On the failure of the bootstrap for matching estimators
By: Alberto Abadie, Guido W. Imbens
Contributors: Imbens, Guido W.; National Bureau of Economic Research
Series: NBER working paper series -- working paper . 325; Working paper series (National Bureau of Economic Research : Online) -- working paper no. . 325.
Publisher: National Bureau of Economic Research
Published: 2006
Place of publication: Cambridge, MA
Language: eng
Format: [electronic resource] /
Description: "Matching estimators are widely used for the evaluation of programs or treatments.  Often researchers use bootstrapping methods for inference.  However, no formal justification for the use of the bootstrap has been provided.  Here we show that the bootstrap is in general not valid, even in the simple case with a single continuous covariate when the estimator is root-N consistent and asymptotically normally distributed with zero asymptotic bias.  Due to the extreme non-smoothness of nearest neighbor matching, the standard conditions for the bootstrap are not satisfied, leading the bootstrap variance to diverge from the actual variance.  Simulations confirm the difference between actual and nominal coverage rates for bootstrap confidence intervals predicted by the theoretical calculations.  To our knowledge, this is the first example of a root-N consistent and asymptotically normal estimator for which the bootstrap fails to work"--National Bureau of Economic Research web site.
Notes: Title from PDF file as viewed on 7/19/2006.

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