Gowhar Meraj
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The role of energy prices in the Environmental Kuznets Curve framework: A systematic review and bibliometric analysis
Haider Mahmood
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Syed Abdul Rehman Khan
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Gowhar Meraj
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Suraj Kumar Singh
doi: http://dx.doi.org/10.21511/ee.17(3).2026.05
Type of the article: Review Article
Abstract
Energy prices are a crucial factor influencing the emissions–income nexus. Hence, this study aims to examine the environmental effects of energy prices within the Environmental Kuznets Curve (EKC) framework through bibliometric analysis and narrative synthesis of empirical studies. For this purpose, 67 Scopus-indexed documents published during 1997–2025 are analyzed. The bibliometric findings reveal that publications have grown at an exponential rate since 2016, peaking at 10 articles in 2023. Bradford’s Law analysis identifies that Environmental Science and Pollution Research is the leading source. Moreover, Lotka’s Law shows that nearly 75% of authors contributed only one or two studies, indicating a diverse research community. Citation analysis further reveals high global citations but limited local citations, suggesting strong external visibility but relatively weak internal connectivity. Thematic analysis identifies carbon dioxide emissions and renewable energy as dominant motor themes, showing increasing scholarly interest in the renewable energy transition due to high energy prices. The empirical synthesis shows that the EKC hypothesis and environmental benefits of high prices are more frequently validated in energy-importing advanced economies. In contrast, studies on energy-exporting economies often fail to validate the EKC hypothesis or report N-shaped EKC patterns, together with adverse environmental effects of energy prices. Overall, the review concludes that the environmental impact of energy prices within the EKC framework varies according to economic development and energy-trade status.Acknowledgment
The authors extend their appreciation to Prince Sattam bin Abdulaziz University for funding this research work through the project number (PSAU/2025/RV/9). All utilized data for analysis are available at Mendeley Data (Mahmood, 2026).
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