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Identifying Treatment Effects Under Data Combination

Fan, Yanqin and Sherman, Robert and Shum, Matthew (2014) Identifying Treatment Effects Under Data Combination. Econometrica, 82 (2). pp. 811-822. ISSN 0012-9682. doi:10.3982/ECTA10601.

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We consider the identification of counterfactual distributions and treatment effects when the outcome variables and conditioning covariates are observed in separate data sets. Under the standard selection on observables assumption, the counterfactual distributions and treatment effect parameters are no longer point identified. However, applying the classical monotone rearrangement inequality, we derive sharp bounds on the counterfactual distributions and policy parameters of interest.

Item Type:Article
Related URLs:
URLURL TypeDescription DOIArticle ItemSSWP 1377
Shum, Matthew0000-0002-6262-915X
Additional Information:© 2014 The Econometric Society. Manuscript received February, 2012; final revision received October, 2013. Article first published online: 1 Apr. 2014. We are grateful to Cheng Hsiao, Sergio Firpo, Marc Henry, Chuck Manski, Kevin Song, and Jeff Wooldridge for valuable comments and discussions. We thank Sang Mok Lee for excellent research assistance, and seminar participants at Michigan State, USC, U. Washington, the Canadian Econometrics Study Group meetings (2011, Toronto), and the Vanderbilt conference, Identification and Inference in Microeconometrics (2012) for useful comments. Formerly SSWP 1377.
Subject Keywords:Counterfactual distributions; treatment effects; partial identification
Issue or Number:2
Record Number:CaltechAUTHORS:20140508-094952115
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Official Citation:Fan, Y., Sherman, R. and Shum, M. (2014), Identifying Treatment Effects Under Data Combination. Econometrica, 82: 811–822. doi: 10.3982/ECTA10601
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:45599
Deposited By: Tony Diaz
Deposited On:08 May 2014 19:33
Last Modified:10 Nov 2021 17:14

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