Estimation of the Global-Scale Ecological Footprint within the Framework of STIRPAT Models: The Quantile Regression Approach

Abstract

Despite the fundamental role of human-induced forces in global environment having changed, knowledge about the specific factors that cause these impacts is limited and uncertainties remain. In this respect, the ecological footprint emerges as a concept used to emphasize both the apparent unsustainability of current practices and the inequalities in resource consumption among countries. The ecological footprint provides a method for measuring how much land can support the consumption of natural resources and provides a precise measure of human impact on the world. In recent years, sustainable development and biological capacity debate has mainly revolved around factors affecting the ecological footprint and approaches to improving environmental quality. Therefore, it is important to determine which factors affect the global ecological footprint. For this aim, a cross-section analysis was carried out with the quantile regression approach applied within the framework of the STIRPAT model structure for 154 countries that were allocated according to their income levels in 2016, taking into account current data. According to the quantile regression findings, the coefficients of the welfare and financial development index are positive and statistically significant. It has been concluded that the population decreases the amount of ecological footprint per person, thus, increasing the total ecological footprint. In addition, it has been determined that the density of the service sector negatively affects the ecological footprint.

Keywords

• kantil regresyon
• ekolojik ayak izi
• stirpat model
• kantil regresyon
• ecological footprint
• stirpat model
• quantile regression