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A Simple Linear Time Series Model with Misleading Nonlinear Properties

Author

Listed:
  • 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.

Suggested Citation

  • Andersson, Michael K. & Eklund, Bruno & Lyhagen, Johan, 1999. "A Simple Linear Time Series Model with Misleading Nonlinear Properties," SSE/EFI Working Paper Series in Economics and Finance 300, Stockholm School of Economics.
    • Handle: RePEc:hhs:hastef:0300
    as

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    Citations

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    Cited by:

    1. Simone Alfarano & Thomas Lux, 2007. "A Minimal Noise Trader Model with Realistic Time Series Properties," Springer Books, in: Gilles Teyssière & Alan P. Kirman (ed.), Long Memory in Economics, pages 345-361, Springer.
    2. 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".
    3. 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.
    4. 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.
    5. 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.
    6. Lahiani, A. & Scaillet, O., 2009. "Testing for threshold effect in ARFIMA models: Application to US unemployment rate data," International Journal of Forecasting, Elsevier, vol. 25(2), pages 418-428.
    7. Kuswanto, Heri & Sibbertsen, Philipp, 2009. "Testing for Long Memory Against ESTAR Nonlinearities," Hannover Economic Papers (HEP) dp-427, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    8. Leipus, Remigijus & Viano, Marie-Claude, 2003. "Long memory and stochastic trend," Statistics & Probability Letters, Elsevier, vol. 61(2), pages 177-190, January.
    9. 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.
    10. 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.

    More about this item

    Keywords

    Fractional integration; Long memory; Smooth transition autoregression;
    All these keywords.

    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; Diffusion Processes

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