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When does information on forecast variance improve the performance of a combined forecast?

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  • Conrad, Christian

Abstract

We show that the consensus forecast can be biased if some forecasters minimize an asymmetric loss function and the DGP features conditional heteroscedasticity. The time-varying bias depends on the variance of the process. As a consequence, the information from the ex-ante variation of forecasts can be used to improve the predictive accuracy of the combined forecast. Forecast survey data from the Euro area and the U.S. confirm the implications of the theoretical model.

Suggested Citation

  • Conrad, Christian, 2017. "When does information on forecast variance improve the performance of a combined forecast?," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168200, Verein für Socialpolitik / German Economic Association.
    • Handle: RePEc:zbw:vfsc17:168200
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    References listed on IDEAS

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    More about this item

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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