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The Canadian Business Cycle: A Comparison of Models


  • Frédérick Demers
  • Ryan Macdonald


This paper examines the ability of linear and nonlinear models to replicate features of real Canadian GDP. We evaluate the models using various business-cycle metrics. From the 9 data generating processes designed, none can completely accommodate every business-cycle metric under consideration. Richness and complexity do not guarantee a close match with Canadian data. Our findings for Canada are consistent with Piger and Morley's (2005) study of the United States data and confirms the contradiction of their results with those reported by Engel, Haugh, and Pagan (2005): nonlinear models do provide an improvement in matching business-cycle features. Lastly, the empirical results suggest that investigating the merits of forecast combination would be worthwhile.

Suggested Citation

  • Frédérick Demers & Ryan Macdonald, 2007. "The Canadian Business Cycle: A Comparison of Models," Staff Working Papers 07-38, Bank of Canada.
  • Handle: RePEc:bca:bocawp:07-38

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    References listed on IDEAS

    1. Sichel, Daniel E, 1993. "Business Cycle Asymmetry: A Deeper Look," Economic Inquiry, Western Economic Association International, vol. 31(2), pages 224-236, April.
    2. 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.
    3. Adrian Pagan & Don Harding, 2005. "A suggested framework for classifying the modes of cycle research," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 151-159.
    4. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    5. Clements, Michael P & Krolzig, Hans-Martin, 2003. "Business Cycle Asymmetries: Characterization and Testing Based on Markov-Switching Autoregressions," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 196-211, January.
    6. 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 61-82, Suppl. De.
    7. Marcelle Chauvet & James D. Hamilton, 2005. "Dating Business Cycle Turning Points," NBER Working Papers 11422, National Bureau of Economic Research, Inc.
    8. 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.
    9. Philip M. Bodman & Mark Crosby, 2000. "Phases of the Canadian business cycle," Canadian Journal of Economics, Canadian Economics Association, vol. 33(3), pages 618-633, August.
    10. Harding, Don & Pagan, Adrian, 2002. "Dissecting the cycle: a methodological investigation," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 365-381, March.
    11. A. Pagan & J. Engel & D. Haugh, 2004. "Some Methods for Assessing the Need for Non-linear Models in Business Cycle Analysis and Forecasting," Econometric Society 2004 Australasian Meetings 284, Econometric Society.
    12. Knüppel, Malte, 2004. "Testing for business cycle asymmetries based on autoregressions with a Markov-switching intercept," Discussion Paper Series 1: Economic Studies 2004,41, Deutsche Bundesbank.
    13. McQueen, Grant & Thorley, Steven, 1993. "Asymmetric business cycle turning points," Journal of Monetary Economics, Elsevier, vol. 31(3), pages 341-362, June.
    14. Timmermann, Allan, 2000. "Moments of Markov switching models," Journal of Econometrics, Elsevier, vol. 96(1), pages 75-111, May.
    15. James Morley & Jeremy M. Piger, 2005. "The importance of nonlinearity in reproducing business cycle features," Working Papers 2004-032, Federal Reserve Bank of St. Louis.
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    Cited by:

    1. Olivier Darné & Laurent Ferrara, 2011. "Identification of Slowdowns and Accelerations for the Euro Area Economy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(3), pages 335-364, June.
    2. Morley James & Piger Jeremy & Tien Pao-Lin, 2013. "Reproducing business cycle features: are nonlinear dynamics a proxy for multivariate information?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(5), pages 483-498, December.
    3. James Morley & Jeremy Piger & Pao-Lin Tien, 2009. "Reproducing Business Cycle Features: How Important Is Nonlinearity Versus Multivariate Information?," Wesleyan Economics Working Papers 2009-003, Wesleyan University, Department of Economics.

    More about this item


    Business fluctuations and cycles; Econometric and statistical methods;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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