In this article, we present a new command, qcte, that implements several methods for estimation and inference for quantile treatment-effects models with a continuous treatment. We propose a semiparametric two-step estimator, where the first step is based on a flexible Box-Cox model, as the default model of the command. We develop practical statistical inference procedures using bootstrap. We implement some simulations to show that the proposed methods perform well. Finally, we apply qcte to a survey of Massachusetts lottery winners to estimate the unconditional quantile effects of the prize amount, as a proxy of nonlabor income changes, on subsequent labor earnings from U.S. Social Security records. The empirical results reveal strong heter...
This paper analyzes two econometric tools that are used to evaluate distributional effects, condi-ti...
This paper reviews strategies that allow one to identify the effects of policy interventions on the ...
Nonparametric estimators for average and quantile treatment effects are constructed using Fractile G...
We propose a new general approach for estimating the effect of a binary treat-ment on a continuous a...
We propose a new general approach for estimating the effect of a bi- nary treatment on a continuous ...
Copyright © 2019 The Authors. This paper considers identification and estimation of the Quantile Tre...
In this article, we discuss the implementation of various estimators proposed to estimate quantile t...
This paper develops a model of causal quantile treatment eects in the presence of endogeneity. The c...
This paper introduces an instrumental variables estimator for the effect of a binary treatment on th...
This paper develops estimators for quantile treatment effects under the identifying restriction that...
Standard causal inference characterizes treatment effect through averages, but the counterfactual di...
The ability of quantile regression models to characterize the heterogeneous impact of variables on d...
Purpose: Several approaches have been proposed to evaluate treatment effect, relying on matching met...
In this paper, we provide efficient estimators and honest confidence bands for a variety of treatmen...
© 2019, © 2019 American Statistical Association. Quantile and quantile effect (QE) functions are imp...
This paper analyzes two econometric tools that are used to evaluate distributional effects, condi-ti...
This paper reviews strategies that allow one to identify the effects of policy interventions on the ...
Nonparametric estimators for average and quantile treatment effects are constructed using Fractile G...
We propose a new general approach for estimating the effect of a binary treat-ment on a continuous a...
We propose a new general approach for estimating the effect of a bi- nary treatment on a continuous ...
Copyright © 2019 The Authors. This paper considers identification and estimation of the Quantile Tre...
In this article, we discuss the implementation of various estimators proposed to estimate quantile t...
This paper develops a model of causal quantile treatment eects in the presence of endogeneity. The c...
This paper introduces an instrumental variables estimator for the effect of a binary treatment on th...
This paper develops estimators for quantile treatment effects under the identifying restriction that...
Standard causal inference characterizes treatment effect through averages, but the counterfactual di...
The ability of quantile regression models to characterize the heterogeneous impact of variables on d...
Purpose: Several approaches have been proposed to evaluate treatment effect, relying on matching met...
In this paper, we provide efficient estimators and honest confidence bands for a variety of treatmen...
© 2019, © 2019 American Statistical Association. Quantile and quantile effect (QE) functions are imp...
This paper analyzes two econometric tools that are used to evaluate distributional effects, condi-ti...
This paper reviews strategies that allow one to identify the effects of policy interventions on the ...
Nonparametric estimators for average and quantile treatment effects are constructed using Fractile G...