Using Panel Data to Evaluate the Factors Affecting Transport Energy Consumption in China's Three Regions

Int J Environ Res Public Health. 2019 Feb 14;16(4):555. doi: 10.3390/ijerph16040555.

Abstract

In China, transportation accounts for a large proportion of total energy consumption and that trend is projected to increase in the future. Through the stochastic impacts by regression on population, affluence, and technology (STIRPAT) model, OLS regressions were conducted to investigate the impacts of gross domestic product (GDP), urbanization, energy intensity and transport structure on the transport energy consumption in China's three regions. The analyses of inter-provincial panel data during the period 2006⁻2015 is compared to the analysis of the data from 1996 to 2005 to determine the change. There were two primary findings from this study. First, the changes of the influencing degree in three regions are considered. GDP is still the main driver of transport energy consumption in eastern region, while urbanization becomes the main driver in the other two regions. Second, the relationship between the elasticity and the value of each variable is detected. The elasticity of transport energy consumption with respect to GDP, transport structure, energy intensity and urbanization have separate positive and significant relationships. The primary measure is to optimize transport structure in the central region, while reducing energy intensity in the western region. Finally, we propose relevant policy recommendations for the three regions.

Keywords: STIRPAT model; energy consumption; influencing factors; panel data; transportation industry.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • China
  • Energy-Generating Resources / statistics & numerical data*
  • Oil and Gas Industry / statistics & numerical data*
  • Technology / statistics & numerical data*
  • Transportation / statistics & numerical data*
  • Urbanization*