Selection of the number of frequencies using bootstrap techniques in log-periodogram regression
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 and compare its performance with other existing techniques for optimal bandwidth selection in a mean squared error 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 analyzed in a long memory context Nile river annual minimum levels and the input gas rate series of Box and Jenkins.
|Date of creation:||Feb 2008|
|Date of revision:|
|Contact details of provider:|| Postal: Avda. Lehendakari, Aguirre, 83, 48015 Bilbao|
Phone: + 34 94 601 3740
Fax: + 34 94 601 4935
Web page: http://www.ea3.ehu.es
More information through EDIRC
|Order Information:|| Postal: Dpto. de Econometría y Estadística, Facultad de CC. Económicas y Empresariales, Universidad del País Vasco, Avda. Lehendakari Aguirre 83, 48015 Bilbao, Spain|
When requesting a correction, please mention this item's handle: RePEc:ehu:biltok:200801. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Alcira Macías)
If references are entirely missing, you can add them using this form.