Study on Spatial Correlation Between Innovation of Carbon Financial Instruments and Green Investment Efficiency Under the Dual Carbon Target: Integration Analysis Based on ArcGIS and Machine Learning

Xuanyu Wu

doi:10.47297/wspceWSP2516-251925.20250905

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Study on Spatial Correlation Between Innovation of Carbon Financial Instruments and Green Investment Efficiency Under the Dual Carbon Target: Integration Analysis Based on ArcGIS and Machine Learning

Volume 9, Issue 5

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Study on Spatial Correlation Between Innovation of Carbon Financial Instruments and Green Investment Efficiency Under the Dual Carbon Target: Integration Analysis Based on ArcGIS and Machine Learning
Study on Spatial Correlation Between Innovation of Carbon Financial Instruments and Green Investment Efficiency Under the Dual Carbon Target: Integration Analysis Based on ArcGIS and Machine Learning
Macau University of Science and Technology, Macau, 999078, China
Vol. 9, Issue 5, Pages: 132-135(2025)
Published：30 October 2025
DOI：10.47297/wspceWSP2516-251925.20250905
Accepted：

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Wu Xuanyu.Study on Spatial Correlation Between Innovation of Carbon Financial Instruments and Green Investment Efficiency Under the Dual Carbon Target: Integration Analysis Based on ArcGIS and Machine Learning[J].Creative Economy,2025,09(05):132-135.
DOI：

Wu Xuanyu.Study on Spatial Correlation Between Innovation of Carbon Financial Instruments and Green Investment Efficiency Under the Dual Carbon Target: Integration Analysis Based on ArcGIS and Machine Learning[J].Creative Economy,2025,09(05):132-135. DOI： 10.47297/wspceWSP2516-251925.20250905.

摘要

Abstract

Under the background of the "dual carbon" goals

innovation in carbon financial instruments has become a key pathway to enhance the efficiency of green investment. Based on financial geography and spatial econometrics theories

this paper constructs an analytical framework of "carbon financial instrument innovation—spatial spillover—green investment efficiency"

integrating ArcGIS spatial analysis and machine learning methods to explore the spatial impact mechanism of carbon financial instrument innovation on green investment efficiency. Utilizing China's carbon market pilot data from 2018 to 2023

the study comprehensively applies the Spatial Durbin Model (SDM)

XGBoost-SHAP interpretation model

and social network analysis (UCINET) to reveal the spatial differentiation characteristics

efficiency spillover pathways

and causes of regional heterogeneity in carbon financial instrument innovation. The results demonstrate that carbon financial instrument innovation exhibits significant spatial spillover effects

with different instruments (such as carbon futures and carbon bonds) showing regional differences in their impacts on green investment efficiency. This research provides theoretical foundations and empirical support for designing differentiated carbon financial policies.

关键词

Keywords

references

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