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A Simple Linear Time Series Model with Misleading Nonlinear Properties

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Author Info

  • Andersson, Michael K.

    (Dept. of Economic Statistics, Stockholm School of Economics)

  • Eklund, Bruno

    ()
    (Dept. of Economic Statistics, Stockholm School of Economics)

  • Lyhagen, Johan

    ()
    (Dept. of Economic Statistics, Stockholm School of Economics)

Abstract

This paper demonstrates that long memory leads to spurious rejection of the linearity hypothesis, when a STAR specification constitutes the alternative.

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Bibliographic Info

Paper provided by Stockholm School of Economics in its series Working Paper Series in Economics and Finance with number 300.

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Length: 5 pages
Date of creation: 09 Feb 1999
Date of revision:
Publication status: Published in Economics Letters, 1999, pages 281-284.
Handle: RePEc:hhs:hastef:0300

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Postal: The Economic Research Institute, Stockholm School of Economics, P.O. Box 6501, 113 83 Stockholm, Sweden
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Web page: http://www.hhs.se/
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Related research

Keywords: Fractional integration; Long memory; Smooth transition autoregression;

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Cited by:
  1. Sang-Kuck Chung, 2006. "The out-of-sample forecasts of nonlinear long-memory models of the real exchange rate," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 11(4), pages 355-370.
  2. Amine LAHIANI & Olivier SCAILLET, . "Testing for threshold effect in ARFIMA models: Application to US unemployment rate data," Swiss Finance Institute Research Paper Series 08-42, Swiss Finance Institute.
  3. Alfarano, Simone & Lux, Thomas, 2006. "A minimal noise trader model with realistic time series properties," Economics Working Papers 2006,11, Christian-Albrechts-University of Kiel, Department of Economics.
  4. Silvestro Di Sanzo, 2007. "Forecasting Time Series with Long Memory and Level Shifts, A Bayesian Approach," Working Papers 2007_03, Department of Economics, University of Venice "Ca' Foscari".
  5. Alfarano, Simone & Lux, Thomas, 2007. "A Noise Trader Model As A Generator Of Apparent Financial Power Laws And Long Memory," Macroeconomic Dynamics, Cambridge University Press, vol. 11(S1), pages 80-101, November.
  6. Leipus, Remigijus & Viano, Marie-Claude, 2003. "Long memory and stochastic trend," Statistics & Probability Letters, Elsevier, vol. 61(2), pages 177-190, January.
  7. Y. Malevergne & V. F. Pisarenko & D. Sornette, 2003. "Empirical Distributions of Log-Returns: between the Stretched Exponential and the Power Law?," Papers physics/0305089, arXiv.org.
  8. Kyrtsou, Catherine & Terraza, Michel, 2002. "Stochastic chaos or ARCH effects in stock series?: A comparative study," International Review of Financial Analysis, Elsevier, vol. 11(4), pages 407-431.
  9. Kuswanto, Heri & Sibbertsen, Philipp, 2009. "Testing for Long Memory Against ESTAR Nonlinearities," Diskussionspapiere der Wirtschaftswissenschaftlichen Fakultät der Leibniz Universität Hannover dp-427, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
  10. van Dijk, Dick & Franses, Philip Hans & Paap, Richard, 2002. "A nonlinear long memory model, with an application to US unemployment," Journal of Econometrics, Elsevier, vol. 110(2), pages 135-165, October.

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