中国における気候政策の不確実性と農業のデジタル・インテリジェント化：省別パネルデータによる実証
Climate policy uncertainty and agricultural digital-intelligent transformation in China: evidence from provincial panel data (原題)
Wenwen Wang, Yuanyi Yang, Yanru Yu, Yanwei Zhang
🤖 gxceed AI 要約
日本語
中国31省の2013〜2022年パネルデータを用い、農業デジタル・インテリジェント化指数を構築。気候政策の不確実性が同転換を有意に抑制し、その効果はデジタル金融が中程度に発達した地域と主要穀物消費地域でのみ顕著であることを示す。農林畜水産業向け融資と農業社会化サービス政策がこの負の効果を緩和することを明らかにした。
English
Using panel data from 31 Chinese provinces (2013-2022), this study builds an agricultural digital-intelligent transformation index. Climate policy uncertainty significantly inhibits this transformation, with effects concentrated in regions with moderately developed digital finance and major grain-consuming areas. Agricultural loans and socialized service policies moderate and weaken the negative effect.
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
日本では農業のスマート化・GX推進が政策課題だが、本論文は政策不確実性が投資を抑制するメカニズムを実証的に示す点で、国内の農業政策・金融支援設計に示唆を与える。SSBJや有報開示との直接接続は薄い。
In the global GX context
While focused on China, this paper contributes to global scholarship on how policy uncertainty shapes transition investment, relevant to debates on stable climate policy signals for agriculture under frameworks like CSRD and transition finance.
👥 読者別の含意
🔬研究者:政策不確実性が農業転換投資を抑制する因果的証拠と、金融・サービス政策の調整効果を提供する。
🏢実務担当者:農業関連企業・金融機関にとって、政策リスクを織り込んだ投資判断と農村金融活用の示唆となる。
🏛政策担当者:気候政策の予見可能性向上と農村信用支援・農業サービス体系整備の重要性を示す。
📄 Abstract（原文）
Introduction Climate policy uncertainty can affect long-term investment decisions in agriculture, yet its influence on agricultural digital-intelligent transformation remains insufficiently understood. This study examines how lagged climate policy uncertainty affects agricultural digital-intelligent transformation and whether rural finance and agricultural service policies can moderate this relationship. Methods Using panel data from 31 Chinese provinces from 2013 to 2022, we construct an agricultural digital-intelligent transformation index. A two-way fixed effects model, instrumental variable estimation, heterogeneity analysis, and moderation tests are adopted for empirical analysis. Results The results show that climate policy uncertainty significantly inhibits agricultural digital-intelligent transformation, and this negative effect remains evident after addressing potential endogeneity. Heterogeneity analysis indicates that the inhibitory effect is significant only in regions with moderately developed digital finance and in major grain-consuming areas. Further analysis shows that loans to agriculture, forestry, animal husbandry and fishery industries and the pilot policy for full-process socialized agricultural services positively moderate this relationship and weaken the adverse effect of climate policy uncertainty. Discussion These findings contribute to the literature on climate policy uncertainty and sustainable agricultural transformation by linking policy expectations, agriculture-related loans, and digital-smart agriculture development. The results suggest that stabilizing climate policy expectations, improving rural credit support, and strengthening agricultural service systems are important for promoting climate-resilient and regionally differentiated digital transformation in agriculture.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.3389/fsufs.2026.1909691first seen 2026-10-10 05:17:43
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