基于深圳、北京、上海、广东、天津、湖北、重庆等7个碳试点地区2014—2019年碳交易价格季度面板数据,首先,在构建能源强度权重矩阵的基础上,采用空间莫兰指数分析碳交易价格的时空特征;然后,使用时空地理加权回归(GTWR)模型,对碳交易价格的驱动因素及其时空异质性进行实证分析。研究结果表明:试点地区碳交易价格具有明显的时空集聚效应和显著空间相关性;不同试点地区碳交易价格的驱动因素存在显著时空异质性,产业结构、工业总产值、能源结构、碳市场交易量、惩罚力度、控排企业数量以及森林覆盖率是其重要的驱动因素;气温、人均国内生产总值、单位GDP能耗、减排目标均未表现出明显的时空异质性特征。通过分析认为,目前应重点优化产业结构、合理制定碳交易政策、健全森林保护机制,以及加强跨区域合作有效衔接各碳市场。

Based on the quarterly panel data of carbon trading prices from 2014 to 2019 in seven carbon pilot areas of Shenzhen, Beijing, Shanghai, Guangdong, Tianjin, Hubei and Chongqing, this paper first used the spatial Moran index to analyze the spatial and temporal characteristics of carbon trading prices on the basis of building the energy intensity weight matrix, and then used the spatial and Temporal Geographic weighted regression(GTWR)model to empirically analyze the driving factors of carbon trading prices and their spatial and temporal differences.The results showed that:Carbon trading prices in pilot areas had obvious temporal and spatial agglomeration effects and significant spatial correlation; The driving factors of carbon trading price in different pilot areas had significant temporal and spatial heterogeneity. Industrial structure, total industrial output value, energy structure, carbon market trading volume, punishment, the number of emission control enterprises and forest coverage were important driving factors; Temperature, GDP per capita, energy consumption of GDP in per unit and emission reduction targets did not show obvious temporal and spatial heterogeneity.This paper reckoned that we should focus on optimizing the industrial structure, reasonably formulating carbon trading policies, improving the forest protection mechanism and strengthening cross regional cooperation to effectively connect various carbon markets.