Evaluating Nonexperimental Estimators for Multiple Treatments: Evidence from Experimental Data

Carlos Flores () and Oscar Mitnik
Additional contact information
Carlos Flores: Department of Economics, University of Miami

No 2010-9, Working Papers from University of Miami, Department of Economics

Abstract: This paper assesses the e¤ectiveness of unconfoundedness-based estimators of mean e¤ects for multiple or multivalued treatments in eliminating biases arising from nonrandom treatment assignment. We evaluate these multiple treatment estimators by simultaneously equalizing average outcomes among several control groups from a randomized experiment. We study linear regression estimators as well as partial mean and weighting estimators based on the generalized propensity score (GPS). We also study the use of the GPS in assessing the comparability of individuals among the di¤erent treatment groups, and propose a strategy to determine the overlap or common support region that is less stringent than those previously used in the literature. Our results show that in the multiple treatment setting there may be treatment groups for which it is extremely di¢ cult to ?nd valid comparison groups, and that the GPS plays a signi?cant role in identifying those groups. In such situations, the estimators we consider perform poorly. However, their performance improves considerably once attention is restricted to those treatment groups with adequate overlap quality, with di¤erence-in-di¤erence estimators performing the best. Our results suggest that unconfoundedness-based estimators are a valuable econometric tool for evaluating multiple treatments, as long as the overlap quality is satisfactory.

Pages: 51 pages
Date: 2009-09
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Published

Downloads: (external link)
https://herbert.miami.edu/_assets/files/repec/wp-2010-9.pdf First version, 2009 (application/pdf)

Related works:
Working Paper: Evaluating Nonexperimental Estimators for Multiple Treatments: Evidence from Experimental Data (2009)
Working Paper: Evaluating Nonexperimental Estimators for Multiple Treatments: Evidence from Experimental Data (2009)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:mia:wpaper:2010-9

Access Statistics for this paper

More papers in Working Papers from University of Miami, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Daniela Valdivia ().