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Non-linear Modelling of the Australian Business Cycle using a Leading Indicator

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Author Info
Roland G. Shami ()
Catherine S. Forbes ()
Abstract

This paper develops a new non-linear model to analyse the business cycle by exploiting the relationship between the asymmetrical behaviour of the cycle and leading indicators. The model proposed is an innovations form of the structural model underlying simple exponential smoothing that is augmented by a latent Markov switching process. Furthermore, the probabilities that drive the Markov process vary with the growth of the leading indicator. The proposed model is used to analyse the Australian business cycle using the gross domestic product as a proxy and the industrial materials prices index as the exogenous leading indicator influencing the transition probabilities. Model parameters are estimated using a Gibbs sampling algorithm and subsequently used for forecasting purposes.

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File URL: http://www.buseco.monash.edu.au/depts/ebs/pubs/wpapers/2002/wp5-02.pdf
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Paper provided by Monash University, Department of Econometrics and Business Statistics in its series Monash Econometrics and Business Statistics Working Papers with number 5/02.

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Length: 26 pages
Date of creation: Aug 2002
Date of revision:
Handle: RePEc:msh:ebswps:2002-5

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Related research
Keywords: Structural model; Markov switching regime; Gibbs sampling; Business cycle; Leading indicator.;

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Find related papers by JEL classification:
E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation
C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Bayesian Analysis
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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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. Hansen, Bruce E, 1992. "The Likelihood Ratio Test under Nonstandard Conditions: Testing the Markov Switching Model of GNP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages S61-82, Suppl. De. [Downloadable!] (restricted)
  2. Albert, James H & Chib, Siddhartha, 1993. "Bayes Inference via Gibbs Sampling of Autoregressive Time Series Subject to Markov Mean and Variance Shifts," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(1), pages 1-15, January.
  3. James D. Hamilton & Gang Lin, 1996. "Stock Market Volatility and The Business Cycle," University of California at San Diego, Economics Working Paper Series 96-18, Department of Economics, UC San Diego. [Downloadable!]
    Other versions:
  4. Beaudry, Paul & Koop, Gary, 1993. "Do recessions permanently change output?," Journal of Monetary Economics, Elsevier, vol. 31(2), pages 149-163, April. [Downloadable!] (restricted)
  5. Aoki, Masanao, 1988. "On alternative state space representations of time series models," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 595-607. [Downloadable!] (restricted)
  6. Filardo, Andrew J. & Gordon, Stephen F., 1998. "Business cycle durations," Journal of Econometrics, Elsevier, vol. 85(1), pages 99-123, July. [Downloadable!] (restricted)
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  7. Masanao Aoki, 1992. "Interactions of Real GNP Business Cycles in a Three Country Time Series Model," UCLA Economics Working Papers 675, UCLA Department of Economics. [Downloadable!]
  8. Stephen G. Cecchetti & Pok-sang Lam & Nelson C. Mark, 1990. "Mean Reversion in Equilibrium Asset Prices," NBER Working Papers 2762, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  9. Clark, Peter K, 1987. "The Cyclical Component of U.S. Economic Activity," The Quarterly Journal of Economics, MIT Press, vol. 102(4), pages 797-814, November. [Downloadable!] (restricted)
  10. Michael D. Boldin, 1996. "A Check on the Robustness of Hamilton's Markov Switching Model Approach to the Economic Analysis of the Business Cycle," Studies in Nonlinear Dynamics & Econometrics, Berkeley Electronic Press, vol. 1(1). [Downloadable!]
  11. 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 357-84, March. [Downloadable!] (restricted)
  12. Harvey, A C, 1985. "Trends and Cycles in Macroeconomic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(3), pages 216-27, June.
  13. Francis X. Diebold & Joon-Haeng Lee & Gretchen C. Weinbach, 1993. "Regime switching with time-varying transition probabilities," Working Papers 93-12, Federal Reserve Bank of Philadelphia.
  14. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70. [Downloadable!] (restricted)
  15. Forbes, C.S. & Snyder, R.D. & Shami, R.S., 2000. "Bayesian Exponential Smoothing," Monash Econometrics and Business Statistics Working Papers 7/2000, Monash University, Department of Econometrics and Business Statistics. [Downloadable!]
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