An optimal test against a random walk component in a non-orthogonal unobserved components model
AbstractIn this paper we consider the problem of testing the null hypothesis that a series has a constant level (possibly as part of a more general deterministic mean) against the alternative that the level follows a random walk. This problem has previously been studied by, inter alia, Nyblom and Makelainen (1983) in the context of the orthogonal Gaussian random walk plus noise model. This model postulates that the noise component and the innovations to the random walk are uncorrelated. We generalize their work by deriving the locally best invariant test of a fixed level against a random walk level in the non-orthogonal case. Here the noise and random walk components are contemporaneously correlated with correlation coefficient rho. We demonstrate that the form of the optimal test in this setting is independent of rho; i.e. the test statistic previously derived for the case of rho=0 remains the locally optimal test for all rho. This is a very useful result: it states that the locally optimal test may be achieved without prior knowledge of rho. Moreover, we show that the limiting distribution of the resulting statistic under both the null and local alternatives does not depend on rho, behaving exactly as if rho=0. Finite sample simulations of these effects are provided to illustrate and generalizations to models with dependent errors are considered. Copyright Royal Economic Society, 2002
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Royal Economic Society in its journal The Econometrics Journal.
Volume (Year): 5 (2002)
Issue (Month): 2 (06)
Contact details of provider:
Postal: Office of the Secretary-General, School of Economics and Finance, University of St. Andrews, St. Andrews, Fife, KY16 9AL, UK
Phone: +44 1334 462479
Web page: http://www.res.org.uk/
More information through EDIRC
Other versions of this item:
- Bailey, R.W. & Taylor, A.M.R., 2000. "An Optimal Test against a Random Walk Component in a Non-Orthogonal Unobserved Components Model," Discussion Papers 00-09, Department of Economics, University of Birmingham.
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- James Morley & Irina B. Panovska & Tara M. Sinclair, 2013. "Testing Stationarity for Unobserved Components Models," Discussion Papers 2012-41A, School of Economics, The University of New South Wales.
- Busetti, Fabio & Harvey, Andrew, 2008.
"Testing For Trend,"
Cambridge University Press, vol. 24(01), pages 72-87, February.
- Ringlund, Guro Bornes & Rosendahl, Knut Einar & Skjerpen, Terje, 2008.
"Does oilrig activity react to oil price changes An empirical investigation,"
Elsevier, vol. 30(2), pages 371-396, March.
- Guro Børnes Ringlund & Knut Einar Rosendahl & Terje Skjerpen, 2004. "Does oilrig activity react to oil price changes? An empirical investigation," Discussion Papers 372, Research Department of Statistics Norway.
- James Morley & Tara M. Sinclair, 2005. "Testing for Stationarity and Cointegration in an Unobserved Components Framework," Computing in Economics and Finance 2005 451, Society for Computational Economics.
- James Morley & Irina Panovska & Tara M. Sinclair, 2008. "A Likelihood Ratio Test of Stationarity Based on a Correlated Unobserved Components Model," Working Papers 2008-011, The George Washington University, Department of Economics, Research Program on Forecasting, revised Sep 2011.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing) or (Christopher F. Baum).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.