Identification of Average Treatment Effects in Nonparametric Panel Models

Susan Athey and Guido Imbens

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Abstract: This paper studies identification of average treatment effects in a panel data setting. It introduces a novel nonparametric factor model and proves identification of average treatment effects. The identification proof is based on the introduction of a consistent estimator. Underlying the proof is a result that there is a consistent estimator for the expected outcome in the absence of the treatment for each unit and time period; this result can be applied more broadly, for example in problems of decompositions of group-level differences in outcomes, such as the much-studied gender wage gap.

Date: 2025-03
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2503.19873

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