基于空间滞后模型的中国省域碳排放量影响因素分析

An Analysis of the Influencing Factors of China’s Provincial Carbon Emissions Based on the Spatial Lag Model

摘要: 降低二氧化碳排放量是我国节能减排的首要目标，探究碳排放量的影响因素对创造绿色中国有着重要的指导作用。本文基于2004年~2019年我国碳排放量面板数据，首先，通过莫兰指数和莫兰散点图研究我国碳排放量的空间相关性，再基于STIRPAT模型和时空双固定效应空间滞后模型构建碳排放的影响因素的空间计量模型。其次，研究我国碳排放量的空间溢出效应。实证研究结果表明：1) 我国各省域碳排放量在空间上有着显著的空间正相关性，我国碳排放量存在明显的空间聚集性；2) 能源结构EC、人均生产总值PGDP和环境规制ER和对碳排放有着负面影响，而人口数POP和研发强度RD抑制了碳排放量；3) 本地区能源消费结构变动会带动碳排放量变大，同时相邻地区的能源消费结构也会影响本地区的碳排放量。最后，本文根据实证研究结果给出相应的合理建议。

Abstract: Reducing carbon dioxide emission is the primary goal of energy saving and emission reduction in our country. Exploring the influencing factors of carbon emission plays an important guiding role in creating Green China. Based on the panel data of our country’s carbon emissions from 2004 to 2019, this paper first studies the spatial correlation of our country’s carbon emissions through Molan index and Molan scatter plot, and based on STIRPAT model and spatiotemporal double fixed effects spatial lag model, the spatial econometric model of influencing factors of carbon emission was constructed. Secondly, we study the spatial spillover effect of carbon emissions in our country. The empirical results show that: 1) the carbon emission of every province in our country has significant positive spatial correlation, the carbon emission of our country has obvious spatial aggregation; 2) energy structure EC, GDP per capita and environmental regulation ER have negative effects on carbon emissions, while population POP and R&D Intensity Rd have negative effects on carbon emissions; 3) the change of energy consumption structure in the region will lead to the increase of carbon emissions, and the energy consumption structure in the neighboring regions will also affect the carbon emissions in the region. Finally, this paper gives some reasonable suggestions according to the empirical results.