Dynamic effects and driving intermediations of oil price shocks on major economies

Interest in oil price shocks' economic effects has grown in recent years. However, previous studies mostly failed to clarify the dynamic transmissions of oil price shocks on representative economies from global and driver perspectives, even ignoring oil price fluctuations when linking oil prices and economy together. This paper examines the dynamic relationships and driving intermediations between multiple oil price shocks and macroeconomy by applying Bayesian vector autoregressive models with stochastic volatility and time-varying parameters, using the USA, China, the Euro-19, and Japan as research objects. Results show that, in the whole sample, all oil prices have the strongest effects on Japan, followed by China, Euro-19, and the USA, with possible directional differences. All oil prices' economic effects intensified during the crisis and Covid-19, accompanying significant oil price fluctuations. Regarding asymmetry, in the whole sample and critical times, stronger effects of rising oil prices show in the short term, but opposite in the long term. Consumer price, interest rate, and exchange rate are the general intermediations of oil prices in China and the USA, Euro-19, and Japan, respectively, and exchange rate is the additional intermediation in China, Euro-19, and Japan during the crisis and Covid-19. Overall, the results are solid.

The Dynamic Impacts of the Global Shipping Market under the Background of Oil Price Fluctuations and Emergencies

With growing uncertainty about the evolution of the global landscape, it is of great practical significance to explore the nonlinear dynamic adjustment relationship among the world oil market, the global bulk shipping market, the stock market, and economic growth in China. This paper applied the TVP-SV-VAR model and selected quarterly data from 1998 to 2020 to explore the dynamics. The results indicated that the impact intensity of BDI on China’s economy had a “positive” to “negative” change in different lag periods. This was mainly due to the fact that the negative impact of higher freight prices on China’s economy outweighed the positive impact of higher trade volumes on China’s economy. The impact intensity of BDI on GDP had a distinct medium- to long-term effect. A positive BDI shock had a dampening effect on stock prices in the short and medium term, while a positive BDI shock could promote stock market prosperity in the long-term perspective. The impulse responses of SSE and GDP to BDI showed that the external shipping market shocks to China’s stock market and economic growth gradually became smaller over time. For impulse response at three different time points, the impact intensity of the BDI to GDP varied at different time points, with the largest shock during the financial crisis in 2008, followed by the shock during the oil price crash in 2014, and the smallest during the COVID-19 epidemic. This demonstrated that the external shipping market’s influence on Chinese economic growth and stock market has gradually weakened over time, illustrating the enhancement of Chinese risk-resilience capacity.