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Analyzing Fixed-event Forecast Revisions

Author

Listed:
  • Philip Hans Franses

    () (Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam)

  • Chia-Lin Chang

    () (Department of Applied Economics, Department of Finance, National Chung Hsing University Taichung, Taiwan)

  • Michael McAleer

    (Econometrisch Instituut (Econometric Institute), Faculteit der Economische Wetenschappen (Erasmus School of Economics), Erasmus Universiteit, Tinbergen Instituut (Tinbergen Institute).)

Abstract

It is common practice to evaluate fixed-event forecast revisions in macroeconomics by regressing current revisions on one-period lagged revisions. Under weak-form efficiency, the correlation between the current and one-period lagged revisions should be zero. The empirical findings in the literature suggest that the null hypothesis of zero correlation between the current and one-period lagged revisions is rejected quite frequently, where the correlation can be either positive or negative. In this paper we propose a methodology to be able to interpret such non-zero correlations in a straightforward manner. Our approach is based on the assumption that forecasts can be decomposed into both an econometric model and expert intuition. The interpretation of the sign of the correlation between the current and one-period lagged revisions depends on the process governing intuition, and the correlation between intuition and news.

Suggested Citation

  • Philip Hans Franses & Chia-Lin Chang & Michael McAleer, 2011. "Analyzing Fixed-event Forecast Revisions," Documentos de Trabajo del ICAE 2011-24, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  • Handle: RePEc:ucm:doicae:1124
    Note: The authors are grateful for the helpful comments and suggestions of seminar participants at Complutense University of Madrid. For financial support, the second author acknowledges the National Science Council, Taiwan, and the third author wishes to thank the Australian Research Council, National Science Council, Taiwan, and the Japan Society for the Promotion of Science.
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    References listed on IDEAS

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    1. Giampiero M. Gallo & Clive W.J. Granger & Yongil Jeon, 2002. "Copycats and Common Swings: The Impact of the Use of Forecasts in Information Sets," IMF Staff Papers, Palgrave Macmillan, vol. 49(1), pages 1-2.
    2. Dovern, Jonas & Weisser, Johannes, 2011. "Accuracy, unbiasedness and efficiency of professional macroeconomic forecasts: An empirical comparison for the G7," International Journal of Forecasting, Elsevier, vol. 27(2), pages 452-465.
    3. Amir, Eli & Ganzach, Yoav, 1998. "Overreaction and underreaction in analysts' forecasts," Journal of Economic Behavior & Organization, Elsevier, vol. 37(3), pages 333-347, November.
    4. Carlos Capistrán & Allan Timmermann, 2009. "Disagreement and Biases in Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(2-3), pages 365-396, March.
    5. Philip Hans Franses & Michael McAleer & Rianne Legerstee, 2009. "Expert opinion versus expertise in forecasting," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(3), pages 334-346.
    6. Clements, M.C., 1996. "Evaluating the Rationality of Fixed-Event Forecasts," The Warwick Economics Research Paper Series (TWERPS) 457, University of Warwick, Department of Economics.
    7. Olga Isengildina & Scott H. Irwin & Darrel L. Good, 2006. "Are Revisions to USDA Crop Production Forecasts Smoothed?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 88(4), pages 1091-1104.
    8. Berger, Allen N & Krane, Spencer D, 1985. "The Information Efficiency of Econometric Model Forecasts," The Review of Economics and Statistics, MIT Press, vol. 67(1), pages 128-134, February.
    9. Kajal Lahiri & Gultekin Isiklar & Prakash Loungani, 2006. "How quickly do forecasters incorporate news? Evidence from cross-country surveys," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(6), pages 703-725.
    10. Philip Hans Franses & Rianne Legerstee, 2010. "Do experts' adjustments on model-based SKU-level forecasts improve forecast quality?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(3), pages 331-340.
    11. Loungani, Prakash, 2001. "How accurate are private sector forecasts? Cross-country evidence from consensus forecasts of output growth," International Journal of Forecasting, Elsevier, vol. 17(3), pages 419-432.
    12. Ashiya, Masahiro, 2003. "Testing the rationality of Japanese GDP forecasts: the sign of forecast revision matters," Journal of Economic Behavior & Organization, Elsevier, vol. 50(2), pages 263-269, February.
    13. Ager, P. & Kappler, M. & Osterloh, S., 2009. "The accuracy and efficiency of the Consensus Forecasts: A further application and extension of the pooled approach," International Journal of Forecasting, Elsevier, vol. 25(1), pages 167-181.
    14. S. Dellavigna., 2011. "Psychology and Economics: Evidence from the Field," VOPROSY ECONOMIKI, N.P. Redaktsiya zhurnala "Voprosy Economiki", vol. 5.
    15. Cho, Dong W., 2002. "Do revisions improve forecasts?," International Journal of Forecasting, Elsevier, vol. 18(1), pages 107-115.
    16. Lawrence, Michael & O'Connor, Marcus, 2000. "Sales forecasting updates: how good are they in practice?," International Journal of Forecasting, Elsevier, vol. 16(3), pages 369-382.
    17. Chang, Chia-Lin & Franses, Philip Hans & McAleer, Michael, 2011. "How accurate are government forecasts of economic fundamentals? The case of Taiwan," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1066-1075, October.
    18. Franses, Philip Hans & Kranendonk, Henk C. & Lanser, Debby, 2011. "One model and various experts: Evaluating Dutch macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 482-495.
    19. David Laster & Paul Bennett & In Sun Geoum, 1999. "Rational Bias in Macroeconomic Forecasts," The Quarterly Journal of Economics, Oxford University Press, vol. 114(1), pages 293-318.
    20. Nordhaus, William D, 1987. "Forecasting Efficiency: Concepts and Applications," The Review of Economics and Statistics, MIT Press, vol. 69(4), pages 667-674, November.
    21. Masahiro Ashiya, 2006. "Testing the rationality of forecast revisions made by the IMF and the OECD," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(1), pages 25-36.
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    Cited by:

    1. Messina, Jeffrey D. & Sinclair, Tara M. & Stekler, Herman, 2015. "What can we learn from revisions to the Greenbook forecasts?," Journal of Macroeconomics, Elsevier, vol. 45(C), pages 54-62.
    2. repec:eee:ecmode:v:68:y:2018:i:c:p:506-513 is not listed on IDEAS
    3. Chia-Lin Chang & Yu-Pei Ke, 2014. "Testing Price Pressure, Information, Feedback Trading, And Smoothing Effects For Energy Exchange Traded Funds," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 9(02), pages 1-26.

    More about this item

    Keywords

    Evaluating forecasts; Macroeconomic forecasting; Rationality; Intuition; Weak-form efficiency; Fixed-event forecasts.;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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