Small Area Estimation erlaubt die Schätzung regionaler Indikatoren anhand kleiner Stichproben. Hierfür werden Survey-Daten mehrerer Regionen in statistischen Modellen kombiniert. Aufgrund der Digitalisierung der Gesellschaft entstehen immer mehr zusätzliche Datenquellen, wie etwa Website- und...

Markov chain Monte Carlo (MCMC)-based simulation approaches are by far the most common method in Bayesian inference to access the posterior distribution. Recently, motivated by successes in machine learning, variational inference (VI) has gained in interest in statistics since it promises a...

The ongoing growth of cities due to better job opportunities is leading to increased labour-related commuter flows in several countries. On the one hand, an increasing number of people commute and move to the cities, but on the other hand, the labour market indicates higher unemployment rates in...

Better understanding the geography of women's labor market outcomes within countries is important to inform targeted efforts to increase women's economic empowerment. This paper assesses the extent to which a method that combines simulated survey data from urban areas in Mexico with broadly...

Das Statistische Bundesamt vergibt seit 1999 Förderpreise an junge Wissenschaftlerinnen und Wissenschaftler, seit 2022 den wissenschaftlichen Nachwuchspreis "Statistical Science for the Society". Der Name zeigt die Internationalität des Preises und bringt zum Ausdruck, dass sowohl die...

One popular small area estimation method for estimating poverty and inequality indicators is the empirical best predictor under the unit‐level nested error regression model with a continuous dependent variable. However, parameter estimation is more challenging when the response variable is...

Socioeconomic indicators play a crucial role in monitoring political actions over time and across regions. Income-based indicators such as the median income of sub-populations can provide information on the impact of measures, e.g., on poverty reduction. Regional information is usually published...

Regional prevalence estimation requires the use of suitable statistical methods on epidemiologic data with substantial local detail. Small area estimation with medical treatment records as covariates marks a promising combination for this purpose. However, medical routine data often has strong...

The bivariate Fay–Herriot model is an area-level linear mixed model that can be used for estimating the domain means of two correlated target variables. Under this model, the dependent variables are direct estimators calculated from survey data and the auxiliary variables are true domain means...