Undersmoothing and Bias Corrected
Whitney K. Newey
Massachusetts Institute of Technology (MIT) - Department of Economics; National Bureau of Economic Research (NBER)
Harvard University - Harvard School of Public Health
MIT Department of Economics Working Paper No. 98-17
There are many important examples of -consistently estimable functionals that are interesting in econometrics, such as average derivatives and nonparametric consumer surplus. Corresponding estimators may require undersmoothing to achieve -consistency, due to first order bias in the expected influence function. We give a general bias correction that can be added to a plug-in estimator to remove the need for undersmoothing and improve its higher order properties. We also describe a bootstrap smoothing correction for the nonparametric estimator that achieves analogous results for the plug-in estimator and show that idempotent transformations of the empirical distribution need not require undersmoothing for -consistency. We find that this bias correction can lead to large efficiency improvements and lower sensitivity to bandwidth choice.
JEL Classification: C13, C14working papers series
Date posted: January 1, 1999
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