A Nonparametric Distribution-Free Test for Serial Independence of Errors

Zaichao Du and Juan Carlos Escanciano

Econometric Reviews, 2015, vol. 34, issue 6-10, 1011-1034

Abstract: In this article, we propose a test for the serial independence of unobservable errors in location-scale models. We consider a Hoeffding-Blum-Kiefer-Rosenblat type empirical process applied to residuals, and show that under certain conditions it converges weakly to the same limit as the process based on true errors. We then consider a generalized spectral test applied to estimated residuals, and get a test that is asymptotically distribution-free and powerful against any type of pairwise dependence at all lags. Some Monte Carlo simulations validate our theoretical findings.

Date: 2015
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DOI: 10.1080/07474938.2014.956616

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