政策の安定性は気候被害が経済成長に与える影響を緩和できるか:北アフリカにおけるグリーン対内直接投資流入からの証拠
Can Policy Stability Buffer Climate Damages on Economic Growth? Evidence from Green Foreign Direct Investment Inflows in North Africa (原題)
FAYOU H, Kaddachi H, Ali B, Saidi H
🤖 gxceed AI 要約
日本語
北アフリカ6カ国・2000〜2022年のパネルデータを用い、気候被害が一人当たりGDP成長に負の影響を与えることをSystem GMMで示した。政治安定性は直接的に成長を押し上げるだけでなく、気候被害の係数を有意に緩和する。さらにグリーンFDI流入がこの緩和効果を増幅させ、再生可能エネルギーやグリーンインフラへの投資が衝撃を吸収することを示唆する。
English
Using a 2000–2022 panel of six North African economies and System GMM, the paper shows climate damages significantly reduce per capita GDP growth. Political stability both directly boosts growth and significantly attenuates climate damage coefficients, while green FDI inflows amplify this buffering effect by channeling capital into renewables and green infrastructure.
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・投資家にとっては、新興国での気候リスクと政策リスクを同時に評価する際の実証的枠組みとして参考になる。特にグリーンボンドや移行金融を通じた北アフリカ向け投融資のリスク評価に示唆を与える。SSBJ・有報のシナリオ分析における海外事業の物理的リスク評価にも応用可能。
In the global GX context
This paper contributes to the global transition finance literature by quantifying how institutional resilience and green FDI jointly buffer climate damages in emerging markets. It offers empirical grounding for sovereign green bond frameworks and bilateral investment treaties, relevant to ISSB/TCFD scenario analysis for cross-border portfolios and to development finance institutions designing climate-resilient capital flows.
👥 読者別の含意
🔬研究者:気候被害・制度品質・グリーンFDIの相互作用を動学パネルで識別する手法と、CDI構築の実証的枠組みを提供する。
🏢実務担当者:北アフリカ等の新興国事業・投融資において、政策安定性とグリーンFDI流入を気候リスク緩和要因として評価する視点を与える。
🏛政策担当者:ソブリングリーンボンド枠組みや二国間投資協定、制度改善を通じて気候耐性資本を誘引する政策設計の根拠を提供する。
📄 Abstract(原文)
<title>Abstract</title> <p> This paper investigates whether policy stability can mitigate the adverse effects of climate-induced damages on economic growth, and whether green foreign direct investment (GFDI) serves as a conduit for this buffering mechanism in North Africa. Using an unbalanced panel dataset covering six North African economies — Algeria, Egypt, Libya, Mauritania, Morocco, and Tunisia — over the period 2000–2022, we employ a two-step System Generalized Method of Moments (System GMM) estimator to address endogeneity, reverse causality, and unobserved heterogeneity. Our empirical strategy integrates a composite Climate Damage Index (CDI) constructed from temperature anomalies, precipitation shocks, and extreme weather event frequencies, alongside the World Governance Indicators (WGI) Political Stability sub-index and UNCTAD-sourced green FDI flows. Results indicate that climate damages exert a statistically significant and economically meaningful negative impact on per capita GDP growth, consistent with the integrated damage function literature. Crucially, policy stability exhibits a strong positive direct effect on growth and, more importantly, significantly attenuates climate damage coefficients through an interactive moderation term, suggesting that institutional resilience functions as an effective buffer. Green FDI inflows amplify this buffering effect: in economies with higher policy stability scores, GFDI channelled into renewable energy, green infrastructure, and environmental technology absorbs a larger fraction of the climate damage shock. Robustness checks using the Difference GMM estimator, alternative governance proxies (Rule of Law, Government Effectiveness), and a jackknife subsample procedure confirm the stability of core findings. These results carry important policy implications for North African governments seeking to leverage sovereign green bond frameworks, bilateral investment treaties, and institutional reforms to attract climate-resilient capital flows. <bold>JEL Classification:</bold> C23; F21; O55; Q54; Q56 </p>
🔗 Provenance — このレコードを発見したソース
- Research Square https://doi.org/10.21203/rs.3.rs-10328826/v1first seen 2026-09-16 04:20:21 · last seen 2026-09-21 04:22:13
🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録(無料・3キーワードまで)。
gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。