Abstract
This paper addresses the choice of an optimal smoothing parameter for local polynomial matching estimators. In order to estimate the MSE of the matching estimator as a bandwidth selection criterion, the Double Smoothing approach (Mýller (1985), Hýrdle, Hall, and Marron (1992)) is applied. The proposed bandwidth selector exhibits a faster rate of convergence than cross-validation selectors for local polynomial regression estimators. A Monte Carlo study reveals that using the proposed algorithm can yield efficiency gains compared to the MISE based cross-validation procedure. Furthermore, the estimated MSE nicely approximates the true MSE of the matching estimator.
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