Modelling Okun’s Law – Does non-Gaussianity Matter?

Tamas Kiss, Hoang Nguyen and Pär Österholm

No 2022:1, Working Papers from Örebro University, School of Business

Abstract: In this paper, we analyse Okun’s law – a relation between the change in the unemployment rate and GDP growth – using data from Australia, the euro area, the United Kingdom and the United States. More specifically, we assess the relevance of non-Gaussianity when mod-elling the relation. This is done in a Bayesian VAR framework with stochastic volatility where we allow the different models’ error distributions to have heavier-than-Gaussian tails and skewness. Our results indicate that accounting for heavy tails yields improvements over a Gaussian specification in some cases, whereas skewness appears less fruitful. In terms of dynamic effects, a shock to GDP growth has robustly negative effects on the change in the unemployment rate in all four economies.

Keywords: Bayesian VAR; Heavy tails; GDP growth; Unemployment (search for similar items in EconPapers)
JEL-codes: C11 C32 C52 E32 (search for similar items in EconPapers)
Pages: 25 pages
Date: 2022-01-17
New Economics Papers: this item is included in nep-cwa, nep-mac and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.oru.se/globalassets/oru-sv/institution ... rs2022/wp-1-2022.pdf Full text (application/pdf)

Related works:
Journal Article: Modelling Okun’s law: Does non-Gaussianity matter? (2023)
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:hhs:oruesi:2022_001

Access Statistics for this paper

More papers in Working Papers from Örebro University, School of Business Örebro University School of Business, SE - 701 82 ÖREBRO, Sweden. Contact information at EDIRC.
Bibliographic data for series maintained by ().