Interplay of Macroeconomics and CO2 Emissions Dynamics: Evidence from Top CO2 Emitting Economies

Abstract

Understanding the dynamic connection between macroeconomic factors and CO2 emissions is vital for developing sustainable and environmentally conscious economic systems. Utilizing a 30-year dataset from the World Bank, focusing on the top 10 CO2-emitting nations, the study employs the Vector Error Correction Model (VECM) to capture both long-term and short-term causal relationships. Descriptive statistics showcase per capita CO2 emissions averaging 8.77 metric tons with notable variability. Key economic indicators, including forest area, foreign direct investment, trade, and GDP, exhibit dynamic trends. Renewable energy consumption averages 15.02%, while energy use per capita stands at 3579.16 kg of oil equivalent. Agricultural land constitutes 32.48%, and the estimated rural population percentage is approximately 33.94%. The VAR model with nine equations is thoroughly evaluated using criteria like BIC (125.280) and HQIC (122.177), signifying model fitting. Coefficients in the model highlight the impact of lagged values on the dependent variable, such as the statistically significant lagged CO2 emissions variable at lag 1. The Impulse Response Function (IRF) illustrates dynamic responses to variable shocks. Forecast Error Variance Decomposition (FEVD) emphasizes the heavy reliance on past values for short-term CO2 forecasts, with external factors gaining significance over longer horizons. This comprehensive approach enhances the understanding of variable contributions to forecast uncertainty, emphasizing the importance of integrating economic development with environmental stewardship.