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Oil price uncertainty and the business cycle: Accounting for the influences of global supply and demand within a VAR GARCH-in-mean framework

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  • Christopher Thiem

Abstract

This article reinvestigates the influence of oil price uncertainty on real economic activity in the United States using a four-variable VAR GARCH-in-mean asymmetric BEKK model. In contrast to previous studies in this area, the analysis focuses on business cycle fluctuations and we control for global supply and demand factors that might affect the real price of oil, its volatility as well as the US economy. We find that – even after accounting for these factors – oil price uncertainty still has a highly significant negative influence on the US business cycle. Our computations show that the effect is economically important during several periods, mostly after a significant variance shift in the mid-1980s. We simultaneously estimate the effect on the global business cycle but find that it is comparatively weak. Finally, significant spillover effects in the GARCH model suggest that oil price volatility is a gauge and channel of transmission of more general macroeconomic shocks and uncertainty. These linkages are particularly strong in case of unexpected bad news.

Suggested Citation

  • Christopher Thiem, 2018. "Oil price uncertainty and the business cycle: Accounting for the influences of global supply and demand within a VAR GARCH-in-mean framework," Applied Economics, Taylor & Francis Journals, vol. 50(34-35), pages 3735-3751, July.
    • Handle: RePEc:taf:applec:v:50:y:2018:i:34-35:p:3735-3751
    DOI: 10.1080/00036846.2018.1436142
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    Cited by:

    1. Zhou, Jinlan & Li, Zhensheng & Liu, Zhuang, 2025. "Oil market uncertainty and China's macroeconomy: Causality-in-quantiles test and quantile spillover effects analysis," Energy Economics, Elsevier, vol. 148(C).
    2. Gürkan Bozma & Murat Akadg & Rahman Aydin, 2021. "Dynamic Relationships between Oil Price, Inflation and Economic Growth: A VARMA, GARCH-in-mean, asymmetric BEKK Model for Turkey," Economics Bulletin, AccessEcon, vol. 41(3), pages 1266-1281.
    3. Alao, Rasheed O. & Payaslioglu, Cem, 2021. "Oil price uncertainty and industrial production in oil-exporting countries," Resources Policy, Elsevier, vol. 70(C).
    4. Chang, Lei & Baloch, Zulfiqar Ali & Saydaliev, Hayot Berk & Hyder, Mansoor & Dilanchiev, Azer, 2022. "Testing oil price volatility during Covid-19: Global economic impact," Resources Policy, Elsevier, vol. 78(C).
    5. Cheng, Dong & Shi, Xunpeng & Yu, Jian & Zhang, Dayong, 2019. "How does the Chinese economy react to uncertainty in international crude oil prices?," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 147-164.
    6. Śmiech, Sławomir & Papież, Monika & Rubaszek, Michał & Snarska, Małgorzata, 2021. "The role of oil price uncertainty shocks on oil-exporting countries," Energy Economics, Elsevier, vol. 93(C).
    7. Dąbrowski, Marek A. & Papież, Monika & Rubaszek, Michał & Śmiech, Sławomir, 2022. "The role of economic development for the effect of oil market shocks on oil-exporting countries. Evidence from the interacted panel VAR model," Energy Economics, Elsevier, vol. 110(C).
    8. Tan, Yan & Uprasen, Utai, 2023. "Asymmetric effects of oil price shocks on income inequality in ASEAN countries," Energy Economics, Elsevier, vol. 126(C).

    More about this item

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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