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Studies in Nonlinear Dynamics & Econometrics

Ed. by Mizrach, Bruce


IMPACT FACTOR 2017: 0.855

CiteScore 2017: 0.76

SCImago Journal Rank (SJR) 2017: 0.668
Source Normalized Impact per Paper (SNIP) 2017: 0.894

Mathematical Citation Quotient (MCQ) 2017: 0.02

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1558-3708
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Volume 12, Issue 1

Issues

Smooth Transition Autoregressive Models -- New Approaches to the Model Selection Problem

Dietmar G. Maringer / Mark Meyer
Published Online: 2008-03-14 | DOI: https://doi.org/10.2202/1558-3708.1469

It has been shown in the literature that the task of estimating the parameters of nonlinear models may be tackled with optimization heuristics. Thus, we attempt to carry these intuitions over to the estimation procedure of smooth transition autoregressive (STAR, Teräsvirta, 1994) models by introducing the following three stochastic optimization algorithms: Simulated Annealing, (Kirkpatrick, Gelatt, and Vecchi, 1983), Threshold Accepting (Dueck and Scheuer, 1990) and Differential Evolution (Storn and Price, 1995, 1997). Besides considering the performance of these heuristics in estimating STAR model parameters, our paper additionally picks up the problem of identifying redundant parameters which, according to our view, has not been addressed in a satisfactory way by now. The resulting findings of our simulation studies seem to argue for an implementation of heuristic approaches within the STAR modeling cycle. In particular for the case of STAR model specification, an application of these heuristics might offer valuable information to empirical researchers.

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Published Online: 2008-03-14


Citation Information: Studies in Nonlinear Dynamics & Econometrics, Volume 12, Issue 1, ISSN (Online) 1558-3708, DOI: https://doi.org/10.2202/1558-3708.1469.

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