Environmental Sustainability and Aid for Trade: A Load Capacity Factor Perspective Using Panel Quantile Regression

Abstract

This study investigates the environmental implications of Aid for Trade (AfT) flows in developing countries by employing the Method of Moments Quantile Regression (MMQR) framework. By utilizing CO 2 emissions, ecological footprint (EF), and the load capacity factor (LCF) as comprehensive indicators, the research assesses the effects of total, energy‐oriented, and non‐energy‐oriented AfT flows. The empirical findings reveal that total AfT disbursements and their sectoral components yield no statistically significant impact on EF. However, all AfT categories positively impact CO 2 emissions across all quantiles in a statistically significant manner, with the positive effect diminishing in higher‐pollution quantiles. When evaluating environmental quality through the LCF framework, only energy‐specific AfT flows are found to exert a statistically significant negative impact, thereby confirming environmental degradation. These results, verified by Driscoll‐Kraay, 2SLS, and FMOLS estimators, demonstrate that environmental consequences are highly sensitive to the chosen indicator. The study discusses these outcomes via scale and composition effects, advocating for a ‘green’ transformation of AfT. It recommends prioritizing energy aid for renewable energy development, particularly for countries with lower pollution levels, in order to promote sustainable trade practices and environmental quality.