The driving effect of digital finance on green total factor productivity-analysis based on double/debiased machine learning model and spatial durbin model

被引:1
作者
Shi, Pengfei [1 ]
Zhang, Honghao [2 ]
Sun, Chaojing [3 ]
Wang, Xinrui [4 ]
Li, Xingming [2 ]
机构
[1] Southwest Univ, Sch Econ & Management, Chongqing, Peoples R China
[2] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan, Peoples R China
[3] Shandong Lab Vocat & Tech Coll, Jinan, Peoples R China
[4] Shandong Vocat & Tech Univ Int Studies, Sch Foreign Languages, Rizhao, Peoples R China
关键词
Digital finance; Tourism green total factor productivity; Double/debiased machine learning model; Spatial durbin model;
D O I
10.1016/j.frl.2025.107463
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
As a crucial component of modern finance, digital finance significantly contributes to enhancing the green economic development. Based on the panel data from 2011 to 2021, this paper explored the impact of digital finance on the tourism green total factor productivity by double/debiased machine learning model and spatial durbin model. The research findings are as follows: (1) Digital finance has significant promoting effect. The tourism green total factor productivity has exhibited a steady upward trend. (2) Technology innovation serves as a critical mediator, facilitating green development in industries through technology diffusion. There are significant differences in the effectiveness of digital finance in different regions. (3) Digital finance not only directly improves the local development, but also fosters the coordinated development of surrounding cities through spatial spillover effects, accelerating the green and high-quality transformation of the region. This paper proposes policy recommendations to accelerate the construction of digital financial infrastructure, enhance regional coordination, and promote innovation-driven development.
引用
收藏
页数:12
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