Priors for the Long Run

Domenico Giannone, Michele Lenza and Giorgio Primiceri

Journal of the American Statistical Association, 2019, vol. 114, issue 526, 565-580

Abstract: We propose a class of prior distributions that discipline the long-run behavior of vector autoregressions (VARs). These priors can be naturally elicited using economic theory, which provides guidance on the joint dynamics of macroeconomic time series in the long run. Our priors for the long run are conjugate, and can thus be easily implemented using dummy observations and combined with other popular priors. In VARs with standard macroeconomic variables, a prior based on the long-run predictions of a wide class of theoretical models yields substantial improvements in the forecasting performance. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.

Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (42)

Downloads: (external link)
http://hdl.handle.net/10.1080/01621459.2018.1483826 (text/html)
Access to full text is restricted to subscribers.

Related works:
Working Paper: Priors for the long run (2018)
Working Paper: Priors for the long run (2017)
Working Paper: Priors for the Long Run (2016)
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:taf:jnlasa:v:114:y:2019:i:526:p:565-580

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/UASA20

DOI: 10.1080/01621459.2018.1483826

Access Statistics for this article

Journal of the American Statistical Association is currently edited by Xuming He, Jun Liu, Joseph Ibrahim and Alyson Wilson

More articles in Journal of the American Statistical Association from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().