The present study aims to discover the impact of political risk, globalization and technological innovation on the ecological footprint in the BRICS economies by employing a dataset covering the period between 1990 and 2017 and incorporating non-renewable energy utilization and economic growth as other regressors through the utilization of panel quantile regression. The outcomes established that economic growth, non-renewable energy usage, political risk and technological innovation increase ecological footprint. Conversely, globalization significantly decreases the ecological footprint. The panel ordinary least squares approach serves as a sensitivity test for the robustness of the analysis. Furthermore, the Dumitrescu-Hurlin panel causality test confirmed that a bidirectional causal interaction exists between ecological footprint and the regressors of technological innovation, globalization, non-renewable energy and economic growth, while a one-way causal interconnection runs from ecological footprint to political risk. Notably, the general policy suggestion indicates the need for policymakers to intensively coordinate efforts to combat the serious environmental deterioration in the BRICS economies.

Technological innovations have been a matter of contention, and their environmental consequences remain unresolved. Moreover, studies have extensively evaluated environmental challenges using metrics such as nitrogen oxide emissions, sulfur dioxide, carbon emissions, and ecological footprint. The environment has the supply and demand aspect, which is not a component of any of these indicators. By measuring biocapacity and ecological footprint, the load capacity factor follows a certain ecological threshold, allowing for a thorough study on environmental deterioration. With the reduction in load capacity factor, the environmental deterioration increases. In the context of the environment, the interaction between technological innovation and load capacity covers the demand and supply side of the environment. In light of this, employing the dataset ranging from 1980 to 2017 for the case of South Africa, the bound cointegration test in conjunction with the critical value of Kripfganz and Schneider showed cointegration in the model. The study also employed the ARDL, whose outcome revealed that nonrenewable energy usage and economic growth contribute to environmental deterioration, whereas technological innovation and globalization improve the quality of the environment. This study validated the hypothesis of the environmental Kuznets curve for South Africa, as the short-term coefficient value was lower than the long-term elasticity. Furthermore, using the frequency-domain causality test revealed that globalization and economic growth predict load capacity in the long term, and nonrenewable energy predicts load capacity factors in the long and medium term. In addition, technological innovation predicts load capacity factors in the short and long term. Based on the findings, we propose that policymakers should focus their efforts on increasing funding for the research and development of green technologies.