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Identifying Treatment Effects under Data Combination

Fan, Yanqin and Sherman, Robert and Shum, Matthew (2013) Identifying Treatment Effects under Data Combination. Social Science Working Paper, 1377. California Institute of Technology , Pasadena, CA. (Unpublished)

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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 datasets. Under the standard selection on observables assumption, the counterfactual distributions and treatment effect parameters are no longer point identified. However, applying the classical monotone re-arrangement inequality, we derive sharp bounds on the counterfactual distributions and policy parameters of interest.

Item Type:Report or Paper (Working Paper)
Related URLs:
URLURL TypeDescription ItemPublished Article
Shum, Matthew0000-0002-6262-915X
Additional Information:We are grateful to Cheng Hsiao, Sergio Firpo, Marc Henry, Chuck Manski, Kevin Song, and Jeff Wooldridge for valuable comments and discussions. We thank SangMok 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 Microecononetrics (2012) for useful comments.
Group:Social Science Working Papers
Subject Keywords:Counterfactual distributions, treatment effects, partial identification
Series Name:Social Science Working Paper
Issue or Number:1377
Classification Code:JEL: C14, C31
Record Number:CaltechAUTHORS:20170726-154328187
Persistent URL:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:79456
Deposited By: Hanna Storlie
Deposited On:07 Aug 2017 21:55
Last Modified:03 Oct 2019 18:20

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