###### Abstract  
Crude oil price shocks have led to a fluctuation in commodity prices through the industrial chain and supply-demand relationships, which can substantially influence a country's economy. In this paper, we propose a transmission model of oil price shocks to Chinese price levels and explore the direct and indirect impacts of crude oil price shocks on various Chinese price indices, combining the Granger causality test, impulse response function, and network analysis method. The empirical data are the Brent, WTI, Dubai, and Daqing spot crude oil prices and eight categories of Chinese price indices from January 2011 to March 2020. We found the following results: (1) Consumer price index (CPI) and the price index for means of agricultural production (MAPPI) cannot be directly impacted by crude oil price fluctuations, while they could be indirectly affected. (2) The duration and degree of the impacts of oil prices on each price index vary, and the export price index (EPI) is the most significantly affected. (3) The proportion of the indirect impact in the total impact of crude oil price shocks ranges from 0.03% to 100.00%. Thus, indirect influence cannot be ignored when analyzing the influence of crude oil price fluctuation on Chinese price level. c 2022 24 944 944 94  
price model [8], and econometric models based on time series [9; 10; 11; 12; 13]. However, first, the general equilibrium models have high data and model settings requirements. Second, although the input-output price model is widely used to analyze the direct and indirect impacts of energy price changes on the prices of all sectors' products [8; 14], the input-output table of China is released every five years; thus, we cannot obtain the newest data to analyze the influence of oil price fluctuation on price levels promptly. Third, time-series data have the advantages of high frequency and good timeliness. Hence, the econometric modeling methods based on time series, such as structural vector autoregression, Granger causality test, and impulse response function, are relatively flexible. However, these econometric methods have limitations for analyzing the indirect effects of one variable on other variables. Therefore, a new analysis framework is inevitable to develop. This paper proposes a novel framework to analyze the direct and indirect influences of crude oil price shocks on Chinese price levels, combining the network analysis method and econometric methods, namely, the Granger causality test and impulse response function. We select the Brent, WTI (West Texas Intermediate), and Dubai spot crude oil prices to represent international crude oil prices and the Daqing spot crude oil price to represent Chinese crude oil prices. Eight Chinese price indices are selected to represent different commodity price levels. First, the Granger causality test is used to reveal the fluctuation transmission relationships among crude oil price and price indices. Then, we analyze the direct effects of crude oil price shocks on every price index based on the impulse response function and extract the response values with their corresponding time to explore the evolution of the direct impact degree and the duration of the impact. Third, based on the results of the Granger causality test and impulse response function, this paper proposes a transmission model of oil price shocks to Chinese price levels using the network analysis method and analyzes the indirect influence on price indices over time. Finally, we calculate the total influence of crude oil price shocks on price indices and compare the indirect impacts with total impacts. Our research provides closer observations that consider the direct and indirect effects of crude oil price shocks on each category of price index. This could produce a more comprehensive picture of the transmission mechanism of crude oil price fluctuations on Chinese price levels and could provide policy implications for China to improve its ability to prevent risk from imported inflation. The paper is organized as follows.