Decarbonization Through Data: The Impact of Public Data Openness on Regional Carbon Emissions
データによる脱炭素化：公共データ開放が地域の炭素排出に与える影響 (AI 翻訳)
Zeye Zhang, Jinfang Wang
🤖 gxceed AI 要約
日本語
本研究は、中国の公共データ開放プラットフォームの段階的導入を利用した差分の差分法により、データ開放が地域の炭素排出に与える影響を検証。結果、データ開放が産業高度化、グリーン技術革新、グリーン金融発展、環境規制の強化を通じて炭素排出を有意に削減することを発見。さらに、中部地域や市場化・デジタル基盤の進んだ地域で効果が顕著であり、二酸化硫黄や粉塵などの汚染物質も同時に削減する相乗効果も確認。
English
This study uses the staggered rollout of public data open platforms in China as a quasi-natural experiment and a staggered difference-in-differences method to examine the impact of data openness on regional carbon emissions. It finds a significant decarbonization effect driven by industrial upgrading, green technological innovation, green financial development, and environmental regulation. Heterogeneity shows stronger effects in Central China and provinces with high marketization and digital infrastructure. The study also finds co-benefits in reducing other pollutants like sulfur dioxide and dust.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
中国の実証ではあるが、公共データ開放が脱炭素に寄与する経路（産業高度化、グリーン金融等）は日本でも参考になる。特に、自治体のデータ開放施策とGXの連携を検討する際の示唆となる。
In the global GX context
This paper provides rigorous causal evidence that public data openness can reduce carbon emissions through multiple channels (industrial upgrading, green innovation, green finance, environmental regulation). It expands the global literature on the environmental co-benefits of open data policies and offers insights for designing data-driven decarbonization strategies.
👥 読者別の含意
🔬研究者:A novel quasi-experimental approach (staggered DID) to study the causal effect of data policy on emissions, with rich mechanism and heterogeneity analyses.
🏢実務担当者:Demonstrates that investing in public data infrastructure can indirectly support corporate decarbonization through improved regulatory oversight, green finance access, and innovation incentives.
🏛政策担当者:Highlights the potential of open data platforms as a cost-effective tool for climate mitigation, with synergistic effects on air pollution control.
📄 Abstract（原文）
Utilizing the progressive rollout of public data open platforms as a quasi-natural experiment, this study applies a staggered difference-in-differences (DID) method to investigate the effect of public data openness on regional carbon emissions. The empirical analysis demonstrates a significant decarbonization effect induced by public data openness, and this conclusion survives a battery of robustness tests. Mechanism analyses confirm that the decarbonization effect of public data openness is driven by enhanced industrial upgrading, green technological innovation, green financial development, and environmental regulation. Heterogeneity analyses reveal that the decarbonization effect is statistically significant mainly in Central China, and in provinces characterized by high marketization and advanced digital infrastructure. Furthermore, public data openness demonstrates a substantial capacity for abating environmental pollutants such as sulfur dioxide and dust, thereby validating a synergistic governance effect. Overall, this study demonstrates the positive role of public data openness in reducing regional carbon emissions, thereby theoretically broadening the literature on its environmental consequences while expanding practical pathways for decarbonization.
🔗 Provenance — このレコードを発見したソース
- crossref https://doi.org/10.3390/su18126269first seen 2026-06-19 05:30:13
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