The Impact of Artificial Intelligence Development on Green Bond Issuance: Evidence From G20 Countries

Abstract

The rapid advancements in artificial intelligence (AI) technologies are transforming the functioning of financial markets and significantly impacting the development of sustainable financing instruments. Green bonds, in particular, have become one of the fastest-growing capital market instruments in recent years for financing climate change mitigation and sustainable development goals. However, empirical studies examining the impact of AI development on green bond markets at the country level remain limited. The aim of this research is to investigate the impact of AI development on green bond issuance in G20 countries using panel data analysis. The study utilizes a panel dataset covering 19 G20 countries from 2016–2021. The ratio of green bond issuance to gross domestic product (GDP) is considered the dependent variable, while AI development is measured using the natural logarithm of the number of AI patents. Per capita GDP, the ratio of domestic loans to private sector GDP, and per capita carbon emissions are included as control variables in the model. Within the scope of empirical analysis, pooled OLS, two-way fixed effects, random effects, Hausman test, and various robustness analyses were applied. The research findings show that the coefficient of the AI patent variable, representing artificial intelligence development, is positive in most models, but it was not statistically significant in the basic two-way fixed effects model. Although a positive and significant relationship was obtained in the robustness analysis using panel-HAC standard errors, alternative model specifications do not strongly support this result. In addition, a high level of multicollinearity was determined between the artificial intelligence indicator and the financial depth variable. This indicates that technological advancement and financial advancement move together and that it is difficult to isolate the independent effect of artificial intelligence. In conclusion, the research reveals a positive but model-sensitive relationship between artificial intelligence development and green bond issuance. The findings show that artificial intelligence investments alone are not sufficient to develop green finance markets; they can contribute more to the development of green bond markets when evaluated together with strong financial systems, institutional capacity, and effective sustainable finance policies. This study is expected to contribute to the literature by examining the relationship between artificial intelligence and green finance at the country level using a panel data approach.