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Forecasting industrial production using models with business cycle asymmetry

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  • Chan Huh
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    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.

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    Bibliographic Info

    Article provided by Federal Reserve Bank of San Francisco in its journal Economic Review.

    Volume (Year): (1998)
    Issue (Month): ()
    Pages: 29-41

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    Handle: RePEc:fip:fedfer:y:1998:p:29-41:n:1

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    Related research

    Keywords: Business cycles ; Industrial productivity ; Econometric models;

    References

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    1. Mark W. French & Daniel E. Sichel, 1991. "Cyclical patterns in the variance of economic activity," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.) 161, Board of Governors of the Federal Reserve System (U.S.).
    2. Ben S. Bernanke, 1990. "On the predictive power of interest rates and interest rate spreads," New England Economic Review, Federal Reserve Bank of Boston, issue Nov, pages 51-68.
    3. Pindyck, Robert S., 1990. "Irreversibility, uncertainty, and investment," Working papers 3137-90., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    4. Simon M. Potter, 1993. "A Nonlinear Approach to U.S. GNP," UCLA Economics Working Papers, UCLA Department of Economics 693, UCLA Department of Economics.
    5. James H. Stock & Mark W. Watson, 1993. "A Procedure for Predicting Recessions with Leading Indicators: Econometric Issues and Recent Experience," NBER Chapters, in: Business Cycles, Indicators and Forecasting, pages 95-156 National Bureau of Economic Research, Inc.
    6. Friedman, Benjamin M & Kuttner, Kenneth N, 1992. "Money, Income, Prices, and Interest Rates," American Economic Review, American Economic Association, American Economic Association, vol. 82(3), pages 472-92, June.
    7. Filardo, Andrew J, 1994. "Business-Cycle Phases and Their Transitional Dynamics," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 12(3), pages 299-308, July.
    8. Ploberger, Werner & Kramer, Walter, 1992. "The CUSUM Test with OLS Residuals," Econometrica, Econometric Society, Econometric Society, vol. 60(2), pages 271-85, March.
    9. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, Econometric Society, vol. 57(2), pages 357-84, March.
    10. Christina D. Romer, 1992. "Remeasuring Business Cycles," NBER Working Papers 4150, National Bureau of Economic Research, Inc.
    11. Granger, Clive W. J. & Terasvirta, Timo, 1993. "Modelling Non-Linear Economic Relationships," OUP Catalogue, Oxford University Press, Oxford University Press, number 9780198773207, October.
    12. Chan G. Huh, 1994. "Asymmetry in the bivariate relationship between output and interest rates," Working Papers in Applied Economic Theory 94-13, Federal Reserve Bank of San Francisco.
    13. Deutsch, Melinda & Granger, Clive W. J. & Terasvirta, Timo, 1994. "The combination of forecasts using changing weights," International Journal of Forecasting, Elsevier, Elsevier, vol. 10(1), pages 47-57, June.
    14. Daniel E. Sichel, 1989. "Business cycle asymmetry: a deeper look," Working Paper Series / Economic Activity Section, Board of Governors of the Federal Reserve System (U.S.) 93, Board of Governors of the Federal Reserve System (U.S.).
    15. Victor Zarnowitz, 1972. "Forecasting Economic Conditions: The Record And The Prospect," NBER Chapters, in: Economic Research: Retrospect and Prospect Vol 1: The Business Cycle Today, pages 183-240 National Bureau of Economic Research, Inc.
    16. Meese, R. & Rogoff, K., 1988. "Was It Real? The Exchange Rate-Interest Differential Ralation Over The Modern Floating-Rate Period," Working papers, Wisconsin Madison - Social Systems 368, Wisconsin Madison - Social Systems.
    17. Francis X. Diebold & Roberto S. Mariano, 1991. "Comparing predictive accuracy I: an asymptotic test," Discussion Paper / Institute for Empirical Macroeconomics, Federal Reserve Bank of Minneapolis 52, Federal Reserve Bank of Minneapolis.
    18. Kling, John L, 1987. "Predicting the Turning Points of Business and Economic Time Series," The Journal of Business, University of Chicago Press, vol. 60(2), pages 201-38, April.
    19. Engle, Robert F. & Granger, C. W. J. & Kraft, Dennis, 1984. "Combining competing forecasts of inflation using a bivariate arch model," Journal of Economic Dynamics and Control, Elsevier, Elsevier, vol. 8(2), pages 151-165, November.
    20. Neftci, Salih N, 1984. "Are Economic Time Series Asymmetric over the Business Cycle?," Journal of Political Economy, University of Chicago Press, University of Chicago Press, vol. 92(2), pages 307-28, April.
    21. Rendigs Fels & C. Elton Hinshaw, 1968. "Forecasting and Recognizing Business Cycle Turning Points," NBER Books, National Bureau of Economic Research, Inc, number fels68-1, October.
    22. Michael D. Boldin, 1992. "Using switching models to study business cycle asymmetries: 1. overview of methodology and application," Research Paper, Federal Reserve Bank of New York 9211, Federal Reserve Bank of New York.
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    Cited by:
    1. Bruno, Giancarlo & Lupi, Claudio, 2003. "Forecasting Euro-Area Industrial Production Using (Mostly) Business Surveys Data," MPRA Paper 42332, University Library of Munich, Germany.
    2. Jörg Döpke & Christian Pierdzioch, 2004. "Politics and the Stock Market � Evidence from Germany," Kiel Working Papers 1203, Kiel Institute for the World Economy.

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