Seismic Risk Features of a Destructive Earthquake Zone

The features of changes in the seismic risk of the zone of a strong earthquake, associated with both destructive consequences and the processes of these recovery. These two factors are the main reason for the change in the seismic vulnerability of preserved (not destroyed) and newly constructed buildings and structures, therefore, changes in the seismic risk of a fairly large area. This problem is not well understood, despite its importance in terms of assessing and reducing risk. The article proposes to divide the zone into subzones on the basis of a specific earthquake, taking into account the intensity and scale of destruction of buildings. This approach makes it possible to more reliably establish the general and local features of the change in the seismic risk of the restored earthquake zone

Bayesian small area estimation for skewed business survey variables

In business surveys, estimates of means and totals for subnational regions, industries and business classes can be too imprecise because of the small sample sizes that are available for subpopulations.We propose a small area technique for the estimation of totals for skewed target variables, which are typical of business data. We adopt a Bayesian approach to inference. We specify a prior distribution for the random effects based on the idea of local shrinkage, which is suitable when auxiliary variables with strong predictive power are available: another feature that is often displayed by business survey data. This flexible modelling of random effects leads to predictions in agreement with those based on global shrinkage for most of the areas, but enables us to obtain less shrunken and thereby less biased estimates for areas characterized by large model residuals.We discuss an application based on data from the Italian survey on small and medium enterprises. By means of a simulation exercise, we explore the frequentist properties of the estimators proposed. They are good, and differently from methods based on global shrinkage remain so also for areas characterized by large model residuals