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Article
Bounding Treatment Effects: Stata Command for the Partial Identification of the Average Treatment Effect with Endogenous and Misreported Treatment Assignment
Stata Journal (2015)
  • Ian McCarthy, Emory University
  • Daniel L Millimet, Southern Methodist University
  • Manan Roy, University of North Carolina at Chapel Hill
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 Association107: 958–975), and Gundersen, Kreider, and Pepper (2012, Journal of Econometrics 166: 79–91) may be imposed. Imbens–Manski confidence intervals are provided.
Disciplines
Publication Date
2015
Citation Information
Ian McCarthy, Daniel L Millimet and Manan Roy. "Bounding Treatment Effects: Stata Command for the Partial Identification of the Average Treatment Effect with Endogenous and Misreported Treatment Assignment" Stata Journal (2015)
Available at: http://works.bepress.com/millimet/69/