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A Data-Driven Nonparametric Specification Test For Dynamic Regression Models

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Author Info
Guay, Alain
Guerre, Emmanuel

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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 Qu b cois de la Recherche sur la Soci t et la Culture (FQRSC). The second author acknowledges financial support from LSTA.

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Publisher Info
Article provided by Cambridge University Press in its journal Econometric Theory.

Volume (Year): 22 (2006)
Issue (Month): 04 (August)
Pages: 543-586
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Handle: RePEc:cup:etheor:v:22:y:2006:i:04:p:543-586_06

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  1. Andrea Vaona, 2008. "The sensitivity of nonparametric misspecification tests to disturbance autocorrelation," Quaderni della facoltà di Scienze economiche dell'Università di Lugano 0803, Biblioteca universitaria di Lugano (University Library of Lugano). [Downloadable!]
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This page was last updated on 2009-11-24.

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