Efficient semiparametric estimation of quantile treatment effects

This paper presents calculations of semiparametric efficiency bounds for quantile treatment effects parameters when se1ection to treatment is based on observable characteristics. The paper also presents three estimation procedures forthese parameters, alI ofwhich have two steps: a nonparametric estimation and a computation ofthe difference between the solutions of two distinct minimization problems. Root-N consistency, asymptotic normality, and the achievement ofthe semiparametric efficiency bound is shown for one ofthe three estimators. In the final part ofthe paper, an empirical application to a job training program reveals the importance of heterogeneous treatment effects, showing that for this program the effects are concentrated in the upper quantiles ofthe earnings distribution.

The effects of tax incentives for small firms on employment levels

This paper will examine the effects of tax incentives for small businesses on employment level evaluating a program with this purpose implemented in Brazil in the 1990s. We first develop a theoretical framework which guides both the de nition of the parameters of interest and their identi cation. Selection problems both into the treatment group and into the data sample are tackled by combining fixed effects methods and regression discontinuity design on alternative sub-samples of a longitudinal database of manufacturing firms. The results show that on the one hand the size composition of the treated fi rms may be changed due to the survival of some smaller firms that would have exited had it not been eligible to the program. On the other hand, the treated firms who do not depend on the program to survive do employ more workers.

Inequality treatment effects

This paper presents semiparametric estimators for treatment effects parameters when selection to treatment is based on observable characteristics. The parameters of interest in this paper are those that capture summarized distributional effects of the treatment. In particular, the focus is on the impact of the treatment calculated by differences in inequality measures of the potential outcomes of receiving and not receiving the treatment. These differences are called here inequality treatment effects. The estimation procedure involves a first non-parametric step in which the probability of receiving treatment given covariates, the propensity-score, is estimated. Using the reweighting method to estimate parameters of the marginal distribution of potential outcomes, in the second step weighted sample versions of inequality measures are.computed. Calculations of semiparametric effciency bounds for inequality treatment effects parameters are presented. Root-N consistency, asymptotic normality, and the achievement of the semiparametric efficiency bound are shown for the semiparametric estimators proposed. A Monte Carlo exercise is performed to investigate the behavior in finite samples of the estimator derived in the paper.

Life expectancy and human capital investment: the arrival of AIDS treatment in Brazil

This paper provides microevidence on the relationship between life expectancy and educational investment decisions. Human capital theory predicts an increase in life expectancy should lead to an augmenting in schooling investment. This paper uses an unique data set on AIDS patients among Brazilian inhabitants in an attempt to estimate the impact of the arrival of Antiretroviral therapy (ART) on educational outcomes. The availability of ART offsets the negative relationship between vertical HIV-transmission and schooling, around 68% and 57% for elementary and high school completion, respectively. Robustness tests indicate the results are not driven by convergence effects.