The Relationship Between Energy Consumption and Economic Growth in China: An Application of the Partial Least Squares Method

Abstract

This article applies the partial least squares (PLS) method and its supplementary methods to model the relationship between energy consumption and economic growth in China. Using the PLS algorithm, we obtain the quantitative linear model. Further analysis of variables and samples shows two methods to reduce China’s energy consumption for unit gross domestic byproduct (GDP) production: Developing the tertiary industry and improving its ratio in GDP and increasing the scale of production and adopting new agricultural technology. Furthermore, studies also reveal two threats: An economic stimulus in rural areas may lead to a sharp and immediate increase in energy consumption and the overheated economy caused by the construction industry will lead to the unusual energy consumption mode. This article offers an empirical case of referential value in the quantitative simulation of the relationship between energy consumption and economic growth, especially in marginal analysis and outlier identification.

Keywords:

• economic growth
• energy consumption
• importance analysis of variables
• partial least squares
• regularity analysis of samples