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Forecasting industrial production using models with business cycle asymmetry

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  • Chan Guk Huh

Abstract

This paper exploits an observed business cycle asymmetry, namely, a systematic shift in the dynamic relationship between output growth and an index for financial market conditions across expansionary and contractionary periods, to forecast monthly growth in industrial production. A bivariate model of monthly industrial production and the spread between the yield on 10-year Treasury notes and the federal funds rate is used as an example. This paper's method does not require a forecaster to make an exact exante determination of turning points in the output series being forecasted. A comparison of the forecast performance of various two-regime nonlinear and conventional linear models suggests that a measureable gain can be made by considering models which explicitly incorporate asymmetry in data.

Suggested Citation

  • Chan Guk Huh, 1998. "Forecasting industrial production using models with business cycle asymmetry," Economic Review, Federal Reserve Bank of San Francisco, pages 29-41.
    • Handle: RePEc:fip:fedfer:y:1998:p:29-41:n:1
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    References listed on IDEAS

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    Cited by:

    1. Döpke, Jörg & Pierdzioch, Christian, 1998. "Brokers and business cycles: Does financial market volatility cause real fluctuations?," Kiel Working Papers 899, Kiel Institute for the World Economy (IfW Kiel).
    2. Bruno, Giancarlo & Lupi, Claudio, 2003. "Forecasting Euro-Area Industrial Production Using (Mostly) Business Surveys Data," MPRA Paper 42332, University Library of Munich, Germany.
    3. Dopke, Jorg & Pierdzioch, Christian, 2006. "Politics and the stock market: Evidence from Germany," European Journal of Political Economy, Elsevier, vol. 22(4), pages 925-943, December.
    4. Bruno, Giancarlo, 2009. "Non-linear relation between industrial production and business surveys data," MPRA Paper 42337, University Library of Munich, Germany.

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