Evaluating real-time VAR forecasts with an informative democratic prior
AbstractThis 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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Bibliographic InfoPaper provided by Federal Reserve Bank of Philadelphia in its series Working Papers with number 10-19.
Date of creation: 2010
Date of revision:
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-06-26 (All new papers)
- NEP-CBA-2010-06-26 (Central Banking)
- NEP-ECM-2010-06-26 (Econometrics)
- NEP-ETS-2010-06-26 (Econometric Time Series)
- NEP-FOR-2010-06-26 (Forecasting)
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