Povertyactionlab.org Planning Sample Size for Randomized Evaluations Esther Duflo J-PAL.
Impact of Ultra-Poor Graduation Pilots: Early Results from Randomized Evaluations
19
[email protected] www.e-mfp.eu Impact of Ultra-Poor Graduation Pilots: Early Results from Randomized Evaluations Bram Thuysbaert Yale University and IPA November 15, 2012 With A.Banerjee, E. Duflo, D. Karlan, J. Morduch, and others Preliminary and Incomplete
description
Impact of Ultra-Poor Graduation Pilots: Early Results from Randomized Evaluations. Bram Thuysbaert Yale University and IPA November 15, 2012. With A.Banerjee, E. Duflo, D. Karlan, J. Morduch, and others Preliminary and Incomplete. - PowerPoint PPT Presentation
Transcript of Impact of Ultra-Poor Graduation Pilots: Early Results from Randomized Evaluations
[email protected] www.e-mfp.eu
Impact of Ultra-Poor Graduation Pilots: Early Results from Randomized
Evaluations
Bram ThuysbaertYale University and IPA
November 15, 2012
With A.Banerjee, E. Duflo, D. Karlan, J. Morduch, and othersPreliminary and Incomplete
[email protected] www.e-mfp.eu
Pilots in 10 Sites
Pilot sponsored by CGAP and Ford Foundation: Ghana, Haiti, Honduras, India(3), Ethiopia, Pakistan, Peru, Yemen
Randomized evaluations at 8 sites ( )
[email protected] www.e-mfp.eu
Who are the Ultra Poor? A few facts Most had at least 2 meals
previous day India: 62% Pakistan: 75% Yemen: 87.5% Ethiopia: 83%But most also faced food shortages
in at least some months in the past year
Large share of expenses spent on food and fuel: Pakistan: 54% India: 72% Peru: 70% Yemen: 69%
Pakistan
Yemen
In past 12 months, did HH members get enough food?
[email protected] www.e-mfp.eu
Who are the Ultra Poor? Vulnerable to shocks
India: 29% of selected HH experience 1 or more health shock in past year
Pakistan: Medical expenses 12% of HH budget
Remote areas More than 1 hour to nearest
health center Peru: 24-30% Honduras: 28-58%
[email protected] www.e-mfp.eu
Fundamental research question
What is the impact of the Graduation model on the ultra poor? Impact evaluation measures:
How have the lives of households changed compared to how they would have changed in the absence of the program?
Note this is different from “How have their lives changed?”
The control group gives us the counterfactual Random treatment assignment
ensures we compare similar types of households
[email protected] www.e-mfp.eu
Data collection
Baseline
Consumption surveys
2nd follow-up survey
1st follow-up survey
Collect data on eligible households
Many sites have quarterly surveys to monitor changes
Survey of same baseline households after 2 years (end of program support)
1 year after 1st follow-up survey to track more long-term impacts
[email protected] www.e-mfp.eu
Sample size Many 100’s of households in
a few tens of villages Survey modules Health indicators Education Consumption Income and activities Assets Credit Risk preferences Ongoing qualitative research
Data collection
[email protected] www.e-mfp.eu
Results from 2nd follow-up survey:
Consumptiono 7% increase in food
consumptiono 20% increase in non-food
consumption
Improved food securityo 14 percentage points
increase in share of households that report having enough food every day
India – West Bengal (Bandhan)Researchers: Banerjee, Duflo et al.
[email protected] www.e-mfp.eu
Livestock holdingso Large effect on animal
holdings (years after asset transfer!)
Income generationo Increased income from
livestocko Increase in profits from
micro-enterprises
Household durableso Significant increase in HH
durables index
India – West Bengal (Bandhan)
[email protected] www.e-mfp.eu
Savings and borrowingo Suggestive evidence of
increase in savings deposited in last 30 days (not statistically significant)
o 52.9% increase in total borrowing
Healtho Increase in health knowledgeo Large gains in mental health
at 1st follow-up but no longer at 2nd follow-up
India – West Bengal (Bandhan)
[email protected] www.e-mfp.eu
Results from 2nd follow-up survey: Consumption
o No effects on consumption or food security
Income generationo Increased income from
livestocko But self-employment
displaces wage laboro No net effect on income
Livestocko Effect on livestock holdings
but decreasing over time Savings and borrowing
o No effects
India – Andra Pradesh(SKS)Researchers: Morduch, Ravi and Bauchet
[email protected] www.e-mfp.eu
PakistanResearchers: Karlan and Pariente
Results from 1st follow-up survey:
Consumptiono 10% increase in monthly
consumption• food consumption• emergency expenses
Improved food securityo Increase in share of
households that eat twice a day (3 % points)
o Decrease in share of households that experience food shortages
[email protected] www.e-mfp.eu
Pakistan
Income generationo Important increase in
agricultural outputo Increase in micro-
enterprise profitso No clear effects on
livestock income
Assetso Increase in livestock
holdingso Increase in physical assets
[email protected] www.e-mfp.eu
HondurasResearchers: Karlan and Thuysbaert
Consumption and non -food expenditureso No effects
Improvement in food security and in self-assessed economic situationo Adults 5 percentage points
less likely to have reduced meals
o Improved perception of own economic situation
[email protected] www.e-mfp.eu
Honduras Income generation
o No effects on overall agricultural output nor business profits
o Increase in vegetable productiono Increased income from livestock
Livestocko 25% increase in total value of
livestock owned Savings
o Increased savings Mental health
o Improvement in happiness index
[email protected] www.e-mfp.eu
Conclusion
First results very promising Enlarged asset base More self-employment Improved food security Increased food and non-food consumption Improved happiness …
But variation across sites Are some areas less suitable for graduation model than others? Choice of livelihoods?
Critical questions for evaluation Long term Cost-effectiveness
No definitive answers yet More data and analysis coming soon!
