 A parametric bootstrap test for cyclesVioletta Dalla and Javier Hidalgo LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library 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(τ), τ ∈ [0; 1]. Because the covariance structure of G(τ) is a complicated function of τ and model dependent, to obtain the critical values (if possible) of maxτ∈[0;1] G(τ) 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) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:6829 Access Statistics for this paper More papers in LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library LSE Library Portugal Street London, WC2A 2HD, U.K.. Contact information at EDIRC. |
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