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A DATA-DRIVEN NONPARAMETRIC SPECIFICATION TEST FOR DYNAMIC REGRESSION MODELS

Published online by Cambridge University Press:  23 May 2006

Alain Guay  and
Emmanuel Guerre
Alain Guay
Affiliation:
Université du Québec à Montréal
Emmanuel Guerre
Affiliation:
LSTA, Université Paris 6
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Abstract

The paper introduces a new nonparametric specification test for dynamic regression models. The test combines chi-square statistics based on Fourier series regression. A data-driven choice of the regression order, which uses the square root of the number of Fourier coefficients, is proposed. The benefits of the new test are (1) the selection procedure produces explicit and chi-square critical values that give a finite-sample size close to the nominal size; (2) the test is adaptive rate-optimal and detects local alternatives converging to the null with a rate that can be made arbitrarily close to the parametric rate. Simulation experiments illustrate the practical relevance of the new test.The first author acknowledges financial support from the Fonds Québécois de la Recherche sur la Société et la Culture (FQRSC). The second author acknowledges financial support from LSTA.

Information

Type
Research Article
Information
Econometric Theory , Volume 22 , Issue 4 , August 2006 , pp. 543 - 586
Copyright
© 2006 Cambridge University Press

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