1. 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
June 2017

2. 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

3. 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

4. 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

5. 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

6. 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,
For details, see PovcalNet.
June 2017
JH: Course on Poverty Measurement

7. 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

8. 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

9. JH: Course on Poverty Measurement
How: Panel Data
For panel data, we survey the household (or individual) more than once.
E.g 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 in six villages in southwestern India.
More details in Module 5
June 2017
JH: Course on Poverty Measurement

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

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

12. Transition Matrix: quintiles
Often uses quintiles, as on the next slide for Vietnam,
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

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

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

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

16. 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

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

18. 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; 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

19. 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