IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

Estimating Deterministic Trends in the Presence of Serially Correlated Errors

  • Eugene Canjels
  • Mark W. Watson

This paper studies the problems of estimation and inference in the linear trend model: yt=à+þt+ut, where ut follows an autoregressive process with largest root þ, and þ is the parameter of interest. We contrast asymptotic results for the cases þþþ

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.nber.org/papers/t0165.pdf
Download Restriction: no

Paper provided by National Bureau of Economic Research, Inc in its series NBER Technical Working Papers with number 0165.

as
in new window

Length:
Date of creation: Sep 1994
Date of revision:
Publication status: published as Canjels, Eugene and Mark W. Watson. "Estimating Deterministic Trends In The Presence Of Serially Correlated Errors," Review of Economics and Statistics, 1997, v79(2,May), 184-200.
Handle: RePEc:nbr:nberte:0165
Note: EFG
Contact details of provider: Postal: National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.
Phone: 617-868-3900
Web page: http://www.nber.orgEmail:


More information through EDIRC

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.:

as in new window
  1. Beach, Charles M & MacKinnon, James G, 1978. "A Maximum Likelihood Procedure for Regression with Autocorrelated Errors," Econometrica, Econometric Society, vol. 46(1), pages 51-58, January.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:nbr:nberte:0165. 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: ()

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.