Filtered Log-periodogram Regression of long memory processes
Filtered log-periodogram regression estimation of the fractional differencing parameter d is considered. Asymptotic properties are derived and the effect of filtering on ˆ d is investigated. It is shown that the estimator by Geweke and Porter-Hudak (1983) can be improved significantly using a simple family of filters. The essential improvement is based on a binary decision that is asymptotically correct with probability one. The idea is closely related to the well known technique of pre-whitening.
|Date of creation:||01 Nov 2008|
|Date of revision:|
|Contact details of provider:|| Postal: Fach D 147, D-78457 Konstanz|
Web page: http://cofe.uni-konstanz.de
More information through EDIRC
|Order Information:|| Web: http://cofe.uni-konstanz.de Email: |
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Katsumi Shimotsu & Peter C.B. Phillips, 2000. "Pooled Log Periodogram Regression," Cowles Foundation Discussion Papers 1267, Cowles Foundation for Research in Economics, Yale University.
- Velasco, Carlos, 1999.
"Non-stationary log-periodogram regression,"
Journal of Econometrics,
Elsevier, vol. 91(2), pages 325-371, August.
- Velasco, Carlos, 1998. "Non-stationary log-periodogram regression," DES - Working Papers. Statistics and Econometrics. WS 4554, Universidad Carlos III de Madrid. Departamento de Estadística.
When requesting a correction, please mention this item's handle: RePEc:knz:cofedp:0810. 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: (Ingmar Nolte)
If references are entirely missing, you can add them using this form.