CONSISTENT ESTIMATION OF TREATMENT EFFECTS UNDER ENDOGENOUS HETEROSKEDASTICITY

主讲人: Haiqing Xu
主讲人简介:

Assistant Professor, The University of Texas at Austin.

Please find Prof. Xu's CV for more information.

主持人: Qingliang Fan
简介:

The empirical literature on program evaluation limits its scope almost exclusively to models where treatment effects are homogenous for observationally identical individuals. This paper considers a treatment effect model in which treatment effects may be heterogeneous, even among observationally identical individuals. Specifically, extending the classical instrumental variables (IV) model with an endogenous binary treatment and a binary instrument, we allow the heteroskedasticity of the error disturbance to also depend upon the treatment variable so that treatment has both mean and variance effects on the outcome. In this endogenous heteroskedasticity IV (EHIV) model with heterogeneous individual treatment effects, the standard IV estimator can be inconsistent and lead to incorrect inference. After showing identification of the mean and variance treatment effects in a nonparametric version of the EHIV model, we provide closed-form estimators for the linear EHIV for the mean and variance treatment effects and the individual treatment effects (ITE). Asymptotic properties of the estimators are provided. A Monte Carlo simulation investigates the performance of the proposed approach, and an empirical application regarding the effects of fertility on female labor supply is considered.

时间: 2018-06-18(Monday)16:40-18:00
地点: N302, Econ Building
类型: 系列讲座