摘要翻译：
本文考虑通过一个交互固定效应模型来识别和估计当未治疗的潜在结果产生时，对被治疗者的平均治疗效果(ATT)。也就是说，除了时间周期和个体的固定效应之外，我们考虑了这样的情况，即存在一个未观察到的时间不变变量，它对未治疗的潜在结果的影响可能随着时间的推移而改变，从而导致治疗组的结果（在不参与治疗的情况下）相对于未治疗组遵循不同的路径。本文所考虑的模型概括了治疗效果文献中的许多常用模型，包括差异中的差异模型和个体特异性线性趋势模型。与大多数关于互动固定效应模型的文献不同，我们不要求时间周期的数目达到无穷大来一致地估计ATT。我们的主要识别结果依赖于某种时间不变协变量（例如，种族或性别）的影响不随时间变化。利用我们的方法，我们表明ATT可以用三个时间周期和面板或重复截面数据来识别。
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英文标题：
《Treatment Effects in Interactive Fixed Effects Models》
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作者：
Brantly Callaway and Sonia Karami
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最新提交年份：
2021
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分类信息：

一级分类：Economics        经济学
二级分类：Econometrics        计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
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英文摘要：
  This paper considers identifying and estimating the Average Treatment Effect on the Treated (ATT) when untreated potential outcomes are generated by an interactive fixed effects model. That is, in addition to time-period and individual fixed effects, we consider the case where there is an unobserved time-invariant variable whose effect on untreated potential outcomes may change over time and which can therefore cause outcomes (in the absence of participating in the treatment) to follow different paths for the treated group relative to the untreated group. The models that we consider in this paper generalize many commonly used models in the treatment effects literature including difference in differences and individual-specific linear trend models. Unlike the majority of the literature on interactive fixed effects models, we do not require the number of time periods to go to infinity to consistently estimate the ATT. Our main identification result relies on having the effect of some time invariant covariate (e.g., race or sex) not vary over time. Using our approach, we show that the ATT can be identified with as few as three time periods and with panel or repeated cross sections data.
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PDF链接：
https://arxiv.org/pdf/2006.15780