Can Environmental Regulation Result in Environmental and Economic Improvements? Evidence From the Sugar Industry Under China's Mandatory Environmental Information Disclosure Policy
Bibliographic record
Abstract
ABSTRACT Environmental information disclosure (EID) policies have been used in many jurisdictions, yet the impact on the environment and economic performance of enterprises remains a question. This study examines China's mandatory EID policy implemented in 2014 as an example of the potential relationship between environmental policy and enterprise performance. We applied a difference‐in‐differences (DID) and propensity score matching (PSM) sampling method to examine the issue, using a panel dataset of nearly 90 sugar enterprises in Guangxi in China from 2008 to 2016. Earnings before income and tax and pollution emissions are considered as proxies of economic and environmental performance, respectively. The results show that the 2014 MEID policy has a significantly positive effect on pollution reduction and a significantly adverse effect on economy. These effects vary with corporation size and ownership. Production shrinkage appears to be the main reason for pollution reduction in Guangxi's sugar industry rather than technological innovation in the pollution treatment process. Furthermore, we discuss the study's limitations and policy implications.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".