Bootstrap-based bandwidth choice for log-periodogram regression |
| |
Authors: | By Josu Arteche Jesus Orbe |
| |
Affiliation: | University of the Basque Country |
| |
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. |
| |
Keywords: | Long memory log-periodogram regression bootstrap bandwidth selection |
|