Applying expert knowledge to measure multidimensional rural poverty in Chittagong (Bangladesh)

1. 14TH EADI General Conference 23-26 June 2014 Responsible Development in a Polycentric World Applying expert knowledge to measure multidimensional ruralpoverty in Chittagong (Bangladesh) Melania Salazar- Ordóñez; Lorenzo Estepa- Mohedano; Rosa Cordón-Pedregosa

2. Content • Introduction and objective • Case study • Methodology • Results • Conclusions

3. 1. Introduction and objective • Growing debate about measuring poverty • Traditional measures vs. Multidimensional measures • Technical & methodological problems: data, theoretical support, accurate indicators, critical thresholds, weight of indicators, etc. • Given homogeneous weights vs. Local expert opinion • Specific country and policy context • Objective: Contribute to the debate on how the indicators should be weighted to form a composite index • Estimating MPI – data of households from South Kosbash (Bangladesh) – using both homogeneous weights for dimensions and indicators, and weights according to experts’ opinion –data of 29 experts in rural development in Bangladesh. • Estimating statistical differences between MPI with homoge-neousweights and with weights according to experts’ opinion

4. 2. Case study • Bangladesh is placed in the Gulf of Bengal, border with India and Myanmar • -147,570 sq Km and 167 million people - • 7 Divisions / 64 Districts / 490 Thanas / 15-20 Villages by Thana • Union Parisads is the local government in rural areas • Agriculture: • 1/3 of the GDP, • over 60% of employment, • Chittagong is one of the 7 Divisions in Bangladesh (28 million of people) • The 3rd contributor to national GDP • 31% of rural population is living below poverty line • South Khosbashis a Union conforming by 14 villages in Comilla Districts

5. 2. Case study Data of households from South Khosbash(Bangladesh) Questionnaire to get data for estimation MPI From Participatory Rural Appraisal process (mixing participatory appraisal methods and focus group discussions) • 1st Questionnaire • Two local Workshops • To introduce / eliminate variables • Understanding bias 2nd Questionnaire Reviewed by BARD members 26 questions: 1) Household member’s data; 2) Household member’s health; 3) House conditions; 4) Agriculture and livestock; 5) Household support (economic and services) and crisis; 6) Household incomes and expenses; and 7) Household member’s networking 21 survey takers 4,999 face-to-face surveys 4,641 (7,2%) August 2011

6. 2. Case study Place: South Khosbash Union • Respondent’s profile: 99.9% household head / 92.2% men / 92.3% married / 31.3% working in agriculture, 13.3% remittances receiver / 35.1% illiterate and 13.7% primary school • Household’s profile on average : 5.16 members / 2.72 men

7. 3. Methodology Multidimensional PovertyIndex – MPI • Deprivation scores are calculated by adding weights of failed indicators; if result > 33%, then household is classified as poor. • Head count ratio (H): number of multidimensio-nally poor people divided by the total population • Intensity of poverty (A): average indicators in which the multidimensionally poor people are deprived. • MPI = H * A

8. 3. Methodology Estimating MPI using homogeneous weights Multidimensional PovertyIndex – MPI Source: Alkire et al. (2013)

9. 3. Methodology Estimating MPI using weights for dimensions and indicators according to experts’ opinion • Different methods to assign weights • Statistical models – e. g. Factor analysis • Participatory methods – e.g. Analytic Hierarchy Process (AHP) Second ones incorporate Stakeholders´ opinions and concretely AHP allows judging the importance of concrete elements giving them priorities (AHP was chosen for this research) AHP is a technique that approaches complex decision problems by means of hierarchical structures and ratio-scale measures In this study, AHP is used as a weighting method to determine the weights of each MPI indicators, through expert knowledge

10. 3. Methodology • Analytic Hierarchy Process (AHP)

11. 3. Methodology • AnalyticHierarchyProcess (AHP) • Data of 29 experts in rural development in Bangladesh: four Directors, five Joint Directors and twenty Senior Scientific Officers of Development Research Centres in Bangladesh • Pair wise comparisons between each dimension yielded the global weights (wgi) • Pair wise comparisons between each indicator, inside the dimensions, produced the local weights (wlj) • Pair wise comparisons were measured with Saaty’s increasing scale from 1 to 9 • Estimation of the weights: row geometric mean • Normalized weights (wnj)= wgi *wlj • Statistical significant differences between MPI with homoge-nous weights and according to experts’ opinions weights: t Student´s test

12. 4. Results Table 2. Weight assigned by experts Source: Authors’ elaboration

13. 4. Results Coherence of results with actual situation of the households at local level: • 88% of HH have at least one member with less of 5 years of schooling • 30% households in food deficit • Only 24% have access to clean water However: • 59% of HH can access electricity • 62% of HH have access to adequate sanitation • Only 12,7% of HH have some children not attending school

14. 4. Results The deprivation scores for each household estimating with the weights given in a homogeneous way or by the experts showed statistically significant differences (t-Student = 97.56, p= 0.000).

15. 5. Conclusions • Well informed local experts paint a picture of multidimensional poverty in South Khosbash substantially different from that stated by the MPI methodology • Local experts take into account the critical issues not yet solved and give them a higher weight • Emphasis is focussed on those critical elements that need special attention at local level • An assignment of weights to the dimensions and indicators of poverty in specific contexts can put a special emphasis on specific policies to fight poverty locally. • The better use of resources will improve efficiency of these policies • The experts weights allow to account for context specificity, but it does not allow comparison with other countries

16. 14TH EADI General Conference 23-26 June 2014 Responsible Development in a Polycentric World Applying expert knowledge to measure multidimensional ruralpoverty in Chittagong (Bangladesh) THANK YOU Melania Salazar- Ordóñez; Lorenzo Estepa- Mohedano; Rosa Cordón-Pedregosa