Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published August 7, 2017 | Submitted
Report Open

Identifying Treatment Effects under Data Combination


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.

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.

Attached Files

Submitted - sswp1377.pdf


Files (156.6 kB)
Name Size Download all
156.6 kB Preview Download

Additional details

August 19, 2023
January 13, 2024