Bootstrap‐based bandwidth choice for log‐periodogram regression

Josu Arteche and Jesus Orbe

Journal of Time Series Analysis, 2009, vol. 30, issue 6, 591-617

Abstract: Abstract. The choice of the bandwidth in the local log‐periodogram regression is of crucial importance for estimation of the memory parameter of a long memory time series. Different choices may give rise to completely different estimates, which may lead to contradictory conclusions, for example about the stationarity of the series. We propose here a data‐driven bandwidth selection strategy that is based on minimizing a bootstrap approximation of the mean‐squared error (MSE). Its behaviour is compared with other existing techniques for optimal bandwidth selection in a MSE sense, revealing its better performance in a wider class of models. The empirical applicability of the proposed strategy is shown with two examples: the widely analysed in a long memory context Nile river annual minimum levels and the input gas rate series of Box and Jenkins.

Date: 2009
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https://doi.org/10.1111/j.1467-9892.2009.00629.x

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Persistent link: https://EconPapers.repec.org/RePEc:bla:jtsera:v:30:y:2009:i:6:p:591-617

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