Abstract
The speed of China’s economic development is gradually accelerating, and the demand for energy is also constantly increasing, especially the demand for coal. In order to reveal whether the coal imports have an impact on China’s economic development, this paper constructs the VAR(6) model by selecting the quarterly data of coal imports (CIV) and gross domestic product (GDP) from 2002 to 2017, performing ADF (Augmented Dickey-Fuller) stationarity test and Johansen cointegration test. It shows that there is a long-term stable equilibrium relationship between coal imports and GDP. Then the impulse response function is used to obtain the relationship between coal imports and GDP. It is found that the impact of coal imports on GDP is greater than the impact of GDP on coal imports.
Highlights
China’s economy has developed rapidly, and the total amount of gross domestic product (GDP) has increased year by year
The impulse response function is used to obtain the relationship between coal imports and GDP
This paper mainly studies the relationship between coal imports and GDP and draws the following conclusions: In the Johansen cointegration test, there is a cointegration relationship between gross domestic product (GDP) and coal imports, and it has a long-term stable and balanced development trend
Summary
China’s economy has developed rapidly, and the total amount of GDP has increased year by year. Wu Yongping [3] described the relationship between coal consumption and economic growth in the world’s major coal-consuming countries through cointegration analysis and Granger causality test. Chen Weidong [4] mainly adopts quantitative analysis to establish a VAR model of coal price and GDP, and dynamically analyzes the long-term impact of coal price on economic growth. Zhou Aiqian [5] analyzed the long-term impact of China’s coal price on economic growth. This paper establishes a VAR model for coal imports and economic growth(GDP), and determines the long-term stable equilibrium relationship between the two through Johansen cointegration test. Where, yt is a m-dimensional endogenous variable vector, xt is a d-dimensional endogenous variable vector. A1, , Ap and B1, , Br are the parameter matrices to be estimated, p is the lag period of the endogenous variable, r is the lag period of the exogenous variable. εt is a random disturbance term, which can be related to the same period, but not autocorrelation
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