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Bias-corrected matching estimators for average treatment effects. (English) Zbl 1214.62031
Summary: The authors [Econometrica 74, No. 1, 235–267 (2006; Zbl 1112.62042)] have shown that simple nearest-neighbor matching estimators include a conditional bias term that converges to zero at a rate that may be slower than $$N^{1/2}$$. As a result, matching estimators are not $$N^{1/2}$$-consistent in general. We propose a bias correction that renders matching estimators $$N^{1/2}$$-consistent and asymptotically normal. To demonstrate the methods proposed in this article, we apply them to the National Supported Work (NSW) data, originally analyzed by R. J. Lalonde [Am. Econ. Rev. 76, 604–620 (1986)]. We also carry out a small simulation study based on the NSW example. In this simulation study, a simple implementation of the bias-corrected matching estimator performs well compared to both simple matching estimators and to regression estimators in terms of bias, root-mean-squared-error, and coverage rates. Software to compute the estimators proposed in this article is available on the authors’ web pages (http://www.economics.harvard.edu/faculty/imbens/software.html) and documented by A. Abadie et al. [Stata J. 4, No. 3, 290–311 (2003)].

##### MSC:
 62G05 Nonparametric estimation 62G20 Asymptotic properties of nonparametric inference 65C05 Monte Carlo methods 91B40 Labor market, contracts (MSC2010) 62P20 Applications of statistics to economics
##### Keywords:
selection of observables; treatment effects; labor market
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