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CONSTRUCTING OPTIMAL DENSITY FORECASTS FROM POINT FORECAST COMBINATIONS

Authors

  • Wagner Piazza Gaglianone,

    1. Research Department, Banco Central do Brasil, Rio de Janeiro, Brazil
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  • Luiz Renato Lima

    Corresponding author
    1. Department of Economics, University of Tennessee at Knoxville, TN, USA
    2. Federal University of Paraiba, Brazil
    • Correspondence to: Luiz Renato Lima, Department of Economics, University of Tennessee at Knoxville, 527A Stokely Management Center, TN 37996-0550, USA.

      E-mail: llima@utk.edu

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SUMMARY

Decision makers often observe point forecasts of the same variable computed, for instance, by commercial banks, IMF and the World Bank, but the econometric models used by such institutions are frequently unknown. This paper shows how to use the information available on point forecasts to compute optimal density forecasts. Our idea builds upon the combination of point forecasts under general loss functions and unknown forecast error distributions. We use real-time data to forecast the density of US inflation. The results indicate that the proposed method materially improves the real-time accuracy of density forecasts vis-à-vis those from the (unknown) individual econometric models. Copyright © 2013 John Wiley & Sons, Ltd.

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