Does the goal of food security hinder the agricultural green and low-carbon transformation? Evidence from China
食料安全保障の目標は農業のグリーン・低炭素転換を妨げるか？中国からの証拠 (AI 翻訳)
Guoqun Ma, Zhiyu Qin, Lihao Yao, Ziqi Mou
🤖 gxceed AI 要約
日本語
中国の主要穀物生産地域指定政策を自然実験として、農業の炭素排出削減と汚染低減効果をDIDと二重機械学習で検証。政策は排出削減に有効で、作物構造調整と緑色技術進歩が経路であることを示した。
English
Using China's major grain-producing areas designation as a quasi-natural experiment, this study employs DID and double machine learning to show the policy significantly reduces agricultural carbon emissions and pollution, with crop structure adjustment and green technology progress as key channels.
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
日本の農業分野におけるGX推進や、食料安全保障と環境政策の両立を考える上で、政策評価の方法論が参考になる。日本の農業政策や地域振興策への示唆が得られる。
In the global GX context
This study contributes to global scholarship on agricultural decarbonization and food security trade-offs, offering rigorous causal evidence and novel ML methods that can inform policy design in other countries.
👥 読者別の含意
🔬研究者:農業分野の低炭素転換と政策評価の因果推論に興味がある研究者は、DIDと二重機械学習の応用例として参照できる。
🏢実務担当者:農業関連企業やサプライチェーン担当者は、政策による排出削減効果と技術導入の重要性を理解するのに役立つ。
🏛政策担当者:農業政策と環境政策の統合を検討する際に、主要生産地域指定の効果と限界を示すエビデンスとして有用。
📄 Abstract（原文）
Agricultural production is crucial to food security and the realization of carbon reduction targets. Whether green and low-carbon development of agriculture can be achieved on the basis of ensuring food security is a common challenge faced by all economies. This study takes China’s 2004 designation of 13 major grain-producing areas as a quasi-natural experiment. Using provincial panel data from 2000 to 2022, a difference-in-differences model is constructed to explore if the policy can boost green transformation while ensuring yield growth. The findings reveal that the policy significantly reduces carbon emissions and agricultural non-point source pollution, with robustness confirmed by placebo tests, PSM-DID, and double machine learning. Crop structure adjustment and green technological progress have been identified as two key channels for promoting carbon reduction effects, among which labor force transfer plays a non-linear moderating role. Heterogeneity analysis indicates that excessive concentration of grain production is detrimental to the reduction and control of agricultural pollution, while the pollution reduction effect of the policy is more pronounced in regions with moderate to high levels of labor aging. It is recommended to further encourage appropriately scaled operations, promote the application and innovation of green agricultural technologies, and tailor strategies to local conditions to achieve agricultural green transformation, while continuing to uphold the major grain-producing areas policy.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1186/s13021-026-00490-wfirst seen 2026-07-28 05:05:37
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