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A Nonlinear Model of the Business Cycle

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  • Simon M. Potter
  • Edward E. Leamer

Abstract

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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Bibliographic Info

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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Keywords: nonlinear; business cycle; Bayesian;

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  1. 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.
  2. Simon M. Potter, 1993. "A Nonlinear Approach to U.S. GNP," UCLA Economics Working Papers 693, UCLA Department of Economics.
  3. Edward E. Leamer, 2001. "The Life Cycle of US Economic Expansions," NBER Working Papers 8192, National Bureau of Economic Research, Inc.
  4. 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.
  5. Benjamin M. Friedman & Kenneth Kuttner, 1993. "Why Does the Paper-Bill Spread Predict Real Economic Activity?," NBER Chapters, in: Business Cycles, Indicators and Forecasting, pages 213-254 National Bureau of Economic Research, Inc.
  6. Francis X. Diebold & Glenn D. Rudebusch, 1994. "Measuring Business Cycles: A Modern Perspective," NBER Working Papers 4643, National Bureau of Economic Research, Inc.
  7. Francis X. Diebold & Glenn D. Rudebusch, 1990. "Have postwar economic fluctuations been stabilized?," Discussion Paper / Institute for Empirical Macroeconomics 33, Federal Reserve Bank of Minneapolis.
  8. Christina D. Romer, 1995. "Remeasuring Business Cycles," NBER Working Papers 4150, National Bureau of Economic Research, Inc.
  9. Ben Bernanke & Jean Boivin & Piotr S. Eliasz, 2005. "Measuring the Effects of Monetary Policy: A Factor-augmented Vector Autoregressive (FAVAR) Approach," The Quarterly Journal of Economics, MIT Press, vol. 120(1), pages 387-422, January.
  10. Benjamin M. Friedman & Kenneth N. Kuttner, 1994. "Indicator properties of the paper-bill spread: lessons from recent experience," Working Paper Series, Macroeconomic Issues 94-24, Federal Reserve Bank of Chicago.
  11. 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.
  12. 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.
  13. 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.
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Cited by:
  1. Ryo Horii & Yoshiyasu Ono, 2005. "Financial Crisis and Recovery: Learning-based Liquidity Preference Fluctuations," Macroeconomics 0504016, EconWPA.
  2. Ryo Horii & Yoshiyasu Ono, 2006. "Learning, Inflation Cycles, and Depression," Discussion Papers in Economics and Business 06-14, Osaka University, Graduate School of Economics and Osaka School of International Public Policy (OSIPP).
  3. Ryo Horii & Yoshiyasu Ono, 2004. "Learning, Liquidity Preference, and Business Cycle," ISER Discussion Paper 0601, Institute of Social and Economic Research, Osaka University.

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