Paula Martinez, Anish Pati, Richard Rian, Jeremiah Soliman, James Zabala
This study explores the relationship between GDP and CO2 emissions across different income brackets, focusing on the validity of the Environmental Kuznets Curve (EKC) hypothesis. It investigates whether economic growth leads to increased environmental degradation, as represented by CO2 emissions, before a turning point is reached where further economic development corresponds with environmental improvement. Through statistical analysis and regression models, the research seeks to discern the patterns of CO2 emissions in developed and developing countries, thereby shedding light on the global dynamics of economic development and environmental sustainability.
We started with processing data, selecting specific countries, merging datasets, and preparing them for isolated regression models. We then created a user-friendly pipeline for the regression model functions. Our statistical analysis aims to answer key questions about the Earth's healing, COVID-19's impact on GDP, and GDP per capita variances across income brackets, using T-tests and ANOVA for hypothesis testing. Finally, we conducted a linear regression analysis to investigate the relationship between GDP and CO2 emissions of the selected countries.
It would be interesting to explore the defining characteristics influencing a country's level of emissions. Dimensionality reduction techniques may help unravel this narrative. Naturally, it's imperative to include more socio-economic and/or demographic variables for a more holistic analysis.