Modelling Okun’s law: Does non-Gaussianity matter?

Tamas Kiss, Hoang Nguyen and Pär Österholm

Empirical Economics, 2023, vol. 64, issue 5, No 9, 2183-2213

Abstract: 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 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.

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)
Date: 2023
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DOI: 10.1007/s00181-022-02309-2

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