Zhang Bo, Dong Jiayan, Xiong Meiyi, Gao Xiang
School of Economics and Management, Hefei University, Hefei, China.
Research Center of Finance, Shanghai Business School, Shanghai, China.
Front Public Health. 2025 Mar 28;13:1574787. doi: 10.3389/fpubh.2025.1574787. eCollection 2025.
Green total factor productivity (GTFP) constitutes a fundamental driver for corporate green transitions, closely related to the United Nations sustainable development goals and what China pursues for "new quality productive forces." As a result, it becomes crucial to find out if and how government green credit policies can improve corporate GTFP. To answer these questions, this study uses the Data Envelopment Analysis (DEA) Epsilon-Based Measure (EBM) model and the Malmquist index to create a novel firm-specific GTFP proxy. We find that macro green credit positively and statistically significantly affects corporate GTFP. Further analysis reveals that the concerned effect is functionary through two channels-R&D investment and public supervision. The effect is more prominent for companies in the growth stage, going through a digital transformation, and working in non-polluting or heavily polluting industries. The implications for a sustainable economy are multifaceted from the perspective of policymakers, such as formulating a series of green credit policies on a local level, facilitating environmental information access, and getting every market participant involved and motivated.
绿色全要素生产率(GTFP)是企业绿色转型的根本驱动力,与联合国可持续发展目标以及中国所追求的“新质生产力”密切相关。因此,探究政府绿色信贷政策能否以及如何提高企业绿色全要素生产率变得至关重要。为回答这些问题,本研究使用数据包络分析(DEA)基于ε的测度(EBM)模型和Malmquist指数创建了一个新的企业特定绿色全要素生产率代理指标。我们发现,宏观绿色信贷对企业绿色全要素生产率有正向且在统计上显著的影响。进一步分析表明,相关影响通过研发投入和公众监督两个渠道发挥作用。对于处于成长阶段、正在进行数字化转型以及从事无污染或重污染行业的公司,这种影响更为显著。从政策制定者的角度来看,对可持续经济的影响是多方面的,例如在地方层面制定一系列绿色信贷政策、促进环境信息获取以及让每个市场参与者都参与进来并激发其积极性。