<![CDATA[As environmental pollutants, particularly carbon dioxide (CO₂), pose increasing health risks, understanding how inequality influences this relationship becomes critical for policy and development planning. This study examines how income inequality and environmental degradation affect health outcomes (LER) using an ARDL model. The model includes CO2, GINI, their interaction (CO2*GINI), PGDP, EC, GCE, and PST. The ARDL approach is chosen for its flexibility with mixed integration orders and inclusion of both current and lagged variables. To verify cointegration, the Bounds test and error correction model (ECM) are applied. DOLS estimation, preferred over FMOLS for addressing endogeneity and serial correlation, is also used (Mark & Sul, 2003; Osabuohien et al., 2014). Data from 1990–2023 are sourced from WDI, WGI, and CBN. Robustness checks include ARCH, Breusch-Godfrey, and Cusum tests. Results reveal that in the long run, most variables, including CO2, GINI, and GINI*CO2, had negative but statistically insignificant effects on life expectancy (LER), except in FMOLS where GINI*CO2 was significantly negative. In the short run, CO2, GINI, and their lags significantly increased LER, while GINI*CO2 showed a mixed effect—negative initially, positive when lagged. PGDP and GCE had mixed impacts. The 12% error correction rate confirms adjustment to equilibrium. The null hypothesis is not rejected, as GINI*CO2 lacks significant long-run influence. Recommendations include implementing policies that reduce CO₂ emissions, promote equitable income distribution, and strengthen healthcare infrastructure to improve long-term health outcomes.]]>
Copyrights © 2025
