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The Stata Journal
Volume 15 Number 2: pp. 411-436

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Bounding treatment effects: A command for the partial identification of the average treatment effect with endogenous and misreported treatment assignment

Ian McCarthy
Emory University
Atlanta, GA
Daniel L. Millimet
Southern Methodist University
Dallas, TX
and IZA
Bonn, Germany
Manan Roy
University of North Carolina
Chapel Hill, NC
Abstract.  We present a new command, tebounds, that implements a variety of techniques to bound the average treatment effect of a binary treatment on a binary outcome in light of endogenous and misreported treatment assignment. To tighten the worst case bounds, the monotone treatment selection, monotone treatment response, and monotone instrumental-variable assumptions of Manski and Pepper (2000, Econometrica 68: 997–1010), Kreider and Pepper (2007, Journal of the American Statistical Association 102: 432–441), Kreider et al. (2012, Journal of the American Statistical Association 107: 958–975), and Gundersen, Kreider, and Pepper (2012, Journal of Econometrics 166: 79–91) may be imposed. Imbens–Manski confidence intervals are provided.
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