We employ a class of time-varying Bayesian vector autoregressive (VAR) models on new standard dataset of China's GDP constructed by Chang et al. (2015) to examine the relationship between China's economic growth and global oil market fluctuations between 1992Q1 and 2015Q3. We find that: (1) the time varying parameter VAR with stochastic volatility provides a better fit as compared to it's constant counterparts; (2) the impacts of intertemporal global oil price shocks on China's output are often small and temporary in nature; (3) oil supply and specific oil demand shocks generally produce negative movements in China's GDP growth whilst oil demand shocks tend to have positive effects; (4) domestic output shocks have no significant impact on price or quantity movements within the global oil market. The results are generally robust to three commonly employed indicators of global economic activity: Kilian's global real economic activity index, the metal price index and the global industrial production index, and two alternative oil price metrics: the US refiners' acquisition cost for imported crude oil and the West Texas Intermediate price of crude oil.

Item Type:	Refereed Article
Keywords:	oil prices, China, TVP-VAR-SV
Research Division:	Economics
Research Group:	Applied economics
Research Field:	Macroeconomics (incl. monetary and fiscal theory)
Objective Division:	Economic Framework
Objective Group:	Macroeconomics
Objective Field:	Macroeconomics not elsewhere classified
UTAS Author:	Nguyen, BH (Dr Bao Nguyen)
ID Code:	141220
Year Published:	2017
Web of Science® Times Cited:	43
Deposited By:	Economics and Finance
Deposited On:	2020-10-05
Last Modified:	2021-08-16
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