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Classical Estimation of Multivariate Markov-Switching Models using MSVARlib

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  • BENOIT BELLONE

    (OECD)

Abstract

This paper introduces an upgraded version of MSVARlib, a Gauss and Ox- Gauss compliant library, focusing on Multivariate Markov Switching Regressions in their most general specification. This new set of procedures allows to estimate, through classical optimization methods, models belonging to the MSI(M)(AH)-VARX ``intercept regime dependent'' family. This research enhances the first package MSVARlib 1.1, which has been deeply inspired by the works of Hamilton and Krolzig. Not to mention the extension to a generalized multivariate regression framework, it notably augments the range of models with a possibly unlimited finite number of Markov states, offers automatic or manual intialization procedures and adds new statistical tests. The first part of this article provides the basic theoretical grounds of the related Markov-switching models. Following sections give some illustrations of the programs through univariate and multivariate examples. One is based on a non-linear reading of the american unemployment rate. A second study is focused on coincident stochastic models of US recessions and slowdowns. The paper concludes on possible extensions and new applications. Detailed guidelines in appendices and tutorial programs are provided to help the reader handling the Gauss package and the joined replication files.

Suggested Citation

  • Benoit Bellone, 2005. "Classical Estimation of Multivariate Markov-Switching Models using MSVARlib," Econometrics 0508017, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpem:0508017
    Note: Type of Document - pdf; pages: 27. Gauss programs, compatible with 3.2 Versions or upper. A complete Gauss library to estimate MSVAR models or Markov switching regressions. Codes, data and programs available at http://bellone.ensae.net
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    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/em/papers/0508/0508017.pdf
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    References listed on IDEAS

    as
    1. Jean-Pierre Urbain & Sébastien Laurent, 2005. "Bridging the gap between Ox and Gauss using OxGauss," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 131-139.
    2. Sichel, Daniel E, 1994. "Inventories and the Three Phases of the Business Cycle," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 269-277, July.
    3. 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.
    4. 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.
    5. James D. Hamilton, 2005. "What's real about the business cycle?," Review, Federal Reserve Bank of St. Louis, issue Jul, pages 435-452.
    6. Benoit Bellone & David Saint-Martin, 2004. "Detecting Turning Points with Many Predictors through Hidden Markov Models," Econometrics 0407001, University Library of Munich, Germany.
    7. Marine Carrasco & Liang Hu, 2004. "Optimal test for Markov switching," 2004 Meeting Papers 374, Society for Economic Dynamics.
    8. 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.
    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. Hansen, Bruce E., 1992. "Testing for parameter instability in linear models," Journal of Policy Modeling, Elsevier, vol. 14(4), pages 517-533, August.
    11. 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.
    12. Ferrara, Laurent, 2003. "A three-regime real-time indicator for the US economy," Economics Letters, Elsevier, vol. 81(3), pages 373-378, December.
    13. Benoit Bellone, 2004. "MSVARlib: a new Gauss library to estimate multivariate Hidden Markov Models," Econometrics 0406004, University Library of Munich, Germany.
    14. Philip Rothman, 1998. "Forecasting Asymmetric Unemployment Rates," The Review of Economics and Statistics, MIT Press, vol. 80(1), pages 164-168, February.
    15. Hamilton, James D., 1996. "Specification testing in Markov-switching time-series models," Journal of Econometrics, Elsevier, vol. 70(1), pages 127-157, January.
    16. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, May.
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    Citations

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    Cited by:

    1. Klaus Abberger & Wolfgang Nierhaus, 2010. "Markov-Switching and the Ifo Business Climate: the Ifo Business Cycle Traffic Lights," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2010(2), pages 1-13.
    2. Fuentes, Cesar A. & Rios, Ronald, 2014. "Non-explicit FOREX intervention: The role of the Central Reserve Bank in a dollarized economy and its effects on expectations from the “peso problem” perspective: The case of Peru," Journal of Business Research, Elsevier, vol. 67(4), pages 558-566.
    3. Ginters BUSS, 2010. "Forecasts With Single - Equation Markov - Switching Model: An Application To The Gross Domestic Product Of Latvia," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 5(2(12)/Sum), pages 48-58.
    4. Pardo, S. & Rautureau, N. & Vallée, T., 2011. "Optimal versus realized policy rules in a regime-switching framework," Economic Modelling, Elsevier, vol. 28(6), pages 2761-2775.
    5. Adél Bosch & Franz Ruch, 2013. "An Alternative Business Cycle Dating Procedure for South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 81(4), pages 491-516, December.
    6. 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.
    7. Klaus Abberger & Wolfgang Nierhaus, 2008. "Markov-Switching und ifo Geschäftsklima," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 61(10), pages 25-30, May.
    8. 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.
    9. Marie Adanero-Donderis & Olivier Darné & Laurent Ferrara, 2009. "Un indicateur probabiliste du cycle d'accélération pour l'économie française," Economie & Prévision, La Documentation Française, vol. 0(3), pages 95-114.
    10. Sulaiman Al-Abduljader & Imad Moosa, 2007. "A Test of the News Model of Stock Price Determination in an Emerging Market: The Case of Kuwait," Working Papers 710, Economic Research Forum, revised 01 Jan 2007.
    11. Chambers, Robert G. & Tzouvelekas, Vangelis, 2013. "Estimating population dynamics without population data," Journal of Environmental Economics and Management, Elsevier, vol. 66(3), pages 510-522.
    12. Benoît Bellone, 2006. "Une lecture probabiliste du cycle d’affaires américain," Économie et Prévision, Programme National Persée, vol. 172(1), pages 63-81.
    13. Adanero-Donderis , M. & Darné, O. & Ferrara, L., 2007. "Deux indicateurs probabilistes de retournement cyclique pour l’économie française," Working papers 187, Banque de France.
    14. Robert G. Chambers & Margarita Genius & Vangelis Tzouvelekas, 2012. "A Supply-Response Model Under Invariant Risk Preferences," Working Papers 1209, University of Crete, Department of Economics.
    15. Wolfgang Nierhaus & Timo Wollmershäuser, 2016. "ifo Konjunkturumfragen und Konjunkturanalyse: Band II," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 72, January.
    16. repec:spr:annopr:v:237:y:2016:i:1:d:10.1007_s10479-014-1651-1 is not listed on IDEAS

    More about this item

    Keywords

    Multivariate Markov-Switching Regressions; Hidden markov Models; Non linear regressions; Open source Gauss library; Business cycle; EM algorithm; Kittagawa-Hamilton Filtering; Recession Detection Models; MSVAR; MS-VAR; Hamilton's Model; Krolzig MSVAR library; Filtered probabilities; Smoothed probabilities.;

    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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