1. 11 The Multidimensional Poverty Index: Achievements, Conceptual, and Empirical Issues Caroline Dotter Stephan Klasen Universität Göttingen Milorad Kovacevic HDRO HDRO Workshop March 4, 2013

2. The MPI Measuring acute multidimensional poverty; Based on dual cut-off approach (1/3); Dimensions: Health (mortality and nutrition), Education (years and enrolement), Standard of living (house, water, sanitation, electricity, cook fuel, assets); MPI = Headcount * Intensity; Data used: DHS, MICS, WHS Calculated for some 110 countries (increasingly available for more than 1 period); 2

3. In praise of an MPI-type Indicator Direct multidimensional complement/competitor to $ a day indicator; –Similar breadth and coverage –Could possibly calculate and monitor global poverty; Also based on capability approach (as is the HDI); Actionable and policy-relevant at the national (and sub- national level); advantage largely unexploited by UNDP; Consistent with reasonable set of poverty measurement axioms (in contrast to HPI); Based on high quality and comparable data, with potential to measure poverty over time; 3

4. Conceptual Issues Dual cut-off navigates between union and intersection approach –But leads to formal and interpretational problems: deprivations entirely ignored below the cut-off seems problematic; –Union approach conceptually to be preferred? Neglect of inequality in the spread of dimensions across the population, which is also problematic; –Proposal by Rippin: In the poverty identification step, use square of weighted deprivation share as poverety indicator (and add those up in aggregation step); –Other proposals in the literature; Use of intensity in the MPI: –cannot compare with $ a day headcount –little variation in intensity (heavily driven by second cut-off); –use headcount as headline indicator with intensity-inequality sensitive measure as complementary indicator? 4

5. Empirical Issues WHS limiting and problematic (and now superfluous?); suggestion to just use MICS and DHS; Standard of living: –Unclear interpretation of electricity access (unequal use!), cooking fuel (depends on cooking situation), and sanitation (needs differ across rural/urban, regions); –Quite large influence on overall MPI; –3 indicators would suffice (and capture others as well): floor, assets, and drinking water; Enrolments: –One child not enrolled, household deprived; –Problem of late enrolments; –Adjust time window to allow for late enrolments (e.g. allow for 2 years late enrolment); 5

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7. Empirical Issues Mortality: –Only consider recent child deaths (MICS: only consider deaths of women who gave births in last 10 years?); Nutrition: –BMI of adults and childhood undernutrition cut-offs not directly comparable; –BMI and underweight subject to bias due to nutrition transition; –Focus on children beyond 6 months? –Proposal: Just focus on childhood undernutrition and stunting; Education: –Cut-off (one person with 5 years enough for non-deprivation) and implies perfect economies of scale (asymmetry); –Proposal: deprived if less than 50% of adults have 5 years+ 7

8. Empirical Issues Asymmetric cut-offs in health, enrolment, nutrition, education: –Has systematic influence on impact of household size on MPI; –Not clear that asymmetries are justified; –Define cut-offs with respect to hh size (e.g. 20% of children are undernourished); Ineligible population: –No children (in school-going age or with nutritional measurement); –Presumed non-deprived in MPI (serious problem and bias!); –Makes severe poverty near-impossible for hh without eligible population; –A serious problem of differential importance across countries; 8

9. 9 All solutions problematic: Non-deprivation assumption; Dropping observations; Using other indicator from same dimension; Proposal: Hybrid approach: Use indicator from same dimension if one indicator is missing, and adjust overall MPI cut-off if both are missing (can be easily implemented); Advantage: Keeps all observations in, uses information to maximum extent; likely to generate least bias; Disadvantage: Decompositoion no longer possible;

10. Implementing the Proposals A reduced and (more robust) MPI? –3 standard of living indicators; –Nutrition: stunting (>6mts) –Mortality: only recent deaths; –Enrolment: allow for late enrolment; –Cut-offs more uniform (>20% affected in nutrition, enrolment, mortality, <50% with 5 years+ education); –Hybrid approach for ineligible population; Implement approach using DHS for Armenia, Ethiopia, and India; Changes incidence (mainly due to education cut-off), but also correlates of poverty (e.g. hh size); 10

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12. Conclusion MPI has been a good start to develop internationally comparable multidimensional poverty indicator; But there are open issues and problems, and refinements at conceptual and empirical level warranted Conceptual level: Union approach, incorporating inequality, headcount the headline indicator? Empirical level: Changes to indicators, cut-offs, data sets used, and assumptions about ineligible population; Most issues can be readily addressed and are worth addressing. 12

13. 13 Original (current) MPI New proposalImplications Headline index MPIHeadcount of MP Better comparability with income poverty Complementary indicators of poverty Headcount, Intensity Intensity, Inequality Intensity of MP; but Which approach to inequality of deprivation ? Cut-off approach Dual Dual → MP Union approach → Measure of deprivation, inequality in deprivation Possible differentiation of deprivation and multidimensional poverty. More analytic power. Dimension cut- off Absolute Consider ‘relative’ cut-offs Hard to implement and also arbitrary? Dimension weights Equal (1/3) Within dimension weights Equal

14. 14 Original (current) MPI New proposalImplications Living standard Drinking water, sanitation, electricity, cooking fuel, floor, assets Drinking water, floor, assets Reduces the importance of living standard; Reduces the headcount Education Enrollment (ages 6-14) Any school- aged child is not attending school in grades 1 to 8 Shorter the enrollment window by 2 years (8 to 14); size adjustment (1 in 5) Reduces the headcount Years of schooling (age 15 and above) Years of schooling is a public good ( no one has 5 or more years of primary education) Some economies of scale but not full; Size adjustment (1 in 2 adults) Increases the headcount Health Nutrition BMI for adults Weight-for-age for children Exclude BMI for adults Height-for-age for children No health indicator for adults; reduces the headcount Mortality Death of children any age, no reference period Death of children below age 5 in the past 5 years; Reference period ?

15. 15 Original (current) MPI New proposalImplications No eligible population Enrollment, Health HH is non- deprived Hybrid approach: 1.Double the weight on adult education 2.BMI of adults 3.Lower cut-off: 2/9 Large number of hh (20%); messy calculation Severe poverty Deprived in more than 1/2 of weighted indicators At least 50% of eligible population in HH is deprived in enrollment and health; no assets; Cut-off 1/3 Reduced headcount