Distribution free goodness-of-fit tests for linear processes

Miguel Delgado (), Javier Hidalgo and Carlos Velasco

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: This article proposes a class of goodness-of-fit tests for the autocorrelation function of a time series process, including those exhibiting long-range dependence. Test statistics for composite hypotheses are functionals of a (approximated) martingale transformation of the Bartlett’s Tp-process with estimated parameters, which converges in distribution to the standard Brownian Motion under the null hypothesis. We discuss tests of different nature such as omnibus, directional and Portmanteau-type tests. A Monte Carlo study illustrates the performance of the different tests in practice.

Keywords: Nonparametric model checking; spectral distribution; linear processes; martingale decomposition; local alternatives; omnibus; smooth and directional tests; long-range alternatives (search for similar items in EconPapers)
JEL-codes: C14 C22 (search for similar items in EconPapers)
Pages: 49 pages
Date: 2005-01
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (30)

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http://eprints.lse.ac.uk/6840/ Open access version. (application/pdf)

Related works:
Working Paper: Distribution Free Goodness-of-Fit Tests for Linear Processes (2005)
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Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:6840

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