Incorporating lag order selection uncertainty in parameter inference for AR models
Parameter inference on autoregressive models is usually carried out conditionally on a previously selected lag order. In the majority of cases the lag order selection is carried out using information criteria and in particular the Akaike (1973), Schwarz (1978) or Hannan and Quin (1979) criteria. It is well known that the latter two criteria are consistent in lag order selection in the sense of of picking the true order of the system with probability one asymptotically. On the other hand, Akaike's criterion is known to overestimate the lag order in this sense. In this note we discuss the asymptotic distribution, of the parameter estimates without conditioning on the lag order selected.
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
|Date of creation:||May 2000|
|Date of revision:|
|Contact details of provider:|| Postal: |
Web page: http://niesr.ac.uk
When requesting a correction, please mention this item's handle: RePEc:nsr:niesrd:175. 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: (Communications Manager)
If references are entirely missing, you can add them using this form.