大数据政策能否提高城市碳释放效率? 一种基于双重机器学习的新方法
Neng Shen1, Guoping Zhang1, Jingwen Zhou1
1School of Economics and Management, Fuzhou University, Fuzhou, Fujian, 350108, China.
Journal of environmental management
|November 23, 2024
概括
大数据政策显著提高了城市碳释放效率. 这是通过政府现代化,企业发展和经济转型实现的,有助于实现"双碳"目标.
科学领域:
- 环境科学 环境科学
- 经济学 经济学 经济学
- 城市研究 城市研究
背景情况:
- 大数据对经济发展至关重要,但它对城市碳释放效率 (UCUE) 的影响未得到充分研究.
- 现有的研究缺乏对大数据政策如何影响UCUE的明确理解.
研究的目的:
- 调查大数据政策对城市碳解锁效率 (UCUE) 的影响.
- 探索大数据政策影响UCUE的机制.
- 分析不同类型城市中这些效应的异质性.
主要方法:
- 使用先进的双重机器学习 (DML) 方法.
- 将大数据综合试验区 (BDCPZ) 视为准自然实验.
- 来自中国282个城市 (2011-2022年) 的雇员面板数据.
主要成果:
- 大数据政策显著增强了UCUE,这是另类机器学习模型证实的.
- 通过政府现代化,企业智能发展和经济转型来改善UCUE.
- 在大城市,旧工业基地,数字经济城市和关键环保城市中,收益更大.
结论:
- 大数据政策是提高城市碳释放效率的有效工具.
- 政策影响包括加强大数据基础设施和促进绿色发展.
- 调查结果支持中国实现"双碳"目标.
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