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Spatial Spillover and the Influencing Factors Relating to Provincial Carbon Emissions in China Based on the Spatial Panel Data Model

Xin Tong (), Xuesen Li (), Lin Tong () and Xuan Jiang ()
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Xin Tong: School of Economics, Central University of Finance and Economics, Beijing 100081, China
Xuesen Li: College of Science and Technology, Shenyang Polytechnic College, Shenyang 110021, China
Lin Tong: Department of Engineering Technology, Dalian Maple Leaf College of Technology, Dalian 116036, China
Xuan Jiang: School of Economics, Central University of Finance and Economics, Beijing 100081, China

Sustainability, 2018, vol. 10, issue 12, 1-17

Abstract: From the perspective of spatial geography, this paper verifies the spatial dependence of China’s provincial carbon emissions. The contribution of impact factors with different fields of view to carbon emissions’ growth is estimated based on the spatial panel data model, t. The study found that during 2000–2015, China’s energy-related carbon emissions in the provinces were dependent on the spatial, and the spatial spillover effect of carbon emissions and its influencing factors in the neighboring provinces are obvious. It was also found that economic growth, industrial structure, financial development, and urbanization rates are positive, and the effect of the population and technological progress on reducing carbon emissions is significant. The effect of source price, export dependence, and fiscal decentralization on carbon emissions’ growth did not pass a significance test. In the formulation of carbon emission-related policies and development plans, the government must consider the effect of the influencing factors affecting the carbon emissions in the adjacent area and combine the carbon emissions and spatial spillover effect of the related factors in order to reduce carbon emissions in the time dimension and the spatial dimension of China as a whole.

Keywords: carbon emissions; space spillovers; influencing factors (search for similar items in EconPapers)
JEL-codes: Q Q0 Q2 Q3 Q5 Q56 O13 (search for similar items in EconPapers)
Date: 2018
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