Technological innovation and energy transition in G7 economies: Country-specific evidence from quantile and wavelet approaches
技術革新とG7経済のエネルギー移行：分位点およびウェーブレットアプローチによる国別証拠 (AI 翻訳)
Ayşegül ÖZKAN
🤖 gxceed AI 要約
日本語
本研究は、G7諸国における技術革新（特許出願で代理）が再生可能エネルギー消費に与える影響を、1985〜2021年の年次データとMCQR、QQKRLS、WQGC手法を用いて分析した。結果は非線形かつ分位点依存の関係を示し、国ごとに異なる影響パターンが確認された。これらの知見は、エネルギー移行政策の立案に重要な示唆を与える。
English
This study examines the impact of technological innovation (proxied by patent applications) on renewable energy consumption in G7 countries using annual data from 1985-2021. Employing Modified Cross Quantile Regression, Quantile-on-Quantile Kernel Regularized Least Squares, and Wavelet Quantile Granger Causality, the findings reveal a nonlinear, quantile-dependent relationship that varies across countries. The results provide important implications for policymakers shaping energy transition strategies.
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
日本はG7の一員として分析対象に含まれており、技術革新と再生可能エネルギー消費の非線形関係に関する結果は、日本のエネルギー移行政策やイノベーション戦略に示唆を与える。特に、定量分析による国別の異質性は、日本の政策立案者にとって有用なベンチマークとなる。
In the global GX context
As part of the G7 analysis, this study offers cross-country evidence on the link between innovation and renewable energy adoption. The findings highlight country-specific dynamics that can inform global energy transition policy, particularly for economies like Japan that are balancing technological advancement with decarbonization targets.
👥 読者別の含意
🔬研究者:This paper provides methodological insights into using quantile and wavelet approaches for analyzing nonlinear relationships in energy transition studies.
🏛政策担当者:Policymakers can use the country-specific findings to design targeted policies that leverage technological innovation for renewable energy expansion.
📄 Abstract（原文）
The aim of this study is to examine the impact of technological innovation on renewable energy consumption in the G7 countries. Annual data covering the period 1985-2021 are used, and the analysis focuses on the G7 countries, including Canada, Germany, France, Italy, Japan, the United Kingdom, and the United States. Renewable energy consumption is considered the dependent variable, while technological innovation is represented by patent applications. In order to analyse the relationship between the variables across different distribution levels and time scales more comprehensively, the Modified Cross Quantile Regression (MCQR), Quantile-on-Quantile Kernel Regularized Least Squares (QQKRLS), and Wavelet Quantile Granger Causality (WQGC) methods are employed. The empirical findings reveal the existence of a nonlinear and quantile-dependent relationship between technological innovation and renewable energy consumption. The results also indicate that the impact of technological innovation on renewable energy consumption exhibits a heterogeneous structure across countries and varies across different quantiles. In addition, the findings identify the presence of time- and quantile-dependent causal relationships running from technological innovation to renewable energy consumption. The findings of this study provide important implications for policymakers, energy sector stakeholders, and researchers by improving the understanding of the role of technological innovation in shaping energy transition policies.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.54821/bes.1871090first seen 2026-07-09 05:02:26
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