Exploring role of energy-related research and development investments, income, and energy sub-types on environmental change in the USA by marginal effect analysis
米国における環境変化に対するエネルギー関連研究開発投資、所得、エネルギーサブタイプの役割を限界効果分析により探る (AI 翻訳)
Mustafa Tevfik Kartal, Dilvin Taşkın, Özer Depren, Fatih Ayhan
🤖 gxceed AI 要約
日本語
本研究は、米国の1974～2022年のデータを用い、カーネルベース最小二乗法（KRLS）モデルで限界効果分析を行った。その結果、エネルギー関連R&D投資のサブタイプはCO2排出に有意な効果を持たず、所得構造もグリーン経済に寄与せず、再生可能エネルギーのみがCO2排出削減に有効であることが示された。原子力と化石エネルギーは排出を増加させる。KRLSモデルの推定能力は約99.7%と高い。
English
Using US data from 1974 to 2022, this study applies a kernel-based least squares (KRLS) model for marginal effect analysis. Findings: energy-related R&D investment subtypes have insignificant effect on CO2 emissions; income structure does not support greening; among energy subtypes, only renewable energy reduces CO2 emissions, while nuclear and fossil increase them. The KRLS model shows high estimation capability (~99.7%).
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
本論文は米国を事例としているが、日本においてもエネルギー関連R&D投資の効果や再生可能エネルギーの重要性を再認識させる。日本のGX政策において、R&D投資の効果検証や再生可能エネルギーへの重点投資の必要性を示唆する。
In the global GX context
This study adds to the global literature on the effectiveness of energy R&D investments and the critical role of renewable energy in reducing CO2 emissions. It challenges the assumption that all R&D investments contribute to decarbonization, informing global climate policy.
👥 読者別の含意
🔬研究者:Researchers can use the KRLS model as a robust method for marginal effect analysis in environmental studies, and the findings challenge the assumed effectiveness of energy R&D.
🏢実務担当者:Corporate sustainability teams should note that only renewable energy among energy subtypes significantly reduces emissions, guiding energy sourcing decisions.
🏛政策担当者:Policymakers should reconsider the structure of energy R&D investments and prioritize renewable energy deployment over nuclear and fossil support.
📄 Abstract（原文）
In response to the climate change problem, ensuring a transformation to green economies is highly critical. Therefore, countries have been trying to make their economies decarbonized by taking various measures. Accordingly, this study examines the USA case by using carbon dioxide emissions (load capacity factor) as the main (robustness) environmental proxy, considers energy-related research and development (R&D) investment types as main explanatory variables, controls income and energy utilization sub-types, and performs a novel kernel-based least squares (KRLS) model on data from 1974 to 2022 to apply a marginal effect analysis. The results show that (i) R&D investment sub-types have an insignificant effect on carbon dioxide (CO 2 ) emissions; (ii) income structure does not contribute in greening economy; (iii) among energy utilization sub-types, only renewable energy has a decreasing effect on CO 2 emissions, whereas nuclear and fossil energy sub-types have a reverse ones; (iv) the effects of the factors on CO 2 emissions differentiate across percentiles and estimation models; (v) the robustness of the empirical results are verified based on alternative indicator; (vi) the KRLS model has a high estimation capability around 99.7%. Hence, the empirical results reveal the critical role of renewable energy use, while the current R&D investment structure, energy utilization, and income are not supportive of a green economy in the USA because these do not provide a decrease in CO 2 emissions.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1177/0958305x261428671first seen 2026-05-05 19:16:25
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。