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

Marian Vavra
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Marian Vavra: Department of Economics, Mathematics & Statistics, Birkbeck

No 1206, Birkbeck Working Papers in Economics and Finance from Birkbeck, Department of Economics, Mathematics & Statistics

Abstract: 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.

Keywords: threshold autoregressive model; Monte Carlo method; bias; asymmetry (search for similar items in EconPapers)
JEL-codes: C15 C22 C46 (search for similar items in EconPapers)
Date: 2012-03
New Economics Papers: this item is included in nep-ecm and nep-ets
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https://eprints.bbk.ac.uk/id/eprint/5953 First version, 2012 (application/pdf)

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