Combining Survey Long-Run Forecasts and Nowcasts with BVAR Forecasts Using Relative Entropy
Ellis Tallman () and
No 1809, Working Papers (Old Series) from Federal Reserve Bank of Cleveland
This paper constructs hybrid forecasts that combine both short- and long-term conditioning information from external surveys with forecasts from a standard fixed-coefficient vector autoregression (VAR) model. Specifically, we use relative entropy to tilt one-step ahead and long-horizon VAR forecasts to match the nowcast and long-horizon forecast from the Survey of Professional Forecasters. The results indicate meaningful gains in multi-horizon forecast accuracy relative to model forecasts that do not incorporate long-term survey conditions. The accuracy gains are achieved for a range of variables, including those that are not directly tilted but are affected through spillover effects from tilted variables. The forecast accuracy gains for inflation are substantial, statistically significant, and are competitive with the forecast accuracy from both time-varying VARs and univariate benchmarks. We view our proposal as an indirect approach to accommodating structural change and moving end points.
Keywords: Bayesian analysis; relative entropy; survey forecasts; nowcasts; density forecasts; real-time data (search for similar items in EconPapers)
JEL-codes: C11 C32 C53 E17 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-for and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
https://doi.org/10.26509/frbc-wp-201809 Full text (text/html)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:fip:fedcwp:1809
Ordering information: This working paper can be ordered from
Access Statistics for this paper
More papers in Working Papers (Old Series) from Federal Reserve Bank of Cleveland Contact information at EDIRC.
Bibliographic data for series maintained by 4D Library ().