Oil market uncertainty and China's macroeconomy: Causality-in-quantiles test and quantile spillover effects analysis

This paper investigates the nonlinear causality and spillover effects between international crude oil market uncertainty and China's macroeconomy. The high-dimensional factor non-anticipated volatility model weighted by Minimum Spanning Tree network centrality is proposed to measure oil supply uncertainty, oil demand uncertainty, and oil precautionary demand uncertainty. We apply the non-parametric quantile Granger causality test method to examine the causality between classified oil market uncertainty and China's macroeconomy. Empirical results confirm that all three kinds of oil market uncertainty have a significant impact on the mean and variance of China's macroeconomy at the vast majority of quantile levels. The volatility spillover index method based on the quantile vector autoregressive model is further applied to explore the spillover effects between oil market uncertainty and the macroeconomy from both static and dynamic perspectives. We find that the static total spillover index exhibits a U-shaped pattern, indicating the risk contagion between classified oil market uncertainty and China's macroeconomy increases as economic conditions become more extreme. The dynamic spillover effects analysis reflects that the main risk transmitter to China's macroeconomy varies at different extreme episodes. Our findings have implications for policymakers to mitigate the risk contagion from oil market uncertainty and enhance the risk prevention system.