This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

A Nonlinear Model of the Business Cycle

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Simon M. Potter
Edward E. Leamer

Additional information is available for the following registered author(s):

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

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

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

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

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length:
Date of creation: 11 Aug 2004
Date of revision:
Handle: RePEc:ecm:nawm04:490

Contact details of provider:
Phone: 1 212 998 3820
Fax: 1 212 995 4487
Email:
Web page: http://www.econometricsociety.org/pastmeetings.asp
More information through EDIRC

For technical questions regarding this item, or to correct its listing, contact: (Christopher F. Baum).

Related research
Keywords: nonlinear; business cycle; Bayesian;

Other versions of this item:

Find related papers by JEL classification:
C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Bayesian Analysis
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation

This paper has been announced in the following NEP Reports:

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Romer, Christina D., 1994. "Remeasuring Business Cycles," The Journal of Economic History, Cambridge University Press, vol. 54(03), pages 573-609, September. [Downloadable!]
    Other versions:
  2. 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. [Downloadable!]
    Other versions:
  3. 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. [Downloadable!] (restricted)
    Other versions:
  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. [Downloadable!] (restricted)
    Other versions:
  5. 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. [Downloadable!] (restricted)
    Other versions:
  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.
    Other versions:
  7. 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. [Downloadable!] (restricted)
    Other versions:
  8. Edward E. Leamer, 2001. "The Life Cycle of US Economic Expansions," NBER Working Papers 8192, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  9. 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. [Downloadable!] (restricted)
    Other versions:
  10. Francis X. Diebold & Glenn D. Rudebusch, 1994. "Measuring Business Cycles: A Modern Perspective," NBER Working Papers 4643, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
  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. [Downloadable!] (restricted)
  12. 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. [Downloadable!] (restricted)
    Other versions:
  13. 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. [Downloadable!] (restricted)
    Other versions:
Full references

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  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). [Downloadable!]
  2. Ryo Horii & Yoshiyasu Ono, 2005. "Financial Crisis and Recovery: Learning-based Liquidity Preference Fluctuations," Macroeconomics 0504016, EconWPA. [Downloadable!]
  3. Ryo Horii & Yoshiyasu Ono, 2004. "Learning, Liquidity Preference, and Business Cycle," ISER Discussion Paper 0601, Institute of Social and Economic Research, Osaka University. [Downloadable!]
Statistics
Access and download statistics

Did you know? You may want to explore EconPapers, which displays the same data as IDEAS in a different way.

This page was last updated on 2009-11-6.


This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.