Nonparametric/semiparametric estimation and testing of econometric models with data dependent smoothing parameters
We consider nonparametric/semiparametric estimation and testing of econometric models with data dependent smoothing parameters. Most of the existing works on asymptotic distributions of a nonparametric/semiparametric estimator or a test statistic are based on some deterministic smoothing parameters, while in practice it is important to use data-driven methods to select the smoothing parameters. In this paper we give a simple sufficient condition that can be used to establish the first order asymptotic equivalence of a nonparametric estimator or a test statistic with stochastic smoothing parameters to those using deterministic smoothing parameters. We also allow for general weakly dependent data.
Year of publication: |
2010
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Authors: | Li, Dong ; Li, Qi |
Published in: |
Journal of Econometrics. - Elsevier, ISSN 0304-4076. - Vol. 157.2010, 1, p. 179-190
|
Publisher: |
Elsevier |
Keywords: | Smoothing parameters Data-driven Cross-validation Asymptotic equivalence |
Saved in:
Online Resource
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