The Likelihood Ratio Test under Nonstandard Conditions: Testing the Markov Switching Model of GNP
A theory of testing under non-standard conditions is developed. By viewing the likelihood as a function of the unknown parameters, empirical process theory enables us to bound the asymptotic distribution of standardized likelihood ratio statistics, even when conventional regularity conditions (such as unidentified nuisance parameters and identically zero scores) are violated. This testing methodology is applied.to the Markov switching model of GNP proposed by Hamilton (1989). The standardized likelihood ratio test is unable to reject the hypothesis of an AR(4) in favour of the Markov switching model. Instead, we find strong evidence for an alternative model. This model, like Hamilton's, is characterized by parameters which switch between states, but the states arrive independently over time, rather than following an unrestricted Markov process. The primary difference, however, is that the second autoregressive parameter, in addition to the intercept, switches between states. Copyright 1992 by John Wiley & Sons, Ltd.
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): 7 (1992)
Issue (Month): S (Suppl. Dec.)
|Contact details of provider:|| Web page: http://www.interscience.wiley.com/jpages/0883-7252/|
|Order Information:|| Web: http://www3.interscience.wiley.com/jcatalog/subscribe.jsp?issn=0883-7252 Email: |
When requesting a correction, please mention this item's handle: RePEc:jae:japmet:v:7:y:1992:i:s:p:s61-82. 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: (Wiley-Blackwell Digital Licensing)or (Christopher F. Baum)
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.