The Volatility Spillover of Global Oil Price Uncertainty

Kamil Pícha, Lucie Tichá, Sanat Chuponov, Jasur Ataev, Dilshod Hudayberganov and Bekhzod Kuziboev
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Kamil Pícha: Department of Trade, Faculty of Economics, Tourism, and Languages, University of South Bohemia, Czech Republic
Lucie Tichá: Department of Trade, Faculty of Economics, Tourism, and Languages, University of South Bohemia, Czech Republic
Sanat Chuponov: Department of Accounting, Non-government Educational Institution Mamun University, Khiva, Uzbekistan
Jasur Ataev: Department of Economics, Urgench State University, Urgench, Uzbekistan
Dilshod Hudayberganov: Department of Economics, Urgench State University, Urgench, Uzbekistan
Bekhzod Kuziboev: Department of Economics, Urgench State University, Urgench, Uzbekistan; & University of Tashkent for Applied Sciences, Tashkent, Uzbekistan

International Journal of Energy Economics and Policy, 2024, vol. 14, issue 3, 619-624

Abstract: This manuscript, for the first time, analyses the volatility spillover of oil price uncertainty in the world using data from oil price uncertainty recently developed by Abdul and Qureshi (2023), spanning the time 1996-2019 on a monthly frequency. ARCH/GARCH (Autoregressive Conditional Heteroskedasticity and Generalized Autoregressive Conditional Heteroskedasticity) models are employed as an econometric tool. The findings suggest that ARCH model is more consistent than GARCH model in assessing the volatility of oil price uncertainty in the world. The results show that the volatility of oil price uncertainty is high in the world. The transition to renewable energy sources is proposed as a way to resist unexpected oil shocks since the production of renewables does not depend on the fluctuations of oil prices. Consequently, uncertainties in the oil price do not hinder economic activities.

Keywords: Oil Price; Uncertainty; Volatility; Autoregressive Conditional Heteroskedasticity; Generalized Autoregressive Conditional Heteroskedasticity (search for similar items in EconPapers)
JEL-codes: C01 C22 O13 (search for similar items in EconPapers)
Date: 2024
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