arXiv · 2503.19873
Identification of Average Treatment Effects in Nonparametric Panel Models
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.
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Susan Athey, Guido Imbens. 2025-03-25. Identification of Average Treatment Effects in Nonparametric Panel Models. https://arxiv.org/abs/2503.19873
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