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限界生産性に基づく生産投入モデルを用いた農業炭素削減コストの推計：中国福建省の証拠

Estimation of agricultural carbon abatement costs using a marginal-productivity-based production-input model: evidence from Fujian Province, China (原題)

Jie Ye, Renshan Xie, Qiao Quan, Feng Xie, Huangwei Li, Ketao Lin, Yang JianZhou

Frontiers in Sustainable Food Systems📚 査読済 / ジャーナル2026-10-25#炭素価格Origin: CN対象セクター: agriculture
DOI: 10.3389/fsufs.2026.1953158
原典: https://doi.org/10.3389/fsufs.2026.1953158

🤖 gxceed AI 要約

日本語

本研究は農業炭素排出を生産要素とみなし、トランスログ生産関数とリッジ回帰を用いて福建省9市のパネルデータ（2010–2023年）から炭素排出のシャドウプライスを推計した。シャドウプライスは全省で持続的に上昇し、削減の機会費用が増大している。東部・北部福建で高く南部で低い「東南沿海－西北内陸」の二重空間構造が確認され、漳州・福州・南平が削減コスト最高、厦門が最低であった。

English

Using a translog production function with ridge regression and SFA robustness checks, this study estimates the shadow price of agricultural carbon emissions across nine Fujian cities (2010–2023). Shadow prices rise steadily, indicating growing opportunity costs of abatement, with a clear coastal-inland spatial divide. Zhangzhou, Fuzhou and Nanping show the highest abatement costs and Xiamen the lowest, supporting differentiated regional carbon policy.

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

中国の双炭目標下での農業炭素削減コストの地域差を定量化した研究。日本でも農業分野の脱炭素（J-クレジット農林業系・みどりの食料システム戦略）における地域別インセンティブ設計を考える際の方法論的参照になる。

In the global GX context

Adds empirical evidence on the opportunity cost of agricultural abatement at subnational scale, relevant to carbon-pricing and just-transition debates in agriculture. Methodologically complements global work on shadow pricing and marginal abatement cost curves for non-industrial sectors.

👥 読者別の含意

🔬研究者:農業部門のシャドウプライス推計にトランスログ＋リッジ回帰＋SFAを組み合わせた手法と地域差の実証例を提供する。

🏢実務担当者:農業関連事業者は地域別の削減コスト差を踏まえた調達・投資判断の参考にできる。

🏛政策担当者:地域別に異なる炭素削減コストを根拠に、差別化された農業脱炭素政策・補助設計を検討できる。

📄 Abstract（原文）

The shadow price of agricultural carbon emissions serves as a key indicator for quantifying the cost of carbon reduction in agriculture and for reflecting the associated opportunity costs. It has substantial theoretical and practical relevance for the green development and low-carbon transformation of agriculture under the dual-carbon goals. It holds significant theoretical and practical value for advancing green development and low-carbon transformation in agriculture under the dual-carbon goals. Drawing on marginal productivity theory, this study classifies agricultural carbon emissions as a production factor, builds a translog production function model, and employs ridge regression to address multicollinearity. Using panel data from nine prefecture-level cities in Fujian Province (2010–2023), we measure the shadow prices of agricultural carbon emissions across cities and conduct robustness tests via stochastic frontier analysis (SFA), exploring spatiotemporal evolutionary patterns and the drivers of regional disparities. The key findings are as follows: (1) Fujian’s agricultural carbon emission shadow prices show an overall sustained upward trend, with the economic opportunity cost of per-unit carbon reduction rising consistently across cities. (2) Significant regional disparities exist—the average shadow prices in eastern and northern Fujian remain among the highest in the province, while southern Fujian remains at a lower level, forming a “southeastern coastal–northwestern inland” dual spatial pattern. (3) The shadow price of agricultural carbon emissions varies significantly across regions, with Zhangzhou, Fuzhou, and Nanping having the highest emission reduction costs and Xiamen having the lowest. By quantifying the spatiotemporal characteristics of the costs of agricultural carbon emission reduction in Fujian, this study provides an economic basis for formulating differentiated carbon reduction policies while identifying limitations such as the restricted scope of carbon source accounting and clarifying directions for future research.

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