Analysis of Energy Consumption Influencing Factors in China Based on the Lasso Method
Abstract: With the acceleration of economic development and the increasing demand for resources, energy consumption shows a rising trend in recent years. To ensure the stable, sustainable and healthy development of China’s economy, it is necessary to study on consumption factors and to forecast energy consumption demand reasonably. As so far, scholars have used simple linear regression, principal component regression and ridge regression method for analyzing China’s energy consumption factors, but models achieved from these studies may be too lean to find more comprehensive energy consumption factors. While according to the related data of domestic energy consumption during 2000-2012, this paper chooses a new method—Lasso method to make regression model for domestic energy consumption, and then we get the main energy consumption effecting factors: economic development, demographic factor, industrial structure, technological progress, energy consumption efficiency and energy price factor, so we can control energy consumption through these main factors. Additionally, we use stepwise regression and ridge regression to make regression models, the results got from the Lasso, stepwise regression and ridge regression are compared, the study shows the Lasso method is better than the other methods in terms of variable selection, because it could find more comprehensive energy consumption factors; for predictions of 2013 and 2014, Lasso method is more accurate than the other two methods.
文章引用: 李晓童 , 覃丹艳 , 吕明慧 (2017) 基于Lasso方法的我国能源消费影响因素分析。 统计学与应用， 6， 73-80. doi: 10.12677/SA.2017.61007
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