The Role of Ancillarity in Inference for Non-stationary Variables

Soren Johansen

Economic Journal, 1995, vol. 105, issue 429, 302-20

Abstract: Some examples of the regression method are compared with likelihood-based inference. It is shown that, although the asymptotic theory is distinctly different for ergodic and nonergodic processes, the likelihood methods lead to the result that asymptotic inference can be conducted in the same way for the two cases by appealing to classical conditioning arguments from statistics using the notion of S-ancillarity or strong exogeneity. It is pointed out that the Fisher information can be considered a measure of the conditional variance of the maximum likelihood estimator given the available information in the sample. Copyright 1995 by Royal Economic Society.

Date: 1995
References: Add references at CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://links.jstor.org/sici?sici=0013-0133%2819950 ... 0.CO%3B2-U&origin=bc full text (application/pdf)
Access to full text is restricted to JSTOR subscribers. See http://www.jstor.org for details.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ecj:econjl:v:105:y:1995:i:429:p:302-20

Ordering information: This journal article can be ordered from
http://www.blackwell ... al.asp?ref=0013-0133

Access Statistics for this article

Economic Journal is currently edited by Martin Cripps, Steve Machin, Woulter den Haan, Andrea Galeotti, Rachel Griffith and Frederic Vermeulen

More articles in Economic Journal from Royal Economic Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley-Blackwell Digital Licensing () and Christopher F. Baum ().