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Evaluating real-time VAR forecasts with an informative democratic prior

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  • Jonathan H. Wright
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    Abstract

    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.

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    File URL: http://www.philadelphiafed.org/research-and-data/publications/working-papers/2010/wp10-19.pdf
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    Bibliographic Info

    Paper provided by Federal Reserve Bank of Philadelphia in its series Working Papers with number 10-19.

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    Date of creation: 2010
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    Handle: RePEc:fip:fedpwp:10-19

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    Keywords: Forecasting ; Real-time data;

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