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MSVARlib: a new Gauss library to estimate multivariate Hidden Markov Models

Author

Listed:
  • Benoit Bellone

    (Direction de la Prévision et de l'analyse économique)

Abstract

This paper introduces a new open source Gauss library to estimate Multivariate Hidden Markov Models (HMM) in their simpler specification. These new programs are based upon the works of Hamilton (1994) and Krolzig (1998) and allow assessment of models with 2, 3 or 4 states through classical optimization of the maximum likelihood method. The modular architecture of the program is presented in a first part. It has been designed to allow new improvements (generalized non linear MS models or enhancement to a Bayesian framework). A second part, gives some illustration through a three state model based on the American Industrial production and a new stochastic coincident indicator of a recession for the US economy, following the papers of Ferrara (2003), Bellone and Saint-Martin (2003) and Bellone (2004).

Suggested Citation

  • Benoit Bellone, 2004. "MSVARlib: a new Gauss library to estimate multivariate Hidden Markov Models," Econometrics 0406004, EconWPA.
  • Handle: RePEc:wpa:wuwpem:0406004
    Note: Type of Document - pdf; pages: 21
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    References listed on IDEAS

    as
    1. Mike Artis & Hans-Martin Krolzig & Juan Toro, 2004. "The European business cycle," Oxford Economic Papers, Oxford University Press, vol. 56(1), pages 1-44, January.
    2. Benoit Bellone, 2004. "Une lecture probabiliste du cycle d’affaires américain," Econometrics 0407002, EconWPA, revised 28 Mar 2005.
    3. Nicolas Chopin, 2001. "Sequential Inference and State Number Determination for Discrete State-Space Models through Particle Filtering," Working Papers 2001-34, Center for Research in Economics and Statistics.
    4. Albert, James H & Chib, Siddhartha, 1993. "Bayes Inference via Gibbs Sampling of Autoregressive Time Series Subject to Markov Mean and Variance Shifts," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(1), pages 1-15, January.
    5. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    6. Marcelle Chauvet & Jeremy M. Piger, 2003. "Identifying business cycle turning points in real time," Review, Federal Reserve Bank of St. Louis, issue Mar, pages 47-61.
    7. Anas, Jacques & Ferrara, Laurent, 2002. "Un indicateur d'entrée et sortie de récession: application aux Etats-Unis
      [A start-end recession index: Application for United-States]
      ," MPRA Paper 4043, University Library of Munich, Germany.
    8. Benoit Bellone & David Saint-Martin, 2004. "Detecting Turning Points with Many Predictors through Hidden Markov Models," Econometrics 0407001, EconWPA.
    9. Eva Andersson & David Bock & Marianne Frisén, 2004. "Detection of Turning Points in Business Cycles," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2004(1), pages 93-108.
    10. Ferrara, Laurent, 2003. "A three-regime real-time indicator for the US economy," Economics Letters, Elsevier, vol. 81(3), pages 373-378, December.
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    Citations

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    Cited by:

    1. Benoit Bellone, 2005. "Classical Estimation of Multivariate Markov-Switching Models using MSVARlib," Econometrics 0508017, EconWPA.
    2. Sébastien Le Coent & Erwan Gautier & Benoît Bellone, 2006. "Les marchés financiers anticipent-ils les retournements conjoncturels ?," Économie et Prévision, Programme National Persée, vol. 172(1), pages 83-99.
    3. Xiaowei Cai & Kyle Stiegert & Stephen Koontz, 2011. "Regime switching and oligopsony power: the case of U.S. beef processing," Agricultural Economics, International Association of Agricultural Economists, vol. 42(1), pages 99-109, January.

    More about this item

    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
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

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