Bayesian Hierarchical Mix-Effects Approach to Impacts of Air Pollution and Economic Growth on Private Health Care Expenditure

Assessment of the interactive effects of specific macro factors such as air pollution, economic growth, and urbanization on private health care expenditure is vital for social sustainability policies. Nevertheless, to the best of our knowledge, previous studies on this topic focused on economies outside ASEAN and, particularly, were conducted in the out-of-date frequentist framework. Furthermore, empirical outcomes are often different, even contradictory. This research aims to revisit the effects of air pollution, economic growth, and urbanization on private health care expenditure in ASEAN using the Bayesian two-level mixed-effects regression via the Metropolis-Hastings algorithm to capture varying effects of the determinants on the response variable, decreasing model uncertainty. The Bayesian outcomes show that income per capita and air pollution positively and strongly impact private health care expenditure. But, interestingly, the impact of urbanization is ambiguous.