Matching Methods in Practice: Three Examples

67 Pages Posted: 29 Mar 2014

See all articles by Guido W. Imbens

Guido W. Imbens

Stanford Graduate School of Business

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There is a large theoretical literature on methods for estimating causal effects under unconfoundedness, exogeneity, or selection-on-observables type assumptions using matching or propensity score methods. Much of this literature is highly technical and has not made inroads into empirical practice where many researchers continue to use simple methods such as ordinary least squares regression even in settings where those methods do not have attractive properties. In this paper I discuss some of the lessons for practice from the theoretical literature, and provide detailed recommendations on what to do. I illustrate the recommendations with three detailed applications.

Keywords: matching methods, propensity score methods, causality, unconfoundedness, potential outcomes, selection on observables

JEL Classification: C01, C14, C21, C52

Suggested Citation

Imbens, Guido W., Matching Methods in Practice: Three Examples. IZA Discussion Paper No. 8049, Available at SSRN: or

Guido W. Imbens (Contact Author)

Stanford Graduate School of Business ( email )

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