Spatial dynamic microsimulations allow for the multivariate analysis of complex socioeconomic systems with geographic segmentation. For this, a synthetic replica of the system as base population is stochastically projected into future periods. Thereby, the projection is based on micro-level...

Spatial dynamic microsimulations have distinct potential to operate and project populations on finely detailed geographic level. For this, a detailed building and dwellings data set is typically needed, such that inner-region migration flows and local population developments may be modelled...

Spatial dynamic microsimulations have distinct potential to operate and project populations on finely detailed geographic level. For this, a detailed building and dwellings data set is typically needed, such that inner-region migration flows and local population developments may be modelled...

Modern systems of official statistics require the estimation and publication of business statistics for disaggregated domains, for example, industry domains and geographical regions. Outlier robust methods have proven to be useful for small area estimation. Recently proposed outlier robust...

Small area estimation methods have become a widely used tool to provide accurate estimates for regional indicators such as poverty measures. Recent research has provided evidence that spatial modelling still can improve the precision of regional and local estimates. In this paper, we provide an...