This paper discusses the evaluation problem using observational data when the timing of treatment is an outcome of a stochastic process. We show that, without additional assumptions, it is not possible to estimate the average treatment effect and treatment on the treated. It is, however,...

This paper introduces a new framework for quantile estimation. Quantile regression techniques have proven to be extremely valuable in understanding the relationship between explanatory variables and the conditional distribution of the outcome variable. Quantile regression allows the effect of...

I introduce a procedure to nonparametrically estimate local quantile treatment effects in a regression discontinuity (RD) design with a binary treatment. Analogously to Hahn, Todd, and van der Klaauw's (2001) estimator for average treatment effects using local linear regression, the estimator...

This paper considers causal inference and sample selection bias in non-experimental settings in which: (i) few units in the non-experimental comparison group are comparable to the treatment units; and (ii) selecting a subset of comparison units similar to the treatment units is difficult because...

A aplicação de métricas de risco na EDP é fundamental não só para apoio à decisão sobre operações de Trading no mercado de electricidade e de combustíveis, como também, na tomada de decisões no âmbito do Plano de Negócios com base numa avaliação periódica do nível de risco de...

This article proposes different tests for treatment effect heterogeneity when the outcome of interest, typically a duration variable, may be right-censored. The proposed tests study whether a policy 1) has zero distributional (average) effect for all subpopulations defined by covariate values,...