In this paper, we propose an indicator of the homeownership rate based on Internet ads offering the housing for rent and sale. We constructed the HOR estimate using the number of ads in four different markets (flats for rent, flats for sale, houses for rent, and houses for sale). Our HOR...

In this paper, we propose an indicator of the homeownership rate based on Internet ads offering the housing for rent and sale. We constructed the HOR estimate using the number of ads in four different markets (flats for rent, flats for sale, houses for rent, and houses for sale). Our HOR...

The paper bases itself on recent theoretical writings in growth economics that empha-size the effects of both own R&D efforts and of interregional technology spillovers on regions´ productivity. We propose robust estimation techniques to evaluate the R&D spillovers across West German functional...

This paper exploits a recent and granular data set for 1,500 German LSIs to conduct a residential mortgage stress testing exercise. To account for model uncertainty when modeling PD dynamics we use a benchmark-constrained Bayesian model averaging approach that combines standard BMA with a...

Knowledge and technological change are often assumed to be the driving forces for long run economic growth. Regions with a higher level of knowledge compared to other regions exhibit a higher per-capita income on average. Agglomeration effects can lead to a steady increase of income and widen...

The aim of this paper is to introduce a new model selection mechanism for cross sectional spatial models. This method is more fexible than the approach proposed by Florax et al. (2003) since it controls for spatial dependence as well as for spatial heterogeneity. In particular, Bayesian and...

The aim of this paper is to introduce a new model selection mechanism for cross sectional spatial models. This method is more flexible than the approach proposed by Florax et al. (2003) since it controls for spatial dependence as well as for spatial heterogeneity. In particular, Bayesian and...

This paper uses Hierarchical Bayes Models to model and estimate spatial health effects in Germany. We combine rich individual-level household panel data from the German SOEP with administrative county-level data to estimate spatial county-level health dependencies. As dependent variable we use...

This paper makes use of Hierarchical Bayes Models to model and estimate spatial health effects. We focus on Germany, combining rich individual-level household panel data with administrative county level information to estimate spatial county-level health dependencies. As dependent variable, we...