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Business cycle detrending of macroeconomic data via a latent business cycle index

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  • Michael J. Dueker
  • Charles R. Nelson

Abstract

We use Markov Chain Monte Carlo methods to augment a vector autoregressive system with a latent business cycle index that is negative during recessions and positive during expansions. We then sample counterfactual values of the macroeconomic variables in the case where the latent business cycle index is held constant at its median value. These counterfactual values represent posterior beliefs about how the economy would have evolved absent business cycle fluctuations. One advantage is that a VAR framework provides model-consistent counterfactual values in the same way that VARs provide model-consistent forecasts, so data series are not detrended in isolation from each other. We apply these methods to estimate the business cycle components of industrial production growth, consumer price inflation, the federal funds rate and the spread between long-term and short-term interest rates. These decompositions provide an explicitly counterfactual approach to deriving empirical business cycle facts that complements other approaches.

Suggested Citation

  • Michael J. Dueker & Charles R. Nelson, 2003. "Business cycle detrending of macroeconomic data via a latent business cycle index," Working Papers 2002-025, Federal Reserve Bank of St. Louis.
  • Handle: RePEc:fip:fedlwp:2002-025
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    References listed on IDEAS

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    1. Chang-Jin Kim & Christian J. Murray, 2002. "Permanent and transitory components of recessions," Empirical Economics, Springer, vol. 27(2), pages 163-183.
    2. Michael Dueker, 2005. "Dynamic Forecasts of Qualitative Variables: A Qual VAR Model of U.S. Recessions," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 96-104, January.
    3. King, Robert G. & Plosser, Charles I. & Stock, James H. & Watson, Mark W., 1991. "Stochastic Trends and Economic Fluctuations," American Economic Review, American Economic Association, vol. 81(4), pages 819-840, September.
    4. Kozicki, Sharon, 1999. "Multivariate detrending under common trend restrictions: Implications for business cycle research," Journal of Economic Dynamics and Control, Elsevier, vol. 23(7), pages 997-1028, June.
    5. Harvey, A C & Jaeger, A, 1993. "Detrending, Stylized Facts and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(3), pages 231-247, July-Sept.
    6. Dueker, Michael, 1999. "Conditional Heteroscedasticity in Qualitative Response Models of Time Series: A Gibbs-Sampling Approach to the Bank Prime Rate," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(4), pages 466-472, October.
    7. John H. Cochrane, 1994. "Permanent and Transitory Components of GNP and Stock Prices," The Quarterly Journal of Economics, Oxford University Press, vol. 109(1), pages 241-265.
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    Cited by:

    1. CĂ©line Gauthier & Fuchun Li, 2005. "Linking real activity and financial markets: the first steps towards a small estimated model for Canada," BIS Papers chapters,in: Bank for International Settlements (ed.), Investigating the relationship between the financial and real economy, volume 22, pages 253-72 Bank for International Settlements.

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    Keywords

    Business cycles ; Time-series analysis;

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