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Impact of Ultra-Poor Graduation Pilots: Early Results from Randomized Evaluations

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.

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Impact of Ultra-Poor Graduation Pilots: Early Results from Randomized Evaluations

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  1. 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

  2. Pilotsponsored by CGAP and Ford Foundation: Ghana, Haiti, Honduras, India(3), Ethiopia, Pakistan, Peru, Yemen Randomized evaluations at 8 sites ( ) Pilots in 10 Sites

  3. 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% Who are the Ultra Poor? A few facts In past 12 months, did HH members get enough food? Yemen Pakistan

  4. 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% Who are the Ultra Poor?

  5. 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 Fundamental research question

  6. 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 Data collection Baseline Consumption surveys 1st follow-up survey 2nd follow-up survey

  7. 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

  8. Pakistan Honduras Asset transfers Ethiopia

  9. Preliminary Results

  10. India – West Bengal (Bandhan)Researchers: Banerjee, Duflo et al. • Results from 2nd follow-up survey: • Consumption • 7% increase in food consumption • 20% increase in non-food consumption • Improved food security • 14 percentage points increase in share of households that report having enough food every day

  11. India – West Bengal (Bandhan) • Livestock holdings • Large effect on animal holdings (years after asset transfer!) • Income generation • Increased income from livestock • Increase in profits from micro-enterprises • Household durables • Significant increase in HH durables index

  12. India – West Bengal (Bandhan) • Savings and borrowing • Suggestive evidence of increase in savings deposited in last 30 days (not statistically significant) • 52.9% increase in total borrowing • Health • Increase in health knowledge • Large gains in mental health at 1st follow-up but no longer at 2nd follow-up

  13. India – Andra Pradesh(SKS)Researchers: Morduch, Ravi and Bauchet • Results from 2nd follow-up survey: • Consumption • No effects on consumption or food security • Income generation • Increased income from livestock • But self-employment displaces wage labor • No net effect on income • Livestock • Effect on livestock holdings but decreasing over time • Savings and borrowing • No effects

  14. Pakistan Researchers: Karlan and Pariente • Results from 1st follow-up survey: • Consumption • 10% increase in monthly consumption • food consumption • emergency expenses • Improved food security • Increase in share of households that eat twice a day (3 % points) • Decrease in share of households that experience food shortages

  15. Pakistan • Income generation • Important increase in agricultural output • Increase in micro-enterprise profits • No clear effects on livestock income • Assets • Increase in livestock holdings • Increase in physical assets

  16. Honduras Researchers: Karlan and Thuysbaert • Consumption and non -food expenditures • No effects • Improvement in food security and in self-assessed economic situation • Adults 5 percentage points less likely to have reduced meals • Improved perception of own economic situation

  17. Honduras • Income generation • No effects on overall agricultural output nor business profits • Increase in vegetable production • Increased income from livestock • Livestock • 25% increase in total value of livestock owned • Savings • Increased savings • Mental health • Improvement in happiness index

  18. 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!

  19. www.poverty-action.org bthuysbaert@poverty-action.org www.cgap.org Thank You!

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