Heterogeneous effects of energy consumption structure on ecological footprint

Abstract

Attention to environmental sustainability has increased among nations, especially after the Paris Agreement and COP26 of 2021. Considering that fossil fuel consumption is one of the main factors causing environmental degradation, altering the energy consumption patterns of nations toward clean energy can be a suitable solution. For this purpose, this study investigates the impact of energy consumption structure (ECS) on the ecological footprint from 1990 to 2017. This research includes three steps: First, the energy consumption structure is calculated using the Shannon-Wiener index. Second, from 64 countries with middle- and high-income levels, the club convergence method is used to identify countries with similar patterns in an ecological footprint over time. Third, using the method of moments quantile regression (MM-QR), we examined the effects of ECS in different quantiles. The results of club convergence show that the two groups of countries with 23 and 29 members have similar behavior over time. The results of the MM-QR model show that for club 1, the energy consumption structure in quantiles of 10th, 25th, and 50th has positive effects on the ecological footprint, while in 75th and 90th are negative. The results of club 2 indicate that the energy consumption structure has positive effects on the ecological footprint in quantiles 10th and 25th, but negative effects on 75th. Also, the results show that GDP, energy consumption, and population in both clubs have positive effects, and trade openness has negative effects on ecological footprint. Considering that the results indicate that changing the structure of energy consumption from fossil fuels to clean energies improves the environmental quality, so governments should use incentive policies and support packages for the development of clean energy and reduce the costs of installing renewable energy.

Keywords: Club convergence; Ecological footprint; Econometrics; Environmental economics; MM-QR model; Shannon–Wiener index.