デジタル農業の発展は農業の低炭素転換を促進できるか？中国からのエビデンス
Can digital agriculture development drive agricultural low-carbon transition? Evidence from China (原題)
Yi Zhang, Wen Wang, Risheng Gao, Hua Lian
🤖 gxceed AI 要約
日本語
中国30省のパネルデータ（2012-2023年）を用い、デジタル農業発展指数を構築し、農業炭素排出強度への影響を検証。デジタル農業は炭素排出強度を有意に削減し、資本の誤配分の是正が経路の一つであることを示す。空間的波及効果や地域差も明らかにし、新興国でのグリーン農業政策への示唆を提供。
English
Using panel data from 30 Chinese provinces (2012-2023), this study constructs a Digital Agriculture Development Index and examines its impact on agricultural carbon emission intensity. Results show that digital agriculture significantly reduces carbon intensity, partly by correcting capital misallocation. Spatial spillovers and regional heterogeneity are also explored, offering policy insights for green agriculture in emerging economies.
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
日本の農業分野では、みどりの食料システム戦略やカーボンニュートラル目標が掲げられ、スマート農業の導入が進む。本稿のデジタル農業と炭素排出の関係性は、日本の農業政策や企業のサプライチェーン排出削減（Scope 3）の文脈で参考になる。ただし、中国の制度・地域特性を考慮する必要がある。
In the global GX context
This paper contributes to the global literature on digitalization and low-carbon transition in agriculture, a sector often overlooked in climate policy. It provides empirical evidence from China, a major emitter, and highlights the role of capital allocation efficiency. The findings are relevant for emerging economies designing green agricultural policies and for global supply chain decarbonization efforts.
👥 読者別の含意
🔬研究者:Provides empirical evidence on the digital agriculture-carbon nexus, with mechanism and spatial analysis, useful for further research in agricultural decarbonization.
🏢実務担当者:Offers insights for agribusinesses and supply chain managers on how digital technologies can reduce carbon footprint, potentially informing investment decisions.
🏛政策担当者:Highlights the potential of digital agriculture policies to contribute to low-carbon transition, relevant for agricultural and climate policy design.
📄 Abstract（原文）
Agriculture faces the dual challenges of climate change mitigation and food security, and reducing agricultural carbon-emission intensity has become an important pathway toward a low-carbon agricultural transformation. Against the backdrop of rapid digitalization in rural areas, whether digital agriculture development can effectively reduce agricultural carbon emission intensity remains an important empirical question. Using panel data for 30 provincial-level regions in China from 2012 to 2023, this study constructs a Digital Agriculture Development Index from three dimensions: digital human capital and application capacity, digital infrastructure and production conditions, and digital industry and service environment. Agricultural carbon emission intensity is measured based on carbon emissions from major crop production inputs and operations. The results show that digital agriculture development significantly reduces agricultural carbon emission intensity, and this finding remains robust after a series of robustness and endogeneity tests. Mechanism analysis indicates that digital agriculture development is significantly and negatively associated with capital misallocation, while capital misallocation is significantly and positively associated with agricultural carbon emission intensity. For labor and land misallocation, the two estimated relationships are not both statistically significant. Spatial econometric results indicate a significant spatial association between digital agriculture development and agricultural carbon emission intensity. In the heterogeneity analysis, the digital-agriculture coefficient is significantly negative in major grain-producing areas and eastern China and statistically insignificant in non-major grain-producing areas and central and western China. Improvements in capital allocation may partly explain how digital agriculture supports the low-carbon transition of agriculture. The findings offer policy implications for advancing green agricultural development in emerging economies.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.3389/fsufs.2026.1922529first seen 2026-09-03 05:08:05
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