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A Check on the Robustness of Hamilton's Markov Switching Model Approach to the Economic Analysis of the Business Cycle

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  • Boldin Michael D.

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    (The Conference Board New York, NY)

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    Abstract

    This note explores the robustness of Hamilton's (Econometrica, 1989) two-regime Markov switching model framework for capturing business-cycle patterns. Applying his exact specification to a revised version of real GNP, I find parameter estimates that are similar to those he reported only when I use the same sample period (1952-1984) and a particular set of starting values for the maximum likelihood procedure. Two other local maxima exist that have higher likelihood values, and neither correspond to the conventional recession-expansion dichotomy. In fact, when the sample period is extended, there is no longer a local maximum near the parameter set reported by Hamilton. Exploring the model and data further, I reject cross-regime restrictions of Hamilton specification, but also find that relaxing these restrictions increases the number of local maxima. However, a parsimonious three-regime model for GNP growth is more robust and plausible, especially when each regime is required to last more than one quarter.

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    Bibliographic Info

    Article provided by De Gruyter in its journal Studies in Nonlinear Dynamics & Econometrics.

    Volume (Year): 1 (1996)
    Issue (Month): 1 (April)
    Pages: 1-14

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    Handle: RePEc:bpj:sndecm:v:1:y:1996:i:1:n:re1

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    Web page: http://www.degruyter.com

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    Cited by:
    1. Clements, M.P. & Krolzig, H-M., 1999. "Business Cycle Asymmetries: Characterisationand Testing Based on Markov-Switching Autoregression," The Warwick Economics Research Paper Series (TWERPS) 522, University of Warwick, Department of Economics.
    2. James Morley & Jeremy M. Piger, 2005. "The importance of nonlinearity in reproducing business cycle features," Working Papers 2004-032, Federal Reserve Bank of St. Louis.
    3. Shami, R.G. & Forbes, C.S., 2000. "A structural Time Series Model with Markov Switching," Monash Econometrics and Business Statistics Working Papers 10/00, Monash University, Department of Econometrics and Business Statistics.
    4. Chang-Jin Kim & James Morley & Jeremy Piger, 2003. "Nonlinearity and the permanent effects of recessions," Working Papers 2002-014, Federal Reserve Bank of St. Louis.
    5. Cem Cakmakli & Richard Paap & Dick van Dijk, 2011. "Measuring and Predicting Heterogeneous Recessions," Tinbergen Institute Discussion Papers 11-154/4, Tinbergen Institute, revised 15 Nov 2011.
    6. Çakmaklı, Cem & Paap, Richard & van Dijk, Dick, 2013. "Measuring and predicting heterogeneous recessions," Journal of Economic Dynamics and Control, Elsevier, vol. 37(11), pages 2195-2216.
    7. J. Polzehl & V. Spokoiny & C. Starica, 2004. "When did the 2001 recession really start?," Econometrics 0411017, EconWPA.
    8. Kapetanios, G., 1999. "Threshold Models for Trended Time Series," Cambridge Working Papers in Economics 9905, Faculty of Economics, University of Cambridge.
    9. Cem Cakmakli & Richard Paap & Dick J.C. van Dijk, 2011. "Modeling and Estimation of Synchronization in Multistate Markov-Switching Models," Tinbergen Institute Discussion Papers 11-002/4, Tinbergen Institute.
    10. Maximo Camacho & Gabriel Perez-Quiros & Hugo Rodríguez Mendizábal, 2009. "High-growth Recoveries, Inventories and the Great Moderation," Banco de Espa�a Working Papers 0917, Banco de Espa�a.
    11. Nadir Ocal & Denise R. Osborn, 2000. "Business cycle non-linearities in UK consumption and production," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(1), pages 27-43.
    12. Don U.A. Galagedera & Roland Shami, 2003. "Association between Markov regime-switching market volatility and beta risk: Evidence from Dow Jones industrial securities," Monash Econometrics and Business Statistics Working Papers 20/03, Monash University, Department of Econometrics and Business Statistics.
    13. Roland G. Shami & Catherine S. Forbes, 2002. "Non-linear Modelling of the Australian Business Cycle using a Leading Indicator," Monash Econometrics and Business Statistics Working Papers 5/02, Monash University, Department of Econometrics and Business Statistics.
    14. Michael T. Owyang & Jeremy Piger & Howard J. Wall, 2005. "Business Cycle Phases in U.S. States," The Review of Economics and Statistics, MIT Press, vol. 87(4), pages 604-616, November.
    15. Lubrano, Michel, 2004. "Modélisation bayésienne non linéaire du taux d’intérêt de court terme américain : l’aide des outils non paramétriques," L'Actualité Economique, Société Canadienne de Science Economique, vol. 80(2), pages 465-499, Juin-Sept.
    16. Matteo Manera & Alessandro Cologni, 2006. "The Asymmetric Effects of Oil Shocks on Output Growth: A Markov-Switching Analysis for the G-7 Countries," Working Papers 2006.29, Fondazione Eni Enrico Mattei.
    17. David N. DeJong & Hariharan Dharmarajan & Roman Liesenfeld & Jean-Francois Richard, 2008. "Exploiting Non-Linearities in GDP Growth for Forecasting and Anticipating Regime Changes," Working Papers 367, University of Pittsburgh, Department of Economics, revised Sep 2008.

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