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Two competitive models and their identification problem: The ESTAR and TSTAR model


  • Heinen, Florian
  • Michael, Stefanie
  • Sibbertsen, Philipp


Determining good parameter estimates in ESTAR models is known to be diffcult. We show that the phenomena of getting strongly biased estimators is a consequence of the so-called identifcation 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 TSTAR model- which has similar properties as the ESTAR model but reduces the effects of the identifcation problem. We also derive a linearity and a unit root test for this model.

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  • Heinen, Florian & Michael, Stefanie & Sibbertsen, Philipp, 2011. "Two competitive models and their identification problem: The ESTAR and TSTAR model," Hannover Economic Papers (HEP) dp-474, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
  • Handle: RePEc:han:dpaper:dp-474

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    More about this item


    Nonlinearities; Smooth transition; Linearity testing; Unit root testing; Real exchange rates;

    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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