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How Far Ahead Can We Forecast? Evidence From Cross-country Surveys

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  • Kajal Lahiri
  • Gultekin Isiklar

Abstract

Using monthly GDP forecasts from Consensus Economics Inc. for 18 developed countries reported over 24 different forecast horizons during 1989-2004, we find that the survey forecasts do not have much value when the horizon goes beyond 18 months. Using two alternative approaches to measure the flow of new information in fixed-target survey forecasts, we found that the biggest improvement in forecasting performance comes when the forecast horizon is around 14 months. The dynamics of information accumulation over forecast horizons can provide both the forecasters and their clients with an important clue in their selection of the timing and frequency in the use of forecasting services. The limits to forecasting that these private market forecasters exhibit are indicative of the current state of macroeconomic foresight.

Suggested Citation

  • Kajal Lahiri & Gultekin Isiklar, 2006. "How Far Ahead Can We Forecast? Evidence From Cross-country Surveys," Discussion Papers 06-04, University at Albany, SUNY, Department of Economics.
  • Handle: RePEc:nya:albaec:06-04
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    1. Lovell, Michael C, 1986. "Tests of the Rational Expectations Hypothesis," American Economic Review, American Economic Association, vol. 76(1), pages 110-124, March.
    2. Oller, Lars-Erik, 1985. "How far can changes in general business activity be forecasted?," International Journal of Forecasting, Elsevier, vol. 1(2), pages 135-141.
    3. de Gooijer, Jan G. & Klein, Andre, 1992. "On the cumulated multi-step-ahead predictions of vector autoregressive moving average processes," International Journal of Forecasting, Elsevier, vol. 7(4), pages 501-513, March.
    4. 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.
    5. N. Gregory Mankiw & Ricardo Reis, 2002. "Sticky Information versus Sticky Prices: A Proposal to Replace the New Keynesian Phillips Curve," The Quarterly Journal of Economics, Oxford University Press, vol. 117(4), pages 1295-1328.
    6. John F. Muth, 1985. "Properties of Some Short-run Business Forecasts," Eastern Economic Journal, Eastern Economic Association, vol. 11(3), pages 200-210, Jul-Sep.
    7. Jacob A. Mincer, 1969. "Models of Adaptive Forecasting," NBER Chapters, in: Economic Forecasts and Expectations: Analysis of Forecasting Behavior and Performance, pages 83-111, National Bureau of Economic Research, Inc.
    8. Gultekin Isiklar & Kajal Lahiri & 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, September.
    9. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    10. Oller, Lars-Erik & Barot, Bharat, 2000. "The accuracy of European growth and inflation forecasts," International Journal of Forecasting, Elsevier, vol. 16(3), pages 293-315.
    11. Michael Artis & Massimiliano Marcellino, 2001. "Fiscal forecasting: The track record of the IMF, OECD and EC," Econometrics Journal, Royal Economic Society, vol. 4(1), pages 20-36.
    12. 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.
    13. Francis X. Diebold & Lutz Kilian, 2001. "Measuring predictability: theory and macroeconomic applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(6), pages 657-669.
    14. David I. Harvey & Stephen J. Leybourne & Paul Newbold, 2001. "Analysis of a panel of UK macroeconomic forecasts," Econometrics Journal, Royal Economic Society, vol. 4(1), pages 37-55.
    15. Mills, Terence C. & Pepper, Gordon T., 1999. "Assessing the forecasters: an analysis of the forecasting records of the Treasury, the London Business School and the National Institute," International Journal of Forecasting, Elsevier, vol. 15(3), pages 247-257, July.
    16. Artis, Michael J & Zhang, W, 1997. "International Business Cycles and the ERM: Is There a European Business Cycle?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 2(1), pages 1-16, January.
    17. N. Gregory Mankiw & Matthew D. Shapiro, 1986. "News or Noise? An Analysis of GNP Revisions," NBER Working Papers 1939, National Bureau of Economic Research, Inc.
    18. Granger, Clive W J, 1996. "Can We Improve the Perceived Quality of Economic Forecasts?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(5), pages 455-473, Sept.-Oct.
    19. Roy Batchelor, 2001. "How useful are the forecasts of intergovernmental agencies? The IMF and OECD versus the consensus," Applied Economics, Taylor & Francis Journals, vol. 33(2), pages 225-235.
    20. Vuchelen, Jef & Gutierrez, Maria-Isabel, 2005. "A direct test of the information content of the OECD growth forecasts," International Journal of Forecasting, Elsevier, vol. 21(1), pages 103-117.
    21. Grace Juhn & Prakash Loungani, 2002. "Further Cross-Country Evidence on the Accuracy of the Private Sector's Output Forecasts," IMF Staff Papers, Palgrave Macmillan, vol. 49(1), pages 1-4.
    22. Sims, Christopher A., 2003. "Implications of rational inattention," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 665-690, April.
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