Functional-coefficient models under unit root behaviour

Ted Juhl

Econometrics Journal, 2005, vol. 8, issue 2, 197-213

Abstract: We analyze the statistical properties of non-parametrically estimated functions in a functional-coefficient model if the data have a unit root. We show that the estimated function converges at a faster rate than under the stationary case. However, the estimator has a mixed normal distribution so that point-wise confidence intervals are calculated using the usual normal distribution theory rather than a Dickey--Fuller distribution. The results are used to show how one can discriminate between a unit root process and a non-linear functional-coefficient process. We illustrate the procedure using U.S. unemployment and interest rate data. Copyright 2005 Royal Economic Society

Date: 2005
References: Add references at CitEc
Citations: View citations in EconPapers (20)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:ect:emjrnl:v:8:y:2005:i:2:p:197-213

Ordering information: This journal article can be ordered from
http://www.ectj.org

Access Statistics for this article

Econometrics Journal is currently edited by Richard J. Smith, Oliver Linton, Pierre Perron, Jaap Abbring and Marius Ooms

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