Statistical Modeling Research Of Energy Intensity In China Based On Skew-normal Distribution

With the rapid development of economy, China’s total energy consumptionincrease dramatically due to the GDP growth. Nowadays, the huge energy use leads toa series of ecological and environmental problems. To promote the economy andsustainable development in our country, we need to improve the energy efficiency andreduce the energy intensity, which have become the focus of recent research. However,the energy intensity data does not follow a normal distribution. If we analyze it withthe normal distribution assumption, the statistical accuracy will decrease dramatically.Therefore, based on the energy intensity data from China during2000-2011, theskew-normal multivariate regression models are established to study the maininfluence factors of energy intensity.Firstly, based on the Monte Carlo simulation methods, the effectiveness of skew-Fdistribution statistics is verified. Secondly, we establish the skew-normal multivariateregression models to study the main influence factors of energy intensity for thenationwide, eastern, and mid-western regions respectively. Thirdly, we obtain thepower of skew-F distribution statistics under the skew-normal multivariate regressionmodel. Furthermore, the robustness of the skew-normal multivariate regression modelis proved using the GEE models. Finally, some countermeasures and suggestions areprovided according to the results of the analysis.This study shows that technology progress, industry structure and energy structurehave significant association with the energy intensity for the nationwide, eastern, andmid-western regions. Specifically, the R&D input and electricity consumptionproportion have significantly negative association with the energy intensity for thewhole country; while the secondary industry proportion has significantly positiveassociation with the energy intensity for various regions. In addition, the technologyprogress and energy structure present some territorialities on the influence strength ofthe energy intensity in our country.