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Identification problems in ESTAR models and a new model

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

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.

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File URL: http://diskussionspapiere.wiwi.uni-hannover.de/pdf_bib/dp-444.pdf
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Paper provided by Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät in its series Hannover Economic Papers (HEP) with number dp-444.

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Length: 32 pages
Date of creation: Mar 2010
Date of revision:
Handle: RePEc:han:dpaper:dp-444
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  1. Robinson Kruse, 2011. "A new unit root test against ESTAR based on a class of modified statistics," Statistical Papers, Springer, vol. 52(1), pages 71-85, February.
  2. Delli Gatti Domenico & Gallegati Mauro & Mignacca Domenico, 1998. "Nonlinear Dynamics and European GNP Data," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 3(1), pages 1-19, April.
  3. n/a, 2001. "Balance of payments prospects in EMU," NIESR Discussion Papers 164, National Institute of Economic and Social Research.
  4. Rapach, David E. & Wohar, Mark E., 2006. "The out-of-sample forecasting performance of nonlinear models of real exchange rate behavior," International Journal of Forecasting, Elsevier, vol. 22(2), pages 341-361.
  5. Kapetanios, George & Shin, Yongcheol & Snell, Andy, 2003. "Testing for a unit root in the nonlinear STAR framework," Journal of Econometrics, Elsevier, vol. 112(2), pages 359-379, February.
  6. Hansen, Bruce E., 1992. "Convergence to Stochastic Integrals for Dependent Heterogeneous Processes," Econometric Theory, Cambridge University Press, vol. 8(04), pages 489-500, December.
  7. Taylor, Mark P & Peel, David A & Sarno, Lucio, 2001. "Nonlinear Mean-Reversion in Real Exchange Rates: Toward a Solution to the Purchasing Power Parity Puzzles," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 42(4), pages 1015-42, November.
  8. Öcal Nadir, 2000. "Nonlinear Models for U.K. Macroeconomic Time Series," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 4(3), pages 1-15, October.
  9. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.
  10. Jansen, Eilev S & Terasvirta, Timo, 1996. "Testing Parameter Constancy and Super Exogeneity in Econometric Equations," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 58(4), pages 735-63, November.
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