Macroeconomics

Theoretical physics

Monetary policy

Volatility (finance)

Inflation (cosmology)

Vector autoregression

China

Archaeology

Supply shock

Demand shock

Economics

Keynesian economics

Physics

Geography

Monetary economics

Variance decomposition of forecast errors

Econometrics

Sociology

Consumption (sociology)

Oil price

Social science

Energy Economics

Using a time-varying parameter structural vector autoregression with stochastic volatility (TVP-SVAR-SV) model, we decompose the structural shocks of oil price fluctuations into four types: oil supply shocks, global demand shocks, domestic demand shocks and oil-specific demand shocks. We then analyze the time-varying effects of these oil price shocks on China's inflation at the import, production and consumption stages using monthly data from January 1999 to December 2016. The results show that the pass-through effects of the four types of oil price shocks on China's inflation at each stage are time-varying and that there are significant differences at different time horizons and points in time. The analysis of the variance decomposition shows that the effects of oil price shocks on China's inflation at each stage are incomplete and decrease along the price chain. The increase in oil prices driven by oil-specific demand shocks is the most important cause of China's inflation at the import and production stages during the full sample period, while China's inflation at the consumption stage is mainly affected by domestic demand shocks. In addition, the inflationary effects of oil price shocks have been dramatically weaker since the international financial crisis compared with before the crisis.

The pass-through effects of oil price shocks on China's inflation: A time-varying analysis