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EVALUATING REAL-TIME VAR FORECASTS WITH AN INFORMATIVE DEMOCRATIC PRIOR

Authors

  • Jonathan H. Wright

    Corresponding author
    1. Department of Economics, Johns Hopkins University, Baltimore, MD, USA
    • Correspondence to: Jonathan Wright, Department of Economics, Johns Hopkins University, 3400 N Charles St, Baltimore MD 21218, USA. E-mail: wrightj@jhu.edu

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SUMMARY

This paper proposes Bayesian forecasting in a vector autoregression using a democratic prior. This prior is chosen to match the predictions of survey respondents. In particular, the unconditional mean for each series in the vector autoregression is centered around long-horizon survey forecasts. Heavy shrinkage toward the democratic prior is found to give good real-time predictions of a range of macroeconomic variables, as these survey projections are good at quickly capturing endpoint shifts. Copyright © 2012 John Wiley & Sons, Ltd.

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