  We investigate state-level age-specific mortality trends based on the United
States Mortality Database (USMDB) published by the Human Mortality Database. In
tandem with looking at the longevity experience across the 51 states, we also
consider a collection of socio-demographic, economic and educational covariates
that correlate with mortality trends. To obtain smoothed mortality surfaces for
each state, we implement the machine learning framework of Multi-Output
Gaussian Process regression (Huynh & Ludkovski 2021) on targeted groupings of
3-6 states. Our detailed exploratory analysis shows that the mortality
experience is highly inhomogeneous across states in terms of respective Age
structures. We moreover document multiple divergent trends between best and
worst states, between Females and Males, and between younger and older Ages.
The comparisons across the 50+ fitted models offer opportunities for rich
insights about drivers of mortality in the U.S. and are visualized through
numerous figures and an online interactive dashboard.
