Matching estimators of average treatment effects: a review applied to the evaluation of health care programmes

Rodrigo Moreno-Serra (rodrigo.morenoserra@york.ac.uk)

Health, Econometrics and Data Group (HEDG) Working Papers from HEDG, c/o Department of Economics, University of York

Abstract: The general aim of this paper is to review how matching methods try to solve the evaluation problem – with a particular focus on propensity score matching – and their usefulness for the particular case of health programme evaluation. The “classical” case of matching estimation with a single discrete treatment is presented as a basis for discussing recent developments concerning the application of matching methods for jointly evaluating the impact of multiple treatments and for evaluating the impact of a continuous treatment. For each case, I review the treatment effects parameters of interest, the required identification assumptions, the definition of the main matching estimators and their main theoretical properties and practical features. The relevance of the “classical” matching estimators and of their extensions for the multiple and continuous treatments settings is illustrated using the example of a health programme implemented with different levels of population coverage in different geographic areas.

Keywords: Evaluation methods; treatment effects; matching; propensity score; programme evaluation. (search for similar items in EconPapers)
JEL-codes: C14 C21 C33 I10 (search for similar items in EconPapers)
Date: 2007-02
New Economics Papers: this item is included in nep-ecm, nep-hea and nep-ppm
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Citations: View citations in EconPapers (2)

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