Uneven efficiency, uneven policy: Regional disparities in China's low-carbon transition through a green public economics lens
不均等な効率、不均等な政策:グリーン公共経済学の視点から見る中国の低炭素移行における地域格差 (AI 翻訳)
Yunyun Gao, Pao‐Yu Tang, Ching‐Cheng Lu, Linlin Liu
🤖 gxceed AI 要約
日本語
本研究はDEAモデルを用いて2008〜2020年の中国30省のエネルギー効率とCO2排出を評価し、Bootstrap補正でバイアスを修正した。東部地域は平均0.873と高い一方、中央・西部は0.577・0.607と低く、全国平均は0.690から0.562に下方修正された。地域差は技術格差を反映し、グリーン金融移転に加え技術普及と能力構築の必要性を示唆する。
English
This study uses a DEA model with CO2 as an undesirable output to assess energy efficiency across 30 Chinese provinces (2008-2020), applying Bootstrap correction. Eastern regions average 0.873, while central and western regions lag at 0.577 and 0.607; the national average drops from 0.690 to 0.562 after correction. Disparities reflect technology gaps, suggesting green financial transfers should be complemented by technology diffusion and capacity building.
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
中国の地域別エネルギー効率の実証分析は、日本企業の中国事業におけるサプライチェーン排出量評価や、地域別の政策リスク理解に有用。SSBJ対応でScope 3排出量の算定が求められる中、中国の省別効率データは排出原単位の推定に活用できる。
In the global GX context
This empirical study on China's regional energy efficiency disparities offers insights for global supply chain decarbonization and regional policy design. It complements ISSB/CSRD disclosure requirements by providing sub-national efficiency benchmarks, and highlights the need for differentiated transition finance and technology transfer in developing regions.
👥 読者別の含意
🔬研究者:Provides a robust DEA-Bootstrap methodology for regional energy efficiency assessment, useful for comparative studies.
🏢実務担当者:Offers sub-national efficiency benchmarks for supply chain emissions estimation and risk assessment in China.
🏛政策担当者:Supports regionally differentiated low-carbon policies and green financial transfer mechanisms.
📄 Abstract(原文)
China's fossil fuel-driven economic expansion has intensified environmental pressures, particularly in terms of CO 2 emissions. As the world's largest emitter and a key participant in the Paris Agreement, China's progress in energy efficiency is critical to global climate objectives. This study employs a DEA (Data Envelopment Analysis)-the Banker, Charnes and Cooper model that incorporates CO 2 as an undesirable output to assess energy efficiency and carbon emissions across 30 Chinese provinces from 2008 to 2020, and applies a Bootstrap correction to address bias and variability in efficiency scores. The results reveal discernible variation in energy efficiency across provinces. Five provinces, namely Hebei, Gansu, Guizhou, Shanxi, and Yunnan, consistently exhibit efficiency values below 0.5, while four provinces, namely Beijing, Guangdong, Hainan, and Jiangsu, consistently achieve efficiency values of 1.0. At the regional level, the eastern region has an average efficiency of 0.873, which is higher than the national average of 0.690, whereas the central region (0.577) and western region (0.607) show declining trends. After Bootstrap correction, the national average efficiency decreases from 0.690 to 0.562, suggesting that the initial estimates may be overestimated. These findings highlight the unevenness in energy efficiency and the potential need for regionally differentiated policies, providing support for targeted policy interventions from a green public economics perspective to enhance energy governance and reduce emissions. Efficiency disparities may partly reflect technology gaps. Accordingly, green financial transfers should be complemented by technology diffusion and capacity building in less developed regions. However, given the bootstrap uncertainty, these implications should be drawn with caution and require further empirical support.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1177/0958305x261473097first seen 2026-08-07 05:00:08
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