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A parametric bootstrap test for cycles

By Violetta Dalla and Javier Hidalgo

Abstract

The paper proposes a simple test for the hypothesis of strong cycles and as a by-product a test for weak dependence for linear processes. We show that the limit distribution of the test is the maximum of a (semi) Gaussian process , τ[0,1]. Because the covariance structure of is a complicated function of τ and model dependent, to obtain the critical values (if possible) of may be difficult. For this reason, we propose a bootstrap scheme in the frequency domain to circumvent the problem of obtaining (asymptotically) valid critical values. The proposed bootstrap can be regarded as an alternative procedure to existing bootstrap methods in the time domain such as the residual-based bootstrap. Finally, we illustrate the performance of the bootstrap test by a small Monte-Carlo experiment and an empirical example

Topics: HB Economic Theory, QA Mathematics
Publisher: Elsevier
Year: 2005
DOI identifier: 10.1016/j.jeconom.2004.09.008
OAI identifier: oai:eprints.lse.ac.uk:35776
Provided by: LSE Research Online
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