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A simple consistent bootstrap test for a parametric regression function

delete1998-11-01
delete207
PRE
AI
Q
Q. Li
S
Suojin Wang
DOI：10.1016/S0304-4076(98)00011-6delete
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Abstract

Abstract

En 中文
A simple consistent test is considered and a bootstrap method is proposed for testing a parametric regression functional form. It is shown that the bootstrap method gives a more accurate approximation to the null distribution of the test than the asymptotic normal theory result. We also propose a consistent test for testing a parametric partially linear model versus a semiparametric partially linear alternative. Monte Carlo simulations suggest that the bootstrap test performs well based on 'wild bootstrap' critical values. (C) 1998 Elsevier Science S.A. All rights reserved.
Keywords:
MODEL-SPECIFICATION TESTS
CONDITIONAL MOMENT TESTS
PARTLY LINEAR-MODEL
GOODNESS-OF-FIT
NONPARAMETRIC REGRESSION
EDGEWORTH EXPANSION
FORM
SELECTION
CHECKING
SERIES
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Journal

Journal of Econometrics cover
Journal of Econometrics
IF:
4
Papers:
5.2K
Citations:
3.0W

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