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Forecasting UK Industrial Production over the Business Cycle

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  • Simpson, Paul W
  • Osborn, Denise R
  • Sensier, Marianne

Abstract

This paper examines the information available through leading indicators for modelling and forecasting the UK quarterly index of production. Both linear and non-linear specifications are examined, with the latter being of the Markov-switching type as used in many recent business cycle applications. The Markov-switching models perform relatively poorly in forecasting the 1990s production recession, but a three-indicator linear specification does well. The leading indicator variables in this latter model include a short-term interest rate, the stock market dividend yield and the optimism balance from the quarterly CBI survey. Copyright © 2001 by John Wiley & Sons, Ltd.

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Bibliographic Info

Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 20 (2001)
Issue (Month): 6 (September)
Pages: 405-24

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Handle: RePEc:jof:jforec:v:20:y:2001:i:6:p:405-24

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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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References

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  1. 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.
  2. Breusch, T S, 1978. "Testing for Autocorrelation in Dynamic Linear Models," Australian Economic Papers, Wiley Blackwell, vol. 17(31), pages 334-55, December.
  3. Hamilton, James D & Perez-Quiros, Gabriel, 1996. "What Do the Leading Indicators Lead?," The Journal of Business, University of Chicago Press, vol. 69(1), pages 27-49, January.
  4. Artis, Michael J & Kontolemis, Zenon G & Osborn, Denise R, 1997. "Business Cycles for G7 and European Countries," The Journal of Business, University of Chicago Press, vol. 70(2), pages 249-79, April.
  5. Artis, Michael J, et al, 1995. "Turning Point Prediction for the UK Using CSO Leading Indicators," Oxford Economic Papers, Oxford University Press, vol. 47(3), pages 397-417, July.
  6. Andreou, Elena & Osborn, Denise R & Sensier, Marianne, 2000. "A Comparison of the Statistical Properties of Financial Variables in the USA, UK and Germany over the Business Cycle," Manchester School, University of Manchester, vol. 68(4), pages 396-418, Special I.
  7. Hess, Gregory D & Iwata, Shigeru, 1997. "Measuring and Comparing Business-Cycle Features," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(4), pages 432-44, October.
  8. Clements, Michael P & Smith, Jeremy, 1996. "A Monte Carlo Study of the Forecasting Performance of Empirical Setar Models," The Warwick Economics Research Paper Series (TWERPS) 464, University of Warwick, Department of Economics.
  9. Engle, Robert F., 1982. "A general approach to lagrange multiplier model diagnostics," Journal of Econometrics, Elsevier, vol. 20(1), pages 83-104, October.
  10. Terasvirta, T & Anderson, H M, 1992. "Characterizing Nonlinearities in Business Cycles Using Smooth Transition Autoregressive Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages S119-36, Suppl. De.
  11. Driffill, John & Sola, Martin, 1998. "Intrinsic bubbles and regime-switching," Journal of Monetary Economics, Elsevier, vol. 42(2), pages 357-373, July.
  12. Simpson, Paul W & Osborn, Denise R & Sensier, Marianne, 2001. "Modelling Business Cycle Movements in the UK Economy," Economica, London School of Economics and Political Science, vol. 68(270), pages 243-67, May.
  13. Filardo, Andrew J, 1994. "Business-Cycle Phases and Their Transitional Dynamics," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 299-308, July.
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Cited by:
  1. Ferrara, L. & Marsilli, C. & Ortega, J-P., 2013. "Forecasting growth during the Great Recession: is financial volatility the missing ingredient?," Working papers 454, Banque de France.
  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. Giancarlo Bruno, 2009. "Non-linear relation between industrial production and business surveys data," ISAE Working Papers 119, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
  4. Yuan, Chunming, 2011. "Forecasting exchange rates: The multi-state Markov-switching model with smoothing," International Review of Economics & Finance, Elsevier, vol. 20(2), pages 342-362, April.
  5. Siliverstovs, B. & van Dijk, D.J.C., 2003. "Forecasting industrial production with linear, nonlinear, and structural change models," Econometric Institute Research Papers EI 2003-16, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  6. Carriero, Andrea & Marcellino, Massimiliano, 2007. "A comparison of methods for the construction of composite coincident and leading indexes for the UK," International Journal of Forecasting, Elsevier, vol. 23(2), pages 219-236.

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