Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference

38 Pages Posted: 9 Jan 2008

See all articles by Daniel E. Ho

Daniel E. Ho

Stanford Law School

Kosuke Imai

Princeton University - Department of Political Science

Gary King

Harvard University

Elizabeth A. Stuart

Johns Hopkins University - Bloomberg School of Public Health

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Abstract

The fast growing statistical literatures on matching methods in several disciplines offer the promise of causal inference without resort to the difficult-to-justify functional form assumptions inherent in commonly used parametric methods. However, these literatures also suffer from many diverse and conflicting approaches to estimation, uncertainty, theoretical analysis, and practical advice. In this paper, we propose a unified perspective on matching as a method of nonparametric preprocessing for improving parametric methods. This approach makes it possible for researchers to preprocess their data (such as with the easy-to-use matching software we offer with this paper) and then to apply whatever familiar statistical techniques they would have used anyway. Under our approach, instead of using matching to replace existing methods, we use it to make existing methods work better, such as by giving more accurate and considerably less model-dependent causal inferences.

Suggested Citation

Ho, Daniel E. and Imai, Kosuke and King, Gary and Stuart, Elizabeth A., Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference. Political Analysis, Vol. 15, pp. 199-236, 2007, Available at SSRN: https://ssrn.com/abstract=1081983

Daniel E. Ho (Contact Author)

Stanford Law School ( email )

559 Nathan Abbott Way
Stanford, CA 94305-8610
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HOME PAGE: http://dho.stanford.edu

Kosuke Imai

Princeton University - Department of Political Science ( email )

Corwin Hall
Princeton, NJ 08544-1012
United States

Gary King

Harvard University ( email )

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Institute for Quantitative Social Science
Cambridge, MA 02138
United States
617-500-7570 (Phone)

HOME PAGE: http://gking.harvard.edu

Elizabeth A. Stuart

Johns Hopkins University - Bloomberg School of Public Health ( email )

615 North Wolfe Street
Baltimore, MD 21205
United States

HOME PAGE: http://www.biostat.jhsph.edu/~estuart

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