Abstract
AbstractIn 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 UK and the USA. 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.
Funder
Jan Wallanders och Tom Hedelius Stiftelse samt Tore Browaldhs Stiftelse
Örebro University
Publisher
Springer Science and Business Media LLC
Subject
Economics and Econometrics,Social Sciences (miscellaneous),Mathematics (miscellaneous),Statistics and Probability
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献