Exploring the interrelationship among health status, CO(2) emissions, and energy use in the top 20 highest emitting economies: based on the CS-DL and CS-ARDL approaches

Carbon dioxide emissions (CO(2)e) which is caused by energy use contributes to the global average surface temperature increase by 1.5 °C as compared to the mid-1800s which is causing a certain change in the climate and becoming an adverse effect on health and economy. The relationship between health status, CO(2)e, and energy use has yet to be thoroughly investigated in the top 20 highest emitting economies. The data from 2000 to 2019 is analyzed by using advanced techniques of cross-sectional augmented distributed lag (CS-DL) and cross-sectional augmented autoregressive distributed lag (CS-ARDL) which take into consideration crucial elements of panel data, namely dynamics, heterogeneity, and cross-sectional dependence. Moreover, cross-sectional augmented error correction method (CS-ECM) and the common dynamic process of the augmented mean group (AMG) are applied for robustness checks. The empirical findings revealed that (i) CO(2)e weakens the health status only in the short-run, whereas health expenditure improves the health status in the both short- and long-runs, while economic growth is not contributing to the health status in the both short- and long-runs; (ii) health expenditure and economic growth only help to mitigate CO(2)e in the long-run, whereas energy use causes CO(2)e in the both short- and long-runs; (iii) energy use causes high economic growth in the both short- and long-runs, whereas CO(2)e aids economic growth in the short-run but is extremely damaging to economic growth in the long-run, while in the both short- and long-runs health expenditure is not aiding the economic growth. This study provides policy recommendations on improving human health by advocating massive health expenditures, CO(2)e easing, promoting renewable energy use or low-emission energy, and steering the economy toward green economic growth. GRAPHICAL ABSTRACT: [Image: see text]