Efficient Estimation of the Parameter Path in Unstable Time Series Models
Ulrich K. Müller and
Review of Economic Studies, 2010, vol. 77, issue 4, pages 1508-1539
The paper investigates inference in non-linear and non-Gaussian models with moderately time-varying parameters. We show that for many decision problems, the sample information about the parameter path can be summarized by an artificial linear and Gaussian model, at least asymptotically. The approximation allows for computationally convenient path estimators and parameter stability tests. Also, in contrast to standard Bayesian techniques, the artificial model can be robustified so that in misspecified models, decisions about the path of the (pseudo-true) parameter remain as good as in a corresponding correctly specified model. Copyright , Wiley-Blackwell.
References: Add references at CitEc
Citations View citations in EconPapers (4) Track citations by RSS feed
Downloads: (external link)
Access to full text is restricted to subscribers.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: http://EconPapers.repec.org/RePEc:oup:restud:v:77:y:2010:i:4:p:1508-1539
Access Statistics for this article
Review of Economic Studies is currently edited by Andrea Prat, Bruno Biais, Kjetil Storesletten and Enrique Sentana
More articles in Review of Economic Studies from Oxford University Press
Series data maintained by Oxford University Press ().