How does oil price uncertainty affect output in the Central and Eastern European economies? – the Bayesian-based approaches

Abstract

Purpose – This paper aims to investigate how oil price uncertainty affects real gross domestic product (GDP) and industrial production in eight Central and Eastern European countries (CEEC). Design/methodology/approach – In the research process, the authors use the Bayesian method of inference for the two applied methodologies – Markov switching generalized autoregressive conditional heteroscedasticity (GARCH) model and quantile regression. Findings – The results clearly indicate that oil price uncertainty has a low effect on output in moderate market conditions in the selected countries. On the other hand, in the phases of contraction and expansion, which are portrayed by the tail quantiles, the authors find negative and positive Bayesian quantile parameters, which are relatively high in magnitude. This implies that in periods of deep economic crises, an increase in the oil price uncertainty reduces output, amplifying in this way recession pressures in the economy. Contrary, when the economy is in expansion, oil price uncertainty has no influence on the output. The probable reason lies in the fact that the negative effect of oil volatility is not strong enough in the expansion phase to overpower all other positive developments which characterize a growing economy. Also, evidence suggests that increased oil uncertainty has a more negative effect on industrial production than on real GDP, whereas industrial share in GDP plays an important role in how strong some CEECs are impacted by oil uncertainty. Originality/value – This paper is the first one that investigates the spillover effect from oil uncertainty to output in CEEC.

Keywords

• Output
• Bayesian quantile regression
• Bayesian MS-GARCH
• Central and Easter European countries
• Oil uncertainty