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Consistent bootstrap tests of parametric regression functions

Title
Consistent bootstrap tests of parametric regression functions
Authors
Whang Y.-J.
Ewha Authors
황윤재
Issue Date
2000
Journal Title
Journal of Econometrics
ISSN
0304-4076JCR Link
Citation
vol. 98, no. 1, pp. 27 - 46
Indexed
SCIE; SSCI; SCOPUS WOS scopus
Abstract
This paper introduces specification tests of parametric mean-regression models. The null hypothesis of interest is that the parametric regression function is correctly specified. The proposed tests are generalizations of the Kolmogorov-Smirnov and Cramer-von Mises tests to the regression framework. They are consistent against all alternatives to the null hypothesis, powerful against 1/√n local alternatives, not dependent on any smoothing parameters and simple to compute. A wild-bootstrap procedure is suggested to obtain critical values for the tests and is justified asymptotically. A small-scale Monte Carlo experiment shows that our tests (especially Cramer-von Mises test) have outstanding small sample performance compared to some of the existing tests. © 2000 Published by Elsevier Science S.A. All rights reserved.
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사회과학대학 > 경제학전공 > Journal papers
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