Matching Methods in Practice: Three Examples

66 Pages Posted: 10 Mar 2014 Last revised: 14 Jan 2022

See all articles by Guido W. Imbens

Guido W. Imbens

Stanford Graduate School of Business

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Date Written: March 2014


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.

Suggested Citation

Imbens, Guido W., Matching Methods in Practice: Three Examples (March 2014). NBER Working Paper No. w19959, Available at SSRN:

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Stanford Graduate School of Business ( email )

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