Dynamic and Asymmetric Influence of Financial Credit, Economic Growth and Technological Innovation on the Ecological Footprint in Sub-Saharan Africa

Abstract

We used a machine learning technique (Kernel Regularized Least Squares, KRLS) to investigate the dynamic and asymmetric influence of financial credit, economic growth and technological innovation (i.e. trade marks) on ecological footprints in 19 selected sub-Saharan African (SSA) countries from 2000 to 2022. The findings show that financial credit, economic growth and technological innovation have asymmetric/non-linear influence on the ecological footprint. A 1% increase in financial credit (domestic credits to the private sector) reduces the ecological footprint by 0.14%. In turn, financial credits decrease the ecological footprint in the 10th to 80th percentiles while increasing it in the 90th percentile. This suggests that financial credit reduces the ecological footprint and a larger increase in financial credit increases it. Economic growth reduces the ecological footprint by 0.003% at the 10th percentile and increases it at the 20th to 90th percentiles. This implies that an increase in economic growth initially reduces the ecological footprint, and a greater increase in economic growth increases the ecological footprint. The findings reveal that technological innovation reduces the ecological footprint in the 10th to 40th percentiles while increasing it in the 50th to 90th percentiles. This suggests that technological innovation initially reduces the ecological footprint, and a steady increase in technological innovation greatly increases the ecological footprint in SSA. The results are robust, supported by Bayesian estimates. To tackle the ecological footprint challenges in SSA, policy implications should introduce green technologies as a means to mitigate the impact of economic growth and financial credit on the ecological footprint in SSA, ultimately promoting climate change mitigation and achieving sustainable development goals by 2030.