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The global supply pressure and oil supply–demand shocks: A time-scale and quantile analysis

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  • Wu, Bangzheng

Abstract

In the context of globalization, the global supply chain faces many challenges. What is the relationship between the global supply chain and the supply–demand structure of crude oil? This paper explores the impact mechanism between global supply chain pressure (GSCPI) and crude oil supply–demand shocks from a time-scale and quantile-based perspective. We select the oil supply–demand shock indices, which include oil supply shocks (S1) and oil demand shocks related to economic activities (D1), consumption (D2), and inventory (D3). GSCPI has a significant effect on S1 and D1 over multiple periods, especially during economic turmoil and crisis. Additionally, quantile-based tests show that GSCPI on S1 and D1 is particularly significant under extreme conditions, whereas the effect of D1 on GSCPI is more significant at lower quantiles. The effect of GSCPI on D2 is significant when supply chain pressure is moderate. The effect of GSCPI on D3 is strengthened under extreme economic stress, whereas the direct effect of D3 on GSCPI is weaker. As a whole, GSCPI has an important effect on the crude oil supply and demand under different economic conditions, while the reverse effect is relatively weak and complex. Therefore, supply chain managers can improve the stability and timeliness of the supply chain by considering crude oil supply–demand shocks. Moreover, energy-related policy-makers should pay attention to changes in the supply chain and take timely remedial measures.

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  • Wu, Bangzheng, 2025. "The global supply pressure and oil supply–demand shocks: A time-scale and quantile analysis," Energy Economics, Elsevier, vol. 147(C).
    • Handle: RePEc:eee:eneeco:v:147:y:2025:i:c:s0140988325003792
    DOI: 10.1016/j.eneco.2025.108555
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    Keywords

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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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