计量经济学
推论
集合(抽象数据类型)
简单(哲学)
变化(天文学)
计算机科学
光学(聚焦)
经济
认识论
人工智能
天体物理学
光学
物理
哲学
程序设计语言
作者
Jonathan Roth,Pedro H. C. Sant’Anna,Alyssa Bilinski,John Poe
标识
DOI:10.1016/j.jeconom.2023.03.008
摘要
This paper synthesizes recent advances in the econometrics of difference-in-differences (DiD) and provides concrete recommendations for practitioners. We begin by articulating a simple set of “canonical” assumptions under which the econometrics of DiD are well-understood. We then argue that recent advances in DiD methods can be broadly classified as relaxing some components of the canonical DiD setup, with a focus on (i) multiple periods and variation in treatment timing, (ii) potential violations of parallel trends, or (iii) alternative frameworks for inference. Our discussion highlights the different ways that the DiD literature has advanced beyond the canonical model, and helps to clarify when each of the papers will be relevant for empirical work. We conclude by discussing some promising areas for future research.
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