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Multidimensional poverty measurement with individual preferences

This document discusses a multidimensional approach to measuring poverty, emphasizing the importance of considering individual preferences. It highlights that poverty is not merely financial but encompasses various dimensions of life, including health and living conditions. The authors derive a measurement procedure that respects individual opinions on well-being by allowing agents to aggregate dimensions themselves. Using real-world data from Russia, they estimate preferences based on life satisfaction and introduce a systematic method for poverty analysis. Overall, this approach is presented as ethically sound and practically implementable.

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Multidimensional poverty measurement with individual preferences

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  1. Multidimensional poverty measurementwith individual preferences Koen Decancq – Marc Fleurbaey – François Maniquet UNDP – March 2014

  2. 1. Motivation • Poverty is multidimensional • Who is poor?

  3. 1. Motivation • Poverty is multidimensional • Who is poor?

  4. 1. Motivation • Poverty is multidimensional • Who is poor?

  5. 1. Motivation • Poverty is multidimensional • Who is poor?

  6. 1. Motivation • Poverty is multidimensional • Who is poor?

  7. 1. Motivation • Poverty is multidimensional • Who is poor?

  8. 1. Motivation • Poverty is multidimensional • Who is poor?

  9. 1. Motivation • Poverty is multidimensional • Who is poor?

  10. 1. Motivation • Poverty is multidimensional • Who is poor?

  11. 1. Motivation • Poverty is multidimensional • Who is poor?

  12. 1. Motivation • Multidimensional poverty measurement without paternalism? • Let agents aggregate the dimensions themselves “... those with a stake in the outcomes will almost certainly be in a better position to determine what weights to apply than the analyst calibrating a measure of poverty.” (Ravallion, 2011) • Acknowledge the heterogeneity in the “opinions on the good life”

  13. 2. Multidimensional poverty measure We axiomatically derive the following procedure

  14. 2. Multidimensional poverty measure We axiomatically derive the following procedure

  15. 2. Multidimensional poverty measure We axiomatically derive the following procedure … and apply it to real-world data (from Russia)

  16. 3. Estimating preferences • We use RLMS-HSE (1995-2005) • We consider four dimensions of life • Equivalized expenditures • Objective (constructed) health index • Constructed house quality index • Unemploment (binary) • Deprivation thresholds: 60% of median value in each continuous dimension

  17. 3. Estimating preferences • Problem: we don’t observe “opinions on the good life” • We estimate them based on life satisfaction data • We run a simple life satisfaction regression, • with some econometric sophistications, • Heterogeneity in β coefficients • Decreasing marginal returns • Control for personality traits (in α) • And then plot indifference maps based on β’s

  18. 3. Estimating preferences

  19. 4. Results: headcounts

  20. 4. Results: overlap of bottom 16,1 % 1,6% 4,1% 3,6% 2,9% 3,5% 2,4%

  21. 5. Conclusion • Multidimensional poverty analysis with respect for preferences … • … is ethically attractive • … is theoretically possible • … is empirically implementable

  22. Life satisfaction regression

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