摘要翻译：
本文说明了当干预前结果趋势表明可能违反平行趋势假设时，熵平衡在差异分析中的应用。我们描述了一组假设，在此假设下，即使在干预前结果趋势不平行的情况下，平衡干预组和对照组对干预前结果趋势的加权也会导致一致的差异中的差异估计。模拟结果证明，当平行趋势假设不能直接满足时，干预前结果趋势的熵平衡可以消除偏差，从而使研究人员能够在比以前公认的更广泛的观察环境中使用差异中的差异设计。
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英文标题：
《Reducing bias in difference-in-differences models using entropy
  balancing》
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作者：
Matthew Cefalu, Brian G. Vegetabile, Michael Dworsky, Christine
  Eibner, and Federico Girosi
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最新提交年份：
2020
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分类信息：

一级分类：Statistics        统计学
二级分类：Methodology        方法论
分类描述：Design, Surveys, Model Selection, Multiple Testing, Multivariate Methods, Signal and Image Processing, Time Series, Smoothing, Spatial Statistics, Survival Analysis, Nonparametric and Semiparametric Methods
设计，调查，模型选择，多重检验，多元方法，信号和图像处理，时间序列，平滑，空间统计，生存分析，非参数和半参数方法
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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 illustrates the use of entropy balancing in difference-in-differences analyses when pre-intervention outcome trends suggest a possible violation of the parallel trends assumption. We describe a set of assumptions under which weighting to balance intervention and comparison groups on pre-intervention outcome trends leads to consistent difference-in-differences estimates even when pre-intervention outcome trends are not parallel. Simulated results verify that entropy balancing of pre-intervention outcomes trends can remove bias when the parallel trends assumption is not directly satisfied, and thus may enable researchers to use difference-in-differences designs in a wider range of observational settings than previously acknowledged.
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