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Business Cycle Turning Points : Mixed-Frequency Data with Structural Breaks


  • Konstantin A., KHOLODILIN
  • Wension Vincent, YAO


This papers develops a dynamic factor models with regime switching to account for the decreasing volatility of the U.S. economy observed since the mid-1980s. Apart from the Markov switching capturing the cyclical fluctuations, an additional type of regime switching is introduced to allow variances to switch between distinct regimes. The resulting four-regime models extend univariate analysis currently used in the literature on the structural break in conditional volatility to the multivariate time series. Besides the dynamic factor model using the data with a single (monthly) frequency, we employ the additonal information incorporating the mixed-frequency data, which include not only the monthly component series but also such an important quarterly series as the real GDP. The evaluation of six different nonlinear models suggests that the probabilities derived from all the models comply with NBER business cycle dating and detect a one-time shifting from high variance to low-variance states in February 1984. In addition, we find that: mixed-frequency models outperform single-frequency models; restricted models outperform unrestricted models; four-regime switching models outperform two-regime switching models.

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  • Konstantin A., KHOLODILIN & Wension Vincent, YAO, 2004. "Business Cycle Turning Points : Mixed-Frequency Data with Structural Breaks," Discussion Papers (IRES - Institut de Recherches Economiques et Sociales) 2004024, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
  • Handle: RePEc:ctl:louvir:2004024

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    References listed on IDEAS

    1. Roberto S. Mariano & Yasutomo Murasawa, 2003. "A new coincident index of business cycles based on monthly and quarterly series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 427-443.
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    5. Chauvet, Marcelle & Potter, Simon, 2001. "Recent Changes in the US Business Cycle," Manchester School, University of Manchester, vol. 69(5), pages 481-508, Special I.
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    7. Kim, Chang-Jin & Nelson, Charles R & Piger, Jeremy, 2004. "The Less-Volatile U.S. Economy: A Bayesian Investigation of Timing, Breadth, and Potential Explanations," Journal of Business & Economic Statistics, American Statistical Association, vol. 22(1), pages 80-93, January.
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    11. Jean-Yves Pitarakis, 2004. "Least squares estimation and tests of breaks in mean and variance under misspecification," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 32-54, June.
    12. Veronica C. Warnock & Francis E. Warnock, 2000. "The declining volatility of U.S. employment: was Arthur Burns right?," International Finance Discussion Papers 677, Board of Governors of the Federal Reserve System (U.S.).
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    16. Chauvet, Marcelle, 1998. "An Econometric Characterization of Business Cycle Dynamics with Factor Structure and Regime Switching," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 969-996, November.
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    Cited by:

    1. repec:hal:journl:hal-01159200 is not listed on IDEAS
    2. Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Documents de travail du Centre d'Economie de la Sorbonne 15009, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.

    More about this item


    Volatility; Structural break; Composite coincident indicator; Dynamic factor model; Markov switching; Mixed-frequency data;

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General

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