Title: Structural Equations, Treatment Effects, and Econometric Policy Evaluation1
Abstract: EconometricaVolume 73, Issue 3 p. 669-738 Structural Equations, Treatment Effects, and Econometric Policy Evaluation† James J. Heckman, James J. Heckman 1Dept. of Economics, University of Chicago, 1126 E. 59th Street, Chicago, IL 60637, U.S.A.; [email protected]Search for more papers by this authorEdward Vytlacil, Edward Vytlacil 2 Dept. of Economics, Stanford University, 579 Serra Mall, Palo Alto, CA 94305, U.S.A.; [email protected]Search for more papers by this author James J. Heckman, James J. Heckman 1Dept. of Economics, University of Chicago, 1126 E. 59th Street, Chicago, IL 60637, U.S.A.; [email protected]Search for more papers by this authorEdward Vytlacil, Edward Vytlacil 2 Dept. of Economics, Stanford University, 579 Serra Mall, Palo Alto, CA 94305, U.S.A.; [email protected]Search for more papers by this author First published: 18 April 2005 https://doi.org/10.1111/j.1468-0262.2005.00594.xCitations: 671Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Abstract This paper uses the marginal treatment effect (MTE) to unify the nonparametric literature on treatment effects with the econometric literature on structural estimation using a nonparametric analog of a policy invariant parameter; to generate a variety of treatment effects from a common semiparametric functional form; to organize the literature on alternative estimators; and to explore what policy questions commonly used estimators in the treatment effect literature answer. A fundamental asymmetry intrinsic to the method of instrumental variables (IV) is noted. Recent advances in IV estimation allow for heterogeneity in responses but not in choices, and the method breaks down when both choice and response equations are heterogeneous in a general way. REFERENCES Ahn, H., and J. L. 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