Matrix Completion Methods for Causal Panel Data Models

In this article, we study methods for estimating causal effects in settings with panel data, where some units are exposed to a treatment during some periods and the goal is estimating counterfactual (untreated) outcomes for the treated unit/period combinations. We propose a class of matrix completio...

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Veröffentlicht in:	Journal of the American Statistical Association Jg. 116; H. 536; S. 1716 - 1730
Hauptverfasser:	Athey, Susan, Bayati, Mohsen, Doudchenko, Nikolay, Imbens, Guido, Khosravi, Khashayar
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Alexandria Taylor & Francis 02.10.2021 Taylor & Francis Ltd
Schlagworte:	Causal models Causality Completion Control methods Dependency Dependency grammar Estimators Interactive fixed effects Literature Longitudinal studies Low-rank matrix estimation Matrices Missing data Panel data Program evaluation Regression analysis Regularization Social sciences Statistical methods Statistics Synthetic controls Time series time series analysis Unconfoundedness
ISSN:	0162-1459, 1537-274X, 1537-274X
Online-Zugang:	Volltext
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