Inference on the Cointegration Rank in Fractionally Integrated Processes

Joerg Breitung and Uwe Hassler
Authors registered in the RePEc Author Service: Jörg Breitung (breitung@statistik.uni-koeln.de) and Uwe Hassler

No 233, Computing in Economics and Finance 2001 from Society for Computational Economics

Abstract: For univariate time series we suggest a new variant of efficient score tests against fractional alternatives. This test has three important merits. First, by means of simulations we observe that it is superior in terms of size and power in some situations of practical interest. Second, it is easily understood and implemented as a slight modification of the Dickey-Fuller test, although our score test has a limiting normal distribution. Third and most important, our test generalizes to multivariate cointegration tests. Thus it allows to determine the cointegration rank of fractionally integrated time series. It does so by solving a generalized eigenvalue problem of the type proposed by Johansen (1988). However, the limiting distribution of the corresponding trace statistic is chi-squared, where the degrees of freedom depend only on the cointegration rank under the null hypothesis. The usefulness of the asymptotic theory for finite samples is established in a Monte Carlo experiment.

Keywords: Long memory; cointegration testing; trace statistic; limiting normality (search for similar items in EconPapers)
JEL-codes: C32 C51 (search for similar items in EconPapers)
Date: 2001-04-01
References: Add references at CitEc
Citations: View citations in EconPapers (3)

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

Related works:
Journal Article: Inference on the cointegration rank in fractionally integrated processes (2002)
Working Paper: Inference on the cointegration rank in fractionally integrated processes (2002)
Working Paper: Inference on the cointegration rank in fractionally integrated processes (2000)
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:sce:scecf1:233

Access Statistics for this paper

More papers in Computing in Economics and Finance 2001 from Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F. Baum (baum@bc.edu).