Testing Stationarity in Small and Medium-Sized Samples when Disturbances are Serially Correlated
AbstractIn this paper, we study the size distortions of the KPSS test for stationarity when serial correlation is present and samples are small and medium-sized. It is argued that two distinct sources of the size distortions can be identified. The first source is the finite-sample distribution of the long-run variance estimator used in the KPSS test, while the second source of the size distortions is the serial correlation not captured by the long-run variance estimator due to a too narrow choice of truncation lag parameter. When the relative importance of the two sources is studied, it is found that the size of the KPSS test can be reasonably well controlled if the finite-sample distribution of the KPSS test statistic, conditional on the time-series dimension and the truncation lag parameter, is used. Hence, finite-sample critical values, that can be applied in order to reduce the size distortions of the KPSS test, are supplied. When the power of the test is studied, it is found that the price paid for the increased size control is a lower raw power against a non-stationary alternative hypothesis.
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Bibliographic InfoPaper provided by Lund University, Department of Economics in its series Working Papers with number 2006:20.
Length: 39 pages
Date of creation: 30 Oct 2006
Date of revision: 09 Nov 2009
Publication status: Published as Jönsson, Kristian, 'Testing Stationarity in Small and Medium-Sized Samples when Disturbances are Serially Correlated' in Oxford Bulletin of Economics and Statistics, 2011, pages 669-690.
Contact details of provider:
Postal: Department of Economics, School of Economics and Management, Lund University, Box 7082, S-220 07 Lund,Sweden
Phone: +46 +46 222 0000
Fax: +46 +46 2224613
Web page: http://www.nek.lu.se/
More information through EDIRC
Stationarity Testing; Unit Root; Finite-Sample Inference; Long-Run Variance; Monte Carlo Simulation; Permanent Income Hypothesis; Private Consumption;
Other versions of this item:
- Kristian Jönsson, 2011. "Testing Stationarity in Small‐ and Medium‐Sized Samples when Disturbances are Serially Correlated," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(5), pages 669-690, October.
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- E21 - Macroeconomics and Monetary Economics - - Macroeconomics: Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
This paper has been announced in the following NEP Reports:
- NEP-ALL-2006-11-25 (All new papers)
- NEP-ECM-2006-11-25 (Econometrics)
- NEP-ETS-2006-11-25 (Econometric Time Series)
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