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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, Philipp
  • Kappler, Marcus
  • Osterloh, Steffen

Abstract

In this paper we analyze the macroeconomic forecasts of the Consensus Forecasts 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 adjusted in order to accommodate the forecasting scheme of the Consensus Forecasts. Furthermore, the pooled approach is extended by a sequential test with the purpose of detecting the critical horizon after which the forecast should be regarded as biased. Moreover, heteroscedasticity in the form of year-specific variances of macroeconomic shocks is taken into account. The results show that in the analyzed period which was characterized by pronounced macroeconomic shocks, several countries show biased forecasts, especially with forecasts covering more than 12 months. In addition, information efficiency has to be rejected in almost all cases.

Suggested Citation

  • 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.
  • Handle: RePEc:zbw:zewdip:6655
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    References listed on IDEAS

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    Keywords

    business cycle forecasting; forecast evaluation; Consensus Forecasts;

    JEL classification:

    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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