Work

Examining the impact of green finance and green innovation on sustainable economic development using machine learning methods

Year: 2025

Type: article

Abstract: Owing to the greater need for sustainable development, the current study examines the influence of green finance and green innovation on sustainable economic development in 82 economies, including 35 developed and 47 developing economies. We employ advanced panel estimation techniques, including GLM, difference GMM, and bootstrap quantile regression, to examine the long-run effects. For robustness, we further integrate machine learning models to capture non-linearities and complex interactions. We find that green finance and green innovation contribute to sustainable economic development by reducing emissions. Moreover, our research indicates that the positive correlation between Green Finance, Green Innovation, and Sustainable Economic Development is notably more robust in developed nations compared to developing ones. These insights offer important policy directions for promoting financial instruments and innovative practices that accelerate sustainability transitions in developing economies.

Source: Discover Sustainability

DOI: 10.1007/s43621-025-02191-9

Authors: Raazia Gul, Shahzad Hussain, Asra Shaikh, Nader Naifar

Institutions: Shaheed Zulfiqar Ali Bhutto Institute of Science and Technology, Rawalpindi Women University, Imam Mohammad ibn Saud Islamic University

Language: English

Topic: Sustainable Finance and Green Bonds

Subfield: Finance

Field: Economics, Econometrics and Finance

Domain: Social Sciences

SDGs: Decent work and economic growth, Industry, innovation and infrastructure, Climate action, Partnerships for the goals

Open Access status: gold

Estimated APC paid: $1,390