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Is it possible to discriminate between different switching regressions models? An empirical investigation

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Author Info
Lanouar Charfeddine () (OEP - Université de Marne-la-Vallée)
Dominique Guegan () (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I, EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris)

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Abstract

In this paper we study, using the sup LR test, the possibility of discrimination between two classes of models: the Markov switching models of Hamilton (1989) and the Threshold Auto-Regressive Models (TAR) of Lim and Tong (1980). This work is motivated by the fact that generally practicians use, in applications, switching models without any statistical justification. Using experiment simulations, we show that it is very difficult to discriminate between the MSAR and the SETAR models specially using large samples. This means that when the null hypothesis is rejected, it appears that different switching models are significant. Moreover, the results show that the power of the sup LR test is sensitive to the mean, the noise variance and the delay parameter. Then, we apply this methodology to two time series: the US GNP growth rate and the US/UK exchange rate. We shall retain retain a Markov switching process for the US GNP growth rate and the US/UK exchange rate (monthly data). For the US/UK exchange rate (quarterly data), we accept the null hypothesis of a random walk.

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Paper provided by HAL in its series Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) with number halshs-00368358_v1.

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Date of creation: 2008
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Publication status: Published, Euro-Mediterranean Economics and Finance Review, 2008, 3, 4, 54-75
Handle: RePEc:hal:cesptp:halshs-00368358_v1

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Keywords: Switching Models; Sup LR test; Empirical power; Exchange rate;

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  5. Hansen, Bruce E, 1992. "The Likelihood Ratio Test under Nonstandard Conditions: Testing the Markov Switching Model of GNP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages S61-82, Suppl. De. [Downloadable!] (restricted)
  6. Hansen, Bruce E, 1996. "Inference When a Nuisance Parameter Is Not Identified under the Null Hypothesis," Econometrica, Econometric Society, vol. 64(2), pages 413-30, March. [Downloadable!] (restricted)
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  7. Tommaso Proietti, 1998. "Characterizing Asymmetries in Business Cycles Using Smooth-Transition Structural Time-Series Models," Studies in Nonlinear Dynamics & Econometrics, Berkeley Electronic Press, vol. 3(3). [Downloadable!]
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  9. Bruce E. Hansen, 1997. "Inference in TAR Models," Studies in Nonlinear Dynamics & Econometrics, Berkeley Electronic Press, vol. 2(1). [Downloadable!]
  10. Carrasco, Marine, 2002. "Misspecified Structural Change, Threshold, and Markov-switching models," Journal of Econometrics, Elsevier, vol. 109(2), pages 239-273, August. [Downloadable!] (restricted)
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  12. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70. [Downloadable!] (restricted)
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  14. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-56, July. [Downloadable!] (restricted)
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