- “Information Policies and Higher Education Choices: Experimental Evidence from Colombia” with Leonardo Bonilla and Nicolas Bottan (Under Review).
This paper studies whether providing information on funding opportunities and average earnings by degree-college pairs affects higher education decisions. We conducted a randomized controlled trial in Bogotá, Colombia, on a representative sample of 120 public high schools, half of which received an informational talk delivered by recent college graduates. Using survey data linked to administrative records, we analyze student beliefs and evaluate the intervention. Findings show that most students overestimate college premiums, but the talk does not affect these beliefs. It does improve knowledge of financing programs, especially among the poor. There is no evidence that information disclosure affects post-secondary enrollment. However, students in treated schools who do enroll choose more selective colleges. These positive effects are mostly driven by students from better socioeconomic backgrounds. We conclude that information policies are ineffective to raise college enrollment in contexts with significant barriers to entry, but may influence intensive margin choices.
*Featured in the World Bank’s Development Impact Blog (Jul 2016).
- “Does the form of delivering educational incentives in conditional cash transfers matter over a decade later?” with Hope Michelson (Submitted).
We study whether Honduran children exposed to a conditional cash transfer program from 2000-2005 experience lasting effects on human capital and labor market participation in early adulthood. The government randomly assigned three forms of delivering educational benefits across targeted municipalities: demand (vouchers), supply (school support), and a combination of both. This program provides an opportunity to explore if and how differential exposure to incentives for education produces longer term effects. Using municipal-level panel data, these effects are estimated using difference-in-differences. We find that the form of delivering cash transfers influences the degree to which these programs make progress towards their objective of reducing poverty. Compared to municipalities receiving support from the national Poverty Reduction Strategy, our study indicates that separate exposure to demand or supply-side incentives has no lasting impact. However, joint exposure to both incentives does lead to measurable improvements in schooling and labor market participation, especially for women.
- “Can’t Stop the One-Armed Bandits: The Effects of Access to Gambling on Crime” with Nicolas Bottan and Ignacio Sarmiento-Barbieri.
We study the effect of a large increase in access to gambling on crime by exploiting the expansion of video gambling terminals in Illinois since 2012. Even though video gambling was legalized by the State of Illinois, local municipalities were left with the decision whether to allow it within their jurisdiction. The City of Chicago does not allow video gambling, while many adjacent jurisdictions do. We take advantage of this setting along with detailed incident level data on crime for Chicago to examine the effect of access to gambling on crime. We use a difference-in-differences strategy that compares crime in areas that are closer to video gambling establishments with those that are further away along with the timing of video gambling adoption. We find that (i) access to gambling increases violent and property crimes; (ii) these are new crimes rather than displaced incidents; and (iii) the effects seem to be persistent in time.
- “How important is spatial correlation in randomized controlled trials?” with Kathy Baylis.
Randomized controlled trials (RCTs) have become the gold standard for impact evaluation since they provide unbiased estimates of causal effects. This paper focuses on RCTs that allocate treatment status over clusters in geographical proximity. We study how omitting spatial correlation in outcomes or unobservables at the cluster-level affects difference-in-difference estimates at the individual-level. Using Monte Carlo experiments, we identify bias and efficiency problems and propose solutions to overcome them. Our framework is then tested on data from Mexico’s Progresa program. Results show that spatial correlation may affect both the precision of the estimate and the estimate itself, especially when geographic dependence is high.