Model-based small area predictors are derived under the assumption that data files are complete. In application to real data, files may contain missing values. We introduce a variant of the bivariate Fay-Herriot model that takes into account for missing values in one component of the target...

In model-based small area estimation an explicit statistical model is used to enhance efficiency of estimation in case of small subsamples. This model assumes a fixed relationship between the statistic of interest and a set of covariates, which is valid for all areas under consideration and can,...

We estimate a logit mixture vector autoregressive model describing monetary policy transmission in the euro area over the period 2003Q1-2019Q4 with a special emphasis on credit conditions. With the help of this model, monetary policy transmission can be described as mixture of two states (e.g.,...

Multi-stage cluster sampling is a common sampling design of social surveys because populations of interest are often structured by, or partitioned into, disjoint organizational and administrative units. The need to use cluster sampling can conflict with survey planners' goal to select a sample...

Innovations in statistical methodology is often accompanied by Monte-Carlo studies. In the context of survey statistics two types of inferences have to be considered. First, the classical randomization methods used for developments in statistical modelling. Second, survey data is typically...

In this paper, we estimate a logit mixture vector autoregressive (Logit-MVAR) model describing monetary policy transmission in the euro area over the period 1999..2015. MVARs allow us to differentiate between different states of the economy. In our model, the state weights are determined by an...

An approach to model-based small area estimation under covariate measurement errors is presented. Using a min-max approach, we proof that regularized regression coefficient estimation is equivalent to robust optimization under additive noise. Applying this equivalence, the Fay-Herriot model is...

The joint usage of unit- and area-level data for model-based small area estimation is investigated. The combination of levels within a single model encloses a variety of methodological problems. Firstly, it implies a critical decrease in degrees of freedom due to more model parameters that need...

Microsimulations usually contain various transition processes such as births and deaths, relocations, and change in household characteristics. The estimation, organisation, and implementation of these processes can have a substantial impact on the simulation outcomes. We propose to evaluate a...

Within this article, a generalized calibration approach is presented, which provides coherent and efficient estimates considering a high number of constraints on different hierarchical levels. These constraints may be obtained from different sources such as survey data, register data,...