Integrated Analysis of Changes in the Structure of Coal Consumption and Economic Growth in China
中国煤炭消费与经济增长的变结构协整分析

Economic growth and energy consumption are popular topics for theoretical research. China is the largest global producer and consumer of coal, which makes research on the relationship between China's coal consumption and economic growth highly relevant. This paper analyses the data generation process for Chinese coal consumption and economic growth based on structural break theory and using Eviews5.0 software. We identified the structural breakpoints and verified that they coincide with political and economic changes in China over the past fifty years. On the basis of this analysis, we designed a structural change cointegration model of the long-term equilibrium relationship between Chinese coal consumption and economic growth, and validated the model predictions. We conclude that without considering the circumstances of structural breaks, China's coal consumption and economic growth sequence is not generated by stable trends, but generated by the unit root process. Also, coal consumption in China is a stable trend process with structural changes, which means that China's coal consumption takes place with deviations in trend due to political, economic, natural disasters and other external factors, but the deviation and fluctuation is temporary. There are balance breaks and trend breaks of Chinese coal consumption in 1960, but the balanced break of Chinese economic growth took place in 1963, and the trend breaks took place in 1958, 1963 and 1978. These results indicate that a data generation process break is often caused by reasons such as a financial crisis, institutional change, natural disasters and other severe external shocks. In considering the circumstances of structural changes, Chinese coal consumption and economic growth still maintain a relationship of long-term equilibrium, and any impact will have a lasting effect on this relationship. Based on the analytical results and forecast predictions, the predictive ability and accuracy of the model is better than a model which hasn't considered the structural break point. Models which consider the structural break point have improved capacity to forecast and analyze China's coal consumption demand. Therefore, the model has practical value for forecasting Chinese coal demand and providing a basis for decision-making.