摘要
大数据治理创新了我国大气污染防治模式。现有文献尚未聚焦于该模式总体效应评价研究。通过提出大数据治理理论分析逻辑,并基于地级市面板数据给出其总体效应的测度。研究表明,“生态环境大数据建设试点”政策实施,显著降低试点城市AQI和PM_(2.5)、PM_(10)、O_(3)等污染物排放浓度,稳健性检验支持该结论。另外通过异质性分析发现,东部城市的大数据治理效应更为显著,中部的AQI和PM_(2.5)抑制效应大于东部,中西部对PM_(10)浓度和O_(3)浓度的抑制效应不明显;同时非资源型城市的治理效应强于资源型城市,治理需加大差异化应对。机制分析反映,大数据治理试点政策显著提高当地政府的科学决策和监管能力,但公众参与效应相对有限。研究结论具有推动我国环境大数据治理的参考价值。
Big data governance has innovated China's air pollution control model.The existing literature has not yet focused on the evaluation study of the overall effect of this model.This paper proposes theoretical analysis logic of big data governance and measurement of its overall effect based on prefecture-level city panel data.The study shows that the implementation of the“ecological environment big data construction pilot”policy significantly reduces the AQI and the concentration of PM2.5,PM_(10),O_(3)and other pollutants in the pilot cities,which is supported by the robustness test.In addition,through the heterogeneity analysis,it is found that the governance effect of big data in eastern cities is more significant,the inhibition effect of AQI and PM2.5 in central China is greater than that in the east,and the inhibition effect on PM_(10)and O_(3)concentrations in central and western China is not obvious;at the same time,the governance effect of non-resource cities is stronger than that of resource cities,hence the greater governance necessity to cope with the differentiation.Mechanism analysis reflects that the big data governance pilot policy significantly improves the local government's scientific decision-making and regulatory capacity,but the public participation effect is relatively limited.The relevant data have reference value for promoting environmental big data governance in China.
作者
王莉
薛飞
WANG Li;XUE Fei(School of Economics and Management,Northwest University,Xi'an 710127,China)
出处
《商业经济与管理》
北大核心
2023年第8期71-82,共12页
Journal of Business Economics
基金
国家社会科学基金重大项目“工业大数据统计测度理论及应用研究”(21&ZD153)
全国统计科学研究项目“数字经济驱动我国农业高质量发展的统计研究”(2021LY068)。
关键词
大气污染
大数据治理模式
治理效应
双重差分
air pollution
big data governance model
governance effect
difference-in-differences