Empirical Analysis of The Determinants of Rural Poverty in Sindh Province of Pakistan Ph.D THESIS BY Lawal Mohammad Anka Enrolment No.10395-C (2006) The thesis is submitted to University of Sindh for fulfillment of the requirement of the award of the degree of Doctor of Philosophy( PhD) In Development Studies Sindh Development Studies Centre University of Sindh Jamshoro Sindh Pakistan 2009
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Empirical Analysis of The Determinants of Rural Poverty in Sindh Province of Pakistan
Ph.D THESIS
BY
Lawal Mohammad Anka Enrolment No.10395-C (2006)
The thesis is submitted to University of Sindh for fulfillment of
the requirement of the award of the degree of Doctor of Philosophy( PhD)
In Development Studies
Sindh Development Studies Centre University of Sindh Jamshoro Sindh Pakistan
2009
ii
Empirical Analysis of The Determinants of Rural Poverty in Sindh Province Of Pakistan
BY
Lawal Mohammad Anka Enrolment No.10395-C (2006)
GUIDE
Prof. Dr. Abida Taherani Director SDSC University of Sindh
Jamshoro
CO-GUIDE
Prof. Dr. Rajab Ali Memon HEC Distinguished Professor (Rtd) and
Consultant Research and Training CRDC University of Sindh Jamshoro
The thesis is submitted to University of Sindh for fulfillment of the requirement of the award of the degree of
Doctor of Philosophy In Development Studies
Sindh Development Studies Centre University of Sindh Jamshoro Sindh Pakistan
2009
iii
DEDICATION
This Humble Effort Is Dedicated To
My Late Father
ALHAJI MUHAMMADU ANKA
My Late Uncle
ALHAJI BUHARI ANKA
My Late Brother’s
BELLO MOHAMMAD ANKA
SALIHU MOHAMMAD ANKA
My Late Cousin
SANI MOHAMMAD ANKA (JARIRI)
May Allah Bless Them Janna Firdosi
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Contents
Dedication……………………………………………………………………………. Certificate ………………………………………….………………………………… i Declaration…………………………………………………………………………… ii Acknowledgements…………………………………………………………………... iii List of Tables………………………………………………………………………… v List of Figures………………………………………………………………………… viii List of Appendices…………………………………………………………………… ix List of Acronym and Abbreviations…………………………………………………. x Glossary of Local Terms…………………………………………………………….. xi Abstract………………………………………………………………………………. xiii Layout of Thesis……………………………………………………………………… xv
Chapter I Introduction…………………………………………… 1 1.1 Historical Perspective on Rural Poverty in Pakistan………………………… 4 1.2 Trends in Incidence of Poverty in Pakistan………………………………….. 5 1.3 Rural Poverty in Sindh……………………………………………………….. 7 1.4 Trends in Incidence of Poverty in Districts of Sindh………………………… 8 1.5 Poverty in Badin District…………………………………………………….. 9 1.6 Poverty in Sanghar District………………………………………………….. 9 2.1 Justification for conducting the research…………………………………….. 12 2.2 Objectives……………………………………………………………………. 13 2.2.1 Overall Objectives…………………………………………………………… 13 2.2.2 Specific Objectives of the Study…………………………………………….. 13 2.3 Hypothesis…………………………………………………………………… 13 2.4 Significance of the study……………………………………………………. 14 2.5 Purpose of the study…………………………………………………………. 14 2.6 Limitation of the study………………………………………………………. 15 2.7 Conclusions………………………………………………………………….. 15
Chapter II Review of Literature…..………………………………… 17 2.1 International Perspective on Poverty and Inequality Issues………………….. 17 2.2 Critique……………………………………………………………………….. 21 2.3 Pakistan Perspective on Poverty and Inequality Issues………………………. 24 2.3.1 A Review of Past Economic Policies (1958-1989)………………………….... 24 2.3.2 The Deepening Economic Crises (1989-1999)……………………………….. 25 2.3.3 Medium Term Poverty Reduction Strategy Paper (MTDF) (2006-2009)……. 26
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2.3.4 Pakistan Poverty Reductions Strategy Paper-II (2006-2011)…………………. 26 2.3.5 The Four Pillars of Sustainable Poverty Reduction…………………………… 27 2.3.6 Pakistan Participatory Poverty Assessment (PPPA) National Report………… 28 2.3.7 Key Conclusions and Policy Issues…………………………………………… 29 2.3.8 Retrospective View in Chronological Order………………………………….. 30 2.4 Critique………………………………………………………………………... 41 2.5 Sindh Perspective on Poverty and Inequality Issues………………………….. 42 2.5.1 Sindh Poverty Reduction Strategy Paper……………………………………… 42 2.5.2 Addressing the problems of Karachi………………………………………….. 42 2.5.3 Addressing the Problems of Non-Karachi Urban Sindh……………………… 43 2.5.4 Accelerating Shared Growth in Rural Sindh………………………………….. 43 2.5.5 Improving Service Delivery…………………………………………………... 43 2.5.6 World Bank Report on Securing Sindh’s Future January 2006…………….... 44 2.5.7 Factors Responsible for Poverty in Sindh……………………………………. 45 2.5.8 Restrospective View in Chronological Order………………………………… 45 2.6 Critique……………………………………………………………………….. 51 2.7 Conclusions………………………………………………………………….... 53
Chapter III Methodology……….…..………………………………. 54 3.1 Sanghar District Profile………………………………………………………. 54 3.1.1 History……………………………………………………………………….. 54 3.1.2 Population, Size, Growth and Distribution…………………………………... 55 3.2 Badin District Profile………………………………………………………… 56 3.2.1 Population Size, Growth and Distribution…………………………………… 56 3.2.2 Area and Household Size…………………………………………………….. 57 3.3 Socio-economic Conditions in District Sanghar……………………………... 57 3.3.1 Water Availability in Sindh………………………………………………….. 58 3.3.2 Current Water Shortage………………………………………………………. 59 3.3.3 Development Potential for Irrigated Agriculture in Arid Desert Areas………. 59 3.3.3.1 Long Term Strategy…………………………………………………………… 59 3.4 Socio-economic Conditions in Badin District………………………………… 60 3.4.1 Overview of the Farming Sector……………………………………………… 61 3.4.2 Overview of the Fishing Sector………………………………………………. 61 3.4.3 Vulnerability of Livelihoods…………………………………………………. 62 3.4.4 On Going Development Initiatives…………………………………………… 63 3.4.5 Study Areas…………………………………………………………………… 63 3.4.6 Map of Sindh………………………………………………………………….. 63 3.5 Data Collection Method………………………………………………………. 64 3.6 Multistage Sampling for Selection of Household…………………………….. 66 3.7 General Measures of Poverty…………………………………………………. 67 3.7.1 Head Count Index…………………………………………………………….. 67 3.7.2 The Poverty Gap…………………………………………………………….... 68 3.7.3 The Sen Index……………………………………………………………….… 68
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3.7.4 Inequality Indices…………………………………………………………….… 68 3.8 Determinants of Poverty……………………………………………………….. 69 3.9 Testing Hypothesis about Coefficients………………………………………… 70 3.10 Partial Correlation……………………………………………………………… 71 3.11 Interpretation of Coefficients Using Odds…………………………………….. 72 3.12 Assessing the Goodness of Fit of the Model………………………………….. 75 3.13 Methodology for Data Collection and Analysis for…………………………… 76 Village Development Organization’s 3.13.1 Population……………………………………………………………………… 76 3.13.2 Sample Selection………………………………………………………………. 76 3.13.3 Analysis of Data……………………………………………………………….. 76 3.14 Conclusions…………………………………………………………………….. 77
Chapter IV Status and Trend Analysis of Rural Poverty in Sindh and Pakistan ……….…..……………………………………. 78 4.1 The Status and Pattern of Rural Poverty………………………………………. 78 4.2 Community and Poverty Issues……………………………………………….. 81 4.3 Structural and Non Structural Vulnerabilities………………………………… 82 4.4 The Need to Improve the Well Being of the Poor…………………………….. 83 4.5 Trend Analysis of Poverty in Sindh Province…….…………………………... 85 4.6 Poverty Ranking of Coastal Districts…………………………………………. 86 4.7 Distribution of Poverty by Assets……………………………………………... 88 4.8 Distribution by Sector and Occupation………………………………………... 89 4.9 The Poverty Profile in Pakistan……………………………………………….. 89 4.10 Trends of Poverty Estimates in Pakistan 1998-99, 2001-02 and 2004-05……. 91 4.11 Trends in the Gini Coefficient……………………...…………………………. 91 4.12 Trends in Agricultural GDP Growth in Pakistan 1999-2000 to 2005-06……... 92 4.13 Trends in Rural Poverty Across Household Groups in Pakistan 2004-05…..… 94 4.14 Conclusions……………………………………………………………………. 94
Chapter V Poverty Alleviation Initiatives ……….…..……………. 96 5.1 Contributions of Governmental Organizations Towards Poverty Alleviation in
Pakistan……………………………………………………………………….. 96 5.1.1 Zakat Programmes…………………………………………………………….. 97 5.1.2 Pakistan Baitul Maal (PBM) Scheme…………………………………………. 99 5.1.3 The Food Support Programme (FSP)…………………………………………. 99 5.1.4 Individual Financial Assistance (IFA)………………………………………… 100 5.1.5 The Khushhal Pakistan Programme (KPP)…………………………………… 100
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5.1.6 Pakistan Poverty Alleviation Fund (PPAF)…………………………………… 100 5.1.7 Khushhali Bank……………………………………………………………….. 101 5.1.8 Small and Medium Enterprises for Empowerment of the Poor in Sindh……... 102 5.1.9 Land Distribution to the Poor for Poverty Alleviation in Sindh…………….... 103 5.1.9.1 Priority Given to the Poorest of the Poor……………………………………... 104 5.1.9.2 Support Package………………………………………………………………. 104 5.1.10 Sindh Progress Towards Achieving Millennium Development Goals (MDG).. 105 5.1.11 Targeting the Poor in Sindh Using the Poverty Score Card…………………... 108 5.2 Contribution of NGO’S To Poverty Alleviation in Sindh…………………..… 109 5.2.1 Participatory Development Approach………………………………………… 109 5.2.2 Contributions………………………………………………………………….. 109 5.2.3 Strengths and Weaknesses of NGO’S………………………………………… 110 5.2.4 Sindh Agricultural and Forestry Workers Coordinating Organization……….. 111 SAFWCO 5.2.5 Sindh Rural Development Project (SRDP)………………………………….… 112 5.2.6 Aga Khan Rural Support Programme (AKRSP)…………………………….… 113 5.2.6.1 Strategy………………………………………………………………………… 114 5.2.6.2 Conditions for Replication…………………………………………………..… 115 5.2.7 National Rural Support Programme in Sindh (NRSP)………………………... 115 5.2.7.1 Establishment of NRSP………………………………………………………... 115 5.2.7.2 Experience in the Project Districts……………………………………………. 116 5.2.7.3 Social Mobilization and Small Scale Interventions…………………………… 116 5.2.7.4 Achievements Recorded………………………………………………………. 117 5.2.8 Badin Rural Development Society BRDS……………………………………. 117 5.2.8.1 Contribution of BRDS to Rural Development and Poverty Alleviation……… 118 5.2.9 Young Sheedi Welfare Organization YSWO Badin………………………….. 119 5.2.10 Sindh Microfinance Network SMN…………………………………………… 120 5.2.10.1 Looking Ahead…………………………………………………………….… 121 5.2.11 Micro Credit for Empowerment of the Poor in Sindh………………………… 124 5.2.11.1 The Micro Credit Programme in Sindh…………………………………….... 124 5.2.11.2 Loans for Low Cost Housing and Goat Rearing…………………………..… 125 5.2.11.3 Microcredit Disbusement In 2006………………………………………...…. 126 5.3 Contributions of Pakistan Poverty Alleviation Fund to Education and Health Care Delivery in Sindh…………………………………………… 126 5.3.1 Health Care Delivery……………………………………………………….… 128 5.4 Conclusions…………………………………………………………………… 129
Chapter VI Results and Discussion………………….…..………… 131 6.0 Household Survey Results………………………………………………….… 131 6.1 Household Related Information…………………………………………….… 131 6.1.1 Age of Household Head…………………………………………………….… 131 6.1.2 Qualification of Household Head…………………………………………….. 132 6.1.3 Skill of Household Head……………………………………………………… 134
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6.1.4 Household Size………………………………………………………………… 135 6.1.5 Household by Members……………………………………………………….. 137 6.1.6 Availability of Electricity……………………………………………………… 138 6.1.7 Availability of Gas…………………………………………………………..… 139 6.1.8 Type of House…………………………………………………………………. 141 6.1.9 Availability of Toilet………………………………………………………...… 142 6.2 Loan Related Information……………………………………………………… 143 6.2.1 Source of Loan…………………………………………………………………. 143 6.2.2 Institution of Loan……………………………………………………………… 144 6.2.3 Recovery of Loan/Payment of Installments……………………………………. 146 6.3 Human / Veterinary Centre Available…………………………………………. 147 6.3.1. Availability of Human dispensary……………………………………………... 147 6.3.2 Availability of Veterinary Centre……………………………………………… 148 6.4 Househould Income……………………………………………………………. 149 6.5 Household Income by Profession……………………………………………… 150 6.5.1 Household Income by Profession in district Sanghar………………………….. 150 6.5.2 Household Income by Profession of Badin……………………………………. 151 6.5.3 Household Expenditure on Different Items for Sanghar District……………… 152 6.5.4 Household Expenditure on Different Items for Badin District………………… 153 6.6 Poverty Measurement………………………………………………………….. 155 6.6.1 Head Count Ratio………………………………………………………………. 155 6.6.2 Headcount Index……………………………………………………………..… 155 6.6.3 Poverty Gap…………………………………………………………………..... 158 6.6.5 Sen Index………………………………………………………………………. 158 6.6.6 Poverty Gap and Sen Index……………………………………………………. 159 6.7 Inequality Measurement……………………………………………………….. 160 6.7.1 Lorenz Curve of Sanghar……………………………………………………..... 160 6.7.2 Lorenz Curve of Badin…………………………………………………………. 161 6.8 Logistic Regression Model Analysis…………………………………………... 163 6.8.1 Logistic Regression Model…………………………………………………….. 163 6.8.2 Poverty Status of Significant Predictors in Sanghar…………………………… 164 6.8.3 Poverty Predictors Using Logistic Regression Model for Sanghar district……. 165 6.8.4 Poverty Predictors Using Logistic Regression Model for Badin district……… 167 6.8.5 Poverty Status of Significant Predictors in Badin……………………………… 168 6.9 Multiple Linear Regression Model Analysis…………………………………... 171 6.9.1 Multiple Linear Regression Model……………………………………………. 171 6.9.2 Multiple Linear Regression Model Data for Badin……………………………. 171 6.9.3 Normal Probability Plot of Multiple Regression Model……………………… 173 6.9.4 Regression Residuals………………………………………………………….. 174 6.9.5 Multiple Linear Regression Model of Transformed Data for Badin………..… 176 6.9.6 Normal Probability Plot of Multiple Regression Model……………………… 177 Using Transformed Model 6.9.7 Regression Residual Plot Using Transformed Values………………………… 178 6.10 Results of Hypothesis Testing…………………………………………………. 180 6.11 Conclusions……………………………………………………………………. 180
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Chapter VII 7.0 Primary Data Analysis and Discussion…………. 181
of Village Development Organization 7.1 Introduction…………………………………………………………………… 181 7.2 Survey Results of VDOs in District Sanghar…………………………………. 183 7.2.1 Activities of VDOs to Alleviate Poverty……………………………………… 183 7.2.2 Empowerment and Participation in the Community………………………….. 185 7.2.3 Perception about Proper Utilization of Microcredit Loans…………………… 186 7.2.4 Status of Health and Nutrition………………………………………………… 187 7.2.5 Improvement of Living Standard after the Loan……………………………… 188 7.2.6 The Role of VDOs in Environmental Degradation……………………………. 189 7.2.7 The Role of VDOs in Establishing Income Generating Business…………...… 190 7.2.8 Recommendations of VDOs for Effective Poverty Alleviation Programmes…. 191 7.2.9 Rural Community Opinion on Government Poverty Alleviation Strategies…... 193 7.2.10 Services Provided by VDOs to Community to Alleviate Poverty……………... 194 7.2.11 Important Services Implemented by VDOs and Problems Encountered………. 195 7.2.12 Increases in Access of Good Quality Water…………………………………… 197 7.2.13 The Role of VDOs in Constructing a Building for the Community…………… 198 in District Sanghar 7.2.14 Leadership Style of VDOs in District Sanghar………………………………… 199 7.2.15 Perception About Total Credit Disbursed to the Community………………….. 200
in District Sanghar 7.2.16 Conditions for Successful Use of Microcredit in District Sanghar……………. 201 7.2.17 Goals Purpose and Aims of VDOs in District Sanghar………………………... 202 7.2.18 Specific Areas VDOs are Working to Alleviate Poverty in District Sanghar…. 204 7.3 Survey Results of VDOs in District Badin…………………………………….. 205 7.3.1 Activities of VDOs to Alleviate Poverty………………………………………. 205 7.3.2 Empowerment and Participation in Community………………………………. 206 7.3.3 Perception on Proper Utilization of Mciro credit Loans………………………. 207 7.3.4 Resources of Health and Nutrition…………………………………………….. 208 7.3.5 Improvement of Living Standard after the Loan………………………………. 209 7.3.6 The Role of VDOs in Saving Environment from Degradation………………… 211 7.3.7 The Role of VDOs/NGOs in Establishing Income Generating Jobs…………... 213 7.3.8 Recommendations of VDOs for Improving Poverty Alleviation Programmes... 214 7.3.9 Rural Community Opinion About Poverty Alleviation Strategies…………….. 215 7.3.10 Services VDOs Should Provide to Alleviate Poverty…………………………. 217 7.3.11 Important Services Implemented by NGOs/ VDOs…………………………… 219 and Problems Encountered 7.3.12 Increase in Access to Good Quality Water……………………………………. 221 7.3.13 The Role of NGOs / VDOs in Constructing a Building for the……………….. 222 Community in District Badin 7.3.14 Leadership Style of VDOs in District Badin………………………………….. 222
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7.3.15 Perception About Total Credit Disbursed to the Community………………… 223 in District Badin 7.3.16 Perception About Proper Utilization of Microcredit Loans…………………… 224 in District Badin 7.3.17 Purpose, Goals and Aims of VDOs in District Badin…………………………. 225 7.3.18 Specific Areas NGOs / VDOs are Working to Alleviate Poverty…………...… 226 in District Badin 7.4 Conclusions……………………………………………………………………. 227
Chapter VIII 8.0 Summary, Conclusions and Recommendations.. 229 8.1 Summary………………………………………………………………………. 229 8.2 Conclusions……………………………………………………………………. 230 8.3 Recommendations…………………………………………………………....... 237 8.4 Follow up studies………………………………………………………………. 245 References…………………………………………………………………………….. 246 Appendices……………………………………………………………………………. 260 Appendix-A Secondary Data………………………………………………………… 260 Appendix-B Selection of Villages, VDOs and Sample Respondents ……………….. 268 in District Sanghar Appendix-C Selection of Villages, VDOs and Sample Respondents ……………….. 276 in District Badin Appendix-D Household Survey Questionnaire…………………………………….... 285 Appendix-E Village Development Organizations Questionnaire…………………… 291
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CERTIFICATE
This is to certify that the research work embodied in this thesis entitled “Empirical
Analysis of the Determinants of Rural Poverty in Sindh Province of Pakistan”
carried out by Mr. Lawal Mohammad Anka under our guidance and supervision is
original, and be accepted as fulfilling the requirement of the degree of Doctor of
Philosophy (Ph.D) in Development Studies.
PROF. DR. ABIDA TAHERANI Guide Director SDSC University of Sindh Jamshoro
PROF. DR. RAJAB ALI MEMON Co-Guide Consultant Research and Training CRDC University of Sindh
Date of Thesis Defence ___________________________
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DECLARATION
I hereby declare that this thesis has been composed by myself and that all the work
carried out herein is also my own except where specially stated.
Lawal Mohammad Anka
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ACKNOWLEDGEMENTS
I wish to express my sincere gratitude and appreciation to my Supervisor Prof. Dr. Abida Taherani, Director SDSC University of Sindh Jamshoro for her excellent guidance, brilliant ideas, Scholarly advice, moral support and hospitality during the course of my study. Dr. Abida’s outstanding academic and research skills as well as dynamic leadership have been instrumental in promoting postgraduate programmes at SDSC. She is a remarkable individual and a role model.It has been a great pleasure to work with her. I am also highly thankful to my Co-Supervisor and Mentor Prof. Dr. Rajab A. Memon, Eminent Scholar and Consultant Research and Training CRDC University of Sindh for his moral support, encouragement, brilliant ideas, scholarly advice and excellent guidance which led to the completion of this study. In fact he made it possible for me to pursue this programme. I am sincerely greatful to Dr. Aijaz A Khooharo, Assistant Professor, Department of Statistics, S.A.U. Tandojam for his scholarly input, regular support and hospitality. His outstanding skills in data analysis were always detailed, incisive and reflective of his considerable knowledge of the subject. I appreciate the personal support and encouragement given to me by Dr. Heman Das Lohano, Associate Professor, IBA Karachi. Special thanks are due to Mr. Suleiman Abro, Chief Executive SAFWCO for providing logistics and transportation during my data collection in District Sanghar. I am also greatful to his staff Mr. Niaz H. Sial, Mr. Mumtaz Dhari and their team of social organizers for taking and bringing me back daily during data collection in Sanghar. I must accord special appreciation to Dr. Akash Ansari,Executive Director Badin Rural Development Society and all his field staff for supporting my research endeavours in a sincere and dedicated manner. I am thankful to Prof. Dr. Rafia A. Shaikh, Pro-Vice Chancellor and Prof. Dr. Iqbal A. Panhwar, Pro-Vice Chancellor Mirpurhas Campus University of Sindh for their moral support and encouragement. Sincere thanks are due to Prof. G.H. Khaskheli, Prof. Iqbal Qazi, Mr. M.A. Talpur, Mr. Z.K. Rind, Mr. G.A. Jariko, Mr. Ghani Soomro and Mr. Raheel Bughio, Senior Faculty Members at SDSC for their regular support and encouragement. Thanks are also due to Mr. Basharat Ali Librarian SDSC, University of Sindh Jamshoro, Mr. Zafar Javed Naqvi, Chief Librian PIDE, Islamabad, Mrs Mahjabeen, Reference Librarian PIDE, Mr. Suleiman Khalhoro and Mr. Rajab Channa, Assistant Librarians, S.A.U. Tandojam Mrs. Amatul Wadood, Librarian AERC University of Karachi, Librarians of World Bank and Asian Development Bank Islamabad for providing secondary literature and other relevant information for my research.
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I likewise owe many thanks to Prof. Dr. Lutfullah Mangi Ex Director Far East and South East Asia Area Study Centre and Dr. S. K. Jamali Assistant Professor Dept of Economics University of Sindh Jamshoro for providing me accommodation both in the campus and Hyderabad respectively.Prof. Dr. Pervez Pathan Professor SDSC and Prof. Shahab Mughal Assistant Professor SDSC extended full support and gave scholarly advice and brilliant ideas throughout the conduct of my research. I would like to thank them for their generosity. Many people outside the university supported my research endeavours. I would like to acknowledge with thanks the various suggestion given to me by Late Dr A R Kemal Ex Director PIDE, Islamabad Ms Rizwana Siddiqui PIDE Islamabad Dr Mohammad Aslam Khan National Planning Commission Islamabad, Dr Sajjad Akhtar CRIPRID Islamabad, Dr Suleman Shaikh Secretary Board of Trustees SZABIST Karachi and Mr Aktar A Hai Joint Director Aplied Economic Research Centre University of Karachi. I am highly thankful to Prof. Dr. A.Q. Mughal Vice Chancellor of Sindh Agriculture University Tandojam, Prof. Dr. Umar Mallah Director DASAR and Prof. Dr. K.B. Mirbahar Faculty of Animal Husbandry and Veterinary Sciences, Sindh Agriculture University Tandojam for their moral support and cooperation during the period of my research work. I also acknowledge the true friendship and best companionship of my friends Mr. Zamir Ujjan, Dr. Ibrahim Radman, Mr. Sohail Qureshi, Mr. Sachal Dino Sheedi, Mr. Ammar Naqvi, Mr. Naseer Ahmed Chishti, Mr. Kamran Channa and Mr. Arshad J. Minhas and his wife Mrs Nabila Arshad for the excellent hospitality they gave me during the period of my study. I must express my sincere gratitude to Alhaji Ahmad Sani, Ex-Governor Zamfara State of Nigeria for approving the Scholarship and Alhaji Musa Ibrahim Anka, Alhaji Halilu Anka, Alhaji Sani Salihu Anka and my brother Alhaji Sani Buhari for making sure that funds are released in good time for me to continue my studies. Behind the scene are Mr. Choudhary Asim Hamayun who entered the data from Badin in SPSS and, Mr. Muhammad Waseem and Muhammad Umar, computer experts I am thankful to them for computerizing the thesis with great patience. Finally I would like to express my feelings of admiration to my wife Maryam daughters Aisha, Asmau and Zainab, parents, brothers and sisters for their love affection whose prayers have always been a source of inspiration for me. They made a lot of sacrifices during my four years absence from home. LAWAL MOHAMMAD ANKA
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LIST OF TABLES 1. Trends in poverty incidence in Pakistan 2004-2005………………… 6 2 Trends of Poverty Incidence in Districts of Sindh (2004-05)……….. 8 3 Population and intercensal increase since 1951 in district Sanghar…. 55 4 Population and intercensal increase since 1951 in district Badin……. 57 5 Water apportionment under water accord……………………………. 58 6 Water shortage in Sindh……………………………………………… 59 7 Extent of damage caused by floods in 2003…………………………. 63 8 Multistage sampling for selection of households……………………. 65 9 Samples Selection from union councils……………………………… 67 10 Source of non-farm income % distribution of reporting households… 80 11 Farm and non-farm poverty by agro climatic zones 000 persons………….. 81 12 Deprivation Ranking of various Districts in Sindh Province………... 87 13 Distribution of Poverty by Asset Sindh……………………………… 88 14 Distribution of Poverty by Sector Occupation………………………. 89 15 Trends in incidence of poverty in Pakistan 1992-2005……………… 90 16 Trends in the Gini Coefficient……………………………………….. 92 17 Agricultural GDP Growth in Pakistan 2005-06……………………… 93 18 Trends in social sector and poverty related expenditure in Pakistan… 96 2001-2006 19 Disbursement and beneficiaries of zakat in Pakistan 2003-04……… 98 20 Percentage province-wise distribution of Pakistan Baitul Maal (PBM)… 99 beneficiary households in Pakistan 2003-04 21 NCHD Adult Literacy Centres and Learners…………………………… 106 22 Current NRSP areas in Thatta and Badin………………………………. 116 23 NRSP community physical infrastructure in Thatta and Badin as…….. 117 of 31 August 2006 24 NGOs Providing Credit to the Poor in Sindh…………………………… 123 25 Micro Credit Disbursed by Various NGOs in Sindh 2007……………… 124 26 SAFWCO Microcredit disbursement 2006-07………………………….. 126 27 Age of Household Head…………………………………………………. 132 28 Qualification of Household Head……………………………………….. 134 29 Skills of Household Head………………………………………………… 135 30 Household Size…………………………………………………………… 137 31 Household by Members………………………………………………….. 138 32 Availability of Electricity………………………………………………… 139 33 Availability of Gas……………………………………………………….. 140 34 Type of House……………………………………………………………. 142 35 Toilet……………………………………………………………………… 143 36a Source of Loan……………………………………………………………. 144 36b Institution of Loan………………………………………………………… 145 36c Whether Installments are Paid Regularly………………………………… 146 37 Human Dispensary Available……………………………………………. 147 38 Availability of Veterinary Centre………………………………………… 148 39 Household Income……………………………………………………….. 149
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40 Head Count Index………………………………………………………… 157 41 Poverty Gap and Sen Index………………………………………………. 159 42 Poverty Predictors Using Logistic Regression Model for Sanghar……… 167 43 Poverty Predictors Using Logistic Regression Model for Badin………… 168 44 Multiple Linear Regression Model Data for Badin……………………… 173 45 Multiple Linear Regression Model of Transformed Data for Badin……. 176 46 Activities of NGOs to Alleviate Poverty………………………………… 184 47 Empowerment and Participation in the Community…………………….. 186 48 Perceptions about Proper Utilization of Microcredit Loans…………….. 187 49 Status of Health and Nutrition……………………………………………. 188 50 Improvement of Living Standard after the Loan………………………… 189 51 The Role of VDOs in Environmental Degradation……………………… 190 52 The Role of VDOS in Establishing Income Generating Businesses……… 191 53 Recommendations of VDOs for Improving Poverty Alleviation………… 192 Programmes 54 Rural Community Opinion About Govt. Poverty Alleviation Strategies… 194 55 Services Provided by VDOs to Community to Alleviate Poverty………… 195 56 Important Services Implemented by VDOs and Problems Encountered….. 197 57 Increase in Access to Good Quality Water………………………………… 198 58 The Role of VDO’s in Constructing a Building for Community in District.. 199 Sanghar 59 Leadership Style of VDOs in District Sanghar…………………………… 200 60 Perception about Total Credit Disbursed to the Community…………….. 201 in District Sanghar 61 Conditions for Successful use of Microcredit in District Sanghar……….. 202 62 Goals, Purpose and Aims of VDOs in District Sanghar………………….. 203 63 Specific Areas VDOs are Working to Alleviate Poverty in……………… 205 District Sanghar 64 Activities of VDOs to Alleviate Poverty………………………………… 206 65 Empowerment and Participation in Community………………………… 207 66 Perception about Proper Utilization of Microcedit Loans………………. 208 67 Status of Health and Nutrition…………………………………………… 209 68 Improvement of Living Standard After the Loan……………………….. 211 69 The Role of VDO in Saving Environment from Degradation…………… 212 70 The Role of VDO/NGOS in Establishing Income Generating Jobs……… 213 71 Recommendations of VDOs for Improving Poverty Alleviation………… 215 Programmes 72 Rural Community Opinion About Govt Poverty Alleviation Strategies… 217 73 Services VDOs Should Prove to Community to Alleviate Poverty……… 219 74 Important Services Implemented by NGOs / VDOs and………………… 220 Problems Encountered 75 Increase in Access to Good Quality Water……………………………….. 221 76 The Role of NGOs / VDOs in Constructing a Building for Community in.. 222 District Badin 77 Leadership Style of VDOs in District Badin………………………………. 223
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78 Perception About Total Credit Disbursed to the Community in………… 224 District Badin 79 Perception About Proper Utilization of Microcedit Loans in District Badin. 225 80 Purpose, Goals and Aims of VDOs in District Badin…………………… 226 81 Specific Areas NGOs / VDOs are Working to Alleviate Poverty in……… 227 District Badin
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LIST OF FIGURES 1 Map of Sindh…………………………………………………………………. 64 2 Household Income by Profession of Sanghar………………………………… 150 3 Household Income by Profession of Badin…………………………………... 151 4 Household Expenditure on Different Items for Sanghar……………………... 153 5 Household Expenditure on Different Items for Badin……………………….. 154 6 Lorenz Curve of Sanghar…………………………………………………….. 161 7 Lorenz Curve of Badin……………………………………………………….. 163 8 Poverty Status of Significant Predictors in Sanghar…………………………. 165 9 Poverty Status of Significant Predictors in District Badin…………………… 170 10 Normal Probability Plot of Multiple Regression Model……………………... 174 11 Regression Residual Plot…………………………………………………….. 175 12 Normal Probability Plot of Multiple Regression Model Using……………… 177 Transformed Model 13 Regression Residual Plot Using Transformed Values……………………….. 178
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LIST OF APPENDICES A Secondary Data………………………………………………………… 260 B Selection of Villages, VDOS and Sample Respondents in…………….. 268 District Sanghar C Selection Of Villages, VDOS and Sample Respondents in……………. 276 District Badin D Household Survey Questionnaire………………………………………. 285 E Village Development Organizations Questionnaire……………………. 291
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ACRONYMS AND ABBREVIATIONS
ADB Asian Development Bank. DCO District Coordination Officer. EDO Executive District Officer. FAO Food and Agricultural Organization of United Nations. GDP Gross Domestic Product. GOP Government of Pakistan. GOS Government of Sindh. IUCN International Union for Conservation of Nature and Natural Resources. LBOD Left Bank Outfall Drain. NCHD National Commission for Human Development. NGO’s Non Governmental Organizations. NHDR National Human Development Report NRSP National Rural Support Programme. OFWM On Farm Water Management. PIDE Pakistan Institute of Development Economics PLSM Pakistan Living Standard Measurement RBOD Right Bank Outfall Drain. SRSP Sindh Rural Support Programme. TMA Tehsil Municipal Administration. VDO’s Village Development Organizations WAPDA Water and Power Development Authority. WWF World Wide Fund for Nature. PPAF Pakistan Poverty Alleviation Fund
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GLOSSARY OF LOCAL TERMS USED
Barani Rainfed normally with reference to agricultural land Deh A little bigger than a village. Equivalent to a mauza in Punjab. Several Goths constitute a deh Goth The smallest unit of settlement which can be equated with a hamlet or village Hari Tenant or peasant Kamdar The supervisor or manager for the large landlord who supervises the tenants and makes on the spot decision in the absence of landlord Katcha The area adjoining the river which used to bring the fertile silts and was highly prized for cultivation Kharif Summer cropping season Mohallah An area of land or cluster of houses inhabited by close relatives taken to mean neighbored in most other areas Naib nazim Deputy mayor convenor of local government council takes over from nazim when he or she is away Nazim Mayor elected head of local government Panchayat Tribal council decision making body most commonly operational in parts of Punjab Rabi Winter cropping season Seth Wealthy or influencial owner Taluka Administrative tier below the district Tehsil Administrative unit of local government between a district and union Wadera/wadero Tribal council decision making body most commonly operational in parts of Sindh Zamindar Landlord Union council Is the lower tier of administrative unit in Pakistan.
xii
Tapas Administrative unit developed by revenue department 3-5 dehs consistute a tapa. Dehs Administrative unit designed by revenue dept. Ghaznavids Royal family of gaznavids Dhands Lakes Sani guni Canal’s name Chew pan Is an ingredient made by local people. It has flavour it gives satisfaction after chewing. Beeri Local cigret made by local people Katchriabadis New developed colonies sorounded by cities specially poor and lower class dwell there. Katcheries Open discussions Pacca houses Cemented constructed houses Jhorpra houses Lowest quality houses Jhorpra Houses of straws, mud and wood Katcha houses Mud made houses
xiii
ABSTRACT Sanghar district has a population of 1.353 million according to 1998 census. Agriculture employees 70% of the rural people out of which 57% are self employed. Farming is mostly at subsistence level except for the bigger land holding. Large number of landless people work on these farms and are mostly paid in cash. Besides subsistence earning high dependency ratio is another reason of poverty. The major source of drinking water supply were hand pumps and pipe water in the district, only 17% of the rural population had access to separate latrines, while 16% have access to shared latrines. Badin district with a population of 1.2 million is one of the richest district in terms of natural resource base but it is the poorest in terms of human development. Extreme natural disasters had adversely affected the district over the last ten years. This has resulted in a general disruption of livelihoods, increased their vulnerability and in some cases led to out migration. Inequality in the distribution of water and lack of basic social services and infrastructure has further resulted in harsh living conditions and extreme poverty. This study was conducted to estimate poverty and inequality in the distribution of income, analyse the determinants and identify the correlates of poverty in Sindh. The study also evaluated various government, NGOs and private sector initiatives towards poverty alleviation. A total sample of 320 households was selected from two district. Multistage sampling was used to select households. The primary data collected from household survey was analysed. For measuring Poverty headcount Index,Poverty gap and Sen Index were used, while for measuring inequality Lorenz curve and gini coefficient were used. For analyzing the determinants and identifying the correlates logistic regression and multiple linear regression models were estimated. The major conclusion drawn from the study revealed that headcount ratio was 52% in Sanghar district, and in Badin it was 56%; while Sanghar district has a poverty gap of 373, and in Badin it is 356. On the same proportion the two districts have a sen index of 0.31 respectively. Logistic regression was applied to primary data. The results revealed that logistic regression satisfy the 85% while multiple linear regression accounted for 47% variation. Land ownership is significant because those who own land will be out of poverty. As the number of earners increases the proportion of household poverty decreases. All variables show significant values except household size which shows a positive sign. In the Lorenz curve and gini coefficient if the gap between the perfect distribution line and Lorenz curve is high it implies that there is inequality in the distribution of income. If Lorenz curve goes down this shows that most of the people in the study areas have low income. It was concluded that land, household size, number of earners and qualification of household head has a significant effect on poverty.
xiv
Based upon the research findings it is recommended that irrigation water may be provided in the study areas so that the poor could utilize their land for crop production. Delivery of essential services and basic necessities of life would reduce the burden of poverty in both Sanghar and Badin. There is a need for a very strong monitoring and evaluation of NGOs / VDOs so as to make sure that their services reach the poorest of the poor in the study areas. The monitoring and evaluation should be carried out by independent research institutions. Government should introduce new housing schemes so as to support those in ultra poverty. Local entrepreneurs and businessmen may launch a massive effort for job creation. Network of institutional credit may be widened to rural areas. One of the measures to alleviate extreme poverty in the study area would be to establish vocational skill training centre through public private partnership to train youth and women for self reliance. Rural leadership and community organizations developed programmes may be launched by major NGOs and public sector organizations. Poor communities may be encouraged to participate in planning and development. There is a need to encourage active participation of rural women in income generating jobs through a very strong social mobilization. These suggestions would facilitate and sustained reduction in poverty and ultimately play a positive role in achieving the United Nations Millennium Development Goals of fighting poverty and hunger by the year 2015.
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LAYOUT OF THESIS
In chapter one the introduction is divided into three parts. The first part discussed the international perspective to poverty, the second part describe poverty issues in Pakistan and the last part discussed the poverty situation in Sindh. The justification for conducting this research is that both Sanghar and Badin districts are ranked 10 and 14 among those districts lacking social amenities in Pakistan, failure to implement poverty reduction programmes properly and the issues of empirical analysis of the determinants of rural poverty has not been done properly. The objectives and hypothesis, significance, purpose and limitation of the study has been discussed. Chapter 2 Provides an in depth review of literature on poverty and inequality from international perspective, Pakistan perspective and Sindh perspective along with their critique. Chapter 3 Describes the research methodology that how the research is going to be carried out. It present an analytical framework that is used for data collection, data anlaysis and presentation. Chapter 4 Describes the status and trend analysis of rural poverty in Sindh and Pakistan. The chapter present various data that will help us understand the nature and dimension of poverty in Pakistan and Sindh respectively. Chapter 5 Describes the various initiatives taken by governmental organization and NGOs in poverty alleviation over the years these organizations have made effort to poverty alleviation in Sindh and Pakistan respectively yet poverty is still increasing. Chapter 6 present results and discussions on household survey. Chapter 7 present data analysis and discussion of village development organization in respect of various initiative taken by them to alleviate poverty in the study area. Chapter 8 present summary conclusions and recommendations aim at poverty reduction on sustainable basis in Sindh.
1
CHAPTER I
INTRODUCTION
Poverty is as an inability to afford the minimum standard of living.
According to the United Nations (UNDP 2006), a person living under one dollar per day
is considered to be living under the poverty line. Poverty is an issue that requires
extraordinary solution in poor communities, and it become a challenge to the people that
live with it. In view of its severity we should first, identify poverty and then evaluate it
and finally eliminate it (Aslam, 2004)
In economic terms a country, region or household are poor when the per
capita income of a country or the income of a household is very low. In political terms a
country a region or a group of people are poor which are dependent on more powerful
groups or individuals in order to express their own rights or choices.
In social terms the manifestation of poverty is revealed when a country,
region or household breeds all types of socially unacceptable behaviors like drug
addiction, crime, prostitution, violence in a family or in a community and terrorism, all of
which degrade human self respect, moral and social values of the society as a whole,
when more and more people in the community become intolerant of each other and are
rude towards each other in their day to day life (Aslam, 2004).
In its environmental terms poverty destroys the living environment not
only of those who live in poverty but of all other human and non human species that
depend on the same resources and ecosystem on which those living poverty depend and
survive upon. People living in poverty cannot change their behavior easily not only
because of lack of resources, but also because of lack of knowledge about their own
2
surroundings and survival techniques, lack of education and illiteracy. More importantly
if they do not change their already marginalized living behaviors they might die. Thus by
destroying their own living environment, the poor in reality are destroying their own
resources on which they survive in the long run (Amjad and Kemal 1997).
In its human dimension, poverty means being poor living in pathetic
conditions, in which people die of extreme hunger, malnutrition and starvation (Arif,
2006). Another human dimension to poverty is when the poor sells their siblings into
child labor, due to lack of money to take care of their young ones (Arif, 2006).
Furthermore, poverty has a human dimension when people have no concern towards their
communities. Lack of patriotism to help the poor, who actually need help due to abject
poverty and lack of opportunities for survival (Arif, 2006)
According to World Bank Report of (2001), vulnerability is lack of
protection to the poor, which may lead to other risks such as injury due to violence, from
undesirable elements. The concept of poverty as powerlessness underlines the importance
of economic vulnerability. The poor are separated from non poor, not only by their
current standard of living but also by their greater vulnerability to economic catastrophe.
A vulnerability that limits their choices and hence the freedom of the poor (World Bank,
2001)
Absolute poverty(1) can be eradicated, if there is higher economic growth,
which reduces distribution of income, economic growth is the key determinant of poverty
1. Absolute Poverty is defined as absence of enough food, water and shelter for survival
3
reduction, when the poor become productive then poverty reduction is possible.
Therefore, we should invest more on human resource development, and expand access to
employment and microcredit (Anwar, 2005). While, sound macroeconomic policies and
growth enhancing structural reforms favor the poor and poverty reduction feed back
positively into growth. Income distribution also matters, reducing inequality will increase
the number of who benefits the same rate of economic growth (Anwar, 2005).
The pace of poverty reduction and human development has been much
slower than the pace of economic growth in Pakistan. Despite impressive economic
growth, around one fourth of the population is living below the poverty line. There are
two major factors that restrict the poor in Pakistan to benefit from rising economic
growth. First, lack of human capital in terms of education, training and health. Second,
the poor are not provided with enough income earning opportunities in terms of jobs. The
government approach has been welfare oriented rather than empowerment of the poor.
No doubt, the long term solution to poverty in Pakistan lies only in accelerated human
development alongwith adequate employment opportunities. Realizing the significance of
poverty alleviation as not an end in itself but also as a critical factor for sustaining future
economic growth, the government of Pakistan has been showing an increasing
commitment to reduce poverty. Over the past five years (2001-2006) alone, the social
sector and poverty related expenditure has been doubled. A number of poverty alleviation
programmes are being implemented to ameliorate the sufferings of the poor and to
improve living conditions in general (Kemal, 1998).
It is important to build assets for sustainable livelihood, natural capital,
social capital, physical capital, human capital and financial capital through social
4
mobilization to harness peoples potential to help themselves. The people and
communities at the grassroot level are more effective in reducing poverty and achieving
well being by mobilizing the underutilized creativity of the poor, local resources and
local knowledge. The experience across countries including Pakistan, indicates that in the
absence of a participatory process, most interventions designed for helping the poor have
not always been successful in reaching the poor and the conventional macro development
interventions are inadequate for poverty reduction and human development (Mahbubul
Haq, 2005).
The success of poverty reduction efforts is therefore contingent upon the
integration of the poor and communities through participatory institutions alongwith a
carefully crafted system for provision of requisite financial resources to the communities.
1.1 Historical Perspective on Rural Poverty in Pakistan
Estimates that were based on basic need of the poor indicates that there
was high rate of economic growth in the 1960s (Kemal, 2003). The country achieved 6.8
percent growth due to sound macroeconomic policies, and bumper harvesting agricultural
sector. This plays a positive role towards growth, of the private sector. As a result of this
success foreign investment increases in the first quarter of 1960s (Kemal, 2003). In the
mid 1960s the country achieved green revolution. This initiative accelerated agricultural
growth through the use of agricultural technology which resulted in wheat self
sufficiency (Kemal, 2003). The major reason why poverty increases in the 1960s was due
to low level of employment opportunities which affected, the livelihood of the poor in
particular (Gazdar, 2007).
5
Pakistan returned to parliamentary system of government from 1970-1977.
The new administration converted the industries from private to government ownership.
Some of these industries were directly under government directives. The economy
declined by 4.8 percent per year. Similarly private investment also went down, in all
important sectors. This period witnessed a skyrocketing inflation, with increase in
petroleum prices. Many people migrated to different countries in search of a better
livelihood (Kemal, 2003).
The military took over from civilian administration from 1977 to 1988.
The economy improved significantly. GDP went upto 6.7 percent as a result of sound
economic programmes. Industries were transferred from national to private ownership,
free from government control. The government implemented Islamic economic policies,
transforming the society in line with Islamic injunctions. A large inflow of cash from
overseas Pakistanis increased, during this period. The poor also benefited from economic
growth (ADB, 2003). In 1992/93 the government started implementing world bank
assisted social action initiative. The aim of this programme was to, give access to the
poor communities in basic health facilities and education, particularly to female and
young girls in rural areas (Zaidi, 2005).
1.2 Trends in Incidence of Poverty in Pakistan
The trends in poverty incidences (table 1) estimated 2 percent rise in
annual growth during 1987-88 and 2004-05 on average. Table 1 indicates a higher
increase in urban poverty during this period. A comparison with 2001-02 and 2004-05
shows that the decline in urban poverty is less than the rural poverty. Rural poverty in
6
this period has reduced by 4 percent, while the reduction is about 2 percent in the case of
urban poverty incidence.
Table-1 Trends in poverty incidence in Pakistan 2004-2005. 1987-88 1996-97 1998-99 2001-02 2004-05
Pakistan 23 28 30 33 30 Urban 19 25 25 30 28 Rural 26 30 32 35 31
Source: Haroon Jamal 2007 income poverty at district level an application of small area estimation technique research report no.70 page 8 SPDC June 2007.
As a result of economic decline poverty increases in the 1960s (Anwar and
Qureshi, 2003). Similarly poverty increases as a result of withdrawal of incentives,
provided by the government. The economy suffered due to low level of investment and
unemployment (Anwar and Qureshi 2003).
The status of poverty from 2001-2005 indicates that the estimated inflation
poverty line is Rs.878.64. Head count ratio declined, from 36.46 percent in 2001 to 23.9
percent in 2004-05. Similarly, poverty has gone down from 39.26 percent to 28.10
percent in rural areas and in the urban areas it has gone down from 22.69 percent to 14.9
percent (Pakistan Economic Survey, 2005-06). In other words, rural poverty has declined
by 11.16 percentage points and urban poverty has decreased by 7.79 percentage points
(Pakistan Economic Survey 2005-06). The other two indicators, poverty gap and severity
of poverty are aggregate measures of spread of the poor below the poverty line i.e. they
aggregate the distance (proximity or remoteness) of all poor individuals from the poverty
line. In line with the improvement in head count, both the poverty gap(2) and severity of
poverty(3) has also reduced substantially in the country. These figures
2. Poverty Gap is the amount of income required to raise everyone who is below the poverty line upto that line. 3. Severity of Poverty : when a person is so poor that he is affected by diseases, malnutrition etc. Severity of poverty affects
life expectancy.
7
coincides with the economic status of 2000-01. The country witness economic growth
and increase in GDP. The government social action programme, is an effort to poverty
alleviation on a sustainable basis (Rizwana and Kemal 2006).
Many research scholars in Pakistan used various methods, applying
various models and other statistical tools so as to come up with positive results. Despite
all efforts and commitments, poverty still remain, high in both rural and urban areas of
the country. To address the root cause of poverty on a sound footing (Jamal, 2003).
Provision of job opportunities to the less privilege near to their homes is very important.
The aim is to discourage migration, of the people to cities and making sure that credit is
delivered, to the poor for self reliant activities (Qureshi and Arif, 1999).
1.3 Rural Poverty in Sindh
Sindh province is endowed with many resources. It is a rich province in
terms of natural resources, situated between European countries and for east. Sindh has
the potential to become a leading economically viable province of Pakistan with about 40
percent industrial output (World Bank, 2006). Sindh has the highest per capita income,
amounting to 55 percent when Pakistan was created in 1947. During the year 2004-05 its
contribution to the country’s GDP decline, in all important sectors of the economy. In
2003-04 about 610,000 citizens of Sindh are unemployed; it is also possible that a total of
500,000 people will remain unemployed, in the coming decade. If the economy fail to
grow at 7-8 percent yearly then, the rate of unemployment will increase upto 1.6 million
by 2013-14 (World Bank Report, 2006). The overall poverty level in Sindh province is
52.2% (Aftab, 2009).
8
Villages in Sindh generally stand out of the proportions of female workers
reporting occupations other than household work. Most women reporting these activities
belong to the Hindu Bheel and Kohli groups. Apart from field work, sewing and
embroidery are the predominant non-farm activities for females. Muslim women are
usually kept in the house undertaking household tasks. Women are more likely to be
illiterate and large family means that women are often pregnant or have given birth. Child
mortality is high leading to additional stress, finding basic necessities for the family,
especially water is a time consuming onerous task (Sindh Poverty Reduction Strategy
Paper 2003).
Presently natural resources of Sindh are under extreme stress.
Environmental degradation due to their over use is rapidly depleting them. In addition
waterlogging, salinity and pollution of water bodies due to absence of the treatment of
effluents and faulty development projects such as the LBOD and RBOD are depriving
people of their means of livelihood. All these constraints make the addressing of
environmental issues difficult and degradation continues to pauperize people. The more
they are impoverished the more the environment comes under stress. Poverty is a part of
this vicious circle and of the accompanying social and political problems which are not
being addressed (Sindh Coastal Dev Project Report 2005).
Poverty has become a major issue in Sindh where 50 percent of the
population lives below the poverty line and suffers from low calorie intake, low per
capita income, unemployment, inadequate access to education, sanitation, health facilities
and unhygienic environment. The present situation in Sindh can be looked at in context
9
of the various issues and measures that have been taken by the government and other
organizations such as the NGOs. (Securing Sindh Future, World Bank Report 2006).
Income is one of the basic indicators of social well being. Sindh had the
highest per capita income from 1975-1995 and income in this period had a faster rate of
growth than in any other province. The gap between per capita income in Sindh and
Punjab in 1975 was Rs.1,250 per annum. By 1995 this gap had increased to Rs.2,800 per
year. The gross regional product (GRP) per capita 1995 at 1980-81 prices was the highest
in Sindh at Rs.5,325 per annum.(Sindh Poverty Reduction Strategy Paper, 2003)
Despite the above figures, more than 11 million men and women in Sindh
are unemployed and around 15 million live below the poverty line. According to the
Pakistan Poverty Reduction Strategy Paper (PPRSP), population below the income
poverty line of one US Dollars per day is 31 percent, which implies that every third
household in Pakistan lacks sufficient income to afford the daily intake of 2,350 calories
per person. The ratio of economically active population to the total population termed as
crude activity or participation rate, is around 22.75 percent in Sindh, but the 1998 census
states a participation rate of 32.73 percent (age 10 and above) in either case it is very low
and indicates a high incidence of poverty (Sindh Poverty Strategy Paper 2003). Since all
sober assessments of Pakistan’s economic and poverty trends suggest that not only has
poverty returned but it is likely to be a permanent phenomenon. The issues of Empirical
Analysis of the determinants of rural poverty in Sindh have not been addressed properly
by scholars this gave the rationale for conducting the present study.
10
1.4 Trends in Incidence of Poverty in Districts of Sindh
Table-2 present trends in incidence of rural poverty in Sindh. The table
shows that Shikarpur ranked 1 with 57.79% urban and 40.28% rural. Thatta ranked 2
with 50.93% urban and 45.73% rural, Larkana ranked 3 with 53.84% urban and 40.87%
rural, Badin ranked 6 with 40.93% urban and 32.42% rural is relatively fair in these
estimates. Similarly Sanghar ranked 14 with 39.66% urban and 20.63% rural is better up
in all the listed districts below. Overall Shikarpur has the highest incidence of poverty
while Sanghar has the lowest incidence of poverty on the basis of these estimates
(Haroon Jamal, 2007).
Table-2 Trends of Poverty Incidence in Districts of Sindh (2004-05).
Districts Ranking(4)
1 highest 16 lowest
Region Overall Urban areas Rural areas
Badin 6 34.83% 40.93% 32.42% Sanghar 14 24.67% 39.66% 20.63% Larkana 3 43.33% 53.84% 40.87%
Shikarpar 1 51.03% 57.79% 40.28% Thatta 2 46.87% 50.93% 45.73%
Source: Haroon Jamal 2007 updating poverty and inequality estimates (2005) SPDC Research Report no.69,
Rural Sindh is one of the poorest areas in the country. The districts Thatta
and Badin were the poorest, according to a nation wide village survey conducted in 2005.
The incidence of rural poverty is high, where about 40 percent of rural people live below
the poverty line. In Thatta and Badin, the figure is considerably as high as high as 70
percent (Sindh Coastal Development Project, 2005 Report).
4. Ranking is defined as the relationship between two items this means the first can be ranked higher than the second one or
each can be ranked equal or the second can be ranked higher than the first.
11
1.5 Poverty in Sanghar District
In Sanghar district, three groups (the Kohli, Punjabi and Bheel) stood out
as having very high poverty ratio(5). The Kohli of Sanghar were infact the poorest single
group in cross village poverty ranking. The Punjabi 1 were landless tenants, migrants
from southern Punjab. The other relatively poor groups included Baluch 5 and to some
extent the Baluch 2. The Baluch 1 and Sammat 1 were less likely to be poor as were the
two Mir Kinship groups. The Khaskhelis too were among the less poor. The poverty
rankings of groups in Sanghar showed that the Hindus and scheduled castes were among
the poorest. The relatively good position of the Mirs was in line with their historically
privilege status, but historically oppressed Khaskhelis appeared to be doing almost as
well as the Mirs (Gazdar, 2007).
1.6 Poverty in Badin District
In general there are variables that can be considered to determine poverty
or sense of well being in Badin. These include food consumption, ownership of livestock,
ownership of durable items and housing condition.
The major problem in the area is the absence of capital or surplus earnings
within the communities; this means that they are excluded from various development
opportunities such as the microfinance scheme. The Badin coastal area needs some form
of protection from periodic cyclones and massive floods or storm surges. Other priorities
are sweet water, health support, small link roads, basic sanitation, support for crops and
livestock and education; because its current benefits in their current environment are
difficult to comprehend (Sindh Participatory Poverty Assessment Report 2003).
5. Poverty ratio is defined as the percentages of poverty level and its also relationship between two amongs.
12
1.7 Justification for conducting the research
Sanghar and Badin Districts are one of the poorest districts in Sindh
province and according to the ranking of those districts lacking social amenities in
Pakistan the incidence of rural poverty is very high. Seventy percent of the people live
below the poverty line. Apart from humanitarian considerations, the high incidence of
poverty becomes a crucial social factor for the governance of civil society.
According to studies conducted by Sindh Coastal Development Authority
in 2005, the important factor in predicting poverty is the proximity and availability of
water. There is no sanitation facilities, 90 percent of residents live in clay wall or plastic
sheet roots structures. The average literacy rate is around 20 percent of the total
population. Poor facilities about roads, power, health and education add up to lack of
access to a range of essential services needed to conduct life beyond survival. The
situation requires emergency rather than development, what is being seen in the area is
the collapse of communities, a situation that requires mitigation before any serious
development strategy can be implemented. The fundamental cause of ill health is lack of
clean drinking water, and the consequence is that people suffer a range of chronic water
borne diseases including hepatitis A,B,C, high blood pressure, kidney failure and joint
disability. Therefore, a huge gap still exists in living standard, education, health and
social amenities in the area. The failure to adequately implement poverty reduction
programmes designed by the government bilateral, multilateral agencies and private
sector initiatives can be seen as the precursor to most of the present causes of poverty in
both rural and urban areas of Pakistan. In view of the above scenario, following are the
justification for conducting the present research.
13
1. Some research scholars have conducted research on poverty in Sindh province but
based on secondary data and they did not use any technique to analyse the data.
2. Similarly, a research was conducted (2005) in Tharparkar area on poverty and
only regression model was used but no other techniques were used, which is being
used in this study to analyse the data.
3. A number of economists had conducted research on poverty in Sindh province but
using a small sample covering a Taluka or Tehsil. But in my own case I am using
a bigger sample of 320 covering 2 districts of Sindh, Sanghar and Badin.
1.8 Purpose of the study
The purpose of doctoral research was to assess the level of poverty in
Sanghar and Badin districts of Pakistan. The assessment provides an overview of poverty
situation in the study areas as well as analysis of its causes and measures to alleviate it.
In the initial poverty evaluation assessment those who are likely to
become poor, are not taken into consideration (GOP PRSP, 2005). Household members
that are clustered near the poverty line, are likely to become extremely poor. The poor in
Sindh have no right to express their opinion, no access to decision making and political
offices as compared to the rich (GOP PRSP, 2005). Poverty evaluations conducted by
various scholars revealed that, without sound economic growth poverty alleviation is not
possible the two are inter linked (Arif and Iqbal 2008). On the otherhand the household
heads working on daily wage in crop sector, engineering, commerce and transport have
the highest level of poverty (Aslam, 2004). Similarly, also in rural areas, the incidence of
poverty is high among share croppers.
14
2.0 Objectives
2.1 Overall Objectives The overall objective of the study is to assess the level of poverty and to
explore associated factors in Badin and Sanghar districts of Sindh province of Pakistan.
2.2 Specific Objectives of the Study
1. To document the status of poverty and undertake trend analysis of poverty
situation in Sindh.
2. To measure the extent of poverty and income inequality in selected districts of
Sindh.
3. To analyze the determinants and identify correlates of poverty in Sindh.
4. To evaluate various government, NGO, and private sector initiatives towards
poverty alleviation.
5. To develop recommendations for public and private sectors regarding poverty
reduction programmes in rural Sindh.
2.3 Hypothesis
The following null hypotheses are proposed to be tested:
1. Rural poverty does not depend upon respondent characteristics such as
educational status, gender, age, and tenancy and marital status.
2. Rural poverty does not depend upon agro-economic indicators: cropping pattern,
low productivity, high input prices and low output prices.
3. Rural poverty does not depend upon household characteristics such as size,
household quality, dependency ratio, and household assets.
2.4 Significance of the study
The study examined the trend analysis of poverty situation in Sindh, by
knowing the extent of poverty and inequality, and identifying the correlates and other
socioeconomic characteristics among the people in the study area. The study also
15
evaluated the activities of NGO’s working on poverty alleviation, achievements and short
comings of these NGOs in the delivery of micro credit, which has been an important
ingredient of poverty alleviation programmes. Over the years, Pakistan’s progress
towards achieving millennium development goals, in respect of poverty alleviation
among the rural population has been slow. This study examined those constraints,
responsible for slow delivery of poverty alleviation programmes in Sindh.
2.5 Limitation of the study
The study was limited to two districts of Sindh i.e. Sanghar (Cotton /
wheat / Fodder Zone) and Badin (Sugarcane, Rice, Vegetables, Oilseeds Zone). Data was
collected from contact and non contact farmers in the villages both of Sanghar and Badin
Districts. A sample size of 320 was used for data collection. Due to limited time and
financial constraints, one year data were gathered from representative sample of the
target groups.
2.6 Conclusions
This chapter is divided into five parts. The first part discussed poverty at
international level and concludes that the success of poverty efforts is therefore, based on
the integration of the poor through participatory institutions. The second part gave an
overview of poverty in Pakistan and concludes that for addressing the root cause of
poverty on a sound footing. There is a need to create more job opportunities, to the less
privilege near their homes (Jafri, 1997). The third part looks at unemployment in Sindh is
likely to increase, if the economy fail to grow between 7-8 per annum (World Bank
16
Report, 2006). The fourth part discusses the prevailing scenario of poverty in Sanghar
and concludes that the deprivation ranking 1 = least deprived to 16 most deprived gives
Sanghar a ranking of 12 for employment 8 for education 10 for housing quality. Similarly
Badin is ranked 10 for employment 6 for education and 8 for housing quality. The fifth
part discussed poverty issues in Badin and concludes that the major problem in the area is
the absence of capital or surplus earnings with the community; this means they are
excluded from various development schemes such as microfinance.
17
CHAPTER II
REVIEW OF LITERATURE
The objective of this section is to review a number of issues related to
poverty and inequality at international level, Pakistan and Sindh respectively.
2.1 International Perspective on Poverty and Inequality Issues Poverty alleviation was the main focus of the international community at
the millennium meeting of the United Nations. Commitment was made there, that
absolute poverty would be reduced by 50% by the year 2015. The World Bank brought a
document in support, pledging to do all it could, to meet the target of taking the poor to a
level of earning that is more than one dollar a day. In doing so, it gave itself a stiff target.
The report lays down that the following was to be done besides the reduction listed
above:
1. Ensure universal primary education
2. Eliminate gender disparity in primary and secondary education.
3. Reduce infant and child mortality by two thirds
4. Reduce maternal mortality by three quarters
5. Ensure universal access to reproductive health services
6. Implement national strategies for sustainable development.
At the current growth rate, the population will increase over 2 billion by
the time the target data is reached. The tragedy is that, all this is analyzed in terms of
commitment of money. Means can never be turned into ends. The attending
circumstances round the world are going to be different, so every country will have to
chart its even course. The objectives by themselves are contradictory and conflicting.
Even in the sub-containment, the differences in culture between India and Pakistan
18
(despite proximity and close links) is so diverse, that some of the options in India are not
workable in Pakistan and vice versa (Zafar, 2004).
The previous strategies that were brought in failed miserably, the amount
of time and resources spent on the quantum and measurement of poverty need not to be
elaborated at this stage, but the fact remains that there seams to be greater effort at
measurements and tangential activities, rather than something direct and tangible. The
decades of the seventies, eighties, and nineties are replete with failures. Had they been
seen as failures, matters could have been put right but that has not been so. The World
Bank is constantly under review to determine its optional working size and it has still not
find one. “Lords of poverty and Masters of Illusions” are two well documented books
which give a graphic picture of what goes on in the World Bank.
The current strategy of the World Bank enters the high moral ground again
by building on past cumulative experience and in the context of the changed global
situation. The strategy is going to be three pronged.
(1) Promoting opportunity
(2) Facilitating empowerment
(3) Enhancing security
This strategy will be considered in the light of how they will be translated
into action in developing countries. The UNDP’s report overcoming poverty was
published in the year 2000. The UNDP considers planning, essential for poverty
reduction. It does not agree with the more radical views expounded by some, that the free
market will allow poverty to be alleviated.
The UNDP links poverty to lack of effective governance and ideally
would like to see that governance is improved and that external assistance is limited to
19
that, but does not address the question of what governance is? The report appears to
assume that developing countries are working under condition of certainty and that the
process of governance is laid down.
There is very little change for developing countries to deliver in terms of
linking the countrys’ policies to alleviation of poverty. The previous policies that were
followed on the dictates of the international agencies have been discarded and a switch is
now considered necessary by those agencies. The structural rigidities that have developed
have been due to failed intervention by international agencies, but it was the policies of
the developing countries that were made to seem responsible for the inadequacies and the
failures (World Development Report, 2001).
Another point made in the report is with regard to world trade. We now
know that there is massive resistance to the WTO and that the Seattle, Prague and Qatar
conferences ended up in smoke. If trade is to be the leader in development, then the
confusion must end. All that the developed countries would be doing is pushing their
surpluses on the developing world. According to Stephanie black the IMF (and by proxy
the WTO) have been successful in selling Florida tomatoes and potatoes in Jamaica, thus
starring the indigenous small producers by putting an end to their future prospects.
Within a month there were riots in Jamaica and the army was called out. According to the
Prime Minister, the army picked off the opposition with sniper fire.
When a country is unable to link its internal policies to poverty alleviation
how does one expect policy makers to be able to develop polices that would lead to
poverty alleviation?. Given this state of affairs, how does one expect to gain from a world
order. The head start of the developed countries is such that, it is impossible for
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developing countries to catch up with them. In any case, the developed countries are
targeting the rich and the efficient in developing countries; the rich who are identified in
with and are the successors of the colonialists.
The UNDP “Report Overcoming Poverty” was published in the year 2000.
The report came out as a result of the social summit 1995. The short coming was that,
despite the urgent need the donor countries were cutting back on financial resources. The
fetish for financial resources is almost the single most valued weapon with the developed
countries. However the critical element in the entire game is not finance at all, but bits
and pieces of relevance that are particular to that culture. The report lists some elements
such as commitment as essential in the fight against poverty. It generally disagrees with
money concept as defining poverty, and visualizes incorporating specific targets like
reducing malnutrition, expanding literacy and increasing life expectancy(UNDP, 2000).
The International Fund of Agricultural development has track record in
dealing with rural poverty much beter than other agencies, linking five cardinal points as
challenges. First that smallholder production and production of staples plays an important
role in the livelihoods of the rural population. Secondly, that reducing rural poverty
requires better allocation and distribution of water to improve production of staples.
Thirdly, that achieving the poverty targets requires resource distribution in favour of the
poor. Fourthly, that particular group merit special attention i.e. women. The problem with
fragmentation is that it displaces policy and one can find all kind of excuses of not
performing.
The fifth challenge is participatory and decentralized functioning.
Participation as the west sees, it is not as strong as it is in the east. The lower the
21
formation in terms of defined organizational structures, greater the existing participatory
levels. The decision making is by consensus and that is good enough (IFAD, 2001).
The food and agricultural organization of the UN (FAO), which is directly
involved in agriculture and food security, has brought about a document. The document
relates poverty to land and natural resources degradation. Sustainability of agriculture is
the growing concern. The FAO lists a number of issues in its report such as; the
degradation figure for land worldwide has gone upto 1.9 million ha. The consequences of
land degradation are such that it increases poverty and permanently. The loser every time
is the small farmer. Majority of the people in developing countries live in rural areas.
Why is it that the policies are not in line with their requirements? The reasons are many,
but the main one is the growing gap between policy makers and rural areas (FAO, 2007).
2.2 Critique
Our understanding on the international perspective to poverty and
inequality issues was that poverty has two root causes, one is lack of economic growth,
the other inequitable income, wealth and resource distribution. Major components of the
latter are concentration of assets in the hands of few, inadequate schooling, lack of social
services and infrastructure and unemployment problems (World Bank, 2005).
The World Bank in its analysis of a dozen of countries argues that changes
in the incomes of the poor can be explained by decomposing them into that part
attributable to overall economic growth and that part ascribed to differences in the
inequality of income distribution. Our impression was that rural, and urban poor were not
disaggregated a task which must be accomplished some day in the future.
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Brazil for example, was enjoying a very high rate of economic growth but
inequality was becoming more severe problem. Given the growth rate, it had experienced
between 1980 and 1990 drop of poverty incidence of 34 percent was forecasted by the
World Bank model. But since inequality increased, there was a drop of only 24 percent in
poverty incidence. And if distribution in Brazil had proceeded to the same extent as
Malaysia given Brazil’s growth rate, poverty reduction would have been in the order of
43 percentage points (Gary and Guy, 2006). So, the pattern of growth and the way the
income effects of growth are distributed as well as its rates are important determinants of
change in the incidence of poverty.
In Malaysia, growth was not as rapid as in Brazil, but income effects from
it were distributed more equitably and while a 19 percent reduction in poverty was
forecasted, actual reduction was 23 percentage points. High growth does not indicate
progress in solving social problems. Pakistan is a high growth, least developed country,
and Brazil, a high growth middle income country. Yet, Brazil has one of the highest
mortality rates for children under 5 years of age among LDC’s and Pakistan has one of
the lowest primary school enrolment rates for children (Samaratne, 2005).
Levels and rates of growth of GNP Grass National Product do not always
limit the progress of social indicators. One particular characteristic of development over
the last several decades is the fact, that social indicators have tended to run ahead of
economic ones. And in some low income countries like China, Srilanka and the Indian
State of Kerala, per capita income levels are very low, but other indicators such as infant
mortality, life expectancy, literacy and nutrition exhibit surprising progress, though the
sustainability of that progress is in question, especially when growth rates are slow and
23
expenditures for non social programmes rise. A country’s solution to problems. Depends
not only on its GNP rough indication of its capacity to act, but also on its distribution of
wealth a sign of its public will. One important limitation to poverty alleviation is that,
third world countries spend half of their total annual expenditures for servicing the
national debt.
Growth without a fairly equitable distribution is a very blunt instrument
for poverty reduction. Even so, researchers have recently concluded that in terms of
satisfying basic needs, average real income growth is much more decisive than change in
income shares. But growth can be honed with institutional change and public policy, so
that improvements in distribution channel income gains to lower strata of society,
perhaps the most enduring manner of targeting a solution for groups in poverty; on the
other hand redistribution without growth is equally suspect, in the absence of growth it is
once and for all event.
If we face a moral problem, that is to be dealt with primarily by
redistribution of assets and income within developing countries, then it must be dealt
through growth and broad processes of growth which require a very substantial set of
incremental resources. The capability of providing those resources determines the time
path over which they are provided then it becomes a moral problem of the rich developed
countries in which 95 to 100 percent of the population is above that poverty line. We
maintain that such growth is essential. Thus, it is very much a moral problem of the rich
countries of the world and one that they do not face up to particularly (World Bank,
2005).
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2.3 Pakistan Perspective on Poverty and Inequality Issues 2.3.1 A Review of Past Economic Policies (1958-1989)
The economic policies implemented by Ayub Khan administration,
created social and regional inequality. It was observed that the main cause of rural
poverty was continued dependence of the poor on landlords. (Saeed, 2005).
The state subsidies provided by the government created a situation, where
by industries were producing low quality products which, cannot generate enough foreign
exchange for the country. The government that took over from Ayub regime went into,
reckless financial allocation for the country’s resources based on, political support instead
of economic efficiency. The Bhutto Regime Nationalise the industries, for better
economic performance and self reliance. This gave the regime more political support
from the masses. (Saeed 2005).
The increase in budget deficit by the Bhutto’s administration has added
huge, expenditure to the government. While during the Zia’s administration financial
resources were used for wasteful political activities instead, of diverting the resources for
development of agriculture and irrigation, as well as human resource development. As a
result of withdraws of support, from foreign donors after the Afghan war investment and
economic growth decreased and budget deficit went up this, increased poverty among the
poor. This period brought about change in structure of the economic growth, as a result of
this development both capital and labour productivity decreased. Similarly, decrease in
capital productivity affects economic growth. Likewise decrease in labour productivity,
affects real wages. Therefore decreased in GDP growth and real wages directly affect the
25
economy and in this situation poverty increase. (Saeed, 2005). The present situation laid
the foundation, of rising poverty and unemployment in the country (Saeed, 2005).
2.3.2 The Deepening Economic Crises (1989-1999)
In the 1990s there was serious political instability in the country
politicians use their position for personal gain, to the detriment of the poor. The law and
order situation, affected foreign investment and economic growth (Shabir, 2004). The
failure of successive governments in this period to address the deteriorating infrastructure
and the emerging financial crisis further exacerbated the unfavourable environment for
investment. During this period the government continued with wasteful expenditure and
decided to reduce development expenditure, which went down from 7.4 percent of the
GDP in (1973-77) to 3.5 percent from 1997-98 to 1999-2000 (Shabir, 2004).
Similarly the GDP decreased from 6.3 percent in the 1980s to 4.2 percent
in 1990s. Increase in employment remain very low at 2.4 percent since 1980s. This shows
that unemployment, increased during 1990s no immediate solution to the problem.
Likewise increase in labour productivity decreased, this bring down real wages which
severely affect the economy (UNDP, 2000).
The regular increase in fluctuations of agricultural output led to increase
in, incidence of poverty among the poor masses. (Hussain, 2004). In view of the adverse
decrease in input productivity small farmers, lacking strong financial resources will face
more problems, than large scale farmers. (Saboor, 2004). Consequently slower and more
unstable growth during the 1990s could be expected to be accompanied by growing
poverty and inequality (Saboor, 2004). The Gini Coefficient which is a measure of the
26
degree of inequality increased from 26.85 in 1992/93 to 30.19 in 1998/99. Similarly, the
percentage of population below the poverty line was 26.6 percent in 1992/93 and
increased to 32 percent in 1998/99 (Saboor, 2004).
2.3.3 Medium Term Poverty Reduction Strategy Paper (MTDF) (2006-2009) The medium term poverty reduction strategy paper aims at forging a broad
based alliance with civil society in the quest to alleviate poverty and accelerate
development. The strategy is being enriched by the on-going process of dialogue with
civil society and the poor. The strategy places considerable emphasis on taking advantage
of the opportunities offered by globalization.
The Poverty Reduction Strategy Paper (PRSP) process has been
completely aligned with the millennium development goals (MDGs) and the medium
term development framework (MTDF). While the MTDF provides a framework for
translating the vision 2030 into action during the period 2005-10. Its emphasis on the
other hand present the strategy to ensure that the growth is broad based and leads to
effective poverty reduction. The detailed policies related to growth promotion are
presented in the MTDF, while the PRSP takes those interventions as given and focuses
on the package of interventions required to ensure that sustained high growth is translated
into effective poverty reduction and the poor and marginalized are protected (GOP
MTDF, 2006).
2.3.4 Pakistan Poverty Reductions Strategy Paper-II (2006-2011) The second five year poverty reduction strategy II produced by the
government give, more emphasis on employment and development of infrastructure. The
27
new programme initiative would require Rs. 1500 billion for implementation. The
strategy paper will learn from, the previous experience in implementing PRSP which
failed to deliver (GOP PRSP, 2005). A total of Rs. 1200 million is needed to implement,
various projects targeting poverty reduction among the poor (GOP PRSP, 2005). Foreign
donors agreed to provide financial support, for the proposed PRSP II initiative. World
Bank promise to disburse $ 8 billion, ADB $1.8 million and UNDP will provide $ 200
million for five years (GOP PRSP, 2005).
The poverty alleviation strategy paper II is designed in the light of UN
millennium development goals. The aim is to expand, the private sector which has been,
the engine for economic growth. (GOP PRSP, 2005). Therefore various initiatives are
taken in order, to make PRSP II achieve its goal. (GOP PRSP, 2005). Foreign donor
advised the government to set aside 4 percent of the GDP for the development of
education, which will in the long run plays a positive role towards, poverty reduction.
(GOP PRSP, 2005).
The aim of millennium development goals is to reduce poverty by increase
in enrolment, up to 100%, reduce death rate of children up to 80 percent, by the year
2015. The MDG goals also include reduction of TB, HIV, Malaria, Hepatitis and
provision of good quality drinking water and arrangement, to protect public health
especially by drainage and efficient disposal of sewage. (GOP PRPS, 2005).
2.3.5 The Four Pillars of Sustainable Poverty Reduction The first pillar to support poverty reduction initiative is economic growth.
Pakistan is a good example of countries, that comparison can be made between economic
growth and poverty reduction. (Israt, 2000). In the year 1969-70 poverty has reached
28
46%. As result of 6 percent economic growth, between 1970 and 1988-89 poverty
declined to 18 percent. For Pakistan to compete in comity of nations, it is important to
maintain 5 to 6 percent economic growth, but this is not enough for poverty reduction,
other factors has to be taken into consideration. The second pillar is large scale
investment in human resource development, this has been ignored for a very long time.
(Israt, 2000). After independence in 1947 literacy target was, expected to be between 90-
92% instead of 49 percent. Likewise the per capita income presently expected to be more
than 1500 instead of 700. (Israt, 2000). Similarly more investment in human resource
development, would have an effect on economic growth, on a long period of time.
The third pillar also shows that investment in human resource
development is not enough, for poverty reduction it is necessary to target poorest of the
poor directly. If this is not done majority of the poor will not benefit from, various
poverty alleviation initiatives. The fourth element is that even if all the three indicators
were achieved, majority of the poor would need safety nets, to be provided by the
government. It is now the responsibility of the government to generate resources through
various sources, for poverty reduction. (Israt, 2000).
2.3.6 Pakistan Participatory Poverty Assessment (PPPA) National Report PPA is defined as an instrument for including poor people’s views in the
analysis of poverty and the formulation of strategies to reduce it through public policy.
Participatory poverty assessment is a powerful tool, that can be used for poverty
reduction, through various methods. First there is a need for social mobilization, to
enlighten the poor about poverty (GOP PPPA, 2002).
29
Second the PPPA should be participatory by involving the poor, in the
process along with government and civil society. This will result to changing policies for
the benefit of the poor. (GOP PPPA, 2002). Third PPPA methods can help in identifying
weaknesses from, various quantitative studies or point out to deviation, or inconsistencies
that can be investigated, through various methods. (GOP PPPA, 2002).
The PPPA in Pakistan started in 2001 and it can be grouped in three
segments (1) Setting up the structure (2) Field survey (data collection) and (3) follow up
(GOP PPPA, 2002). The programme encouraged many people to participate, particularly
the poor who are considered as important primary stakeholders. Similarly government
functionaries in the local, provincial, and federal government, various NGOs and civil
societies, are considered as other stakeholders. Journalists, opinion leaders, academicians
from universities and research institutions are also recognized as secondary stakeholders.
(GOP PPPA, 2002).
2.3.7 The Key Conclusions and Policy Issues were as Follows:
The major conclusion drawn from PPPA is that it was a thorough research
conducted, in small villages of poor communities all over Pakistan. The ability to
perceive and understand the true nature, of poverty and how the poor react to its intensity
and possible ways to alleviate it on a long term basis. (GOP PPPA, 2002). The key
conclusion is grouped into six themes.
1. The less privilege people want to have access to land, water and protection from
environmental harzards.
2. The safety nets provided can not protect the poor.
3. Facilities and services provided were not sufficient.
4. Employment opportunities are lacking for the poor in rural areas.
30
5. The female population live in miserable conditions.
6. Justice is not provided to the poor and they have no access to political leadership.
2.4 Critique
The Pakistan poverty reduction strategy paper-I focusses on employment
generation and poverty reduction. Therefore, in order to achieve the above strategy
employment opportunities, Should be initiated in both rural and urban districts (GOP
MTDF, 2006). In the areas of micro credit, the government agencies that are working for
poverty alleviation through their NGOs must ensure that they identify the actual
vulnerable groups i.e those who really need assistance and disburse credit to them so as to
come out of poverty. It has been observed that the major reason why poverty is
increasing, is because government programmes actually do not go the target communities
mostly in developing countries and if that continues, it will be difficult to reduce poverty
The PRSP process has been completely aligned to millennium
development goals MDG and the Medium Development Frame work (MTDF) while the
MTDF provides a framework for translating the vision 2030 into action during the period
2005-10 (GOP PRSP, 2005). For poverty alleviation to succeed in Pakistan, we need as
detail scenarios of poverty generation as possible, otherwise poverty alleviation
programmes will merely treat the symptoms, rather than the root causes.
The second critique is about the nature of growth process which can play a
significant role in eliminating poverty of an obsolete nature over the long run. We
constantly emphasize that dealing with absolute poverty and not distribution of income as
represented by Gini coefficient. The people concern with poverty in the foreign
assistance community themselves virtually never focus on this issue of the details of rural
31
development strategy which would bring about rapid poverty reduction (GOP PPPA,
2003).
2.5 Sindh Perspective on Poverty and Inequality Issues 2.5.1 Sindh Poverty Reduction Strategy Paper
Pakistan policies to reduce poverty are organized around the poverty
reduction strategy paper (PRSP) framework, which is being implemented by federal and
provincial governments. The Sindh poverty reduction strategy paper focusses on the
following:
2.5.2 Addressing the problems of Karachi
Nearly one third of Karachi’s solid waste amounting to more than 2,200
tons is not picked each day and instead dumped in its natural drains. The traffic
conditions along several major corridors are rapidly approaching situation and levels of
airborne particular matter in the most heavily trafficked parts of central business are
about 10 times the prescribed safe levels. The major constraints to investing in Karachi
are:
An inefficient land market that reduces access to increase the cost of real estate.
The delay and high cost of enforcing contract and judicial efficiency.
Poor quality of urban infrastructure especially electricity water supply and
sanitation.
Policy uncertainty and lack of strong leadership.
The following land market distortions are the focus of discussion in the
strategy paper.
Lack of competition among the largest landowners.
Unclear property rights and lack of transparency.
Inflexible and non-uniform zoning laws and arbitrarily low floor area ratios.
Pro-tenant legislation and high taxes on property-related transaction
32
2.5.3 Addressing the Problems of Non-Karachi Urban Sindh
The strategy to develop Karachi as the primary engine of growth and the
neglect of other urban centres is being increasingly questioned in Sindh, this is evident
from the investment climate. Survey indicates that Pakistani business men perceive
Hyderabad and Sukkur as the second and third largest cities in Sindh after Karachi. Sindh
may need to pursue a two fold urban renewal strategy; one that sustain the organism of
Karachi and another that unlocks the growth potential of its second-tier cities.
2.5.4 Accelerating Shared Growth in Rural Sindh
A strategy to accelerate shared growth in rural Sindh needs to be based on
regions, comparative advantage resources constraints and changes in market place out
line above. The emphasis should be on.
Improving productivity of water through a more effective and transparent
water management system.
Creating the right environment for modernization and diversification with the
crop sub sector.
Diversifying away from the crop sector to livestock fisheries and non-farm
activities.
2.5.5 Improving Service Delivery
It is not an exaggeration to say that public service delivery system of
Sindh in rural areas is in a state of crises. Following facts may be considered.
(a) The net enrolment rate in primary schools has declined from 45 percent in 1995-
96 to 40 percent in 2001-02 and further to 39 percent in 2003-04.
(b) There has been no improvement in the health indicators of children during the last
15 years in Sindh.
33
(c) According to government survey, only 23, 16 and 11 percent showed satisfaction
over current water supply, sewerage, sanitation and garbage services respectively
provided by the government.
The major focus of the paper in addressing the above issues are:
Raising the capacity of government institutions tackling corruption.
Creating more competition in provision of public services.
Ensuring effective coordination within the governments (PRSP Sindh, 2003).
2.5.6 World Bank Report on Securing Sindh’s Future January 2006 According to World Bank Report (2006), the incidence of poverty in rural
areas of Sindh, especially southern districts and urban and Peri-urban areas excluding
some parts of Karachi is amongst the highest in Pakistan
The aggregate estimates of the poverty head count based on the household
income and expenditure survey (HIES) data hide this extreme high growing incidence.
Poverty in overall Sindh based on the latest HIES data is 48.4 percent. This means, nearly
one in every two in Sindh is below the poverty line out side of Karachi and this include
all the people living in Hyderabad and Sukkur.
2.5.7 Factors Responsible for Poverty in Sindh
(1) Access to land is the pre-requisite for direct access to credit. The poor is at
disadvantage in terms of aquiring land and its distribution. This has contributed to
the growing poverty in Sindh.
(2) Lack of poor maintainance water courses, low water rates, poor system of
assessment is responsible for huge wastage of water and lack of irrigation water.
(3) Natural disasters and sea intrusion occurring particularly in Badin and Thatta
districts has directly affected the economy of Sindh.
(4) Unsatisfactory performance in both health and education sectors, issues such as
gender differences in school enrolment, infant mortality and immunization had
not been addressed.
34
(5) The present situation of Judiciary and police may also be the major factors
responsible for poverty in Sindh.
Finally World Bank Report (2006) recommends that poverty reducing
expenditure targets on health, education and drinking water will be transferred to districts
and Tehsil governments. Government of Sindh will also give high priority in allocation of
additional resources for the maintenance and rehabilitation of rural infrastructure.
2.3.8 Retrospective View in Chronological Order
Rashida and Uzma (2009) explores linkages between governance and pro
poor growth in Pakistan. The analysis revealed that governance indicators are one of the
lowest in comparison with other countries. The study further revealed that the dimensions
of pro poor growth which include poverty, inequality and growth indicates that the poor
did not benefit from economic growth. Poverty and inequality increased, while inflation
is much higher for the poor as compared to rich households. Many people believe that in
terms of economic status they were better in 2005 as compared to 2009. The results
shows that there is a strong linkage between indicators of governance and pro poor
growth in the country. Econometric analysis also revealed that a strong relationship still
exist between good governance, poverty reduction and inequality.
Sarah (2009) examine the role of Pakistan poverty alleviation fund on
poverty reduction in Pakistan. The study revealed that 37,500 villages and rural
settlements now have access to microfinance, this means 13.8 million beneficiaries. The
loan recovery rate is 100%. About 9.5 million people have been impacted by water,
health and education projects. By the end of 2008 the fund has conducted 7,700 trainings
to more than 279,000 beneficiaries 45% of them are women. The financial limit of
35
Rs.500,000 per project was raised and the overall cost per person was Rs.5000, in this
way it can reach larger populations.
Riaz Haq (2009) describes the role of microfinance institution in fighting
poverty in Pakistan. The positive impact of loans disbursed by microfinance banks has
been recognized. For example a customer to Kashf Foundation revealed that due to the
success of her business she was able to finance her husband’s illness through health
insurance provided by Kashf. Similarly a customer to Asasah claimed that her dairy
business profit doubled due to micro loan she receives. A shopkeeper who received loan
of Rs.35,000 from Tameer claimed that his business increased two times due to the loan.
The banking sector presently gives loan to 6 million borrowers meaning only 15% had
access to credit in Pakistan and that 85% of the population have no access to credit, that
is why they had to rely on local money lenders for their credit needs.
Shahbaz et al. (2009) utilizes data from 1991 to 2007 in their research on
economic growth and its determinants in Pakistan. Logistics regression model was
constructed to identify the linkages. The study concludes that logistics regression model
gives better results than simple or multiple linear regression models.
Burki and Khan (2008) examined the impact of wheat price boom on
poverty distribution and welfare of wheat consumers in Pakistan. The findings of this
research revealed that wheat price brought about a small decrease in poverty in rurul
areas and increased poverty in urban areas. If the international price were imposed on
consumers this will increase the overall poverty to 16% while specifically in urban areas
poverty will increase by 66%.
36
Arif and Iqbal (2008) focused on regional differences in poverty in
Pakistan. They found that infrastructural development has a significant impact on poverty
reduction. Multivariate analysis indicates that access to road and electricity, provision of
educational facilities for girls and health facilities to the community plays an important
role in identifying the level of poverty. The study further revealed that investment in rural
infrastructure and provision of education and health facilities will play a good role to
increase the income of the poor and poverty reduction.
GOP (2008-09) described poverty in different dimension such as lack of
income, inability to afford good quality life, lack of opportunities available to the poor,
and inadequate access to human development. It is expected that GDP should grow at
2.0% in the year 2008-09. The agricultural sector is expected to grow by 4.7% while the
services sector shall grow at 3.6% in 2008-09. According to UN poverty in Pakistan has
increase due to food inflation. The number of people living under the poverty line was
about 45 million people in 2008. The various initiatives launched by the government such
as Benazir Income Support Programme, Pakistan Poverty Alleviation Fund, Punjab Food
Support Scheme, People’s Works Programme and Baitul Maal Scheme has contributed
tremendously towards poverty reduction particularly to destitutes, widows, ophans and
needy people.
Lawal et al. (2008) present the findings of research on rural household
security among agro pastoralists in Nigeria. The study was based on a sample of 87 agro-
pastoralist food households shows that majority of the agro -pastoralist households in the
study area are food secured. The probability that an agro pastoralist household will be
food secured increases as crop enterprises are further diversified and decreases as
37
household size increases. Food insecurity among the agro -pastoralists is poverty
triggered and not as a result of low crop output.
Asif (2007) investigates factors affecting occupational choices in rural
North West Pakistan. Census data of 2825 households in 6 villages was used for the
analysis. The author compares six district occupations with non farm informal activities.
It was revealed that due to lack of natural, financial and human capital many people in
the study area had to look for employment in the formal sector.
Munawar et al. (2006) assess the impact of small scale irrigation on
agricultural production and poverty in marginal areas of Punjab. They computed head
count index, it was found to be 33 percent in the area. Poverty head count index were
computed to be 50, 34, 20, 37, 4, 42, 33 and 19 percent respectively for Jang, Ghaib,
Fateh Jang, Attock, Gujar Khan, Kahuta, Rawalpindi and Chakwal districts. The analysis
of farm size with access to irrigation was carried out the study revealed that head count
was 44% small farmers, 40% of medium and 12% large scale farmers.
Mallick and Ghani (2005) review the relationship between poverty,
population growth and environmental factors like good governance, literacy and
education, employment opportunities both for men and women, in urban and rural areas,
income distribution, investment in social sector, improvement in contraceptive access and
supply will make it possible to achieve sustainable population in poor countries. The need
is to set priorities. Currently, over half of the world population is living below 2 dollars a
day poverty line according to the UN projections, fertility in developing countries will
drop to an average of 2.1 children by 2050 and eventually to 1.85 children. It was
concluded that higher population growth has implication for natural resources. Pakistan
38
has to incur huge expenses on importing food items like edible oil, wheat and pulses.
Pakistan could not replicate the industrial countries transition because of its inability to
modernise agriculture or develop industrial base. Finally, population growth
environmental degradation and high debt levels are a cause to rural poverty.
Anwar (2005) examines the prevalence of relative poverty in Pakistan. It
was found that 40.3 percent of all individuals were poor in the country. The results
suggest that 60 million individuals were poor in Pakistan, of which 46.1 and 14.4 million
individuals were located in rural and urban areas, respectively. Trends in relative poverty
suggest that poverty rose from 34 percent in 1984-85 to 40 percent in 2001-02. Thus,
relative poverty increased more rapidly than absolute poverty during the above period.
Some policy implication were to formulate pro-poor policies, first the country has been
pursuing a poverty reduction strategy paper (PRSP) over the last five years. Secondly,
there is an increasing recognition that economic growth alone is not enough for poverty
reduction because of the existence of inequalities in the socio-economic structure of the
country. Thirdly, poverty reduction strategy should be based on policies of building up
the assets of the poor. Fifth, focus on agrarian strategies especially those favouring rural
industrialization can lead to pro-poor growth.
Arif (2004) examines the health status of Pakistani children using two
important indictors, mobility and malnutrition measured by weight for age and height for
age. The main data source used in this study is the 2000-01 Pakistan Social Economic
Survey (PSES), which provides sufficient information of child health and poverty.
Findings of the study shows that both exclusive breast feeding during first 4-5 months of
life and immunization can help control the occurrence of illness significantly among
39
young children (0-5) month. The rise in poverty since the mid 1990s has adversely
influenced the nutritional status of children. More resources should be available for
preventive health care aspects. Coverage of child’s immunization should be enhanced and
the provision of safe drinking water may be given high priority in the social sector
polices.
Hamayun (2004) investigates gender related interventions introduced by
Aga Khan Rural Support Programme AKRSP in district Chitral. The study findings show
that gender related interventions introduced by AKRSP has played a positive role in the
development of rural women in the area. In addition to the provision of water supply
schemes, health and credit facilities training had also been imparted to local women in
agriculture, livestock and vocational enterprise development. These trainings had made
positive impact and increase the income of respondents. Overall these interventions had
improved the socio-economic conditions of women to a greater extent in the area.
Zaman and Aman (2004) analyse the effects of poverty on community.
They measured poverty in terms of basic needs such as health education and employment
on the most deprived and neglected areas of Dera Ismail Khan district of NWFP. About
16 villages were selected for the study. The results of the study revealed that out of 16
villages only 3 villages have 100% illiteracy rate. While high literacy rates were found in
Mohallah Musazai 32% and Nai Basti Chodwan 12%. Only 2 villages have 100% basic
health facilities while the rest 14 have been deprived from this facility. Langarkot has the
highest unemployment rate 93.04% while the low unemployment rate was found in Gara
Guldad 60%.
40
“According to Hussain, 2003 poverty alleviations is important as, it affects
the welfare of the poor. It is the responsibility of the government to ensure that, various
welfare oriented programmes are implemented to move the poor out of ultra poverty. It is
argued that, increase in job opportunities in government departments will help the
economy to grow is not logical. This is because it is not sustainable and poverty will
increase in manifolds. The paper recommended a positive approach, to poverty
alleviation. It is based on various method used by various, donor and funding genecies
and empirical results from Pakistan”.
Various studies conducted were, compared with results on different
procedures. (Kemal 2003). The two major conclusions drawn from the analysis are (1) It
is not necessary that economic growth is slow (2) poverty alleviation depends, on job
opportunities and provision of microcredit to the poor. (Kemal 2003). The official
poverty line is based on various, criteria and complex method used were, prices can be
adjusted. (Kemal 2003).Various poverty estimates can be obtained by using different
methods. (Kemal 2003). There was a fluctuation on estimates obtained, in the trend of
rural and urban poverty in the nineties. The major conclusion was that, the incidence of
poverty in the late nineties, is more than in early nineties. (Kemal 2003).
“Similarly Hussain, 2003 initiate a policy for poverty reduction that, gives
a new structure on macro economic growth in favour of the poor communities”. The
latest observation revealed that, the wide spread ill health is the major problem that push
the middle income group into poverty and the poor, into abject poverty. There is a need
for various programmes on environmental protection, provision of good quality water,
and improvement of poor quality health care, particularly in rural areas.
41
There is a need to restructure growth so as to influence poverty reduction
ability this can be achieved by addressing four issues.
a. Small investment can be used to achieve higher economic growth.
b. Provision of job opportunities to the poor.
c. To achieve higher export targets.
d. Reduction of poverty on a large scale with greater equity and sincerity. (Hussain
2003).
Khan (2003) identifies the law and order in Sindh and its causes as the
primary reason for increases in poverty in Sindh. An unfortunate fact about the economic
policy in Pakistan is that, it is not sensitive to the employment and developments needs.
The domestic manufacturing which remained greatly protected in the past and yet could
not perform well, is going to further suffer, because of the free trade region which is
being vigorously persued in Pakistan mainly under IMF conditionalities i.e. political
stability and improved law and order situation, together with a sustained 7 percent GDP
growth was required. An important area to be developed is the labour market information
system and also the social mobilization.
Sharif (2003) analyse the determinants of rural poverty in Cholistan
Bahawalpur. He concluded that land distribution was highly unequal with a gini
coefficient of 0.68. Similarly the degree of inequality in the distribution of income is
lower than a gini coefficient of 0.36.
ADB (2002) reported that poverty rose more sharply in rural areas in the
1990s and in the FY 1999; the incidence of rural poverty (36.3) was significantly higher
than urban poverty (22.6) percent. Inequality also increased in Pakistan during the 1990s
42
in both urban and rural areas. In line with the national picture between 1993 and 1999,
the incidence of poverty increased in the Punjab from 25.2 percent to 33.0 percent in
Sindh from 24.1 percent to 26.6 percent, NWFP from35.5 percent to 42.6 percent and
Baluchistan from 38.2 percent to 45.8 percent. In general, ADB endorses government
poverty reduction strategy for Pakistan and will compliment government efforts.
However, ADB operational strategy will be selective in that, it will focus only on
interventions aimed at addressing critical bottlenecks and promoting growth in sectors or
activities that have maximum poverty impact.
Anwar and Qureshi (2002) evolve a consensus on the use of a consistent
poverty line, sources of data and data adjustment for measuring poverty have come up
with a services for the period 1990-91 to 2001. They conclude that the use of consistent
time series estimates of the poverty line shows that the head count measure of poverty
has increased from 17.2 in 1990-91 to 30.4 percent in 1998-99 and to 35.6 in 2001. They
have also raised serious doubts on the methodology adopted by the World Bank for its
estimates of poverty in the 1990s and concluded that the stagnation and or a slight
reduction, in poverty estimates seems to be a statistical artefact due to overestimation of
poverty in earlier years relative to late 1990s by the World Bank.
Malik et al. (2002) reviewed micro credit as a tool for poverty alleviation
in Pakistan. The poverty profile of Pakistan shows that a quarter to one third (30-50
million) of its population lived below the poverty line, while less than one `third of the
country’s population are poor almost one half (70 million) suffer from deprived
opportunities. The role of micro credit is considered as essential for the uplift of poor and
destitute and thus serves as an effective means of reducing the incidence of poverty.
43
Disbursement of credit at reasonable terms and conditions boosts agriculture and
industrial growth generates self employment opportunities and fulfils household
consumption requirements. Micro credit decreases employment and increases
productivity. Its impact as human resource development is also very important. The paper
recommends that to keep service charges and administrative cost low, the formal sector
should have to adopt quick and simple lending procedures.
Hina Nazli et al (2000) examined linkages between rural non-agricultural
employment poverty in Pakistan. There is a shift away from farm to non farm activities in
rural areas. The analysis shows that average workers in the non farm sector have been
better than agricultural labourers. It can be concluded that a dynamic labour intensive
agriculture combining with a modernizing non-agriculture can lead to a broad spread of
employment and income with resulting growth egalitarian distribution and elimination of
rural poverty. Policy intervention to promotion of farm employment is also justified to
stop to some extent migration to cities.
Kemal (1998) examines Pakistan experience in eradicating poverty,
determining the areas of ommisions and commissions in the policy formulation. Four
mechanisims which may generate poverty or help alleviation of poverty were examined;
(1) economic programmes and policies which promotes employment, (2) the taxation
policy of the government, (3) the provision of social services to the poorer section of the
society and (4) transferring income to the poorer section of the society. The increase in
employment opportunities would also tend to increase the wage rate and as such
functional income distribution would improve with positive implications for poverty.
Finally, zakat, ushr and baitul maal need to be made more effective. If transparent
44
methods are employed to select the recipients, then the revenues from zakah may also
increase.
Jafri (1997) presented some information on a number of government
sponsored poverty alleviation measures with a brief discussion about how poverty has
been measured in Pakistan, showing in poverty over the last fifteen years. Saqib (1998)
revealed that agricultural growth can play a vital role in alleviating rural poverty. It was
concluded that agriculture generally performed well. Its average annual growth rate since
1959-60 had been impressive (3 percent) while in the last decade it was about 4.0
percent. However, it has not been consistent e.g. it increased to 11.72 percent in the year
1995-96 but decreased to 0.12 percent in the very next year (1996-97), became 3.82
percent in 1997-98 and again 0.35 percent in the year 1998-9. Even a little shock to
agriculture is bound to affect not only the country’s growth performance, but a large
segment of the country’s population as well. Like many other South Asian countries,
poverty in Pakistan was a rural phenomenon and agriculture will play a critical role in the
fight against poverty in the country.
Malik (1996) concluded that overall poverty trends in rural areas of
Pakistan have fallen. Survey results from villages show a highly skewed landholding
pattern with a Gini Coefficient of 0.56 of the 100 households surveyed. It was found that
only 10 of the 19 in the landless category were categorized as poor although the intensity
of poor was found to be particularly severe amongst the landless and most of the poor in
this village come from the landless category. Conclusions from this research suggest that
a better distribution of assets and access to resources is necessary to eliminate poverty
and the need to promote non farm activities.
45
Shirazi (1994) examines the incidence of poverty and identifies socio-
economic profiles of rural poor in Pakistan. The findings of the study revealed that
majority of the male household head are in the age group of 40-49, similarly majority of
the female household head are in the age group of 30-39. classification of poor according
to marital status revealed that 95% of male household and 75% of female household head
are married.
Ghausi (2006) reported the woes of rural Sindh and observed that given its
feudal traditions, progressive ideas and reforms have always taken more time to take
roots in the interior of Sindh than in most other regions of Pakistan. For the last few
years, Sindh government has been attributing growing poverty in its rural areas to the
damage of crops and livestock caused by continuous drought for three years. The World
Bank too endorsed this view and held water scarcity as number one issue that confronts
the provincial agriculture and reduces crop production. In its rejoinder to the World
Bank, the Sindh Government claimed that except for sugarcane, all the three major crops
(wheat, cotton and rice) have shown growth in output during the last five years
(2001-2006). The Sindh Board of Internal revenue reported that shortage of irrigation
water has reduced cultivated area by 15.59 million acres to hardly half a million acres.
IUCN (2006) argued that in terms of Human Development Index within
Pakistan, the urban areas of Sindh have the highest ranking with a HDI of 0.659, greater
than for Pakistan as a whole. But, rural Sindh has an HDI of 0.456, which is the lowest in
Pakistan. This shows that, there is a gap between rural and urban areas in, comparison to
other provinces (IUCN report, 2006). There are indications that over two-thirds of the
households in rural Sindh may be classified as vulnerable. More than 11 million men and
46
women in Sindh are unemployed and around 15 million live below the poverty line.
Sindh’s child mortality rate is 109 per 1000 live birth as compared to a national average
of 103. Sindh had the lowest enrolment ratio for primary schooling compared to other
provinces.The student teacher ratio for Sindh in 1999 was worst falling behind 10 points
as compared to other provinces. With an increase in levels of poverty over the last
decade, more children dropout of school to help their families by engaging in economic
activity. The report concluded that it is unlikely that the targets set by the PPA and PRS
will be achieved in the absence of effective institutions and governance system.
Murtazulhaq and Aziz (2006) mentioned that the incidence of poverty is
high in Sindh for those who depend entirely on livestock. Majority of non-poor depend
on crops while the poor on livestock. Although, the economics of livestock production is
heavily distorted in favour of large scale production yet this sector has enourmous
potential to combat poverty in Sindh and strengthen economic growth. It is recommended
that there is need to improve and extend veterinary services to village level. The animal
breeders at village level should be educated to use urea and molasses with roughages for
improved nutritive value.
Pakistan Participatory Poverty Assessment (PPPA) Sindh (2006) reported
that in many parts of Sindh rural, the single most important problem is the extreme
inequality in land distribution. This creates poverty and inequality among the rural
populace. The PPA confirms that bonded labour is thriving in parts of Sindh and is the
reason for poverty. Landlord dominance also extends to water rights especially in
conditions of scarcity. The decrease in water availability causes chain reactions with
respect to livestock holdings, lower agricultural yields as well as the increasing scarcity
47
of fodder forced many households to sell their animals. Creating an enabling environment
to adapt and strengthen livelihoods through a social protection system is a central
component of a poverty reduction strategy. The possibility of poorest, especially if they
live in remote areas are never reached. Therefore, the possibility of distributing zakat in
the form of food, clothes or housing should be examined. Finally, poverty reduction
strategies need to be both roburst about treating corruption as an issue needing attention,
and realistic about how effective reforms are likely to be (irrigation management, tax
administration, social protection, law and order)etc.
Securing Sindh’s Future, World Bank Document (2006) reported that the
incidence of poverty in rural Sindh and the urban and peri-urban areas is among the
highest in Pakistan, based on the latest HIES (2001) data it is 48.4 percent and 36.7
percent when included. This means nearly one in every two in Sindh is living below the
poverty line. In terms of Human Development, Sindh is far behind the rest of the country
with the largest rural urban gap is the key indicators. One out of every ten children born,
dies before his or her first birthday and one out of every nine children, dies before
reaching five years of age. Every 20 minutes a woman dies from complications relating
to pregnancy and child birth. One in five persons in Sindh does not have access to safe
drinking water. The factors responsible for this sad and deteriorating situation in Sindh
are (i) land distribution in Sindh is highly skewed the prevalence of an unequal land
distribution and acquisition is thus a major cause of poverty, (ii) the deterioration of the
irrigation network due to poor maintenance and (iii) the province is a victim of natural
disasters such as draught cyclones and sea intrusion. Finally the World Bank
recommends that poverty reducing expenditure targets on health, education and drinking
48
water should be transferred to Districts and Tehsil governments. Government of Sindh
will also give high priority in allocating additional resources for the maintenance and
rehabilitation of rural infrastructure.
NUPAP Sindh (2005) reported that there was improvement in the existing
physical infrastructure with community participation. Most of the communities of urban
slum areas in Sindh are living below the poverty line and Jacobabad is worst among
them. Micro credit intervention is the most important element after social mobilization.
NUPAP Jacobabad have identified cases for intervention in micro credit and 10 cases
have been shortlisted for NLC credit intervention. Mobilization and empowerment of
poor communities, especially women through low cost self help, local initiatives to
support income generation and improve local conditions. Partnership among local
communities and NGOs was achieved for sustainable development and poverty
alleviation.
Veloram (2005) reported that despite various measures poverty is not
decreasing and some estimates show that it is even increasing in rural areas. The
estimates of the study reveal that three-fourth of population of Tharparkar district live in
poverty. All the villages under survey have no access to electricity, safe drinking water
and sanitation; while only 26.4% households have health facility at the village. Logistic
regression was applied to explore the significant factors increasing poverty. The highest
probabilities for poor were estimated for less educated household heads, seasonally
migratory families, households with less numbers of earners, higher number of age
dependency in households etc. It was recommended that the public and private sector
49
organizations should alleviate poverty in Tharparkar district and launch various
programmes to address the above factors.
Sindh Poverty Reduction Strategy Paper (2003) reported that instead of
building on the initial advantages to become the country’s engine for economic growth,
Sindh has been gradually losing its position of pre eminence due to the following factors
(i) growth and employment (ii) poverty and social indicators (iii) inequality, social and
gender gaps. The urgency for Sindh to grow and develop rapidly has never been more
compelling than it is today. The basic development strategy presented in this paper rests
on two key pillars (i) enhancing Sindh’s growth performance by establishing a
competitive and predictable business environment in the urban areas and by addressing
the looming water problems in rural Sindh (ii) investing in people by improving their
access to social services, particularly for the poor and those living in rural areas, through
a combination of fiscal and governance reforms. It was concluded that a large part of
these problems can be addressed through policy and institutional interventions, but none
of this can be achieved without the full ownership and commitment of the political class,
whose support and leadership are critical to the success of any reform programme in the
province.
ADB (2002) reported that poverty rose more sharply in rural areas in the
1990’s and in the FY 1999. The incidence of rural poverty (36.3%) was significantly
higher than urban poverty (22.6%). Inequality also increased in Pakistan during the
1990’s both in urban and rural areas. In line with the national picture between 1993 and
1999 the incidence of poverty increased in the Punjab from 25.5 percent to 33.0 percent
in Sindh from 24.1 percent to 26.6 percent, NWFP from 35.5 percent to 42.6 percent and
50
Baluchistan from 38.2 percent to 45.8 percent. In general, ADB endorses government
poverty reduction strategy for Pakistan and will compliment governments efforts.
However, ADB’s operational strategy will be selective in that, it will focus on
interventions aimed at addressing critical bottlenecks and promoting growth in sectors or
activities that have maximum poverty reduction impact.
According to NHDR report the lowest socially developed districts were
Tharparkar, Badin, Sanghar, Thatta and Dadu. The latest studies conducted, supported the
above ranking, a good example is a survey organized by Agha Khan University covering
seven, districts of Sindh (NHDR, 2002).The survey further revealed that 70-80 percent of
rural household remain poor for very long period of time (NHDR Report, 2002). Skill
based training is recommended to primary school leavers, from poor communities this
can play a positive role in poverty reduction (NHDR Report, 2002).
Bhatti (1999) observed that fishermen in Sindh spend 5.6 percent of their
disposable income on muslim festivals. Averagely, 22 percent of the children are going to
school, their parents spend 6 percent of the their income on education. Health facilities
are not available, according to government figures one doctor is available for 2100
persons, majority of the people are affected by lungs infections and spend 0.5 percent of
their income on medicine. It was concluded that fishermen spend 20.5 percent of their
income on food, 4.0 percent on clothing, 1.7 percent on transport, 3.0 percent on fuel and
6.5 percent on other expenses of their disposable income. This implies that they are living
below the poverty line.
It was recommended that mobile floating health unit may be provided in
every big lake such as Manchhar, Kinjhar so as to provide treatment to fisherman.
51
Potable drinking water may be provided to fishermen in rural areas. Cooperative societies
may be established wherever the inland source of fish exists. Special loan for the
improvement of the living standard, education, medical care may be provided to
fishermen, this will encourage them to work efficiently.
2.6 Critique
Poverty alleviation effort in Sindh province is being sustained through
local initiatives as well as international assistance. There are, however several obstacles
to the effective implementation of poverty programmes. Some of these obstacles hinge on
the fact that many of the programmes were either not well designed / formulated or
implemented in a coordinated manner. Most of them relied solely on government
subvention for their operation, resulting in financial problems during periods of decline in
government revenues, discontinuities and other bureaucratic delays.
Some international poverty alleviation programmes have failed, owing
largely to inadequate financing, particularly lack of commitment on part of the executors
of various programmes has constituted the problems. Also some aspects of public
spending even though conceived with good intention have not been adequately targeted
and judiciously directed to fighting poverty in Sindh.
The problems of inadequate supply of water and poor maintenance of rural
infrastructure including rural roads, electrification and its sustainability have also not
been helpful in the effort to reduce poverty. Similarly, housing is very costly to acquire in
view of exorbitant cost of building materials, which the poor can hardly afford, thus
adding housing problems faced by the rural poor. Some of the present social policies
remain generally unsuitable for addressing the problems of poverty.
52
The lowest human development index 0.456 recorded by Sindh province
shows that, there is wide rural/urban inequality in the province (Securing Sindh’s Future,
2006). There are indications that over two thirds of the households in rural Sindh may be
classified as vulnerable, inspite of the fact that Sindh has the highest per capita income in
Pakistan. Sindh’s child mortality rate is 109 per 1000 lives, compared to a national
average of 103. It is unlikely that the targets set by the Pakistan poverty reduction
strategy paper will be achieved in the absence of effective institutions and governance
system.
The distribution of key private assets, is highly unequal and this is the
fundamental cause of poverty. This makes them poor and helps to maintain the rural
areas in a state of underdevelopment. Despite, some promising changes in rural areas, it
seems clear that several factors have combined to increase deprivation of some of the
poorest in Sindh over the last 25 years or so. The shortage of irrigation water
compounded by drought has led to serve disruption in crop yields in the province.
The only safety net that is generally known to local people in Sindh is
zakat, unless it is given to deserving people and equitably poverty will remain with the
vulnerable groups. A critical factor affecting the ability to cope with shock is that poor
and the very poor families tend to have limited assets available. This increases their
vulnerability and results in a situation where a shocks for instance in illness or loss in
income sources causes a decline in well being that is difficult to recover from.
Efficient design of poverty reduction programmes in Sindh requires that
the poor must be identified and targeted and policies adopted should be consistent and
sustainable. Lack of participation, failure to draw the poor into the design of
53
development programmes and inadequate access to assistance for those living at the
margin and those victimised by transitory poverty and all district specific issues identified
by the PPA such as exploitation of poor people, lack of law and order and absence of
security, the constant unrest and fear which has led some families to leave their villages,
the increasing encroachment of sea-water on to the land, extreme insecurity particularly
felt by woman and several other issues must be addressed so as to reduce poverty in the
rural masses of Sindh.
2.7 Conclusions
The review of the literature from international perspective to poverty
concludes that the World Bank three pronged strategy of promoting opportunities for the
poor, facilitating empowerment and enhancing security is yet to be translated into action
in poor countries. In Pakistan, the biggest challenge is achieving the millennium
development goals by 2015 through sound economic growth, greater emphasis on human
resource development, and availability of safety nets by the government for future needs.
(World Bank, 2005). Unless this is done poverty reduction efforts will not succeed in the
near future. While in Sindh province, the poverty reduction strategy paper major focus
was on addressing the problems of Karachi, addressing the problems of non-Karachi
urban Sindh, accelerating shared growth in rural Sindh and improving service delivery;
these issues will play a very good role in sustained poverty reduction in Sindh.
54
CHAPTER-III
METHODOLOGY
3.1 Sanghar District Profile Sanghar district derives its name from its headquarter town and was
carried out from Tharparkar and Nawabshah districts on 1st July 1953. The district lies
between 25030, to 26-29 north latitudes and 68025 to 70013 east longitudes. It is bounded
on the north by Khairpur district, on the north west by Nawabshah district, on the east by
Jaisalmir and Jodhpur (India), on the South of Mirpurkhas and Umerkot districts and on
the west and South West by Hyderabad district and the district occupies a total area of 10,
728 square Kilometers (District Census Report Sanghar, 1998).
3.1.1 History Sanghar appeared on the Map of Sindh in the shape of small village during
Talpurs rule in the years 1840-43 and it was renamed after Sanghar stream. It was
through this stream that Sher Muhammad could save his life having escaped from chase
by Sir Charles Napier.
Sanghar district has great importance due to political, cultural and
economic reasons. Its fertile lands are irrigated by irrigation system of river Indus before
the conquest of Sindh by Muhammad Bin Qasim. One can find ruins of Bahmanabad
three miles away to the west of Jhol Town. This place known as Depar Ganghar was
build after the name of Persian ruler Bahman URD Sher (241-246 AD) in fourth century.
Later this town came to be known as Bahmanabad (GOP Sanghar, 1998).
55
3.1.2 Population, Size, Growth and Distribution
Sanghar population consists of six talukas, is about 1453.03 thousands in
the year 1998 in comparison to 917.86 thousand in the year 1981 in comparison to 917.86
thousand in the year 1981. During the last 17 years the population increase to 58.31
percent (District Census Report Sanghar, 1998). In general the annual population growth
in 1998 has reduced from 3.44 percent to 2.74 percent (District Census Report Sanghar,
1998).
Due to population increase at 2.74 percent per year. It is likely to double in
the next 25 years. Table 3 describe the population increase since 1951 (District Census
Report Sanghar, 1998). The area occupies a total of 10,728 sq km with a population
density of 135.4 in 1998 (District Census Report Sanghar, 1998).
Table-3 Population and intercensal increase since 1951 in district Sanghar. Description 1951 1961 1972 1981 1998
Population in (Thousands) 319.07 427.84 689.76 917.86 1453.03 Intercensal increase (percent) - 34.09 61.22 33.07 58.31 Cumulative increase (percent) - 34.09 116.18 187.67 355.40 Average Annual Growth Rate (percent) - 3.00 4.18 3.44 2.74 Source: District Census Report of Sanghar Population Census Organization Statistics Div. Govt.
of Pakistan Islamabad October 1999.
Among the six talukas of the district, Shahdadpur taluka has the highest
share of 23.45 percent of the district population, followed by 22.52 percent Khipro
Taluka, 18.23 percent Sanghar Taluka, 15.87 percent, Tando Adam Taluka, 13.73 percent
Sinjhoro Taluka, and the lowest Share of 6.20 percent in Jam Nawaz Ali.
Area: The area of district is 10728 square kilometers, yielding a population density of
135.4 in 1998 which has increased from 86.0 in 1981 (GOP Sanghar, 1998).
56
3.2 Badin District Profile
According to Badin District Profile, 2006 the district had five talukas
which include Badin, Matli, Tando Bago, Golarchi and Talhar. It lies within 6.726 sq km.
with the transfer of power from central government to local government, the talukas(6)
were further subdivided to 49 Union councils, 109 Tapas and 511 Dehs. Badin has the
reputation of being the, headquaters of Indus Valley Civilization. Islam came into formal
existence in the year 711. In the early years of Sindh the area was control by the,
caliphate and later the royal family of Ghaznavids(7) took over. In the year 1592 the
Mughal emperors were in complete control of Sindh (GOP Badin, 2006).
3.2.1 Population Size, Growth and Distribution
In the year 1981-98 the annual growth rate declined from 2.95 percent to
2.6 percent during 1972-1981. On the other hand growth, went up from 2.26 to 2.71
percent in 1951-1961. In the next 31 years the district population is expected to double.
Table 4 describe population increase, this shows both the trend and annual increase since
1951 (GOP Badin, 1998).
6. Taluka: Administrative tier below the district
7. Ghaznavids: Royal family of gaznavids.
57
Table-4 Population and intercensal increase since 1951 in district Badin. Description 1951 1961 1972 1981 1998
Population (in thousands)
256.04 333.81 607.40 776.61 1136.04
Intercensal - - - - - Increase (percent) - 30.38 81.96 27.86 46.28 Cumulative - - - - - Increase (percent) - 30.38 137.23 203.32 343.70 Average - - - - - Growth rate (percent)
- 2.71 5.26 2.95 2.26
Source: District Badin Population www.badin.gov.pk
Available information revealed that, Badin taluka has the highest
population in comparision to Talhar taluka. Malti is the most crowded population at
247.8. This is followed by Tando Bago, and Badin taluka, which has 171.9 and 170.6
respectively (GOP Badin, 1998).
3.2.2 Area and Household Size
The total area covering the district is 6726 sq km with a population density
of 168.9 in 1998 (World Bank, 2005). The average household size in, Badin was 5.3 in
the year 1998. While in urban and rural areas it was 6.4 and 5.2 respectively (World
Bank, 2005).
3.3 Socio-economic Conditions in District Sanghar
The Census of 1951 reported the population of 319,000 in Sanghar
District, which increased to 1.453 million according to the 1998 census. Agriculture
employs 70% of the rural people, out of which 57% are self employed. Women are taken
as unpaid family helpers (56%). The farming is mostly at subsistence level except for the
58
bigger land holding. The large number of landless people work on these farms and are
mostly paid in cash. Cash income is less than Rs.400 per capita per month. Besides
subsistence earning, high dependency ratio is another reason for poverty. The major
sources of drinking water supply are hand pumps and pipe water. In the district only 17%
of the rural population has access to separate and 16% have access to shared latrines. The
separate kitchen facility is available to 21% of the households, while 26% households
used shared kitchens.
3.3.1 Water Availability in Sindh
Compared with its increasing needs, water availability to Sindh is being
reduced every year and the situation becomes worse during the drought period. Yearly
average water availability in the province computed from the data from year 1970 to
2002 is 45 MAF. This information helps us to predict the water security of Sindh.
According to water accord 1991 (table-5), Sindh has been awarded 48.7 MAF for both
Rabi and Kharif seasons. The worst ever drought conditions in Sindh experienced from
1998-2002, show that it received water much less than 45 MAF.
Table-5 Water apportionment under water accord.
Province Kharif Rabi Total
Punjab 37.07 18.87 55.94 Sindh 33.94 14.82 48.76 NWFP (a) Canals (b) Civil canals
3.48 1.80
2.30 1.20
5.78 3.00
Baluchistan 2.85 1.02 3.87 Total allocation 77.34 37.01 114.35 Source: Water Accord, Report 1991.
59
3.3.2 Current Water Shortage
Table 6 shows the current water shortage during the last three years.
Table-6 Water shortage in Sindh.
Year Kharif
Year Rabi
Accord allocation
Actual with
drawals
Shortages %
Accord allocation
Actual with
drawals
Shortages %
1999 33.94 32 6 1999-2000
14.82 12.82 17
2000 33.94 25.55 25 2000-2001
14.82 8.5 43
2001 33.94 24.47 28 2001-2002
14.82 6.84 54
Source: Sindh Development Forum, 2002.
The above data demonstrate the severity in water shortage affecting the
socioeconomic and environmental system in the province. Because of the water shortage
and water logging and salinity, farming situation is being deteriorated fast in the irrigated
agriculture areas, forcing rural people to migrate to the cities for livelihood.
3.3.3 Development Potential for Irrigated Agriculture in Arid Desert Areas Considering the issues of water shortage and increasing poverty in the area
as discussed earlier, the situation can be reversed and the area can be developed
economically. But there is need to devise long term development strategy.
3.3.3.1 Long Term Strategy
Availability of irrigation water at tail
Water management strategy
Water conservation plan
Shifting of cropping plan
Shifting of cropping pattern to low delta crops
60
Indigenous water use techniques
Land leveling
Construction of roads, wells, veterinary hospitals, installation of hand pumps
Protect grazing areas
Organise skill development programme for women.(SAFWCO, 2004)
3.4 Socio-economic Conditions in Badin District
Badin was formed as a separate district in 1975 and is considered as one of
the richest districts in terms of its natural resource base and one of the poorest in terms of
human development. According to the 1998 census, the population of Badin district was
1.136 million. On the basis of current growth rate of 2.26% per annum, it is estimated
that the current population of the district is about 1.328 million.
Extreme weather events and natural disasters have persistently plagued the
coastal areas of Sindh, especially the Badin district and adversely affected the district
over the last ten years. Preliminary reports prepared by UN Agencies (FAO and WFP)
suggest that the impact of these natural calamities has been severe for low income and
vulnerable groups and has resulted in a general disruption of livelihood, increased their
vulnerability and in some cases led out to migration. In addition to these natural disasters,
Badin has also suffered as a result of inequality in water distribution and lack of basic
social services and infrastructure. This has further aggregated the harsh living conditions
and extreme poverty in the district (World Bank, 2005).
61
3.4.1 Overview of the Farming Sector
The economy of Sindh is relatively industrialized, with agriculture
contributing 23 percent of the provincial GDP. Due to the prevalence of traditional
systems of irrigation, the cultivable land has degraded to a varying degree causing a
serious threat to food security and incomes of the farming community particularly of
small landowners and tenants.
The situation is even worse in Badin as a result of the degradation of the
natural resource base. Agricultural production has suffered as a result of reduced water
flows in the Indus. According to WAPDA(8), during 2000-2001, the total water released
was 0.72 MAF and in 2001-2002 it was 1.92 MAF. This flow was for a short period in
the kharif season and there was no flow in the rabi season. A comparison of the area
under crop between 1998 and 2002 in Badin district shows that the cultivation of rice,
sugarcane and wheat has gone down while the area under cotton has increased.
3.4.2 Overview of the Fishing Sector
Overall fisheries sector provides employment to about 300,000 fishermen
directly and another 400,000 people are employed in ancillary industries. Out of the
annual fish export of Pakistan worth US$100 million, about 10% originate from Badin
coast.
Additional threats to the inland fisheries come from pollution of lakes and
change in the system of regulating of inland fishing. The Indus delta creeks and dhands
receive agricultural affluent containing pesticides from drains and are affected due to the
8. WAPDA: Water and Power Development Authority
62
intrusion of sea water and lack of fresh water flow, thus threatening the fish production in
Badin distrct.
3.4.3 Vulnerability of Livelihoods
Badin district has experienced four natural disasters in the last five years
namely a cyclone in 1999, drought in 2000, earthquake in 2001 and drought and floods in
July 2003. Similar natural disasters have occurred in the past with varying impacts on
livelihood. The drainage infrastructure in central Sindh has lowered and controlled the
ground water level in Nawabshah, Sanghar and Mirpurkhas districts and disposes saline
effluents into the fresh water lakes and coastal areas as it passes through Badin.
In Badin district, the run off from the prolonged and high intensity rainfall
in 2003, together with the high velocity canal flows that breached Sani Guni Canal,
Phulley Canal, Nasir Canal and other distributaries flooded in lower Badin. To make
matters worse a flow of sea water from the opposite direction prevented the flood water
from draining into the sea. Thus the flood water mixed with the sea water accumulated
and formed a pool in the thickly accumulated talukas of Badin and SF Rahu, Golarchi,
Tando Bagho, Matli and Talhar (World Bank, 2005).
63
Table-7 Extent of damage caused by floods in 2003.
Description
Badin
Area square KM 17,475 Population 1.136 million Affected population 366,000 Number of talukas 5 Affected talukas 3 Persons killed 86 Animals perished 5,462 Cropped area affected (acres) 226,000 Houses fully damaged 56,000 Houses partially damaged 135,850 Source: UN Assessment Report, 2003. 3.4.4 On Going Development Initiatives
The government has undertaken measures to address the problems of
people affected by disasters as well as repairing the damages to infrastructure affected by
floods, cyclone and earthquake. In response to the drought of the last few years, the
government has provided funds for relief operations, waived land taxes, postponed the
recovery of loans, provided subsidized wheat, mobilized medical and veterinary team to
the affected areas.
Many donors responded quickly and provided relief measures when
disasters occurred (World Bank, 2005).
3.4.5 Study Areas
3.4.6 Map of Sindh
Map of Sindh showing the location of study areas. Sanghar district is
cotton / wheat / fodder zone, while Badin district is sugarcane, rice, vegetables, oilseeds
zone
64
Figure 1 Map of Sindh
3.5 Data Collection Method A total sample of 320 households was selected from two districts. The
sample size is appropriate at 6% error rate, 5% level of significance, and proportion of
0.5 which gives maximum variance of 0.25 [0.5*(1-0.5)=.25]when population is very
large enumerated from 3000 thousand to millions (Wunsch, 1986). Sampling plan is
depicted in Table 1. Multistage sampling plan was used to select households. Cluster
sampling has two important advantages over Simple Random Sampling and Stratified
Sampling. Firstly, it is economical and secondly it is suitable for selecting a sample
when the sampling frame of individual elements is not available. Cluster Sampling only
needs a list of elements in the clusters sampled (Anderson et al., 1993).
65
In the fist stage, one Taluka was selected from each district; in the second
stage, 2 union councils were selected from each taluka; in third stage, 10 villages were
selected from each union council; and in fourth stage, 8 households were selected from
each village. Thus, a sample of 160 households were selected from each district.
To have a representative sample of the rural area for poverty estimation
and its predictors, it is decided to collect data on households of following major
occupational groups, namely landowners, tenants, wage labourer, artisan, and
businessman. An equal sample size of 64 households was selected from each occupation
group, disproportion to population size since exact population size of each occupational
group cannot be enumerated through available documentation and resources.
Table-8 Multistage sampling for selection of households. District Stages Total
First Second Third Fourth
Talukas Selected Taluka
UCs /Taluka
Villages /UC
Households / village
Badin 1. Badin 2. Matli 3. Talhar 4. Shaheed Fazil
Rahoo (Golarchi) 5. Tando Bago
Badin 2 10 8 160
Sanghar 1. Sanghar 2. Jam Nawaz
Ali 3. Khipro 4. Shahdadpur 5. Sinjhoro
Tando Adam
Shahdad pur
2 10 8 160
Total 320
66
A well structured questionnaire was developed and used to collect
information of households. Efforts will be made to collect information on, personal
profile of household head, family structure, house and living status, dependency ratio,
number of earners, sources of income, access to facilities etc. Checklists will be
developed often intensive review of literature and in consultation of the supervisory
committee and researchers to conduct interviews with officials of district govt in both
Sanghar and Badin district as well as VDOs, NGOs and micro credit agencies actively
working the study area.
3.6 Multistage Sampling for Selection of Household
(a) Sanghar
Table 9 shows that Sanghar district has a population of 1.3 million
according to 1998 census. Taluka Shahdadpur was selected. Two union council from
Shahdadpur were selected Barhoon has a population of 31,288 while Lundo has a
population of 27,821. Thus 85 sample size was selected Barhoon UC and 75 sample size
was selected in respect of Lundo UC.
(b) Badin
Similarly Badin district has a population of 1.2 million. Taluka Badin was
selected. Bughra Memon UC selected from taluka Badin with a population of 32,089 and
Seerani has a population of 29,674. Thus 83 sample size was selected for Bughra
Memon. Similarly 77% sample size was selected in respect of Seerani UC. About 160
sample size was selected for each district. The total sample size for the two district was
320.
67
Table-9 Samples Selection from union councils.
Districts Selected Taluka
UCs Population Proportion Sample
Sanghar (1.3 million) Census 1998
Shahdpur Barhoon 31,2,88 53% 85 Lundo 27,821 47% 75 Total 59,109 100% 160
Badin (1.2 million) Census 1998
Badin Bughra Memon 32,089 52% 83 Sirani 29,674 48% 77 Total 61,763 100% 160
Total 320
3.7 General Measures of Poverty
Extent of poverty and income inequality will be calculated from the data
collected from the two districts. Head count index, the poverty gap, Sen index will be
calculated to measure the extent of poverty while Lorenz curve will be developed and
Gini coefficient will be estimated for income inequalities in the study area. A brief on
each measure is given as under:
3.7.1 Head Count Index
Absolute poverty may be measured by the number of head count (h) of
those whose income fall below the absolute poverty line when the head count is taken as
a fraction of the total population (n). The head count index may be defined as;
n
hHCI
Where HCI = Head count index h = Number of poor n = Population
68
3.7.2 The Poverty Gap
The measures of the total amount of income necessary to raise everyone
whose income is below the poverty line. The total income short fall or total poverty gap
(TPG) of the poor is defined as:
H
iip yyTPG
1
)(
Where TPG = Total poverty gap H = No of the poor who fall below poverty line yp = Poverty line yi = Income of the poor 3.7.3 The Sen Index
Sen (1976) suggested that along with measuring head counts of persons in
poverty a more comprehensive measure of poverty should incorporate the average level
of income of those persons and how far this level is below the poverty threshold. In other
words Sen index will measure the poverty gap of the poor, it is defined as follows:
1
11q
qGpiHS
Where H = Head count ratio i = Ratio of the average income of the poor Gp = Gini coefficient of income among the poor q = Number of people below the poverty line 3.7.4 Inequality Indices
Inequality can be measured by using Lorenz Curve and Gini Coefficient.
Lorenz Curve is defined as a graph depicting the variance of the size
distribution of income from perfect equality. Gini coefficient is defined as an aggregate
69
numerical measure of income inequality ranging from zero (perfect equality) to one
(perfect inequality).
It is graphically measured by dividing the area between the perfect
equality line and Lorenz Curve. The higher the value of the coefficient, the higher the
inequality of income distribution and the lower it is the more equitable distribution of
income.
3.8 Determinants of Poverty To analyze the determinants and identify the correlates of poverty in
Sindh, logistic regression was be applied to primary data. Logistic regression analysis
allows one to predict probability of a binary dependent variable from a set of independent
variables that may be continuous, discrete, or a mix of them. Logistics regression method
is a powerful technique because it is relatively free of restrictions and it allows analyzing
a mix of all types of predictors.
The logistics regression model can be written as follows:
z
z
e
eyob
1)1(Pr
70
Where y = Binary dependent variable (y = 1 if event occurs, y = o otherwise) e = The base of natural logarithms and Z = β0 + β1+ β2 X1 + β3 X2 + …………….. + βp X p With constant β0 coefficient, βj are predictors for p predictors (j = 1,2,3……p)
Parameters of the model are estimated using maximum likelihood method
the estimates of coefficients are the values that maximize the probability of drawing the
sample actually obtained. Backward stepwise elimination method was applied to select
significant factors. Backward elimination starts with all of the variables in the model.
Then, at each step, variables are evaluated for entry and removal. The score static is
always used for determining whether variables should be added to the model. Just as in
forward selection, the Wald statistic, the likelihood ratio statistic, or the conditional
statistic was used to select for removal.
3.9 Testing Hypothesis about Coefficients
Solving for logistic regression coefficients 0 and j and their standard
errors involves calculus, in which values are found using maximum likelihood methods.
These values, in turn, are used to evaluate the fit of one or more models. If an acceptable
model is found, the statistical significance of each of the coefficients is evaluated using
the Wald test. For large sample sizes, the test that a coefficient is 0 can be based on the
Wald Statistic, which has chi-square distribution. When a variable has a single degree of
freedom, the Wald Statistic is just the square of the ratio of the coefficient to its standard
error. For categorical variables, the Wald Statistic has degree of freedom equal to one
less than the number of categories. The Wald Statistic can be obtained by dividing the
coefficient by its standard error and can be written as,
71
j
E.SW j
j
, (where j=1,2,3,........,p)
“Unfortunately, the Wald statistic has a very undesirable property. When
the absolute value of regression coefficient becomes large, the estimated standard error is
too large. This produces a Wald Statistics that is too small, leading the analyst to fail to
reject the null hypothesis that the coefficient is 0, when infact the analyst should have
done it. Therefore, whenever the coefficient is large, analyst should not rely on the Wald
statistic for hypothesis testing. Instead, the analyst should build a model with and without
that variable and base the hypothesis test on the change in the log-likelihood” (Hauck and
Donner, 1977).
3.10 Partial Correlation
As is the case with multiple regression, the contribution of individual
variable in logistic regression is difficult to determine. The contribution of each variable
depends on the other variables in the model. This is a problem, particularly when
independent variables are highly correlated.
A statistic that is used to look at the partial correlation between the
dependent and each of the independent variables is the R statistic “(Atkitson, 1980). R
can range in value from -1 to +1. A positive value indicates that as the variable increases
in value, so does the likelihood of the event occurring. If R is negative, the opposite is
true. Small values for R indicate that the variable has a small contribution to the model.
72
The R statistic can be defined as,
)O(LL
2K - StatisticWaldR
2
Where K is the degrees of freedom for the variable (Atkinson, 1980). The
denominator is -2 times the log-likelihood of a base model that contains only the
intercept, or a model with no variable if there is no intercept. The sign of the
corresponding coefficient is attached to R. The value of 2K in equation 3.2 is an
adjustment for the number of parameters estimated. If the Wald statistic is less than 2K,
R is set to 0.
3.11 Interpretation of Coefficients Using Odds
In logistic regression, stated earlier that the parameters of the model are
estimated by using the maximum likelihood method. That is, the coefficients that make
our observed results most “likely” are selected. Since the logistic regression model is
non-linear, an algorithm is necessary for parameter estimation (Atkitson, 1980). In
multiple linear regression, the interpretation of the regression coefficient is straight
forward. It tells the amount of change in the dependent variable for a one-unit change in
the independent variable.
To understand the interpretation of the logistic coefficients, consider a
rearrangement of the equation of the logistic model, i.e.,
Z
Z
ie
eY
1
73
Where PP X.......XXZ 22110
The logistic regression model can be written in terms of the odds of an
event occurring. The odds of an event occurring are defined as the ratio of the probability
that it will occur to the probability that it will not. For example, the odds of getting a
head on single flip of a coin are 0.5/0.5= 1. Similarly, the odds of getting a diamond on a
single draw from a card deck are 0.25/ 0.75= 1/ 3. So, it is obvious that odds simple mean
the probability.
The logistic model in terms of log of the odds, which is called a lo
or PP
i
i X.......XXY-1
Ylog
22110
That is, the linear regression equation is the (natural log of) probability of
being in one group divided by the probability of being in the other group. Above
equation reveals that the logistic coefficients can be interpreted as the change in the log
odds associated with a one-unit change in the independent variable.
Since it is easier to think of odds rather than log odds, the logistic
regression equation can be written in terms of odds as
e.......eee eY-1
YPPPP XXXX.......XX
i
i 2211022110
The raised to the power i is the factor by which the odds change when
the ith independent variable increases by one unit. If i is positive, this factor will be
74
greater than 1, which means that the odds are increased, if i is negative, the factor will
be less than 1, which means that the odds are decreased. When i is 0, the factor equals
1, which leaves the odds unchanged. The odds ratio is the increase (or decrease if the
ratio is less than one) in odds of being in one outcome category when the value of the
predictor increases by one unit.
For example, the estimated probability of event occurring is 0.37, while
keeping one of the independent variables (i.e., p) at 0 and other variables constant. The
probability of non-event becomes 0.63 (i.e., 1-0.37). The odds of event occurring are then
estimated as:
0.53- are odds log and 59.037.01
37.0
)Pr(
)Pr(
eventnon
eventOdds
Following the same procedure as before, but using a value of 1, instead of
0, for the same independent variable (p), while keeping other variables constant, the
estimated probability of event occurring is 0.554. Similarly, the estimated odds are 1.24,
and the log odds are 0.22.
By increasing the value of IV (p) by one unit, the log odds are increased
by about 0.75, which is the value of the coefficient for IV (p). Similarly, the odds
changed from 0.59 to 1.24. The ratio of the odds of event occurring when IV (p) is 1 to
the same odds when IV (p) is 0 is about 2.1. This ratio is called the odds ratio. The odds
ratio for a variable tells the change in odds for a case when the value of that variable
75
increased by 1. The coefficients, i are natural logs of the odds ratio; odds ratio = e .
For example, the odds ratio = 7614.0e = 2.1413, where 7614.0 . The odds ratio is
represented by )(Exp will be shown in the proceeding chapter.
The confidence interval for the odds ratio is based on the confidence
interval for the corresponding logistic regression coefficient; the confidence interval for
the odds ratio will include 1 whenever the confidence interval for the regression
coefficient contains 0. To calculate the 95% confidence interval for the odds ratio, first
calculate the 95% confidence interval for the regression coefficients by using,
)E.S(96.1%95
For example, the lower and upper limits are –0.75 and 2.27, respectively,
where 7614.0 and S.E = 0.7708. Likewise, the 95% confidence interval for odds ratio
becomes e-0.75 = 0.47 and e2.27 = 9.7. This confidence interval tells that the values
anywhere from 0.47 to 9.7 are plausible for the population value of the odds ratio for the
variable.
When an independent variable is continuous, such as age, blood pressure,
or years of education, the odds ratio for a unit change in the value of the independent
variable may be less informative than the odds ratio associated with a decade change in
age, or a 5mm change in blood pressure.
3.12 Assessing the Goodness of Fit of the Model
Whenever a model is fitted to the data, the main objective is to know how
well the model fits not only the sample of data from which it is derived, but also the
76
population from which the sample data were selected. A model always fits the sample
that is used to estimate it better than it will fit the population. There are numerous
models in logistic regression i.e., a constant (intercept) only model that includes no
predictor, an incomplete model that includes the constant plus some predictors, a full
model that includes the constant plus all the predictors (including, possibly, interactions
and variables raised to a power), and a perfect (hypothetical) model that would provide
exact fit of expected frequencies to observed frequencies if only the right set of predictors
were measured. For large data sets, it may be feasible to split the data into two parts. A
model can be estimated on one part and then applied to the other to see how well it fits.
3.13 Methodology for Data Collection and Analysis for Village Development
Organization’s VDOs 3.13.1 Population The target population for this study consists of village development
organization’s workers and farmers in district Sanghar / Badin.
3.13.2 Sample Selection There are 50 VDOs working in each (Sanghar and Badin) district for
poverty alleviation. However due to the limitation of time and financial status of the
researcher only 10 village development organizations were selected from each district.
3.13.3 Analysis of Data
Statistical Package for Social Sciences (SPSS version 16) was used to
analyze the data. The data gathered through survey were analyzed using frequency
distribution and corresponding percentages.
77
3.14 Conclusions
This chapter present the methodology of the study how the research is
going to be carried out. A total sample of 320 households were selected from two district.
Multistage sampling was used to select households thus a sample of 160 was selected
from Sanghar and Badin. Various techniques were used for analyzing primary data
collected from households survey such as headcount index, poverty gap and sen index
formulas for measuring poverty. Gini coefficient and Lorenz curve was used for
measuring inequality in the study area. Logistics regression and multiple linear regression
models were used for analyzing determinants and identifying the correlates. To assess the
various initiatives taken by village development organization to alleviate poverty data
was collected from 10 villages in both Sanghar and Badin SPSS version 16 was used to
analyse the data.
78
CHAPTER-IV
STATUS AND TREND ANALYSIS OF RURAL POVERTY IN SINDH AND PAKISTAN
4.1 The Status and Pattern of Rural Poverty
The pattern of poverty in Pakistan is complex varying between the
agricultural and non farm sectors between ethnic tribal groups and between provinces and
within provinces, the costal areas of Sindh is significantly more impoverished than the
rest of that province. Factors effecting poverty include traditional practices and behavior
(especially towards women) tribal rivalries and divisions, cross-border conflicts language
differences and the persistence of a feudal landholding system related in part to
inheritance practice that progressively reduce the size of cultivable plots. The agricultural
sector is the largest employer in rural areas. However unfavorable labor land ratio limits
income earning opportunities as the population increases and landholding become so
small that they become uneconomical. In consequence the proportion of persons
employed in agriculture has declined from 68 percent in the early 80s to around 60
percent today. The rural non farm sector is dominated by informal activities that most
absorb a large majority of unskilled, uneducated and poor individuals who have sold their
land.
The very poorest households depend more on unskilled labor income,
while self generated or self employed income is the most important source of income of
the households in higher income groups. As a consequence, the labor pool available for
employment by commercial enterprises of the farm is rather poor quality in terms of its
compositions and skills. Coastal Sindh, it will be seen have poor reputation for its skill
79
base. Looking across the spectrum of poverty majority of the poor wage employees are
found in the construction sector followed by service sector. Again it will be seen that this
pattern is not common to coastal Sindh where the majority of people work as wage
laborers either in fishing or agriculture.
Unemployment alone fails to present the true picture of the rural labor
market. A very large segment of the labor force is characterized by underemployment.
This phenomenon is most common in the agriculture and informal sectors. In Badin men
work about 15 days in a month and rest at home for the remaining 15 days. While at
home they usually rest and do not contribute in household chores. They play music, chew
pan and visit the market where they take tea and other activities.
According to the report prepared by Sindh Coastal Development Authority
female underemployment has been persistently four times as high as that of male under
employment. Most female work as unpaid family help. Out of the total of working
women, only one percent belonged to professional category and one percent worked as
administrative and managerial workers.Majority of them worked in agricultural (54%)
craft related work (11%) or in elementary occupation (27%). Among Farm household,
one third of households are livestock holders. However 64 percent of the livestock
holders are self employed or obliged to work in the non-farm unskilled labor market
(Sindh Coastal and Community Dev Project 2005).
80
Table-10 Source of non-farm income % distribution of reporting households
Source of Non Farm Income
Farm Households Non-Agric Households
Livestock Holders
Services 11.9 22.7 8.0 Business 7.1 19.5 8.4 Livestock 3.0 0.3 9.4 Remittances 2.9 1.7 1.3 Agric Labor 21.6 4.9 14.9 Non Agric Labor 18.5 42.5 46.8 Rent 1.6 0.7 0.9 Poultry 0.2 0.2 0.4 Others 6.6 7.5 9.9 None 26.5 0.0 0.0 Source: Agricultural Census of Pakistan (2000). Table-10 shows that the distribution of economic activity for farm
households is more even than for non-farm households. This result correlates with the
incidence of poverty in non-farm households. More than 40 percent of persons from non
farm households are compelled to be laborers or low skilled service workers. Less than
20 percent work in some form of business.
A high incidence of poverty is found among non-farm households
compared to farm households. The average annual income of farm households is 1.7
times higher than those of non-farm households. According to some survey data poverty
is concentrated in those areas growing the major commodity crops (wheat, cotton and
rice). The cotton and wheat growing areas of Sindh have the highest incidence of poverty
but also have the highest farm based poverty indicator suggesting that low commodity
prices and the structure of agricultural marketing for the major crops have a serious
impact on poverty (Agricultural Census of Pakistan 2000).
81
Table-11 Farm and non-farm poverty by agro climatic zones 000 persons
Agro climatic zones
1993-94 1998-99 2001-02 Farm Non
farm Farm Non
farm Farm Non
farm Rice / wheat Punjab 21.6 39.9 22.3 33.1 24.9 40.4
Cotton / wheat Punjab 19.9 31.4 35.2 44.7 42.1 55.6
Cotton / wheat Sindh 33.4 34.2 20.4 32.2 59.3 57.7
Rice / Others Sindh 25.7 27.1 19.5 14.6 60.8 53.0
NWFP 23.0 32.3 31.7 31.1 45.7 47.6
Baluchistan 33.0 21.1 31.3 26.7 40.4 39.4
Source: Malik 2005 Sindh Coastal Development Authority. Table-11 shows that cotton / wheat in Sindh recorded the highest of farm
poverty 59.3 and also in respect of rice / others farm poverty has 60.8 making it the
highest farm poverty in rural Sindh.
4.2 Community and Poverty Issues
The area may be divided into and within the command areas of irrigation
system below the Kotri Barrage and those areas outsides it. Within the commands areas a
so called water course community exists which comprises a group of landholders that
divert the entire stream allocated to their block of land from the canal turn wise have
learnt to follow a distribution all shareholders can rely and do not have to negotiate or
struggle to get water from each other at each turn. Besides organizing to bring reliability
to their every day farming operations these individual water users on one channel unite to
find ways to maintain a reliable supply of water through their outlet in the canal.
Towards the coast and as the availability of sweet water decreases in the
face of encroachment by the sea, there are communities of fisher folk some of whom may
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be termed coastal and others who are termed island dwellers. These communities are
comprised of fisher folk with little subsistence farming, especially animal husbandry
(camel, cows and goats). They mainly live on coast and Indus delta on a small island or
creeks. Fishing is the only and major means of livelihood adopted by these communities
do not sell fish directly in the market but sell it to a saith near contracts point in the
village (Sindh Coastal and Community Dev Project 2005).
4.3 Structural and Non Structural Vulnerabilities
Villages that are structured in close proximity of Arabian sea are most
frequently subject to periodical disasters. The structured and placement of houses non
availability of disasters resistance physical infrastructures and remoteness come into
alliance to constitute the physical vulnerability of the community at large.
The villages situated at the tail end of the incursion of the sea (Salinization
of their productive land) and loss of sweet water. Land under cultivation have become
saline and degraded due to successive floods and sea erosion further a huge irrigation and
and drainage infrastructure (LBOD and RBOD) have added to vulnerabilities of the area
and communities living therein (eg floods occurred because of the sudden breach of
LBOD which caused huge losses).
Non structural vulnerabilities relate to the way that how ownership of
resources is distributed among communities and how the available resources are used to
cope with any trend, shock and seasonality. The absence of rights ( eg to land), lack of
access to other productive resources and non availability of formal portative resources
and non availability of formal protection and safety nets reduce the social resilience and
coping capacity of communities against vulnerabilities in the both districts of Thatta and
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Badin. It leaves them to opt for a repressive loaning system and in some cases restoring
to begging as survival strategy. In this context communities of the area are largely
depending upon poor and fragile resource base with no control over and entitlements of
ritual resources like arable land, human rights and small scale entrepreneurship. These
non structural dimension of vulnerability in production depends on improving the
efficiency of the existing irrigation system.
Notably, given the limited scope for major increases in water supply in
and outside the Indus basin, improvement of efficiency of currently available water use
remains the only viable option for increasing productivity of irrigated agriculture in the
area in a sustainable way (World Bank, 2005).
4.4 The Need to Improve the Well Being of the Poor
One of the less anticipated problems encountered was the inability of the
more vulnerable communities to provide for a fund capital and development needs. In
part this was due to the precarious hand to mouth existence that the more vulnerable
communities endure. The absence of seed capital or surplus earnings within the
communities means that they are excluded from various development opportunities such
as the microfinance scheme. In essence the community was not able to take the first few
steps towards helping itself. This means that those communities never reach a point of
critical mass sufficient to help themselves on the road towards economic and social self
sufficiency.
And when there are funding programs they rarely reach much below the
level of district governments or occasionally the taluka and union council level of these a
large number appear to be thwarted by institutional ineptness or indifference or
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accompanied by excessively complicated procedures. Further more most programs have
an affinity for public sector involvement which is not always the best way of ensuring
effective or need based delivery.
The Badin coastal area need some form of protection from periodic
cyclones and massive inundations from floods or storm surges. Other priorities were
sweet water, health support small links roads, basic sanitation, support for crops and
livestock and education because its benefits in their current environment are difficult to
comprehend.
These are fragile communities. In looking for an entry point or to engage
with these communities it is evident that first and foremost the communities need to be
energized by seeing something worth while and tangible. Such an inducement quickly
shows that despair is not necessarily a difficult state. But large organizations such as bank
and public sector are not very good at the subtle move needed to orchestrate such small
scale initiatives. They can deal with large programs and policy issues but actual on
ground, micro size interventions are simply beyond them.
Some how large sums needed to be diffused into a series of smaller
targeted interventions; to improve the well being of the poor in rural areas of Sindh
The above analysis on the status of poverty situation in rural Sindh reveals
that the poverty situation remain as it is as all the outstanding issues have not been
resolve. The problems of inadequate supply and poor maintenance of rural intrastate,
including rural roads, electrifications, water supply and its sustainability have also not
been helpful in the effort to adequately reduce poverty. discontinuity of projects and
programmes of rural developments has continued to be a major problem, housing is very
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costly to acquire in view of exorbitant cost of building materials which the poor can
hardly afford, thus accentuate the housing problems facing the rural poor in Sindh.
Some of the present social sector policies remain generally unsuitable for
addressing the problems of poverty, for instance while education absorbs relatively
medium proportion of federal Government budget over the, years the allocation pattern
indicates that greater emphasis in higher education whereas primary and adult education
seems to be most needed by the poor. Similarly some policy designed to address
problems in the health sector appear inadequate unstable and not targeted to the poor.
It is notable from the above discussion that rural Sindh now faces
enormous development challenges that are key to both welfare improvement for the
general population and to poverty reduction in particular. Given the state magnitude and
dynamics of poverty in the province it is imperative that government makes a firm
commitment to resolve poverty issues in rural areas. To address these challenges,
pursuance of rapid growth must be evolved as an integral part of poverty reduction
programme. Participation in the growth process by the poorest communities is the surest
way of ensuring poverty reduction.
Therefore local community participation in the planning, implementation
process of development programmes should be widened and deepened. (World Bank,
2005)
4.5 Trend Analysis of Poverty in Sindh Province
Sindh is a resource rich province and it handles 90 percent of international
trade. The large scale manufacturing sector accounts for 25 percent of the GDP. Despite
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all these achievements, the incidence of poverty in rural areas of Sindh is among the
highest in Pakistan.
The poor in Sindh can be categorized into five groups, each with its own
attendant and unique problems. The rural poor overall are cut off from access to essential
public services and reasonable means to generate sustainable incomes and are tied to
traditional customs and mode of production and livelihoods. Within this group is a sub
group of ultra poor, who lives in the southern districts and have been a repeated victims
of natural calamities such as drought, followed by excessive rainfall, flooding, cyclone
earthquake of sea intrusion due to increasing soil salinity. This group of the very
vulnerable represents the special requirements of Sindh province in terms of poverty
reduction. In view of the foregoing therefore we shall present the trend analysis of
poverty in Sindh province.
4.6 Poverty Ranking of Coastal Districts
Communities in the coastal districts of Sindh, specially Thatta and Badin
are very poor and deprived of the opportunities of socio-economic development. The
SPDC (1998) deprivation ranking presented below places, Badin and Thatta, at 14 and 15
rank among 16 districts of Sindh. Only Tharparkar district being more backward than
these two coastal districts (Table-12).
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Table-12 Deprivation Ranking of various Districts in Sindh Province. Districts Provincial rank order
1 = least deprived 16 = most deprived
National rank order 1 = least deprived 100 = most deprived
Deprivation scale (1-100)
Low deprivation Karachi 1 1 1.0 Hyderabad 2 12 56.3 Medium deprivation Sukkur 3 21 65.7 Larkana 4 27 69.7 N.Feroze 5 28 70.4 Nawabshah 6 29 74.7 Khairpur 7 38 75.8 Dadu 8 39 76.3 High deprivation Shikarpur 9 44 77.9 Sanghar 10 47 78.8 Mirpurkhas 11 52 81.0 Ghotki 12 59 84.8 Jacobabad 13 63 85.7 Badin 14 76 92.4 Thatta 15 78 94.7 Tharparkar 16 84 100.00 Source: SPDC 2001 Estimates Based on Population and Housing Census 1998.
Besides the poverty of opportunity, the income poverty is also quite
visible from the following data on rural wage rates and income generation structures.
Routine rate of agricultural labour are as follows:
Harvesting of sugarcane = Rs. 3 per 40 kg
Picking of chillies Rs.40 per 40 kg
Wheat / Rice harvesting1/12 share of total harvested crop
Tomatoes Rs. 2 per 12 kg (one basket of 12 kg)
The daily wage of beeri labour is Rs.100 per 1000 beeris. A labourer
makes an average of 700 to 1000 beeri in a day. The daily wage of woodcutters is Rs.10
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per 40 kg. He pays Rs.2 to the oxen cart owner, as fare and saves only Rs.8 per 40 kgs. A
man sells about 7 to 10 maund (1 maund = 40 kgs) per day. The daily wages of the
construction labourer is 80 to 100 rupees, but they do not get to do this job on a daily
basis. The daily wages of the hawker is Rs.50-100.
A goat worth Rs 1500 sold at the rate of Rs 500 in the time of disaster.
Milk man buys milk from the villages at the rate of 10 to 12 liter kg and sells in the
market Rs. 15-20 per kg (SPDC, 2007).
4.7 Distribution of Poverty by Assets In Sindh, there are large concentrations of lower income population in
Katchiabadis, where defector ownership prevails. The above analysis identifies possible
intervention areas that can impact poverty reduction, while inter-provincial variation
highlights the need for a somewhat provincially differentiated approach to poverty
reduction (Table-13).
Table-13 Distribution of Poverty by Asset Sindh. Land / poverty Sindh Pakistan
Rural areas Land ownership 20.97 17.90 No land ownership 4.26 31.82 Urban areas Property ownership 8.72 16.97 No property ownership 20.15 28.14 Housing Rural areas House ownership 38.46 28.97 No house ownership 32.68 36.54 Urban areas House ownership 22.11 28.16 No house ownership 13.31 25.76 Source: SPDC estimates based on PIHS – HIES 2001-02.
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4.8 Distribution by Sector and Occupation The examination of the prevalence of poverty by sector shows that as
expected a relatively higher incidence of poverty exists in agriculture. Poverty incidence
among share croppers is significantly high in Sindh (60 percent). It was also observed
that 25 percent cultivators in Sindh are living below the poverty line. The prevalence of
poverty among the self employed may be explained by the dominance of the informal
sector hawkers, tea stall operators, petty traders and so forth. Poverty among the self
employed in Sindh is relatively lower than 27%. This is on the account of higher earnings
/ wages in Karachi (Table-14) (SPDC, 2007).
Table-14 Distribution of Poverty by Sector Occupation.
Sector Sindh Pakistan
Service 24.37 28.08 Mining and manufacturing 22.59 28.84 Agriculture 43.06 32.99 Occupation category agriculture Own cultivator 24.45 18.83 Livestock tenderer 42.15 34.18 Contract cultivator 19.96 36.80 Share cropper Occupation category non agriculture
Employer 18.12 18.19 Self employed 25.44 30.42 Wage employed 26.66 30.51 Source: SPDC Estimates based on PIHS – HIES 2001-02. 4.9 The Poverty Profile in Pakistan Poverty measures for Pakistan are based on the household income and
expenditure surveys (HIES). Poverty in Pakistan has followed cyclical trend in the last
four decades. Poverty increased in the 1960s, but declined in the 1970s and 1980s. But,
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the trend reversed in the 1990s, lately poverty has shown an unprecedented decline in
short period of four years (from 2002-2006). The government of Pakistan has claimed
that poverty has been reduced from 34.46 percent in 2001 to 23.90 percent in 2005
(CRPRID, 2006).
Table-15 gives the estimates of poverty from 1992 to 2005. It shows that
at present more than one third of population of Pakistan is living below the national
poverty line(9). Poverty has mostly depicted an increasing trend between 1992 and 2001.
It increased from 25.46 in 1992 to 34.46 in 2001. The depth of poverty as measured by
poverty gap also increased from 4.27 percent in 1992 to 7.03 percent in 2001; whereas
the severity of poverty has almost doubled in the same period. The recent figures for
2004-05 show that poverty has declined from 34.46 to 23.9 percent (GOP, 2005-06).
Table-15 Trends in incidence of poverty in Pakistan 1992-2005.
1992-93 1993-94 1996-97 1998-99 2000-01 2004-05 Head count ratio Pakistan 25.46 28.17 25.78 31.08 34.46 23.9 Rural 27.63 33.54 30.17 35.13 39.26 28.1 Urban 19.99 15.39 15.84 21.37 22.69 14.9 Poverty gap Pakistan 4.27 5.22 4.38 6.58 7.03 4.76 Rural 4.6 6.25 5.25 7.55 8.04 5.64 Urban 3.43 2.74 2.41 4.27 4.55 2.87 Severity Pakistan 1.1 1.44 1.14 2.06 2.13 1.48 Rural 1.18 1.76 1.39 2.38 2.44 1.77 Urban 0.89 0.69 0.6 1.29 1.35 0.84 Source: CRPRID centre for research on poverty reduction Islamabad 2005, GOP 2005, 2006.
9. NPL: National Poverty Line is the determine by the national planning commission based on the economic situation prevailing at a certain period of time.
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4.10 Trends of Poverty Estimates in Pakistan 1998-99, 2001-02 and 2004-05. Estimates of poverty in Pakistan vary considerably depending on
methodology used, because a high percentage of rural households have per capita
expenditures close to the official poverty line (appendix-8) it shows that 10.9 percent of
rural households in 2001-02 had per capita expenditures within ±/-5 percentage of the
official poverty line in 2004-05, 8.95 percent of rural household were within ±/-5 percent
of the planning commission official poverty line of Rs.878.60. Thus, small changes in
calculated real income expenditure, whether due to actual changes in expenditure, price
deflators or other methodological factors related to updating a poverty line can lead to
misleadingly large variations in poverty estimates.
The national poverty line has mostly depicted an increasing trend between
1992 and 2001. It increased from 25.46 in 1992 to 34,46 in 2001. The depth of poverty as
measured by poverty gap from 4.27 percent in 1992 to 7.03 percent in 2001; whereas, the
severity of poverty has almost doubled in the same period. The recent figures for 2004-
2005 show that poverty has reduced from 34.46 to 23.9 percent. (GOP, 2005-06)
4.11 Trends in the Gini Coefficient In the 1970s there was an inverse relationship between poverty and
income distribution (Table-16), with the latter improving and the former worsening. Both
the 1989s and the 1990s, poverty and income distribution moving in the same direction
with poverty falling in the 1980s and income distribution improving. The decades of the
1990s had a positive trends, currently income distribution based on Gini coefficient is
worse than what it was in the early 1990s. Not only that but the concern ratio of income
has also worsened in recent years with the share of the income of the highest twenty
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percent increasing over time with that of the lowest twenty percent falling (Mahbubul
Haq, 2005).
Table-16 Trends in the Gini Coefficient. Year Total Rural Urban
1963-64 0.355 0.348 0.368 1966-67 0.351 0.314 0.388 1969-69 0.328 0.293 0.370 1969-70 0.330 0.295 0.361 1970-71 0.326 0.273 0.359 1971-72 0.344 0.309 0.381
1979 0.375 0.319 0.380 1984-85 0.428 0.345 0.379 1985-86 0.355 0.330 0.354 1986-87 0.346 0.312 0.357 1987-88 0.348 0.307 0.366 1990-91 0.407 0.410 0.390 1992-93 0.390 0.367 0.384 1993-94 0.400 0.40 0.350 1996-97 0.400 0.41 0.380 1998-99 0.410 0.40 0.330
Sources: MHCHD/UNDP 1999 P 85 Govt of Pakistan 1998-99 Pakistan Economic Survey 2002-
03 P 50.
4.12 Trends in Agricultural GDP Growth in Pakistan 1999-2000 to 2005-06 Annual agricultural growth in Pakistan averaged 3.7 percent over four
decades from 1959-60 to 2001-02; although, there were wide year to year variations.
Apart from a period of slow growth in the first half of the 1970s, average agricultural
growth exceeded 3.2 percent annually from 1960-2000 due to large part of high growth in
the crop sector in the 1970s and 1980s as a result of green revolution (improved seed,
increased fertilizer use and irrigation). However, the performance of the agricultural
sector particularly, the crop subsector has suffered in recent years because of severe
drought in the country as well as environmental factors.
Pakistan’s agricultural sector grew at a modest rate of 2.6 percent per year
from 1999-2000 to 2005-06 (0.3 percent per year on a per capita basis), real value added
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of major crops (wheat, basmati and other rice, cotton, sugarcane, maize), which
accounted for about two thirds of agricultural crop, GDP grew by 2.6 percent per year
over this period. There have been substantial fluctuations in real crop GDP in recent
years due largely to variations in water availability. For example, real crop income fell by
3.6 percent in 2005-06 after it rose by 17.8 percent the previous year due to a record
cotton crop (production increased by 42 percent). Total GDP grew by 2.3 percent
annually, almost entirely due to a 2.1 percent yearly increase in crop GDP/hectare, while
the cropped area increased by only 0.2 percent per year. Livestock which account for half
of agricultural GDP grew by an average of 3.5 percent per year Table-17 (GOP, 2005-
06).
Table-17 Agricultural GDP Growth in Pakistan 2005-06.
2005-06 value added
2005-06 share Agri.
GDP
2005-06 share
total GDP
2000-06 growth
rate Agriculture 1055.2 100.0% 21.6% 2.6% Major crops 371.1 35.2% 7.6% 2.8% Minor crops 129.9 12.3% 2.7% 0.9% Livestock 523.5 49.6% 10.7% 3.5% Fishing 14.2 1.3% 0.3% -0.9% Forestry 16.5 1.6% 0.3% -5.7% Industry 1270.1 - 26.0% 7.9% Services 2554.2 - 52.3% 5.9% GDP (factor cost) 4879.5 - 100.0% 5.6% Population 155.4 - - 2.1% Agri. GDP / per capita (Rs.) 6790 - - 0.5% Cropped area (000,000) 22.5 - - 0.2% Crop GDP / Ha (000 Rs.) 22.3 - - 2.1% Source: Pakistan Economic Survey 2005-06.
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4.13 Trends in Rural Poverty Across Household Groups in Pakistan 2004-05 Majority of Pakistan’s rural poor are neither tenant farmers nor farm
owners. Non farm households (excluding agricultural labourer household) accounted for
57 percent of the rural poor in 2004-05. Farmers comprised only 35 percent of the
households in the bottom 40 percent of rural per capita expenditure distribution. The
remaining 8 percent were agricultural labourer households. This distribution of rural
poverty closely reflects land distribution which is highly unequal in Pakistan. According
to the 2000 agricultural census, only 37 percent of rural households owned land and 61
percent of land owning households owned less than 5 acres or 15 percent of the total
land. Two percent of households owned 50 acres or 30 percent of total land. Moreover,
returns to land are estimated to be about half of incomes (value added) from crop
agriculture, with only about five percent of value added paid to hired agricultural labour.
Moreover, non farm income is a major source of revenue, even for farmers with land.
According to 2004-05 PSLM data, crop, livestock and agricultural wage labour incomes
account for only 25, 8 and 4 percent respectively; of the total rural incomes, 40 percent
remittances 9 percent, and other income 15 percent comprise the reminder even for farm
households crop incomes account for only about half (49 percent) of the total income
(Pervez et al. 2005).
4.14 Conclusions
This chapter presents the status and trend analysis of rural poverty in
Sindh and Pakistan. The analysis has been carried out using different data from secondary
sources. Available information indicates that 54 percent of the population was found
among the poorest category while 79 percent were poor. Poverty was highly correlated
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with household economic characteristics such as land ownership and employment
opportunities. Villages that are situated in close proximity of the four Arabian Sea are the
most frequent subject of periodical disasters. Poverty is concentrated in those areas
growing the major commodity crops wheat, cotton and rice. Furthermore, the analysis
revealed that trends in gini coefficient in the 1970s shows an inverse relationship between
poverty and income distribution, with letter improving and the former worsening. Land
distribution is highly unequal in Pakistan, according to agricultural census of 2000 only
37% of the rural households owned land and 61% of land owning households owned less
than 5 acre or 15% of the total land. During the period of 1998-2002, the dominant
growth component contributed adversely to the rise in poverty. Finally, in the year 2004-
05 the growth effect remained dominant but redistribution benefited urban areas and
adversely affected the rural areas.
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CHAPTER-V
POVERTY ALLEVIATION INITIATIVES
5.1 Contributions of Governmental Organizations Towards Poverty Alleviation
in Pakistan
Poverty alleviation programmes in Pakistan can be divided into four broad
categories: (i) Programmes generating income and employment opportunities, (ii) Social
and human development, (iii) Infrastructure and community development and (iv) Social
protection schemes. The comparative size and mode of financing of these projects differ
widely from each other. Table 18 reflects the latest trends in pro-poor budgetary spending
in Pakistan.
Table-18 Trends in social sector and poverty related expenditure in Pakistan
2001-2006. 2001-02 2002-03 2003-04 2004-05 2005-06 2006-07 Community Services
10.98 16.57 28.53 44.71 45.25 42.5
Human Development
90.67 105.81 134.05 155.81 196.84 21.4
Rural Development
24.3 34.18 44.52 59.69 68.74 29.7
Safety nets 8.33 13.75 12.32 8.438 9.65 3.7 Governance 32.98 38.54 41.81 50.52 58.21 15.3 Total 167.25 208.84 261.3 316.24 378.81 22.7 Source: Human Development South Asia 2006. Poverty in South Asia Challenges and Responses.
Published by Mahbubul Haq Human Dev Centre Islamabad. Despite financial constraints, such expenditure more than doubled
between 2001 and 2006, growing at an average rate of almost 23 percent per annum. All
categories of pro-poor expenditure recorded growth over the period. However, the
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steepest acceleration has been witnessed in the expenditure on community services,
which increased four times. The expenditure on roads and highways constitute major
share under this head, underlining the necessity of employment generation for the poor.
However, human development remains a top priority of the government accounting for
more than half of the total expenditure (Table 18). The most worrying situation was the
expenditure on food subsidies, food support programmes; and low cost housing has been
stagnant even in norminal terms with negative repercussions for the poor and the needy.
The major governmental poverty alleviation programmes in Pakistan are
reviewed below.
5.1.1 Zakat Programmes
The principal form of cash transfers to the poor and disadvantaged in
Pakistan is through the publicly administered system of zakat. The two main types of
support programmes, the Guzara Allowance and the permanent rehabilitation grant,
absorb in excess of 70 percent of zakat related disbursements. The programmes run under
zakat are classified as regular and other programmes. Funds for the permanent
rehabilitation scheme and for regular programmes are disbursed through provinces, while
those for other programmes are distributed directly by the central zakat council. Guzara
allowance (or subsistence allowance), one of the major zakat programmes, is a typical
cash transfer, paid at the rate of Rs.500 per month to eligibles and is one of the main
instruments of support wielded by the local zakat committee. Those eligible are;
(i) Adult living below poverty line (Rs.670 per month for 2002) with preference
to widows and disabled.
(ii) Unemployed and
(iii) Not habitual beggers
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The local zakat committee establishes the eligibility of the person and the
list of recipients has to be pasted outside the local mosque. Three different categories of
educational assistance are also provided under zakat. The payment is made directly to
institutions, where eligible students are enrolled. Stipend are given to students enrolled in
the mainstream public or private sector schools (Table-19)
Table-19 Disbursement and beneficiaries of zakat in Pakistan 2003-04. Total amount
disbursed (Rs. Million)
Total number of
beneficiaries (A) Regular Zakat Programmes Guzara allowance 1923.3 813,642 Educational stipends 408.9 289,181 Stipend to student in deeni madras 174.3 69,851 Health care 152.3 186,750 Social welfare / rehabilitation 121.1 25,544 Marriage assistance to unmarried women 122.4 11,876 Sub-Total (A) 2902.2 1396,844 (B) Other Regular Head Eid grants 209.2 0 Leprosy patients 0.5 56 Permanent rehabilitation scheme of zakat phase III 2319.5 175,664 Educational stipend (Technical) 429.2 22,310 Sub-Total (B) 2958.4 198,030 Grand Total (A + B) 5860.6 1594,874 Source: Govt. of Pakistan 2006 B, Zakat Disbursmeent, Mahbubul Haq Centre for Human
Development, 2006 Report.
Zakat is being used to finance health care under the national level health
programmes managed by the provincial and central zakat councils. The zakat council
determines the eligibility of an unmarried woman unable to bear expenses related to her
marriage. Almost one third of the total disbursement under zakat was devoted to PRS
(permanent rehabilitation scheme) benefiting around 10,000 people with the average
value of the grant being Rs.17,000 (MHHDCI, 2006).
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5.1.2 Pakistan Baitul Maal (PBM) Scheme
The Pakistan Baitul Maal (PBM), which operates under the administrative
control of the Ministry of Women Development, Social Welfare and Special Education,
was established as an autonomous corporate body under a special act of 1991. The PBM
was set up to help the destitute, needy widows and orphans, invalids and other such
people who are in dire need of assistance. The two main benefits that it provides are the
food support programme and individual financial assistance. As shown in (Table-20),
majority of the beneficiaries (52 percent) belongs to Punjab, while less than 5 percent of
the recipients are from Baluchistan, signaling with the population share of the provinces.
Table-20 Percentage province-wise distribution of Pakistan Baitul Maal (PBM) beneficiary households in Pakistan 2003-04.
Project Punjab Sindh NWFP Baluchistan ICT AJK x
NA Food support program 52 21 18 4 5 Individual financial assistance 44 26 10 11 10 National centre for rehabilitation of child centres
36 25 20 12 6
Instructional rehabilitation 53 0.50 27 0.49 19 Source: Mahbubul Haq Centre for Human Development, 2006 Report.
5.1.3 The Food Support Programme (FSP)
A redesigned food subsidy scheme was initiated in 1994, which was
renamed as the Atta Subsidy Scheme in July 1997, aimed at providing a cash grant of
Rs.200 per month per family to 520,000 poor households across Pakistan. The aim of the
food support programme was to provide a food safety net for the poorest households to
those with income below Rs.2000 per month. FSP is a cash transfer of Rs.2,400 per
annum in two installments of Rs.1,200 each to 1.25 million households.
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5.1.4 Individual Financial Assistance (IFA)
The primary purpose of individual financial assistance (IFA) is to support
the poor, widow, destitute women, orphans and disabled persons through medical
treatment, education stipends, rehabilitation and general assistance. Financial assistance
can only be given once a year. Assistance for medical treatment is provided through
government hospital up to the maximum of Rs.300,000. Bright, deserving students are
also give stipend to cover tuition fees up to Rs.40,000, can be paid to the poor to make
them self-reliant.
5.1.5 The Khushhal Pakistan Programme (KPP)
The Khushhal Pakistan Programme (KPP) is an important public sector
programme to create employment opportunities for unemployed poor. Under this
programme, members of the national assembly (MNAs) are authorized to identify and
finance development schemes upto Rs.5.00 million in their constituencies. The
programme provides essential infrastructure in rural and low income urban areas by
building farm to market roads, water supply schemes, repairing existing schools, small
rural roads, streets, drains and storm channels. The sectoral and provincial distribution of
RPP shows that more than half of the disbursements were made for Punjab, 22 percent
for Sindh, 14 percent for NWFP and less than 10 percent for other areas of Pakistan.
5.1.6 Pakistan Poverty Alleviation Fund (PPAF)
The PPAF was established six years ago and provides soft laons to 65
different partner organizations, which, in turn lend to individuals and groups within their
target communities. It also provides grants on a cost sharing basis for development of
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small scale community infrastructure and strengthens micro-finance institutions (MFIs)
by supporting their capacity building activities. To date, the PPAF has managed
cumulative disbursements of nearly Rs.14 billion. A study conducted by Gallup Pakistan,
found adequate evidence to suggest that on the average low income households, who
borrow from the PPAF, are better off than what they would have been if they had not
borrowed (MHHDCI, 2006).
5.1.7 Khushhali Bank
Khushhali Bank launched its operation as a micro-credit financial
institution in the year 2000, with the prime objective to establishing a pro-poor
sustainable financial services delivery network in the country. With a predominantly rural
portfolio, the bank now has service outlets in all provinces. The bank provides short-
tenure micro loans ranging up to US # 500 dolars for working capital and asset purchase.
Nearly one-third of its 50,000 clients are women. The processing of loans is strengthened
through the involvement of community based organizations (CBOs) in lieu of the
traditional collateral requirements defined as those, living below the level of the
microfinance lending programmes of the Khushhali bank, have enjoyed considerable
improvement in economic / social welfare indicators and have also benefited from
accelerated income generating activities in the agricultural sector. However, in general
there has not been a significant impact on caloric intake of the borrowers or their
consumption expenditure on non-food items. Similarly, the bank clients have not
displayed better performance in terms of school enrolment of their children.
For Khushhali Bank to realize its potential impact, it is essential to bypass
the information problems while conducting micro-credit operations on a truly massive
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scale. For long term sustainability, it is therefore, imperative to achieve high repayment
rates while charging interest rates that cover the cost of lending (Microfinance in
Pakistan, 2005).
5.1.8 Small and Medium Enterprises for Empowerment of the Poor in Sindh
The small and medium enterprises development authority (SMEDA) in
Pakistan was established in October, 1998 as an autonomous corporate body headed by
the Prime Minister. The terms of reference of (SMEDA) are that it will be an apex policy
making body for small and medium enterprises (SMEs) and provide and facilitate support
services, generate massive employment opportunities, give industrial growth, revitalize
small business and back start the economy through aggressive launch of SME support
programme. The SME sector has great potential for generating employment, especially
for the low income groups thus creating a business environment that is supportive of
SMEs. This is an important part of the government’s poverty reduction strategy. This
sector contributes 30 percent of the GDP with value addition to the manufacturing sector
of around 35 percent and generating 25 percent of manufacturing sector export earning
(US $ 2.5 billion). It also provides 99 percent of non-agricultural jobs. The micro
enterprises development initiatives such as provision of credit through banks are expected
to spar economic activity mainly in the self employed segment of the population
(SMEDA, 2008).
The government recognizes that SME led private sector development
needs further strengthening of the regulatory environment, adjustment in potential
policies and provision of support services for enterprise establishment, development of
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quality improvement and export marketing in the short to medium term. SME led
economic growth is expected to reduce poverty through
(1) Income generating activities in rural and urban areas.
(2) Creating employment opportunities
(3) Providing forward linkages to the micro-enterprices benefiting from the
availability of micro credit.
5.1.9 Land Distribution to the Poor for Poverty Alleviation in Sindh
The Government of Sindh has announced grant of state land to the poor in
all districts, where state land is available with primary objective of reaching out to the
most marginalized segment of Sindh population. Grant of the state land to the poor Haris
is one of the central poverty reduction strategy of the new government. The policies of
land grant followed by different governments have however been more or less a routine
affair and there has been no attempt to target the landless in transparent manner.
Similarly also there was no attempt to facilitate institutional support to the poor
beneficiaries in terms of connecting them to rural credit markets etc for enabling them to
move to sustainable livelihoods. The broad policy framework has been evolved on the
basis of past lessons and major weaknesses of the past policies. What has basically
surfaced, is the fact that the past land grant were primarily implemented through a
mechanism provided under the land revenue act. In view of the above, the government
has drawn out the framework of a policy that builds upon past mistakes and oversights
for ensuring sustainability of reforms. The major feature of the framework are presented
below:
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5.1.9.1 Priority Given to the Poorest of the Poor
The second major feature is the targeting component which involves a
legal prescribed procedure in the land revenue act of 1912, through which the revenue
department would hold open katcheries for inviting applications for grant of land to
eligible poor. It has been acknowledged that the government would need to be very sure
that land is being allotted to the landless Haris and from amongst many landless it is
going to the most poor. As this would certainly be a challenging task the Chief Minister
has approved formal involvement of the rural support programmes (RSPs), in the
implementation of this programme for two tasks namely, (1) identification of the poor
landless Haris and then (2) Devising and extending support package. The rural support
programmes are currently working in 462 union councils in Sindh and they are already
working on an extensive exercise for poverty profiling in all the union councils through
the poverty card they would be able to categorise various levels of poverty such as
destitute, chronic poor, transitory poor etc. Government has accordingly, approved to use
this information to verify the credentials of the Haris once the applications are received.
5.1.9.2 Support Package
The third major policy component is that the beneficiaries of state land
would be fully supported through a support package for at least a period of two years, till
the time they attain sustainable livelihoods. The support package would depend on the
type of land, however in general it encompases availability of water, provision of
essential inputs including seed, fertilizer and pesticides. The policy is to formulate
cooperatives of Haris, wherever possible and to extend this support package to them on
the basis of economies of scale.
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Another component of the policy is that particular support package will be
developed and delivered through the RSPs. The government is strongly committed to
implement this reform in a much more transparent way than has ever been attempted
before. This programme would help to solve the problems related to use of inefficient
capital intensive techniques, due to distorted factor market prices and that small farmers
do not have access to the liberal credit subsidies on imported machinery and capital
equipment (GOS, 2008).
5.1.10 Sindh Progress Towards Achieving Millennium Development Goals (MDG)
Pakistan is well set on the track to achieve MDGs by 2015. As a result of
the overall macro-economic stability, structural reforms, high GDP growth rate combined
with pro-poor expenditures in the recent past, the overarching MDG goal of reducing
poverty to 13% by 2015 is likely to be achieved. This Optimism is based on the
government commitment and policies under implementation. The challenges are
enormous, one in four Pakistanis still lives below the poverty line. In terms of human
development index developed by UNDP, Pakistan stands at 134 out of 177 countries. The
overall literacy rate at 53% is low. These challenges and attaining MDGs can best be met
by pursuing pro poor economic growth, the deepening the on-going reforms, continuity
and sustainability of policies and programmes, and involvement of communities in the
development process. In view of the foregoing, therefore, we shall present the progress
towards achieving MDG for Sindh province specifically.
1. Eradicate Extreme Poverty and Hunger, Social Protection Strategy: The long
term objective of social protection strategy of Pakistan is to develop an integrated
and comprehensive social protection system covering all the population,
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especially the vulnerable poor and the vulnerable non-poor. The immediate focus
is on providing cash/conditional cash transfers to the poorest, the poor and
vulnerable, who constitute about 20% of the population. The number of
beneficiaries is expected to increase from 2.2 at present to 3.2 million in the next
five years.
2. Achieve Universal Primary Education New Initiatives by the Sindh
Government: The Directorate of Literacy and Non-formal Education, Education
and Literacy Department, Government of Sindh at present is operating the Adult
Literacy Programme under Education Sector Reforms. From the year 2001-2005,
30,398 illiterates have graduated from a total of 970 Adult Literacy Centres. An
estimated 750 Adult Literacy Centres were established in Sindh during 2006-07,
where approximately 22,500 illiterates will be made literate.
3. Promoting Gender Equality and Empowerment: The National Commission
for Human Development NCHD has been given two mandates, one to increase
adult literacy in the country and the other is to attain universalization of primary
education. Since its inception, a total of 4376 literacy centres were established in
Sindh and a total of 106,034 people were trained.
Table-21 NCHD Adult Literacy Centres and Learners.
Provinces
No. of Districts
Literacy Centres
Learners
Number Share Number Share Punjab 20.0 (34.0) 9139 43.1 207,709.0 43.8 (57.0)
Sindh 13.0 (24.0) 4367.0 20.6 106.034 22.4 (24.0)
NWFP 24.0 (24.0) 5498 25.9 114,460.0 24.2 (4.0)
Baluchistan 9.0 (29.0) 2198 10.4 45.597.0 9.6 (5.0)
Total 66.0 (101) 21,202.0 100.0 473,800.0 100.0
Source: Pakistan Millennium Development Goals Report 2006 Report Page 46.
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4. Reducing Child Mortality: In the case of Sindh, among the top 5, the top most
ranking district Larkana lost its first place and is replaced by Hyderabad in 2005.
Sanghar District lost 11 places and slipped from position 15 in 2005 ranking.
Among the bottom, 3 districts improved their ranking in 2005. Thatta, Ghotki and
Badin moved up to middle ranks.
5. Improve Maternal Health (MCH): The lady health workers programme was
initiated in 1994 to provide health care services to women on their doorsteps,
thereby bridging the gap between the community and institutionalized services.
The government has also introduced the national maternal and child helath
(MCH) programme. It is aimed at improving access to high quality and effective
services for all. There are nine years left for the achievement of the MDG on
maternal health, this has proved very difficult to achieve. What is required now is
increased commitment and priority action, so that the desired goal can be
achieved by 2015.
6. Ensure Environmental Sustainability: In the case of Sindh, among the top 5,
Hyderabad and Dadu lost their places and are replaced by mid level cities of
Sanghar and Nawabshah. Among the bottom 5, greater reshuffling took place and
Sanghar, Jacobabad and Ghotki joined the mid level rank. While Thatta, Khairpur
and Mirpurkhas slipped to bottom 5 places in 2005. The clean water for all
proposed time frame will enable most of the districts to achieve national targets
well before 2015.
7. Combat HIV/AIDS, Malaria and Other Diseases: The prevalence of
HIV/AIDS, malaria and other communicable diseases in Sindh and Pakistan has
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been fluctuating from year to year. The prevalence of HIV/AIDS in general
population is still less than 1 percent of the population and Pakistan is therefore
considered a low prevalence country (CRPRID, 2006).
5.1.11 Targeting the Poor in Sindh Using the Poverty Score Card
The poverty score card for Pakistan has been developed as a tool to
measure change in poverty in an effective way and to support the management of
development programmes in microfinance and also in other development sectors. It is
also a useful tool for social investors that need to measure their results according to the
triple bottom line objectives i.e. financial, social and environmental results.
Poverty scoring is a tool for measuring poverty mainly developed for
giving practitioners a simple, effective and low cost tool for observing the progress
targeted by projects. It is useful to donors for improving transparency and accountability
with regard to the income related MDG. The score card uses the 2001 Pakistan Integrated
Household Survey to construct an easy to use objective, it estimates the likelihood that a
participant has expenditure below the national poverty line.
However, over a period of time, some of the most frequent questions
asked; include who are the poor? How many poor are there? Where do they live and what
is their social and economic profile? In order to answer these questions, the RSPs with
the help of Grameen foundation USA, developed a poverty score card that answers all the
questions.
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5.2 Contribution of NGO’S To Poverty Alleviation in Sindh
The desire to help those in need is as old as civilization itself.
Volunteerism is not new in Pakistan. It has a long history dedicated and selfless workers
who have devoted their lives to respond to the needs of people. Volunteerism in Pakistan
has come to be identified by the organizations to which they belong not too long ago,
mostly the non formal organizations were simply known as voluntary social
organizations / agencies. Presently, the voluntary organization are in more organized
form and are widely known as NGOs.
Realizing the importance of NGOs as a helping hand to state in socio-
economic development by the present government, citizen community board (CCBs) has
become a part of the local development agenda.
Most NGOs are welfare oriented. They are usually operative at the level of
neighborhoods and are involved in the provision civic amenities such as basic health,
education, library facilities, vocational training, youth programmes, credit, income
generating activities etc (Shireen, 1998).
5.2.1 Participatory Development Approach
Participatory development is a process which involves the participation of
the poor at the village level to build their human natural and economic resource base for
breaking out of the poverty nexus. It specifically aims at achieving a localized capital
formation process based on the progressive development of group identity skill
development and local resources generation. The beginning of the process is therefore,
the emergence of a nascent form of community consciousness.
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5.2.2 Contributions
The total coverage of NGOs at present is relatively insignificant,
compared to the magnitude of the poor population. According to survey conducted by
NHDR/PIDE 2001, the total received by all categories of the sample population, the
percentage of loans received from NGOs was only 0.8 percent in rural areas and 1
percent in urban areas.
Similarly the national rural support programme (NRSP) which is by far
the largest NGO in the country, operating in twenty seven districts, has a total coverage
of only 293,000 beneficiaries. The NHDR/AI survey shows that there was considerable
variation with respect to the effectiveness of targeting of the poor between various NGOs
and the impact of intervention on income, nutrition and health of the poor.
NGOs, that enabled the formation of autonomous organizations of the
poor could play an important role in creating a systemic relationship between local
governance and poor communities. Such a relationship would enable the poor to
participate in identification and implementation of development projects as well as
decisions related with access over markets and local power structures. Equally important
the emphasis perhaps may need to shift from building centralized NGOs in a large
number of districts with low intensity of coverage and high overheads in each towards
district specific NGOs, which achieve full coverage of the poor population in the villages,
union councils and tehsils of that district.
Perhaps the single most important factor to the success of NGOs is the
quality of leadership. Specifically it is the ability to relate with humility and love with the
poor. The successful NGO leader creates the team synergy to develop innovative
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responses to each new problem on the ground. The second factor in the success of small
NGOs, which engaged in social mobilization is the identification, training and fostering
of village level activists who gradually begin to manage existing community organization
(COs) enabling NGO staff to give more time to develop new COs. The third factor in the
success of small NGOs is the ability of level leadership to devolve responsibilities
acknowledge their achievements and to learn from them just as much as it is necessary
for leadership to learn from the poor.
The fourth factor in the success of small NGOs in reaching significant
scale is the development of credible accounting procedures and a regular monitoring and
evaluation exercise on the basis of which donor funding can be sought when it is
required. In each case successful NGO apart from devising some modes of reflection and
action with the village communities also develops formalized recording and reporting
system.
5.2.3 Strengths and Weaknesses of NGO’S Like other sectors, the NGO are not exceptional in having strengths and
weaknesses. Some strengths and weaknesses are as follows:
a. Strengths: NGO have special ability to reach the poor and other segments of society
overlooked by public and commercial sectors. NGO facilitate local resource mobilization
and have programmes of local participation in development. Service delivery at low cost
and innovative solutions to novel problems are their strengths. The biggest strength of
these organizations is the openness in thought. They are said to be learning organizations
their capacity grows from small size with administrative flexibility and have relatively
more freedom from political constraints.
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b. Weaknesses: Due to the small size and budget, NGO lack in technical capacity
because the highly trained technical and professional people do not find much attraction
for career jobs in this sector. NGO have limited ability to scale up successful projects to
achieving regional or national impact. This is due to their small size and resources, that
there are unscientific administrative system, intensive focus on a few committees, the
difficulties in maintaining their essential value consensus; soon as the staff expands
interaction to developing real efficiency and expertise in a well defined technological
environment and even living with their own commitments to their beneficiary
populations (Shireen, 2002).
5.2.4 Sindh Agricultural and Forestry Workers Coordinating Organization
SAFWCO
Since inception in 1986, SAFWCO has worked to improve the quality of
life especially the poor. SAFWCO approach is based on five steps such as mobilization,
organization, strategic planning, partnership building through small projects and
facilitation towards sustainability.
SAFWCO’s work is spread across Sanghar District as a demonstration of
how to empower people. Significant work has been done in the field of social
organization and services delivery, agriculture and economic development, natural
resource development and human institutional development. The work in social
organization and service delivery builds the social and physical infrastructure enabling
the rural poor to address systemic process of poverty. The process of organization and
infrastructure building helps them to participate and take control over resources. The
human and institutional development process mainly targets awareness and
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consciousness raising, combined with skills and tools development. The natural resources
management and agriculture and economic development programmes are aimed at
consolidating the social organization process that gives people a sense of accomplishment
and confidence in the process. SAFWCO MicroFinance Programme is a part of
agriculture and economic development sector (SAFWCO Annual Report, 2005).
5.2.5 Sindh Rural Development Project (SRDP)
In view of the denial by the provincial government of Sindh about the
existence of the bonded labour in agricultural sector and the presence of private jails in
the province, Asian Development Bank initiated a process for launching a loan project in
Sindh for the abolition of the bonded labour in Agricultural Sector in 1998 with the name
of Sindh Rural Development Project (SRDP). According to the project documents, the
overall goal of the project was to reduce poverty in four districts of southern Sindh,
through increasing empowerment and improving governance, improving access of the
rural poor to public services, transferring technology for improved livelihoods and
providing essential infrastructure. In addition to the above, the project aimed at
improving the social status and economic well-being of the poorest groups in the project
area with a focus on the following target groups; (i) haris and agricultural labourers, (ii)
marginal owners-cum tenants (with less than 2 ha) and (iii) small village based artisans.
There was a particular focus on women as the most disadvantaged among the target
groups (SRDP, 2007).
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5.2.6 Aga Khan Rural Support Programme (AKRSP) Since it began, 13 years ago the Aga Khan Rural Support Programme
(AKRSP) has transformed the remote Northern areas and Chitral in Pakistan into rural
development success stories. Its distinctive approach has provided the inspiration for
other programmes in Pakistan and elsewhere.
The key element of the programme is institutional development at village
level, which provides the framework for community members to take advantage of
outside assistance as well as to use their own resources more productively. AKRSP
started the process by providing an agent to help villagers form a village organization and
undertake a significant investment in productive infrastructure of their choice, such as
irrigation facilities or a local road that will benefit their community. The programme
provides a one time grant to complement villagers contributions to the infrastructure
projects. The grant process helps village organizations to mobilize savings and acquire
agricultural technology and production inputs. As benefits accrue, AKRSP facilitates
links with other entities providing health and education services.
5.2.6.1 Strategy
With rapid population growth, limitations on usable land and improved
accessibility, the economic environment in the programme area is changing. Though,
farming is important, most households earn between 30-50 percent of their income of the
farm often in non agricultural jobs. AKRSP is responding to expanding into the
promotion of non-agricultural investment.
People in the project areas are increasingly demanding social services and
investments in health and education. In response, AKRSP is facilitating links between
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village organizations and other providers. In future most of the basic infrastructure and
social service investment in the region is likely to come from the government.
5.2.6.2 Conditions for Replication
In Pakistan AKRSP has been successfully spread over three districts under
separate day to day management and its replication has begun in two adjacent districts
with support from Asian Development Bank and government of Pakistan. The prospects
of replicating the AKRSP model on a broad scale depends partly on the macro and
sectoral policy environment including the regulatory system for finanace, natural
resource and commerce as well as state support services. Experience over the past 50
years, for example in Brazil, Kenya, Korea, Malawi, Malaysia, Taiwan and China
suggests that most successful governments sponsored rural development programmes
have been run by autonomous and accountable parastatals bodies with carefully crafted
institutional development strategies (AKRSP, 2007).
5.2.7 National Rural Support Programme in Sindh (NRSP)
5.2.7.1 Establishment of NRSP
In 1991, the Government of Pakistan (GOP) supported the country wide
replication of the rural support programme model which culminated in the creation of the
NRSP. In 1992, Government of Pakistan provided NRSP with a grant of Rs.500 million
to start operations. As other resources became available, particularly from donors and
also from provincial governments, RSP expanded beyond initial eight districts. Cost
recovery from NRSP’s micro-credit programme, which credit organization in Pakistan
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with 160,893 active loans totaling, Rs.1,779 million (US $29.6 million), now provides a
significant proportion of NRSPs operating funds (NRSP, 2006).
5.2.7.2 Experience in the Project Districts
NRSP is established in the project districts with 12 years of operation in
Badin and 6 years in Thatta. It engaged in community mobilization, savings and the
implementation of small scale civil works in these areas. The details of current NRSP
activities in Thatta and Badin districts are shown in (Table-22).
Table-22 Current NRSP areas in Thatta and Badin. District Tehsil / Taluka Field Unit Badin * Badin
* Golarchi Tando bago Talhar Matli
Badin Golarchi Tando Bago Talhar Matli
Thatta Thatta Sajawal Mirpur Bathro *Mirpur Satro
Thatta Sajawal Mirpur Bathro Mirpur Satro
Source: NRSP records * Project areas 5.2.7.3 Social Mobilization and Small Scale Interventions NRSP community organizations have proven successful in facilitating
needs identification by villages and in arranging for demand to be effectively met in
participatory ways. Community organizations (CO) members and their households can
avail themselves of a number of services from NRSP including training, micro-credit and
support for small-scale civil works interventions. NRSP has also put in place important
sustainability measures and is helping (COs), register a community citizens board and
access funding from district governments.
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Table-23 NRSP community physical infrastructure in Thatta and Badin as of 31 August 2006.
Badin Thatta Total
Completed projects 322 111 433 Total cost in (Rs. Million)
84,337 14.29 98.647
Donor share 60.936 11.326 72.26 Community share 23.421 2.964 26.36 Source: NRSP records 5.2.7.4 Achievements Recorded
NRSP performance was evaluated as part of a case study for 2004
Shanghai Conference on scaling up poverty reduction. It was estimated that membership
in the NRSP community organizations (CO) resulted in about 7.5 percent higher
household incomes annually. Similarly, NRSP estimates show that poverty levels were
lower in member households. The UNDP supported Pakistan National Human
Development Programme Report (2003) states that 68 percent, of the NRSP respondents
ate daily 68 percent ate better than before, 50 percent felt improvements in health and 82
percent experienced a sustainable increase in income after disbursement of credit (NRSP,
2006).
5.2.8 Badin Rural Development Society BRDS Badin Rural Development Society (BRDS) has been working for the
upliftment and community participation in development initiatives at district level since
last one decade. It aims at strengthening the standard of health, food security, water and
sanitation better participation of women, creating equal opportunities for vulnerable
groups and poverty alleviation in the targeted areas of District Badin especially the
coastal belt. These communities face devastation and catastrophies like earthquake,
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droughts, drenchers and other fatal calamities. Badin Rural Development Society has
adopted its integrated social mobilization strategy for the development of area, ensuring
women participation or giving preference to women in all its activities.
5.2.8.1 Contribution of BRDS to Rural Development and Poverty Alleviation a. Education
Giving right to education is one of the strategic objective of BRDS; the
organization has vision to advocate the right of child education for both girl or boy to
avail their education with appropriate facilities. In the year 2007, BRDS has provided
bags and other educational materials. Over 4000 children have benefited from their
activities. In 2008, BRDS planned to give these materials to only newly enrolled schools
except girls schools initiated by the community and BRDS.
b. Achievements
1. Overall children enrollment increased in sponsored villages.
2. Communities have learnt strategies of how they can advocate the right to
education.
3. People are sensitized over right of education and now equally respond to daughter
and son for studying.
4. Communities are requesting British Petroleum (BP) for social investment in
infrastructure.
5. Children are well organized and attached with BRDS educational facilities.
c. Social Mobilization
In district Badin, the programme intervention was based on report
building, mobilization and organization for sustainable positive changes in physical and
behavioural attitudes within the target communities. During the year 2007, BRDS team
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mobilized thousands of coastal communities to mainstream them in the people’s oriented
development. There are 60 villages in union councils Seerani, Bhugra Memon and
Ahmed Rajo, where community groups are formed; there are 1500 women and 2800 men
who are active members in these groups. BRDS team is regularly interacting with these
groups to identify innovative ideas and approaches which can lead to a progressive
society (BRDS, 2007).
d. Achievements
1. 1500 women and 2800 men in 60 villages are engaged in development process
2. 10 villages are registered for being part of development in district government
initiatives.
3. All women council seats are filled by competitive process in recent local bodies
election.
4. 35 mother committees are formed for girls enrolment and school management.
5. Female group members are sending their children in schools and accepted equal
right of education for both girls and boys.
6. 10 youth groups are functioning properly at community level.
5.2.9 Young Sheedi Welfare Organization YSWO Badin YSWO came into being in the year 1987 with determination, commitment
and dedication of the poor Sheedi people under the distinguished leadership of Faiz
Mohammad Bilali. This organization has become the silver lining for the poor and
marginalized communities of Badin District, particularly those living along the coastal
belt. In 1989, it was registered with social welfare department government of Sindh,
under social voluntary organization act, 1961.
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a. Achievements
(1) 58 Villages in 5 union councils of Ahmad Rajo, Bhugra Memon, Abdullah Shah,
Lunwari Sharif and Kadhan have been selected for disaster preparedness and
management project.
(2) 116 Community organizations have been formed.
(3) 9 clusters of the target villages have been formed.
(4) 01 Emergenccy centre has been established and equiped with necessary
emergency items.
(5) 04 Trainings have been given to the officials of community organizations.
(6) Site has been selected for construction of 2 demoraised platforms in 2 cluster
locations in Tehsil Badin.
(7) 12 TBA Training participants have been selected, while contents have been
discussed with lady doctor.
(8) 3 Radio Programmes have been broadcasted out of 10 programmes.
(9) In poverty Alleviation and income generation activities, 431 goat / sheep have been
distributed to 143 beneficiaries in Badin.
(10) 600 goats have been given to 200 beneficiaries in tehsil Johi, district Dadu
through local partner village Shadabad Welfare Organization.
(11) 200 beneficiaries have been finalized in Tehsil Diplo, District Tharparkar through
local NGO (Young Sheedi Welfare Organization Annual Report, 2007).
5.2.10 Sindh Microfinance Network SMN
Sindh Agriculture and Forestry Workers Coordinating Organization
(SAFWCO) being a practitioner in the fields, felt the need of a platform for small scale
NGO/CBO who are practitioners and providing microfinance services in their respective
areas of Sindh.
Sindh Microfinance Network (SMN) is a Network for organizations
engaged in microfinance and dedicated in improving the outreach and sustainability of
microfinance in Sindh. Microfinance sector in Sindh is in the initial stages of
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development. Estimates suggest 2 million households need the microfinance services
(Table-27).
SMN is established to provide a forum for microfinance practitioners to
exchange views and experiences on issues of common interest for the majority of the
population, this changing scenario has meant decreasing individual control over
livelihoods. The objectives of SMN were as follows.
1. Enhance the capacity and support of technical assistance.
2. Build a microfinance database of microfinance institutes.
3. Conduct research on microfinance related issues and provide development
services.
4. Facilitate effective networking at provincial, national and institutional level
5. Disseminate information and share experiences and lesson learnt.
5.2.10.1 Looking Ahead
The microfinance sector in Sindh continues to pursue a low yield strategy.
This is on the back of efficient operation, low delivery costs, competitive credit risk, high
capital adequacy, higher investment in human resources, and system improvement should
lead to a sustainable industry which is not the case currently. The microfinance sector in
Pakistan in poised for growth product diversification and market segmentation. There are
also very clear signs that both microfinance institutions (MFIs) and microfinance banks
(MFBs) is well needed to build linkages where they share the same market niche and will
soon be competing both amongst themselves and with each other with this possibility.
There is an increased need for high quality services providers that can build the necessary
infrastructure and reduces the business risk faced by MFPs. The recent guidelines for
commercial banks to do micro financing issued by the State Bank of Pakistan will on one
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hands build awareness amongst commercial banks, to move down the market for direct
lending and on the other open avenues for existing MFPs to leverage their balance sheets
by entering into commercial transaction with banks. This will build confidence between
microfinance players and the commercial sector and will diversify the funding options
available to the sector. However, for MFPs to achieve this, they will need to improve
their performance by showing a posture bottom line, a healthy balance sheet and strong
cash flow. The microfinance institutions will be required to provide hard numbers, the
rough improved disclosures, audits by high quality firms and credit ratings in the future.
The availability of different kind of products and value added services is also becoming
increasingly important (SMNR, 2005).
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Table-24 NGOS Providing Credit to the Poor in Sindh.
District of Sindh
BB BWA GSS LSRDA MRD SAFWCO OWPRA VDO OPPOCT SRSP GSF
Badin 12 12 Dadu 60 60 Hyderabad 292 292 Khairpur Mirs 631 344 975 Matiari 729 729 Mirpurkhas 701 701 Nawabshah 895 895 Sanghar 7256 47 82 7385 Tando Alllhyar
135 135
Tharparkar 434 434 Umer Kot 61 61 Sukkur 24 24 434 292 60 909 655 8,880 47 82 7688 1328 344 20.791
Source: Sindh Microfinance Network performance Bulletin Jan-Dec 2005 P18.
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Table-25 Micro Credit Disbursed by Various NGOS in Sindh 2007.
Districts Micro Credit Micro Savings Potential micro fiancé
market Active Borrowers
Gross Loan Portfolio
Active Savers
Value of Savings
Badin 6,439 71,052,551 44,529 31,918,271 294,781 Dadu 9,353 92,511,878 30,390 26,622,000 447,305 Ghotki 7,535 81,415,062 590 3,037,000 248,442 Hyderabad 30,482 267,858,171 12,441 52,637,239 517,652 Jacobabad 11,264 115,099,522 218 8,378,000 361,146 Jamshoro 2,945 21,530,508 - - - Karachi 83,892 768,106,687 50,541 1,429,734,228 1,329,990 Source: Micro watch journal of the Pakistan microfinance network issue No5 quarter 3 (July-Sept
2007) Page13.
5.2.11 Micro Credit for Empowerment of the Poor in Sindh
5.2.11.1 The Micro Credit Programme in Sindh
Sindh Agriculture and Forestry Workers Coordinating Organization
(SAFWCO) started the savings and credit programme as part of social organization
process. The saving groups were the pivots around which the women organizations were
created. These organizations consolidated themselves the need to increase household
income emerged as a priority issue. Since the villagers were reluctant to leave their
existing sources of income, the idea of alternate income earning activities emerged. The
women took the lead as they SAFWCO, therefore came to support the women initiatives
in industrial homes, poultry / goat raising and dairy cooperation and even in operating
small ration shops in the village. Together with this SAFWCO conceptialised the
revolving fund and loan servicing charge as a sustainable means of keeping the operation
going. In the year 2002, about 3500 people benefited from the credit programme and over
Rs. 20 million have been disbursed. SAFWCO microfinance team has grown from one
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social organiser and eight volunteers to a professionally managed workforce of eight
people. The recovery is monitored through computer software and credit coordinators
supervise and assist borrower in loan utilisation. As result of this, the loan recovery is
near 96%. The main delays are in the housing loans for reconstruction of shelter
destroyed in 1992 floods (SAFWCO, 2005).
5.2.11.2 Loans for Low Cost Housing and Goat Rearing
SAFWCO initiated this programme in 1994, buying loans for low cost
housing and goat rearing. The major part of the lending was for construction of low cost
houses damaged due to flooding in the year 1992. The affected people were provided
with long term (7 years repayment period) loans ranging from Rs. 5,000 to Rs. 35,000; a
total of Rs. 4, 227, 653 was disbursed to 199 affected families in 13 villages. They charge
12% lumpsum service calculated on a one year one time base to recover the operational
cost. Majority of this loan was later adjusted or written off as the agricultural income
declined and unemployment increased due to drought conditions. The funding for home
reconstruction was provided by International Development and Refugees Foundations
(IDRE), Canada through the South Asian Partnership (SAP) Pakistan. In the same year
SAFWCO started lending to help women of poor household to purchase goat kids that
they could rear and then sell for a profit. This was called the goat rearing programme
(GRP). The Trust for Voluntary Organizations (TVO) provided a revolving and
institutional support for this.
In this programme 1,218 women received Rs. 2,562,000 as loans at an
average of Rs. 2,000 per borrower, 15% per annum service was collected to recover
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operational and inflation costs. The repayment period was for one year. The project
ended in 1997 and was very successful as most of the beneficiaries made profit from goat
rearing, this has changed their lives.
5.2.11.3 Microcredit Disbusement In 2006
During the year 2006, outstanding loan portfolio increased to 102% as
compared to last year; financial self sufficiency and operating self sufficiency ratios also
increased. With the passage of time, SAFWCO realized that the beneficiaries of micro
credit need capacity building in accounting, business development, skills and enterprise
development. The human institution development (HID) unit initiated capacity building
programmes as well (SAFWCO Report, 2005).
Table 26 SAFWCO Microcredit disbursement 2006-07. Product Name Min Rs Max Rs Period Agricultural Loans 5,000 30,000 6 months Regular Monthly Loans 2,000 30,000 3-18 months Half Installment Loans 5,000 30,000 6-18 months Buffalo Purchasing Loan 10,000 30,000 12-18 months Festival Loans 8,000 30,000 12 months Eud Azha Loans for Mal Goats 8,000 12,000 3 months Small Enterprise Loan 35,000 100,000 18-24 months Source: SAFWCO Bridging Communities Financial Needs Annual Report 2007 P-14.
5.3 Contributions of Pakistan Poverty Alleviation Fund to Education and Health Care Delivery in Sindh
Strengthening quality education has become a global agenda at all
educational levels and more so at the primary level. The quality of basic education is
important not only for preparing individuals for subsequent educational levels, but to
equip them with the requisite basic skills. Quality education also ensures increased access
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equality and it is mainly due to these reasons that various international forums and
declarations have pledged improvements in quality of education. National commitment
towards quality education has become significantly visible since late eightees. Since then,
various stakeholders have started taking initiative and interventions for improving quality
with national and foreign funding (PPAF, 2005).
Responding to a long standing demand of rural communities, Pakistan
Poverty Alleviation Fund (PPAF) is committed to improving the living standards of poor.
It has introduced a health and education component in their programme in 2004. The
educational programme is significantly designed to provide quality learning at primary
levels. It aims at empowering poor families / group communities through improved
access to quality education. It is expected that through this, children from marginalized
communities would be mainstreamed. Main features of the PPAF education programme
include.
- Establishment of formal primary schools.
- Financial assistance for construction, furniture and fixture, teachers salary,
training of teachers, utilities and other recurring expenses.
- Enrollment of children aged 4-9 years according to the criteria practiced by
education department.
- Teacher student ratio of 1:30.
- Provision of affordable education (students would pay school fee regularly).
- Ensuring that deserving students are given scholarship to meet the expenses.
- Syllabus that allows mainstreaming of education.
- Local and trained teachers.
- Proper school uniform for students.
- Morning schools with standard timings.
- Ensured community participation
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In line with these beliefs, one of the initial partners that PPAF selected
was SAFWCO in Shahdadpur Sindh, where literacy rates are very low especially in case
of girls. The project was initiated in july, 2005; one of two pilot schools was established
in village Maqsoodo Rind. SAFWCO held several deliberations with the community and
finally after acquiring every one’s consent, a primary school was established.
5.3.1 Health Care Delivery
a. District Sanghar
In unpriviledged settlements, as is the case in rural Sindh, women and men
experience health problems due to lack of basic amenities and bad hygiene practices.
Malnutrition, anemia, diarrhea, malaria and other tropical diseases including tuberculosis
are common occurances. As a consequence, mortality rates are very high, especially in
expecting mothers and infants. Women have lesser access to basic preventive and
curative health facilities due to traditional biases of society. The lack of emergency
obstetric services is another matter of particular concern. Health policies and programmes
often perpetuate gender sterotypes by failing to consider socio-economic disparities
among women and not fully taking into account the lack of autonomy experienced by
women with regards to decisions about their own health care. Keeping in view the poor
health scenario in rural areas Pakistan, Poverty Alleviation Fund has recently ventured
into preventive and curative health care in order to improve health status of target
communities through provision of comprehensive quality of basic health services. The
main objectives of this programme are:
- Enhanced access to quality of basic health services.
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- Improved health status of target communities with a special focus on maternal and
child health.
- Active participation of all stakeholders, including community in health service
management.
In this regard the PPAF strategy strives to establish Community Health
Centers (CHC) in villages constituting around 3000 households and / or a population of
approximately 20,000 people. The CHC would be equipped by a team of trained medical
practitioners comprising of a Doctor, Lady Health Visitor (LHV), Traditional Birth
Attendant (TBA) and Dispenser/Lab Technician each. The CHC would also provide
mobile health facilities through 3-4 outreach teams comprising of 2 TBA, 2 LHWs and
one male Health Assistant. One team will cover 700 to 1000 households (PPAF Report,
2005).
5.4 Conclusions
The contribution of governmental organization was quite satisfactory.
Despite financial constraints, expenditure doubled between 2001 and 2006 growing at an
average rate of 23% per annum. Non governmental organizations (NGOs) contributed
significantly through various interventions on poverty alleviation in Sindh. The single
most important factor to the success of NGOs was the quality of leadership. Specifically
it is the ability to relate with humility and love with the poor. Sindh Agricultural and
Forestry Workers Coordinating Organization believes that institution building at
grassroot level helps in bringing social change in the society. It has made social
mobilization as core activity and entry point followed by different development
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interventions. The Agha Khan Rural Support Programme (AKRSP) provides a one time
grant to complement villagers contributions to the infrastructure projects. The grant
process helps village organizations to mobilize savings and acquire agricultural
technology and production inputs. As benefits spread the AKRSP facilitates links with
other entities providing health and education services. The National Rural Support
Programme (NRSP) success show that poverty levels were lower in member households.
According to UNDP report 2003, 68 percent of the NRSP respondents ate daily 68
percent ate better than before, 50 percent felt improvements in health and 82 percent
experienced a sustainable increase in income after disbursement of credit. The Pakistan
Poverty Alleviation Fund (PPAF) educational programme provide quality learning at
primary levels through this, children from maginalised communities would be
mainstreamed. Similarly PPAF ventured into preventive health care in order to improve
the health status of the target community through provision of comprehensive quality of
basic health services. The major strength of NGOs was their special ability to reach the
poor and other segments of the society. While their weaknesses was small size and
budget limited ability to scale up successful project achieving regional or national impact.
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CHAPTER-VI
RESULTS AND DISCUSSION
This chapter presents the results of household survey on the basis of
primary data collected in both Sanghar and Badin districts of Sindh province.
6.0 Household Survey Results 6.1 Household Related Information
6.1.1 Age of Household Head
Demographic information is obtained to compare the influence of various
characteristics such as age, education, skillfulness and other efficiencies in management
of socio-economic affairs of families by the household heads. Results (Table-27) revealed
that the average age of household head in Sanghar district was 40±1.02 years, while in
Badin district, the average age of household head was 44±1.17 years. This implies that
majority of household heads are middle age people. These findings coincide with Asif
(2007), who reported that the household heads were in the age of group of 44 years in the
rural areas of NWFP, nevertheless, there is a wide spread variation in the age of
household heads in Pakistan. Similarly Shirazi (1994) indicated that majority of male
headed poor households in NWFP fall in the age group of 40-49 years while, majority of
female headed poor households fall in the age group of 30-39 years. Choudhary et al.
(2009) empirically found that as far as the age of household head is concerned, the older
the household head 40 years and above, lower will be the incidence of poverty in view of
his or her work experience. Nguyen (2007) agreed that the age of household head has
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certain positive impact on the households’ living standards; and older the household
head, better will be the living conditions.
Table-27 Age of Household Head.
District N Minimum Maximum Mean Standard Error (SE)
Sanghar 160 18 70 40.38 1.01
Badin 160 22 85 43.85 1.17
Overall 320 18 85 42.12 0.75
Source: Survey Results 2007 and 2008.
6.1.2 Qualification of Household Head
Education is the most significant element to influence socio-economic
conditions of a society and educated household head will manage family affairs better
than an uneducated one. Survey results (Table-28) revealed that majority (40%) of the
respondents in district Sanghar were educated upto primary level and 30.6% were
illiterate. In case of Badin district 28% of the household heads were educated upto
primary level, but majority of them (43%) were illiterate and only 1.3% were educated
upto graduate or postgraduate level. Overall, the total number of respondents was 315 for
the two districts, 116 (36.80%) were illiterate, 107 (34.00%) were educated upto primary,
44 (14.20%) were matriculates, 21 (6.70%) had intermediate, 20 (6.30%) were graduates
and 7 (2.2%) postgraduates.
These findings are in line with those of Shirazi (1994), who reported that
the proportion of poor households heads in Pakistan were not highly educated and mostly
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poor households heads are educated upto primary level or below matriculation. Similarly,
the farm level survey estimates provided by NFDC (2002) indicate that about 34% of the
farmers were illiterate, while proportion of farmers under matric, intermediate,
graduation and post-graduation were 29, 23, 11 and 3 percent, respectively. Furthermore,
the above findings are further supported by Cruces and Wodon (2007), who reported that
a high job qualification of the house hold head has positive impact on the life of the
household as a whole. Little et al. (2008), reported that having a family member with
secondary and university education with stable employment in the formal sector can
increase the income of the household in general. Amara and Sial (2009) argued that lack
of education is one of the major factors which lead one to become poor. Generally, it is
recognized that healthy and more educated adult members in a household contribute their
income levels and reduce poverty. If household members are not adult and educated they
can become the cause of poverty. Choudhary et al. (2009), reported strong and significant
association among educational attainment and rural poverty; household with no
educational attainment have the highest incidence, depth and severity of poverty. There is
evidence that with a rising level of educational attainment all the three measures fall.
Furthermore, Nguyen (2007) reported that education has a very strong effect on the living
standards of households and more the education of household head, higher will be the
households’ living standards.
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Table-28 Qualification of Household Head.
Qualification Total
IlliteratePrimary Matric IntermediateGraduatePostgraduate
Sanghar N 48 63 21 8 12 5 157
% 30.60% 40.10% 13.40% 5.10% 7.60% 3.20% 100.00%
Badin N 68 44 23 13 8 2 158
% 43.00% 27.80% 14.60% 8.20% 5.10% 1.30% 100.00%
Overall N 116 107 44 21 20 7 315
% 36.80% 34.00% 14.00% 6.70% 6.30% 2.20% 100.00%
Source: Survey Results 2007 and 2008.
6.1.3 Skill of Household Head
The (Table-29) shows that 19.41% household heads in Sanghar district
having no skill, while 17.5, 12.5, 11.9, 8.80 and 6.90 percent of the household heads were
skillful to become electrician, carpenter, plumber, mason, auto mechanic and barber,
respectively. However, 5.61% of the household heads were skillful to join the profession
as blacksmith. Similarly, in Badin district, 38.1 percent of the household heads had no
skill, while 11.3, 8.1 7.5 and 6.9 percent of them had skills to become mason, electrician,
plumber, barber and blacksmith, respectively. Similarly, 6.3% of the household heads in
district Badin had skills in woodwork to become carpenters. The comparative study of the
two districts showed that the people in Sanghar district were more skillful than those
living in Badin district. This also indicates that this adverse situation is closely associated
with poor literacy rate in Badin district. The overall total number of respondents in two
districts was 320, of which 28.75 percent had no skill, 12.81 percent were electrician,
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9.70 percent plumber, 6.90 percent mechanic, 11.60 percent mason, 7.50 percent mat
making, 9.40 percent carpenter, 6.30 percent blacksmith and 7.20 percent barber.
Table-29 Skills of Household Head.
Districts
Skills
Total No any Skill
Electri cian
Plum ber
Mechanical Mason Mat making
Carpen ter
Black smith
Barber
Sanghar N 31 28 19 14 19 9 20 9 11 160
%19.38%17.50% 11.90% 8.80% 11.90% 5.60% 12.50% 5.60% 6.90% 100.00%
Badin N 61 13 12 8 18 15 10 11 12 160
%38.10% 8.10% 7.50% 5.00% 11.30% 9.40% 6.30% 6.90% 7.50% 100.00%
Overall N 16 41 31 22 37 24 30 20 23 320
%28.75%12.81% 9.70% 6.90% 11.60% 7.50% 9.40% 6.30% 7.20% 100.00%
Source: Survey Results 2007 and 2008.
6.1.4 Household Size
The household size is the major factor that influences socio-economic
conditions of a family. Survey results (Table-30) revealed that the household size in
Sanghar district was 9.12±0.37 members, while in Badin district, the average household
size was 7.62±0.28 members. Overall, the total number of sample respondents was 320
with a mean household size of 8.37±0.24 members. The results are in concurrence with
those of Shirazi (1994), who reported that the proportion of poor households is higher in
large size households than small size households. The families with 7 to 8 members had
the highest proportion of male household heads. Similarly, families having 5-6 had the
highest proportion of female household heads. Supporting those findings (GOP, 1998), it
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has been stated that the average household size in Sindh was 6 members. In rural areas, it
was 5.5 members; while in urban areas it was 6.8 members. According to Pakistan
Integrated Household Survey (PIDE, 1991), there was a bigger mean household size of
7.5 members in Pakistan. Amara and Sial (2009) stated that it is likely for one to be poor,
if there is large number of persons (household size), dependency ratio is another factor of
being poor. A high dependency ratio decreases the level of earning in relation to needs
and therefore, increases the risk of poverty (Lipton, 1983; Baluch Bob and Mc Collough,
1998). The chance of a household being poor increased due to its household size and
dependency ratio, while more male household head means less poverty. The above
findings are in agreement with those Choudhary et al. (2009), who reported that families
that live in larger households with an average family size of 8 persons are in the poorest
quantile as compared to 6 persons in the non poor quantile; and similar pattern has been
found in many developing countries Mailk, 1991). It is hypothesized that the larger the
household size, higher will be the level of poverty incidence and vice versa. Malik (1991)
further reported that a household size of 7-8 members was found to be most prone to
poverty. On average, 8 and above members in a household imply the highest incidence,
depth, and severity of poverty. The analysis concluded that an optimal household size is 3
members as it experiences a lower depth and intensity of poverty. Furthermore, Nguyen
(2007) reported that household with more dependents especially with more household
members (larger household size) means they have lower living standards.
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Table-30 Household Size.
District N Minimum Maximum Mean Standard Error (SE)
Sanghar 160 2 30 9.12 0.37
Badin 160 2 18 7.62 0.28
Total 320 2 30 8.37 0.24
Source: Survey Results 2007 and 2008.
6.1.5 Household by Members
It was noted from the survey results (Table-31) of district Sanghar that the
highest proportion (32%) of people had household size 7-9 members; while the lowest
proportion of household members (5%) was upto 3 members. Similarly, 26.9 percent
households had family size of 4-6 members. However, 15.60, 10.60 and 10.00 percent
households had 10-12, 13-15 and 16 family members, respectively.
In Badin district, the highest proportion (36.90%) of households had
family of 4-6 members, while 2.54% of household had the family size of 16 members.
Similarly, household by members upto 3 were 9.40%, between 25% 7-9 members, 18.80
% between 10-12 members and 7.50% between 13-15 members, respectively.
The comparative study of the two districts showed that Sanghar district
had 11 household by members between 7-9, 13-15, 5 and above 16, 12 members more
than Badin district.
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Similarly Badin district had up to 3, 7 members between 4-6, 16 and 10-12
5 more members than Sanghar district. Overall total number of respondents was 320 for
the two districts. Household members up to 3, 23 (7.20%) 10-12, 55 (17.20%) 13-15, 29
(9.10%) and above 16, 20 (6.30%).
Table-31 Household by Members.
District
Members Total
Up to 3
4-6 7-9 10-12 13-15 above 16
Sanghar N 8 43 51 25 17 16 160
% 5.00% 26.90% 31.90% 15.60% 10.60% 10.00% 100.00%
Badin N 15 59 40 30 12 4 160
% 9.40% 36.90% 25.00% 18.80% 7.50% 2.50% 100.00%
Overall N 23 102 91 55 29 20 320
% 7.20% 31.90% 28.40% 17.20% 9.10% 6.30% 100.00%
Source: Survey Results 2007 and 2008.
6.1.6 Availability of Electricity
Survey results (Table-32) revealed that in district Sanghar 140
representing 88 percent of the respondents agreed that electricity was available in their
village, while 19 representing 12 percent respondents replied that electricity was not
available in their village. Similarly in Badin district, 47 representing 30 percent of the
respondents reported that electricity was available; while 112 representing 70 percent of
the respondents living without facility of electricity. Sanghar district has the highest
number of respondents than Badin that agreed electricity was available in their respective
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villages. Similarly, Badin district has the highest number of respondents than Sanghar,
who reported that there was no electricity in their villages. The overall total number of
respondents was 318, 58.80% had electricity, while 41.20% had no electricity in their
houses. The above findings are in agreement with Nguyen (2007), who reported that
having access to electricity means better living standard.
Table-32 Availability of Electricity.
District
Electricity available
Total Yes No
Sanghar N 140 19 159
% 88.10% 11.90% 100.00%
Badin N 47 112 159
% 29.60% 70.40% 100.00%
Overall N 187 131 318
% 58.80% 41.20% 100.00%
Source: Survey Results 2007 and 2008.
6.1.7 Availability of Gas
The data regarding the availability of gas in the study area is summarized
in Table-33 and the results revealed that in Sanghar district, 5.20 percent of the
respondents agreed that gas was available, while 94.80 percent indicated that gas was not
available in their village. In Badin district, only 0.60 percent of the respondents had gas
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facility, while 99.40 percent of the people in Badin district had no natural gas facility for
cooking.
The comparative study of the two districts showed that more people in
Sanghar district were availing gas facility as compared to those living in district Badin.
Overall number of respondents was 315 and 2.9% had gas facility, while 97.10% were
without gas facility. These findings are in concurrence with those of Zaman and Aman
(2004), who reported that the poor are characterized by inadequate access to public
services in general. Only 52.2% poor households had electricity connections compared to
76% non-poor households; and gas connections existed in 10.9% of poor households
compared to 22.9% for non-poor households.
Table-33 Availability of Gas.
District
Gas is available
Total Yes No
Sanghar N 8 147 155
% 5.20% 94.80% 100.00%
Badin N 1 159 160
% 0.60% 99.40% 100.00%
Overall N 9 306 315
% 2.90% 97.10% 100.00%
Source: Survey Results 2007 and 2008.
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6.1.8 Type of House
Survey results (Table-34) revealed that in Sanghar district the majority of
respondents (38.90%) live in pacca houses, while the lowest (4.50%) live in Jhopra
houses; 24.20 percent and 32.50 percent live in semi pacca and katcha houses,
respectively.
In Badin district the highest majority of respondents (69.40%) live in semi
pacca houses(10); 10.00 and 13.10 percent live in pacca and Jhopra houses(11),
respectively. This shows that sample respondents in Sanghar district enjoy better housing
facilities than those in Badin district, based on the number of people living in pacca and
semi pacca houses, respectively. Overall number of respondents was 317 and 24.30
percent live in pacca houses, while 15.80 percent semi pacca houses, 51.10 percent
katcha houses(12) and 8.80 percent live in Jhopra houses. These results are in line with
those of Sharif (2003), who reported that in household size, dependency ratio and those
who build their house with mud and straw are the determinants that are significantly
correlated with the probability of being in extreme poverty in the study area of the
Punjab.
10. Pacca houses Cemented constructed houses
11. Jhorpra Houses of straws, mud and wood
12. Katcha Mud made houses
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Table-34 Type of House.
District Type of House Total
Pacca Semi Pacca Katcha Jhorpra
Sanghar N 61 38 51 7 157
% 38.90% 24.20% 32.50% 4.50% 100.00%
Badin N 16 12 111 21 160
% 10.00% 7.50% 69.40% 13.10% 100.00%
Overall N 77 50 162 28 317
% 24.30% 15.80% 51.10% 8.80% 100.00%
Source: Survey Results 2007 and 2008.
6.1.9 Availability of Toilet
It was noted (Table-35) in Sanghar district, 6.40 percent of the
respondents had non-flush toilet in their houses, while 37.60 and 56.10 percent had pit
latrines and open space toilets, respectively. Similarly, in Badin district, 1.30 percent
respondents had non-flush toilets, while 21.30 percent and 77.50 percent respondents had
pit latrines and open space toilets, respectively.
These results show that sample respondents in Sanghar district had better
toilet facilities than those in Badin district, based on the number of people having non
flush toilets and pit latrines in their houses. Overall number of respondents was 317 and
3.80 percent had non-flush toilets, 29.30 percent had pit latrines and 66.90 percent had
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open space toilets. The above findings are partially supported by Nguyen (2007), who
reported having a better toilet facility means better living standard.
Table-35 Toilet.
District
TOILET Total Non Flush Toilet/WC Pit Literine Open Space
Sanghar N 10 59 88 157
% 6.40% 37.60% 56.10% 100.00%
Badin N 2 34 124 160
% 1.30% 21.30% 77.50% 100.00%
Overall N 12 93 212 317
% 3.80% 29.30% 66.90% 100.00%
Source: Survey Results 2007 and 2008.
6.2 Loan Related Information
6.2.1 Source of Loan
Loan plays a great role in the livelihood of people living in the areas
having no certain sources of income to manage their households. (Table-36a) revealed
that in Sanghar district 84.38 percent of the respondents obtained loans from various
sources to manage livelihood, while 15.63% had no credit facilities.
Similarly, in Badin district, 45.63 percent of the respondents obtained
loans from different credit agencies, while 54.38 percent respondents did not obtain credit
facilities. This indicates that more people in Sanghar (84.38%) had access to credit
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facilities as compared to those in Badin district (45.63%). Furthermore, the greater
number (54.38%) of respondents in Badin had no access to credit facilities as compared
to those in Sanghar district (15.63%). Overall the number of respondents were 320 and
65.00 percent of them obtained the loans from various sources, while 35.00 percent did
not have credit facilities. These findings are in line with Cheng (2007) who reported that
majority of the house hold have no demand for micro credit because they do not
understand the lengthy and complicated procedures of banks.
Table-36a Source of Loan
District Loans obtained
Total Yes No
Sanghar N 135 25 160
% 84.38% 15.63% 100.00%
Badin N 73 87 160
% 45.63% 54.38% 100.00%
Overall N 208 112 320
% 65.00% 35.00% 100.00%
Source: Survey Results 2007 and 2008.
6.2.2 Institution of Loan
The responses of the people interviewed during the survey were
consolidated (Table-36b) regarding institution of loans and it was observed that in
Sanghar district, 31.10 percent of the respondents obtained loans from Banks, while
23.70 percent and 45.20 percent obtained their loans from NGOs and local money
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lenders, respectively. Similarly, in Badin district 43.80 percent of the respondents
obtained their loans from Banks, 23.30 percent from NGOs and 32.90 percent from local
money lenders; which indicates that the highest number of respondents obtained their
loans from local money lenders and the lowest from NGOs in Sanghar district, while in
Badin district, most of the respondents availed loaning facility of Banks and few of them
got loans from NGOs. In all, the number of respondents was 208, out of this 35.60
percent were facilitated by Banks, 23.60 percent got loans from NGOs and 40.90 percent
availed loan facility from local money lenders. Tipple and Coulson (2007) also were of
the similar experience and reported that many poor household who wanted to use formal
credit from banks found it impossible because of the complicated procedure.
Table-36b Institution of Loan.
District Institution of Loan Total
Bank NGO Local Lender
Sanghar N 42 32 61 135
% 31.10% 23.70% 45.20% 100.00%
Badin N 32 17 24 73
% 43.80% 23.30% 32.90% 100.00%
Overall N 74 49 85 208
% 35.60% 23.60% 40.90% 100.00%
Source: Survey Results 2007 and 2008.
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6.2.3 Recovery of Loan/Payment of Installments
The respondents in both the districts were also enquired for recovery of
loans and the results (Table-36c) showed that in Sanghar district, 96.30 percent of the
respondents paid their loans regularly, while 3.70 percent could not pay the installments
regularly. Similarly, in Badin district 97.26 percent respondents paid by installments
regularly, while 2.74 percent could not pay their loan by installments. This shows that
majority of the respondents both in Sanghar and Badin districts paid by installment
regularly.
The overall number of respondents was 208, out of them 96.63 percent
paid their loans by installments regularly, while 3.37 percent could not pay their
installments of loan as per the devised recovery schedule. The above findings are in line
with Padia (2005), who reported that repayment of loans offered by Dhan Foundation for
women’s empowerment was 98%.
Table-36c Whether Installments are Paid Regularly.
District Whether installments are paid regularly
Total
Yes No
Sanghar N 130 5 135
% 96.30% 3.70% 100.00%
Badin N 71 2 73
% 97.26% 2.74% 100.00%
Overall N 201 7 208
% 96.63% 3.37% 100.00%
Source: Survey Results 2007 and 2008.
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6.3 Human / Veterinary Centre Available
6.3.1. Availability of Human dispensary
Availing health facility of the state is the fundamental right of the people.
During survey, the respondents were asked to perceive on this aspect and responses are
summarized in Table-37. In Sanghar district, 31 percent of the respondents showed
positive perceptions on availability of human dispensary and 69.1 percent reported that
there was no human dispensary in their village. Similarly, in Badin district only 7.6
percent agreed that dispensary was available, while majority 92.40 percent perceived that
they had no dispensary facility. The overall number of respondents was 309, of which
19.1 percent reported the existence of human dispensary.
The findings of the present investigations are well comparable with those
of Zaman and Aman (2004), who reported that health facility is an important factor
which has direct influence to contribute to poverty and lack of health facilities leads to an
unhealthy society.
Table-37 Human Dispensary Available. District Whether dispensary available Total
Yes No
Sanghar N 47 105 152
% 30.90% 69.10% 100.00%
Badin N 12 145 157
% 7.60% 92.40% 100.00%
Overall N 59 250 309
% 19.10% 80.90% 100.00%
Source: Survey Results 2007 and 2008
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6.3.2 Availability of Veterinary Centre
Livestock play an important role in the livelihood of rural population of
the country. Survey results in Table-38 show that in Sanghar district 14.1 percent of the
respondents agreed that veterinary centre was available in the vicinity, Similarly, in
Badin district 1.3 percent of the respondents reported the existence of veterinary centre,
in their village.
The overall number of respondents was 315, of which 7.6 percent
perceived existence of veterinary centre, while 92.4 percent reported that there was no
veterinary centre in their village. This shows that people need veterinary hospitals/
centres, so as to improve the health and nutritional status of their animals.
Table-38 Availability of Veterinary Centre.
District Veterinary Centre Available Total
Yes No
Sanghar N 22 134 156
% 14.10% 85.90% 100.00%
Badin N 2 157 159
% 1.30% 98.70% 100.00%
Overall N 24 291 315
% 7.60% 92.40% 100.00%
Source: Survey Results 2007 and 2008.
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6.4 Househould Income
Income of the household is the key element that affects living status of
people. Information presented in Table-39 shows that the average household income in
Sanghar district was Rs.9926±639 per month, while the income per person was
Rs.1231.00 per month. Similarly, in Badin district the household income was Rs.7463.00
±494.00 per month, with average per person income of Rs.1194.00 per month. This
indicates that the people in Sanghar district had higher household and individual income
than those in Badin district.
Table-39 Household Income.
Particular DISTRICT Mean Standard Error
Household Income
Sanghar 9,926 639
Badin 7,463 494
Total 8,687 408
Income per Person
Sanghar 1,231 76
Badin 1,194 91
Total 1,213 59
Source: Survey Results 2007 and 2008.
150
6.5 Household Income by Profession
6.5.1 Household Income by Profession in district Sanghar
Figure-2 illustrates that majority (50%) of the respondents in Sanghar
district belonged to agricultural profession, while 14.4 percent were businessmen/
shopkeepers, about 10% were labourers and 7% milk sellers. Similarly, equally 3% each
belonged to teaching, carpentry and artisans, respectively, and equally 2% of the
respondents belonged to poultry, mechanic, service, embroidery and electrical
professions, respectively. It indicates that in Sanghar district, most of the people belongs
to agriculture profession and business/shop keeping, which has proved to be the most
important among other professions.
Fig. 2. Household Income by Profession of Sanghar
151
6.5.2 Household Income by Profession of Badin
Household income by profession of Badin is shown in Figure-3, which
illustrates that majority (44%) of the respondents in Badin district are engaged in
agriculture profession, while 9% and 8% were labourers and businessmen, respectively.
Similarly, 5% each were mechanics and teachers and 4% each were government
employees and artisans. Fishing and carpentry were the professions each of 3%, while on
the same proportion 2% of the respondents were engaged with embroidery making,
electrician and blacksmith, respectively. This implies that in Badin district, agriculture
and wage labour has proved to be the most important professions based on the data
presented.
Fig. 3. Household Income by Profession of Badin.
152
6.5.3 Household Expenditure on Different Items for Sanghar District
Household expenditure on different items for Sanghar district is shown in
Figure-4, which illustrates that majority of the respondents in the study area spent major
portion of income (46%) on food items. Only 9% of the income was spent by the
respondents on health care while, an equal proportion (8%) of their income was reported
to be spent on transport, education and clothing / shoes, etc. Similarly they spent 5% of
their income on payment of electricity bills and 2% on payment of telephone bills. About
15% of the income was spent on other heads (miscellaneous). This shows that majority of
the respondents in Sanghar district spent their income on the most important items i.e.
food, health, transport and education, respectively; while the smaller part of their income
they spent on clothing, electricity bills, phone bills and other miscellaneous expenditures.
Segregated data by status of poverty in Sanghar district revealed that for
poor households more budget was recorded on food (48% for poor and 45 for non-poor)
items. This could be due to more number of household members in comparison of non-
poor. Besides this, more proportion of budget was found on health, which may also be
attributed to bigger household size and poor health condition of the family members. On
the contrary, more proportion of budget of non poor families was recorded on transport,
education, clothing, electricity, and phone, which clearly depicts the picture of wellbeing
of non-poor household in comparison of poor houeholods.
153
Fig. 4. Household Expenditure on Different Items for Sanghar.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Pro
po
rtio
n o
f H
ou
seh
old
Bu
dg
et
Misc. 17% 10% 14%
Phone 2% 3% 2%
Electricity 4% 6% 5%
Clothing 6% 11% 8%
Education 4% 9% 8%
Transport 7% 8% 8%
Health 12% 8% 9%
Food 48% 45% 46%
Poor Not Poor Overall
6.5.4 Household Expenditure on Different Items for Badin District
Figure-5 shows the household expenditure on different items for Badin
district, which indicated that the respondents spent 47% of their income on purchasing
food items; while 8% of the income was spent on transport and 7% on health care. About
6% of their income was spent on clothing / shoes etc. and only 4% of the income was
spent on education. Similarly, on the same proportion, 3% of their income was spent each
on payment of electricity and telephone bills, respectively. This implies that respondents
in Badin district spent most of their income on food, health, transport and education,
while, a smaller part of their income was spent on clothing / shoes, payment of electricity
and phone bills and other miscellaneous expenditures.
154
The findings illustrated in Figure-4 and 5 are further supported by Bhatti
(1990) who reported that fishermen in Sindh province spent about 45% of their income
on food, 4.0% on clothing, 1.7% on transport and 6.5% on other expenses. This implies
that they were living the life below the poverty line.
Segregated data by status of poverty in Badin district revealed that for
poor household more budget was recorded on food (49% for poor and 46% for non poor).
Similarly more proportion of budget was found on health (13% for poor and 7% for non
poor). Likewise more proportion of budget of non poor families was also recorded on
telephone, electricity, clothing, education and transport. This shows that the non poor
possesses better economic status as compared to poor households in the study area.
Fig. 5. Household Expenditure on Different Items for Badin.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Pro
po
rtio
n o
f H
ou
seh
old
Bu
dg
et
Misc. 18% 11% 22%
Phone 2% 4% 3%
Electricity 2% 4% 3%
Clothing 6% 11% 4%
Education 3% 8% 6%
Transport 7% 9% 7%
Health 13% 7% 8%
Food 49% 46% 47%
Poor Not Poor Overall
155
6.6 Poverty Measurement
6.6.1 Head Count Ratio
The head count index may be defined as;
Where
HCI = Head count index
h = Number of poor
n = Population
6.6.2 Headcount Index
Information presented in Table-40 shows that in district Sanghar 52.00
percent of the respondents come under the category of poor, while 48.00% were not poor.
Similarly, in Badin district, head count index was 56.2 percent, while 43.8 percent were
reported not to be poor. This implies that Sanghar district has the higher number of
people living above the poverty line as compared to those in Badin district, which has the
higher number of people living below the poverty line or in ultra poverty as shown in the
table. The overall number of respondents was 320, of which 54.10% were poor, while
45.90% were not poor. The findings of the present study are further supported by Arif
(2000), who reported that in the wheat-cotton zones of Sindh province, the incidence of
poverty was upto 57.5 percent. Similarly, according to the World Bank (2002), in
Pakistan nearly 57% of the households are prone to falling into poverty when clustered
n
hHCI
156
around the poverty line. Likewise, Hussain et al. (2006) identified poverty and head
count index, it was found to be 33.00 percent in the area. However, poverty head count
indices were 50, 34, 20, 37, 43, 33 and 19 percent for Jand Pindi Ghaib, Fateh Jang,
Attock, Gujar Khan, Kahuta, Rawalpindi, Talagang and Chakwal areas of the Punbjab
province, respectively.
Jamal (2006) correlates household consumption or poverty using the latest
household survey in Pakistan by Logistic regression and found that 55.01% people in the
study area are poor, while 89.19% are not poor. Baye (2005), stated that the poverty
profiles in 1996 show the spread, death and severity of poverty in Cameroon was higher
in rural than in urban areas. Thus, policy measures to assist the poor in Cameroon should
focus on rural areas. The above findings are partially supported by Gelbard et al. (2005),
who reported that in 2003 poverty was only 22 percent in urban areas while in rural areas
it was 38 percent, suggesting that poverty is more in rural areas than in urban areas.
Similarly, Bayu et al. (2007) predicted poor and non poor using Logistic model, and
found that 58.7% people in the study area of Indonesia are poor, while 32.3% are not
poor. The above findings are partially supported by Sharma (2007), who reported that
lack of alternatives opportunities significantly increased poverty in the country. The
intensity of poverty was more in rural areas than in urban areas. These findings were
further supported by Siddique (2000), who reported that head count ratio of Bangladesh
was 53.1% for rural areas, while for urban areas it was 36.6%. This shows that the
incidence of poverty is more in rural areas than in urban areas. The present findings are
partially supported by Mitra (1993), who reported that 54% of families in rural areas of
Arunachal Pradesh were poor in 1993. These figures are likely to increase in the coming
157
years if poverty alleviation measures were not adopted. Similarly, findings were also
reported by Kabann et al. (2009), that in rural areas of Ugunda female headed household
are more likely to be poor than their male counterparts. The older the household head the
greater the chance that he will be below the poverty line. More children in household
appear to be associated with poverty and poverty appears to be associated with greater
number of households.
Table-40 Head Count Index.
District
Poverty Status Total
Poor Non Poor
Sanghar N 83 77 160
% 51.9% 48.1% 100%
Badin N 90 70 160
% 56.2% 43.8% 100%
Overall N 173 147 320
% 54.10% 45.90% 100%
Source: Survey Results 2007 and 2008.
158
6.6.3 Poverty Gap Results
Where
TPG = Total poverty gap H = No of the poor who fall below poverty line yp = Poverty line yi = Income of the poor
yp = Rs. 1000 1000 – 627 = 373
yi = Rs. 628
yp = Rs. 1000 1000 – 644= 356 yi = Rs. 644
6.6.5 Sen Index Results
where:
P = number of people below the poverty line N = total number of people in society B = poverty line income A = average income of those people below the poverty line
Sanghar = 83 x 1000 – 627 = 0.31
160 627
Badin = 90 x 1000 – 644 = 0.31
160 644
Sanghar
Badin
159
6.6.6 Poverty Gap and Sen Index
Poverty gap and sen index were summarized and presented in Table-41,
which showed that in Sanghar district the average poverty gap was Rs.373 only, while in
Badin it was reported to be Rs.356 only. This shows that the amount of income required
to remove the poor out of poverty is much higher in Sanghar than in Badin district. The
Sen index both for Sanghar and Badin districts was equally 0.31. The sen index shows
that the intensity or severity of poverty in the two districts remained the same. The
overall poverty gap and sen index was reported to be 364 and 0.31, respectively.
The results of the present study are in agreement with Jamal (2006), who
reported that, the incidence, depth and severity of poverty is high in rural areas as
compared with urban areas.
Table-41 Poverty Gap and Sen Index.
District Poverty Gap Sen Index (Severity) Sanghar 373 0.31
Badin 356 0.31
Overall 364 0.31
Source: Survey Results 2007 and 2008.
160
6.7 Inequality Measurement
6.7.1 Lorenz Curve of Sanghar
Figure-6 shows Lorenz curve and Gini coefficient, for district Sanghar. To
compute the Gini coefficient, first the area of lower triangle and area under curve was
calculated. The shaded area was further divided by area of lower triangle. This gives that
0.37, the quotient is the Gini coefficient, a measure of inequality. In other words, the Gini
coefficient is the shaded area in Black. Lorenz curve shows the cumulative share percent
of income earned on the vertical axis against the cumulative share percent of people from
lower income. Quadratic model was developed to estimate the area under Lorenz curve
y = a x + b x + cx2, which is the requirement for computing Gini coefficient. If the gap
between the perfect distribution line and Lorenz curve is high, it implies that there is
inequality in the distribution of income. If the Lorenz curve goes down, this shows that
most of the people in the study area have low income, only few possessed most part of
the income.
Similarly, Saboor (2004) estimated income inequality in rural Sindh to be
0.386 in 1998-99 and 0.387 in 2001-02. This indicates that the impact of inequality in
increasing poverty is somewhat greater than the growth in average income in reducing
poverty. Sharif (2003), in his poverty analysis in Cholistan Punjab, concluded that land
distribution is highly unequal with a Gini coefficient of 0.68. The degree of inequality in
income distribution is lower than a Gini coefficient of 0.36. It was found that the
estimates are very close to Lin et al. (2008), who reported that rural inequality was still
higher than urban inequality with Gini coefficient of 0.349 and 0.341, respectively.
161
Fig.6. Lorenz Curve of Sanghar.
6.7.2 Lorenz Curve of Badin
Lorenz curve was used to know the inequality in the distribution of
income that exists in the study area and figure-7 shows the results of Lorenz curve and
Gini coefficient. To compute the Gini coefficient first the area of lower triangle and then
area under curve was calculated. The shaded area was further divided by the area of
lower triangle, which gives 0.38; the higher the coefficient, the more unequal the
distribution of income. Lorenz curve shows the cumulative share percent of income
earned on the vertical axis against the cumulative share percent of people from lower
162
income. Quadratic model was developed to estimate area under Lorenz curve y = ax + bx
+cx2, which is the requirement for computing Gini coefficient.
More accurate results can be obtained by using other methods to
approximate the area B, such as the Lorenz curve is approximated with quadratic function
between intervals, or can build on the right approximation to the distribution function that
goes with the known data. If the population mean and boundary values are known, it can
be used to improve the accuracy of the approximation (Gini, 1921 and Xu, 2004).
The above findings presented in Figure-6 and 7 are in accordance with
Malik (1996), who have worked on the overall poverty trend in rural areas of Pakistan.
Survey results from villages show a highly skewed landholding pattern with a Gini
coefficient of 0.56% of the 100 household surveyed. It was found that only 10 of the 19
in the landless category were categorized as poor, although the intensity of the poor was
found to be particularly severe amongst the landless and most of the poor in this village
come from the landless category. These results are partially in line with the report of
Mahbubul Haq Centre for Human and Development, Islamabad, reported that the overall
trends in gini coefficient in Pakistan in 1979 was 0.37, while the Gini coefficient was
0.31 and 0.38 for rural and urban areas, respectively. The results of the present study are
also in agreement with Siddique (2000), who reported that the gini coefficient of
Bangladesh in 1996 was 0.38, for rural areas it was 0.364 and urban areas 0.381; urban
inequality increased from 0.381 to 0.45.
163
Fig.7 Lorenz Curve of Badin.
6.8 Logistic Regression Model Analysis 6.8.1 Logistic Regression Model Where y = Binary dependent variable (y = 0 for poor, and y = 1 for non poor) e = The base of natural logarithms and
z
z
e
ey
1)Pr(
164
With constant β0 coefficient, βj are predictors for p predictors (j = 1,2,3……p) Proposed X1, X2, X3 ……………….Xn (Independent Variables) could be Dependency ratio, number of earners, educations of household head, etc. 6.8.2 Poverty Status of Significant Predictors in Sanghar
Figure-8 displays poverty predictors using Logistic Regression Model,
which was applied primarily for Sanghar district. Dependent variable was poverty status
and the significant independent variables were land ownership, household size, number
of earners and qualification of household. The empirical results show that land ownership
and household size were significant at P<0.01. Similarly, the number of earners and
qualification of household heads were significant at P<0.05; this indicates that number of
earners and qualification of household heads has higher significance level than land
ownership and number of earners. Choudhary et al. (2009) reported that in the regression
analysis household size, land holding and age of household were found to influence the
dependent variable per capita income in a significant way.
165
Fig. 8 Poverty Status of Significant Predictors in Sanghar
6.8.3 Poverty Predictors Using Logistic Regression Model for Sanghar district
Table-42 illustrates the poverty status of significant predictors in Sanghar
district, and the segregated data based on without land ownership unveiled that 58%
respondents were poor, while 43% were non poor, and those who owned land, 38% were
poor and 62% were non poor. Similarly, family members upto 6.28% were poor and 73%
were non poor. The family members above 6.63% were poor and 37% were non poor.
Those earning upto 25%, 64% of them were poor and 36% were non poor, while, those
earning above 25%, of them 41% were poor and 59% were non poor. On the other hand,
166
family members educated upto primary level, 58% were poor and 42% were non poor.
Similarly, those educated above primary level, 40% were poor and 60% were non poor.
The analysis concludes that family members who were owners of land had higher living
standard than those without land. Similarly, of family members upto 6 members, 73%
were living above the poverty line, while 28% remained in poverty. On the other hand,
those earning upto 25%, 64% of them remained in poverty, while 37% were living above
the poverty line. However, those earning above 25%, 59% of them live above the poverty
line; of the household members educated upto primary level 58% live below the poverty
line, while 42% live above the poverty line. Likewise, those educated above primary
level, 40% of them live below the poverty line and 60% have gone out of poverty.
The above findings are in concurrence with those of Saboor (2004), who
reported that the non-farm households in Sindh suffer more from poverty as compared to
farm households. The average income is important parameter in explaining the variation
in the incidence of poverty. All factors such as land ownership, literacy rate, family size
etc influence the poverty significantly. The above findings are in similarity to those of
Sharif (2003), who reported that in Cholistan province of the Punjab, 69.54 percent
household are extremely poor, and 75.77 percent in terms of population, bulk of the
extreme poor is found among the small farm owners and landless households. Similarly,
Zaman and Aman (2004) argued that education is the most important factors
distinguishing the poor from non poor in Pakistan, poverty declines as education of
household head increases. HIES household income expenditure survey data 1998-99
showed that 42% of the population living in households with illiterate heads are poor as
compared to 21% of households with literate household heads.
167
Table-42 Poverty Predictors Using Logistic Regression Model for Sanghar B SE Wald Sig
Constant 0.461 0.557 0.686 0.407
Land Ownership (No land =0 & Land Owner = 1)
1.613 0.462 12.203 0.000**
Household Size (up to 6 members = 0 & Above 6 Members = 1)
-1.381 0.439 9.878 0.002**
Number of Earners Up to 25% of HHs = 0 & Above 25% members = 1)
1.046 0.461 5.150 0.023*
Qualification of Household Head (Up to Primary = 0 & Above Primary = 1)
0.806 0.379 4.522 0.033*
Poverty Status: Poor = 0 Non poor = 1 Correctly Define 85% Ns= Non Significant; * = Significant at 5%; **=Significant at 1%
6.8.4 Poverty Predictors Using Logistic Regression Model for Badin district
The results in Table-43 revealed the poverty predictors using logistic
regression model, which was applied to primary data for Badin disrict. Dependent
variable was poverty status, while the independent variables were land ownership,
household size, number of earners and qualification of household head. Empirical results
show that land ownership, number of earners and qualification of household head were
significant at P<0.05. On the other hand, only number of earners were significant at
P<0.01. This indicates that land ownership, number of earners and qualification of
household head has a better significance level than the number of earners.
The findings presented in Table-42 and 43 are well supported by Qureshi
and Arif (1999), who recorded a higher incidence of poverty among the non-farm
households in all provinces of Pakistan based on the HIES data for 1993-94 and 1998-99.
168
Similar analysis were reported by Kemal (2003) for the HIES data (2001-02), who found
a higher incidence of poverty among non farm households in all zones except in Barani
Punjab in 1993-94 and 1998-99.
Table-43 Poverty Predictors Using Logistic Regression Model for Badin. B SE Wald Sig
Constant 1.059 .877 1.458 .227
Land Ownership (No land =0 & Land Owner = 1)
2.763 1.341 4.242 .039*
Household Size (up to 6 members = 0 & Above 6 Members = 1)
-2.829 .455 38.628 .000**
Number of Earners Up to 25% of HHs = 0 & Above 25% members = 1)
2.126 .856 6.170 .013*
Qualification of Household Head (Up to Primary = 0 & Above Primary = 1)
.963 .511 3.553 .050*
Poverty Status: Non poor = 0 & Poor = 1 Correctly Define = 84% Ns= Non Significant; * = Significant at 5%; **=Significant at 1%
6.8.5 Poverty Status of Significant Predictors in Badin
Figure-9 presents poverty status of significant predictors in Badin district
and the respondents were enquired for their responses regarding ownership of land.
Accordingly, 58% of those without land were poor, while 42% were non poor. On the
other hand of those who owned land 22% were poor and 78% were non poor. Family
members, upto 6.22% were poor and 78% were non poor and families with above 6
members, 85% were poor, while 15% were non poor. Sample respondents earning upto
25%, 94% were poor while 6% were non poor; of those earning above 25%, 47% were
poor, while 53% were non poor. It was noted that 62% of the family members educated
169
upto primary level, were poor, while 38% were non poor. Similarly 4% those of educated
above primary level were poor and 59% were non poor.
The analysis concluded that the respondents without land were living life
below the poverty line, while those who own land majority of them escaped the poverty
menace. Similarly, among the families upto 6 members, majority were living above
poverty line, while families above 6 members, majority were living life below the
poverty line. Those earning upto 25%, majority of them were poor, while those earning
above 25%, a small proportion of them were under the poverty line. On the qualification
of household head majority of the respondents educated upto primary level, remained
below the poverty line, while majority of those educated above primary level were living
life above poverty line in the study area. The above findings are in agreement with
Bastin and Nicola (2007), who reported that lack of full land ownership acts as a double
constraint on agriculture productivity and increase the number of household likely to
become poor instead of escaping the poverty menace.
These results are further in line with those of Ashraf et al. (1999), who
estimated the incidence and determinants of rural poverty in the Punjab with special
reference to non farm household category. Similar results have also been reported by
Javed and Khilji (2008), who reported that as education level of head of the family
increases, he will go out of poverty and the education of other family members increases.
Furthermore, Khan (2008) reported that poverty status is clearly related to land holdings.
This means that those who have access to land ownership will go out of poverty and
those who have no access to land are likely to remain in poverty. Amara and Sial (2009)
170
also reported that ownership of land reduces the risk to enter into poverty. These findings
are also in line with Quasem (2004), who reported that majority of the landless household
remains poor and their children has no access to education in comparison to landowners
in the study area. In a study, Emtage et al. (2007) reported that lack of access to land as
the major cause of poverty. Households that are below the poverty line cannot be
expected to devote time and resources to non profitable business.
Fig.9 Poverty Status of Significant Predictors in District Badin
171
6.9 Multiple Linear Regression Model Analysis 6.9.1 Multiple Linear Regression Model Multiple linear regression model was used to know the relationship
between 1 dependent and 2 or more independent variables. It is used to know the
influence of independent variable on the dependent variable multiple linear regression
model was applied to primary data collected from Badin district.
1. Relationship between 1 dependent & 2 or more independent variables is a linear
function
6.9.2 Multiple Linear Regression Model Data for Badin
Multiple linear regression model data for Badin shown in Table-44
revealed that dependent variable was per capita income, while the independent variable
was land ownership, household size and number of earners. Multiple linear regression
model was applied to primary data collected from certain areas of Badin District. The
results showed that land ownership is significant at P<0.01. Similarly household size and
number of earners were also significant at P<0.01 each, respectively.
172
The analysis revealed that the qualification of household head was
excluded because the probability was more than 5% of the p-value. So, it can be said that
the results are satisfactory and provide better basis for policy formulation and suggested
future in depth research in the study area. The above findings are partially supported by
Choudhary et al. (2009) who reported that in the regression analysis household size, land
holding and age of household were found to influence the dependent variable per capita
income in a significant way.
In another study, Wang et al. (2007) reported that both multiple linear
regression model and logistic regression model can accurately predict over 50% which
households are poor. The logistic regression model performs better than the multiple
linear regression model in terms of predicting poverty status of the households. Similarly,
Pingping Wang (2007), suggested that the logistic regression model is more accurate than
the multiple linear regression model.
y = βo+β1X1+ β2X2+β3X3
y = Pc income (poverty status)
βo = Intercept
β1 β2 β3 = Slopes
X1 = LO Land Ownership
X2 = HS Household size
X3 = NE Number of earners
y = 957.171+2510.967LO+61137HS+547.934NE
173
Table 44 Multiple Linear Regression Model Data for Badin.
Unstandardized
Coefficients Standardized Coefficients
T Sig.
B Std.
Error Beta
(Constant) 957.171 230.818 4.147 .000 Land Ownership (No land =0 & Land Owner = 1) 2510.967 343.895 .471 7.302 .000** Household Size (up to 6 members = 0 & Above 6 Members = 1) -611.372 159.655 -.261 -3.829 .000** Number of Earners Up to 25% of HHs = 0 & Above 25% members = 1) 547.934 202.116 .184 2.711 .007**
R-square = 0.380 Dependent Variable: Per Capita Income Ns= Non Significant; * = Significant at 5%; **=Significant at 1%
6.9.3 Normal Probability Plot of Multiple Regression Model
Fig 10 shows the normal probability plot of multiple regression model.
The graph show that before transformation errors are not normally and independently
distributed.
174
Fig.10. Normal Probability Plot of Multiple Regression Model
Assumption 1: Errors should be normally and independently distributed Remarks: Assumption does not withstand/ satisfy
6.9.4 Regression Residuals
Fig 11 shows the regression residuals. Before transformation it is not
normally distributed. Increasing variance of errors when original data were used.
175
Fig.11. Regression Residual Plot
Assumption 2: Variances of the errors should be constant Remarks: Assumption does not withstand/satisfied
176
6.9.5 Multiple Linear Regression Model of Transformed Data for Badin
As it is evident from Table-45, the dependent variable is per capita
income, while the independent variables were land ownership, household size and
number of earners. Multiple linear regression model was applied to primary data from
Badin. The results showed that land ownership was significant at P<0.01. Similarly,
household size and number of earners were also significant at P<0.01. This indicates that
the regression results were quite good. It was also observed that our coefficient of
determination (R2) value was high because most of the regression coefficients showed
significant results.
Table 45 Multiple Linear Regression Model of Transformed Data for Badin. Unstandardized
Coefficients Standardized Coefficients
t Sig.
B Std. Error
Beta
(Constant) 6.353 .131 48.369 .000 Land Ownership (No land =0 & Land Owner = 1)
.818 .194 .253 4.219 .000**
Household Size (up to 6 members = 0 & Above 6 Members = 1)
-.440 .090 -.308 -4.891 .000**
Number of Earners Up to 25% of HHs = 0 & Above 25% members = 1)
.779 .115 .425 6.760 .000**
R-square = 0.46 Dependent Variable: Per Capita Income Ns= Non Significant; * = Significant at 5%; **=Significant at 1%
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6.9.6 Normal Probability Plot of Multiple Regression Model Using Transformed Model
Fig 12 show the normal probability plot of multiple regression model
using transformed data. After transformation the errors obtained are normally distributed.
Errors are values we get after subtracting the effects of independent variable from
depending variable.
Fig.12. Normal Probability Plot of Multiple Regression Model Using
Transformed Model
Assumption 1: Errors should be normally and independently distributed Remarks: Assumption withstands/Satisfied
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6.9.7 Regression Residual Plot Using Transformed Values
Fig 13 shows the regression residual plot using transformed values. After
transformation it is normally distributed. The variance errors becomes the same.
Fig.13. Regression Residual Plot Using Transformed Values.
Assumption 2: Variances of the errors should be constant Remarks: Assumption withstands/satisfied
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Logistics regression model for both Sanghar and Badin revealed that
dependent variable (poverty status) is correlated with independent variables viz. land
ownership, household size, number of earners and qualification of household head.
Logistic regression is assumption free model while Multiple linear
regression has two assumptions to be tested for valid conclusions.
Logistic regression model defined 85% cases correctly about poverty
status (poor or non poor) while multiple linear regression reported R-square 0.46, which
revealed that about 46% variation in dependent variable (per capita income) were
accounted for by independent variables. (Shahbaz et al. 2009) utilizes data from 1991 to
2007 in his research study on economic growth and its determinants in Pakistan.
Logistics regression model has been constructed to find the required linkages. It provides
better results than simple or multiple linear regression models. Chaudhary et al. (2009)
also reported that logistic regression model was used in analyzing the determinants of
rural poverty. The results shows that household size, dependency ratio, the presence of
female household head and residence in a katcha house was positively and significantly
correlated with the probability of being poor. Variables that were negatively and
significantly correlated with the probability of being poor were educational attainment of
households head, literate household head whether the household head is a farmer or
labourer, age of household head, household visit to health centre and landlholdings.
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6.10 Results of Hypothesis Testing
Based upon Logistics Regression results the following hypothesis have
been tested and reported.
(1) Poverty depend upon respondents or household characteristics that is educational
level.
(2) Poverty depends upon agro-economic indicators that is land ownership.
(3) Poverty depend upon household characteristics that is household earners and
proportion of earners total household size.
On the basis of the above null hypothesis is rejected and alternate
hypothesis is accepted.
6.11 Conclusions
This chapter present the results of house hold survey data analysis.
Various statistical models were used in the analysis of data. The comparative analysis of
the two districts shows, that Sanghar district is better up in almost all the indicators used
in this analysis, than Badin district. The major reason why Badin district remain
underdeveloped for a very long time was, the extreme natural disasters had adversely
affected the district. This has resulted in general disruption of livelihoods, increased
vulnerability, and in some cases led to out migration.
It is concluded that household size, number of earners and qualification of
households head has a significant effect on poverty.
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CHAPTER-VII
7.0 PRIMARY DATA ANALYSIS AND DISCUSSION OF VILLAGE DEVELOPMENT ORGANIZATIONS (VDOs)
7.1 Introduction
Village development organizations VDO’s are a step towards participatory
rural development. It has been globally recognised that any programme focusing on rural
development cannot achieve its goals unless, the target communities are willing to
actively participate, in the programme implementation to ensure sustainability. (VDO
Assessment Report Sanghar, 2007).
In order to ensure the participation of communities in development
programmes, they are first mobilized and motivated through a variety of methods. Once
the communities are mobilized, they are motivated to form VDO’s to have a common
collective platform where representation of every community member is ensured. These
community organizations are strengthend by building the capacity of their members.
They are considered as local resource for successful implementation of development
programmes. (SAFWCO research Report, 2006).
Social mobilization is an important tool used by VDO’s to engage
people’s participation in achieving a specific development goal through self-reliant
efforts. It involves all relevant segments of the society, including decision and policy
makers, opinion leaders, bureaucrats, technocrats and industrial associations etc. it also
aims at mobilizing the necessary resources, disseminating information tailored to target
audience, generating inter-sectoral process.
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The process of developing active and sustainable VDO’s is based on
social justice and mutual respect for all. Members of VDO’s in this process, enable
connections to be made between communities and government departments responsible
for rural development (Fatima, 1997).
There are 50 VDO’s working for poverty alleviation in each district
Sanghar and Badin. However due to limitation of time and financial status of the
researcher only 10 village development organizations, on the basis of their increased
involvement were selected. A sample of 62 members and officials of VDO’s were
selected for conducting the interview. The investigation was carried out by the researcher
himself to get the accurate information. The list of VDO’s in both Sanghar and Badin
districts are as follows:
a. Sanghar District
Village welfare Development Organization Mohammad Khan Khaskhelli.
Village Development Organization Mua Chora
Village Welfare Development organization Shah Mardan Abad.
Female Welfare Development Organization Ahmad Khan Khaskhelli Village.
Indus Welfare Association Kurkali village.
Village Welfare Development Organization Murad Ali Rind.
Nojwaw Etehad village Development Organization Essan Chandio Village.
Village Development Organisation Sher Khan Lashari.
Rashida Social Welfare Development Organization Kheto Jat Village.
Village Development Organization Daim Thahim.
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b. Badin District
Village Development Organization Arab Sheedi.
Village Development Organization (male and female) Bughro Mall.
BRDS Village Development Organization Ishaq Khaskhelli.
Village Development Organization Mircho Mall.
Darya Khan khaskhelli Welfare Organization.
Juman Mallah Welfare Organization.
Bahar Community Organization Buxkho Dero.
Village Development Organization Deenar Khan Talpur.
Village Development Organization Umar Khaskhelli.
Village Development Organization Punhoo Pali.
Data gathered through survey were analysed using frequency distribution
and corresponding percentages.
Survey results and analysis of VDO’s in both Sanghar and Badin districts
are presented as follows:
7.2 Survey Results of VDOs in District Sanghar
7.2.1 Activities of VDOs to Alleviate Poverty
Thirty eight (38) out of 62 representatives of VDOs were of the opinion
that social mobilization programmes were launched, and 56.5% of the respondents agreed
that microcredit was disbursed to the community for poverty alleviation, while 43.5%
were satisfied over awareness programmes in order to enlighten the poor. Considering
human resource development to be important, 29% of the respondents received trainings
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to improve their knowledge, exactly the same proportion (29%) of the representatives
agreed that self employment leads to prosperity. About one fourth (24%) of the
respondents were in favour of activities about “savings” launched in their village (Table-
49). According to 12.9% of the respondents empowerment activities were not
satisfactory, and suggested further improvement.
Similarly, self reliant and development work were implemented with
success according to 11.3% and 9.7% respondents; regular meetings were held and
participation was satisfactory as perceived by 8.1% and 4.8% of the respondents,
respectively. Overall, social mobilization has proved to be the most important activity in
the area, while regular meeting was the least important activity considered by the
respondents in the study area. The above findings are in line with Rajivan (2005) who
reported that awareness building and empowerment are the most important tools in
poverty alleviation.
Table- 46 Activities of NGOs to Alleviate Poverty. S.No. Particulars Number Percent 1. Social Mobilization 38 61.3 2. Microcredit 35 56.5 3. Awareness 27 43.5 4. Trainings 18 29.0 5. Self Employment 18 29.0 6. Savings 15 24.2 7. Empowerment 8 12.9 8. Self Reliant 7 11.3 9. Development work 6 9.7 10. Regular Meetings 5 8.1 11. Participation 3 4.8 Source: Survey Results 2007.
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7.2.2 Empowerment and Participation in the Community
Progress on empowerment and participation has been summarized in
Table-47, which indicates that 50% of the respondents agreed that the progress towards
empowerment was satisfactory, while 37% of the respondents perceived inadequacy of
funds to implement projects, while 16% organized team building / leadership activities to
develop leadership skills of the respondents. Progress towards empowerment was not
satisfactory according to 13% of the respondents; this implies that there was a need to
focus on empowerment which has been an important activity. The young generation
needs technical skills to become self reliant as perceived by 11.2% respondents, while
effective leaderships is needed to achieve a positive change in the community only was
the suggestion of 16% respondents to adopt it. It is obvious that the overall empowerment
and participation in the community was satisfactory as perceived by majority of the
respondents in the study area.
Similar results have also been reported by Hamayun (2004), who studied
AKRSP (Aga Khan Rural Support Programme) intervention for women in Chitral
district. These include formation of women organization, team building/leadership skills,
and technical skills for self reliance, imparting various trainings and providing credit to
women to purchase farm inputs used for income generating business. Jalaluddin (2003)
reported that empowerment provided to the farming community has helped them to
address the genuine issues regarding their livelihood.
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Table-47 Empowerment and Participation in the Community. S.No. Particulars Number Percent 1 Progress of Empowerment Satisfactory 31 50 2 Funds are Needed to Implement Project 23 37 3 Team Building / Leading 10 16 4 Progress of Empowerment not Satisfactory 8 13 5 Technical Skills for Self Reliance 7 11.2 6 Effective Leadership 1 1.6 Source: Survey Results 2007.
7.2.3 Perception about Proper Utilization of Microcredit Loans
The results in Table-48 present the perception on proper utilization of
microcredit loans and it was noted that 66% of the respondents had positive perceptions
on proper utilization of microcredit loans. Due to these loans, a substantial increase was
reported in household income. Nearly one fourth (26%) of the respondents were of the
opinion that agricultural loans should be recovered after a fixed period of time i.e. 6
month while for business in 1 year.
This is a very important process; it should be adhered strictly so as to
avoid wasteful expenditure, because 12.9% of the respondents believe that loans were not
properly utilized. In view of the above, there is a need for regular mobilization of the
community on the importance of proper utilization of credit. However, majority of the
respondents agreed that overall loans were properly utilized and this has changed the
lives of the poor in the area of study.
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Table-48 Perceptions about Proper Utilization of Microcredit Loans. Perceptions Number Percent
Loan was Properly Utilized 41 66.1 Agriculture loan should be recovered after 6 month and small business loan in one year
16 25.8
Loans were not properly utilized properly 8 12.9 Source: Survey Results 2007.
7.2.4 Status of Health and Nutrition
It is apparent from the survey results (Table-49) that 53.2% of the
respondents were of the view that health facilities were in bad shape and need
improvement. On the other hand, due to establishment of health centre in their village,
21% of the respondents perceived that status of health and nutrition has improved.
Similarly, 13% had the opinion that they are establishing a dispensary on self help basis
so as to improve health care in the area. Only, 8.0% argued that health and nutrition was
improved after the formation of VDO. Equally, the same proportion (8.0%) of
respondents believed that health condition of the people is fair, while 4.8% perceived that
awareness through seminar/training was provided on health and nutrition with success.
Due to lack of health care facilities in their village, 3.2% reported that only minor cases
are treated here and major cases were sent to Shahdadpur city hospital. Overall, the status
of health and nutrition was not satisfactory; the community and VDOs should put their
heads together to address the issue. Similarly, the above findings are in agreement with
Gera (2007), who reported that despite noble intensions of the government in addressing
health and nutrition issues, the prevailing conditions and health care particularly in rural
areas remains pathetic and abysmal.
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Zaman and Aman (2004), reported that relatively poor communities have
inadequate access to public health services. It was further noted that 45% of children in
poor households aged 1-5 years have been fully immunized as against 58% in non-poor
households. Similarly, 83.9% children with recent problems of diarrhea belonging to poor
households are less likely to have had medical consultation compared to non poor
households (22.9%)
Table-49 Status of Health and Nutrition. S.No. Particulars Number Percent6 Health facilities are in bad shape and need improvement 33 53.2 3 Status of Health Nutrition is good / improved due to
establishment of health centre 13 21
5 Establishing a dispensary on self help basis 8 13 4 After the formation of VDO nutrition and health improved 5 8.0 7 Health condition is fair and nutrition is simple 5 8.0 1 Awareness Seminars / Training conducted on Health and
Nutrition 3 4.8
2 Minor cases are treated here and major cases send to Shahdadpur
2 3.2
Source: Survey Results 2007. 7.2.5 Improvement of Living Standard after the Loan
According to data related to improvement of living standards after availing
the facility of loan (Table-50), all the sample respondents (100%) agreed that their
income has increased and living standard improved due to the loan given to them. Only
4.8% of the respondents believed that the loan has little impact on living standards due to
small amount disbursed. There was a need to increase the loan to a reasonable amount, so
that it could be of great benefit to borrowers in the area. Equally, on the same proportion
4.8% perceived that due to the loan facility their income increased partially. The loan has
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changed the lives of 3.2% borrowers and now they are self reliant, this means that the
major goal of credit agencies has been achieved. According to 16% of the respondents
engaged in farming, seed is available to them now due to availability of the loan facility,
this will lead to self sufficiency in agriculture in the study area. Overall, the loaning
facility has improved the living standards of the people in the study area.
Table-50 Improvement of Living Standard after the Loan. S.No. Particulars Number Percent 1 Income increased and living standard improved due
to the loan 62 100
2 The loan was very small and its impact was very little
3 4.8
3 The loan improved our income partially 3 4.8
4 We are self reliant due to the loan 2 3.2
5 Seed is available to us every where due to the loan 1 16
Source: Survey Results 2007. 7.2.6 The Role of VDOs in Environmental Degradation
Local organizations have a major role to play in saving the environment
from degradation. It is evident from the results (Table-51) that 65% of the respondents
perceived that tree planting campaigns were organized in the study area and the
environmental conditions reflected to determine whether the people in the study area are
healthy or not. However, 34% of the respondents practice weekly sanitation, waste
disposal and general cleaning programmes so as to maintain a healthy environment.
Similarly, 27.4% of the respondents were entirely unaware of the environmental issues
and they need to be enlightened on a regular basis.
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Air and water pollution have been a serious environmental threat in the
study area for a very long time as perceived by 9.7% of the respondents. Only 3.2% of
the respondents are working with the district government to address deforestation
problem that is harmful to their environment, while the overall tree planting campaigns
were organized by the majority so as to improve the environmental conditions in the
study area.
Table- 51 The Role of VDOs in Environmental Degradation. S.No. Particulars Number Percent
1 Tree plantation campaigns 40 64.5
2 Sanitation and waste disposal 21 33.9
3 Knowledge about environmental issues 17 27.4
4 Air and water pollution 6 9.7
5 Working with district Govt. to address deforestation problem
2 3.2
Source: Survey Results 2007. 7.2.7 The Role of VDOs in Establishing Income Generating Business
The local NGOs like VDOs has an effective role to motivate the people of
the locality for a particular purpose. Information collected regarding the role of VDOs in
establishing income generating business is summarized in Table-55 and the data showed
that 64.5% of the respondents were found to have established some income generating
business for the youth, while 53.2% had no concern with such activities. Likewise, 9.6%
of the respondents helped the poor of the area to establish embroidery and knitting
business, while 8.0% supported some women to start tailoring and embroidery business
so as to raise their income and improve their socio-economic condition; and 4.8%
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respondents claimed to have money for financing future projects to improve welfare in
the area.
Sindh Agriculture and Forestry Workers Coordinating Organization
(SAFWCO), a local NGO is training youth graduates and junior professionals for self
reliance; some enterprise development packages were included in the training as
perceived by 3.2% respondents. These trainings are important for their professional
development as they will learn various technical, professional, administrative,
interpersonal skills that will help them perform their duties excellently well for
achievement of organizational goals and objectives. Overall income generating business
established by majority of the VDOs has helped people to become self reliant.
Table-52 The Role of VDOS in Establishing Income Generating Businesses. S.No. Particulars Number Percent1 Establish some income generating jobs for youth 40 64.5 2 No effort is made 33 53.2 4 Established embroidery and knitting business for the poor 6 9.6 3 Support some women to sart rally and embroidery business 5 8.0 5 Money is available for future projects. 3 4.8 6 Safwco is training junior professionals for self reliance
enterprise dev packages were included in the training. 2 3.2
Source: Survey Results 2007. 7.2.8 Recommendations of VDOs for Effective Poverty Alleviation Programmes
Table-53 contained the data regarding recommendation of VDOs for
improving the performance, of poverty alleviation programmes. The results revealed that
60% of the respondents suggested that agricultural loans should be provided with low
interest rate, as this will be an incentive to support small farmers who relied on farming
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for their livelihood. Similarly, 11.3% of the respondents argued that government should
provide irrigation water so as to alleviate poverty in the area and address all outstanding
issues concerning water problems. Moreover, 9.7% of the respondents perceived that
vocational training centers should be established so as to train young and middle age
people for various skills to become self reliant citizens. Likewise, 8.1% of the
respondents were of the view that small projects/small factories should be established in
the area to address unemployment issues, while provision of income generating business
was suggested by 4.8% respondents.
Road and transport facilities are essentially needed so that the farmers and
businessmen can transport their goods from their village to cities with easy access. It was
observed that 3.2% of the respondents suggested quality education at low cost and social
mobilization/technical advice should be provided so as to have an egalitarian and
enlightened society. Overall, majority of the respondents perceived that provision of
agricultural loans with low interest rate will help to increase agricultural production in the
study area.
Table-53 Recommendations of VDOs for Improving Poverty Alleviation
Programmes. S.No. Demands Number Percent
1. Agriculture loans with low interest rate 37 59.7 2. Irrigation water 7 11.3 3. Vocational training centre 6 9.7 4. Small projects /small factories 5 8.1 5. Income generating jobs 3 4.8 6. Road and transport facilities 2 3.2 7. Quality education at low cost 2 3.2 8. Social mobilization/technical advice 2 3.2 Source: Survey Results 2007.
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7.2.9 Rural Community Opinion on Government Poverty Alleviation Strategies
Impact assessment of a project is prerequisite to regulate the pace of
development in relation to poverty alleviation from the societies. According to
information gathered in Table-54, 53.2% of the respondents believed that government
poverty alleviation strategies are good in principle, while 29% respondents were of the
view that these policies have less impact on their communities. Similarly, 27.4%
respondents were completely ignorant and they were entirely unaware whether these
policies are implemented or not. Moreover, 9.6% respondents showed negative opinion
on the policy because they were not benefiting from it, while there was no response from
4.8% respondents. VDO officials should organize regular awareness campaigns in their
respective villages to enlighten the poor about government policies/programmes and
strategies, and their benefits to the people. This will help them to know about new
projects implemented by the government that will obviously contribute to change their
lives and the community as a whole. Majority of the respondents believe that government
poverty alleviation strategies are good in principle and need to be translated to make them
more effective and beneficial to the society. In a similar study, Ahmed (2001) stated that
in almost all developing countries people believe that governments do not do enough for
poverty alleviation.
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Table-54 Rural Community Opinion About Govt. Poverty Alleviation Strategies.
S.No. Particulars Number Percent 1 Govt. poverty programme is good in principle 33 53.2 2 It has less impaction the poor or not reaching the
poor 18 29
4 They don’t know about it/not implemented/not better for us
17 27.4
5 It is not a good policy as we are not benefiting from it
6 9.6
3 No response 3 4.8 Source: Survey Results 2007. 7.2.10 Services Provided by VDOs to Community to Alleviate Poverty
The local NGOs are considered as most effective organizations to develop
social change in the societies. Table-55 showed that 27.4% of the representatives of the
VDOs were of the opinion that sustainable projects at community level may be
implemented, and 21.0% suggested that skill/need based training programmes should be
imparted for self reliance. Funds should be provided to the community through VDOs as
demanded by 18% of the respondents, while 11.3% urged that vocational training centres
may be established for training of male and female youth, to make them self reliant.
According to 9.7% respondents, the VDOs should focus on awareness campaigns, so as
to increase the perception of the poor on various issues concerning their lives. Likewise,
8.1% argued that VDOs should arrange for credit facilities in collaboration with local
banks willing to provide financial facilities to the poor on interest free basis. Management
techniques and other useful training should be imparted to improve their managerial, and
interpersonal skills as reported by 4.8% of the respondents, while 3.2% demanded that
income generating business should be provided to them to become self reliant and escape
the menace of poverty. Overall, majority of the respondents believed that if sustainable
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projects were implemented in the community, solutions to various problems would have
been achieved with success.
Table-55 Services Provided by VDOs to Community to Alleviate Poverty. S.No. Particulars NumberPercent1 Sustainable projects at community level 17 27.4 2 Skill/need based training should be given to the poor for self
reliance 13 21.0
3 Funds should be provided to the community through VDOs 11 17.7 4 Establish vocational training centres for male and female youth 7 11.3
5 VDOs should focus on awareness campaign 6 9.7 6 VDOs should arrange for credit facilities to the community 5 8.1 7 Management and other useful training should be imparted 3 4.8 8 Income generating jobs should be provided 2 3.2 Source: Survey Results 2007. 7.2.11 Important Services Implemented by VDOs and Problems Encountered
Survey results in Table-56 showed that the VDOs are rendering important
services. The results revealed that 58% of the respondents agreed that they disbursed
micro credit to the community, while 48.35 and 25.8% delivered health facilities and
conducted awareness seminars, respectively. Similarly, 16.1% of the respondents
launched awareness and social mobilization programmes to increase the perception of the
poor about programmes implemented in their area. Likewise, income generating business
and vocational training centers were established as reported by 9.6% and 8.0%
respondents, respectively. According to 4.8% respondents, agricultural inputs, livestock
and hand craft facilities were provided to them at their doorstep. Equally on the same
proportion, 4.8% of the respondents agreed that drinking water supply was provided in
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view of acute shortage of water in the area. Empowerment is an important rural
development tool and moral support during emergencies was provided to the people to
encourage them as reported by 3.2% each, respectively. Financial aid was provided
according to 1.6% respondents and equally the same proportion (1.6%) agreed that
community conflicts were resolved.
The major problems encountered by the VDOs were lack of cooperation
from land department and lack of commitment and interest by the people to address their
social problems. Accute shortage of irrigation water is one of the major problems as
opinioned by 3.2% of the respondents in the study area. Overall, majority of the
respondents believe that micro credit was disbursed to the community for self reliance.
These results have also been supported by Badini (2006), who reported that the main
problems of NGOs in Balochistan province of Pakistan were lack of funds, coordination,
computer training, scientific equipments, transport facilities and confirmed the findings
of the present study of Sanghar and Badin districts of Sindh province.
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Table-56 Important Services Implemented by VDOs and Problems Encountered.
S. No.
Particulars N %
IMPORTANT SERVICES IMPLEMENTED 1 Micro credit 36 58 2 Health facilities 30 48.3 3 Awareness seminars 16 25.8 4 Social mobilization 10 16.1 5 Income generating jobs 6 9.6 6 Establish vocational centre and provide training to youth 5 8.0 7 Agriculture inputs livestock and hand craft facilities provided 3 4.8 8 Drinking water supply was provided 3 4.8 9 Empowerment 2 3.2 10 Provide support during emergencies 2 3.2 11 No response 2 3.2 12 Financial aid was provided 1 1.6 13 Community conflict 1 1.6 MAIN PROBLEMS EXPERIENCED 14 Lack of cooperation form land Dept 2 3.2 15 Lack of coordination from officials 2 3.2 16 Lack of interest by people to address their problems 2 3.2 17 Shortage of irrigation water 2 3.2 Source: Survey Results 2007.
7.2.12 Increase in Access of Good Quality Water
Information presented in Table-57 shows that 45% of the respondents
perceived that hand pumps were provided with the coordination of Sindh Agricultural
and Forestry Workers Coordinating Organization (SAWFCO), a local NGO to help
alleviate their water problems. According to 24.1% respondents, they are working with
Pakistan Poverty Alleviation Fund (PPAF) and SAWFCO to provide easy access to sweet
water for the community.
Similarly, 16.1 respondents agreed that some of the NGOs have build a
water tank that supplied good quality water. Equally on the same proportion 16.1% of
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respondents, reported that few houses have no access to quality water and sweet water
was available only to 4.8% respondents. Likewise, 4.8% respondents opinioned that they
have established water supply scheme to the village on self help basis, while 3.2%
claimed lack of access to quality water. Furthermore, it was noted that 3.2% respondents
adviced people to boil water before use, because in general, water in this area is polluted
and unhygienic. Installation of hand pumps by SAFWCO has tremendously increased
access of good quality water for the community.
Table-57 Increase in Access to Good Quality Water. S.No. Particulars Number Percent 1 Provide hand pumps with help of sawfco 28 45 2 Working with safwco and PPAF to provide access to
sweet water. 15 24.1
3 Some NGO’s build a water tank that supplied quality water
10 16.1
4 Only few houses don’t have access to quality water. 10 16.1 5 Sweet water is available everyone access to it 3 4.8 6 Able to provide drinking water supply scheme to the
village 3 4.8
7 Some people don’t have access to quality water 2 3.2 8 Advice people to boil water because water here is not
good 2 3.2
9 No response 2 3.2 Source: Survey Results 2007. 7.2.13 The Role of VDOs in Constructing a Building for the Community in District
Sanghar
The survey results (Table-58) showed the role of VDOs in constructing a
building in district Sanghar and noted that 100% of the respondents gave technical advice
which help in constructing a building, while 51.6% provided financial support in the
execution and implementation of the project. Similarly, 27.4% assisted in the technical
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aspect of the building such as ensuring that the project is executed according to layout
plan, monitoring the project has been completed successfully, satisfying all the
requirements. Technical advice proved to be the best that helped in constructing a
building in the area.
Table-58 The Role of VDO’s in Constructing a Building for Community in
District Sanghar. S.No. Particulars Number Percent1 Gave Technical Advice 62 100 3 Gave financial support 32 51.6 2 Assist in construction management 17 27.4 Source: Survey Results 2007. 7.2.14 Leadership Style of VDOs in District Sanghar
The data in Table-59 showed that all the respondents (100%) agreed that
the leadership style adopted by their VDOs was participatory, and 17.7% reported that
democratic leadership style was adopted by their VDO; NGOs using participatory
leadership style should ensure that maximum participation of the people at all levels in
planning, implementation and evaluation of projects are strictly adhered to. There was no
response from 3.2% of the respondent regarding participatory and democratic leadership
styles; participatory leadership proved to be the best style adopted by the VDOs in district
Sanghar.
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Table-59 Leadership Style of VDOs in District Sanghar. S.No. Particulars Number Percent1 Leadership style is participatory 62 100 2 Leadership style is democratic 11 17.7 3 No response 2 3.2 Source: Survey Results 2007. 7.2.15 Perception About Total Credit Disbursed to the Community in District
Sanghar
Data regarding perceptions of respondents on total credit disbursed in
district Sanghar are presented in Table-60 and accordingly, 16.1% of the respondents
reported that an amount of Rs.140,000 was disbursed to 22 female clients, this will help
them to start some income generating activities. Equally on the same proportion of an
amount Rs.140,000 was disbursed to 22 male clients, total amount of Rs.375,000 was
disbursed to the community as perceived by 11.2% respondents. Similarly, Rs.200,000
was disbursed in general and Rs.536,000 was disbursed to 73 clients as reported by
11.2% respondents, while Rs.90,000 was disbursed to 12 clients and 351,000 also
disbursed to 40 clients according to 11.2% respondents. According to 9.6% of the
respondents, Rs.210,000 was disbursed to 110 clients, 1.6 respondents reported that an
amount of Rs.8,000 was disbursed to 110 clients. Similarly, 1.6 respondents reported
Rs.8,000 was disbursed as 1st loan and Rs.10,000 as 2nd loan to the needy poor. A total of
Rs.300 million was disbursed by SAFWCO a local NGO to 40,000 clients in the area for
establishing income generating business enabling them to be self reliant at all times. The
highest disbursement from SAFWCO shows their level of commitment to poverty
alleviation in the area of study.
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Table-60 Perception about Total Credit Disbursed to the Community in District Sanghar.
S.No. Particulars Number Percent 1 Rs.140,000 was disbursed to 22 female clients 10 16.1 2 Rs.140,000 was disbursed to 22 clients 8 13 3 Rs.375,000 was disbursed to the community 7 11.2 4 Rs.200,000 was disbursed 7 11.2 5 Rs.536,000 was disbursed to 73 clients 7 11.2 6 Rs.90,000 was disbursed to 12 clients 7 11.2 7 Rs.351,000 was disbursed to 40 clients 7 11.2 8 Rs.175,000 was disbursed to 24 clients male and
female 6 9.6
9 No credit was disbursed 6 9.6 10 Rs.210,000 disbursed to 110 clients 6 9.6 11 1st loan disbursed Rs.8,000
2nd loan disbursed Rs.10,000 1 1.6
12 SAFWCO disbursed Rs.300 million to 40,000 clients 1 1.6 Source: Survey Results 2007. 7.2.16 Conditions for Successful Use of Microcredit in District Sanghar
Survey results (Table-61) showed that 66% of the respondents perceived
positively and agreed that the loan given by SAFWCO was properly utilized, while
25.8% respondents argued that agricultural loans be recovered in 6 months and small
business loan in one year. This is to allow them maximum time to utilize the money
properly. According to 13% respondents, loans were not utilized properly. So, it is
suggested that VDOs should give more counseling and advice to clients to avoid misuse
of the loan. Similarly, 11.2% of the respondents agreed that microcredit was disbursed for
establishing small shops and for purchase of livestock. A small number of respondents
(3.2%) believed that loan recovery should be on installments basis allowing the clients to
concentrate more in making their business successful, so that they would be self reliant.
The loan ceiling of SAFWCO was between Rs.5000-30,000 as reported by 1.6
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respondents. These figures may be increased in view of regular demand for credit and the
current inflationary trends in the country. Overall, majority of the respondents perceived
that micro credit was properly utilized by the beneficiaries for establishing sustainable
business in the area of study.
Table-61 Conditions for Successful use of Microcredit in District Sanghar. S.No. Particulars Number Percent1 Proper utilization of the loan 41 66 2 Conditions are that agric loan be recovered in 6 month and
small business loan one year 16 25.8
3 Loans were not utilized properly 8 13 4 Microcredit was disbursed for establishing small shops and
for livestock 7 11.2
5 Recovery loan should be on installment basis 2 3.2 6 SAFWCO loan ceiling is between Rs.5000-30,000 1 1.6 Source: Survey Results 2007. 7.2.17 Goals Purpose and Aims of VDOs in District Sanghar
Perceptions of respondents from Sanghar district in relation to goals,
purpose and aims of VDOs are presented in Table-62. The results revealed that 48.3% of
the respondents opined that awareness campaign was the goal of their VDO, while 42%
respondents reported that community participation was the goal of their VDO. Exactly on
the same proportion, 42% of the respondents believed that development of village is
encouraging people to help themselves was the goal and aim of their VDO. Similarly,
32.2% of the respondents thought that access to education and health was the main aim of
their VDO.
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The results further show that 17.7% respondents had their goals and
objective of poverty alleviation in the area, while 9.6% believe that to establish
vocational training centre for income generating business has always been the goal they
wanted to achieve. Likewise, 4.8% of the respondents thought that empowerment of the
poor is the aim of their VDO. Similarly, 3.2% respondents agreed that their goal was to
establish capacity building for their VDO to become sustainable and strong enough.
Provision of micro credit facilities to the poor in emergencies and welfare at the time of
floods and cyclone was the goal of their VDOs as reported by 3.2% each of the
respondents, respectively. However, according to only 1.6% of the respondents the
advocacy and mobilization was the goal of their VDO; this shows that awareness
campaign has been the most important goal for most of the VDOs in the study areas.
Table-62 Goals, Purpose and Aims of VDOs in District Sanghar. S.No. Particulars Number Percent1 Awareness campaign 30 48.3 2 Community participation 26 42 3 Development of village helping people to help themselves 26 42 4 Access to Education and Health 20 32.2 5 Poverty alleviation 11 17.7 6 To establish vocational training centre for income
generating jobs 6 9.6
7 Empowerment 3 4.8 8 Capacity building of VDO to become sustainable 2 3.2 9 Provision of micro credit facilities to the poor 2 3.2 10 Emergencies and welfare in time of flood etc 2 3.2 11 Advocacy and mobilization 1 1.6 Source: Survey Results 2007.
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7.2.18 Specific Areas VDOs are Working to Alleviate Poverty in District Sanghar
The study results regarding specific areas VDOs are working to alleviate
poverty is shown in Table-63, which revealed that majority (80.6%) of the respondents
indicated that their VDO is working in areas of social development and community
infrastructure, while 66% of the respondents were working in areas related to issues of
young generation. Likewise, 64.5% respondents reported that they are working on areas
of health and awareness; 51.6% showed that they are working to provide micro credit and
finance to the poor to help them establish their own business for self reliance. On the
status of on going projects in the area, 69.3% respondents perceived positive for on-going
projects relating to poverty alleviation, while 35.4% respondents indicated that there was
no such on-going project at the moment in the study area. Overall, the majority of the
VDOs are working in social development and community infrastructure; this has proved
to be the most important area for most of the VDOs.
The above findings coincide with VDO Assessment Report District
Sanghar (2007) which indicates that 56% of the local organizations have coordinated
with SAFWCO in different programmes and the highest is micro credit and finance
programme in which nearly 96% of them have been involved.
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Table-63 Specific Areas VDOs are Working to Alleviate Poverty in District Sanghar.
S.No. Particulars Number Percent AREAS 1 Social development and community infrastructure 50 80.6 2 Education 41 66 3 Health and Awareness 40 64.5 4 Micro credit and finance 32 51.6 STATUS OF PROJECT
Ongoing project No on going project
43 22
69.3 35.4
Source: Survey Results 2007.
7.3 Survey Results of VDOs in District Badin 7.3.1 Activities of VDOs to Alleviate Poverty
The survey results in relation to VDO activities to alleviate poverty are
summarized in table-64, which indicated the 36 out of 62 representatives of VDOs were
of the opinion that awareness programmes were organized to increase the perception of
the people on various programmes, while 32.2% of the respondents showed that social
mobilization activities were adopted by the VDOs. Similarly, 3.2% of the respondents
were in favour of activities about saving campaigns launched in their villages.
It was further noted that equally 3.2% of the respondents reported that
they performed activities to empower the community and disburse micro credit to the
poor. Considering human resource development to be important, 3.2% of the respondents
arranged trainings to improve their knowledge, only 1.6% arranged regular meetings to
discuss strategies to be adopted for development of the area and self reliant activities,
respectively. Overall, awareness programmes have perceived to be extremely important
by the majority of respondents in the area, followed by social mobilization and savings.
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The above findings are in agreement with those of Jalaluddin (2003), who reported that
social mobilization promotes democratic activities and help the local authorities to
alleviate poverty and improve the livelihoods of the rural farmers in particular. Similarly,
these findings coincide with Parthasarathy (2005), who reported that their NGO has
generally adopted social mobilization to increase the perception of their members on
various programme for poverty alleviation.
Table-64 Activities ofVDOs to Alleviate Poverty. S.No. Particulars Number Percent
1 Awareness 36 58
3 Social Mobilization 20 32.2
9 No Response 15 24.1
2 Savings 2 3.2
4 Empowerment 2 3.2
5 Microcredit 2 3.2
7 Training 2 3.2
8 Regular Meetings 1 1.6
6 Self Reliant 1 1.6 Source: Survey Results 2007
7.3.2 Empowerment and Participation in Community
Progress on empowerment and participation has been summarized in
Table-65, which indicated that 64.5% of the respondents perceived that the progress of
empowerment was satisfactory, while 8% respondents believe that there was lack of
cooperation in addressing various problems they face; only 3.2% of the respondents
perceived that team building and technical skills for self reliance were the most important
activities for poverty alleviation. Majority of these believe that progress towards
empowerment was satisfactory and it will help the community towards building a better
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society in peace and tranquility. The above findings are partially supported by Little et al.
(2008), who reported that progress towards pastoralist empowerment is satisfactory and
pastoralist should become more politically empowered. Furthermore, Amjad (2005)
reported that government of Pakistan has taken many bold steps to empower women and
the result was satisfactory. It also ensured that the policies on improving the status of
women are carried out. Sankar (2005) concluded that empowerment and participation
was done with success as women at the collective level began to participate in
community activities, this helped in poverty alleviation.
Table-65 Empowerment and Participation in Community. S.No. Particulars Number Percent1 Progress of empowerment satisfactory 40 64.5 2 Progress of empowerment not satisfactory 23 37 3 Lack of cooperation 5 8 4 Team building / leading 2 3.2 5 Technical skills for self reliance 2 3.2 Source: Survey Results 2008.
7.3.3 Perception on Proper Utilization of Mciro credit Loans
Perceptions of respondents regarding proper utilization of mcirocredit
loans is presented in Table-66 which shows that majority of the respondents (64.5%)
agreed that the condition attached to successful use of credit was that credit must be
utilized properly and paid back. Likewise, 21% of the respondents believe that
microcredit must be given to those who deserve it, and 3.2% respondents agreed that
conditions are determined when the credit was disbursed. It is necessary to select and
identify competent groups who can utilize the loan properly as argued by 16.1%
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respondents. Similarly, 3.2% think that they had no credit from banks and NGOs should
give them credit facilities to become self reliant. Overall, majority of the respondents
agreed that credit becomes successful when it is utilized properly and paid back by the
beneficiaries, followed by the opinion that credit should be given to only those, who
deserve to avoid waste of resources.
Table-66 Perception about Proper Utilization of Microcedit Loans. S.No. Particulars Number Percent
1 The condition is that the credit has to be utilized properly and paid back
40 64.5
2 Microcredit should be given to those who deserve it 13 21
3 Conditions are determined when the credit is disbursed 2 3.2 4 Select and identify competent groups 10 16.1
5 No credit banks and NGOs should give us credit 2 3.2 6 No response 11 18
Source: Survey Results 2008
7.3.4 Status of Health and Nutrition
The data pertaining to status of health and nutrition are reported in Table-
67 which display the summarized information on the status of health and nutrition of the
people in the study area. Survey results revealed that majority (69.3%) of the respondents
reported very poor status of health in their area; likewise 19.3% reported that status of
health was satisfactory. Similarly, 9.6% of the respondents agreed that immunization and
polio vaccination activities were implemented with success. There was lack of
cooperation from the poor and no effort to address health care problems as reported by
8% respondents. Similarly, 4.8% of the respondent organized seminars on Hiv/Aids
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prevention to enlighten the community about the protective measures to be adopted.
Moreover, 60 schools started health and nutrition programmes through their NGO as
reported by 3.2% respondents.
Equally on the same proportion (3.2%) reported that they had no funds to
start working in areas of health and nutrition for the community. Overall, majority
believe that status of health and nutrition was very poor and they had to work very hard
to address the problem. There have been some efforts but is not enough, a lot needs to be
done to achieve success to this aspect. The above findings are in agreement with Mitra
(1993), who reported that health and nutrition is still in bad shape. The nutritional and
health education programme do not benefit members of the household in the study area.
Table- 67 Status of Health and Nutrition. S.No. Particulars Number Percent
1 Status of health is very poor in our area 43 69.3
2 Status of health is satisfactory 12 19.3
3 Immunization and polio activities were implemented with success
6 9.6
4 Lack of cooperation from the poor and no effort to address health care problems in the area
5 8
5 Organize seminars on HIV / Aids prevention 3 4.8
6 No response 3 4.8
7 60 schools start health and nutrition programme through our NGO
2 3.2
8 No funds to start work on health and nutrition 2 3.2
Source: Survey Results 2008
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7.3.5 Improvement of Living Standard after the Loan
Data regarding improvement of living standards of the people after
availing loan facility is presented in Table-68, and according to information provided,
42% of the respondents believe that their income remained stagnant, because they had no
credit facilities at their disposal. Similarly, 24.1% respondents perceived that only 30% of
the people improved their living standard, while 70% of the people still live below the
poverty line. Likewise, 19.3% respondents were of the opinion that their living standard
will improve only if they have access to credit facilities, while 18% respondents reported
that their income increased through agriculture and livestock farming. Only 8% suggested
that vocational training centre may be established for capacity building of youth in rural
areas. Floods and cyclones destroyed their land, that is why they remained poor as
reported by 4.8% respondents. Equally on the same proportion (4.8%) perceived that if
sufficient water is available, their income will increase; shortage of water was their major
problem. Overall, majority of the respondents believed that their income remained
stagnant due to lack of credit, on the same token, 70% still live below the poverty line;
therefore, credit is needed to bring them back to the track of normal life.
The above findings are well comparable with those of Zaman and Aman
(2004), who reported that the rural poor are highly vulnerable to floods, draughts and
cyclones. The two household income expenditure survey (HIES) data of 1998-99 and
2000-01 show that the estimated increase in overall poverty is attributed largely to the
increase in rural poverty. Similarly, Adi (2007) reported that if success is to be recorded
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in poverty alleviation, it is important to support agriculture and non agricultural activities;
specifically skill acquisition by way of vocational training should be encouraged.
Table-68 Improvement of Living Standard After the Loan.
S.No. Particulars Number Percent 2 Income remain stagnant because we have no credit
facilities 26 42
3 Only 30% of people living standard improve about 70% still live below the poverty line
15 24.1
8 No response 15 24.1 6 Living standard will improve only if people get credit 12 19.3 1 Income increase through agriculture and livestock
farming 11 18
7 Need vocational training and credit to become self reliant
5 8
4 Floods and cyclone destroyed our land that was why we remain poor
3 4.8
5 If water is available income will increase shortage of water is our major problem
3 4.8
Source: Survey Results 2008.
7.3.6 The Role of VDOs in Saving Environment from Degradation
The opinions regarding the role of VDOs in saving the environment from
degradation are shown in Table-69 and the results revealed that 40.3% of the respondents
advice people to conduct general cleaning of houses, streets and drainages on regular
basis, while about 29% are working to address deforestation and air pollution problems.
Similarly, 24.1% respondents informed that tree planting campaigns were organized on
environmental day. Badin LDA law Development Association has introduced new
smokeless store to reduce pollution problems in the area as reported by 18% respondents.
Similarly, 13% respondents believe that their VDOs gave regular awareness to the people
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of the area on environmental degradation. According to 3.2% respondents Badin based
NGOs are working hard on environmental health programme at their respective village
level. Equally, on the same proportion 3.2% agreed that they are working in collaboration
with UNDP to address environmental issues.
Overall, the advice given by the majority to conduct general cleaning of
houses, streets and drainage on regular basis was on the right direction, it will create an
impact on the general welfare of the area, if done with commitment and sincerity. The
above findings coincide with the findings of Zaman and Aman (2004), who reported that
in rural areas of NWFP, environmental degradation and deterioration of natural
environment, poor drainage situation, deforestation and air pollution have been the major
causes of poverty.
Table- 69 The Role of VDO in Saving Environment from Degradation. S.No. Particulars Number Percent
1 Advice people to do general cleaning of houses, streets and drainage on regular basis
25 40.3
3 Working to address deforestation and air pollution problems
18 29
2 Plant trees and observe weekly environmental day
15 24.1
5 Law development association (LDA) Badin has introduce new smokeless stove to reduce pollution problems
11 18
7 VDO gave regular awareness on environmental degradation
8 13
8 No response 7 11.2 4 Badin based NGO is working on environmental
health programme in our village 2 3.2
6 Working in collaboration with UNDP to address environmental issues
2 3.2
Source: Survey Results 2008.
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7.3.7 The Role of VDOs/NGOs in Establishing Income Generating Jobs
Survey results in Table-70 showed that 18% of the respondents are
working to create more job opportunities for the poor, while 13% respondents have done
nothing so far. Similarly, 8% respondents believe that their VDO has done nothing so far
and about 8% believe that their VDO gave loans to 2 citizens to start small business;
4.8% VDO representatives reported that their organization has established a marketing
system and it has remained successful. Likewise, 4.8% respondents reported that their
VDO distributed 20 sheep and 20 goats which created some job opportunities for the
community. Moreover, 3.2% established a livestock programme with the support of
Badin Rural Development Society (BRDS). Equally on the same proportion, 3.2%
reported that they developed tomato farming for the poor and they are working with
district government to establish a vocational training centre in the area.
Overall majority of the respondents believe that they are working to create
more jobs for the poor, which is a positive development in the right direction.
Table-70 The Role of VDO/NGOS in Establishing Income Generating Jobs. S.No. Particulars Number Percent 1 Working to create more job opportunities for the poor 11 18 2 Nothing was done so far 8 13 3 VDO gave loans to 2 people to start small shop 5 8 4 VDO establish a marketing system it was successful 3 4.8 5 No credit to start new business for self reliance 3 4.8 6 VDO distribute 20 sheeps and 20 goats this will create more
jobs 3 4.8
7 Establish a livestock programme with the support from BRDS
2 3.2
8 Develop a tomato farming for the poor 2 3.2 9 Working with the District Govt. to establish a vocational
training centre 2 3.2
10 No response 33 53 Source: Survey Results 2008.
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7.3.8 Recommendations of VDOs for Improving Poverty Alleviation Programmes According to information presented in Table-71, 56.4% of the respondents
suggested that credit facilities should be given to the poor, while 13% favoured the
establishment of vocational training centre for training of youth and adults in various
skills. Community saving must be encouraged, according to 11.2% of the respondents. In
view of shortage of funds, 9.6% demanded that NGOs and banks should introduce
microcredit activities in the area. Similarly, 8% argued that community should be
educated about poverty alleviation programmes; and government should distribute more
land to the poor so as to grow more crops as advised by 3.2% respondents. Likewise,
3.25% respondents agreed that NGOs/VDOs should create more job opportunities for the
poor, and 1.6% respondents suggested that group formation should be encouraged.
According to 1.6 respondents, NGOs/VDOs should involve the poor in implementing
poverty alleviation programmes; and exactly on the same proportion, 1.6% perceived that
NGOs/VDOs should work towards improving quality education for the poor. Similarly,
1.6% believe that government should provide technical assistance to the community,
while sugar mills/textile mills should be established so that the poor can get employment
as demanded by 1.6% respondents. Likewise, 1.6% respondents reported that government
should establish linkage between technical people and their work place.
Overall majority of the respondents urged government to provide credit
facilities to the poor; the second on priority list was establishment of vocational training
centre, while the third was that the community savings should be encouraged. These three
are interlinked to each other and if all are provided it will surely reduce the level of
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poverty among the poor in the study area. The above findings are in concurrence with
those of Badini (2006), who suggested that government may consider jobs skill training
center in partnership with NGOs for human resource development, while conducting a
similar study in Quetta district of Balochistan.
Table-71 Recommendations of VDOs for Improving Poverty Alleviation
Programmes. S.No. Particulars Number Percent
1 Credit facilities should be given to the poor 35 56.4 2 Vocational training centre should be established 8 13 3 Community saving must be encouraged 7 11.2 4 NGOs / banks should introduce microfinance
activities in our area 6 9.6
5 Community should be educated about poverty alleviation programmes
5 8
6 Govt. should distribute more lands to the poor so as to grow more crops
2 3.2
7 NGOs/VDOs should provide more job opportunities to the poor
2 3.2
8 Group formation should be encouraged 1 1.6 9 NGO/VDOs should involve the poor in implementing
poverty programmes 1 1.6
10 NGOs/VDOs should work towards improving quality education for the poor
1 1.6
11 Govt. should provide technical assistance to the community
1 1.6
12 Sugar mills / textile mills should be established so that the poor can get employment
1 1.6
13 Govt. should provide linkage between technical people with their work place
1 1.6
Source: Survey Results 2008.
7.3.9 Rural Community Opinion About Poverty Alleviation Strategies The survey results in Table-72 showed that 61.2% of the respondents
favored the poverty alleviation strategy and suggested government to make it work
properly, while 27.4% respondents believe that the community is not benefiting from
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poverty programmes of the government. Communities should be involved in formulating
poverty alleviation programes as advised by 1.6% respondents and equally on the same
proportion, 1.6% respondents perceived that in principle, government poverty
programmes are good but mostly suffer due to poor implementation. Likewise, 16.1%
respondents strongly supported government poverty alleviation strategies and 3.2% of the
respondents opined that they are unaware of the government poverty programmes.
Rozgar scheme(13) is a good initiative, aiming at poverty alleviation as reported by 1.6%
respondents; while 4.8% respondents believe that this strategy has never worked for the
poor. Similarly, 1.6% respondents agreed that NCHD National Council for Human
Development Programme is a good initiative and they hope it will be continued by the
present government. Survey results further revealed that 4.8% respondents indicated that
government is not working on any poverty reduction programme in their area; this
strategy cannot succeed unless it aims at changing the lives of the poor and vulnerable as
reported by 1.6% respondents. Likewise, 1.6% respondents demanded that government
should give them credit to purchase inputs, seed and livestock for self reliance. Majority
of the respondents believe that government poverty reduction strategies are very good in
principle but they should be made to work properly. Secondly, they believe that they are
not benefiting from government programmes, therefore, in view of the above village
development organizations, NGOs and other stakeholders should assist government to
make these programmes succeed. The above findings are partially supported by Biswas
(2007), who reported that poverty alleviation schemes in rural areas of India have been
implemented only in paper and resources, were not utilized properly.
13. Rozgar Schemes: is a micro credit scheme giving to the poor for self reliance.
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Table-72 Rural Community Opinion About Govt Poverty Alleviation Strategies.
S.No. Particulars Number Percent
1. Good strategy but government should make it work properly.
38 61.2
2. Community is not benefiting from poverty programmes of the government.
17 27.4
3. Strongly support government poverty alleviation strategies.
10 16.1
4. This strategy has never worked for the poor. 3 4.8 5. Government is not working in any poverty reduction in
our area. 3 4.8
6. Not aware of government poverty programmes. 2 3.2 7. Communities should be involved in formulating poverty
alleviation programmes and strategies. 1 1.6
8. In principle government poverty programmes are good but mostly they fail due to poor implementation.
1 1.6
9. Rozgar scheme is a good initiative aimed at poverty alleviation.
1 1.6
10. NCHD is a good initiative we hope it will continue. 1 1.6 11. This strategy cannot succeed unless it aims at changing
the lives of the poor and vulnerable. 1 1.6
12. Government should give us credit to purchase inputs, seeds and livestock for self reliance.
1 1.6
Source: Survey Results 2008.
7.3.10 Services VDOs Should Provide to Alleviate Poverty The survey results regarding services VDOs provide to alleviate poverty
are presented in Table-73, which showed that 40.3% of the respondents argued that
VDOs should provide microcredit to the poor, while 18% stressed that VDOs should
establish livestock rearing programme and disburse credit to the poor to sustain the
programme. Similarly, 13% of the representatives of VDOs were of the opinion that
sustainable income generating projects at community level may be created. NGOs/VDOs
should work in areas of education and health as demanded by 9.6% respondents. Equally
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on the same proportion, 9.6% perceived that VDOs should focus on awareness campaign,
and 3.2% favoured the VDOs on supply of agricultural inputs and seeds to farmers.
Likewise 3.2% respondents reported that VDO should give sewing machines to the poor
women to make them self reliant, while 1.6% respondents believe that NGOs/VDOs
should liaise with government to establish skill acquisition centre for women. According
to respondents’ opinion, 1.6% were of the view that NGOs/VDOs should work to
increase access to water for their communities; while NGOs/VDOs should create
community savings being very important for poverty alleviation as demanded by 1.6%
respondents. Similarly, 1.6% respondents advised that VDOs should develop the
institutional sector in collaboration with bigger NGOs, and 1.6% were of the opinion that
VDOs/NGOs should develop the capacity of individuals and provide basic infrastructure
for the poor. Majority of the respondents favoured provision of microcredit to the poor,
mobilization and empowerment of the poor and establishment of livestock rearing
programme, coupled with provision of credit to sustain it as the major solution to
lingering poverty problems in the area.
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Table-73 Services VDOs Should Prove to Community to Alleviate Poverty. S.No. Particulars Number Percent1 Provide microfinance to the poor 25 40.3 3 NGOs/VDO should mobilize and empower the poor 11 18 7 VDOs should establish livestock rearing programme and
give credit to the poor to sustain it 11 18
8 NGOs / VDOs should create income generating jobs for the poor
8 13
2 NGO / VDOs should work in areas of education and health 6 9.6 5 Give awareness to the poor 6 9.6 4 NGOs / VDOs supply agriculture inputs and seeds to
farmers 2 3.2
12 VDOs should give sewing machines to poor women to become self reliant
2 3.2
6 NGOs / VDOs should liase with the govt. to establish skill acquisition centre for women
1 1.6
9 NGOs/VDOs should work to increase access to water for their communites
1 1.6
10 NGOs/VDOs should create community savings this is very important for poverty alleviation
1 1.6
11 VDOs should developed the institutional sector in collaboration with bigger NGOs
1 1.6
13 VDOs/NGOs should develop the capacity of individual and provide basic infrastructure for the poor
1 1.6
Source: Survey Results 2008.
7.3.11 Important Services Implemented by NGOs/ VDOs and Problems
Encountered Perceptions of respondents regarding important services implemented by
VDOs is presented in Table-74, the results revealed that 34% of the respondents reported
that their VDO installed water pumps in their area to increase access to water, while
19.3% made efforts to empower the poor to become self reliant. Similarly, 18%
respondents created awareness to establish income generating business for the
community and 8% encouraged people to send their children to school, this effort
resulted in increase in the school enrollment. Equally on the same proportion, 8%
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respondents gave social mobilization to the poor, while 4.8% perceived that they
established saving programme and increased membership fees. Through self efforts they
also constructed a mosque as reported by 3.25% respondents and only 1.65% respondents
believed that they addressed various problems such as provision of inputs to farmers and
credit facilities to women for income generating business. However, 1.6% VDO
representatives believed that they are working on reproductive health, human rights and
environmental issues of the study area. Similarly, 1.6% respondents admitted that they
did little for the community; but at the same time they are looking for ways to address
lingering poverty issues in the area. Equally on the same proportion, 1.6% respondents
reported that they achieved gender equity in the area, while the overall majority of the
respondents believed that their greatest achievement was installation of water pumps,
made efforts to empower the poor and created awareness to establish income generating
business.
Table-74 Important Services Implemented by NGOs / VDOs and Problems Encountered.
S.No. Particulars Number Percent1 VDO delivered water pumps to increase access to water 21 34 2 Empower the poor to become self reliant 12 19.3 3 Create awareness to establish income generating jobs 11 18 4 Encourage people to send their children to school due to
this enrolment increase 5 8
5 Gave social mobilization to the poor 5 8 6 Establish saving programme and increase membership fees 3 4.8 7 Through self effort we construct a mosque 2 3.2 8 VDO solved many problems such as provision of inputs to
farmers and credit facilities was given to women 1 1.6
9 VDO worked on reproductive health, human rights and env issues
1 1.6
10 Did very little for the community we are looking for ways to address poverty issues
1 1.6
11 Achieved gender equity in our area 1 1.6 12 No response - - Source: Survey Results 2008.
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7.3.12 Increase in Access to Good Quality Water The data in Table-75 showed that 34% of the respondents installed
tubewells in their village on self help basis, while 27.4% reported that 10 hand pumps
were installed with the help of BRDS(14). Similarly, 24.1% reported that they have
planmed to build a water tank so as to provide access to quality water in their village,
while 18.5% informed that underground water is saltish and due to this situation they are
working to provide sweet water to the poor. Badin based NGOs are working to increase
access to drinking water to the poor as reported by 4.8% respondents and according to
3.2% respondents they made small savings and purchase few water pumps. Likewise,
3.2% respondents reported that their VDO has played advisory role on self help basis,
provision of water pumps by BRDS and proposal to build a water tank will surely address
water problems on a long term basis.
Table-75 Increase in Access to Good Quality Water. S.No. Particulars Number Percent1 Establish some tube wells on self help basis 21 34 2 Ten hand pumps were installed with the help of BRDS 17 27.4 3 Plan to build a water tank in addition to water pumps 15 24.1 4 Underground water is salty we are working to provide
sweet water to the poor 11 18
5 Badin based NGOs are working to increase access to water to the poor
3 4.8
6 Made small savings and purchase few water pumps 2 3.2 7 VDO provide advisory role on how to address water
problems 2 3.2
Source: Survey Results 2008.
14. BRDS: Badin Rural Development Society is a local NGO.
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7.3.13 The Role of NGOs / VDOs in Constructing a Building for the Community in District Badin
Information collected regarding the role of VDO in constructing a building
for the community is summarized in Table-76 and the results revealed that 82.2% of the
respondents gave technical advice which helped the people in constructing the building.
Similarly, 48.3% respondents assisted in construction management, and 4.8%
respondents provided financial support for ensuring that the project is successfully
implemented without financial constraints. Overall, the technical advice provided and
willingness to participate in construction management was quite laudable and this led to
the success of the project.
Table-76 The Role of NGOs / VDOs in Constructing a Building for Community
in District Badin. S.No. Particulars Number Percent 1 Gave technical advice 51 82.2 2 Assisted in construction management 30 48.3 3 Gave financial support 3 4.8 4 No response 1 1.6 Source: Survey Results 2008.
7.3.14 Leadership Style of VDOs in District Badin The data regarding leadership style of VDOs are presented in Table-77,
which indicated that 84% of the respondents had democratic way of leadership, while
40.3% reported that they have adopted participatory leadership style in their organization.
The above findings are in concurrence with those of Institutional
Assessment SAFWCO Partner VDOs Report (2006), which concluded that majority of
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the respondents followed the democratic style of leadership and within the VDOs,
decisions are made by consensus on the basis of shared opinion, especially in the
preparation of annual development plans.
Table-77 Leadership Style of VDOs in District Badin. S.No. Particulars Number Percent 1 Leadership style through democratic style 52 84 2 Leadership style by participation 25 40.3 3 No response - 0 Source: Survey Results 2008. 7.3.15 Perception About Total Credit Disbursed to the Community in District
Badin Survey results presented in Table-78 revealed the perceptions of
respondents on credit disbursed to community and 48.3% of the respondents reported that
they have no credit facilities, while 16.1% indicated that no NGO/Bank is working in
their area for disbursement of microfinance loans. Twenty five women benefited from
livestock credit delivered by BRDS increased their income as reported by 13%
respondents, while 11.2% perceived that they got credit from private money lenders with
high interest rate. The poor had no credit to be self reliance as perceived by 8%
respondents. Equally on the same proportion, 8% reported that 15 male and 5 female
members benefited from credit, 4.8% contacted microfinance banks to give them credit
facilities, while VDO gave 20 of their members a credit of Rs.5000 each, but it was not
sufficient as reported by 3.2% respondents. Similarly, 1.6% agreed that their NGO gave
them credit ranging from Rbs.8,000 – Rs.12,000 and the overall situation indicated
insufficient credit facilities to the poor in the study area. Credit given by various NGOs
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was not sufficient, they need to increase the loans and give it a wider coverage ensuring
that those who deserve actually get the loans.
Table-78 Perception About Total Credit Disbursed to the Community in
District Badin. S.No. Particulars Number Percent 1 No credit facilities 30 48.3 2 No any NGO / Bank is working in our area on
microfinance 10 16.1
3 25 women got livestock credit from BRDS this increase their income
8 13
4 Credit from private money lenders with high interest rate was given to us
7 11.2
5 The poor has no credit to become self reliant 5 8 6 15 male and 5 female members benefited from credit 5 8 7 Contacted microfinance banks to give us credit 3 4.8 8 VDO gave 20 members credit Rs.5000 each but it is
not sufficient 2 3.2
9 NGOs gave us credit ranging from Rs.8000 to Rs.12,000
1 1.6
10 No response 20 32.2 Source: Survey Results 2008.
7.3.16 Perception About Proper Utilization of Microcredit Loans in District Badin The results in Table-79 show that majority of the respondents (64.5%)
agreed that credit must to be utilized properly and paid back while according to the
opinion of 21% respondents, microcredit should be given to those who deserve it, and
16.1% favoured identification of competent groups who can utilize credit properly.
Likewise 3.2% believe that conditions are determined when the credit is disbursed to
beneficiaries. Survey results further revealed that 3.2% respondents think that they had no
credit; they call upon banks and NGOs to provide them credit facilities to improve their
living standard. Overall majority believe that credit must be utilized properly and repaid
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back and credit should be given on merit only to those beneficiaries who deserve it, this
will help credit agencies recover their loans from reliable beneficiaries. The above
findings are in agreement with Baye (2002), who reported people in areas are in poverty
because of lack of credit facilities, education and institutional arrangement that influence
rural activities and asset accumulation.
Table-79 Perception About Proper Utilization of Microcedit Loans in District
Badin. S.No. Particulars Number Percent 1 The condition is that the credit has to be utilized
properly and paid back 40 64.5
2 Microcredit should be given to those who deserve it 13 21 3 Select and identify competent groups 10 16.1 4 Conditions are determined when the credit is
disbursed 2 3.2
5 No credit banks and NGOs should give us credit 2 3.2 6 No response 11 18 Source: Survey Results 2008. 7.3.17 Purpose, Goals and Aims of VDOs in District Badin According to respondents’ opinion in Table-80, 53% of the representatives
believe that they are working in areas of education and health, while 32.2% agreed that
they are working in areas of community development, helping people to help themselves.
Similarly 32.2% respondents organized awareness campaign in their village, while 29%
respondents adopted social mobilization to promote democratic activities and assist
community leaders to build second line leadership and 26% informed that they are
working in areas of empowerment and community participation. Survey results further
revealed that 24.1% of the respondent agreed that microcredit was provided to the poor,
3.2% are working to create income generating business and building community
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infrastructure. Equally on the same proportion, 3.2% believe that they are working to
establish a vocational training centre for training both male and female on various skills
that will help them become self reliant. Only 3.2% reported that they are working in areas
of peace and human rights for their respective communities, but majority of the
respondents reported that they are working to improve the standard of education and
health, while others mobilize the people to help themselves and the third most important
was the awareness campaign. These four goals proved to be the most important factors
for the development of any society on a long term basis.
Table-80 Purpose, Goals and Aims of VDOs in District Badin. S.No. Particulars Number Percent1 Working in areas of education and health 33 53 2 Development of community, helping people to help them
selves 20 32.2
3 Awareness campaign 20 32.2 4 Social mobilization 18 29 5 Working in areas of empowerment and community
participation 16 26
6 Provision of microfinance and credit facilities 15 24.1 7 Creating income generating jobs and building community
infrastructure 2 3.2
8 Working to establish a vocational training centre for both male and female
2 3.2
9 Working in areas of peace and human right 2 3.2 Source: Survey Results 2008. 7.3.18 Specific Areas NGOs / VDOs are Working to Alleviate Poverty in District
Badin The survey results in Table-81 revealed that 68% of the respondents are
working in areas of microcredit and finance for the poor in study area, while 64.5%
reported that they are working in areas of social development and development of
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community infrastructure. Similarly, 1.6% are working in areas of education, 1.6%
agreed that they are working on empowerment and social mobilization in their respective
areas and 43.5% reported positive for on-going projects in their area. All the respondents
(100%) reported no on-going project in their areas, while the overall majority agreed that
they are working in areas of microcredit and finance but still there is shortage of credit
for the poor. The next group claimed that they are working in social development and
community infrastructure. These areas are to be developed at the moment and a lot need
to be done to make improvements in the above areas.
Table-81 Specific Areas NGOs / VDOs are Working to Alleviate Poverty in District Badin.
S.No. Particulars Number Percent1 Microcredit and finance 42 68 2 Social development and community infrastructure 40 64.5 3 Education 2 1.6 4 Empowerment and social mobilization 2 1.6 5 STATUS OF PROJECT 6 Ongoing project 27 43.5 7 No ongoing project 62 100 Source: Survey Results 2008.
7.4 Conclusions
This chapter present the results of analysis of various village development
organizations selected for the study. The comparative analysis of the two district shows
that NGOs and VDOs are working effectively to improve rural livelihoods in Sanghar
such as construction of hospital in Moa chora, primary schools, roads and other
infrastructural facilities provided by SAFWCO a local NGO. While in Badin district few
facilities were provided by VDOs and NGOs.
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It is concluded that VDOs and NGOs in Badin need to improve thier
performance for the general welfare of the people. Poverty alleviation is collective
responsibility of all. Therefore all stakeholders had to put heads together to assist the
VDOs in improving rural livelihoods in the study area.
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CHAPTER-VIII
SUMMARY, CONCLUSIONS AND RECOMMENDATIONS
8.1 Summary
The research study on “Empirical analysis of the determinants of rural
poverty in Sindh province of Pakistan” was carried out with the objective to document
the status and trend analysis of poverty situation in Sindh, measure the extent of poverty
and income inequality in selected districts of Sindh, analyse the determinants and identify
the correlates of poverty in Sindh, evaluate various government, NGOs and private sector
initiatives towards poverty alleviation and finally develop recommendations for public
and private sector regarding poverty reduction programmes in rural Sindh.
Methodology of the study was designed with a sample selection of 320
households from two districts. The sample size is appropriate at ± 6% error rate, 5 %
level of significance and proportion of 0.5 which gives maximum variance of 0.25 when
population is very large enumerated from 3000 thousand to million (Wunsch stage
sampling plan was used to select households. In the first stage one taluka was selected
from each district in the second stage two union councils were selected from each taluka
in the third stage ten villages were selected from each union council and in the fourth
stage eight households were selected from each village. Thus a sample of 160 households
were selected from each district.
To have a representative sample of the rural areas for poverty estimation
and its predictors it was decided to collect data on households of the following major
occupational groups namely landowners, tenants, wage labourers, artisans, business men,
fishermen and farmers. The techniques used to analyse the data were for measuring
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poverty head count index, poverty gap and sen index formulas were used. For analyzing
the determinants and identifying the corelates of poverty logistic regression and multiple
linear regression models were used.
In all, fourteen hypothesis were grouped into three. They were tested using
logistic regression model and null or alternate hypothesis were accepted or rejected on
the basis of significant levels of coefficients. The first hypothesis that poverty depend
upon respondents or household characteristics that is educational level. The second
hypothesis was that poverty depends upon agro-economic indicators that is land
ownership. The third hypothesis was that poverty depend upon household characteristics
that is household earners to that of proportion of earners total household size. All the
three hypotheses were tested and results showed that they were positively correlated with
poverty, thus null hypotheses were rejected and alternatives hypothesis were accepted. In
assessing the activities of village development organizations in the study areas. Data was
collected from 10 village development organizations in each district. Statistical packages
for social sciences SPSS version 16 was used to analyse the data. Secondary information
collected from various NGO’s and VDO’s helped us to critically assess the performance
of these NGO’s and VDO’s. Estimates obtained from the study were interpreted and
attempts were made to justify the findings of the present study with that of earlier studies.
8.2 Conclusions
Findings of the study revealed that public policy on poverty reduction
lacks coherent long term strategy. Similarly various poverty alleviation programmes have
failed to address the problems of rural poverty and inequality in both Sanghar and Badin
districts based on realities on the ground. It is important to examine these issues and
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address them on a long term sustainable basis. Private individuals, industrialists,
philanthropists, landlords, businessmen, farmers all stakeholders collectively have to play
a positive role in this regard.
The primary and secondary data used in this study would help policy
makers to design result oriented programmes that would address poverty and inequality
in the study area. Some important findings of the study on the basis of analysis from
primary data are as follows:
a. Conclusion Based on Analysis from Household Survey
1. Data revealed that the average age of household head in Sanghar district was 40 ±
1.01 years, while in Badin district the average age was 44 ± 1.17. This implies that
majority of the household heads are middle age people.
2. Data shows that majority i.e. 40% of the respondents in Sanghar district were
educated upto primary level and 30.6% were illiterate. In case of Badin district 28%
of the households heads were educated upto primary level.
3. Survey data confirms that respondents in Sanghar were more skill full than those
living in Badin district. This situation is closely associated with poor literacy rate in
Badin district.
4. Results revealed that the average household size in Sanghar district was 9.12 ± 0.37
members while in Badin district it was 7.62 ± 0.28 members.
5. Sanghar district has the highest number of respondents 88.1% compared to Badin
29.6% that agreed electricity was available in their respective villages. Similarly
Badin district has the highest number of respondents than Sanghar who reported that
there was no electricity in their villages.
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6. In Sanghar district 5.20 percent of the respondents agreed that gas was available,
while 94.80 percent agreed that gas was not available in their village. In Badin district
only 0.60 percent of the respondents had gas facility. While 99.4 percent had no gas
facility for cooking. This shows that majority of the people do not have gas facility in
Sanghar as compared to Badin.
7. Data confirms that in Sanghar majority of the respondents (38.90%) live in Pacca
houses, while the lowest (4.50%) live in Jhopra houses. About 24.20 percent and 32.5
percent live in semi pacca and Katcha houses respectively. In Badin district the
highest number of respondents 69.40% live in Katcha houses, 10.00 and 13.10
percent live in pacca and Jhopra houses respectively. This shows that sample
respondents in Sanghar district enjoy better housing facilities than those in Badin.
8. In Sanghar, 84.38 percent of the respondents obtained loans from various sources to
manage livelihood, while 15.63% had no credit facilities. Similarly in Badin 45.63%
percent of the respondents obtain loans from various sources, while 54.38 percent
respondents did not obtained credit facilities. This indicated that more people in
Sanghar (84.38%) had access to credit facilities as compared to Badin (45.63%).
9. Data revealed that in Sanghar district 96.30% of the respondents paid their loans
regularly, while 3.70 percent did not pay by installment regularly. While in Badin
district 97.26 percent respondents paid the installment regularly, while 2.74 percent
did not pay. This shows that majority of the respondents both in Sanghar and Badin
paid their loans regularly only a small fraction of respondents could not pay regularly.
10. Survey results in Sanghar district revealed that 31 percent of the respondents agreed
that human dispensary was available. About 69.1 percent reported that there was no
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human dispensary in their village. Similarly in Badin district only 7.6 percent agreed
that dispensary was available, while majority 92.40 percent perceived that they had
no dispensary facility.
11. In Sanghar district 14.1 percent of the respondents agreed that veterinary centre was
available whereas the majority 86 percent of the responded negatively. Similarly in
Badin district 1.3 percent of the respondents reported the existence of veterinary
centre while 98.7 percent of the respondents reported no existence of veterinary
centre in their village. This shows that people need veterinary hospitals/ centers so as
to improve the health and nutritional status of their animals.
12. Results in Sanghar district show that the average household income was Rs. 9926 ±
639 while the income per person was Rs. 1231 similarly in Badin district the
household income was Rs. 7463 ± 494 with average per person income of Rs. 1194.
This shows that the people in Sanghar have high household and individual income as
compared to Badin district.
13. Data confirms that in Sanghar district 52 percent of the respondents come under the
category of poor, while 48.1% were not poor. Similarly in Badin district head count
index was 56.2 percent while 43.8 percent were not poor. This shows that Sanghar
district has the highest number of people living above the poverty line as compared to
Badin which has the highest number of people living below the poverty line or ultra
poverty.
14. Survey results showed that in Sanghar district the average poverty gap was Rs. 373
while in Badin it was reported as Rs. 356. This shows the amount of income required
to remove the poor out of poverty is much higher in Sanghar than in Badin district.
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The sen index for two district was 0.31. Sen index show that the intensity or severity
of poverty in the two district remain the same.
15. Lorenz curve and gini coefficient for Sanghar and Badin districts were computed to
be 0.37 and 0.38 respectively.
16. Logistic regression model was applied to primary data from Sanghar district.
Dependent variable was poverty status and independent variables were land
ownership, household size, number of earners and qualification of household. The
empirical results shows that land ownership and household size were significant at P
> 0.01. Similarly number of earners and qualification of household heads were
significant at P < 0.05. This indicates that the number of earners and qualification of
household head has higher significance level than the land ownership and household
size.
17. Logistics regression model was applied to primary data for Badin. Dependent variable
was poverty status, while independent variable were land ownership, household size,
number of earners and qualification of household head. Empirical results shows that
land ownership, number of earners and qualification of household head were
significant at P< 0.05.on the other hand only number of earners were significant at P<
0.01.This indicates that land ownership,number of earners and qualification of
household heads, has a better significance level than the number of earners.
18. Multiple linear regression model was applied to primary data for Badin only to show
the superiority of logistic regression model over multiple linear regression model. The
dependent variable was per capita income, while independent variable was land
ownership household size and number of earners. Empirical results shows that land
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ownership is significant at P < 0.01. Similarly household size and number of earners
were also significant at P < 0.01 each respectively. The analyses revealed that the
qualification of household head was excluded because the probability is more than
5% of the P value. This shows satisfactory results and provide better basis for policy
formulation and suggested future in-depth research in the study area.
19. Logistics regression is assumption free model while multiple linear regression has
two assumptions to be tested for valid conclusion. Logistic regression model defined
85% cases correctly about poverty status (poor or not poor) while multiple linear
regression reported R2 0.46, which revealed that about 46% variation in dependent
variable (per capita income) were accounted for by independent variables. As stated
in the results and discussion many studies have proved the superiority of logistic
regression over multiple linear regression model in terms of predicting who are poor
and not poor.
20. It was further observed that our coefficient of determination (R2) value was high
because most of the regression coefficient showed significant results.
21. It is concluded that land ownership, household size, number of earners and
qualification of household head has significant effect on poverty. On the basis of the
above null hypothesis is rejected and alternate hypotheses are accepted.
b. Conclusions Based on Analysis from Village Development Organizations The results of data analysis from village development organizations in
Sanghar district revealed that the methodology adopted by VDOs are social mobilization
(61.3%) micro credit (56.5%) awareness (43.5%). Majority of the respondents are fully
satisfied with these three methods. About 50% of the respondents agreed that
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empowerment was satisfactory, while 13% respondents did not agree. It was noted that
66% of the respondents had positive perception on proper utilization of mcirocredit loans.
Due to these loans a substantial increase in household income was reported. About 53.2%
of the respondents were of the view that health facilities were in bad shape in their village
while 21% perceived that status of health and nutrition has improved. According to data
regarding improvement of living standard after the loan all the sample respondents 100%
agreed that their income increased and living standard improved due to the loan. Only
4.8% of the respondents believed that the loan had little impact on their living standards
due to small amount disbursed. Survey data further revealed that 64.5% of the
respondents were found to establish some income generating business for the youth,
while 53.2% had no concern with such activities. Similarly 45% of the respondents
perceived that hand pumps provided with the help of Sindh Agricultural and Forestry
Workers Coordinating Organization (SAFWCO), a local NGO had helped alleviate their
water problems. According to 24.1% respondents, they were working with Pakistan
Poverty Alleviation Fund (PPAF) to provide easy access to sweet water for the
community.
Survey results in Badin district indicated that 20 out of 62 representatives
of VDOs were of the opinion that awareness programmes were organised to increase the
perception of the people on various programmes. About 32.2% of the respondents
showed that social mobilization activities were adopted by the VDOs.
According to data regarding empowerment and participation in the
community 64.5% of the respondents perceived that the progress of empowerment was
satisfactory, while 8% respondents believed that there was lack of cooperation in
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addressing various problems faced by the community. Perceptions of respondents
regarding proper utilization of micro credit loans revealed that 64.5% agreed that the
condition attached to successful use of credit was that credit must be utilized properly and
paid back. Likewise 21% of the respondents believe that micro credit must be given to
those who deserve it. Survey results on status of health and nutrition shows that majority
69.3% of the respondents indicated that the situation was very poor in their area.
Similarly 19.3% of the respondents reported that the status was satisfactory. Data
regarding improvement of living standard after disbursement of loan revealed that 42% of
the respondents believe that their income remain stagnant because they have no credit
facilities at their disposal. Likewise 24.1% respondents agreed that only 30% of the
people improved their living standard, while 70% still live below the poverty line.
Sample respondents opinion on the role of VDOs/NGOs in establishing income
generating jobs showed that 18% of the respondents are working to create more job
opportunities for the poor, while according to 13% they have done nothing so far. Survey
results on increase in access to good quality water revealed that 34% of the respondents
installed tubewells in their village on self help basis while 27.4% reported that 10 hand
pumps were installed with the help of a local NGO Badin Rural Development Society
BRDS.
8.3 Recommendations
On the basis of conclusions drawn from primary data analysis and
qualitative inferences, the following policy recommendations are developed and
presented as follows:
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a. Recomendation Based on Analysis from Household Survey
1. Supply of quality agricultural inputs at reasonable rates may be ensured and rates of
agricultural produce may be equated to inflation.
2. Micro credit facilities should be provided to the poor house holds.
3. Public spending on basic social and economic services should be increased.
4. Poor communities may be encouraged to participate in planning and development
dialogues.
5. Local entrepreneurs and business men should launch a massive effort for job creation
and employment generation in both Sanghar and Badin this will reduce high level of
poverty.
6. Delivery of essential services and basic necessities of life would reduce the burden of
poverty in both Sanghar and Badin.
7. It is recommended the government should introduce new housing schemes through
public private partnership so as to support those in ultra poverty.
8. Head count ratio shows that the number of poor are more than non poor. One of the
measures to alleviate this extreme poverty, would be establish vocational skill
training centers in both districts through the public private partnership, so as to train
youth and women for self reliance.
9. Rural leadership and community organization developed programmes may be
launched by major NGOs and public sector organization.
10. It is recommended that VDOs should encourage the formation of service cooperatives
at village level by channeling short and medium term credit through this agency. This
will reduce reliance on money lenders.
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11. Majority of the respondents in Badin revealed that for the last 3 years NGOs are not
working for poverty alleviation in their villages. It is recommended that government
should start implementing new poverty alleviation pogrammes to support the poor.
12. Majority of the respondents in the study area lauded the policies of the previous
government such as Rozgar Scheme and NCHD National Centre For Human
Development. In view of the above it is recommended that the new government
should continue with the above programmes to alleviate poverty.
13. The rice growers of Badin district are of the opinion that local government should be
involved towards improvement of market facilities in their area.
14. There is a need to encourage active participation of rural women in income
generating jobs through a very strong social mobilization.
15. There is a need to increase the volume of zakat and other social safety nets and
improve targeting of beneficiary and efficiency in distribution. This will surely
contribute to poverty alleviation particularly in Badin district.
16. There is a need to improve health and nutrition, preventive hygiene provision of safe
drinking water to support the rural poor.
17. Microcredit institutions working to help the rural poor in Sindh should examine
operational procedures of partner organization through whom the credit is disbursed
for better targeting the poor.
18. Network of institutional credit may be widened in rural areas.
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b. Recommendation Based on Analysis from Village Development Organization 1. VDOs should raise money so as to buy communication facilities.
2. Credit agencies should provide free interests loans to the poor so that they can be self
reliant.
3. Infrastructural development is needed in both Sanghar and Badin so as to reduce the
level of poverty among the poor.
4. VDOs must liase with bigger NGOs so as to establish income generating business to
those in extreme poverty.
5. VDOs should not rely on government to provide funds for future projects. Instead
they can raise funds through savings and donations from rich individuals.
6. VDOs should establish good relations with land department so that the problems of
the community could be addressed.
7. There is a need for capacity building this will help the VDOs to bring people together
for solving their own problems.
8. Irrigations water should be provided in Badin so that the poor could utilize their lands
for crop production.
9. VDOs should be build water tank in the villages in view of shortage of water for
drinking.
10. There is a need to start different public welfare schemes at grass root level for
improving livelihood of the poor.
11. VDOs along with rich individuals and philanthropist should build houses to all those
effected by floods and cyclones, give them credit facilities for income generating
business.
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12. A Pragmatic interventions by NGOs and other government aid agencies would reduce
reliance on child labour.
13. Government should restrict children from performing hazardous jobs such as hawking
and should protect the right of a child in the study areas.
14. Micro Finance Banks should introduce micro saving and micro insurance schemes
through creativity and innovation so as to provide better services to poor borrowers in
Sanghar and Badin.
15. Rural women NGOs already working in Sanghar and Badin be strengthened, they
should include in their charters training of women for income generating jobs.
16. There is need to investigate the socio-cultural and economic reasons of low female
participation in agricultural activities in the study area.
17. VDOs and NGOs should develop working relationship between different agencies for
smooth functioning of poverty alleviation programmes.
18. Donor Agencies should establish more trainings in partnership with VDOs and NGOs
for upgrading and improving human resources through better medical services,
nutrition and environmental conditions.
19. Government should give support price to farmers in the study area and motivate them
to adopt recommended practices this will reduce poverty among the poor.
20. VDOs and NGOs should ensure that new agricultural technologies are introduced to
help farmers to improve and increase production so as to improve their living
standards.
21. VDOs and NGOs should ensure that farmers get fair prices of their product through
out the year this will help them in raising their income and go out of poverty.
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22. Both Sanghar and Badin districts should improve their drainage system and keep their
environment clean. This is for their betterment.
23. It is recommended that a committee should be constituted in the study areas to
manage the sanction of loans to rural women and recovery of installment as well.
24. Trees make the environment clean and protect the industrial pollution. In this regard
there should be a sharp campaign about growing trees in the study area.
25. Government should provide facilities for institutional building to the local VDOs /
NGOs. This will encourage them to work sincerely towards poverty alleviation.
c. Village Development Organizations and NGOs Should
1. Address the real problems of the poor in their respective communities.
2. Ensure sustainability of income generating activities in their respective areas.
3. Ensure a strong and regular feedback regarding solutions of problems related to water
supply, road construction, building of a primary school, bridge or rural health centre.
4. Establish girls primary schools in the study area.
5. Plan and implement poverty alleviation programmes in District Sanghar and Badin.
6. Focus on awareness campaign, mobilization, provision of irrigation water health and
education facilities. These issues should be given priority at all times.
d. General Recommendations
1. There is need for a very strong monitoring and evaluation of NGOs so as to make
sure that their services reach to the poorest of the poor in the study area. The
monitoring and evaluation should be carried out by independent research
organizations.
2. Empower the poor with the objectives of providing them with a voice within their
society so that empowerment is linked back to the economic performance of the poor.
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3. An institutional framework is needed that is favourable to the reduction of poverty
which can analyse the trends in trade microfinance environment and their impact on
the poor.
4. Rural poor in Sanghar and Badin should involve themselves in other socioeconomic
activities such as monitoring input market and agro processing in order to diversify
their means of livelihood so as to generate more income.
5. Poverty push children to child labour as observed in the study areas there is need to
establish a child support policy similar to that of united states which will support
these children.
6. Foreign NGOs should provide facilities for institutional building to the local
VDOs/NGOs.
7. Handsome package should be given to VDOs/NGOs workers on the basis of
performance this will encourage them to give positive results.
8. There is a need to create conditions in which the poor are either given or enabled to
acquire their assets and a peaceful environment to benefit from those assets.
9. It is important to develop crop forecasting mechanism in the study areas this will
provide reliable information to farmers on a regular basis.
10. All stake holders should develop institutional reforms with pro-poor strategies in the
irrigation sector.
11. Loaning procedures of formal credit institutions is complicated, it should be
simplified and preferably translated in local languages such as Urdu, Sindhi, Punjab,
Pashto and Baloch languages.
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12. Active and committed women engaged in poverty alleviation in rural areas should be
guaranteed loans for promoting cottage industries.
e. Strategy for Self Employment in Sindh to Alleviate Poverty Among the Poor
The rural areas of Sindh has a very good scope for promoting self
employment and income. The desired results could be achieved if a comprehensive
longterm strategy comprising of various programmes and policies should be evolved and
implemented with sincerity. The strategy should combine the following:-
1. Proper and regular supply of farm inputs with reasonable prices for outputs.
2. Cooperative farming for small farmers.
3. Penalty for leaving land uncultivated for more than one year.
4. Adequate credit facility with guidance and supervision.
5. Provision of information, with proper guidance and counseling.
6. Proper manpower training and re-orientation of education system.
7. Provision of socio-economic infrastructure
8. Decentralization and community participation.
245
8.4 Follow Up Studies
• This research work should be repeated time and again to identify the number,
intensity dimension and nature of poverty problems which may arise with passage
of time in both Sanghar and Badin districts.
• Follow up studies may be conducted in future to continue where the researcher
stopped and to identify those in ultra poverty and recommend poverty alleviation
measures so as to bring the poor out of poverty. In particular this type of studies
may be conducted in Tharparkar and Jacobabad areas where the incidence of
poverty is also reported to be high.
• There is a need for research that will create a better understanding of the linkage
between growth and poverty and help to formulate policies that seeks to maximize
the effect of growth on poverty.
246
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APPENDIX-A
SECONDARY DATA
A1 Sindh Intra-Province Ranking Net Primary School Enrolment Rate
1998 2005 Rank District Rate Rank District Rate 1 Karachi 56.9 1 Karachi 65.0 2 Nowshero Feroz 38.4 2 Sukkur 55.0 3 Sukkur 36.2 3 Nowshero Feroz 54.0 4 Hyderabad 35.9 4 Shikarpur 52.0 5 Khairpur 33.5 5 Ghotki 50.0 6 Dadu 32.2 6 Badin 48.0 7 Sanghar 30.3 7 Tharparkar 46.0 8 Nawabshah 24.9 8 Hyderabad 45.0 9 Mirpurkhas 28.7 9 Khairpur 44.0 10 Larkana 28.5 10 Larkana 42.0 11 Ghotki 24.4 11 Mirpurkhas 42.0 12 Jacobabad 21.8 12 Sanghar 42.0 13 Badin 18.4 13 Nawabshah 41.0 14 Shikarpur 18.2 14 Dadu 40.0 15 Thatta 16.3 15 Thatta 33.0 16 Tharparkar 13.0 16 Jacobabad 25.0 Source: Pakistan Millennium Development Goals Report 2006. Centre for Research on Poverty
Reduction and Income Distribution Planning Commission Islamabad. A2 Sindh Intra-Province Ranking on Literacy Rate 10 years and above.
1998 2005 Rank District Rate Rank District Rate 1 Karachi 65.3 1 Karachi 78.1 2 Sukkur 46.6 2 Sukkur 63.3 3 Hyderabad 44.3 3 Nowshero Feroz 58.1 4 Nowshero Feroz 39.1 4 Shikarpur 55.9 5 Mirpurkhas 36.0 5 Hyderabad 52.5 6 Dadu 35.6 6 Ghotki 50.8 7 Khairpur 35.0 7 Khairpu 48.1 8 Larkana 35.0 8 Dadu 47.3 9 Nawabshah 34.1 9 Nawabshah 45.2 10 Shikarpur 32.0 10 Sanghar 45.1 11 Sanghar 31.0 11 Mirpurkhas 44.0 12 Ghotki 29.0 12 Badin 41.8 13 Badin 24.6 13 Larkana 38.2 14 Jacobabad 23.7 14 Tharparkar 36.2 15 Thatta 22.1 15 Thatta 34.6 16 Tharparkar 18.3 16 Jacobabad 33.8 Source: Pakistan Millennium Development Goals Report 2006. Centre for Research on Poverty
Reduction and Income Distribution Planning Commission Islamabad.
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A3 Sindh Intra-Province Ranking on GPI NER Net Enrolment Rate. 1998 2005
Rank District Rate Rank District Rate 1 Karachi 0.94 1 Karachi 0.97 2 Mirpurkhas 0.79 2 Sukkur 0.86 3 Hyderabad 0.76 3 Shikarpur 0.86 4 Sukkur 0.75 4 Nowshero Feroz 0.84 5 Larkana 0.74 5 Dadu 0.78 6 Badin 0.74 6 Hyderabad 0.76 7 Dadu 0.73 7 Ghotki 0.75 8 Khairpur 0.73 8 Sanghar 0.75 9 Nawabshah 0.72 9 Badin 0.74 10 Shikarpur 0.72 10 Tharparkar 0.72 11 Sanghar 0.71 11 Thatta 0.71 12 Ghotki 0.68 12 Khairpur 0.71 13 Nowshero Feroz 0.67 13 Mirpurkhas 0.69 14 Jacobabad 0.64 14 Nawabshah 0.65 15 Tharparkar 0.64 15 Larkana 0.63 16 Thatta 0.62 16 Jacobabad 0.47 Source: Pakistan Millennium Development Goals Report 2006. Centre for Research on Poverty
Reduction and Income Distribution Planning Commission Islamabad. A4 Sindh Intra-Province Ranking on Youth Literacy GPI Gender Party Index.
1998 2005 Rank District Rate Rank District Rate 1 Karachi 0.92 1 Karachi 0.98 2 Hyderabad 0.72 2 Sukkur 0.75 3 Mirpurkhas 0.59 3 Hyderabad 0.69 4 Sukkur 0.58 4 Mirpurkhas 0.65 5 Dadu 0.51 5 Shikarpur 0.65 6 Sanghar 0.46 6 Nowshero Feroz 0.61 7 Larkana 0.45 7 Dadu 0.58 8 Nowshero Feroz 0.45 8 Nawabshah 0.56 9 Nawabshah 0.45 9 Khairpur 0.55 10 Khairpur 0.43 10 Badin 0.55 11 Shikarpur 0.42 11 Larkana 0.48 12 Badin 0.39 12 Thatta 0.45 13 Thatta 0.39 13 Sanghar 0.43 14 Jacobabad 0.37 14 Ghotki 0.42 15 Ghotki 0.29 15 Tharparkar 0.42 16 Tharparkar 0.23 16 Jacobad 0.32 Source: Pakistan Millennium Development Goals Report 2006. Centre for Research on Poverty
Reduction and Income Distribution Planning Commission Islamabad.
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A5 Sindh Intra-Province Ranking on Immunnization 12-23 Month 1998 2005
Rank District Rate Rank District Rate 1 Larkana 69.8 1 Hyderabad 87.9 2 Nowshero Feroz 65.0 2 Nowshero Feroz 87.6 3 Karachi 64.3 3 Karachi 83.4 4 Sanghar 63.7 4 Shikarpur 82.9 5 Hyderabad 63.1 5 Larkana 82.1 6 Mirpurkhas 62.5 6 Dadu 78.4 7 Sukkur 59.9 7 Ghotki 78.1 8 Khairpur 59.2 8 Sukkur 75.3 9 Jacobabad 58.8 9 Badin 75.0 10 Shikarpur 55.7 10 Mirpurkhas 70.6 11 Dadu 55.4 11 Thatta 63.7 12 Nawabshah 54.5 12 Khairpur 61.7 13 Tharparkar 53.6 13 Tharparkar 53.6 14 Thatta 51.9 14 Nawabshah 51.5 15 Ghotki 51.8 15 Sanghar 45.8 16 Badin 43.6 16 Jacobabad 35.2 Source: Pakistan Millennium Development Goals Report 2006. Centre for Research on Poverty
Reduction and Income Distribution Planning Commission Islamabad. A6 Sindh Intra-Province Ranking on Water Supply.
1998 2005 Rank District Rate Rank District Rate 1 Shikarpur 98.2 1 Shikarpur 99.7 2 Jacobabad 97.1 2 Ghotki 99.6 3 Ghotki 96.8 3 Hyderabad 99.0 4 Nowshero Feroz 94.9 4 Nowshero Feroz 99.0 5 Nawabshah 94.5 5 Nawabshah 98.9 6 Khairpur 94.2 6 Khairpur 98.3 7 Sukkur 93.1 7 Sukkur 98.1 8 Larkana 89.6 8 Larkana 93.1 9 Hyderabad 89.6 9 Jacobabad 93.0 10 Karachi 84.9 10 Sanghar 90.3 11 Sanghar 71.2 11 Karachi 88.8 12 Dadu 68.9 12 Badin 88.0 13 Mirpurkhas 49.5 13 Dadu 73.7 14 Badin 41.4 14 Thatta 64.0 15 Thatta 40.3 15 Mirpurkhas 58.2 16 Tharparkar 4.2 16 Tharparkar 28.3 Source: Pakistan Millennium Development Goals Report 2006. Centre for Research on Poverty
Reduction and Income Distribution Planning Commission Islamabad.
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A7 Sindh Intra-Provinicial Ranking on Sanitation. 1998 2005
Rank District Rate Rank District Rate 1 Karachi 95.8 1 Nowshero Feroz 98.5 2 Larkana 73.3 2 Larkana 97.6 3 Hyderabad 71.4 3 Nawabshah 96.0 4 Nowshero Feroz 71.0 4 Karachi 95.1 5 Dadu 67.2 5 Sanghar 94.9 6 Sukkur 58.4 6 Dadu 94.1 7 Shikarpur 57.6 7 Hyderabad 88.8 8 Thatta 52.0 8 Ghotki 86.0 9 Khairpur 52.0 9 Sukkur 82.5 10 Nawabshah 50.8 10 Shikarpur 81.1 11 Mirpurkhas 44.1 11 Jacobabad 76.4 12 Sanghar 43.7 12 Khairpur 72.1 13 Badin 43.4 13 Badin 70.0 14 Jacobabad 35.6 14 Thatta 63.9 15 Ghotki 26.7 15 Mirpurkhas 50.0 16 Tharparkar 22.1 16 Tharparkar 33.2 Source: Pakistan Millennium Development Goals Report 2006. Centre for Research on Poverty
Reduction and Income Distribution Planning Commission Islamabad. A8 Loans advance to rural poor in Sindh from inception upto 2006. Description As at December
2005 Current year
2006 As at December
2006 Loans disbursed Male
Female Total
75,443,456 65,480,227 140,923,683
74,344,000 53,405,000 127,749,000
147,787,456 118,885,227 268,672,683
Clients served Male Female Total
9,187 9,127 18,314
7,729 5,157 12,886
16,916 14,284 31,200
Source: SAFWCO Annual Report 2006 Page 12. A9 Loans advance under different categories during the year 2006.
Loans Heads
Male Female Total
Agricultural Development
1135 14,707,000 121 1,404,000 1,256 16,111,000
Livestock Management
1841 17,362,000 3419 38,266,000 5,260 55,628,000
Retailing 3410 30,996,000 914 8,178,000 4,324 39,174,000 Handcraft Development
128 1,116,000 509 3,880,000 637 4,996,000
Other Business
1215 10,163,000 194 1,677,000 1,409 11,840,000
Total 7728 74,344,000 5157 53,405,000 12886 127,749,000 Source: SAFWCO Annual Report 2006 Page 12.
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A10 Income Increase after Loan Disbursed By NGOs.
Did Loan Result in Sustainable Increase in Income NGOs Yes % No % Equal % Total %
KK 42.90 47.60 9.50 100.00 OPP 71.10 17.80 11.10 100.00
PIEDAR 56.50 21.70 21.70 100.00 KASHF 66.70 33.30 - 100.00 NRSP 81.60 7.90 10.50 100.00 OWP - - 100.00 100.00 ASB 53.30 46.70 - 100.00
Source: NHDR/A1 Hamid Spot Survey 2001. A-11 Proportion of people below poverty line between 1990 and 2015
Indicators Definition 1990/91 2001-01 2010 MTDF Targets
2015 MDG Targets
Proportion of people below the calorie based food plus non-food poverty line.
26.1% 32.1% 21% 13%
Source: MTDP frame work 2005-10 planning commission Govt of Pakistan May 2005 P58. A-12 Proportion of people who suffer from hungar have between 1990 and 2015.
Indicators Definition 1990/91 2001-01 2010 MTDF Targets
2015 MDG Targets
Proportion of people below minimum level of dietary energy consumption. Prevalence of under weight children under 5 years of age
Proportion of people
below 2350 per day
Proportion of people
below 2350 calories per day of food
intake
25%
40%
30%
41.5%
15%
28%
13%
<20%
Source: MTDP frame work 2005-10 planning commission Govt of Pakistan May 2005 P58.
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A-13 Millennium development goals strategies. Indicators Benchmark
2004-05 MTDF Targets
2010 MDG Targets
2015 MDG
Targets Proportion of people below minimum level of dietary energy consumption.
25%
30%
15%
13%
Prevalence of under weight children under 5 years of age
40%
41.5% 28%
<20%
Source: MTDP frame work 2005-10 planning commission Govt of Pakistan May 2005 P58. A-14 Millennium Development Goals Strategies.
Indicators Benchmark 2004-05
MTDF Targets 2010
MDG Targets
Literacy rate (Poplot) Total Male Female Youth literacy rate (Pop 15-24) Total Male Female Gender parity (index (GPI) Primary education secondary education
56 62 44
66 79 52
0.80 0.72
77 85 66
80 90 70
0.94 0.90
88 89 87
100 100 100
1.00 0.94
Source: MTDP frame work 2005-10 planning commission Govt of Pakistan May 2005 P 76.
266
A-15 Less Developed Districts in provinces of Pakistan. Punjab SINDH NWFP BALUCHISTAN
Rajanpur D.G. Khan Layyah Bhakker Mazaffargargh Bahawalfur Bahawalnagar Khushab
Mithi Thatta Badin Gotki
Sanghar Parts of
Mirpurkhas Part of
Khairpur Parts of Sukkur
Charsadda Bannu
Lakki Marwat Tank
Batgram
Upper Dir
Shanglapar
Kohistan
Musa Khel Kharan Kohlu
Awaran Zhob
Jhal Magsi
Panjgur
Khuzdar
Source: MTDP frame work 2005-10 planning commission Govt of Pakistan May 2005 P 219 A-16 Public expenditure in education and tertiary enrolment in Asia.
Country Public Expenditure on Education (%GDP)
Tertiary Enrolment (% of population age
17-12 years) South Korea Japan Singapore Malaysia China India Pakistan
7.9 3.6 3.0 7.9 2.3 4.2 2.2
77.6 47.7 46.0 28.2 12.6 10.5 4.2
Source: Global Compititiveness Report (2004-05) and Higher Education Commission Islamabad. A17 Future Water Availability in Sindh (1998-2030).
Year Population (million)
Water flow to sindh (MAF) Per capita water availability (cubic meter)
1 45 40 35 25
1998 30 1852 1646 1440 1029
2002 34 1634 1452 1271 908
2010 43 1292 1148 1005 718
2020 56 992 882 772 551
2030 75 741 658 576 412
Source: (1) 25 years of Sindh Statistics Govt. of Sindh 1998 (2) IUCN Report on Sindh 2005.
267
A18 Ten indicators to Assess poverty in Developing Countries Recommended by Dr. Muhammad Yunus of Greem Bank Dhaka Banglandesh
A person is considered to have moved out of poverty if his family fulfils the followings:
1. The family lives in a house worth Rs. 20,000 or a house with a tin roof and each member of the family is able to sleep on bed instead of on the floor.
2. Family members drink pure water of tube wells or water purified by using
alum, arsenic free, purifying tablets or pitcher filters.
3. All children in the family over six year of age going to school or finished primary school.
4. Family members have adequate clothing for every day use warm clothing
for winter such as sweaters, blankets etc mosquito nets to protect themselves from mosquitoes.
5. Family has sources of additional income such as vegetable garden, fruit
bearing trees etc so that they are able to fall back on these sources of income when they need additional money.
6. The borrower maintains an average annual balance of Rs. 5000 in his/her
saving account.
7. Family experiences no difficulty in having three square meals a day throughout the year i.e. no member of the family goes hungry any time of the year.
8. Family can take case of their health if any member of the family falls ill,
family can afford take care of all necessary step to seek adequate health care.
Source: Grameen bank, 2007 Dhaka www.grameen.com
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APPENDIX-B
SELECTION OF VILLAGES, VDOS AND SAMPLE RESPONDENTS IN DISTRICT SANGHAR
B1 VILLAGES SELECTED FOR HOUSEHOLD SURVEY IN LUNDO UC
1. Village Mithu Rind 2. Village Qurban Ali Zardari 3. Village Bhaji Rind 4. Village Jando Rind 5. Village Sarfraz Lashari 6. Village Dhighano Rind 7. Village Muhib Ali Rind 8. Village Murad Ali Rind 9. Village Yaro Rind 10. Village Khan Rind
B2 VILLAGES SELECTED FOR HOUSEHOLD SURVEY IN BARHOON UC
1. Village Bachal Unar 2. Village Beero Mula Keerio 3. Village Khioro Khan Sanjrani 5. Village Shah Mardan Abad 6. Village Mulla Hurmat 6. Village Dhani Bux Sanjrani 7. Village Mir Ghulam Shah 8. Village Gul Mohammad Sanjrani 9. Village Mohammad Umar Kerio 10. Village Khair Mohammad Dhan B3 LIST OF VILLAGE DEVELOPMENT ORGANIZATIONS (VDO’S) AND
IN SHAHDADPUR DISTRICT SANGHAR
1. Village Welfare Development Organization Moh’d Khan Khaskhelli 2. Village Development Organization Mua Chora 3. Village Welfare Development Organization Shah Mardan Abad 4. Females Welfare Development Organization Ahmed Khan Khaskhelli Village 5. Indus Welfare Association Kurkali Village 6. Village Welfare Development Organization Murad Ali Rind 7. Nojwaw Etahad Village Development Organization Essan Chandio Village 8. Village Development Organization Sher Khan Lashari 9. Rashidia Social Welfare Development Organization Kheto Jat Village 10. Village Development Organization Daim Thahim
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B4 LIST OF SAMPLE RESPONDENTS FROM LUNDO UC TALUKA SHAHDADPUR
1. VILLAGE MITHU RIND
1. Sukhio Rind 2. Lakladino Rind 3. Madad Ali Rind 4. Gul Bahar 5. Ranam Ali 6. Sobdar Khan 7. Allah Wadayio Rind 8. Kamal Khan Rind
2. VILLAGE QURBAN ALI ZARDARI
1. Shahid Ali zardari 2. Mukhtiar Ali 3. Irshad Ali 4. Mian Bux Zardari 5. Ali Mohammad 6. Tagio Khan 7. Leemon Khan 8. Muhran Ali
3. VILLAGE BHAJI RIND
1. Jam Sadiq Ali 2. Goman Khan 3. Mustaq Ali 4. Ghulam Hyder Rind 5. Lashkari Rind 6. Barkat Ali 7. Asadullah Rind 8. Walidad Rind
4. VILLAGE JANDO RIND
1. Gulab Khan Rind 2. Dil Murad Lashari 3. Mohammad Juman Rind 4. Shahid Faqeer 5. Imam Bux Rind 6. Ahmad Khan Rind 7. Mohammad Amin 8. Ahmad Khan Sarwari
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5. VILLAGE SARFRAZ LASHARI
1. Yar Muhammad Lashari 2. Akbar Ali 3. Qurban Ali Lashari 4. Mashook Ali 5. Amir Ali 6. Mumtaz Ali 7. Ghulam Shabir 8. Rajab Ali Lashari
6. VILLAGE DHIGHANO RIND
1. Feroz Ali Rind 2. Ashik Hussain 3. Ghulam Nabi Rind 4. Taj Muhammad 5. Arif Rind 6. Ghulam Sarwar Rind 7. Altaf Hussain Rind 8. Ghulam Raza Rind
7. VILLAGE MUHIB ALI RIND
1. Shahid Hussain Pinjaro 2. Mashong Ali 3. Mohammad Ali Rind 4. Mohram Uajuno 5. Mohammad Achar 6. Muhib Ali Rind 7. Mohammad Ibrahim Rind 8. Ala Mohammad
8. VILLAGE MURAD ALI RIND
1. Ali Dino Rind 2. Ali Nawaz Rind 3. Mashong Ali Rind 4. Mohammad Hassan Lakho 5. Aijaz Ali Rind 6. Muhbat Ali Rind 7. Abdul Khalique 8. Ashique Hussain Rind
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9. VILLAGE YARO RIND
1. Himat Ali Rind 2. Zahoor Ali Rind 3. Ali Shah Rind 4. Akhtar Ali Rind 5. Ghulam Mustafa Rind 6. Qambar Ali Rind 7. Taj Khan 8. Mohammad Sharif
10. VILLAGE KHAN RIND
1. Malaro Khan Rind 2. Arbab Khan 3. Sajjan Ali 4. Muhammad Murad 5. Abdul Salam 6. Inayat Ali 7. Mohammad Azeem 8. Pireendito Rind
B5 LIST OF SAMPLE RESPONDENTS FROM BARHOON UC TALUKA SHAHDADPUR DISTRICT SANGHAR
1. VILLAGE BACHAL UNAR
1. Mohammad Bachal Unar 2. Lal Mohammad 3. Ali Mohammad 4. Lalo Bhull 5. Ghodo Bhul 6. Anopu Bhul 7. Khan Mohammad 8. Amboo Bhul
2. VILLAGE BEERO MULA KEERIO
1. Hassan Bux Keerio 2. Soodo Khan 3. Manshiar Bhatt 4. Munthar Ode 5. Dildar Hussain 6. Rajab Ali Keerio 7. Sanwan Keerio 8. Chanesar Keerio
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3. VILLAGE KHIORO KHAN SANJRANI
1. Rajh Mohammad Sanjrani 2. Hussain Bux Sanjrani 3. Noor Muhammad 4. Ali Ahsan Sanjrani 5. Mula Bux Sanjrani 6. Sultan Ahmed 7. M. Bux Sanjrani 8. Mohammad Azeem
5. VILLAGE SHAH MARDAN ABAD
1. Noor Mohammad Mangi 2. Khair Muhammad. 3. Shahnawar Mangi 4. Muhammad Iliyas 5. Shad Ali 6. Muhammad Juman 7. Bahram Hussain 8. Manik Mangi
6. VILLAGE MULLA HURMAT
1. Kurban Ali 2. Abdul Hadi shah 3. Mumtaz Ali 4. Mohammad Hussain 5. Abdul Alim shah 6. Abdul Raheem Kario 7. Ali Hassan Talpur 8. Ashil Ali Sayad
6. VILLAGE DHANI BUX SANJRANI
1. Mohammad Isa 2. Dholio Khan 3. Dilbar Hassan 4. Mohammad Yusuf 5. Abdul Rauf 6. Niaz Hussain 7. Allh Warayo Sanjrani 8. Asghar Ali
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7. VILLAGE MIR GHULAM SHAH
1. Ghulam Mujtaba 2. Shankhar Bheel 3. Ali Sher Shah 4. Ghulam Shabir Bahanojo 5. Abdul Sattar Bahanojo 6. Tik Mio 7. Mohammad Sachal 8. Mir Ahmed
8. VILLAGE GUL MOHAMMAD SANJRANI
1. Ahmed Solangi 2. Gul Mohammad Sanjrani 3. Suleiman Sanjrani 4. M Juman Solangi 5. Ali Bux Solangi 6. M. Mithal Solangi 7. Khuda Bux Sanjrani 8. Hussain Bux Solangi
9. VILLAGE MOHAMMAD UMAR KERIO
1. Photo Kerio 2. Munawar Ali Kerio 3. Mohammad Idress 4. Manzoor Ahmed Kerio 5. Mitho Khan 6. Abdullah Kerio 7. Mohammad Khan 8. Lakhadino Kerio
10. VILLAGE KHAIR MOHAMMAD DHAN
1. Jani Bheel 2. Mohammad Yusuf 3. Hurchand Bheel 4. Atam Bhul 5. Allah Bux Dhari 6. Sokhsijo Bheel 7. Arbab Ali Dhari 8. Ali Mohammad Dhari
274
B6 LIST OF MEMBERS OF VILLAGE DEVELOPMENT ORGANIZATIONS INTERVIEWED IN DISTRICT SANGHAR
1. VILLAGE WELFARE DEVELOPMENT ORGANIZATION MOH’D
KHAN KHASKHELLI
1. Mohammad Miral 2. Abdul Latif 3. Wahid Ali 4. Ghulam Mohammad 5. Amir Ali 6. Atta Muhammad Khaskhelli
2. VILLAGE DEVELOPMENT ORGANIZATION MUA CHORA
1. Mohammad Abbas Dhari 2. Abdul Majeed Dhari 3. Ghulam Qadir Dhari 4. Ali Hassan Dhari 5. Mohammad Ameen 6. Muhammad Saddique
3. VILLAGE WELFARE DEVELOPMENT ORGANIZATION SHAH
MARDAN ABAD
1. Abdul Nawaz 2. Ali Hassan 3. Shah Nawaz 4. Abdul Haq 5. Nur Muhammad 6. Ali Nawaz
4. FEMALEs WELFARE DEVELOPMENT ORGANIZATION AHMED KHAN KHASKHELLI VILLAGE
1. Salim Katoon 2. Ms Hanifa 3. Khatoon Bibi 4. Bilayat Khatoon 5. Sadori Bibi 6. Ms Habib Khatoon
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5. INDUS WELFARE ASSOCIATION KURKALI VILLAGE
1. Abdul Ghafoor 2. Jaga Ram 3. Ran Faisal 4. Rashid Hussain 5. Tajmal Hussain 6. Ran Abid
6. VILLAGE WELFARE DEVELOPMENT ORGANIZATION MURAD ALI
RIND
1. Aijaz Ali Rind 2. Habib Allah Rind 3. Altaf Hussain Rind 4. Muhammad Hassan Lakho 5. Qanbar Ali 6. Karim Bux
7. NOJWAW ETAHAD VILLAGE DEVELOPMENT ORGANIZATION ESSAN CHANDIO VILLAGE
1. Mohammad Yaqoob 2. Khan Mohammad 3. Ghulam Nabi 4. Abdul Rahman 5. Nazeer Ahmad 6. Mohammad Pinjal
8. VILLAGE DEVELOPMENT ORGANIZATION SHER KHAN LASHARI
1. Haal Nawaz Lashari 2. Gul Hassan Khashkheli 3. Bashir Ahmad Khaskhelli 4. Nazar Mohammad Chang 5. Riaz Hussain 6. Ali Nawaz Lashari
9. RASHIDIA SOCIAL WELFARE DEVELOPMENT ORGANIZATION
KHETO JAT VILLAGE
1. Karim Bux 2. Mohammad Malook 3. Mohammad Ilyas Mahar 4. Daoo 5. Mr Kheto 6. Mr Neebo
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10. VILLAGE DEVELOPMENT ORGANIZATION DAIM THAHIM
1. Bahadur Thahim 2. Mohammad Thahim 3. Gul Mohammad Thahim 4. Anwar Ali Thahim 5. Hazoor Bux Thahim 6. Ghulam Hyder Thahim
APPENDIX-C
SELECTION OF VILLAGES, VDOs AND SAMPLE RESPONDENTS IN DISTRICT BADIN
C1 LIST OF SAMPLE RESPONDENTS SEERANI UC
1. Micho Mall Village 2. Ishaq Khaskheli Village 3. Haji Sumar Mallah Village 4. Allah Dino Khaskheli Village 5. Arab Sheedi Village 6. Mithoo Turk Village 7. Hameer Bheel Village 8. Bhugro Mall Village 9. Hote Moosepoto Village 10. Ahmedabad Village C2 LIST OF SAMPLE RESPONDENTS BUGHRA MEMON UC TALUKA
BADIN DISTRICT BADIN
1. Deenar Talpur Village 2. Umar Khaskheli Village 3. Allah Rakio Jat Village 4. Punhoo Pali Village 5. Allah Rakio Jat Village 6. Khamoon Mallah Village 7. Ramzan Jat Village 8. Bakhsho Dero Village 9. Juma Mallah Village 10. Darya Khan Khashkeli Village
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C3 LIST OF VILLAGE DEVELOPMENT ORGANIZATIONS (VDOs) IN TALUKA BADIN DISTRICT BADIN INTERVIEWED FROM 15 MAY 2008 TO 7 NOV 2008
1. Village Development Organization Arab Sheedi 2. Village Development Organization (Male and Female) Bughro Mall 3. Brds Village Development Organization Ishaq Khaskheli 4. Village Development Organization Mircho Mall 5. Darya Khan Khaskheli Welfare Organization 6. Juman Mallah Welfare Organization 7. Bahar Community Organization Buxkho Dero 8. Village Development Organization Deenar Khan Talpur 9. Village Development Organization Umar Khaskheli 10. Village Development Organization Punhoo Pali C4 LIST OF SAMPLE RESPONDENTS SEERANI UC TALUKA BADIN
DISTRICT BADIN
1. MICHO MALL VILLAGE
1. Dhano Meghwar 2. Bhoro Meghwar 3. Bheemo Meghwar 4. Sakrio Meghwar 5. Anb Meghwar 6. Kachro Meghwar 7. Mircho Meghwar
2. ISHAQ KHASKHELI VILLAGE
1. Ali Ahmad 2. Ramzan Khaskheli 3. Dr Abdul Aziz 4. Mohammad Khaskheli 5. Mehram Khaskheli 6. Abdul Razak Khaskheli 7. Ibrahim Khaskheli 8. Juman Khaskheli
3. HAJI SUMAR MALLAH VILLAGE
1. Gul Hassan Mallah 2. Muhd Arib Mallah 3. Rashid Khan 4. Aijaz Hashim 5. Abdul Sattar 6. Bashir Ahmad
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4. ALLAH DINO KHASKHELI VILLAGE
1. Gul Hassan Khaskheli 2. Usman Khaskheli 3. Miseeri Khaskheli 4. Vikyo Khaskheli 5. Abu Talib Khaskheli 6. Abdullah Khaskheli 7. Ahmad Khaskheli 8. Karim Bux Khaskheli
5. ARAB SHEEDI VILLAGE
1. Ghulam Hassan Sheedi 2. Achar Sheedi 3. Num Sheedi 4. Ismail Sheedi 5. Ghulam Sheedi 6. Ali Muhammad 7. Kandero Sheedi 8. Ramzan Sheedi
6. MITHOO TURK VILLAGE
1. Khali Ahmad 2. Abdul Basit 3. Shabbir Hussain 4. Amanullah Bashar 5. Ghulam Ali 6. Muhammad Imran 7. Saleem Akhtar 8. Shamim Ahmad
7. HAMEER BHEEL VILLAGE
1. Galo Bheel 2. Baghai Bheel 3. Soomar Bheel 4. Hameer Bheel 5. Photo Bheel 6. Dodo Bheel 7. Bachayo Bheel 8. Narain Bheel
279
8. BHUGRO MALL VILLAGE
1. Sajan Meghwar 2. Sakrio Mal 3. Manghal Meghwar 4. Soomar Meghwar 5. Soomar Meghwar 6. Mangi Meghwar 7. Kirshan Meghwar 8. Poem Meghwar
9. HOTE MOOSEPOTO VILLAGE
1. Syed Sohail Shah 2. Hussain Ahmad 3. Tariq Majeed 4. Pervez Tahir 5. Munawar Bashir 6. Ghulam Mustafa 7. Faiz Muhammad 8. Zamir Hussain
10. AHMEDABAD VILLAGE
1. Abdul Razak 2. Talha Mehmood 3. Akbar Ali 4. Ghulam Murtaza 5. Arshad Javed 6. Aslamm Mustafa 7. Muzafar Ahmed 8. Abdul Jabbar
C5 LIST OF SAMPLE RESPONDENTS BUGHRA MEMON UC TALUKA
BADIN DISTRICT BADIN
1. DEENAR TALPUR VILLAGE
1. Zubair Khaskheli 2. Mohammad Sharif Khaskheli 3. Khuda BBux Khaskheli 4. Abdul Satar Khaskheli 5. Ali Mohammad Lakho 6. Mohammad Iqbal Mandhro 7. Allah Bux Talpur 8. Ali Ahmad Lohar
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2. UMAR KHASKHELI VILLAGE
1. Ramzan Khaskheli 2. Ghulam Mohammad Khaskheli 3. Mohammad Umar Khaskheli 4. Zahoor Ahmad Khaskheli 5. Mohammad Haroon Khaskheli 6. Gul Hassan Khaskheli 7. M-Warayo Khaskheli 8. Mohammad Rahim Khaskheli
3. ALLAH RAKIO JAT VILLAGE
1. Ghulam Mustafa Khaskheli 2. Zafar Usman 3. Mohamad Farook 4. Mustaq Hussain 5. Arif Javed 6. Zaheer Ahmad 7. Mirza Saleem 8. Arshad Zaheer
4. PUNHOO PALI VILLAGE
1. Haji Abdul Wahid Pali 2. Imran Khan Pali 3. Abdul Satar Mandhro 4. Ali Mohammad Pali 5. Amir Bux Pali 6. Mohammad Soomar Mallah 7. Abdul Jabar Pali 8. Mohammad Musa Pali
5. ALLAH RAKIO JAT VILLAGE
1. Khalid Usman Mallah 2. Sohail Mohammad Mallah 3. Mohammad Sajjad Mallah 4. Aslam Riaz Mallah 5. Mansoor Qadir Mallah 6. Abdullah Ahmad Mallah 7. Sharif Sohail 8. Anwar Nasim
281
6. KHAMOON MALLAH VILLAGE
1. Khamoon Mallah 2. Noori Mallah 3. Mithoo Mallah 4. Abdul Hakeem Mallah 5. Allah Dino Mallah 6. Abdul Karim Mallah 7. Ramzan Mallah 8. Hassan Mohd Mallah
7. RAMZAN JAT VILLAGE
1. Yar Mohammad Jat 2. Nabi Bux Jat 3. Dhani Bux Jat 4. Mohammad Hassan Khaskheli 5. Allah Warayo Mallah 6. Mohammad Hassan Jat 7. Abdul Hafiz Jat 8. Nawaz Ali Jat
8. BAKHSHO DERO VILLAGE
1. Abdul Aziz Bhatti 2. Abdullah Joyo 3. Mohammad Uris Chang 4. Lakha Dino Khumbar 5. Khamoo Khumbar 6. Abdullah Bhatti 7. Khadim Hussain Khaskheli 8. Lal Mohammad Joyo
9. JUMA MALLAH VILLAGE
1. Majeed Mallah 2. Ramzan Umar Mallah 3. Tahir Mallah 4. Mohammad Ismail Mallah 5. Mohammad Sharif Mallah 6. Ramzan Ali Mallah 7. Abdullah Hussain Mallah 8. Ibrahim Master Mallah
282
10. DARYA KHAN KHASHKELI VILLAGE
1. Ayoob Khaskheli 2. Allah Bachayo Khaskheli 3. Amir Ali Khaskheli 4. Zameer Ali Khaskheli 5. Ghulam Shabir Khaskheli 6. Allah Jurio Khaskheli 7. Bashir Ahmad Khaskheli 8. Aijaz Ali Khaskheli
C6 LIST OF VILLAGE DEVELOPMENT ORGANIZATIONS (VDOs) IN
DISTRICT BADIN INTERVIEWED
1. VILLAGE DEVELOPMENT ORGANIZATION ARAB SHEEDI
1. Num Sheedi 2. Ramzan Sheedi 3. Achar Sheedi 4. Kandero Sheedi 5. Allah Bachayo Sheedi 6. Taju Sheedi
2. VILLAGE DEVELOPMENT ORGANIZATION (MALE AND FEMALE)
BUGHRO MALL
1. Tajo Bughro Mall 2. Marai Bughro Mall 3. Megha Bughro Mall 4. Pooran Bughro Mall 5. Walan Bughro Mall 6. Pirma Bughro Mall
3. BRDS VILLAGE DEVELOPMENT ORGANIZATION ISHAQ
KHASKHELI
1. Dr Abdul Aziz 2. Abdul Razak 3. Mehram Khaskheli 4. Mohammad Khaskheli 5. Ahmad Ali 6. Ramzan Khaskheli
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4. VILLAGE DEVELOPMENT ORGANIZATION MIRCHO MALL
1. Kachro Mall 2. Gulb Rai 3. Walam Gee 4. Prem Chand 5. Khajo Mal 6. Ghuman Das
5. DARYA KHAN KHASKHELI WELFARE ORGANIZATION
1. Allah Bachayo Khaskheli 2. Pervaiz Ali 3. Aijaz Ali Khaskheli 4. Wali Mohammad Khaskheli 5. Bashir Ahmad 6. Mohammad Sohail Khaskheli
6. JUMAN MALLAH WELFARE ORGANIZATION
1. Mohammad Ibrahim 2. Mohammad Sharif 3. Abdul Hafeez 4. Mohammad Uris 5. Mohammad Saleh Mallah 6. Mohammad Ramzan Mallah
7. BAHAR COMMUNITY ORGANIZATION BUXKHO DERO
1. Mohammad Usman Khumber 2. Manthar Mandhro 3. Khalid Hussain 4. Abdullah Joyo 5. Abdullah Bhatti 6. Khadim Hussain
8. VILLAGE DEVELOPMENT ORGANIZATION DEENAR KHAN TALPUR
1. Muzafar Talpur 2. Abdul Aleem Talpur 3. Mohammad Khan Talpur 4. Mohammad Iqbal Talpur 5. Abdul Raheem Talpur 6. Rajab Ali Talpur
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9. VILLAGE DEVELOPMENT ORGANIZATION UMAR KHASKHELI
1. Muneer Ahmad 2. Meen Wasayo 3. Mohammad Haroon 4. Mohammad Rahim Khaskheli 5. Zahoor Ahmad 6. Mohammad Umar Khaskheli
10. VILLAGE DEVELOPMENT ORGANIZATION PUNHOO PALI
1. Ali Mohammad Pali 2. Mohammad Bux 3. Iqbal Pali 4. Rasheed Ahmad 5. Abdul Jabbar Pali 6. Atta Mohammad
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APPENDIX-D
HOUSEHOLD SURVEY QUESTIONNAIRE
EMPIRICAL ANALYSIS OF THE DETERMINANTS OF RURAL POVERTY IN SINDH PROVINCE OF PAKISTAN
Questionnaire No____________ Semi-structured questionnaire for household survey I Address Name of village________________________________UC______________________ Deh_________________Taluka___________________District______________
I Respondent
1 Name_____________________________ 2. Caste__________________________ 3.Age_______________________________ 4. Gender: Male / Female 5. Qualification______________________6. Profession___________________
7. Relation with household head________________________________________
8. Family language________________________________________________ 9. Total family members_____________________________________________ 10. Skills_________________________________________________________
III Household Head 1. Name________________________________________ 2. Age__________ 3. Gender : Male / Female 4. Qualifications___________________________
1 = self 2 = husband 3 = son / daughter 4 = son / daughter in low 5 = son / daughter 6 = father / mother 7 = brother / sister 8 = other relatives 9 = other non-relatives
1 = electrician 2 = plumber 3 = mechanical / technical 4 = mason 5 = mat making 6 = carpenter 7 = black smith 8 = barber 9 = other specify
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IV Family profile
Family members living in same household
Gender Age groups Total <16 years 17-25 years 26-65 years >65 years
Male
Female
Total
V Education
Children attending schools
Gender
Male
Female
Primary
Middle / high
College
University
VI Sources of income
1. Family income S.No Gender Major profession Part time profession
Profession Income / month
Profession Income / month
1 Male / Female
2 Male / Female
3 Male / Female
4 Male / Female
5 Male / Female
6 Male / Female
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2. Tenancy status in agriculture
(a) Land lord (b) Tenant (c) Peasant proprietor (d) Lease 3. Total area___________________________________________________(acres) 4. Economics of crops
Season Crop Area sown (acres)
Production Rate per (mds)
Total revenue (Rs) in share
Total cost (Rs) in share
Rabi crops
A
B
C
Kharif crops
A
B
C
5. Livestock available Buffaloes Male
Total Female Milking
Cows Male
Total female Milking
Goats:
Sheep:
Total cost on annual feed (Rs) / month
6. Milk production and domestic consumption
Milk production
(litres)
Local consumption
(liters)
Milk sold literes
Price / litre
Buffaloes
Cows
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7. Wages by profession Profession / skills
No. of family members engaged
Wages /day Work days / month
Distance from work place
Satisfied with wages
Agricultural labour
Artisan Black smith Carpenter Electrician Embroidery Fishing Hat making Mat making Mechanic Poultry Rilly making Shops Stone minning
Wood cutter Other specificy
VII Assets household productive assets Assets Number Assets Number Cycle Sewing machine Radio TV Computer VIII Income from other sources Source 1 = agriculture 2 = fishing 3 = livestock 4 wood cutting 5 = seed and by products of trees 6 = sale of birds 7 mat making
Income in cash
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IX Expenditure Head of expenditure Amount
(Rs.) Head of expenditure Amount
(Rs) Kitchen expenditure e.g. vegetables, meat, fish species
Pocket money Children
Cereals
House wife Wheat Old age Rice Maintenance Motor
cycle
Others Car Grain mills (grinding cereals)
Tractor
Clothing Utility bills Electricity Shoes Gas Education Phone Transport Maintenance of house Usable items (towel, soap, etc)
Servant(s)
Health Doctor’s fees
Recreation & religions activities
Medicine Others Others Total X Loans Have you receive loans? Yes give details
Name of institution
Amount Interest Purpose of loan
Year Wheather installments are regularly
paid
If no reasons
1. Do you think the amount borrowed increased household income? Yes / No. 2. If no tick the most appropriate reason
Low amount High interest rate Small duration Not properly
utilized
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XI Facilities in village 1. Education Schools Gender Yes / No If no nearest school KM
Primary Boys Girls
Middle Boys Girls
High Boys Girls
2. Health and water facilities Hospital Yes / No If no nearest one KM
Dispensary / rural health centre Animal hospital Water supply XII Source of energy Electricity 1 = yes and 2 = no
Gas 1 = yes 2 = no
XIII House type, rooms and toilet facility House type Please tick (√) home type
Pacca Semi pacca Katcha Jhopra
No. of rooms Toilet facility (please tick) (1) Non flush toilet / wc (2) pit latrine (3) open space XIV Water facility in house Source
Pump Well Water supply Others specify
Quality 1. Braclish 2. Drinkable 3. Sweet
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APPENDIX-E
VILLAGE DEVELOPMENT ORGANIZATIONS QUESTIONNAIRE
EMPIRICAL ANALYSIS OF THE DETERMINANTS OF RURAL POVERTY IN SINDH PROVINCE OF PAKISTAN
(A) I name and address of organization Name ___________________________________________________________ Address _________________________________________________________ Registered under act________________________________________________ Staffing Paid staff Volunteer
Full time x Part time 1.Professional / Technical [ ] [ ] [ ] 2. Office (Clerks, Typists etc) [ ] [ ] [ ] 3. Non Office (Chowkidar etc) [ ] [ ] [ ] (B) Type of organization (NGOS) Association 1. Non Government Organization [ ] 2. Coordinating NGO [ ] 3. Community Group [ ] 4. Social Welfare Group [ ] 5. Service Organization [ ] 6. Any Other [ ] 2. Does your organization establish or help to establish any association working on
poverty alleviation? Yes / No. __________________________________________________________________
____________________________________________________________________________________________________________________________________
3 Geographical area activities (please identify) 1. Local Community [ ] 2. Taluka [ ] 3. District [ ] 4. Division [ ] 5. Province [ ] 6. Country / National [ ]
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4. Target population i. Types_________________ ii. Numbers_________________ 5. In what area does your organization provide raining to the community. i. Staff Development [ ] ii. Community Health [ ] iii. Road Construction [ ] iv. Income Generation [ ] v. Marketing [ ] vi. Poverty Alleviation [ ] 6 Are you familiar with the concept of poverty alleviation? Yes / No 7 Is your organization working on poverty alleviation? Yes / No 8 Does your organization believe tat the practices / strategies adopted by your
organization will reduce poverty in the area (a) Not at all ________________________________________________ (b) To some extent____________________________________________ (c) Very much________________________________________________ 9 What methodology NGOs use to provide / adopt poverty alleviation programmes
in their communities. __________________________________________________________________
______________________________________________________________________________________________________________________________________________________________________________________________________
10 What is the progress of empowerment and participation so far by your organization in the community?
________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
11 Do you have micro-credit facilities? How much was disbursed to communities for poverty alleviation.
_________________________________________________________________________________________________________________________________________________________________________________
12 What is the conditions for successful use of micro-credit. __________________________________________________________________
______________________________________________________________________________________________________________________________________________________________________________________________________
13 What is the status of health and nutrition in the areas of your operation. __________________________________________________________________
______________________________________________________________________________________________________________________________________________________________________________________________________
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14 Do you think that the income of the people has increased and their living standard has improved after the loan.
________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
15 What is the leadership style of your organization. __________________________________________________________________
______________________________________________________________________________________________________________________________________________________________________________________________________
16 What is your NGO doing in saving children engaged in hazardous occupations? __________________________________________________________________
______________________________________________________________________________________________________________________________________________________________________________________________________
17 What is your organization doing to increase access to good quality drinking water for the community?
________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
18 What is your NGO doing in areas of environmental degradation? __________________________________________________________________
______________________________________________________________________________________________________________________________________________________________________________________________________
19 Does your organization establish or help to establish any employment generating business Yes / No.
________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
20 Purpose aims, goals objectives (please described briefly) __________________________________________________________________
______________________________________________________________________________________________________________________________________________________________________________________________________
21. Did your organization assisted in the construction of building for the community. How?
1. Financially [ ] 2. Technical Advice [ ] 3. Construction Management [ ]
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22 Describe the most important services and facilities available to this organization and the main problems experienced in achieving your goals.
________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
23 What are your suggestions in developing and promoting poverty alleviation programmes?
________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
24 What is your opinion about the government poverty alleviation strategy? __________________________________________________________________
______________________________________________________________________________________________________________________________________________________________________________________________________
25 In your opinion what kind of services NGOs personnel should provide in order to achieve the goals of poverty alleviation
________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
26 Personel interviewed Name__________________________________________Age_____________ Address___________________________________________________________ Telephone No._______________________________________________ Day_________________Month____________Year__________________