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Using Long-, Medium-, and Short-Term Trends to Forecast Turning Points in the Business Cycle: Some International Evidence

Author

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  • García-Ferrer Antonio

    (Universidad Autónoma de Madrid, Universidad Autónoma de Madrid, ricardo.queralt@uam.es)

  • Queralt Ricardo A.

    (Universidad Autónoma de Madrid, Universidad Autónoma de Madrid, ricardo.queralt@uam.es)

Abstract

This paper provides rules for anticipating business-cycle recessions and recoveries for countries showing asymmetric cycle durations. Based on a Schumpeterian framework, we analyze business cycles as sums of short-, medium-, and long-term cycles defined for a particular class of unobserved component models. By associating the trend with the low frequencies of the pseudo-spectrum in the frequency domain, manipulation of the spectral bandwidth allows us to define subjective length trends with specific properties. In this paper, we show how these properties can be exploited to anticipate business-cycle turning points, not only historically, but also in a true ex-ante forecasting exercise. This procedure is applied to U.S. post-World War II GNP quarterly data, as well as to another set of European countries.

Suggested Citation

  • García-Ferrer Antonio & Queralt Ricardo A., 1998. "Using Long-, Medium-, and Short-Term Trends to Forecast Turning Points in the Business Cycle: Some International Evidence," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 3(2), pages 1-29, July.
    • Handle: RePEc:bpj:sndecm:v:3:y:1998:i:2:n:2
    DOI: 10.2202/1558-3708.1042
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    Citations

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    Cited by:

    1. Gustavo A. Marrero & Juan G. Rodriguez, 2012. "Macroeconomic determinants of inequality of opportunity and effort in the US: 1970-2009," Working Papers 249, ECINEQ, Society for the Study of Economic Inequality.
    2. Garcia-Ferrer, Antonio & Bujosa-Brun, Marcos, 2000. "Forecasting OECD industrial turning points using unobserved components models with business survey data," International Journal of Forecasting, Elsevier, vol. 16(2), pages 207-227.
    3. Gustavo A. Marrero, 2007. "Traditional versus unobserved components methods to forecast quarterly national account aggregates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(2), pages 129-153.
    4. Bujosa, Marcos & Garcia-Ferrer, Antonio & Young, Peter C., 2007. "Linear dynamic harmonic regression," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 999-1024, October.
    5. Garcia-Ferrer, Antonio & Queralt, Ricardo & Blazquez, Cristina, 2001. "A growth cycle characterisation and forecasting of the Spanish economy: 1970-1998," International Journal of Forecasting, Elsevier, vol. 17(3), pages 517-532.
    6. Javier Gómez Biscarri, 2002. "Dating Recessions from Industrial Production Indexes: An Analysis for Europe and the US," Faculty Working Papers 05/02, School of Economics and Business Administration, University of Navarra.
    7. Chian, Abraham C.-L. & Rempel, Erico L. & Rogers, Colin, 2006. "Complex economic dynamics: Chaotic saddle, crisis and intermittency," Chaos, Solitons & Fractals, Elsevier, vol. 29(5), pages 1194-1218.

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