Two competitive models and their identification problem: The ESTAR and TSTAR model
AbstractDetermining 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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Bibliographic InfoPaper provided by Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät in its series Diskussionspapiere der Wirtschaftswissenschaftlichen Fakultät der Leibniz Universität Hannover with number dp-474.
Length: 36 pages
Date of creation: May 2011
Date of revision:
Nonlinearities; Smooth transition; Linearity testing; Unit root testing; Real exchange rates;
Find related papers by 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 &bull Diffusion Processes
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-05-30 (All new papers)
- NEP-ECM-2011-05-30 (Econometrics)
- NEP-ETS-2011-05-30 (Econometric Time Series)
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