摘要
基于1980~2013年的时间序列数据,考虑金融相关率、外商直接投资占比、私营部门信贷占比和金融机构存贷款比率四个金融发展指标,运用SVAR模型、协整分析和误差修正模型对中国金融发展与碳排放之间的短期和长期关系进行经验检验,并运用状态空间模型对各个金融发展指标对碳排放的敏感度进行分析。结果发现,金融发展对碳排放有明显的动态影响,外商直接投资占比不论从长期还是短期都与碳排放呈负相关关系;金融机构存贷比则和碳排放成正相关关系;金融相关率与私营部门信贷占比对碳排放的影响在长期和短期的作用方向不一致;不同的金融发展指标对碳排放的敏感度在不同的时期也表现出不同的特征。最后,根据实证结论提出了减少碳排放的对策建议。
Based on the time series data from 1980 to 2013, considering financial interrelations ratio, the percentage of FDI to GDP, the percentage of Credit to private sector to GDP, the ratio of deposits and loans of financial institutions, using Structural Vector Auto Regression(SVAR), co-integration analysis, and error correction model(ECM), the paper tests the long-term and short-term relationship between China's financial development and carbon emission, and then by using the state-space model, it analyzes each indicator's sensitivity to carbon emission. The results show that financial development has obvious dynamic impact on carbon emissions, the percentage of FDI to GDP is always negatively correlated with carbon emission in terms of long-term or short-term; the ratio of deposits and loans of financial institutions are positively correlated with carbon emission; the effect direction of financial interrelations ratio and the percentage of Credit to private sector to GDP to carbon emission is not the same in long-term and shortterm. The sensitivity of different financial development indicator to carbon emission performs different features. Finally, it presents some suggestions to reduce carbon emission according to the empirical results.
出处
《湖南商学院学报》
2016年第1期79-88,共10页
Journal of Hunan Business College
关键词
金融发展
碳排放
SVAR模型
协整检验
状态空间模型
financial development
carbon emission
SVAR Model
co-integration test
State-space Model