Abstract
Promoting the ESG concept is of great significance for the realization of the ‘Carbon Peaking and Carbon Neutrality’ Goals and ESG has gradually become a comprehensive system for evaluating sustainable development. Based on the 2015 ESG ratings of SynTao Green Finance as a quasi-natural experiment and based on the panel data of China's A-share listed companies from 2010 to 2020, this study deeply explores the impact of ESG ratings on the continuous innovation ability of enterprises by constructing a multi-temporal double-difference model and a triple-difference model. The results show that ESG ratings can significantly enhance firms’ continuous innovation ability, a conclusion supported by a series of robustness tests. The positive impact of ESG ratings is more prominent for firms with low market attention, state-owned enterprises, and firms with high digital transformation. The impact mechanism suggests that ESG ratings advance firms’ ability to continuously innovate by increasing employment, improving employee income, and enhancing firm value. It is further found that ESG ratings are more effective in enhancing the continuous innovation ability of heavy polluters and capital – and technology-intensive firms than other firms. The findings of the study help to promote the sustainable development of enterprises and realize the synergy between ESG construction and high-quality development.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
The data that support the findings of this study are available upon reasonable request from the corresponding author.
Notes
1 According to the algorithm of sustained innovation capacity is expressed in terms of R&D expenditures (IIP), which is done by adopting a pre-post comparison of R&D expenditures to reflect the degree of innovation continuity. Specifically, the firm’s innovation persistence in year t is equated to the chain growth rate of the sum of the firm’s R&D expenditures between years t-1 and t over the sum of R&D expenditures between years t-2 and t-1, multiplied by the sum of R&D expenditures between years t-1 and t.