Sieve Nonparametric Likelihood Methods for Unit Root Tests

Francesco Bravo

Discussion Papers from Department of Economics, University of York

Abstract: This paper develops a new test for a unit root in autoregressive models with serially correlated errors. The test is based on the ``empirical'' Cressie-Read statistic and uses a sieve approximation to eliminate the bias in the asymptotic distribution of the test due to presence of serial correlation. The paper derives the asymptotic distributions of the sieve empirical Cressie-Read statistic under the null hypothesis of a unit root and under a local-to-unity alternative hypothesis. The paper uses a Monte Carlo study to assess the finite sample properties of two well-known members of the proposed test statistic: the empirical likelihood ratio and the Kullback-Liebler distance statistic. The results of the simulations seem to suggest that these two statistics have, in general, similar size and in most cases better power properties than those of standard Augmented Dickey-Fuller tests of a unit root. The paper also analyses the finite sample properties of a sieve bootstrap version of the (square of) the standard Augmented Dickey-Fuller test for a unit root. The results of the simulations seem to indicate that the bootstrap does solve almost completely the size distortion problem, yet at the same time produces a test statistic that has considerably less power than either that of the empirical likelihood or of the Kullback-Liebler distance statistic.

Keywords: Autogregressive approximation; bootstrap; empirical Cressie-Read statistic; generalized empirical likelihood; linear process; unit root test. (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm and nep-ets
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.york.ac.uk/media/economics/documents/discussionpapers/2005/0533.pdf Main text (application/pdf)

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:yor:yorken:05/33

Access Statistics for this paper

More papers in Discussion Papers from Department of Economics, University of York Department of Economics and Related Studies, University of York, York, YO10 5DD, United Kingdom. Contact information at EDIRC.
Bibliographic data for series maintained by Paul Hodgson ().