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Unobserved Leading and Coincident Common Factors in the Post-War U.S. Business Cycle

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Author Info
Konstantin A. KHOLODILIN (UNIVERSITE CATHOLIQUE DE LOUVAIN, Institut de Recherches Economiques et Sociales (IRES))

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Abstract

The paper introduces a two-factor model of the common leading and coincident economic indicators. Both factors are unobserved and each of them captures the dynamics of a corresponding group of the observed time series. The common leading factor is assumed to Granger-cause the common coincident factor. This property is used to estimate these two 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. Moreover, a possibility of the individual leading variables having different leads over the common coincident indicator is considered. These models - both with linear and with regime-switching dynamics - were applied to the US monthly macroeconomic time series. The business cycle dating resulting from the nonlinear model closely corresponds to the NBER chronology and leads its turning points by 3-5 months.

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Publisher Info
Paper provided by Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES) in its series Discussion Papers (IRES - Institut de Recherches Economiques et Sociales) with number 2002008.

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Length: 21
Date of creation: 01 Jan 2002
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Handle: RePEc:ctl:louvir:2002008

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Related research
Keywords: dynamic factor analysis; Markov switching; leading indicator; coincident indicator; Granger causality;

Find related papers by JEL classification:
C5 - Mathematical and Quantitative Methods - - Econometric Modeling
E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles

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  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. [Downloadable!]
  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. [Downloadable!] (restricted)
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  3. Kim, Chang-Jin, 1994. "Dynamic linear models with Markov-switching," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 1-22. [Downloadable!] (restricted)
  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. [Downloadable!] (restricted)
  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 969-96, November.
  6. 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. [Downloadable!] (restricted)
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