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Pollutant emissions from coal-burning power plants have been deemed toadversely impact ambient air quality and public health conditions. Despite thenoticeable reduction in emissions and the improvement of air quality since theClean Air Act (CAA) became the law, the public-health benefits from changes inemissions have not been widely evaluated yet. In terms of the chain ofaccountability (HEI Accountability Working Group, 2003), the link betweenpollutant emissions from the power plants (SO2) and public health conditions(respiratory diseases) accounting for changes in ambient air quality (PM2.5) isunknown. We provide the first assessment of the longitudinal effect of specificpollutant emission (SO2) on public health outcomes that is mediated throughchanges in the ambient air quality. It is of particular interest to examine theextent to which the effect that is mediated through changes in local ambientair quality differs from year to year. In this paper, we propose a Bayesianapproach to estimate novel causal estimands: time-varying mediation effects inthe presence of mediators and responses measured every year. We replace thecommonly invoked sequential ignorability assumption with a new set ofassumptions which are sufficient to identify the distributions of the naturalindirect and direct effects in this setting.

Bayesian Longitudinal Causal Inference in the Analysis of the Public Health Impact of Pollutant Emissions