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<p>This study examines the relationship between international financial inflows for clean energy research and development (IFF), foreign direct investment (FDI), economic growth (GDP), renewable energy consumption (REC), natural resource rents (TNRR), and environmental outcomes in 22 Asian countries. The analysis uses panel-corrected standard errors (PCSE) and feasible generalized least squares (FGLS) to evaluate the impact of IFF and other factors on six environmental indicators: total ecological footprint per capita (TEFPC), carbon emissions (carbon), cropland emissions (CPL), fishing grounds (FGG), forest products (FTP), and grazing land (GGL). The results indicate that clean energy financing and renewable energy consumption are associated with lower levels of ecological footprint across several models. In contrast, FDI shows a positive association with higher emissions in the estimated models. Evidence consistent with a non-linear income–environment relationship is observed in selected specifications, aligning with the Environmental Kuznets Curve (EKC) hypothesis. The findings suggest that renewable energy use and clean energy–oriented financial flows are related to environmental outcomes within the sample, while FDI is associated with increased environmental pressure in certain dimensions. The analysis is limited to selected Asian countries, period, indicators, and empirical specifications considered. Overall, the study adds empirical evidence on the relationships among finance, energy, and environmental indicators in a multidimensional context.</p>

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Assessing the environmental impact of international funding for clean energy R&D in Asian economies

  • 期刊论文

  • 发表日期：

    2026年2月27日

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  • Abdul Khaliq,
  • Muhammad Rizwan Yaseen,
  • Madeeha Nisa

摘要

This study examines the relationship between international financial inflows for clean energy research and development (IFF), foreign direct investment (FDI), economic growth (GDP), renewable energy consumption (REC), natural resource rents (TNRR), and environmental outcomes in 22 Asian countries. The analysis uses panel-corrected standard errors (PCSE) and feasible generalized least squares (FGLS) to evaluate the impact of IFF and other factors on six environmental indicators: total ecological footprint per capita (TEFPC), carbon emissions (carbon), cropland emissions (CPL), fishing grounds (FGG), forest products (FTP), and grazing land (GGL). The results indicate that clean energy financing and renewable energy consumption are associated with lower levels of ecological footprint across several models. In contrast, FDI shows a positive association with higher emissions in the estimated models. Evidence consistent with a non-linear income–environment relationship is observed in selected specifications, aligning with the Environmental Kuznets Curve (EKC) hypothesis. The findings suggest that renewable energy use and clean energy–oriented financial flows are related to environmental outcomes within the sample, while FDI is associated with increased environmental pressure in certain dimensions. The analysis is limited to selected Asian countries, period, indicators, and empirical specifications considered. Overall, the study adds empirical evidence on the relationships among finance, energy, and environmental indicators in a multidimensional context.