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Government R&D investment in energy and its non-linear environmental effects: Evidence for the USA

エネルギー分野への政府研究開発投資とその非線形的な環境効果：米国の証拠 (AI 翻訳)

Sellami O, Youssef SB

Research Squareプレプリント2026-06-17#エネルギー転換Origin: US対象セクター: energy
DOI: 10.21203/rs.3.rs-10049335/v1
原典: https://doi.org/10.21203/rs.3.rs-10049335/v1

🤖 gxceed AI 要約

日本語

1980～2023年の米国データを用い、再生可能エネルギーおよび化石燃料への政府研究開発支出がCO2排出と再生可能エネルギー消費に与える影響をARDL/NARDLモデルで分析。環境クズネッツ曲線の妥当性を確認し、再エネR&D支出の増加はCO2削減に有効である一方、化石燃料R&Dは逆効果であることを示した。政策立案者への示唆を含む。

English

Using US data from 1980-2023, this study examines the impact of government R&D spending on renewables and fossil fuels on CO2 emissions and renewable energy consumption with ARDL/NARDL models. It confirms the Environmental Kuznets Curve and finds that increased renewable R&D reduces CO2, while fossil fuel R&D has opposite effects. Causal links are identified, offering policy recommendations for R&D allocation.

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

米国を対象とした分析だが、日本でも再エネ関連の研究開発投資が議論されており、R&D支出の環境効果に関する実証エビデンスは日本のエネルギー政策立案にも示唆を与える。特に、非対称効果の検出は投資の増減の影響を考慮する上で有用。

In the global GX context

This paper provides robust econometric evidence on the differentiated impacts of public R&D in renewables vs. fossil fuels, contributing to global debates on innovation policy for energy transition. The use of nonlinear models offers nuanced insights for countries designing green R&D portfolios.

👥 読者別の含意

🔬研究者:Provides empirical evidence on the environmental Kuznets curve and asymmetric effects of R&D, useful for further studies on innovation-led decarbonization.

🏛政策担当者:Highlights the importance of targeting R&D toward renewables to achieve emission reductions, with clear causal implications for budget allocation.

📄 Abstract（原文）

<title>Abstract</title> <p> Amid the escalating climate challenges, this paper aims to provide econometric evidence on the role of research and development in mitigating pollution and promoting clean energy consumption. As proxies for R&D, we select public R&D spending directed to renewable sources (RDR) and to fossil fuels (RDF) in the leading country in terms of R&D spending, the United States, during the period 1980–2023. Using the autoregressive distributed lag model (ARDL), as well as its nonlinear specification (NARDL), we found some interesting results. Specifically, we confirmed the validity of the Environmental Kuznets Curve (EKC) with a turning point estimated at approximately 51140 USD. In addition, positive changes to RDR decrease CO <sub>2</sub> and increase renewable energy consumption (RE), while negative changes have the reverse effect. In contrast, changes to RDF yield effects opposite to those of RDR. Furthermore, based on the Toda and Yamamoto method, we detect a one-way causality running from negative changes in RDF to GDP and CO <sub>2</sub> . In light of these results, we recommend that US policymakers increase spending on R&D, particularly in the field of renewable energy, given its benefits for clean energy consumption and pollution reduction. <bold>JEL classifications :</bold> Q42, Q43, Q53, O31, O33, C32 </p>

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