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Spatial Analysis of Research & Development and Environmental Taxation Impacts on Air Pollution in Europe

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  • Syed Jaffar Abbas

Abstract

Air pollution poses significant health and environmental challenges. This study estimates the determinants of PM2.5 air pollution across 31 European countries using a range of econometric techniques, including fixed effects, random effects, system GMM, SAR, SDM, SAR-GMM, and SDM-GMM models. Understanding how various socio-economic and environmental factors interact to influence PM2.5 levels is crucial for effective policymaking. The findings indicate that economic growth, renewable energy, environmental taxes, and research and development expenditures contribute to reducing PM2.5 levels. Conversely, urban population growth is associated with increased PM2.5, highlighting the need for improved urban planning. Spatial econometric models reveal a positive spillover effect, where pollution in one region can significantly impact neighboring areas. Additionally, the regressors exhibit important spatial effects on PM2.5 levels. Univariate analysis of Moran’s I reveals positive spatial autocorrelation in air pollution, while bivariate Moran’s I shows a clear spatial linkage between regressors and PM2.5 levels. Policy recommendations include promoting sustainable economic growth, investing in renewable energy, implementing environmental taxes, enhancing urban planning, increasing research and development, fostering international cooperation, and strengthening regulation.

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  • Syed Jaffar Abbas, 2025. "Spatial Analysis of Research & Development and Environmental Taxation Impacts on Air Pollution in Europe," SAGE Open, , vol. 15(3), pages 21582440251, August.
    • Handle: RePEc:sae:sagope:v:15:y:2025:i:3:p:21582440251367581
    DOI: 10.1177/21582440251367581
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