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Analytical Derivatives for Markov Switching Models

Author

Listed:
  • Jeff Gable
  • Simon van Norden
  • Robert Vigfusson

Abstract

This paper derives analytical gradients for a broad class of regime- switching models with Markovian state-transition probabilities. Such models are usually estimated by maximum likelihood methods, which require the derivatives of the likelihood function with respect to the parameter vector. These gradients are usually calculated by means of numerical techniques. The paper shows that analytical gradients considerably speed up maximum-likelihood estimation with no loss in accuracy. A sample program listing is included.

Suggested Citation

  • Jeff Gable & Simon van Norden & Robert Vigfusson, 1995. "Analytical Derivatives for Markov Switching Models," GE, Growth, Math methods 9508001, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpge:9508001
    Note: 24 printed pages, compressed PostScript file. Other recent Bank of Canada working papers are listed on the last page of this report.
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    Citations

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    Cited by:

    1. Ryan Lemand, 2003. "The Contagion Effect Between the Volatilities of the NASDAQ-100 and the IT.CA :A Univariate and A Bivariate Switching Approach," Econometrics 0307002, University Library of Munich, Germany, revised 07 Dec 2020.
    2. Ryan Lemand, 2003. "New Technology Stock Market Indexes Contagion: A VAR-dccMVGARCH Approach," Econometrics 0307003, University Library of Munich, Germany, revised 07 Dec 2020.
    3. John Murray & Simon van Norden & Robert Vigfusson, 1996. "Excess Volatility and Speculative Bubbles in the Canadian Dollar: Real of Imagined?," Technical Reports 76, Bank of Canada.
    4. Simon van Norden & Robert Vigfusson, 1996. "Regime-Switching Models: A Guide to the Bank of Canada Gauss Procedures," Econometrics 9603004, University Library of Munich, Germany.
    5. Andrew P. Blake, 2004. "Analytic Derivatives for Linear Rational Expectations Models," Computational Economics, Springer;Society for Computational Economics, vol. 24(1), pages 77-96, August.
    6. Yang, Minxian, 2001. "Closed-form likelihood function of Markov-switching models," Economics Letters, Elsevier, vol. 70(3), pages 319-326, March.
    7. Maddalena Cavicchioli, 2021. "Statistical inference for mixture GARCH models with financial application," Computational Statistics, Springer, vol. 36(4), pages 2615-2642, December.
    8. Ryan Lemand, 2003. "Should Stock Market Indexes Time Varying Correlations Be Taken Into Account? A Conditional Variance Multivariate Approach," Econometrics 0307004, University Library of Munich, Germany, revised 07 Dec 2020.

    More about this item

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • D5 - Microeconomics - - General Equilibrium and Disequilibrium
    • D9 - Microeconomics - - Micro-Based Behavioral Economics

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