Abstract

Currently, due to the recent unprecedented urbanization and industrialization, energy consumption in China is increasing at an enormous speed. However, this process should go hand in hand with sustainable energy development that is based on three interconnected dimensions: (i) energy security, (ii) energy affordability, and (iii) environmental sustainability. It becomes very obvious that an increase in energy efficiency leads to the increase in both energy security and environmental sustainability. Therefore, inadequate energy efficiency causes energy security and environmental sustainability issues, and thus negatively influences economic development of China (or any other country for that matter). This paper explores the intrinsic relationship among urbanization, industrialization, and energy security, as well as the influencing mechanisms of urbanization and industrialization on energy efficiency using a fixed effect model. The paper employs panel data from 30 provinces in mainland China collected in the time range from 2006 to 2015. Our results demonstrate that urbanization and industrialization can significantly improve energy efficiency. Although energy security level decreases considerably with the rise of energy consumption and population growth, the increase in urbanization and industrialization levels can increase energy security through energy efficiency improvements. Moreover, it appears that changes in disposable income and population structure do not alter the effects of industrialization and urbanization on energy security. We conclude that Chinese provinces with high and low urbanization levels should focus on technological innovation and increase industrial development and technological input, respectively. Local governments in China can formulate policies and regulations and promote urbanization according to local economic development and industrial and population structure. The paper also presents theoretical references and decision support that might help in developing local laws and regulations promoting energy efficiency during urbanization and industrialization.

Highlights

  • Energy might be crucial for achieving sustainable development

  • When lnPdi increases to a certain point, the technological efficiency improved by the upgrading of industrialization level will reduce the growth rate of energy consumption and make it lower than the growth rate of gross domestic product (GDP)

  • In order to assess the effect of industrialization and urbanization on energy security, we constructed a STIRPAT model using energy efficiency as a proxy variable of energy security and choosing industrialization and urbanization rates, consumption expenditure, and population size as variables

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Summary

Introduction

Energy might be crucial for achieving sustainable development. There is no doubt that it is the main driver of economic growth and has significant impact on environment. The rapid growth of economic development in China in the past 40 years led to problems such as total energy reserves, environmental pollution, and contradictions between energy supply and demand [4] These contradictions continue to accumulate, which has caused energy security issues that present serious concerns both for the government and for the public. With economic and social developments and population growth, the energy security problem in China is becoming prominent as a response to the increasing pressing energy demand and per capita energy consumption. In order to fulfil the main objectives of this paper, we employed an empirical test of impact elasticity and influencing mechanism of urbanization and industrialization on energy security using the panel data of 30 provinces from China ranging from 2006 to 2015.

Literature Review
Setting Up the Model
Sample Selection and Data Processing
Main Variables and Descriptive Statistical Analysis
Descriptive Statistical Analysis
Model Selection
Robustness Test
Subsample Regression Analysis
Sample Classification Based on Industrialization Level
Sample Classification Based on Urbanization Level
Sample Classification Based on Geographical Positions
Discussions
Findings
Conclusions

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