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Design-based Analysis in Difference-In-Differences Settings with Staggered Adoption

Susan Athey and Guido Imbens

Papers from arXiv.org

Abstract: In this paper we study estimation of and inference for average treatment effects in a setting with panel data. We focus on the setting where units, e.g., individuals, firms, or states, adopt the policy or treatment of interest at a particular point in time, and then remain exposed to this treatment at all times afterwards. We take a design perspective where we investigate the properties of estimators and procedures given assumptions on the assignment process. We show that under random assignment of the adoption date the standard Difference-In-Differences estimator is is an unbiased estimator of a particular weighted average causal effect. We characterize the proeperties of this estimand, and show that the standard variance estimator is conservative.

Date: 2018-08, Revised 2018-09
New Economics Papers: this item is included in nep-ecm and nep-exp
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (135)

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http://arxiv.org/pdf/1808.05293 Latest version (application/pdf)

Related works:
Journal Article: Design-based analysis in Difference-In-Differences settings with staggered adoption (2022) Downloads
Working Paper: Design-based Analysis in Difference-In-Differences Settings with Staggered Adoption (2018) Downloads
Working Paper: Design-based Analysis in Difference-In-Differences Settings with Staggered Adoption (2018) Downloads
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