The impact of environmental tax reform on industrial green development: evidence from China
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Bibliographic record
Abstract
Introduction The transformation of environmental protection fees into environmental protection taxes in China reflects a broader commitment to ecological civilization. This reform aligns fiscal instruments with environmental objectives, aiming to internalize environmental costs and incentivize greener industrial behavior. However, empirical evidence on its actual impact on industrial green development remains limited. This study addresses this gap by investigating how the reform affects green total factor productivity (GTFP) in key industrial sectors. Methods We build a Difference-in-Differences model to assess the causal impact of the 2018 environmental tax change, using it as a quasi-natural experiment. A-share listed companies in industries with high levels of pollution from 2013 to 2022 are included in the sample. To further explore the transmission mechanism, we use mediation effect models to test whether the reform influences GTFP through changes in the degree of resource misallocation and green technological innovation. Multiple robustness checks, including parallel trends test, propensity score matching and placebo test, are conducted to ensure result validity. Results The results indicate that the reform significantly improves industrial green development, as measured by firm-level GTFP. In state-owned and highly polluting businesses, the effect is particularly noticeable. According to mechanism testing, the policy effect is communicated through a decrease in the degree of resource misallocation and more investment in green innovation. These findings are robust across alternative model specifications and variable definitions. Discussion This study offers new insights into how environmental tax policies contribute to sustainable industrial transformation. It highlights the importance of fiscal policy tools in steering firm behavior toward greener practices. Policymakers should focus on refining tax enforcement and complementing it with innovation incentives to amplify the reform’s effectiveness. The evidence underscores the critical role of institutional design in aligning industrial growth with environmental goals.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it