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Testing for Smooth Transition Nonlinearity in the Presence of Outliers

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Author Info

  • van Dijk, D.J.C.
  • Franses, Ph.H.B.F.
  • Lucas, A.

Abstract

Regime-switching models, like the smooth transition autoregressive (STAR) model are typically applied to time series of moderate length. Hence, the nonlinear features which these models intend to describe may be reflected in only a few observations. Conversely, neglected outliers in a linear time series of moderate length may incorrectly suggest STAR type nonlinearity. In this paper we propose outlier robust tests for STAR type nonlinearity. These tests are designed such that they have a better level and power behavior than standard nonrobust tests in situations with outliers. We formally derive local and global robustness properties of the new tests. Extensive Monte Carlo simulations show the practical usefulness of the robust tests. An application to several quarterly industrial production indices illustrates that apparent nonlinearity in time series sometimes seems due to only a small number of outliers.

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Bibliographic Info

Paper provided by Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute in its series Econometric Institute Research Papers with number EI 9622-/A.

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Date of creation: 01 Jan 1996
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Handle: RePEc:ems:eureir:1382

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Related research

Keywords: nonlinearity; outliers; robust estimation;

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References

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  1. Terasvirta, T & Anderson, H M, 1992. "Characterizing Nonlinearities in Business Cycles Using Smooth Transition Autoregressive Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages S119-36, Suppl. De.
  2. Ritva LUUKKONEN & Timo TERASVIRTA, 1991. "Testing Linearity of Economic Time Series against Cyclical Asymmetry," Annales d'Economie et de Statistique, ENSAE, issue 20-21, pages 125-142.
  3. Nathan S. Balke & Thomas B. Fomby, 1991. "Large shocks, small shocks, and economic fluctuations: outliers in macroeconomic times series," Research Paper 9101, Federal Reserve Bank of Dallas.
  4. Franco Peracchi, 1987. "Robust M-Tests," UCLA Economics Working Papers 459, UCLA Department of Economics.
  5. Hoek, Henk & Lucas, Andre & van Dijk, Herman K., 1995. "Classical and Bayesian aspects of robust unit root inference," Journal of Econometrics, Elsevier, vol. 69(1), pages 27-59, September.
  6. Granger, Clive W. J. & Terasvirta, Timo, 1993. "Modelling Non-Linear Economic Relationships," OUP Catalogue, Oxford University Press, number 9780198773207, Octomber.
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