Regression-based cointegration estimators with applications
Provides a framework for understanding the relationships between alternative cointegrating estimators with special attention given to single equation procedures. The approach consists of augmenting the long-run model with general short-run dynamic specifications and identifying the specific assumptions implied by each of these estimators about the short-run dynamics. Understanding this hierarchical structure between estimators is important since it shows the conditions when consistent and asymptotically efficient parameter estimates may be obtained from standard econometric packages. Since the alternative estimators are shown to be nested in a general framework, this suggests that general-to-specific methodology may be adopted to test between these alternative specifications. To highlight the salient characteristics of the alternative estimators, the framework is related to two theoretical economic models: stock prices and money demand; and applied to the demand for imports and testing of the crowding out hypothesis.
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.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 22 (1995)
Issue (Month): 1 (January)
|Contact details of provider:|| Web page: http://www.emeraldinsight.com|
|Order Information:|| Postal: Emerald Group Publishing, Howard House, Wagon Lane, Bingley, BD16 1WA, UK|
Web: http://www.emeraldinsight.com/jes.htm Email:
When requesting a correction, please mention this item's handle: RePEc:eme:jespps:v:22:y:1995:i:1:p:3-22. 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: (Virginia Chapman)
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.