Evaluating real-time VAR forecasts with an informative democratic prior

Jonathan Wright

No 10-19, Working Papers from Federal Reserve Bank of Philadelphia

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.

Keywords: Forecasting; Real-time data (search for similar items in EconPapers)
Date: 2010
New Economics Papers: this item is included in nep-cba, nep-ecm, nep-ets and nep-for
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.philadelphiafed.org/-/media/frbp/asset ... ers/2010/wp10-19.pdf (application/pdf)

Related works:
Journal Article: EVALUATING REAL‐TIME VAR FORECASTS WITH AN INFORMATIVE DEMOCRATIC PRIOR (2013)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:fip:fedpwp:10-19

Ordering information: This working paper can be ordered from

Access Statistics for this paper

More papers in Working Papers from Federal Reserve Bank of Philadelphia Contact information at EDIRC.
Bibliographic data for series maintained by Beth Paul ().