Abstract
Green credit is a financial tool stimulating environmental protection by allocating credit funds for cleaner and energy-efficient activities. However, the mechanisms of credit allocation can affect the effectiveness of green credit. This study discusses the concepts of lending discrimination and endogenous clean technology based on the economic growth model with environmental constraints. This allows explaining the mechanism through which lending discrimination and green innovation influence the effect of green credit on (reduction of) environmental impact. Furthermore, empirical data on Chinese provinces from 2012–-2022 confirm that lending discrimination weakens the positive effect of green credit in reducing environmental impact. Additionally, green credit can reduce environmental impact by enhancing corporate green innovation. This study provides theoretical and empirical evidence for understanding the relationship between green credit and environmental impact and offers insights for optimizing green credit.
Zhang, S.; Zhang, C.; Fang, X.; Zhang, D.; Baležentis, T. 2026. How can green credit reduce environmental costs? Analysis based on an extended economic growth model with environmental constraints. Structural change and economic dynamics : Elsevier. ISSN 0954-349X. eISSN 1873-6017. 78, p. 326–342. DOI: 10.1016/j.strueco.2026.04.001. [Scopus; Social Sciences Citation Index (Web of Science)].