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A Note on the Finite Sample Properties of the CLS Method of TAR Models

  • Marian Vavra

    (Department of Economics, Mathematics & Statistics, Birkbeck)

In this paper we focus on the finite sample properties of the conditional least squares (CLS) method of threshold autoregressive (TAR) parameters under the following conditions: (a) non-Gaussian model innovations; (b) two types of asymmetry (i.e. deepness and steepness) captured by TAR models. It is clearly demonstrated that the finite sample properties of the CLS method of TAR parameters significantly differ depending on the type of asymmetry. The behavior of steepness-based models is very good compared to that obtained from deepness-based models. Therefore, extreme caution must be excercised to preliminary modelling steps, such as testing the type of asymmetry before estimating TAR models in practice. A mistake in this phase of modelling can, in turn, give rise to very problematic results.

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File URL: http://www.bbk.ac.uk/ems/research/wp/2012/PDFs/BWPEF1206.pdf
File Function: First version, 2012
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Paper provided by Birkbeck, Department of Economics, Mathematics & Statistics in its series Birkbeck Working Papers in Economics and Finance with number 1206.

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Date of creation: Mar 2012
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Handle: RePEc:bbk:bbkefp:1206
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  1. Maria-Teresa Perez & Ana-Maria Fuertes & Jerry Coakley, 2001. "Numerical Issues in Threshold Autoregressive Modelling of Time Series," Working Papers wp01-09, Warwick Business School, Finance Group.
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  9. Peel, D A & Speight, A E H, 1998. "Modelling Business Cycle Nonlinearity in Conditional Mean and Conditional Variance: Some International and Sectoral Evidence," Economica, London School of Economics and Political Science, vol. 65(258), pages 211-29, May.
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