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Identification problems in ESTAR models and a new model

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  • Donauer, Stefanie
  • Heinen, Florian
  • Sibbertsen, Philipp

Abstract

In ESTAR models it is usually difficult to determine parameter estimates, as it can be observed in the literature. We show that the phenomena of getting strongly biased estimators is a consequence of the so-called identification problem, the problem of properly distinguishing the transition function in relation to extreme parameter combinations. This happens in particular for either very small or very large values of the error term variance. Furthermore, we introduce a new alternative model - the T-STAR model - which has similar properties as the ESTAR model but reduces the effects of the identification problem. We also derive a linearity and a unit root test for this model.

Suggested Citation

  • Donauer, Stefanie & Heinen, Florian & Sibbertsen, Philipp, 2010. "Identification problems in ESTAR models and a new model," Hannover Economic Papers (HEP) dp-444, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    • Handle: RePEc:han:dpaper:dp-444
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    References listed on IDEAS

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    Cited by:

    1. Addo, Peter Martey & Billio, Monica & Guégan, Dominique, 2014. "The univariate MT-STAR model and a new linearity and unit root test procedure," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 4-19.
    2. Mario Cerrato & Christian De Peretti & Nick Sarantis, 2007. "A nonlinear panel unit root test under cross section dependence," Documents de recherche 07-12, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.
    3. Peter Martey Addo & Monica Billio & Dominique Guegan, 2011. "A test for a new modelling : The Univariate MT-STAR Model," Post-Print halshs-00659158, HAL.

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    More about this item

    Keywords

    Nonlinearities; Smooth transition; Linearity testing; Unit root testing; Real exchange rates;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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