4.6 Article

The Dynamic Correlation between China's Policy Uncertainty and the Crude Oil Market: A Time-varying Analysis

Journal

EMERGING MARKETS FINANCE AND TRADE
Volume 58, Issue 3, Pages 692-709

Publisher

ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
DOI: 10.1080/1540496X.2020.1837106

Keywords

Policy uncertainty; crude oil returns; dynamic correlation; China; Time-varying parameter structural vector autoregression model (TVP-SVAR)

Funding

  1. Natural Science Foundation of Jiangxi Province of China [20202BAB201006]

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This research examines the dynamic correlation between China's policy uncertainty and crude oil markets. The results show that the correlation is time-varying and non-linear. The independence between policy uncertainty and oil returns varies more constantly, while the interaction between policy uncertainty and global oil production varies at a lower frequency. The different types of policy uncertainty also have different associations with global oil returns.
This research investigates the dynamic correlation between China's policy uncertainty and the crude oil markets (i.e. domestic and international markets) using monthly time-series data from May 2003 to December 2018. To consider the non-linear and dynamic properties, we adopt the time-varying parameter structural vector autoregression model (TVP-SVAR) to estimate the dynamic correlations between the time series. By employing four categorical policy uncertainty indices, i.e. monetary policy uncertainty index (MYPU), fiscal policy uncertainty index (FLPU), exchange rate policy uncertainty index (EXER), and trade policy uncertainty index (TEPU), our results reveal that the correlation between China's policy uncertainty and real crude oil returns is time-varying and non-linear. Specifically, the independence between policy uncertainty and oil returns varies more constantly and at a high degree while the time-varying interaction between policy uncertainty and global oil production (global economic activity) varies at a lower frequency and at a low level. Furthermore, regarding the associations between categorical policy uncertainty and global oil returns, the average correlation of EXER (negative) is the strongest one, followed by FLPU (negative), then MYPU (positive), and finally TEPU (negative). Moreover, it is noteworthy that WTI (Daqing) crude oil prices are utilized to increase the robustness of our conclusions. Finally, we generally confirm the dynamic and negative correlation between China's geopolitical risk and crude oil returns. It is evidently clear from the results that investors should pay close attention to the policy uncertainty to avoid the adverse impact of specific policy uncertainty on crude oil returns.

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