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财政纵向失衡对城市绿色全要素生产率的影响——双重机器学习下来自土地财政视角的理论阐释

Impact of Fiscal Vertical Imbalance on Urban Green TFP—Theoretical Explanation from the Perspective of Land Finance Under Double/Debiased Machine Learning
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摘要 本文在推动绿色发展的时代背景下,从土地财政的角度为财政纵向失衡如何影响城市绿色全要素生产率提供一种新的理论阐释,并进一步量化分析异质性环境规制情境下影响机制的适用范围。具体而言,本文在利用网络爬虫技术手工整理匹配百万条土地交易信息以及使用两期前沿技术下的曼奎斯特-卢恩伯格指数测度城市绿色全要素生产率的基础上,基于2007—2019年的城市面板数据,运用双重机器学习模型、倾向得分匹配方法等进行了多维检验。研究发现,财政纵向失衡推动了土地财政规模的扩张,阻碍了城市绿色全要素生产率,并且土地财政是重要影响渠道。进一步分析发现,传导渠道会受到环境规制的调节影响,在低环境规制情境下,作用机制的适用性更强。考虑城市异质性特征发现,财政纵向失衡对三线以下城市、非资源型城市以及内陆城市绿色全要素生产率的阻碍作用更强。由此,本文提出完善纵向转移支付体系,降低地方政府对土地财政过度依赖的政策建议。 Based on the characteristics of vertical fiscal imbalance faced by local governments,this paper provides a new theoretical interpretation of how vertical fiscal imbalance affects urban green total factor productivity(TFP)from the perspective of land finance.Furthermore,it quantifies the application scope of the impact in the context of heterogeneous environmental regulations.Specifically,after explaining that green TFP has both environmental and technological connotations,this paper theoretically analyzes and clarifies how vertical fiscal imbalance affects urban green TFP by expanding land fiscal scale and aggravating environmental pollution under the fiscal decentralization system.Then,it uses the web crawler technology of Python software to collect nearly two million pieces of land transaction information,and manually sort out and match them to the city-level land transfer transaction scale,seeking to accurately measure the scale of land finance and reduce the measurement error.At the same time,the biennial Malmquist-Luenberger productivity index(BMLPI)is used to measure urban green TFP.Based on the urban panel data from 2007 to 2019,this paper empirically tests the impact of vertical fiscal imbalance on urban green TFP,and further analyzes the moderating effect of heterogeneous environmental regulation on the channels of action by using double/debiased machine learning(DML),propensity score matching(PSM)and panel Tobit models.The findings reveal that under the fiscal decentralization system,fiscal vertical imbalance expands the land fiscal scale and reduces urban green TFP.The mechanism analysis shows that land finance is an important channel for fiscal vertical imbalance to reduce urban green TFP.Further analysis shows that land finance,as a transmission channel,is affected by environmental regulation,and the applicability of the mechanism is stronger in low environmental regulation.This impact gradually increases with the reduction of the intensity of environmental regulation.Considering urban heterogeneity,it is found that compared with cities above the third tier,resourcebased cities and coastal cities,the vertical fiscal imbalance has a stronger obstacle to green TFP in cities below the third tier,non-resource-based cities and inland cities.This paper proposes to optimize the fiscal expenditure structure of local governments and improve the efficiency of fiscal expenditure to meet the reasonable needs of residents for livelihood public goods and services.It is also necessary to improve the vertical transfer payment system between governments,especially clarifying the specific use,direction and scope of special transfer payments between the central government and local governments.This will reduce regional imbalance,alleviate the fiscal pressure on local governments,and decrease the excessive dependence of local governments on land finance.
作者 吕祥伟 张莉娜 LYU Xiangwei;ZHANG Lina(Shandong Technology and Business University,Yantai 264005)
出处 《经济与管理研究》 北大核心 2024年第4期56-75,共20页 Research on Economics and Management
基金 教育部人文社会科学研究青年基金项目“合村并居”后农村劳动力就业的分化与集聚效应研究(22YJC790101) 山东工商学院科研启动项目“全球价值链嵌入下产业集聚对绿色全要素生产率的影响研究”(014/306480)。
关键词 财政纵向失衡 土地财政 城市绿色全要素生产率 环境规制 双重机器学习模型 fiscal vertical imbalance land finance urban green TFP environmental regulation double/debiased machine learning model
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