Module 3 Poverty Dynamics

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Presentation transcript:

Module 3 Poverty Dynamics Measuring poverty Multidimensional poverty Poverty Dynamics Panel Data Inference with Panel Data International Poverty Comparisons Vulnerability Tackling Poverty Module 3 Poverty Dynamics Jonathan Haughton jhaughton@Suffolk.edu June 2017

JH: Course on Poverty Measurement Objectives Explain why we need to measure poverty over time (“poverty dynamics”) Enumerate the main sources of data on poverty dynamics Construct a transition matrix using panel data Identify the chronically, persistently, and transient poor June 2017 JH: Course on Poverty Measurement

What, why “poverty dynamics” Simply: the measurement of poverty over time Useful to: Monitor, evaluate, the effects of policies, shocks, projects Distinguish between households that are persistently poor (so need more income) and occasionally poor (may need insurance, transfers) June 2017 JH: Course on Poverty Measurement

JH: Course on Poverty Measurement How? Ask about the past Rarely done, because of concerns about accuracy e.g. Survey after a crisis, ask questions about situation before and during crisis June 2017 JH: Course on Poverty Measurement

JH: Course on Poverty Measurement Case: Krishna et al. 316 households in 20 villages in W. Kenya; also a similar approach in Rajasthan. Asked villagers to identify who among them was poor 25 years earlier. Verified with individuals. Transition matrix: June 2017 JH: Course on Poverty Measurement

How? Repeated Cross-Sections Commonest situation: Cross-section data at two or more points in time Example: Dollar and Kraay (2002) 418 “episodes” from 137 countries over 4 decades allowing comparison of poverty over 5-year spans Conclusion: “Growth is good for the poor” (in the long run) Example: Chen and Ravallion (2008) Use information from 675 surveys for 116 countries to estimate evolution of poverty in LDCs, 1981-2005 For details, see PovcalNet. June 2017 JH: Course on Poverty Measurement

JH: Course on Poverty Measurement Example: Cambodia Two similar surveys; poverty lines adjusted for inflation; Poverty fell modestly. June 2017 JH: Course on Poverty Measurement

JH: Course on Poverty Measurement Example: Peru Calculate poverty rates by group of household Report relative risks e.g. P0 = 10% nationally, 15% for laborers, so relative risk of being poor is +50% for laborers. June 2017 JH: Course on Poverty Measurement

JH: Course on Poverty Measurement How: Panel Data For panel data, we survey the household (or individual) more than once. E.g. 1993 Vietnam Living Standards Survey interviewed 4,800 households. Of these, 4,305 were interviewed again in 2008. E.g. Institute for Crop Research in the Semi-Arid Tropics (ICRISAT) surveyed 240 households annually from 1975-1985 in six villages in southwestern India. More details in Module 5 June 2017 JH: Course on Poverty Measurement

Transition matrix: poverty, Rwanda May 26, 2017 JH / Panel Data / NISR, Kigali

JH / Panel Data / NISR, Kigali May 26, 2017 JH / Panel Data / NISR, Kigali

Transition Matrix: quintiles Often uses quintiles, as on the next slide for Vietnam, 1993-1998. Note the considerable mobility; 59% changed quintile between 1993 and 1998. “Shooting stars” rose at least 2 quintiles. Interesting to ask why. [Haughton et al. 2001] Signal or noise? Pritchett et al. think half of observed mobility may reflect measurement error June 2017 JH: Course on Poverty Measurement

JH / Panel Data / NISR, Kigali May 26, 2017 JH / Panel Data / NISR, Kigali

JH / Panel Data / NISR, Kigali May 26, 2017 JH / Panel Data / NISR, Kigali

Issue: Inconsistency in method over time June 2017 JH: Course on Poverty Measurement

JH: Course on Poverty Measurement Issue: deflation When comparing two surveys, adjust for inflation. The Achilles heel of inter-temporal poverty comparisons India: official price indexes over-inflated poverty line 4 percentage points too much, 1993/94 to 1999/2000 So reduction in poverty was understated Also, urban cost of living overstated +15%, not +36%, relative to rural It matters! June 2017 JH: Course on Poverty Measurement

JH: Course on Poverty Measurement Price adjustments June 2017 JH: Course on Poverty Measurement

Issue: Questionnaire comparability Southwest China Poverty Monitoring Survey Mean income per capita: 855 to 993 yuan, 1995 to 1996; +16%! 1995 survey: one-time recall; 1996 survey: diary India: National Sample Surveys 1993/4: P0 = 36%; down to 26% by 1999/2000. But latter questionnaire had fewer consumption items; shorter recall period for food; longer recall period for some durables. Deaton (2001): if survey instrument unchanged, 28% poverty rate in 1999/2000 June 2017 JH: Course on Poverty Measurement

JH: Course on Poverty Measurement Further reading On price indexes, Haughton & Khandker, Chapter 16 Base-weighted Laspeyres index is commonly used, but overstates inflation. Tornqvst index better. Deaton (2001) has a good discussion. On designing questionnaires Grosh and Glewwe (2000), Designing Household Survey Questionnaires for Developing Countries June 2017 JH: Course on Poverty Measurement