CAJ | 학술논문

文章基于1995-2011年面板数据，采用空间计量模型，通过构建经济权重矩阵，分别从空间滞后模型(SLM)和空间误差模型(SEM)对中国30个省（市、区）的二氧化碳排放强度驱动因素进行研究。研究结论表明：在样本期间，中国二氧化碳排放强度的Moran指数均为正值，且通过了1%的显著性水平检验，表明其具有显著的空间依赖性，本地区的碳排放强度会受到邻近省份碳排放的显著影响；二氧化碳排放强度与产业结构、能源消费结构、能源强度成正比，与外商直接投资、人均GDP、人口密度成反比。最后，文章提出相关政策建议，即优化产业结构、改善能源使用结构、适当提高建成区的人口密度等能有效降低中国的碳排放强度。
문장기우1995-2011년면판수거，채용공간계량모형，통과구건경제권중구진，분별종공간체후모형(SLM)화공간오차모형(SEM)대중국30개성（시、구）적이양화탄배방강도구동인소진행연구。연구결론표명：재양본기간，중국이양화탄배방강도적Moran지수균위정치，차통과료1%적현저성수평검험，표명기구유현저적공간의뢰성，본지구적탄배방강도회수도린근성빈탄배방적현저영향；이양화탄배방강도여산업결구、능원소비결구、능원강도성정비，여외상직접투자、인균GDP、인구밀도성반비。최후，문장제출상관정책건의，즉우화산업결구、개선능원사용결구、괄당제고건성구적인구밀도등능유효강저중국적탄배방강도。
Based on the panel data of 1995~2011, the paper studies the driving factors of CO2emission intensity of 30 provinces in China by the spatial lag model(SLM) and spatial error model(SEM) through establishing the economic weight matrix on the basis of spatial econometric model. The results show that CO2 emissions intensity's Moran index of China is positive and passes a significant level of 1%inspection. It indicates that CO2 emissions intensity has significant spatial dependence in China and CO2 emissions intensity of the local region will be greatly influenced by the neighboring provinces. CO2 emissions intensity is proportional to industrial structure, energy consumption structure and energy intensity, while it is inversely proportional to FDI, population density and per capita GDP. Finally, the article puts forward relevant policy suggestions which include optimizing the industrial structure, improving the energy structure and increasing built-up area's population density properly to reduce carbon emissions of China.