Abstract
Our paper proposes a novel measure of global energy market uncertainty and studies its impact on oil prices. The current literature primarily relies on a single or small number of observable variables, or general macroeconomic uncertainty (JLN) and economic policy uncertainty (EPU) indices to reflect energy market uncertainty. Using a Factor Augmented Vector Autoregression model (FAVAR), we construct time-varying global energy market uncertainty in a data-rich environment. Our estimates show variations from JLN and EPU proxies. The results reveal that real oil prices respond strongly to our proposed aggregate energy market uncertainty shocks. We also find heterogeneous responses to different types and magnitudes of uncertainty shocks. The real price of oil is affected the most under unexpected strong demand for alternative energy sources scenario.
Highlights
There is growing evidence linking climate change with escalated frequency and/or magnitude of extreme weather-related events, that constitute substantial risks to firms and society at large (IPCC, 2018)
While the focus of this paper is to construct energy market uncer tainty proxies, another contribution is to capture the impulse responses of oil prices to shocks in uncertainty measures using both Bayesian Structural VAR (B-SVAR) and Quantile SVAR (Q-SVAR) models
Following Caraiani et al (2021), simulations of the above scenarios are carried out using a Q-SVAR model, where quantiles-based impulse response functions (IRFs) of oil price following a shock to the alternative energy demand uncertainty can be estimated
Summary
There is growing evidence linking climate change with escalated frequency and/or magnitude of extreme weather-related events (e.g., heatwaves, hurricanes, floods and storms), that constitute substantial risks to firms and society at large (IPCC, 2018). One factor that has received less attention is the impact of uncertainty raised from the global energy market on oil prices (Van Robays, 2016). We propose a different measure of global energy market specific uncertainty. Our energy market uncertainty indicator is not reliant on a specific theoretical model, it measures the common fluctuations in uncertainty across 216 series, ranging from energy prices, conventional and alternative energy demand, fossil-fuel and alternative energy supply, inventories, key macroeconomic and financial variables. While the focus of this paper is to construct energy market uncer tainty proxies, another contribution is to capture the impulse responses of oil prices to shocks in uncertainty measures using both Bayesian Structural VAR (B-SVAR) and Quantile SVAR (Q-SVAR) models.
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