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Specification testing for regression models with dependent data

Hidalgo, Javier (2008) Specification testing for regression models with dependent data. Journal of Econometrics, 143 (1). pp. 143-165. ISSN 0304-4076

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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
Official URL:
Additional Information: © 2008 Elsevier
Library of Congress subject classification: H Social Sciences > HB Economic Theory
Q Science > QA Mathematics
Journal of Economic Literature Classification System: C - Mathematical and Quantitative Methods > C2 - Econometric Methods: Single Equation Models; Single Variables
Sets: Departments > Economics
Research centres and groups > Suntory and Toyota International Centres for Economics and Related Disciplines (STICERD)
Collections > Economists Online
Date Deposited: 20 Apr 2011 10:20

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