evaluating real-time var forecasts with an informative democratic prior (replication data)

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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Suggested Citation

Wright, Jonathan H. (2013): EVALUATING REAL-TIME VAR FORECASTS WITH AN INFORMATIVE DEMOCRATIC PRIOR (replication data). Version: 1. Journal of Applied Econometrics. Dataset. http://dx.doi.org/10.15456/jae.2022320.0732855917