A Parametric Bootstrap Test for Cycles

Violetta Dalla and Javier Hidalgo

STICERD - Econometrics Paper Series from Suntory and Toyota International Centres for Economics and Related Disciplines, LSE

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 G(t), t ? [0; 1]. Because the covariance structure of G(t) is a complicated function of t and model dependent, to obtain the critical values (if possible) of maxt?[0;1] G(t) 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.

Keywords: Cyclical data; strong and weak dependence; spectral density functions; Whittle estimator; bootstrap algorithms (search for similar items in EconPapers)
JEL-codes: C15 C22 (search for similar items in EconPapers)
Date: 2005-02
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Citations: View citations in EconPapers (37)

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Persistent link: https://EconPapers.repec.org/RePEc:cep:stiecm:486

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