Assessing the Function of the Technological Finance Cooperation Pilot Policy in China: Effect on Inclusive Green Growth

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Authors

Guoyong Wu, mengmin Sun

Abstract

To attempt to find a win-win path between environmental conservation and economic expansion, it is especially crucial to accurately define the influence of emerging policies on green effects. Based on the dataset of 282 cities at the prefectural level and above from 2010 to 2020, this paper uses difference-in-difference and dual machine learning models to investigate the impact and internal mechanism empirically of pilot policy combining science technology, and finance on inclusive green urban growth. The results show that the policy of the Technology Finance Cooperation Pilot (TFCP) has a considerable positive influence on inclusive green growth (IGG) in cities, especially when it comes to promoting economic growth and enhancing income distribution. After various robustness tests, the above conclusions are still valid. Meanwhile, from the mechanism analysis results, the policy mainly improves the level of IGG in cities by improving technological progress, enhancing the level of green innovation, and accelerating the development of digital inclusive finance. Furthermore, the impact of the TFCP policy on urban IGG is heterogeneous and mainly depends on the financial condition, geographical location, political status, and industrial characteristics of the city. Further analysis of the spatial effect of policies shows that due to the "siphon effect", the policy of TFCP has an incentive effect on the IGG level of pilot cities, while it has an inhibitory effect on non-pilot cities. Through comprehensive empirical analysis, this study not only strongly validates the positive role of TFCP policy on the IGG of urban economy, but also deeply explores the potential mechanism of this policy, providing new profound insights and enlightenment for policy making.

DOI

https://doi.org/10.31223/X5QD9G

Subjects

Environmental Sciences

Keywords

inclusive green growth, science and technology finance, quasi-natural experiment, dual machine learning, spatial effect

Dates

Published: 2024-10-03 07:28

Last Updated: 2024-10-03 14:28

License

CC BY Attribution 4.0 International

Additional Metadata

Data Availability (Reason not available):
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Conflict of interest statement:
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.