Spatial effect of economic performance on the ecological footprint: evidence from Asian countries

This study analyzed the systematic use of the spatial econometric technique in estimating the Environmental Kuznets Curve (EKC) for the ecological footprint of Asian countries from 1990 to 2018. The conventional econometric methods often overlook spatial dependence, which can lead to estimation biases. To mitigate potential spatial dependence, we utilized the stochastic impact by regression on population, affluence, and technology (STIRPAT) model. We applied the Spatial Lag Model (SLM), Spatial Error Model (SEM), and Spatial Durban Model (SDM). The estimated results verified the existence of spatial correlation in ecological footprint across countries, and there is strong evidence of EKC between ecological footprint and GDP per capita. In other words, as GDP increases from low to high, ecological degradation increases for a longer period until it reaches a turning point and decreases afterward. The results reveal that energy consumption and urbanization have an adverse impact on the ecological footprint. The study suggests that policymakers should strive to develop consistent and coordinated environmental policies with their neighboring countries to promote sustainable economic growth in the region. Investing in renewable energy is crucial in order to decrease dependence on fossil fuels. Additionally, implementing a well-designed plan for urban populations is necessary to minimize the negative impact on the ecological footprint.