The impact of climate change and technological innovation on economic recovery in sub-Saharan Africa: A machine learning perspective

Abstract

The COVID-19 pandemic has led to a global economy slowdown. Sub-Saharan Africa’s (SSA) economy is gradually recovering from the pandemic. This study examines whether climate change variables (such as temperature, carbon dioxide emissions) and technological innovation (measured by total patent applications) can forecast the economic recovery of 19 selected countries in SSA from 2000 to 2022. We applied Kernel-based Regularized Least Squares (KRLS), a machine learning technique, while controlling for financial development, human capital and inflation rates. Our findings indicate that climate change exerts a negative and significant influence on SSA's economic recovery. Specifically, rise in average annual surface temperature change and carbon dioxide emissions decrease in economic recovery. An increase in average technological innovation improves in economic recovery. Inflation rate is associated with reduction in economic recovery. We discuss policy implications and mechanisms through which technological innovation and climate change affect the SSA economy, offering practical policy suggestions.