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The Impact of Tax Incentives on the Innovative Capacity of Renewable Energy Enterprises in China

Year: 2025
Type: article
Abstract: Stimulating technological innovation in renewable energy enterprises is vital for achieving sustainable development and mitigating climate change. China, as the world’s largest carbon emitter, has enacted various tax incentives aimed at enhancing innovation and alleviating financial pressures in its rapidly growing new energy power generation industry. However, empirical evidence concerning the effectiveness of these incentives, their heterogeneous effects across enterprises, and underlying mechanisms remains limited. This study employs a difference-in-differences (DID) approach combined with fixed-effects regression models using balanced panel data from 112 publicly listed new energy enterprises in China from 2017 to 2023. Additionally, a mediation analysis is conducted to test whether increased electricity generation mediates the relationship between tax incentives and innovation outcomes. The empirical results show that tax incentives significantly boost innovation, as evidenced by increased R&D intensity and patent productivity. However, notable heterogeneity exists private firms respond more strongly than state-owned enterprises; large enterprises benefit more substantially than SMEs; and firms in eastern coastal regions exhibit greater responsiveness compared to inland firms. Furthermore, electricity generation output significantly mediates this relationship, indicating that tax incentives indirectly enhance innovation by improving operational capacity. These findings underscore the importance of targeted fiscal policies. Policymakers should refine tax incentives tailored to firm-specific characteristics such as ownership structure, scale, and geographic location. Enterprises, in turn, should strategically utilize these incentives to strengthen innovation capabilities, thus contributing to sustained competitive advantages and the broader goal of sustainable development.
Language: English
Open Access status: diamond
OpenAlex ID: W4414743127
FWCI: 3.788
Cites: 35
Cited by: 4
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