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Nonlinear Autoregressive Models and Long Memory

Author

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  • George Kapetanios

    (Queen Mary, University of London)

Abstract

This note shows that regime switching nonlinear autoregressive models widely used in the time series literature can exhibit arbitrary degrees of long memory via appropriate definition of the model regimes.

Suggested Citation

  • George Kapetanios, 2004. "Nonlinear Autoregressive Models and Long Memory," Working Papers 516, Queen Mary University of London, School of Economics and Finance.
    • Handle: RePEc:qmw:qmwecw:516
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    References listed on IDEAS

    as
    1. Diebold, Francis X. & Inoue, Atsushi, 2001. "Long memory and regime switching," Journal of Econometrics, Elsevier, vol. 105(1), pages 131-159, November.
    2. Michael Falk, 1989. "A note on uniform asymptotic normality of intermediate order statistics," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 41(1), pages 19-29, March.
    3. Davidson, James & Sibbertsen, Philipp, 2005. "Generating schemes for long memory processes: regimes, aggregation and linearity," Journal of Econometrics, Elsevier, vol. 128(2), pages 253-282, October.
    4. Tweedie, Richard L., 1975. "Sufficient conditions for ergodicity and recurrence of Markov chains on a general state space," Stochastic Processes and their Applications, Elsevier, vol. 3(4), pages 385-403, October.
    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.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Long memory; Nonlinearity;

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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