Impact of Macroeconomic Variables and Mortality Rates Under 5 on CO2 Emissions: A Case Study of Lithuania

This study examined how Lithuania’s CO2 emissions were affected by macroeconomic variables and mortality rates between 1995 and 2020. ARDL analysis, cointegration regression, diagnostics test, and robustness test were used to quantify the impact of mortality rates, macroeconomic variables, and CO2 emissions. The findings of the unit root test confirmed that all variables are stationary. Similarly, the ARDL bound test values show that the variables are cointegrated and that a long-run relationship exists between them. However, the ARDL methods both showed that mortality rates, trade openness, and economic growth have a significant positive impact on CO2 emissions. Hence, renewable energy consumption helps reduce CO2 emissions. Furthermore, diagnostic tests confirmed no serial correlation, no heteroscedasticity exists, and robust tests also show that the model is stable. While cointegration regression results are similar to the ARDL model test. The study analysis suggests the essential policy recommendations aimed at reducing CO2 emissions and the need to improve health sectors (specifically, mortality rates under 5). This study expands the existing literature on environmental economics, and its findings will help improve policy and frameworks in Lithuania to reduce carbon emissions.