 4.9 Results of PSM - DID Method in 2006/ 2008 70 l.c om Table 4.10 Results of PSM – DID Method in 2008/2010 71 n a Lu n va y te re th t to ng LIST OF FIGURES hi ep Figure 1 Global Remittances Inflow 11 w n Figure ODA, FDI and Remittance in Viet Nam from 2000 to 2011 13 lo ad Figure Neo-classical mechanism leading to equilibrium 20 y th ju Figure 2 Motives for Remittances 26 yi pl Figure Example of Common Support 38 al n ua Figure An example of Difference in Difference 46 n va ll fu oi m at nh z z k jm ht vb om l.c gm n a Lu n va y te re th 10 t to Table E.18: Model estimated by OLS Model in 2006/2008 ng hi ep w n lo ad ju y th yi pl n ua al n va ll fu Table E.19: Model estimated by Extended OLS Model in 2006/2008 oi m at nh z z k jm ht vb om l.c gm n a Lu n va y te re th 157 t to Table E.20: Model estimated by The Simple Fixed-Effect Model in 2006/2008 ng hi ep w n lo ad ju y th yi pl n ua al n va ll fu Table E.21: Model estimated by The Extended Fixed-Effect Model in 2006/2008 oi m at nh z z k jm ht vb om l.c gm n a Lu n va y te re th 158 t to Table E.22: Common support and balancing tests in 2008/2010 ng hi ep w n lo ad ju y th yi pl n ua al n va ll fu oi m at nh z z k jm ht vb om l.c gm n a Lu n va y te re th 159 t to ng hi ep w n lo ad ju y th yi pl n ua al n va ll fu oi m at nh z z k jm ht vb om l.c gm n a Lu n va y te re th 160 t to Table E.23: Model estimated by OLS Model in 2008/2010 ng hi ep w n lo ad ju y th yi pl n ua al va n Table E.24: Model estimated by Extended OLS Model in 2008/2010 ll fu oi m at nh z z k jm ht vb om l.c gm n a Lu n va y te re th 161 t to Table E.25: Model estimated by The Simple Fixed-Effect Model in 2008/2010 ng hi ep w n lo ad ju y th yi pl n ua al n va ll fu oi m Table E.26: Model estimated by The Extended Fixed-Effect Model in 2008/2010 at nh z z k jm ht vb om l.c gm n a Lu n va y te re th 162 t to Table E.27: Model estimated by OLS Model in 2008/2010 ng hi ep w n lo ad ju y th yi pl n ua al va n Table E.28: Model estimated by Extended OLS Model in 2008/2010 ll fu oi m at nh z z k jm ht vb om l.c gm n a Lu n va y te re th 163 t to Table E.29: Model estimated by The Simple Fixed-Effect Model in 2008/2010 ng hi ep w n lo ad ju y th yi pl n ua al n va fu ll Table E.30: Model estimated by The Extended Fixed-Effect Model in 2008/2010 oi m at nh z z k jm ht vb om l.c gm n a Lu n va y te re th 164 t to Table E.31: Model estimated by OLS Model in 2008/2010 ng hi ep w n lo ad ju y th yi pl n ua al n va Table E.32: Model estimated by Extended OLS Model in 2008/2010 ll fu oi m at nh z z k jm ht vb om l.c gm n a Lu n va y te re th 165 t to Table E.33: Model estimated by The Simple Fixed-Effect Model in 2008/2010 ng hi ep w n lo ad ju y th yi pl n ua al n va ll fu oi m at nh z z k jm ht vb om l.c gm n a Lu n va y te re th 166 t to Table E.34: Model estimated by The Extended Fixed-Effect Model in 2008/2010 ng hi ep w n lo ad ju y th yi pl n ua al n va ll fu oi m at nh z z k jm ht vb om l.c gm n a Lu n va y te re th 167 t to Table E.35: Model estimated by OLS Model in 2008/2010 ng hi ep w n lo ad ju y th yi pl n ua al n va ll fu Table E.36: Model estimated by Extended OLS Model in 2008/2010 oi m at nh z z k jm ht vb om l.c gm n a Lu n va y te re th 168 t to Table E.37: Model estimated by The Simple Fixed-Effect Model in 2008/2010 ng hi ep w n lo ad ju y th yi pl n ua al n va ll fu m oi Table E.38: Model estimated by The Extended Fixed-Effect Model in 2008/2010 at nh z z k jm ht vb om l.c gm n a Lu n va y te re th 169 t to Table E.39: Model estimated by OLS Model in 2008/2010 ng hi ep w n lo ad ju y th yi pl n ua al n va ll fu Table E.40: Model estimated by Extended OLS Model in 2008/2010 oi m at nh z z k jm ht vb om l.c gm n a Lu n va y te re th 170 t to ng hi Table E.41: Model estimated by The Simple Fixed-Effect Model in 2008/2010 ep w n lo ad ju y th yi pl n ua al n va ll fu oi m at nh Table E.42: Model estimated by The Extended Fixed-Effect Model in 2008/2010 z z k jm ht vb om l.c gm n a Lu n va y te re th 171