Tests of the Seasonal Unit Root Hypothesis Against Heteroscedastic Seasonal Integration
AbstractThis paper considers the problem of testing for a nonstochastic seasonal unit root in a seasonally observed time-series process against the alternative of a randomized seasonel root with mean unity; that is, the process displays heteroscedastic seasonal integration.
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Bibliographic InfoPaper provided by Department of Economics, University of Birmingham in its series Discussion Papers with number 99-13.
Length: 20 pages
Date of creation: 1999
Date of revision:
UNIT ROOTS ; TESTS;
Other versions of this item:
- Taylor, A M Robert & Smith, Richard J, 2001. "Tests of the Seasonal Unit-Root Hypothesis against Heteroscedastic Seasonal Integration," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(2), pages 192-207, April.
- C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
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- Abadir, Karim M. & Distaso, Walter, 2007.
"Testing joint hypotheses when one of the alternatives is one-sided,"
Journal of Econometrics,
Elsevier, vol. 140(2), pages 695-718, October.
- K Abadir & W Distaso, . "Testing joint hypotheses when one of the alternatives is one-sided," Discussion Papers 05/13, Department of Economics, University of York.
- Fong, Pak Wing & Li, Wai Keung, 2003. "On time series with randomized unit root and randomized seasonal unit root," Computational Statistics & Data Analysis, Elsevier, vol. 43(3), pages 369-395, July.
- Luis Gil-Alana, 2010. "A seasonal fractional multivariate model. A testing procedure and impulse responses for the analysis of GDP and unemployment dynamics," Empirical Economics, Springer, vol. 38(2), pages 471-501, April.
- Fong, P.W. & Li, W.K. & An, Hong-Zhi, 2006. "A simple multivariate ARCH model specified by random coefficients," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 1779-1802, December.
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