Estimation of Panel Data Models with Binary Indicators When Treatment Effects are Not Constant Over Time
Estimation of Panel Data Models with Binary Indicators When Treatment Effects are Not Constant Over Time
复制标题
当治疗效果随时间变化不恒定时用二元指标估计面板数据模型
DOI：
10.2139/ssrn.720061
复制
发表时间：
2004
期刊：
影响因子：
--
通讯作者：
F. Windmeijer
中科院分区：
文献类型：
--
作者：
A. Laporte;F. Windmeijer
我们表明，两种常用的估计程序来处理面板数据模型中相关的未观察到的异质性，组内和第一差分OLS，可以导致非常不同的处理效果估计，当这些不是随时间恒定的，处理是一种只有偶尔改变的状态。因此，在用二元指标变量估计面板数据模型时，重要的是考虑灵活的时变处理效应，如婚姻状况对心理健康的影响的例子所说明的那样。
We show that two commonly employed estimation procedures to deal with correlated unobserved heterogeneity in panel data models, within-groups and first-differenced OLS, can lead to very different estimates of treatment effects when these are not constant over time and treatment is a state that only changes occasionally. It is therefore important to allow for flexible time varying treatment effects when estimating panel data models with binary indicator variables as is illustrated by an example of the effects of marital status on mental wellbeing.