An Applied Comparison of Area-Level Linear Mixed Models in Small Area Estimation

This article reviews four area-level linear mixed models that borrow strength by exploiting the possible correlation among the neighboring areas or/and past time periods. Its main goal is to study if there are efficiency gains when a spatial dependence or/and a temporal autocorrelation among random-area effects are included into the models. The Fay–Herriot estimator is used as benchmark. A design-based simulation study based on real data collected from a longitudinal survey conducted by a statistical office is presented. Our results show that models that explore both spatial and chronological association considerably improve the efficiency of small area estimates.     

Guns and Suicides

There is a consensus in the literature that the ratio of suicides committed with guns to total suicides is the best indirect measure of gun ownership. However, such a proxy is not accurate for any locality with low population density in view that suicides are rare events. To circumvent this issue, we exploit the socioeconomic characteristics of the suicide victims in order to come up with a novel proxy for gun ownership. We assess our indicator using suicide micro-data from the Brazilian Ministry of Health between 2000 and 2010.