Risk attitudes, vulnerability, and multidimensional poverty of rural households in Vietnam

Risk attitudes, vulnerability, and multidimensional poverty of rural households in VietnamRisk attitudes, vulnerability, and multidimensional poverty of rural households in VietnamRisk attitudes, vulnerability, and multidimensional poverty of rural households in VietnamRisk attitudes, vulnerability, and multidimensional poverty of rural households in VietnamRisk attitudes, vulnerability, and multidimensional poverty of rural households in VietnamRisk attitudes, vulnerability, and multidimensional poverty of rural households in VietnamRisk attitudes, vulnerability, and multidimensional poverty of rural households in VietnamRisk attitudes, vulnerability, and multidimensional poverty of rural households in VietnamRisk attitudes, vulnerability, and multidimensional poverty of rural households in VietnamRisk attitudes, vulnerability, and multidimensional poverty of rural households in VietnamRisk attitudes, vulnerability, and multidimensional poverty of rural households in VietnamRisk attitudes, vulnerability, and multidimensional poverty of rural households in VietnamRisk attitudes, vulnerability, and multidimensional poverty of rural households in VietnamRisk attitudes, vulnerability, and multidimensional poverty of rural households in VietnamRisk attitudes, vulnerability, and multidimensional poverty of rural households in VietnamRisk attitudes, vulnerability, and multidimensional poverty of rural households in VietnamRisk attitudes, vulnerability, and multidimensional poverty of rural households in VietnamRisk attitudes, vulnerability, and multidimensional poverty of rural households in VietnamRisk attitudes, vulnerability, and multidimensional poverty of rural households in VietnamRisk attitudes, vulnerability, and multidimensional poverty of rural households in VietnamRisk attitudes, vulnerability, and multidimensional poverty of rural households in VietnamRisk attitudes, vulnerability, and multidimensional poverty of rural households in VietnamRisk attitudes, vulnerability, and multidimensional poverty of rural households in VietnamRisk attitudes, vulnerability, and multidimensional poverty of rural households in VietnamRisk attitudes, vulnerability, and multidimensional poverty of rural households in VietnamRisk attitudes, vulnerability, and multidimensional poverty of rural households in VietnamRisk attitudes, vulnerability, and multidimensional poverty of rural households in Vietnam

MINISTRY OF EDUCATION AND TRAINING UNIVERSITY OF ECONOMICS HO CHI MINH CITY VO THI ANH NGUYET Code: NCS2019009 RISK ATTITUDES, VULNERABILITY, AND MULTIDIMENSIONAL POVERTY OF RURAL HOUSEHOLDS IN VIETNAM Ho Chi Minh City, June 2023 MINISTRY OF EDUCATION AND TRAINING UNIVERSITY OF ECONOMICS HO CHI MINH CITY VO THI ANH NGUYET RISK ATTITUDES, VULNERABILITY, AND MULTIDIMENSIONAL POVERTY OF RURAL HOUSEHOLDS IN VIETNAM Major: Development Economics Code: 9310105 SCIENCE INSTRUCTOR Assoc.Prof.Dr TRAN TIEN KHAI Ho Chi Minh City, June 2023 COMMITMENT I hereby declare that this thesis has been completed based on the results of my research and that the results of this research have not been used for any other similar topic Ho Chi Minh city, June 2023 THANK YOU First of all, I would like to thank the teachers at University of Economics Ho Chi Minh city for creating favorable conditions for me during my study as well as during the completion of my graduation thesis In particular, I would like to sincerely thank my supervisor enthusiastically guided, monitored, and gave useful advice to help me solve the problems encountered in the research process and complete the thesis in the best way He has suggested to me the ideas that underpin the discovery in research, contributing to inspiring me to complete the thesis well I'm so grateful for that Ho Chi Minh city, June 2023 i CONTENTS CHAPTER INTRODUCTION 1.1 THE RATIONALE OF THE STUDY 1.1.1 Relationship between risk attitudes, vulnerability, and multidimensional poverty 1.1.2 The rationale of the study 1.2 RESEARCH OBJECTIVES AND QUESTIONS 1.2.1 Research objectives 1.2.2 Research questions 1.3 RESEARCH SUBJECTS 1.4 RESEARCH SCOPE 1.5 THE THESIS’S CONTRIBUTION 11 1.5.1 The practical implication of this study 11 1.5.2 The thesis’s contribution 13 CHAPTER 16 LITERATURE REVIEW 16 2.1 THEORETICAL FRAMEWORKS 16 2.1.1 Empirical studies on the relationship between risk attitudes, vulnerability, and multidimensional poverty 16 2.1.1.1 Empirical studies on the relationship between risk attitudes and multidimensional poverty 16 2.1.1.2 Empirical studies on the relationship between vulnerability and multidimensional poverty 18 2.1.2 Relationship between risk attitudes, vulnerability and multidimensional poverty and theory framework 20 2.1.2.1 Relationship between risk attitudes and multidimensional poverty 20 2.1.2.2 The relationship between vulnerability and multtidimensional poverty 24 2.1.3 Analytical framework 28 ii 2.1.4 Research gaps 32 2.2 CONCEPTS AND THEORY OF MULTI-DIMENSIONS POVERTY 33 2.2.1 Concepts 33 2.2.2 The evolution of the approach to measure poverty in the world from unidimensional poverty to multi-dimensional poverty 35 2.2.3 Methods of measuring multidimensional poverty 36 2.2.3.1 The fuzzy approach 36 2.2.3.2 Alkire–Foster Method for Multidimensional Poverty Measurement 38 2.2.4 Application of measuring unidimensional and multidimensional poverty in Vietnam 43 2.3 VULNERABILITY CONCEPTS AND THEORY 44 2.3.1 The concept of vulnerability 44 2.3.2 Vulnerability measurement methods 46 2.3.2.1 Vulnerability measurement levels 46 2.3.2.2 The Livelihood Vulnerability Index- Intergovernmental Panel on Climate Change (LVI-IPCC) 47 2.3.2.3 The Household Vulnerability Index (HVI) is a measure of vulnerability at the household level 50 2.3.3 Vulnerability assessment frameworks 52 2.4.1 Concepts 55 2.4.2 The utility function 57 2.4.3 Measuring attitudes towards risk 59 CHAPTER 61 INFLUENCE OF DISASTER ASSISTANCE ON MULTIDIMENSIONAL POVERTY: EVIDENCE FROM RURAL VIETNAM 61 3.1 INTRODUCTION 61 3.2 POVERTY AND NATURAL DISASTER ASSISTANCE 63 3.3 METHODOLOGY .65 3.3.1 Alkire–Foster method for multidimensional poverty measurement 65 iii 3.3.2 Propensity score matching (PSM) 65 3.3.3 Data 68 3.4 RESULTS 71 3.4.1 Multidimensional poverty status quo 71 3.4.2 Distribution of the multidimensional poor households in Vietnam in the period from 2014 to 2018 by economic regions 74 3.4.3 Multidimensional poverty index (MPI) by region in Vietnam in period 20142018 76 3.4.4 The impact of disaster assistance on the multidimensional poverty levels of households in Vietnam 77 3.5 CHAPTER CONCLUSION .89 CHAPTER 90 CLIMATE CHANGE AND RURAL VULNERABILITY IN VIETNAM: AN ANALYSIS OF LIVELIHOOD VULNERABILITY INDEX 90 4.1 INTRODUCTION .90 4.2 LITERATURE REVIEW: RELATIONSHIP BETWEEN CLIMATE CHANGE AND RURAL VULNERABILITY 92 4.3 METHODS AND DATA SET 93 4.3.1 Calculating the LVI 93 4.3.2 Calculating the LVI-IPCC 95 4.3.3 Study area 97 4.4 FINDINGS AND DISCUSSION 98 4.4.1 Exposure profile 98 4.4.2 Adaptive profiles: Socio-demographic profile, livelihood strategies, and social networks 102 4.4.3 Sensitivity profiles: Health, food, and water status 102 4.4.4 Major Components for LVI 103 4.4.5 LVI-IPCC analysis 105 4.5 CHAPTER CONCLUSION 109 iv CHAPTER 110 ASSESSING THE IMPACT OF SHOCKS ON HOUSEHOLD VULNERABILITY: EVIDENCE FROM RURAL VIETNAM 110 5.1 INTRODUCTION 110 5.2 SHOCKS AND HOUSEHOLD VULNERABILITY .111 5.2.1 Shocks 111 5.2.2 Vulnerability 112 5.2.3 Shocks and household vulnerability 113 5.3 METHODOLOGY 115 5.3.1 Calculating the Household Vulnerability Index (HVI) 115 5.3.2 Empirical Model Specification 119 5.3.3 Data 119 5.4.2 The impact of shocks on household vulnerability in Vietnam 125 5.5 CHAPTER CONCLUSIONS 130 CHAPTER 131 THE RELATIONSHIP BETWEEN RISK ATTITUDE, VULNERABILITY, AND MULTIDIMENSIONAL POVERTY 131 6.1 THE IMPACT OF RISK ATTITUDES ON CLIMATE CHANGE RESILIENCE 131 6.1.1 The relationship between risk attitudes and climate change resilience 131 6.1.2 Methodology 132 6.1.3 The influence of risk attitudes on climate change resilience 132 6.2 THE RELATIONSHIP BETWEEN RISK ATTITUDE, VULNERABILITY, AND MULTIDIMENSIONAL POVERTY 138 6.2.2 Methodology 140 6.3 CHAPTER CONCLUSION 154 CHAPTER 155 CONCLUSIONS AND POLICY IMPLICATIONS 155 7.1 CONCLUSIONS .155 7.2 POLICY IMPLICATIONS .157 v 7.2.1 Policy implications in Vietnam 157 7.2.2 Policy implications for each region 158 ENGLISH REFERENCES 161 VIETNAMESE REFERENCES 209 APPENDIX 207 APPENDIX 232 APPENDIX 235 APPENDIX 240 vi LIST OF ABBREVIATIONS 3SLS Three-stage least squares A Average deprivation share ASF African swine fever ATT The average treatment effect on the treated CCVA Climate Change Vulnerability Assessments CCVI Climate Change Vulnerability index CF Contributing factor DPSIR Drivers-Pressures-States-Impacts and Respones EPVI Energy Poverty Vulnerability Index EVI Economic Vulnerability Index FANRPAN The Food, Agriculture and Natural Resources Policy Analysis Network OLS Ordinary Least Squares GDP Gross Dometics Product GSO General Statistics Office H Headcount ratio HCCVI Habitat Climate Change Vulnerability Index HVI Household Vulnerability Index IPCC Intergovernmental Panel on Climate Change IV Instrumental Variable LSMS Living Standard Measurement Surveys LVI The Livelihood Vulnerability Index LVIp Livelihood Vulnerability Index for province p MCA Multiple Correspondence Analysis MDP Multidimensional Poverty MLVI the Multidimensional Livelihood Vulnerability Index Mp Major components for province p MPI Multidimensional Poverty Index MPHS Multi Purpose Housdhold Survey 227 Table A.8: Livelihood Vulnerability Index (LVI) sub-component values Major components Sociodemographic profile Subcompon ents SD1 SD2 SD3 Livelihood units Ratio % 0.63 23.66 0.71 12.84 0.54 21.92 0.57 18.13 0.49 30.20 5.00 100 0.00 MRD Max Min 29.91 2.95 6.16 5.48 15.01 2.27 6.71 2.01 100 100 0 L1 % 6.45 21.31 6.85 14.73 22.82 100 L2 % 55.20 89.22 79.45 84.99 81.88 100 km 0.30 1.12 0.25 2.87 0.27 1.79 0.27 2.55 0.29 2.08 0.5 80 0.2 % 12.19 8.86 14.73 9.63 24.16 100 H3 % 26.52 22.59 29.45 23.51 36.91 100 H4 % 0.00 0.00 0.00 0.00 0.00 100 Ratio Ratio 0.97 0.65 1.10 0.66 1.05 0.60 1.13 0.75 1.02 0.70 0.5 0.5 44.80 52.69 87.68 77.28 41.78 54.11 75.35 53.54 74.50 28.86 100 100 0 0.45 21.51 97.85 89.25 9.32 0.34 12.20 74.07 46.21 58.02 0.39 16.44 48.29 43.49 2.74 0.37 60.34 88.39 17.85 1.98 0.45 89.93 90.60 62.42 8.05 0.50 100 100 100 100 0.13 0 0 0.26 60.57 2.05 22.98 0.49 16.10 1.53 9.92 0.03 51.01 610 100 0 0.94 2.13 0.92 H2 SN1 SN2 F1 % % F2 Water Central Highlands 4.30 2.15 SN3 Food NC&SC C* % % H1 Social networks Northern Midlands &Mountain SD4 L3 Health Red River Delta F3 F4 W1 W2 W3 W4 Natural ND1 disasters and ND2 climate variability ND3 ND4 ND5 ND6 % % % % minut es % % Celsi us 0.00 0.32 0.00 100 4.61 4.74 2.83 1.37 1.05 9.60 0.82 hours mm % 50.89 139.12 4.00 58.05 183.70 3.54 62.26 232.80 4.27 45.01 134.25 4.99 40.02 114.90 3.80 104.73 412.51 7.74 34.29 113.68 2.43 Source: Calculated from VARHS, DMPTC and Provincial Statistical Yearbook 228 Table A.9: The explanation of variables affecting household vulnerability Variable HVI Natural_shocks Explanation Household Vulnerability Index (0,1) Estimated damage due to natural shocks (thousand USD) Biological_shocks Estimated damage due to biological shocks (thousand USD) Economic_shocks Estimated damage due to economic shocks (thousand USD) Age of household head Age Gender Ethnicity Education Dependents Households size Wage/salary Agriculture activities Non-farm activities Source FANRPAN, 2011 Opiyo, 2014; Visser, 2014; Akampumuza & Matsuda, 2017; Hill & Porter, 2017; Sun et al, 2010; Nguyen & Leisz, 2021; Nguyen et al., 2021b Hung et al., 2021; Raynor & Panza, 2021; Narayan, 2020; Nguyen et al., 2021a; Song et al., 2020 Opiyo, 2014 Opiyo, 2014; Thabane, 2015; Zhou et al, 2016; Jimoh, 2021; Dwyer et al., 2004; Smith et al., 2015 Gender of household head, if Dwyer et al., 2004; Opiyo, 2014; household head is female received Thabane, 2015; Zhou et al, 2016; 1, otherwise Akampumuza & Matsuda, 2017; Jimoh, 2021; Walugembe et al., 2019 Ethnic of household head, if Mustafa et al., 2011; Zhou et al, 2016; household head is Kinh people received 1, otherwise Education level of household head Frankenberg et al., 2013; Opiyo, 2014; (0,12) Mustafa et al., 2011; Pichler & Striessnig, 2013; Zhou et al, 2016; Jimoh, 2021; Total number of dependents Opiyo, 2014; Mustafa et al., 2011; Total number of household Opiyo, 2014; Thabane, 2015; members Walugembe et al., 2019 Numbers of households working Dwyer et al., 2004; Mustafa et al., for a wage/salary outside the 2011; Thabane, 2015; Jimoh, 2021 household Participating in household Jimoh, 2021 production related to agriculture, Praveen & Sharma, 2019; Thabane, forestry, and aquaculture; 2015; participating 1, otherwise Doing trading, services, Imai et al., 2015; Jimoh, 2021; transportation, or other business Thabane, 2015; 229 Variable Using resources Doing housework Participation in social Divorced Explanation (self-employed) for the household Non-farm, non-wage activities, not housework; participating 1, otherwise Using common property resources to generate income for the household (hunting, fishing in the sea or lakes not on your property, gathering honey and berries, gathering forestry products etc ); used 1, otherwise Doing housework or chores (cleaning, collecting firewood, washing clothes, cooking, etc ); doing 1, otherwise The number of social activities that the household participates in if household head is divorced or separated received 1, otherwise Widowed if household head is widowed received 1, otherwise Single if household head is single received 1, otherwise Source Thabane, 2015; Jimoh, 2021 Thabane, 2015; Freedman et al., 2014; Tabler & Geist (2021) Mustafa et al., 2011; Walugembe et al., 2019 Herbst-Debby et al., 2021; Kadir & Bifulco, 2013; Putra et al., 2019; Zhou et al., 2016 Herbst-Debby et al., 2021; Kadir & Bifulco, 2013; Putra et al., 2019; Zhou et al., 2016 Kadir & Bifulco, 2013; Putra et al., 2019; Zhou et al., 2016 230 Table A.10: The explanation of variables affecting climate change resilience Variables Explanation The binary dependent variables New varieties Get the value if the household applies new plant varieties, otherwise get a value of Investment Get the value if the household households have more investment, otherwise get a value of Diversification Get the value if the household has seasonal diversification, otherwise get a value of Crop insurance Get the value the if household participates in crop insurance, otherwise get a value of Relevant referees Shikuku et al., 2017; Begho, 2021; Jianjun et al., 2015; Jin et al., 2020 Bergfjord, 2013; Jin et al., 2020; Jianjun et al., 2015 Bezabih & Sarr, 2012; Sarwosri & Mußhoff, 2020; Shikuku et al., 2017; Jin et al., 2020 Menapace et ql., 2016; Petrolia et al., 2013; Simon & Fiorentino, 2014; Jianjun et al., 2015; Sherrick et al., 2004; Zhang et al., 2021; Pham et al., 2021 Independent variables Risk averse Get the value if a farmer is risk averse, otherwise get a value of Age Age of household head Farmland Land area owned (1000 m2) Credit Get the value if a farmer participates in credit, otherwise get a value of Average monthly income of household (million VND) Education level of household head (years) Income Education Petrolia et al., 2013; Simon & Fiorentino, 2014; Jianjun et al., 2015; Sherrick et al., 2004 Jin Jianjun et al., 2015; Sherrick et al., 2004; Zhao et al 2016 Jin Jianjun et al., 2015; Sherrick et al., 2004; Pham et al., 2021; Zhao et al 2016 Jin et al., 2020 Deressa et al., 2009; Jin Jianjun et al., 2015; Jin et al., 2020 Jin Jianjun et al., 2015; Jin et al., 2020 231 Table A.11: Descriptive statistics for 3SLS regression Variable Obs Mean Sta Dev Min Max Deprivation scores 1,472 0.126 0.117 0.611 HVI 1,472 0.623 0.039 0.437 0.728 Risk aversion 1,472 0.618 0.486 Age 1,472 50.400 12.278 18 94 Gender (Male=1, Female=0) 1,472 0.867 0.339 Ethnic (Kinh=1, others 0) 1,472 0.466 0.499 Education 1,472 6.431 3.796 12 Dependents (people) 1,472 1.909 1.329 Household members (people) 1,472 4.614 1.758 12 Married 1,472 0.885 0.319 Divorced 1,472 0.014 0.119 Widowed 1,472 0.095 0.293 Credit 1,472 0.342 0.475 Disaster 1,472 0.401 0.490 Agricutural activitiesa 1,472 2.811 1.295 10 Non-farm activitiesb 1,472 0.291 0.722 Log(Income) 1,472 2.465 0.382 0.585 4.818 Social activities 1,472 0.898 0.303 Natural shocks (thousand USD) Biological shocks (thousand USD) Economic shocks (thousand USD) 1,472 0.003 0.029 0.652 1,472 0.013 0.139 4.043 1,472 0.017 0.175 3.913 232 APPENDIX Influence of disaster assistance on multidimensional poverty Iteration 0: log likelihood = -1781.4613 Iteration 1: log likelihood = -1694.4893 Iteration 2: log likelihood = -1686.3913 Iteration 3: log likelihood = -1686.3643 Iteration 4: log likelihood = -1686.3643 Probit regression Number of obs Log likelihood = -1686.3643 = 23,183 LR Chi-squared(22) = 190.19 Prob > Chi-squared = 0.0000 Pseudo R2 = 0.0534 disaster_assistance | Coef Std Err z P>|z| [95% Conf Interval] + -flood | -.122579 110016 -1.11 0.265 -.3382065 0930484 storm | -.3203932 1449369 -2.21 0.027 -.6044644 -.036322 drought | 6728993 1930704 3.49 0.000 2944884 1.05131 Age | 0076138 0020808 3.66 0.000 0035355 0116921 Gender | -.0093695 0792571 -0.12 0.906 -.1647106 1459716 ethnic | -.2606147 0662903 -3.93 0.000 -.3905413 -.1306881 married | 1897887 0898989 2.11 0.035 01359 3659873 credit | 0909022 0535653 1.70 0.090 -.0140839 1958883 farmland1000m2 | 0002609 0006494 0.40 0.688 -.0010119 0015337 renting | 2402539 0743296 3.23 0.001 0945705 3859372 poverty_2018 | 0896998 0722183 1.24 0.214 -.0518454 231245 children | 0253549 0228746 1.11 0.268 -.0194785 0701882 Disabilitysick | -.1511255 1033217 -1.46 0.144 -.3536323 0513814 ederlyretired | 023025 06172 0.37 0.709 -.0979441 143994 unemployed | -.2461442 1058851 -2.32 0.020 -.4536751 -.0386132 Southeast | 2274208 1039597 2.19 0.029 0236636 4311781 Northwest | -.0974233 1113037 -0.88 0.381 -.3155746 120728 Northeast | -.4116916 1179534 -3.49 0.000 -.6428761 -.1805071 RedRiverDelta | 2077527 0763568 2.72 0.007 0580961 3574093 NorthCentral | 5322565 0770177 6.91 0.000 3813045 6832085 SouthCentralCoast | 0851653 0928575 0.92 0.359 -.096832 2671626 Central_Highland | 2241936 1026858 2.18 0.029 0229331 4254541 _cons | -2.718982 1627342 -16.71 0.000 -3.037935 -2.400029 margins, dydx(*) atmeans post Conditional marginal effects Number of obs Model VCE : OIM Expression : Pr(disaster_assistance), predict() = 23,183 233 dy/dx w.r.t : flood storm drought Age Gender ethnic married credit farmland1000m2 renting poverty_2018 children Disabilitysick ederlyretired unemployed Southeast Northwest Northeast RedRiverDelta NorthCentral SouthCentralCoast Central_Highland | Delta-method | dy/dx Std Err z P>|z| [95% Conf Interval] + -flood | -.0036906 0033095 -1.12 0.265 -.0101772 0027959 storm | -.0096465 004326 -2.23 0.026 -.0181254 -.0011676 drought | 0202599 0058648 3.45 0.001 0087651 0317547 Age | 0002292 0000621 3.69 0.000 0001075 000351 Gender | -.0002821 0023862 -0.12 0.906 -.004959 0043948 ethnic | -.0078467 0019854 -3.95 0.000 -.0117379 -.0039554 married | 0057142 0026961 2.12 0.034 00043 0109985 credit | 0027369 00161 1.70 0.089 -.0004187 0058925 farmland1000m2 | 7.85e-06 0000195 0.40 0.688 -.0000305 0000462 renting | 0072336 0022367 3.23 0.001 0028497 0116176 poverty_2018 | 0027007 0021724 1.24 0.214 -.0015572 0069586 children | 0007634 0006884 1.11 0.267 -.0005859 0021127 Disabilitysick | -.0045501 0031015 -1.47 0.142 -.010629 0015287 ederlyretired | 0006932 0018578 0.37 0.709 -.0029479 0043344 unemployed | -.007411 0031717 -2.34 0.019 -.0136275 -.0011945 Southeast | 0068473 0031186 2.20 0.028 0007348 0129597 Northwest | -.0029333 0033529 -0.87 0.382 -.0095049 0036383 Northeast | -.0123953 0034618 -3.58 0.000 -.0191803 -.0056104 RedRiverDelta | 0062551 0022837 2.74 0.006 001779 0107311 NorthCentral | 0160254 0023134 6.93 0.000 0114912 0205595 SouthCentralCoast | 0025642 0027929 0.92 0.359 -.0029098 0080382 Central_Highland | 0067501 0030842 2.19 0.029 0007051 0127951 The program is searching the nearest neighbor of each treated unit This operation may take a while ATT estimation with Nearest Neighbor Matching method (random draw version) Analytical standard errors n treat n contr ATT Std Err t 342 365 -0.015 0.007 -2.160 Note: the numbers of treated and controls refer to actual nearest neighbour matches The program is searching for matches of treated units within radius This operation may take a while 234 ATT estimation with the Radius Matching method Analytical standard errors n treat n contr ATT Std Err t 339 22334 -0.018 0.005 -3.619 Note: the numbers of treated and controls refer to actual matches within radius The program is searching for matches of each treated unit This operation may take a while ATT estimation with the Kernel Matching method n treat n contr ATT Std Err t 342 22484 -0.018 Note: Analytical standard errors cannot be computed Use the bootstrap option to get bootstrapped standard errors Bootstrapping of standard errors command: attk Deprivation_score disaster_assistance , pscore(luu) comsup bwidth(.06) statistic: attk = r(attk) note: label truncated to 80 characters Bootstrap statistics Number of obs = 23183 Replications = 50 -Variable | Reps Observed Bias Std Err [95% Conf Interval] -+ -attk | -.0271612 -.0095249 (N) | 50 -.0183431 -.001365 0043881 -.0269521 -.0110689 (P) | -.0261323 -.0090714 (BC) -Note: N = normal P = percentile BC = bias-corrected ATT estimation with the Kernel Matching method Bootstrapped standard errors n treat n contr ATT Std Err t 342 22484 -0.018 0.004 -4.180 - 235 APPENDIX Whole country Linear regression Number of obs = 2,974 F(18, 2955) = 53.65 Prob > F = 0.0000 R-squared = 0.2564 Root MSE = 03465 | HVI | Robust Coef Std Err t P>|t| [95% Conf Interval] + -natural_2018thousandUSD | 0059457 0059821 0.99 0.320 -.0057839 0176752 biological_2018thousandUSD | -.0053558 0045391 -1.18 0.238 -.014256 0035443 economic_2018thousandUSD | 0053319 0024406 2.18 0.029 0005464 0101174 age | -.0007553 0000566 -13.35 0.000 -.0008662 -.0006444 ethnic | -.0003124 0018616 -0.17 0.867 -.0039626 0033378 gender | -.0047667 0025507 -1.87 0.062 -.009768 0002346 education | -.0013215 0002051 -6.44 0.000 -.0017237 -.0009193 HHmember | -.0163918 0008014 -20.45 0.000 -.0179632 -.0148204 dependents | 0088736 0007364 12.05 0.000 0074296 0103176 Workingforawagesalary | -.0000475 000711 -0.07 0.947 -.0014416 0013465 Participatinginhouseholdprodu | 0044609 0008206 5.44 0.000 0028518 00607 Doingtradingservicestranspo | -.0028829 0010051 -2.87 0.004 -.0048537 -.000912 Usingcommonpropertyresources | -.0003817 0007004 -0.54 0.586 -.0017549 0009916 Doinghouseworkorchoresclean | 0027821 0006632 4.19 0.000 0014816 0040826 Participation_in_social | -.0065365 0020669 -3.16 0.002 -.0105892 -.0024837 divorced | -.0096533 0062184 -1.55 0.121 -.0218462 0025395 widowed | -.0119137 0028276 -4.21 0.000 -.017458 -.0063694 single | -.0113651 0075648 -1.50 0.133 -.0261979 0034676 _cons | 7199781 0046006 156.50 0.000 7109574 7289988 - 236 Northern Midlands and Mountains Linear regression Number of obs = 1,362 F(18, 1343) = 34.57 Prob > F = 0.0000 R-squared = 0.2980 Root MSE = 03372 | HVI | Robust Coef Std Err t P>|t| [95% Conf Interval] + -natural_2018thousandUSD | 0171217 0093489 1.83 0.067 -.0012183 0354618 biological_2018thousandUSD | -.0059312 0036664 -1.62 0.106 -.0131237 0012612 economic_2018thousandUSD | -.0066991 0080966 -0.83 0.408 -.0225825 0091842 age | -.001005 0000832 -12.08 0.000 -.0011682 -.0008418 ethnic | 0034634 0029178 1.19 0.235 -.0022605 0091873 gender | 0022108 0036842 0.60 0.549 -.0050166 0094381 education | -.0013085 0002882 -4.54 0.000 -.001874 -.0007431 HHmember | -.0173773 0011718 -14.83 0.000 -.019676 -.0150786 dependents | 0105973 0010659 9.94 0.000 0085062 0126883 Workingforawagesalary | -.0016508 0009796 -1.69 0.092 -.0035724 0002709 Participatinginhouseholdprodu | 0035613 0012687 2.81 0.005 0010724 0060502 Doingtradingservicestranspo | -.0024634 001648 -1.49 0.135 -.0056964 0007696 Usingcommonpropertyresources | 0009242 0008859 1.04 0.297 -.0008137 0026621 Doinghouseworkorchoresclean | 0046418 0010045 4.62 0.000 0026712 0066124 Participation_in_social | -.0131484 0027156 -4.84 0.000 -.0184758 -.007821 divorced | -.0123259 0081926 -1.50 0.133 -.0283976 0037458 widowed | -.0026703 0042743 -0.62 0.532 -.0110553 0057147 single | -.0210132 0106962 -1.96 0.050 -.0419962 -.0000302 _cons | 724415 0062054 116.74 0.000 7122417 7365883 - 237 Red River Delta Linear regression Number of obs = 362 F(18, 343) = 18.42 Prob > F = 0.0000 R-squared = 0.4206 Root MSE = 02946 | HVI | Robust Coef Std Err t P>|t| [95% Conf Interval] + -natural_2018thousandUSD | 0048309 0079009 0.61 0.541 -.0107093 0203711 biological_2018thousandUSD | -.0455018 0152691 -2.98 0.003 -.0755347 -.0154689 economic_2018thousandUSD | -.003216 0028688 -1.12 0.263 -.0088585 0024266 age | -.0006078 0001762 -3.45 0.001 -.0009544 -.0002612 ethnic | -.0111892 0145871 -0.77 0.444 -.0398807 0175022 gender | 0031363 0054043 0.58 0.562 -.0074935 013766 education | -.000089 0005694 -0.16 0.876 -.0012089 001031 HHmember | -.0198559 002433 -8.16 0.000 -.0246414 -.0150704 dependents | 0091776 0021294 4.31 0.000 0049893 013366 Workingforawagesalary | -.0006782 0022444 -0.30 0.763 -.0050927 0037363 Participatinginhouseholdprodu | 0008569 002438 0.35 0.725 -.0039384 0056521 Doingtradingservicestranspo | -.00131 002056 -0.64 0.524 -.005354 0027339 Usingcommonpropertyresources | -.0026295 0029069 -0.90 0.366 -.0083472 0030881 Doinghouseworkorchoresclean | 0015433 0019224 0.80 0.423 -.0022378 0053244 Participation_in_social | 0010702 0055765 0.19 0.848 -.0098982 0120386 divorced | -.0176189 0101723 -1.73 0.084 -.0376267 002389 widowed | -.0097264 0065695 -1.48 0.140 -.0226479 0031951 single | 025923 0094317 2.75 0.006 0073718 0444742 _cons | 7206625 0199384 36.14 0.000 6814455 7598795 - 238 North Central and South-Central Coast Linear regression Number of obs = 432 F(17, 414) = 14.34 Prob > F = 0.0000 R-squared = 0.3580 Root MSE = 03198 | HVI | Robust Coef Std Err t P>|t| [95% Conf Interval] + -biological_2018thousandUSD | 0615471 0532199 1.16 0.248 -.0430678 166162 economic_2018thousandUSD | 0185931 0048794 3.81 0.000 0090017 0281845 age | -.0006363 0001414 -4.50 0.000 -.0009142 -.0003584 ethnic | 0128301 0056297 2.28 0.023 0017638 0238965 gender | -.0194326 0066855 -2.91 0.004 -.0325745 -.0062908 education | -.0018826 000552 -3.41 0.001 -.0029678 -.0007975 HHmember | -.0150918 002003 -7.53 0.000 -.0190291 -.0111545 dependents | 0027144 0019241 1.41 0.159 -.0010677 0064966 Workingforawagesalary | -.0021959 0020681 -1.06 0.289 -.0062613 0018694 Participatinginhouseholdprodu | -.0000505 0021576 -0.02 0.981 -.0042917 0041906 Doingtradingservicestranspo | -.0044486 0027527 -1.62 0.107 -.0098597 0009625 Usingcommonpropertyresources | 0027846 0025264 1.10 0.271 -.0021817 0077508 Doinghouseworkorchoresclean | 006319 0018145 3.48 0.001 0027522 0098858 Participation_in_social | -.0061359 0081755 -0.75 0.453 -.0222066 0099348 divorced | -.0105214 0127423 -0.83 0.409 -.0355691 0145263 widowed | -.0216792 0070531 -3.07 0.002 -.0355435 -.0078148 single | -.0163954 013379 -1.23 0.221 -.0426947 0099039 _cons | 7340311 0138825 52.87 0.000 7067422 76132 - 239 Central Highland Linear regression Number of obs = 625 F(18, 606) = 6.19 Prob > F = 0.0000 R-squared = 0.1671 Root MSE = 03545 | HVI | Robust Coef Std Err t P>|t| [95% Conf Interval] + -natural_2018thousandUSD | -.0044023 0197559 -0.22 0.824 -.0432006 034396 biological_2018thousandUSD | -.0083138 0103807 -0.80 0.424 -.0287004 0120728 economic_2018thousandUSD | 0043114 003048 1.41 0.158 -.0016745 0102973 age | -.0004899 000132 -3.71 0.000 -.0007491 -.0002308 ethnic | -.0067809 0033947 -2.00 0.046 -.0134476 -.0001141 gender | -.006701 0061015 -1.10 0.273 -.0186837 0052818 education | -.001368 0004296 -3.18 0.002 -.0022117 -.0005243 HHmember | -.0124593 0018508 -6.73 0.000 -.016094 -.0088245 dependents | 007525 0016236 4.63 0.000 0043365 0107134 Workingforawagesalary | 0017461 001341 1.30 0.193 -.0008876 0043797 Participatinginhouseholdprodu | 0049544 0017657 2.81 0.005 0014868 008422 Doingtradingservicestranspo | -.000431 0024276 -0.18 0.859 -.0051984 0043365 Usingcommonpropertyresources | -.0002613 0018932 -0.14 0.890 -.0039793 0034567 Doinghouseworkorchoresclean | -.0005322 001209 -0.44 0.660 -.0029066 0018422 Participation_in_social | -.0068423 0049879 -1.37 0.171 -.0166379 0029533 divorced | -.0046979 0132698 -0.35 0.723 -.0307581 0213624 widowed | -.0174744 0067879 -2.57 0.010 -.030805 -.0041438 single | -.0118712 0156984 -0.76 0.450 -.0427009 0189586 _cons | 7083388 0106845 66.30 0.000 6873556 729322 - 240 APPENDIX The relationship between risk attitude, vulnerability, and multidimensional poverty Three-stage least-squares regression -Equation Obs Parms RMSE "R-sq" Chi-squared P -Deprevatio~e 1,468 12 1070609 0.1682 366.04 0.0000 HVI 1,468 15 1151462 -7.5206 207.13 0.0000 risk_averse 1,468 4897166 -0.0164 43.64 0.0000 -| Coef Std Err z P>|z| [95% Conf Interval] + -Deprevationscore | HVI | 1.045628 2369776 4.41 0.000 5811607 1.510096 risk_averse | -.0099013 0204119 -0.49 0.628 -.0499079 0301052 age | 0015055 0003525 4.27 0.000 0008146 0021965 ethnic | -.0993042 0071228 -13.94 0.000 -.1132647 -.0853438 education | -.0033163 0008986 -3.69 0.000 -.0050775 -.0015551 Doingtradingservicestranspo | 0035282 0038637 0.91 0.361 -.0040445 0111009 HHmember | 0003271 0018592 0.18 0.860 -.0033169 0039711 dependents | -.0031141 0025922 -1.20 0.230 -.0081947 0019665 married | -.0467098 0346084 -1.35 0.177 -.1145411 0211215 widowed | -.0559407 0359253 -1.56 0.119 -.1263531 0144717 divorced | -.0203267 0409482 -0.50 0.620 -.1005837 0599303 credit | -.0024067 0012485 -1.93 0.054 -.0048538 0000403 _cons | -.4756583 1608156 -2.96 0.003 -.7908511 -.1604654 + -HVI | Deprevationscore | 1.088405 1663126 6.54 0.000 7624384 1.414372 age | -.0015336 000293 -5.23 0.000 -.0021079 -.0009592 gender | -.0002066 003074 -0.07 0.946 -.0062316 0058184 education | 0035766 0010717 3.34 0.001 001476 0056771 ethnic | 1077559 0172647 6.24 0.000 0739176 1415941 dependents | 0038705 0025156 1.54 0.124 -.00106 008801 Participation_in_social | -.0023157 0040121 -0.58 0.564 -.0101793 0055478 Doingtradingservicestranspo | -.0043577 0040848 -1.07 0.286 -.0123637 0036484 logincome | 0061962 0048467 1.28 0.201 -.0033031 0156955 241 married | 0465989 0376713 1.24 0.216 -.0272355 1204333 widowed | 0577949 0393294 1.47 0.142 -.0192893 1348791 divorced | 0099586 0438499 0.23 0.820 -.0759855 0959028 natural_2018thousandUSD | -.0205333 0195483 -1.05 0.294 -.0588473 0177807 biological_2018thousandUSD | 0083092 0046805 1.78 0.076 -.0008644 0174829 economic_2018thousandUSD | 004156 0031346 1.33 0.185 -.0019877 0102998 _cons | 4230117 0561193 7.54 0.000 3130199 5330035 + -risk_averse | Deprevationscore | -.8750346 3101349 -2.82 0.005 -1.482888 -.2671813 HVI | 5734792 1.070863 0.54 0.592 -1.525373 2.672332 age | 0027862 0013488 2.07 0.039 0001425 0054298 gender | -.0220877 038084 -0.58 0.562 -.096731 0525555 education | -.0089524 0043879 -2.04 0.041 -.0175524 -.0003523 agricultureactivities | 0542794 0140142 3.87 0.000 0268121 0817467 disaster | -.0545481 0239544 -2.28 0.023 -.1014978 -.0075984 HHmember | -.0413528 0139467 -2.97 0.003 -.0686879 -.0140177 _cons | 3686776 7461818 0.49 0.621 -1.093812 1.831167 Endogenous variables: Deprevationscore HVI risk_averse Exogenous variables: age ethnic education Doingtradingservicestranspo HHmember dependents married widowed divorced credit gender Participation_in_social logincome natural_2018thousandUSD biological_2018thousandUSD economic_2018thousandUSD agricultureactivities disaster