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Model Averaging Over Nonparametric Estimators

Daniel Henderson () and Christopher Parmeter

A chapter in Essays in Honor of Aman Ullah, 2016, vol. 36, pp 539-560 from Emerald Publishing Ltd

Abstract: Abstract It is known that model averaging estimators are useful when there is uncertainty governing which covariates should enter the model. We argue that in applied research there is also uncertainty as to which method one should deploy, prompting model averaging over user-defined choices. Specifically, we propose, and detail, a nonparametric regression estimator averaged over choice of kernel, bandwidth selection mechanism and local-polynomial order. Simulations and an empirical application are provided to highlight the potential benefits of the method.

Keywords: Cross-validation; kernel; local-polynomial; model averaging; C13; C14; C52 (search for similar items in EconPapers)
Date: 2016
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