Abstract: While oil consumption is more visible in rich economies, it is also increasing in emerging economies. Yet South Africa, as a large oil importer, keeps facing growing oil consumption and it is projected to remain vulnerable to oil price fluctuations irrespective of the stage of their economic cycle. As such, the purpose of this paper is to investigate the relationship between various uncertainty measures and oil price fluctuations in South Africa from 2000M1 to 2020M3. Our uncertainty indicators recognized numerous points of view, including climate policy uncertainty (CPU), financial globalization uncertainty (FGU), and economic policy uncertainty (EPU). The Quantile Auto Regressive Distributive Lag (QARDL) model is applied to assess the quantile-based relationship of the variables. Besides, the non-linear autoregressive distributed lag (NARDL) is also applied to investigate the asymmetric effect. The QARDL results point out that the CPU, FGU, and EPU contribute to the different quantiles of oil price shocks. Precisely, the CPU has substantially and persistently become an essential determinant influencing oil price shocks in South Africa. The NARDL results aligned with the positive relationship of all the determinants on OPS. Policymakers should consequently pay greater attention to climate policy uncertainty and financial globalization uncertainty, given their significant influence on oil price shocks.

Keywords: oil price shocks, quantile ARDL, NARDL, Uncertainties, climate policy, economic policy.

JEL codes: F64, F65.

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