IDEAS home Printed from https://ideas.repec.org/a/ebl/ecbull/eb-01c50001.html
   My bibliography  Save this article

Latent Leading and Coincident Factors Model with Markov-Switching Dynamics

Author

Listed:
  • Konstantin Kholodilin

    () (Institut des recherches économiques et sociales)

Abstract

This paper introduces a two-factor model of leading and coincident economic indicators. The common leading factor is assumed to Granger-cause the common coincident factor. This property is used to estimate the two common factors simultaneously and hence more efficiently. Two models of the latent leading and coincident factors are studied: a model with linear dynamics and a model with Markov-switching dynamics introduced through the leading factor intercept term. The first model encompasses the comovements between the individual time series. The second model, moreover, takes care of possible asymmetries between the business cycle regimes.

Suggested Citation

  • Konstantin Kholodilin, 2001. "Latent Leading and Coincident Factors Model with Markov-Switching Dynamics," Economics Bulletin, AccessEcon, vol. 3(7), pages 1-13.
  • Handle: RePEc:ebl:ecbull:eb-01c50001
    as

    Download full text from publisher

    File URL: http://www.accessecon.com/pubs/EB/2001/Volume3/EB-01C50001A.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. James H. Stock & Mark W. Watson, 1988. "A Probability Model of The Coincident Economic Indicators," NBER Working Papers 2772, National Bureau of Economic Research, Inc.
    2. Diebold, Francis X & Rudebusch, Glenn D, 1996. "Measuring Business Cycles: A Modern Perspective," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 67-77, February.
    3. Kim, Chang-Jin, 1994. "Dynamic linear models with Markov-switching," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 1-22.
    4. Chauvet, Marcelle & Potter, Simon, 2000. "Coincident and leading indicators of the stock market," Journal of Empirical Finance, Elsevier, vol. 7(1), pages 87-111, May.
    5. 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.
    6. 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, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kholodilin Konstantin A., 2005. "Forecasting the German Cyclical Turning Points: Dynamic Bi-Factor Model with Markov Switching," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 225(6), pages 653-674, December.
    2. Konstantin A. Kholodilin, 2006. "Using the Dynamic Bi-Factor Model with Markov Switching to Predict the Cyclical Turns in the Large European Economies," Discussion Papers of DIW Berlin 554, DIW Berlin, German Institute for Economic Research.
    3. repec:ebl:ecbull:v:3:y:2002:i:5:p:1-15 is not listed on IDEAS
    4. Konstantin A. Kholodilin, 2005. "Forecasting the Turns of German Business Cycle: Dynamic Bi-factor Model with Markov Switching," Discussion Papers of DIW Berlin 494, DIW Berlin, German Institute for Economic Research.

    More about this item

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ebl:ecbull:eb-01c50001. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (John P. Conley). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.