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A cautionary note on outlier robust estimation of threshold models

  • Paolo Giordani

    (University of New South Wales, Australia)

Chan and Cheung (1994) propose a GM approach to outlier robust estimation of threshold models. We show that their estimator can be inconsistent and extremely inefficient even when the model is correctly specified and the disturbances are normally distributed, and outline situations in which the problem is likely to be more severe. Copyright © 2006 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/for.972
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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 25 (2006)
Issue (Month): 1 ()
Pages: 37-47

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Handle: RePEc:jof:jforec:v:25:y:2006:i:1:p:37-47
DOI: 10.1002/for.972
Contact details of provider: Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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  1. van Dijk, Dick & Teräsvirta, Timo & Franses, Philip Hans, 2000. "Smooth Transition Autoregressive Models - A Survey of Recent Developments," SSE/EFI Working Paper Series in Economics and Finance 380, Stockholm School of Economics, revised 17 Jan 2001.
  2. van Dijk, D.J.C. & Franses, Ph.H.B.F. & Lucas, A., 1996. "Testing for Smooth Transition Nonlinearity in the Presence of Outliers," Econometric Institute Research Papers EI 9622-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  3. Kapetanios, George, 2000. "Small sample properties of the conditional least squares estimator in SETAR models," Economics Letters, Elsevier, vol. 69(3), pages 267-276, December.
  4. Balke, Nathan S & Fomby, Thomas B, 1997. "Threshold Cointegration," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 38(3), pages 627-45, August.
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