Managing GDP Tail Risk

Thibaut Duprey and Alexander Ueberfeldt

Staff Working Papers from Bank of Canada

Abstract: We propose a novel framework to analyze how policy-makers can manage risks to the median projection and risks specific to the tail of gross domestic product (GDP) growth. By combining a quantile regression of GDP growth with a vector autoregression, we show that monetary and macroprudential policy shocks can reduce credit growth and thus GDP tail risk. So policymakers concerned about GDP tail risk would choose a tighter policy stance at the expense of macroeconomic stability. Using Canadian data, we show how our framework can add tail event information to projection models that ignore them and give policy-makers a tool to communicate the trade-offs they face.

Keywords: Central bank research; Economic models; Financial stability; Financial system regulation and policies; Interest rates; Monetary Policy; Monetary policy framework (search for similar items in EconPapers)
JEL-codes: D8 E44 E52 E58 G01 (search for similar items in EconPapers)
Pages: 66 pages
Date: 2020-01
New Economics Papers: this item is included in nep-cba, nep-fdg, nep-mac and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (21)

Downloads: (external link)
https://www.bankofcanada.ca/wp-content/uploads/2020/01/swp2020-3.pdf Full text (application/pdf)

Related works:
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:bca:bocawp:20-3

Access Statistics for this paper

More papers in Staff Working Papers from Bank of Canada 234 Wellington Street, Ottawa, Ontario, K1A 0G9, Canada. Contact information at EDIRC.
Bibliographic data for series maintained by ().