Reducing size distortions of parametric stationarity tests
AbstractThe use of asymptotic critical values in stationarity tests against the alternative of a unit root process is known to lead to over-rejections in finite samples when the considered process is stationary but highly persistent. We claim that, in recent parametric tests, this is caused by estimation errors which result when the autoregressive parameters used to describe the short-run dynamics of the process are replaced by estimators. We suggest a modification that corrects for these errors. Simulation results show that the modified test works reasonably well when the persistence is moderate and there is no time trend in the model but it is less effective when the model contains a time trend. An empirical illustration with inflation rate data is provided. Copyright 2003 Blackwell Publishing Ltd.
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Bibliographic InfoArticle provided by Wiley Blackwell in its journal Journal of Time Series Analysis.
Volume (Year): 24 (2003)
Issue (Month): 4 (07)
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Web page: http://www.blackwellpublishing.com/journal.asp?ref=0143-9782
Other versions of this item:
- Lanne, Markku & Saikkonen, Pentti, 2000. "Reducing size distortions of parametric stationarity tests," SFB 373 Discussion Papers 2000,12, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
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