Estimation of counterfactual distributions with a continuous endogenous treatment

In this article, I propose a method to estimate the counterfactual distribution of an outcome variable when the treatment is endogenous, continuous, and its effect is heterogeneous. The types of counterfactuals considered are those in which the change in treatment intensity can be correlated with th...

Full description

Saved in:
Bibliographic Details
Published inEconometric reviews Vol. 43; no. 8; pp. 595 - 637
Main Author Pereda-Fernández, Santiago
Format Journal Article
LanguageEnglish
Published New York Taylor & Francis 13.09.2024
Taylor & Francis Ltd
Subjects
Birth weight
Continuity (mathematics)
Copula
counterfactual distribution
Counterfactual thinking
Econometrics
endogeneity
Endogenous
Mothers
policy analysis
quantile regression
Quantiles
unconditional distributional effects
Online AccessGet full text

Cover

More Information
Summary:In this article, I propose a method to estimate the counterfactual distribution of an outcome variable when the treatment is endogenous, continuous, and its effect is heterogeneous. The types of counterfactuals considered are those in which the change in treatment intensity can be correlated with the individual effects or when some of the structural functions are changed by some other group's counterparts. I characterize the outcome and the treatment with a triangular system of equations in which the unobservables are related by a copula that captures the endogeneity of the treatment, which is nonparametrically identified by inverting the quantile processes that determine the outcome and the treatment. Both processes are estimated using existing quantile regression methods, and I propose a parametric and a nonparametric estimator of the copula. To illustrate these methods, I estimate several counterfactual distributions of the birth weight of children, had their mothers smoked differently during pregnancy.
ISSN:0747-4938
1532-4168
DOI:10.1080/07474938.2024.2357429