Contemporaneous threshold autoregressive models: Estimation, testing and forecasting

Dueker, M.J. and Sola, Martin and Spagnolo, F. (2007) Contemporaneous threshold autoregressive models: Estimation, testing and forecasting. Journal of Econometrics 141 (2), 517 - 547. ISSN 0304-4076.

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Official URL: http://dx.doi.org/10.1016/j.jeconom.2006.10.022

Abstract

This paper proposes a contemporaneous smooth transition threshold autoregressive model (C-STAR) as a modification of the smooth transition threshold autoregressive model surveyed in Teräsvirta [1998. Modelling economic relationships with smooth transition regressions. In: Ullah, A., Giles, D.E.A. (Eds.), Handbook of Applied Economic Statistics. Marcel Dekker, New York, pp. 507–552.], in which the regime weights depend on the ex ante probability that a latent regime-specific variable will exceed a threshold value. We argue that the contemporaneous model is well suited to rational expectations applications (and pricing exercises), in that it does not require the initial regimes to be predetermined. We investigate the properties of the model and evaluate its finite-sample maximum likelihood performance. We also propose a method to determine the number of regimes based on a modified Hansen [1992. The likelihood ratio test under nonstandard conditions: testing the Markov switching model of GNP. Journal of Applied Econometrics 7, S61–S82.] procedure. Furthermore, we construct multiple-step ahead forecasts and evaluate the forecasting performance of the model. Finally, an empirical application of the short term interest rate yield is presented and discussed.

Metadata

Item Type:	Article
Keyword(s) / Subject(s):	Smooth transition threshold autoregressive, forecasting, nonlinear models
School:	Birkbeck Faculties and Schools > Faculty of Business and Law > Birkbeck Business School
Research Centres and Institutes:	Applied Macroeconomics, Birkbeck Centre for
Depositing User:	Administrator
Date Deposited:	11 Aug 2011 11:26
Last Modified:	02 Aug 2023 16:55
URI:	https://eprints.bbk.ac.uk/id/eprint/3930

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