| Title | Artificial Intelligence Drives the Coordinated Development of Green Finance and the Real Economy: Empirical Evidence from Chinese Provincial Level |
|---|---|
| ID_Doc | 33712 |
| Authors | Peng, GD; Han, MC; Yuan, HK |
| Title | Artificial Intelligence Drives the Coordinated Development of Green Finance and the Real Economy: Empirical Evidence from Chinese Provincial Level |
| Year | 2023 |
| Published | |
| Abstract | This article constructs the subsystems of modern finance and the real economy by selecting indicators. Using the method of coupling coordination analysis, it measures the coordination status of 30 provinces (municipalities, autonomous regions) in China. The findings show that only 7 provinces are in a coordinated state, while the remaining 23 provinces are in a disordered state. To address this general lack of coordination, we analyze the direct and indirect mechanisms of artificial intelligence (AI) based on its principles of operation and conduct empirical tests. In the empirical analysis, we measure the level of AI innovation development using patent data from the Qizhidao Database and the level of AI technology application using data on industrial robot penetration from the International Federation of Robotics. We employ panel data at the provincial level from 2010 to 2019 and conduct least squares regression tests on the direct and indirect effects of AI. The results are significant and pass robustness tests, endogeneity tests, and heterogeneity tests. The research findings indicate that AI can directly promote the coordinated development of green finance and the real economy by addressing information asymmetry and other issues. It can also indirectly promote their coordinated development by improving institutional levels, technological levels, human capital levels, and government governance capabilities. Furthermore, subgroup analysis reveals that the effects are more pronounced in regions with higher investment in AI research and development, a larger number of AI talents, and better AI infrastructure. These results are consistent with the basic logical understanding. Finally, based on the research conclusions, we propose four policy recommendations to increase the application of AI in the fields of economy and finance. |
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