Can ESG Performance Reduce the Credit Risk of Intelligent Manufacturing Enterprises? —— Theoretical Deduction and Preliminary Evidence Based on Green Innovation and Financing Constraints

Abstract

Amidst the global economic acceleration toward green, low-carbon, and digital transitions, this paper aims to explore the mechanism by which Environmental, Social, and Governance (ESG) performance affects the credit risk of intelligent manufacturing enterprises. Based on a core sample of A-share listed intelligent manufacturing enterprises selected in the Ministry of Industry and Information Technology’s “Publicity List of Intelligent Manufacturing Standard Application Pilot Projects” from 2015 to 2023, this study conducts an exploratory empirical test using a panel two-way fixed effects model and the Distance to Default (DD) from the KMV model, built upon in-depth theoretical deduction. Theoretical logical deduction indicates that ESG performance primarily exerts its credit risk prevention function through the dual paths of “promoting green technological innovation (production side)” and “alleviating financing constraints (capital side)”. Preliminary empirical results reveal that, constrained by the strictly screened sample size and the loss of degrees of freedom caused by two-way fixed effects, the continuous ESG indicator fails to fully pass the traditional statistical significance test; however, its positive coefficient characteristics are highly consistent with theoretical expectations. In the robustness tests where it is replaced with a categorical variable, good ESG performance demonstrates a significant effect of expanding the distance to default and reducing credit risk. Furthermore, combining the nature of property rights and R&D intensity, this paper conducts an in-depth theoretical discussion on the heterogeneous characteristics of this effect. By strengthening theoretical deduction and mechanism logic, this study provides theoretical support and preliminary empirical insights for promoting the sustainable transition and preventing and resolving credit risks within the specific micro-group of intelligent manufacturing enterprises.