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Assessing household vulnerability and coping strategies to floods [Elektronische Ressource] : a comparative study of flooded and non-flooded areas in Bangladesh, 2005 / von Israt Rayhan

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Assessing Household Vulnerability and Coping Strategies to Floods: A Comparative Study of Flooded and Non-flooded Areas in Bangladesh, 2005 Von der Wirtschaftswissenschaftlichen Fakultät der Gottfried Wilhelm Leibniz Universität Hannover zur Erlangung des akademischen Grades Doktor der Wirtschaftswissenschaften -Doctor rerum politicarum- genehmigte Dissertation von Md. Israt Rayhan (M.Sc.) Geboren am 24.05.1977 in Dhaka, Bangladesch 2008 Erstgutachterin: Professor Dr. Ulrike Grote Institut für Umweltökonomik und Welthandel Wirtschaftswissenschaftliche Fakultät der Leibniz Universität Hannover Zweitgutachter: Professor Dr. Hermann Waibel Institut für Entwicklungs- und Agrarökonomik Wirtschaftswissenschaftliche Fakult Tag der Promotion: 12.06.2008 Table of Contents List of Tables iii List of Figures iv List of Boxes v List of Appendices vi Acronyms viii Abstract ix Zusammenfassung xi Acknowledgement xiv 1. Introduction 1 1.1 Problem Statement 2 1.2 Research Objectives and Questions 4 1.3 Outline of this Study 5 2. Literature Review: Theoretical and Empirical 6 2.1 Vulnerability Concept from Economics Literature 6 2.1.1 Poverty Dynamics Literature 6 2.1.2 Asset-based Literature 12 2.1.3 Livelihoods Literature 13 2.1.4 Food Security Literature 14 2.

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Published 01 January 2008
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Assessing Household Vulnerability and Coping Strategies to
Floods: A Comparative Study of Flooded and Non-flooded
Areas in Bangladesh, 2005





Von der Wirtschaftswissenschaftlichen Fakultät der
Gottfried Wilhelm Leibniz Universität Hannover
zur Erlangung des akademischen Grades

Doktor der Wirtschaftswissenschaften
-Doctor rerum politicarum-

genehmigte Dissertation
von



Md. Israt Rayhan (M.Sc.)

Geboren am 24.05.1977 in Dhaka, Bangladesch

2008















Erstgutachterin: Professor Dr. Ulrike Grote
Institut für Umweltökonomik und Welthandel
Wirtschaftswissenschaftliche Fakultät der Leibniz Universität Hannover

Zweitgutachter: Professor Dr. Hermann Waibel
Institut für Entwicklungs- und Agrarökonomik
Wirtschaftswissenschaftliche Fakult

Tag der Promotion: 12.06.2008 Table of Contents

List of Tables iii
List of Figures iv
List of Boxes v
List of Appendices vi
Acronyms viii
Abstract ix
Zusammenfassung xi
Acknowledgement xiv
1. Introduction 1
1.1 Problem Statement 2
1.2 Research Objectives and Questions 4
1.3 Outline of this Study 5
2. Literature Review: Theoretical and Empirical 6
2.1 Vulnerability Concept from Economics Literature 6
2.1.1 Poverty Dynamics Literature 6
2.1.2 Asset-based Literature 12
2.1.3 Livelihoods Literature 13
2.1.4 Food Security Literature 14
2.2 Vulnerability Concept from Non-economics Literature 14
2.2.1 Sociology and Anthropology Literature 15
2.2.2 Disaster Management Literature 15
2.2.3 Environment Literature 16
2.2.4 Health and Nutrition Literature 16
2.3 Assessment of Literature from Different Disciplines 17
2.4 Summary and Conclusion 18
3. Conceptual Framework and Methodology 19
3.1 Conceptual Framework: Poverty, Risk and Vulnerability 19
3.1.1 Risk and Uncertainty 23
3.1.2 Utility Function and Risk Aversion 23
3.2 Indicators of Vulnerability to Flood Risk 28
3.3 Methodologies for Estimating Vulnerability 32
3.3.1 Vulnerability to Poverty Line 32
3.3.2 Vulnerability to Expected Poverty 36
3.3.3 Vulnerability to Expected Utility 43
3.3.4 Vulnerability Estimate using Monte Carlo Bootstrap Simulation 46
3.3.5 Poverty Line 50
3.4 Summary and Conclusion 51
4. Case Study: Bangladesh, Survey Area Profiles and Descriptive Analysis 56
4.1 Country Background: Bangladesh 56
4.1.1 Topography of Bangladesh 56
4.1.2 Patterns and Types of Floods 58
4.1.3 Some Statistics on Rural Bangladesh 61
4.2 Profile of Survey Areas 61
i4.3 Sampling Design: Quantitative and Qualitative Data Collection 63
4.4 Exploring Data and Checking Assumptions 66
4.4.1 Randomness of Sample 66
4.4.2 Normality Test 67
4.4.3 Detection of Outliers 68
4.5 Descriptive Analysis of Sample Households 70
4.5.1 Socioeconomic Profiles of Sample Households 70
4.5.2 Distribution of Households in Different Income Sources 73
4.5.3 Flood Severity and Transition of Poverty 75
4.6 Summary 77
5. Econometric Modeling of Poverty and Vulnerability 79
5.1 Determinants of Households’ Income: Multivariate Regression Analysis 79
5.2 Determinants of Poverty to Floods: Multinomial Logit Model Approach 88
5.3 Interpreting Vulnerability Estimates 92
5.3.1 Vulnerability to Poverty Line Estimates 93
5.3.2 Vulnerability to Expected Poverty Estimates 96
5.3.3 Vulnerability to Expected Utility Estimates 99
5.3.4 Vulnerability Estimates from Monte Carlo Bootstrap Approach 103
5.3.5 Comparing Vulnerability Estimates from Four Methodologies 106
5.4 Summary 108
6. Coping with Floods 110
6.1 Coping Strategies of Flooded Households 110
6.2 Diversification as Coping Strategy 117
6.2.1 Crop Diversification 118
6.2.2 Income Diversification 121
6.3 Migration as Coping Strategy 124
6.3.1 Synopsis of Migrants 124
6.3.2 Social Network and Migration 126
6.3.3 Vulnerability and Consequences of Migration 127
6.4 Summary 128
7. Summary and Conclusion 129
7.1 Policy Recommendation 137
7.2 Scope for Further Research 138
References 140
Appendices 152










iiList of Tables


Table 3.1: Sources of risks 28
Table 3.2: Strategies for flood risk management 30
Table 3.3: Indicators of vulnerability to floods 31
Table 3.4: Comparison of four methodologies to estimate vulnerability 53
Table 4.1: Main types of information obtained through the sample survey 66
Table 4.2: Socioeconomic profile of surveyed flooded and non-flooded households 72
Table 4.3: Cross tabulation of districts and households income sources by flood status 74
Table 4.4: Flood severity in four districts 75
Table 4.5: Income and poverty for flooded households 76
Table 4.6: Classification of transient and chronic poverty in flooded households 77
Table 5.1: Multivariate regression of log per capita income before flood 80
Table 5.2: Regression of log per capita income for flooded households 83
Table 5.3: Ree for non-flooded households 86
Table 5.4: Determinants of poverty to floods: multinomial logit model 91
Table 5.5: Estimates of vulnerability of flooded households by the VPL approach 94
Table 5.6: Estimates of poverty and vulnerability across groups by the VPL approach 95
Table 5.7: Vulnerability estimates by the VEP approach 97
Table 5.8: Major sources of income and vulnerability by the VEP approach 99
Table 5.9: Decomposition of vulnerability to poverty and risks by the VEU approach 101
Table 5.10: Correlations among the elements of vulnerability 102
Table 5.11: Changes in poverty gaps for flooded households 103
Table 5.12: Estimates of vulnerability by the Monte Carlo Bootstrap simulation 106
Table 5.13: Comparison of vulnerability estimates from the four methodologies 107
Table 6.1: Types of coping strategies and frequency of flooded households 111
Table 6.2: Utilization of loans and savings by flooded households 114
Table 6.3: Determinants of coping strategies: tobit model estimates 116
Table 6.4: Vulnerability differentials for different crop producers in Jamalpur 119
Table 6.5: Vulnerability differentials for different crop producers in Nilphamari 121
Table 6.6: Income correlation matrix by sources of income 123
iiiList of Figures


Figure 1.1: Frequency and area covered by floods in Bangladesh 3
Figure 2.1: Vulnerability and non-linear income poverty 11
Figure 3.1: Risk and utility curve 27
Figure 4.1: Map of Bangladesh, major rivers and survey areas in 2005 62
Figure 4.2: Normal Q-Q plot of per capita income 67
Figure 4.3: Normof log per capita income 68
Figure 4.4: Percentage distribution of households by different income sources 73
Figure 5.1: Predicted and actual per capita income after flood for flooded households 85
Figure 5.2: Estimated vulnerability by the VEP approach 98
Figure 6.1: Percentage distribution of households’ coping strategies among districts
and poverty levels 112
Figure 6.2: Types of migration for flooded households 124
























ivList of Boxes


Box 3.1: Working concept of household vulnerability 19
Box 3.2: Framework of this study: vulnerability to floods 22
Box: 4.1: Some definitions used in survey of this study 65





































vList of Appendices


Appendix 4.1: Frequency distribution of flooded and non-flooded households among
four districts 152
Appendix 4.2: Cross tabulation of districts and income sources 152
Appendix 4.3: Cross tabulation of district level households’ poverty and income
sources 153
Appendix 4.4: Cross tabulation of district level poverty and income sources for
flooded households 153
Appendix 4.5: Cross tabulation of district level poverty and income sources for
non-flooded households 154
Appendix 4.6: Cross tabulation of income sources of households and before
flood quartiles 154
Appendix 4.7: Poverty status before flood by districts 155
Appendix 4.8: Transition of poverty status of flooded households 156
Appendix 5.1: List of variables according to household’s characteristics 157
Appendix 5.2: Graphical presentation of heteroscedastic pattern of sample data 158
Appendix 5.3: Description of flood shock variables 159
Appendix 5.4: Estimation of measurement error using estimates of the non-food share159
Appendix 5.5: Summary of variables for flooded households 160
Appendix 5.6: Correlates of vulnerability in income 160
Appendix 5.7: Correlates of vulnerability in income with bootstrap standard errors
and robust estimates 160
Appendix 5.8: Changes in income (per capita) in Taka: Means and Standard
Deviations 161
Appendix 5.9: Changes in income (per adult equivalent) in Taka: Means and
Standard Deviations 162
Appendix 5.10: Proportional changes in income by per capita and adult
equivalence scale: Means and Standard Deviations 163
Appendix 5.11: Proportional change in per capita income among districts 164
Appendix 5.12: Observed changes in measured poverty in per capita income 165
viAppendix 6.1: Monthly interest rates among borrowing categories 166
Appendix 6.2: Classification of borrowing by districts and poverty status 166
Appendix 6.3: Classification of borrowing by districts and income quartiles 167
Appendix 6.4: Income sources, amount of borrowing and households’ frequency 167
Appendix 6.5: Determinants of borrowing as a coping strategy: tobit model
estimate 168
Appendix 6.6: Determinants of savings as a coping strategy: tobit model estimate 169
Appendix 6.7: Determinants of selling assets as a coping strategy: tobit model
estimate 170
Appendix 6.8: Crops in Bangladesh and cultivation periods 171
Appendix 6.9: Coefficient of variation in quartiles for each district (per capita) 171
Appendix 6.10: Coefficient of variation in quartile for each district (per adult
equivalence scale) 172
Appendix 6.11: Sources of income and vulnerability 172
Appendix 6.12: Impacts of migration 173
Appendix A: Flooded and non-flooded survey areas in four districts 174
Appendix B: Questionnaire of field survey for this study 175





















viiAcronyms


ADB = Asian Development Bank
BBS = Bangladesh Bureau of Statistics
BLUE = Best Linear Unbiased Estimates
BRE = Brahmaputra River Embankment
CE = Certainty Equivalence
CRRA = Constant Relative Risk Aversion
FAP = Flood Action Plan
FEI = Food Energy Intake
FGD = Focus Group Discussion
FGLS = Feasible Generalized Least Square
GIS = Geographical Information System
GLM = Generalized Linear Model
GLS = Generalized Least Square
GNP = Gross National Product
IFRC = International Federation of Red Cross and Red Crescent Societies
ILO = International Labor Office
IV = Instrumental Variable
NGO = Non Governmental Organization
OLS = Ordinary Least Square
PL = Poverty Line
PMS = Poverty Monitoring Survey
PR = Permanent Component
Q-Q plot = Quantile-Quantile plot
RESET = Regression Equation Specification Error Test
TOL = Tolerance Limit
TR = Transitory Component
VEP = Vulnerability to Expected Poverty
VER = Vulnerability Exposure to Risk
VEU = Vulnerability to Expected Utility
VIF = Variance Inflating Factor
VPL = Vulnerability to Poverty Line









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