An investigation into the primary causes of carbon dioxide releases in Kenya: Does renewable energy matter to reduce carbon emission?

This study estimates the effects of gross domestic product (GDP), population, renewable energy consumption, fossil fuels, and foreign direct investment (FDI) on Kenya's carbon emissions by considering time series data from 1972 to 2021. This investigation makes use of the "Autoregressive Distributed Lag (ARDL)" method, which is grounded in the theoretical framework of the "Stochastic Impacts by Regression on Population, Affluence, and Technology" model known as the STIRPAT model. According to the empirical results, the variables have long-run cointegration. This study lends credence to earlier research by demonstrating that a rise in Kenya's GDP and population can increase the country's CO2 emissions. All estimation methods used in this study also demonstrated that GDP growth has a negative impact on CO2 emissions, while population growth has a positive effect in the long run. In the context of ARDL, the impact of fossil fuels on CO2 emissions is positive but not statistically significant. Achieving Kenya's sustainable development required significant investments in the country's renewable energy infrastructure because renewable energy reduces emissions. Based on these findings, policymakers can make informed decisions about the sustainable use of renewable energy.