"Decomposition methods" (with Sergio Firpo), Handbook of Labor, Human Resources and Population Economics, 2023.
This chapter uses the classic Oaxaca-Blinder (OB) decomposition for the mean as its point of departure and then focuses on the last 15 years of decomposition methods that go beyond the mean. The analysis starts from the formal decomposition theory and its link with the treatment effect literature. Then, the OB decomposition is formally derived, and next, the other methods for decomposition are shown. Finally, a link is made between this literature and structural models. In this way, this chapter can be seen as a guide for performing decomposition methods.
"Passing through the supply chain: Implications for market power" (with Carolina Melo and Rodrigo Moita), International Journal of Industrial Organization, 2021.
In this paper, we study the connection between pass-through and market power in the Brazilian Liquefied Petroleum Gas (LPG) industry. We use a state tax shock and apply a difference-in-differences strategy to estimate pass-through –at different levels of the supply chain –and an instrumented difference-in-differences strategy to estimate demand and then feed a theoretical model to make inferences about a conduct parameter –that measures market power. We find an incomplete pass-through at the distribution level, for the supply chain as a whole, and a more-than-complete one at the retail level. Furthermore, we estimate the price elasticity of demand to be greater than one. When we feed a theoretical pass-through model under imperfect competition with these estimates, we obtain a high conduct parameter at the whole supply chain level and an even higher one at the retail level alone. These results show that considering only the whole supply chain pass-through may lead to hasty conclusions about market power. Besides contributing to the empirical literature that connects pass-through with market power, we contribute to ongoing national discussions regarding competitiveness in the LPG industry.
"Sample selection in unconditional quantile models".
We propose constructing a consistent estimator that addresses the problem of sample selection in unconditional quantile models. The proposed approach is based on three steps: (i) estimation of a control function using a logistic distribution regression; (ii) construction of a counterfactual distribution of the latent dependent variable conditional on the previously estimated control function; (iii) application of the recentered influence function (RIF) on the estimated counterfactual distribution and, finally, we run an ordinary least square regression.
"Where the sentence is served: community service and entrepreneurship among ex-felons" (with Vera Rocha).
People with criminal records are likely to face major barriers in the labor market due to stigma, yet access to employment is crucial for their (re)integration into the broader society. Recent research and policy initiatives point to entrepreneurship – the act of launching a business, either as self-employed or as an employer – as a pathway to reintegrate ex-felons into the labor market, by mitigating the penalty of stigmatization these individuals would otherwise face among employers. However, we still know little about how successful ex-felons become as entrepreneurs and, ultimately, how effective entrepreneurship can be as an integration route for them. We embrace this question in a large-scale project, in which we study the trajectories of individuals with criminal records in the Danish labor market. This paper focuses on the first part of this project, in which we investigate how the type of sentences received by people with criminal records relate to their subsequent labor market trajectories and, more in particular, their transition into entrepreneurship. We study how using community service as an alternative sanction to imprisonment shapes entrepreneurship rates among ex-felons. We find that the type of sentence received matters: community service reduces entrepreneurship rates compared to prison sentences. This points out that individuals sentenced with community service might suffer less stigma in the labor market than those receiving prison sentences, making them less likely to turn to entrepreneurship after serving their sentences.
"Challenges and solutions to maintain the validity of the experimental analysis of large social programs in the public sector" (with Ricardo Paes de Barros, Sergio Firpo, Ricardo Henriques, Laura Machado, and Mirela Carvalho).
In this paper, we document the challenges faced and solutions proposed by evaluators of a large-scale, long-term school and educational-system management program implemented in Brazil’s public schools. There were three main challenges: (i) differential reactions to the evaluation from treated and control units, (ii) political cycles and bureaucracy turnover, and (iii) usual statistical issues, such as contamination, small sample sizes, and attrition. The first was solved by adopting outcome measures, whose performance incentives were independent of the treatment assignment. Dissemination of initial evaluation results among managers and school principals, who recognized the program’s benefits and demanded its continuation, was a way to deal with the second challenge. Finally, the long-term trust relationship built with implementers, school principals, and managerial staff of the state bureaucracy allowed evaluators to avoid contamination effects and abrupt program terminations, which would have reduced sample sizes. Although other countries deal with different contexts and specificities, the Brazilian case can anticipate recurring problems and offer insights into evaluating large-scale and high-complexity programs with similar characteristics.