Minimum wage policies are implemented in most developing countries, so understanding their consequences is critical to determine their effectiveness. This paper studies the labor market and poverty effects of Honduran minimum wages from 2005-2012. In this period, there were annual reforms to multiple minimum wages, a 60% increase, and changes in the number of minimum wage categories. Using 13 household surveys as repeated cross-sections, I estimate the net effects of minimum wage hikes using large variation within categories over time. Evidence shows that employers partially comply with minimum wage laws, and respond to hikes by increasing their level of non-compliance. Higher minimum wages reduce covered (formal) employment and increase uncovered (informal) employment. Formal sector wages increase but rising labor supply in the informal sector leads to a negative net effect on wages. I find no evidence that raising minimum wages reduces poverty.

*Featured in the World Bank’s Development Impact Blog (Nov 2016).

  • “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.

  • “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.