处理效应评估中的内生性与无应答偏差:基于工具变量的非参数因果识别

Endogeneity and non‐response bias in treatment evaluation – nonparametric identification of causal effects by instruments

Journal of Applied Econometrics · 2020
被引 15
人大 AABS 3

中文导读

提出一种基于两个工具变量的非参数方法,同时处理治疗内生性和样本流失/无应答偏差,识别对依从者和总人口的平均处理效应,并应用于评估健身房训练对自评健康的影响。

Abstract

Summary This paper proposes a nonparametric method for evaluating treatment effects in the presence of both treatment endogeneity and attrition/non‐response bias, based on two instrumental variables. Using a discrete instrument for the treatment and an instrument with rich (in general continuous) support for non‐response/attrition, we identify the average treatment effect on compliers as well as the total population under the assumption of additive separability of observed and unobserved variables affecting the outcome. We suggest non‐ and semiparametric estimators and apply the latter to assess the treatment effect of gym training, which is instrumented by a randomized cash incentive paid out conditional on visiting the gym, on self‐assessed health among students at a Swiss university. The measurement of health is prone to non‐response, which is instrumented by a cash lottery for participating in the follow‐up survey.

内生性非回应偏差工具变量处理效应