IDEAS home Printed from https://ideas.repec.org/p/ecm/nawm04/490.html
   My bibliography  Save this paper

A Nonlinear Model of the Business Cycle

Author

Listed:
  • 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

Suggested Citation

  • Simon M. Potter & Edward E. Leamer, 2004. "A Nonlinear Model of the Business Cycle," Econometric Society 2004 North American Winter Meetings 490, Econometric Society.
  • Handle: RePEc:ecm:nawm04:490
    as

    Download full text from publisher

    File URL: http://repec.org/esNAWM04/up.26196.1049203074.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Diebold, Francis X & Rudebusch, Glenn D, 1992. "Have Postwar Economic Fluctuations Been Stabilized?," American Economic Review, American Economic Association, vol. 82(4), pages 993-1005, September.
    2. Gertler, Mark & Lown, Cara S, 1999. "The Information in the High-Yield Bond Spread for the Business Cycle: Evidence and Some Implications," Oxford Review of Economic Policy, Oxford University Press, vol. 15(3), pages 132-150, Autumn.
    3. Potter, Simon M, 1995. "A Nonlinear Approach to US GNP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(2), pages 109-125, April-Jun.
    4. 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.
    5. Lang, William W. & Nakamura, Leonard I., 1990. "The dynamics of credit markets in a model with learning," Journal of Monetary Economics, Elsevier, vol. 26(2), pages 305-318, October.
    6. Romer, Christina D., 1994. "Remeasuring Business Cycles," The Journal of Economic History, Cambridge University Press, vol. 54(03), pages 573-609, September.
    7. Martin Chalkley & In Ho Lee, 1998. "Learning and Asymmetric Business Cycles," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 1(3), pages 623-645, July.
    8. Russell Cooper & Andrew John, 1988. "Coordinating Coordination Failures in Keynesian Models," The Quarterly Journal of Economics, Oxford University Press, vol. 103(3), pages 441-463.
    9. 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 555-576, June.
    10. 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.
    11. Arturo Estrella & Anthony P. Rodrigues & Sebastian Schich, 2003. "How Stable is the Predictive Power of the Yield Curve? Evidence from Germany and the United States," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 629-644, August.
    12. 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.
    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.
    14. Neftci, Salih N, 1984. "Are Economic Time Series Asymmetric over the Business Cycle?," Journal of Political Economy, University of Chicago Press, vol. 92(2), pages 307-328, April.
    15. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2004. "Measuring the effects of monetary policy: a factor-augmented vector autoregressive (FAVAR) approach," Finance and Economics Discussion Series 2004-03, Board of Governors of the Federal Reserve System (U.S.).
    16. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    17. Edward E. Leamer, 2001. "The Life Cycle of US Economic Expansions," NBER Working Papers 8192, National Bureau of Economic Research, Inc.
    18. Friedman, Milton, 1993. "The "Plucking Model" of Business Fluctuations Revisited," Economic Inquiry, Western Economic Association International, vol. 31(2), pages 171-177, April.
    19. 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.
    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. 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).
    2. Marcelle, Chauvet & Simon, Potter, 2007. "Monitoring Business Cycles with Structural Breaks," MPRA Paper 15097, University Library of Munich, Germany, revised 31 Apr 2009.
    3. Horii, Ryo & Ono, Yoshiyasu, 2009. "Information Cycles and Depression in a Stochastic Money-in-Utility Model," MPRA Paper 13485, University Library of Munich, Germany.
    4. Gupta, Rangan & Wohar, Mark, 2017. "Forecasting oil and stock returns with a Qual VAR using over 150years off data," Energy Economics, Elsevier, vol. 62(C), pages 181-186.
    5. Ryo Horii & Yoshiyasu Ono, 2005. "Financial Crisis and Recovery: Learning-based Liquidity Preference Fluctuations," Macroeconomics 0504016, EconWPA.
    6. Ryo Horii & Yoshiyasu Ono, 2004. "Learning, Liquidity Preference, and Business Cycle," ISER Discussion Paper 0601, Institute of Social and Economic Research, Osaka University.

    More about this item

    Keywords

    nonlinear; business cycle; Bayesian;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ecm:nawm04:490. 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: (Christopher F. Baum). General contact details of provider: http://edirc.repec.org/data/essssea.html .

    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.