Urbanization, economic growth, energy consumption, and CO2 emissions: Empirical evidence from countries with different income levels

被引:372
|
作者
Wang, Shaojian [1 ]
Li, Guangdong [2 ]
Fang, Chuanglin [2 ]
机构
[1] Sun Yat Sen Univ, Sch Geog & Planning, Guangdong Prov Key Lab Urbanizat & Geosimulat, Guangzhou 510275, Guangdong, Peoples R China
[2] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
来源
基金
中国国家自然科学基金;
关键词
Urbanization; Economic growth; Energy consumption; CO2; emissions; Panel causality; Income level countries; CARBON-DIOXIDE EMISSIONS; FOREIGN DIRECT-INVESTMENT; PANEL-DATA ANALYSIS; ELECTRICITY CONSUMPTION; CAUSAL RELATIONSHIP; ERROR-CORRECTION; TRADE OPENNESS; ENVIRONMENTAL DEGRADATION; NEXUS EVIDENCE; GDP CAUSALITY;
D O I
10.1016/j.rser.2017.06.025
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The growth of anthropogenic CO2 emissions has been widely attributed to the combustion of energy in support of human activities associated with economic development. While the link between urbanization, economic growth, energy consumption, and CO2 emissions has, as a result, received considerable multidisciplinary scholarly attention, little work has been undertaken with respect to the how differences in the development stages or income levels of the countries studied may affect these relations. Here, we empirically explore the link between urbanization, economic development, energy consumption, and CO2 emissions, specifically taking into account the different income levels of the countries studied. A series of panel data models and a balanced dataset for a panel of 170 countries were utilized in the study, which took the period of 1980-2011 into consideration. The result of panel cointegration tests suggested that a cointegration relationship existed between variables in all the countries studied, and that a statistically significant positive relationship existed between the variables employed in the long run. The results of a Granger causality test based on the Vector Error-Correction Model (VECM) provided evidence of varied Granger causality relationships between the variables across the income-based subpanels. Moreover, we also undertook an impulse response and variance decomposition analysis that allowed us to forecast the impacts of economic growth, urbanization, and energy consumption on future CO2 emissions during the period surveyed. Our results cast a new light on the importance of a country's development stage and income level for government policy decisions relating to the reduction of CO2 emissions.
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页码:2144 / 2159
页数:16
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