1. How do Vouchers Work? Evidence from Colombia Eric Bettinger, Case Western U Michael Kremer, Harvard Juan Saavedra, Harvard 7 June 2007 World Bank

2. Educational Vouchers Controversial and Often Debated Educational Reform Large-Scale Voucher Programs –Chile & Colombia –US Sites (Milwaukee, Cleveland, Florida, Ohio) –Other Voucher-Like Programs Private Programs in US Regulated Voucher Programs Internationally (e.g. Sweden, Japan, The Netherlands) Motivation for Programs Differ Substantially Across Sites –Competition and Opportunity –Overcrowding

3. Evidence on Educational Vouchers International Evidence –Colombia –Chile US Evidence –New York City Scholarship Program –Milwaukee Voucher Program –Other Private/Public Programs

4. Welfare Implications of Vouchers Costs/Benefits to Students Directly Receiving the Voucher –Cost of Voucher –Change in Educational Outcomes Costs/Benefits to Students not Receiving the Voucher –Change in Peers –Competition –Change in Resources

5. Peer Effects and Vouchers Hsieh and Urquiola (2006) –Chilean Voucher Program –Key Finding was that Aggregate Outcomes Did Not Change –Voucher Recipients Experienced a Positive Peer Effect –Other “Left Behind” Students Experienced a Negative Effect Epple and Romano (1998) –Model of Educational Vouchers –Peer Effects Need Not Be Zero Sum but Some Students are Worse Off

6. Other Peer Effect Literature Sacerdote (2001) Duncan, Boisjoly, Kremer, Levy and Eccles (2005) Zimmerman (2003)

7. Simple Model with Peer Effects Consider the Following Educational Production Function Y i = Educational Outcome Student i X i = Socioeconomic Characteristics of Student i = Average Characteristic of School P = Program Participation

8. Model (cont.) Positive Voucher Effects but No Peer Effects β 1 =0, β 2 >0 Positive Voucher Effects are Solely Peer Effects β 1 >0, β 2 =0

9. Voucher Comparisons Because of Randomization, Difference in Average Outcome of Voucher Lottery Winners and Losers Measures the Effect: Reported Effects in Angrist et. al. (2002, 2006)

10. Social Effects Depends on Values of β 1 and β 2 If β 1 =0, β 2 >0, then social effect is β 2 If β 1 >0, β 2 =0, then no social effect in simple linear-in-means peer effect model

11. How does One Untangle Peer and Voucher Effects? Ideal Experiment: –Randomly Assign Voucher Students to Group with “Worse” Peers –Measure Whether Voucher Effect is Present When Peer Effect is Bad –If Voucher Effects are from Peer Effects, then Voucher Effects Should Disappear or Even Be Negative Colombia PACES Program May Have Such an Experiment

12. Colombia’s PACES Program Objectives –Increase secondary school enrollment for poor Rules –Student must be entering 6th grade and under 15 years old –Students must provide evidence that they live in poor neighborhood (strata 1 or 2) –Renewable through graduation unless student is retained in a grade –Vouchers awarded by lottery if demand exceeds supply –Covered about 60% of fees Scope –216 Municipalities have Participated –Over 125,000 secondary students have received support

13. Previous Work on Colombia Angrist, Bettinger, Bloom, King, Kremer (AER 2002) Surveyed Voucher Applicants from Bogotá 1995 Lottery Compared Voucher Lottery Winners and Losers Effects after Three Years Key Findings on Voucher Recipients: –Increased Usage of Private Schools –Higher Educational Attainment –No Difference in Drop-out Rates –Less Grade Repetition –Higher Test Scores –Less Incidence of Teen-age Employment

14. More Previous Work on Colombia Angrist, Bettinger, Kremer (AER 2006) Tracked Applicants to Bogotá 1995 Lottery Using Administrative Records Compared Voucher Lottery Winners and Losers Effects after Six to Seven Years Key Findings on Voucher Recipients: –Increased Likelihood of Taking College Entrance Exam –Improved Exam Performance in Math and Language

15. Other Details on Colombia’s PACES Students Had to be Accepted at a Private School PRIOR to the Voucher Lottery –Some Students Applied to Vocational Schools –Vocational Schools May Attract “Worse” Peers The Voucher was Portable in Theory but Not Practice –1998 MIT Survey of Voucher Applicants Shows that Voucher Winners Did Not Retain Voucher When Transferring Schools

16. Patterns of Attendance School Applied To Vocational School Attended Three Years after Voucher Lottery Winner Vocational.5962 Non-Vocational.2692 Dropout.1346

17. Patterns of Attendance School Applied To Vocational School Attended Three Years after Voucher Lottery WinnerLoser Vocational.5962.4264 Non-Vocational.2692.4264 Dropout.1346.1473

18. Patterns of Attendance School Applied To VocationalNon-Vocational School Attended Three Years after Voucher Lottery WinnerLoserWinnerLoser Vocational.5962.4264.0369.0626 Non-Vocational.2692.4264.7995.7517 Dropout.1346.1473.1590.1790

19. Voucher Winners and Vocational Schools Voucher Winners who Applied to Vocational Schools Stay in Vocational Schools Lack of Portability Creates Rigidity –Voucher Winners Stay Even if School is Suboptimal Did Vocational Schools Have “Worse” Peers?

20. Were Vocational Schools Worse? WB Funded School Survey in 2006 Attempted to Contact 300 Schools –Chose Schools with Most Voucher Applicants Attending –Schools Represented 85 Percent of Voucher Applicants Survey Gathered Significant Data on Peer and School Quality

21. Comparing Peer Quality Estimate for Sample of Students Who Applied to Vocational Schools Prior to Lottery W i = α + γV i +πZ i + u i W i = School characteristic of student i V i = Student i is voucher winner Z i = Other Student Characteristics Key issue will be low sample size. We only know schools of attendance for about 200 voucher students who had wanted to attend vocational school. –Pooling Estimates

22. Diffs in Peer Quality

23. More Diffs in Peer Quality

24. How to Increase Power? Average Effect Sizes –Normalize Measures Standard Deviation Units Monotonicity –Estimate Effect Sizes Simultaneously Fully Interacted Model Similar to Seemingly Unrelated Regression –Combine Coefficients Kolmogorov-Smirnov –If there is no Effect of a Program, the Family of T- Statistics Should Behave Like Normal Distribution –Doesn’t Account for Correlation Between Outcomes

25. Average Effect Sizes

26. Family of T-Statistics Vocational Voucher Applicants

27. Family of T-Statistics Non- Vocational Voucher Applicants

28. Key Results on Peer Quality Among Voucher Applicants to Vocational Schools, Winners’ Peers Are –Less Likely to Attend College –Less Likely to Graduate –More Likely to Attend Remedial Programs –Attend Schools with Lower Fees Voucher Winners’ Schools Also Appear to Have –Less Qualified Teachers –More Facilities on Campus Same Differences are not Present Among Applicants to Non-Voucher Schools

29. Are Voucher Effects Still Present?

31. Key Conclusions Among Students Who Originally Applied to Vocational Schools, Voucher Winners... –Attended Schools with Worse Observable Characteristics –Had Higher Likelihood of Taking the ICFES College Entrance Exam –Had Higher Test Scores on ICFES Exam Peer Effects cannot Explain Voucher Effects

32. Voucher Mechanisms? Incentives –Vouchers were Renewable Conditional on Passing –Emerging Literature on Incentives (e.g. Kremer, Miguel, and Thornton 2005) Attending School that Students Value More –Vocational Schools Increasingly Focused on Emerging Service Industry –Private Sector Has Adjusted Quickly to Changes in Labor Market –Differences in Apprenticeship Opportunities –Industrial versus Commercial Education Curricula Limited Commercial Education Slots in Public Sector Private Commercial Schools Retain Students

33. In Conclusion Peer Effects are Important in Education Disentangling Voucher and Peer Effects is Difficult –Need Unique Experiment where Vouchers Assign Students to “Worse” Peers –Applicants to Vocational Schools (PRIOR) to Colombian Voucher Lottery Vocational Voucher Winners Attend Schools with “Worse” Peers Vocational Voucher Winners Have Higher Academic Achievement Than Voucher Lottery Losers Peer Effects May Not Explain the Voucher Effects Other Mechanisms are Plausible