Accounting for the combined impacts of natural resources rent, income level, and energy consumption on environmental quality of G7 economies: a panel quantile regression approach

Abstract

As the argument widens on the need to cut down on global carbon emissions, this study addresses environmental degradation using a combination of second-generation empirical methodologies including, quantile regression (QR), augmented mean group (AMG), fully modified ordinal least square (FMOLS), and dynamic ordinal least square (DOLS) to examine the impacts of natural resource rents alongside disaggregated energy consumption on the environmental quality of the G7 economies within the framework of the stochastic impact by regression on population, affluence, and technology (STIRPAT) model. The empirical findings reveal that the total natural resources rent indicates a positive significant relationship with pollution in all the quantiles except Q 0.05. Additionally, the findings for renewable energy consumption are adverse and significant throughout the assessed quantiles while fossil fuel energy consumption is reported to have a positive and significant effect on carbon dioxide emissions, thus, increasing environmental degradation experienced in the G7 economies. The extended findings from the Granger causality analysis also show that income levels combined with fossil fuel use have a strong effect on environmental degradation, while the total natural resources rent granger causes clean energy consumption within the G7 countries. This finding supports the assertions that natural resource revenue is mostly channeled into further productivity avenues which consequently lead to further environmental degradation. As such, while maintaining targeted revenue agenda, we strongly recommend that productivity gains from natural resource rents within the G7 economies should be harnessed for investment in clean energy for a more sustainable environment.