1. Meeting of the Poverty and Social Protection Network Inter-American Development Bank Washington DC, 29-30 October, 2009

2. OPHI Oxford Poverty & Human Development Initiative Department of International Development Queen Elizabeth House, University of Oxford www.ophi.org.uk Maria Emma Santos The Multidimensional Approach: Poverty Measurement & Beyond Oxford Poverty & Human Development Initiative, University of Oxford, UK and Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET)-Universidad Nacional del Sur, Argentina

3. Applications of OPHI Method to MD Poverty Measurement Latin America Battiston, Cruces, Lopez-Calva, Lugo, Santos (2009) – OPHI WP 17 India Alkire & Seth (2008) – OPHI WP 15 Bhutan Santos & Ura (2008) – OPHI WP 14 Sub-Sahara Africa Batana (2008) – OPHI WP 13 Bangladesh Poverty among children Roche (2009) – OPHI RP 11 – OPHI Workshop on MD Measurement in Six Contexts Afghanistan Poverty among children Biggeri, Trani & Mauro (2009) – OPHI Workshop on MD Measurement in Six Contexts Pakistan Awan (2009) – in progress China Yu (2009) – in progress

4. Selected Results from Latin America Battiston, Cruces, Lopez-Calva, Lugo & Santos (2009)

5. Dataset Socioeconomic Database for Latin America and the Caribbean (SEDLAC): CEDLAS - World Bank. Comprises household surveys of the different LA countries. They have been homogenized to make variables comparables. Countries: Argentina, Brazil, Chile, Uruguay, El Salvador and Mexico. Argentina & Uruguay: only urban areas. 5 observations between 1992 and 2006 (most of them: 1992, 1995, 2001, 2003 and 2006). Unit of Analysis: Household. All members of a household identified as poor are considered poor.

6. Selected Dimensions & Cutoffs IndicatorDeprivation Cutoff ‘Equal’ Weights Voices of the Poor Weights Income Having a per capita family income of US$2 a day 12.4 Child in School (UBN) Having all children between 7 and 15 years attending 11.8 Education of HH (UBN) Household Head with at least five years of education 10.6 Running Water (proxies health-VP) Having tap water in the dwelling 10.6 Sanitation (UBN) Having flush toilet or pit latrine in the dwelling 10.3 Shelter (UBN) House with non-precarious wall materials 103

7. Result 1: Decreasing trend in MD Poverty in the last 14 years

8. M0 with k=2 and equal weights. Same decreasing trend with other measures.

9. Reduction in both the % of the multidimensionally poor and the average number of deprivations the poor experience. El Salvador: proportionally larger reduction in the average number of deprivations: from 4.1 to 3.4 (a reduction of 21%). H was reduced from 75% to 64%, ie. 15%) Chile: proportionally larger reduction in the headcount: from 28% to 7% (ie. 73%). Average deprivation decreased from 2.7 to 2.4 (ie. 13%).

10. Result 2: People in rural areas are more likely to be poor and to suffer coupled disadvantages

11. Year 2006

12. Result 3: Deprivation in sanitation and education of the household head are the main contributors in all countries. Deprivation in children attending school is the lowest contributor.

13. M0 with k=2 – Year 2006

14. Selected Results from other studies India: Alkire & Seth (2008) Sub-Sahara Africa: Batana (2008)

15. India: MD Poverty Ranking vs. Income Poverty Ranking Deteriorated from Rank 1 to Rank 18 Improved from Rank 7 to Rank 1

16. Sub-Sahara Africa Robustness test across k Burkina is always poorer than Guinea, regardless of whether we count as poor persons who are deprived in only one kind of assets (0.25) or every dimension (assets, health, education, and empowerment, in this study). (DHS Data used)

17. Further possibilities of application of OPHI Method I: Targeting of Social Programs

18. Poverty Measurement IDENTIFICATIONAGGREGATION + AF Method: Dual cutoff Within dimension cutoff: z j Across dimensions cutoff: k (from union to intersection) AF Method: FGT family Can be used to identify beneficiaries of targeted programs (Azevedo & Robles, 2009)

19. Example of targeting errors of using the income identification method (rather than the MD poverty identification) Bhutan: five dimensions, income included, equal weights Santos & Ura (2008) % of Populationk=1k=2k=3k=4k=5 Income Non-Poor but Multidimensionally Poor (Exclusion Errors using the Income Approach) 40.7%15.8%4.6%0.5%0% Income Poor but Multidimensionally Non-Poor (Inclusion Errors using the Income Approach) 0%2.1%8.1%15.9%21.8%

20. Further possibilities of application of OPHI Method II Beyond Poverty: Applications to measurement in other contexts that are also inherently multidimensional

21. Governance Singh (2009) – OPHI Workshop of Multidimensional Measurement in Six Contexts ) proposed to use the AF methodology as an alternative to the Mo Ibrahim Index of African Governance. Unit of analysis: countries Set cutoffs for the different indicators of governance (not easy!) Identify countries ‘failing’ in one or more indicators. Rank them by their average deprivation. Advantage over Mo Ibrahim Index: adequate treatment of ordinal data.

22. Quality of Education Foster & Santos together with Szekely & De Hoyos (2009) – In progress – OPHI Workshop of Multidimensional Measurement in Six Contexts Unit of analysis: schools Set cutoffs for the different indicators of education quality (again-not easy!) – inputs & outputs. One possibility: to focus on ‘quality deprived’ schools. Rank them by their average deprivation (or its complement: the average achievement) Get an overall measure of deprivation in education quality

23. Example: Argentina – Calculations performed using Operativo Nacional de Evaluacion 2000

24. Quality of Education Foster & Santos with Szekely & De Hoyos (2009) – In progress – OPHI Workshop of Multidimensional Measurement in Six Contexts Another option: An extension of the methodology allows evaluating both poor performers & good performers. Use of the dual cutoff to identify ‘quality deprived’ schools and ‘good quality’ schools and assess how poorly the poor performers are doing and how well the good performers are doing. Rank them by their average deprivation or achievement. Negative values correspond to ‘quality deprived schools’, while positive values correspond to ‘good quality’ schools.

25. Example: Argentina Two schools in the ranking Operativo Nacional de Evaluacion 2000 School in Air(q0(k=1))r(q0(k=9))Aver. Test Score Deprived in… Cordoba6 (1143) -0.33 (1226) 0.67 (1422) 39.5% (2593) Computers Infrastructure Test performance. Bs As7 (276) -0.22 (691) 0.78 (994) 72.3% (465) Professional training for teachers 1-drop out rate. The number in parenthesis is the position in the ranking.

26. Social Responsibility Trafton (2009) - OPHI Workshop of Multidimensional Measurement in Six Contexts Proposes the use of the AF methodology to assess outcomes in aspects related to social responsibility. Example: Fair Trade firm wishing to compare coops on the dimensions of –working conditions –measures taken towards the implementation of organic production –the ability of the coop to pre-finance farmers –the degree of development of community resources with the Fair Trade premium provided to the coop.

27. Corruption Foster, Horowitz & Mendez (2009) – OPHI WP 29- OPHI Workshop of Multidimensional Measurement in Six Contexts Propose the use of poverty measurement technology to measure corruption. Imagine one has reports of transactions’ amounts between government departments & clients. One can identify corrupt transactions between the different departments and clients (as well as over time) and calculate: –The frequency of corrupt transactions – analogous to simple head count ratio. –Excess value of corrupt transactions – analogous to poverty gap. –The excess value of corrupt transactions relative to the client’s resources.

28. Concluding Remarks Poverty is inherently multidimensional and its measurement has fostered the design of sounded identification & aggregations methodologies, based on axiomatic approaches that make them transparent. One of them is the AF method. This can be used not only for poverty measurement, but also - in its identification part - for identifying potential beneficiaries of social programs. Moreover, because multidimensional measurement is required in many other contexts, the methodology can prove useful beyond poverty measurement.

29. Thanks for listening! Questions? Comments?