Influences of Environmental Regulations on Industrial Green Technology Innovation Efficiency in China
Influences of Environmental Regulations on Industrial Green Technology Innovation Efficiency in China
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DOI：
10.3390/su14084717
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发表时间：
2022-04
期刊：
影响因子：
3.9
通讯作者：
W. Shen;Jianing Shi;Qinggang Meng;Xiaolan Chen;Yufei Liu;Ken Cheng;Wenbin Liu
中科院分区：
文献类型：
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作者：
W. Shen;Jianing Shi;Qinggang Meng;Xiaolan Chen;Yufei Liu;Ken Cheng;Wenbin Liu
《巴黎协定》标志着2020年后全球应对气候变化的行动，中国提出了碳达峰和碳中和的双重碳目标。本文通过分析环境规制对中国绿色技术创新的影响，分析了环境规制对中国实现双重碳目标的贡献。首先，考虑到各省、各行业能源消费结构的差异，计算了工业CO2排放量，并将其作为工业GTI的不良产出。在此基础上，采用规模收益可变的非定向两阶段网络SBM-DEA模型，测算了2005-2017年我国29个省（市、自治区）的工业绿色技术创新效率。最后，分别考察了绿色技术研发阶段、绿色技术商业化阶段和总体绿色技术创新阶段工业GTIE的动态演化和区域差异，分析了指令型、市场型和自愿型环境约束对工业GTIE的影响。研究发现，中国工业GTIE总体上处于较低但逐渐上升的阶段，且呈现出省际梯度变化，区域差异日益突出。研究发现，环境要求类型对工业GTIE的影响存在动态效应、门槛效应、滞后效应和地区差异。
The Paris Agreement marks global response to climate change after 2020 and China has proposed the dual carbon goals, carbon peaking and carbon neutrality, in response. This paper analyses the contribution to dual carbon goals by analyzing the impact of environmental regulations (ERs) on green technology innovation (GTI) in China. First, considering variances in energy consumption structure across provinces and industries, industrial CO2 emission is calculated and set as an undesirable output of industrial GTI. Then, industrial green technology innovation efficiencies (GTIE) of 29 provinces in China between 2005–2017 are calculated using a non-oriented two-stage network SBM-DEA model assuming variable returns to scale. Last, dynamic evolution and regional differences of industrial GTIE during green technology R&D, green technology commercialization, and overall GTI stages are respectively observed, and the influences from different types of ERs, command-based (CER), market-based (MER), and voluntary (VER), on industrial GTIE are analyzed. We identify China is overall experiencing relatively low but gradually increasing industrial GTIE and Industrial GTIE present gradient changes across provinces with increasingly prominent regional difference. It is found that influences of types of ERs on industrial GTIE present dynamic effect, threshold effect, lag effect and regional differences.