Latent Causal Socioeconomic Health Index

• Main Authors: Kuh, Swen, Chiu, Grace S, Westveld, Anton H
• Format: Journal Article
• Language: English
• Published: 24-09-2020
• Subjects: Quantitative Finance - Economics; Statistics - Applications; Statistics - Methodology
• DOI: 10.48550/arxiv.2009.12217

This research develops a model-based LAtent Causal Socioeconomic Health
(LACSH) index at the national level. Motivated by the need for a holistic
national well-being index, we build upon the latent health factor index (LHFI)
approach that has been used to assess the unobservable ecological/ecosystem
health. LHFI integratively models the relationship between metrics, latent
health, and covariates that drive the notion of health. In this paper, the LHFI
structure is integrated with spatial modeling and statistical causal modeling.
Our efforts are focused on developing the integrated framework to facilitate
the understanding of how an observational continuous variable might have
causally affected a latent trait that exhibits spatial correlation. A novel
visualization technique to evaluate covariate balance is also introduced for
the case of a continuous policy (treatment) variable. Our resulting LACSH
framework and visualization tool are illustrated through two global case
studies on national socioeconomic health (latent trait), each with various
metrics and covariates pertaining to different aspects of societal health, and
the treatment variable being mandatory maternity leave days and government
expenditure on healthcare, respectively. We validate our model by two
simulation studies. All approaches are structured in a Bayesian hierarchical
framework and results are obtained by Markov chain Monte Carlo techniques.