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American Economic Review Vol. 101 No. 3 2011

Flexible Estimation of Treatment Effect Parameters

Thomas MaCurdy1; Xiaohong Chen2; Han Hong1

1 Stanford University, 579 Serra Mall, Stanford, CA 94305. · 2 Yale University, 30 Hillhouse Ave, New Haven, CT 06520.

Abstract

A variety of identification strategies have a common cell structure, in which the observed heterogeneity of the regression defines a partition of the sample into cells. Typically in the presence of exogenous covariates that define the cell structure, identification assumptions are imposed conditional on each value of the covariate, or cell by cell. Treatment effects across cells are typically heterogeneous. Researchers might be interested in unconditional parameters which are the averaged treatment effects across the cells. Alternatively, treatment effects can be estimated more efficiently if researchers are willing to impose additional parametric and semiparametric structures on the heterogeneous treatment effects across cells.

DOI
10.1257/aer.101.3.544
Volume
101
Issue
3
Pages
544-551
Language
en
Sources
bibtex:phds-export.bib openalex crossref

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