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The accuracy and efficiency of the Consensus Forecasts: A further application and extension of the pooled approach

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  • Ager, P.
  • Kappler, M.
  • Osterloh, S.

Abstract

This paper analyses the performance of consensus forecasts, published by Consensus Economics, for 12 countries over the period from 1996 to 2006 regarding bias and information efficiency. A pooled approach is employed which permits the evaluation of all forecasts for each target variable over 24 horizons simultaneously. It is shown how the pooled approach needs to be set up in order to accommodate the forecasting scheme of the consensus forecasts. Furthermore, the pooled approach is extended by a sequential test for detecting the critical horizon after which the forecast should be regarded as biased. Moreover, heteroscedasticity in the form of target-year-specific variances of macroeconomic shocks is taken into account. The results show that in the analysed period, which was characterised by pronounced macroeconomic shocks, several countries show biased forecasts, especially with forecast horizons of more than 12 months. In addition, information efficiency has to be rejected in almost all cases.

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Bibliographic Info

Article provided by Elsevier in its journal International Journal of Forecasting.

Volume (Year): 25 (2009)
Issue (Month): 1 ()
Pages: 167-181

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Handle: RePEc:eee:intfor:v:25:y:2009:i:1:p:167-181

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Web page: http://www.elsevier.com/locate/ijforecast

Related research

Keywords: Evaluating forecasts Business cycle forecasting Inflation forecasting Consensus forecasts Bias and efficiency;

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  1. Isiklar, Gultekin & Lahiri, Kajal, 2007. "How far ahead can we forecast? Evidence from cross-country surveys," International Journal of Forecasting, Elsevier, vol. 23(2), pages 167-187.
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  3. 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.
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  7. Batchelor, Roy, 2007. "Bias in macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 23(2), pages 189-203.
  8. Isiklar, Gultekin, 2005. "On aggregation bias in fixed-event forecast efficiency tests," Economics Letters, Elsevier, vol. 89(3), pages 312-316, December.
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  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. Davies, Anthony & Lahiri, Kajal, 1995. "A new framework for analyzing survey forecasts using three-dimensional panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 205-227, July.
  13. Fildes, Robert & Stekler, Herman, 2002. "Reply to the comments on 'The state of macroeconomic forecasting'," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 503-505, December.
  14. Fred Joutz & Michael P. Clements & Herman O. Stekler, 2007. "An evaluation of the forecasts of the federal reserve: a pooled approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(1), pages 121-136.
  15. Stekler, H.O., 2007. "The future of macroeconomic forecasting: Understanding the forecasting process," International Journal of Forecasting, Elsevier, vol. 23(2), pages 237-248.
  16. Jacob A. Mincer & Victor Zarnowitz, 1969. "The Evaluation of Economic Forecasts," NBER Chapters, in: Economic Forecasts and Expectations: Analysis of Forecasting Behavior and Performance, pages 1-46 National Bureau of Economic Research, Inc.
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  18. Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119.
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