Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/262150 
Erscheinungsjahr: 
2022
Schriftenreihe/Nr.: 
Working Paper No. 1/2022
Verlag: 
Örebro University School of Business, Örebro
Zusammenfassung: 
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 modelling 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.
Schlagwörter: 
Bayesian VAR
Heavy tails
GDP growth
Unemployment
JEL: 
C11
C32
C52
E32
Dokumentart: 
Working Paper

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