Sarah Baird (George Washington University) Francisco Ferreira (World Bank)

1. Relative Effectiveness of Conditional vs. Unconditional Cash Transfers for Schooling in Developing Countries: a systematic review Sarah Baird (George Washington University) Francisco Ferreira (World Bank) Berk Özler (University of Otago/World Bank) Michael Woolcock (World Bank)

2. Outline • Background & objectives • Search strategy & selection criteria • Data collection & analysis • Main Results • Authors Conclusions • Acknowledgements & Funding

3. Background and objectives

4. Background • Increasing educational attainment around the world is one of the key aims of the Millennium Development Goals • There are many social protection programs in developing countries that aim to improve education • Conditional Cash Transfers (CCTs) are “… targeted to the poor and made conditional on certain behaviors of recipient households.” • As of 2007, 29 countries around the world had some type of a Conditional Cash Transfer program (CCT) in place, with many others planning or piloting one (World Bank, 2009) • Unconditional Cash Transfer programs (UCT) are also common and have also been shown to change behaviors on which CCTs are typically conditioned.

6. Background • The debate over whether conditions should be tied to cash transfers has been at the forefront of recent global policy discussions. • The main argument for UCTs is that the key constraint for poor people is simply lack of money (e.g. because of credit constraints), and thus they are best equipped to decide what to do with the cash (Hanlon, Barrientos and Hulme 2010). • Three main arguments for CCTs: market failure that causes suboptimal levels of education; investments in education below socially optimal level; political economy.

7. Objectives • This systematic review aims to complement the existing evidence on the effectiveness of these programs and help inform the debate surrounding the design of cash transfer programs. • Our main objective was to assess the relative effectiveness of conditional and unconditional cash transfers in improving enrollment/dropout, attendance and test scores in developing countries. • Our secondary objective was to understand the role of different dimensions of the cash transfer programs including: • Role of the intensity of conditions • Transfer size • Baseline enrollment

8. Search strategy and selection criteria

9. Search Strategy • Five main strategies were used to identify relevant reports • (1) Electronic searches of 37 international databases (concluded on April, 18 2012) • (2) contacted researchers working in the area • (3) hand searched key journals • (4) reviewed websites of relevant organizations • (5) given the year delay between the original search and the final edits of the review we updated our references with all new eligible references the study team was aware of as of April 30, 2013.

10. Eligible Reports • Report had to either assess the impact of a conditional cash transfer program (CCT), with at least one condition explicitly related to schooling, or evaluate an unconditional cash transfer program (UCT). • The report had to include at least one quantifiable measure of enrollment, attendance or test scores. • The report had to be published after 1997 • The report utilize a randomized control trial or a quasi-experimental design. • The report had to take place in a developing country.

12. Data collection and analysis

13. Calculating Effect Sizes • Measures of treatment effects come from three different types of studies: CCT vs. control, UCT vs. control, and, for four experimental studies, CCT vs. UCT. For these latter set of studies, a separate effect size for CCT and UCT (each compared with the control group of no intervention) is constructed. • We construct odds ratios for effect size measures of enrollment and attendance, and report test score results in standard deviations. • Economists typically do not report the ideal level of information, almost exclusively use cluster designs, and there are multiple reports per study, as well as multiple measures per report.

14. Calculating Effect Sizes • We define an intervention to be a UCT or a CCT. • We define a study to be a different version of a UCT or a CCT (or in a few experiments a UCT and a CCT) implemented in different places • For many of these studies, there are multiple publications (journal articles, working papers, technical reports, etc.). We refer to these as reports. • In our meta-analysis, the unit of observation is the study. This means that we would like to construct one effect size per study for the overall effect on any of our three outcome variables and for each subgroup (if reported).

15. Calculating Effect Sizes • For each subgroup, we construct one effect size by synthesizing and summarizing multiple effect sizes within each report, then again synthesizing and summarizing those combined effect sizes from different reports within a study. • We create synthetic effects when the effect sizes are not independent of each other. This is the case when there are multiple effects reported for the same sample of participants. These effects are combined using a simple average of each effect size (ES) and the variance is calculated as the variance of that mean with the correlation coefficient rassumed to be equal to 1 • When two or more ES are independent of each other, we create summary effects. To combine these estimates into an overall estimate (or an estimate for a pre-defined subgroup), we utilize a random effects (RE) model.

16. Main results

17. Results of the search • 75 reports were included in our review.

18. Results of the search

21. CCT vs. UCT—too simplistic? • Could we categorize all programs, and not just the CCTs, in order of the intensity of schooling conditionalities imposed by the administrators?  • 0. UCT programs unrelated to children or education – such as Old Age Pension Programs(2) • 1. UCT programs targeted at children with an aim of improving schooling outcomes –such as Kenya’s CT-OVC or South Africa’s Child Support Grant  • 2. UCTs that are conducted within a rubric of education – such as Malawi’s SIHR UCT arm or Burkina Faso’s Nahouri Cash Transfers Pilot Project UCT arm (3) • 3. Explicit conditions on paper and/or encouragement of children’s schooling, but no monitoring or enforcement – such as Ecuador’s BDH or Malawi’s SCTS (8)

22. CCT vs. UCT—too simplistic? • 4. Explicit conditions, (imperfectly) monitored, with minimal enforcement – such as Brazil’s Bolsa Familia or Mexico’s PROGRESA (8) • 5. Explicit conditions with monitoring and enforcement of enrollment condition – such as Honduras’ PRAF-II or Cambodia’s CESSP Scholarship Program (6) • 6. Explicit conditions with monitoring and enforcement of attendance condition – such as Malawi's SIHR CCT arm or China’s Pilot CCT program (10)

27. Authors conclusions

28. Authors’ Conclusions (1) • Our main finding is that both CCTs and UCTs improve the odds of being enrolled in and attending school compared to no cash transfer program. • The pooled effect sizes for enrollment and attendance are always larger for CCT programs compared to UCT programs but the difference is not significant. • The findings of relative effectiveness on enrollment in this systematic review are also consistent with experiments that contrast CCT and UCT treatments directly. • When programs are categorized as having no schooling conditions, having some conditions with minimal monitoring and enforcement, and having explicit conditions that are monitored and enforced, a much clearer pattern emerges. • While interventions with no conditions or some conditions that are not monitored have some effect on enrollment rates (18-25% improvement in odds of being enrolled in school), programs that are explicitly conditional, monitor compliance and penalize non-compliance have substantively larger effects (60% improvement in odds of enrollment).

29. Authors’ Conclusions (2) • The effectiveness of cash transfer programs on test scores is small at best. • It seems likely that without complementing interventions, cash transfers are unlikely to improve learning substantively. • Limitations: • Very few rigorous evaluations of UCTs—need more research! • Study limited to education outcomes • Most of the heterogeneity in effect sizes remains unexplained • Not much information on cost • Researchers: • Report relevant data to calculate effect size (i.e. control means at baseline and follow up) • Self reports vs. more objective measures.

30. Acknowledgements and Funding • Thank you!! • International Development Coordinating Group of the Campbell Collaboration for their assistance in development of the protocol and draft report. • John Eyers and Emily Tanner-Smith as well as anonymous referees for detailed comments that greatly improved the protocol. • David Wilson for help with the effect size calculations. • Josefine Durazo, Reem Ghoneim, and Pierre Pratley for research assistance. • Funding • This research has been funded by the Australian Agency for International Development (AusAID). • The views expressed in the publication are those of the authors and not necessarily those of the Commonwealth of Australia. The Commonwealth of Australia accepts no responsibility for any loss, damage or injury resulting from reliance on any of the information or views contained in this publication • The Institute for International and Economic Policy (IIEP) at George Washington University also assisted with funding for a research assistant.