Hidalgo, Javier (2008) Specification testing for regression models with dependent data. Journal of Econometrics, 143 (1). pp. 143-165. ISSN 0304-4076
Full text not available from this repository.Abstract
We examine a consistent test for the correct specification of a regression function with dependent data. The test is based on the supremum of the difference between the parametric and nonparametric estimates of the regression model. Rather surprisingly, the behaviour of the test depends on whether the regressors are deterministic or stochastic. In the former situation, the normalization constants necessary to obtain the limiting Gumbel distribution are data dependent and difficult to estimate, so it may be difficult to obtain valid critical values, whereas, in the latter, the asymptotic distribution may not be even known. Because of that, under very mild regularity conditions, we describe a bootstrap analogue for the test, showing its asymptotic validity and finite sample behaviour in a small Monte-Carlo experiment.
Item Type: | Article |
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Official URL: | http://www.journals.elsevier.com/journal-of-econom... |
Additional Information: | © 2008 Elsevier |
Divisions: | Economics STICERD |
Subjects: | H Social Sciences > HB Economic Theory Q Science > QA Mathematics |
JEL classification: | C - Mathematical and Quantitative Methods > C2 - Econometric Methods: Single Equation Models; Single Variables |
Date Deposited: | 20 Apr 2011 10:20 |
Last Modified: | 11 Dec 2024 23:23 |
URI: | http://eprints.lse.ac.uk/id/eprint/35800 |
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