Driving Sustainable Innovation in Asia through Environmental Tax Reform in China’s Energy-Intensive Industries
DOI:
https://doi.org/10.62177/amit.v1i6.980Keywords:
Environmental Protection Tax Law, Corporate Innovation, R&D Investment, Heavily Polluting Enterprises, Difference-in-DifferencesAbstract
This study examines the impact of China's 2018 Environmental Protection Tax Law (EPTL) on technological innovation in energy-intensive industries, addressing gaps in understanding how market-based environmental policies influence R&D reallocation and firm behavior in developing economies. Employing a difference-in-differences (DID) framework augmented with propensity score matching (PSM-DID), we analyze panel data from A-share listed firms over 2012–2023, treating heavily polluting enterprises as the experimental group. Innovation is proxied by the natural log of patent applications plus one, with R&D intensity serving as the mediator, and heterogeneity explored across ownership structure, firm size, and technological sophistication. Results indicate that the EPTL significantly boosted patent applications by 25.5% in treated firms, primarily through enhanced R&D investment. Mediation analysis confirms R&D as the key channel, aligning with the Porter Hypothesis by demonstrating how environmental taxes internalize externalities and spur innovation offsets. Heterogeneity effects reveal stronger impacts in state-owned enterprises (coefficient: 0.317), large firms (0.312), and high-tech entities (0.365) compared to counterparts (0.166, 0.160, 0.192), underscoring resource advantages and institutional factors in amplifying policy efficacy. This research contributes novel micro-level evidence on the dynamic mechanisms of environmental taxation, bridging the "Porter Paradox" by highlighting context-specific innovation responses. Findings inform policy design for balancing environmental stringency with economic growth, advocating flexible tax incentives and R&D supports to foster sustainable industrial transformation in emerging markets.
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Copyright (c) 2025 Wei Zhao, Junkang Zhang, Aldis Bulis, Hao Chen

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
DATE
Accepted: 2025-12-29
Published: 2025-12-31











