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Evaluating German business cycle forecasts under an asymmetric loss function

  • Jörg Döpke


  • Ulrich Fritsche


  • Boriss Siliverstovs


Based on annual data for growth and inflation forecasts for Germany covering the 1970-2007 period and up to 17 different forecasts per year, we test for a possible asymmetry of the forecasters’ loss function and estimate the degree of asymmetry for each forecasting institution using the approach of Elliot et al. (2005). Furthermore, we test for the rationality of the forecasts under the assumption of a possibly asymmetric loss function and for the features of an optimal forecast under the assumption of a generalised loss function. We find evidence of the existence of an asymmetric loss function of German forecasters only in the case of pooled data and a quad-quad loss function. We can reject the hypothesis of rationality of the growth forecasts based on a pooled dataset, but not on data for single institutions. The rationality of inflation forecasts is frequently rejected in the case of single institutions, and also for pooled data.

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Article provided by OECD Publishing,Centre for International Research on Economic Tendency Surveys in its journal OECD Journal: Journal of Business Cycle Measurement and Analysis.

Volume (Year): 2010 (2010)
Issue (Month): 1 ()
Pages: 1-18

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Handle: RePEc:oec:stdkab:5kmlj35rx10s
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  1. Batchelor, Roy & Peel, David A., 1998. "Rationality testing under asymmetric loss," Economics Letters, Elsevier, vol. 61(1), pages 49-54, October.
  2. G. A. Christodoulakis & E. C. Mamatzakis, 2009. "Assessing the prudence of economic forecasts in the EU," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(4), pages 583-606.
  3. Hansen, Bruce E & West, Kenneth D, 2002. "Generalized Method of Moments and Macroeconomics," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 460-69, October.
  4. Artis, M. & Marcellino, M., 1999. "Fiscal Forecasting: the Track Record of the IMF, OECD and EC," Economics Working Papers eco99/22, European University Institute.
  5. Patton, Andrew J. & Timmermann, Allan, 2007. "Testing Forecast Optimality Under Unknown Loss," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1172-1184, December.
  6. Christoffersen, Peter F. & Diebold, Francis X., 1997. "Optimal Prediction Under Asymmetric Loss," Econometric Theory, Cambridge University Press, vol. 13(06), pages 808-817, December.
  7. Graham Elliott & Ivana Komunjer & Allan Timmermann, 2005. "Biases In Macroeconomic Forecasts: Irrationality Or Asymmetric Loss?," CAMA Working Papers 2005-14, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  8. Ager, Philipp & Kappler, Marcus & Osterloh, Steffen, 2007. "The Accuracy and Efficiency of the Consensus Forecasts: A Further Application and Extension of the Pooled Approach," ZEW Discussion Papers 07-058, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
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  10. Jonas Dovern & Johannes Weisser, 2008. "Are They Really Rational? Assessing Professional Macro-Economic Forecasts from the G7-Countries," Kiel Working Papers 1447, Kiel Institute for the World Economy.
  11. Osterloh, Steffen, 2006. "Accuracy and properties of German business cycle forecasts," ZEW Discussion Papers 06-87, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
  12. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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  15. George A. Christodoulakis & Emmanuel C. Mamatzakis, 2008. "An assessment of the EU growth forecasts under asymmetric preferences," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(6), pages 483-492.
  16. Alan S. Blinder, 1999. "Central Banking in Theory and Practice," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262522608, June.
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