Log-periodogram estimation of the memory parameter of a long-memory process under trend
We show that log-periodogram-based estimators for the memory parameter in a stationary invertible long-memory process do not confuse small trends with long-range dependence. In the case of slowly decaying trends we show by Monte Carlo methods that the tapered periodogram is quite robust against these trends and reduces the bias obtained when employing the standard log-periodogram estimator. Thus, comparing the tapered and the non-tapered estimator gives a tool at hand for distinguishing slowly decaying trends and long-range dependence.
Volume (Year): 61 (2003)
Issue (Month): 3 (February)
|Contact details of provider:|| Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description|
|Order Information:|| Postal: http://www.elsevier.com/wps/find/supportfaq.cws_home/regional|
References listed on IDEAS
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.:
- Velasco, Carlos, 1999. "Non-stationary log-periodogram regression," Journal of Econometrics, Elsevier, vol. 91(2), pages 325-371, August.
- Philipp Sibbertsen, 2004.
"Long memory versus structural breaks: An overview,"
Springer, vol. 45(4), pages 465-515, October.
When requesting a correction, please mention this item's handle: RePEc:eee:stapro:v:61:y:2003:i:3:p:261-268. See general information about how to correct material in RePEc.
If references are entirely missing, you can add them using this form.