Research Article
Evaluation of the Effectiveness of Green Finance Pilot Policies - An Empirical Study Based on Dual Machine Learning
@INPROCEEDINGS{10.4108/eai.29-3-2024.2347471, author={Tingyan Xiong and Yiting Yan and Yangchen Yu}, title={Evaluation of the Effectiveness of Green Finance Pilot Policies - An Empirical Study Based on Dual Machine Learning}, proceedings={Proceedings of the 3rd International Conference on Bigdata Blockchain and Economy Management, ICBBEM 2024, March 29--31, 2024, Wuhan, China}, publisher={EAI}, proceedings_a={ICBBEM}, year={2024}, month={6}, keywords={green finance; dual machine learning; causal forests}, doi={10.4108/eai.29-3-2024.2347471} }- Tingyan Xiong
Yiting Yan
Yangchen Yu
Year: 2024
Evaluation of the Effectiveness of Green Finance Pilot Policies - An Empirical Study Based on Dual Machine Learning
ICBBEM
EAI
DOI: 10.4108/eai.29-3-2024.2347471
Abstract
Holding the guidance of high-quality green development, vigorously developing green finance has become a consensus in policy and practice. Based on the provincial panel data of 30 provinces in China from 2011 to 2020, this paper uses the double difference and double machine learning method to explore the impact and heterogeneity of establishing green finance reform and innovation pilot zones on local green finance development. The study found that the establishment of pilot zones has improved the local comprehensive development level of green finance, and this impact has significant heterogeneity in fiscal balance, industrial coordination, and environmental regulation. The research conclusion reveals the differences in green finance development and has an enlightening effect on promoting and optimizing green finance policies.
