気候変動、二酸化炭素排出、および作物生産：チュニジアからの実証的証拠
CLIMATE CHANGE, CARBON DIOXIDE EMISSIONS, AND CROP PRODUCTION: EMPIRICAL EVIDENCE FROM TUNISIA (原題)
Jihène Khalifa
🤖 gxceed AI 要約
日本語
チュニジアの1996〜2024年データを用い、NARDLモデルで気温・降水量・CO2排出が作物生産に与える影響を分析。短期的にはCO2排出増が作物生産を有意に減少させ、長期的にも持続的な負の影響を及ぼすことを示す。肥料使用は正の効果を持ち、非対称的な関係も確認された。気候スマート農業と低炭素開発への投資を提言する。
English
Using Tunisian data (1996–2024) and a NARDL model, this study examines how temperature, precipitation, and CO₂ emissions affect crop production. Rising CO₂ emissions significantly reduce crop output in both the short and long run, while fertilizer use has a positive effect. Asymmetric dynamics are identified, and the authors recommend climate-smart agriculture and low-carbon development to protect food security.
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
日本企業のGX文脈では直接の接点は薄いが、気候変動が農業サプライチェーンや食料安全保障に及ぼす物理的リスクを定量的に示す点は、TCFD/SSBJの物理的リスク評価や食品・農業関連企業の適応策検討に参考となる。
In the global GX context
This paper adds to the global evidence base on physical climate risk in agriculture, relevant to TCFD/ISSB physical-risk disclosure and adaptation finance. It offers a developing-economy, non-linear perspective that complements predominantly OECD-focused climate-agriculture literature.
👥 読者別の含意
🔬研究者:NARDLによる非対称効果の実証は、気候-農業研究における非線形モデリングの応用例として参考になる。
🏢実務担当者:食品・農業サプライチェーンを持つ企業が、気候変動による原材料調達リスクを評価する際の定量的根拠となりうる。
🏛政策担当者:気候スマート農業や低炭素開発への投資判断において、途上国農業の脆弱性を示すエビデンスとして活用できる。
📄 Abstract（原文）
This study investigates the effects of climate change and carbon dioxide (CO₂) emissions on crop production in Tunisia over the period 1996–2024. Given the increasing challenges posed by climate variability and environmental degradation to agricultural sustainability, this research contributes to the achievement of the United Nations Sustainable Development Goals (SDGs), particularly SDG 2 (Zero Hunger), SDG 13 (Climate Action), and SDG 15 (Life on Land). To capture both linear and asymmetric dynamics, the Nonlinear Autoregressive Distributed Lag (NARDL) model is employed to examine the impacts of average temperature, precipitation, and CO₂ emissions on agricultural productivity. The empirical findings reveal that, in the short run, rising CO₂ emissions significantly reduce crop production, highlighting the immediate adverse effects of environmental degradation on Tunisia’s agricultural sector. In the long run, CO₂ emissions exert a substantial and persistent negative impact on agricultural productivity, suggesting that continued environmental pressures may threaten food security and sustainable agricultural development. Conversely, fertilizer use has a significant positive effect on crop production, underscoring its role in supporting agricultural output and resilience. Although arable land, average temperature, and precipitation exhibit positive associations with crop production, their estimated effects are not statistically significant. Furthermore, the NARDL analysis uncovers important asymmetric relationships, demonstrating that positive and negative shocks in climate-related variables and CO₂ emissions affect agricultural output with differing magnitudes and directions. These findings emphasize the vulnerability of Tunisia’s agricultural system to climate change and environmental degradation while highlighting the importance of adaptive agricultural practices and effective climate mitigation policies. The study recommends strengthening investments in climate-smart agriculture, sustainable land management, and low-carbon development strategies to enhance agricultural resilience, support long-term food security, and advance progress toward the SDGs.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.5281/zenodo.22142273first seen 2026-09-18 04:36:42 · last seen 2026-09-18 04:36:44
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