An integrated analysis of AI-driven green financing, subsidies, and knowledge to enhance CO2 reduction efficiency

Chien-Chiang Lee, Jafar Hussain and Qasir Abass

Economic Analysis and Policy, 2025, vol. 85, issue C, 675-693

Abstract: The demanding global challenge of climate change necessitates innovative strategies to achieve carbon neutrality, particularly in industrial sectors that contribute significantly to Carbon dioxide (CO2) emissions. In this context, understanding the interplay between Artificial intelligence (AI) driven green financing and targeted subsidies is critical for enhancing emission reduction efficiency (ERE). This research explores a significant advancement in revealing optimal pathways toward carbon neutrality through AI-driven green financing at the industrial level. Robust regression analysis and simulation-based optimization were employed on data from 1000 firms in Punjab, Pakistan. The study indicates the positive impact of knowledge about green awareness, green inventions, and emission impact awareness on CO2 ERE. The finding elaborates that subsidies targeting CO2 emission impact awareness have a more significant influence on CO2 ERE than AI-based green financing, focusing on the pivotal role of targeted financial incentives in achieving effective industrial-level carbon reduction. These insights offer valuable guidance for policymakers and industry practitioners, emphasizing the interconnected dynamics of AI-driven green financing and optimal subsidies in realizing sustainable economic outcomes.

Keywords: Industries; AI-driven green financing; Subsidies; Knowledge; Robust regression; Optimization; CO2 reduction efficiency (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecanpo:v:85:y:2025:i:c:p:675-693

DOI: 10.1016/j.eap.2024.12.021

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