EconPapers    
Economics at your fingertips  
 

Data-based priors for vector autoregressions with drifting coefficients

Dimitris Korobilis

No 2014-022, SIRE Discussion Papers from Scottish Institute for Research in Economics (SIRE)

Abstract: This paper proposes full-Bayes priors for time-varying parameter vector autoregressions (TVP-VARs) which are more robust and objective than existing choices proposed in the literature. We formulate the priors in a way that they allow for straightforward posterior computation, they require minimal input by the user, and they result in shrinkage posterior representations, thus, making them appropriate for models of large dimensions. A comprehensive forecasting exercise involving TVP-VARs of different dimensions establishes the usefulness of the proposed approach.

Keywords: TVP-VAR; shrinkage; data-based prior; forecasting (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ets and nep-for
Date: 2014-01
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9) Track citations by RSS feed

Downloads: (external link)
http://hdl.handle.net/10943/567

Related works:
Working Paper: Data-based priors for vector autoregressions with drifting coefficients (2014) Downloads
Working Paper: Data-based priors for vector autoregressions with drifting coefficients (2014) Downloads
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:edn:sirdps:567

Access Statistics for this paper

More papers in SIRE Discussion Papers from Scottish Institute for Research in Economics (SIRE) 31 Buccleuch Place, EH8 9JT, Edinburgh. Contact information at EDIRC.
Bibliographic data for series maintained by Research Office ().

 
Page updated 2019-11-13
Handle: RePEc:edn:sirdps:567