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A Nonlinear Model of the Business Cycle

  • Simon M. Potter
  • Edward E. Leamer

The usual index of leading indicators has constant weights on its components and is therefore implicitly premised on the assumption that the dynamical properties of the economy remain the same over time and across phases of the business cycle. We explore the possibility that the business cycle has phases, for example, recessions, recoveries and normal growth, each with its unique dynamics. Based on this possibility we develop a nonlinear model of the business cycle that combines a number of previous approaches. We model the state of the economy as a latent variable with a threshold autoregression structure. In addition to dependence on its own lags the latent variable is also determined by observed economic and financial variables. In turn these variables are modeled as following a nonlinear vector autoregression with regimes defined by the latent business cycle variable. A Markov Chain Monte Carlo algorithm is developed to estimate the model. Special attention is paid to specification of prior distributions given the large dimension of the model. We also investigate using the business cycle chronology of the NBER to aid in the classification of the latent variable. The two main empirical objectives of the model are to provide more accurate predictions of economic variables particularly at turning points and to describe how the dynamics differ across business cycle phases

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Paper provided by Econometric Society in its series Econometric Society 2004 North American Winter Meetings with number 490.

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Date of creation: 11 Aug 2004
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Handle: RePEc:ecm:nawm04:490
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  1. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2004. "Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach," NBER Working Papers 10220, National Bureau of Economic Research, Inc.
  2. Mark Gertler & Cara S. Lown, 2000. "The Information in the High Yield Bond Spread for the Business Cycle: Evidence and Some Implications," NBER Working Papers 7549, National Bureau of Economic Research, Inc.
  3. Francis X. Diebold & Glenn D. Rudebusch, 1994. "Measuring Business Cycles: A Modern Perspective," NBER Working Papers 4643, National Bureau of Economic Research, Inc.
  4. Pesaran, M. Hashem & Potter, Simon M., 1997. "A floor and ceiling model of US output," Journal of Economic Dynamics and Control, Elsevier, vol. 21(4-5), pages 661-695, May.
  5. Francis X. Diebold & Glenn D. Rudebusch, 1991. "Have postwar economic fluctuations been stabilized?," Working Paper Series / Economic Activity Section 116, Board of Governors of the Federal Reserve System (U.S.).
  6. Benjamin M. Friedman & Kenneth N. Kuttner, 1991. "Why does the paper-bill spread predict real economic activity?," Working Paper Series, Macroeconomic Issues 91-16, Federal Reserve Bank of Chicago.
  7. Christina D. Romer, 1992. "Remeasuring Business Cycles," NBER Working Papers 4150, National Bureau of Economic Research, Inc.
  8. Arturo Estrella & Anthony P. Rodrigues & Sebastian Schich, 2000. "How stable is the predictive power of the yield curve? evidence from Germany and the United States," Staff Reports 113, Federal Reserve Bank of New York.
  9. Benjamin M. Friedman & Kenneth N. Kuttner, 1998. "Indicator Properties Of The Paper-Bill Spread: Lessons From Recent Experience," The Review of Economics and Statistics, MIT Press, vol. 80(1), pages 34-44, February.
  10. Edward E. Leamer, 2001. "The Life Cycle of US Economic Expansions," NBER Working Papers 8192, National Bureau of Economic Research, Inc.
  11. Potter, Simon M, 1995. "A Nonlinear Approach to US GNP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(2), pages 109-25, April-Jun.
  12. Koop, Gary & Potter, Simon M., 1998. "Bayes factors and nonlinearity: Evidence from economic time series1," Journal of Econometrics, Elsevier, vol. 88(2), pages 251-281, November.
  13. Estrella, Arturo & Hardouvelis, Gikas A, 1991. " The Term Structure as a Predictor of Real Economic Activity," Journal of Finance, American Finance Association, vol. 46(2), pages 555-76, June.
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