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The stochastic unit root model and fractional integration: An extension to the seasonal case

The stochastic unit root model and fractional integration: An extension to the seasonal case In a recent paper, Yoon (Working Paper, Department of Economics and Related Studies, University of York, 2003. Presented at the ESF‐EMM Second Annual Meeting, Rome, Italy, 2003) asserts that the stochastic unit root (STUR) model is closely related to long memory processes, and, in particular, that it is a special case of an I(d) process, with d = 1.5. In this paper we question this claim by using parametric and semiparametric techniques for modelling long memory. We extend the analysis by considering both non‐normality and seasonality, and shed light, theoretically and by means of Monte Carlo methods, on the relationship between the seasonal STUR and the seasonal I(d) models. The results show that methods that are specifically designed for testing I(d) statistical models are not appropriate for testing the STUR model. Moreover, they have in some cases very low power against STUR alternatives. Copyright © 2007 John Wiley & Sons, Ltd. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Applied Stochastic Models in Business and Industry Wiley

The stochastic unit root model and fractional integration: An extension to the seasonal case

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Publisher
Wiley
Copyright
Copyright © 2007 John Wiley & Sons, Ltd.
ISSN
1524-1904
eISSN
1526-4025
DOI
10.1002/asmb.683
Publisher site
See Article on Publisher Site

Abstract

In a recent paper, Yoon (Working Paper, Department of Economics and Related Studies, University of York, 2003. Presented at the ESF‐EMM Second Annual Meeting, Rome, Italy, 2003) asserts that the stochastic unit root (STUR) model is closely related to long memory processes, and, in particular, that it is a special case of an I(d) process, with d = 1.5. In this paper we question this claim by using parametric and semiparametric techniques for modelling long memory. We extend the analysis by considering both non‐normality and seasonality, and shed light, theoretically and by means of Monte Carlo methods, on the relationship between the seasonal STUR and the seasonal I(d) models. The results show that methods that are specifically designed for testing I(d) statistical models are not appropriate for testing the STUR model. Moreover, they have in some cases very low power against STUR alternatives. Copyright © 2007 John Wiley & Sons, Ltd.

Journal

Applied Stochastic Models in Business and IndustryWiley

Published: Sep 1, 2007

References