1. Module 4 Panel Data Jonathan Haughton June 2017 Measuring poverty
Multidimensional poverty
Poverty Dynamics
Panel Data
Inference with Panel Data
International Poverty Comparisons
Vulnerability
Tackling Poverty
Module 4 Panel Data
Jonathan Haughton
June 2017

2. JH: Course on Poverty Measurement
Objectives
Examine the advantages of panel surveys
Explain how panel data can measure changes in poverty more precisely
Summarize the drawbacks of panel surveys, including attrition bias, decreased representativeness, and high managerial demands
June 2017
JH: Course on Poverty Measurement

3. JH: Course on Poverty Measurement
Types of panel data
Households
e.g and 1998 Vietnam Living Standards Surveys
Dwellings
e.g. Peru Living Standards Survey: in 1990 returned to 1,280 dwellings in Lima area
Individuals
e.g. U.S. Panel Survey on Income Dynamics (PSID), individuals surveyed regularly since 1968
June 2017
JH: Course on Poverty Measurement

4. JH: Course on Poverty Measurement
Hybrids
Constructed from repeated cross-sections
e.g. Khandker et al. on districts in Thailand
Rotating panels
e.g. Cote d’Ivoire.
1985: 1600 hh : 800 of these others.
June 2017
JH: Course on Poverty Measurement

5. Advantages of Panel Surveys
Only way to measure transitions over time
Less need for retrospective reporting
Greater precision (see next slide)
So smaller sample OK
Can control for unobserved characteristics (see Module 5)
Useful in impact evaluation
June 2017
JH: Course on Poverty Measurement

6. JH / Panel Data / NISR, Kigali
Precision
If independent samples:
t-statistic = 0.181, not significant
t = if n=500
If paired
t-statistic = 5.393, change statistically v. significant
Implication: Smaller samples OK
May 26, 2017
JH / Panel Data / NISR, Kigali

7. Types of poverty (Rwanda example)
Chronically poor need support
Transiently non-chronically poor need insurance
May 26, 2017
JH / Panel Data / NISR, Kigali

8. JH: Course on Poverty Measurement
June 2017
JH: Course on Poverty Measurement

9. JH: Course on Poverty Measurement
Targeting is hard
June 2017
JH: Course on Poverty Measurement

10. Drawbacks of Panel Data
Attrition bias
e.g. Michigan PSID: 12-15% dropped out after 1st round, and 2.4% p.a. dropped out after that.
Loss of representativeness
e.g. Over time, panel would age, leaving out newly-formed couples
Defining the household: which to follow?
e.g. year 0: husband + wife1 + child1
year 2: husband + wife2 + child2 // wife1 + child1
Cost
Track households, needs good management
June 2017
JH: Course on Poverty Measurement

11. JH: Course on Poverty Measurement
Reading
Haughton & Khandker, chapter 11
Jalan and Ravallion (1998) on targeting
Jalan, Jyotsna, and Martin Ravallion “Transient Poverty in Postreform Rural China.” Journal of Comparative Economics 26: 338–357.
Khandker, Koolwal, Haughton & Jitsuchon (2012) on constructing a hybrid panel
Khandker, Shahidur, Gayatri Koolwal, Jonathan Haughton, and Somchai Jitsuchon Household Coping and Response to Government Stimulus in an Economic Crisis. Policy Research Working Paper, World Bank, Washington DC.
June 2017
JH: Course on Poverty Measurement