This research develops a model-based LAtent Causal Socioeconomic Health
(LACSH) index at the national level. We build upon the latent health factor
index (LHFI) approach that has been used to assess the unobservable
ecological/ecosystem health. This framework integratively models the
relationship between metrics, the latent health, and the covariates that drive
the notion of health. In this paper, the LHFI structure is integrated with
spatial modeling and statistical causal modeling, so as to evaluate the impact
of a continuous policy variable (mandatory maternity leave days and
government's expenditure on healthcare, respectively) on a nation's
socioeconomic health, while formally accounting for spatial dependency among
the nations. A novel visualization technique for evaluating covariate balance
is also introduced for the case of a continuous policy (treatment) variable. We
apply our LACSH model to countries around the world using data on various
metrics and potential covariates pertaining to different aspects of societal
health. The approach is structured in a Bayesian hierarchical framework and
results are obtained by Markov chain Monte Carlo techniques.Comment: 31 pages. arXiv admin note: substantial text overlap with
arXiv:1911.0051