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The spectral representation of Markov switching ARMA models

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  • Pataracchia, Beatrice

Abstract

In this paper we propose a method to derive the spectral density function of Markov switching ARMA models. We apply the Riesz-Fischer theorem which defines the spectral representation as the Fourier transform of the autocovariance functions.

Suggested Citation

  • Pataracchia, Beatrice, 2011. "The spectral representation of Markov switching ARMA models," Economics Letters, Elsevier, vol. 112(1), pages 11-15, July.
  • Handle: RePEc:eee:ecolet:v:112:y:2011:i:1:p:11-15
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    References listed on IDEAS

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    Cited by:

    1. repec:ebl:ecbull:eb-17-00098 is not listed on IDEAS
    2. Beatrice PATARACCHIA, "undated". "Design-Limits in Regime-Switching cases," EcoMod2008 23800104, EcoMod.
    3. Chikashi Tsuji, 2014. "Did the Stock Market Regime Change after the Inauguration of the New Cabinet in Japan?," Business and Management Horizons, Macrothink Institute, vol. 2(1), pages 98-108, June.
    4. Cavicchioli, Maddalena, 2013. "Spectral density of Markov-switching VARMA models," Economics Letters, Elsevier, vol. 121(2), pages 218-220.

    More about this item

    Keywords

    Multivariate ARMA models Regime switching models Markov switching models Frequency domain;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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