An introduction to matching methods for causal inference and their implementation in Stata

Barbara Sianesi

German Stata Users' Group Meetings 2010 from Stata Users Group

Abstract: Matching, especially in its propensity-score flavors, has become an extremely popular evaluation method. Matching is, in fact, the best-available method for selecting a matched (or reweighted) comparison group that looks like the treatment group of interest. In this talk, I will introduce matching methods within the general problem of causal inference, highlight their strengths and weaknesses, and offer a brief overview of different matching estimators. Using psmatch2, I will then step through a practical example in Stata that is based on real data. I will then show how to implement some of these estimators, as well as highlight a number of implementational issues.

Date: 2010-07-13
New Economics Papers: this item is included in nep-ltv
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Citations: View citations in EconPapers (4)

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http://fmwww.bc.edu/repec/dsug2010/sianesi.pdf (application/pdf)
http://fmwww.bc.edu/repec/dsug2010/sianesi_materials.zip (application/zip)

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Working Paper: An introduction to matching methods for causal inference and their implementation in Stata (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:boc:dsug10:02

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