"This paper suggests an approach for analyzing a dependent competing risks model in presence of partly identified interval data. We apply our nonparametric bounds framework to empirically evaluate the effect of unemployment benefits on the cumulative incidence of local job finding and...

"In many situations the applied researcher wants to combine different data sources without knowing the exact link and merging rule. This paper considers different interpolation methods for interpolating attributes from German labor office districts to German counties and vice versa. In...

"In this paper we derive nonparametric bounds for the cumulative incidence curve within a competing risks model with partly identified interval data. As an advantage over earlier attempts our approach also gives valid results in case of dependent competing risks. We apply our framework to...

"Many popular estimators for duration models require independent competing risks or independent censoring. In contrast, copula based estimators are also consistent in presence of dependent competing risks. In this paper we suggest a computationally convenient extension of the Copula Graphic...

"We analyse the main determinants for job separation with transition to unemployment using individual administrative data from Germany. While the sample size is large and the information in target variables is often highly accurate, non-target variables are subject to considerable measurement...

"We consider an extension of conventional univariate Kaplan-Meier type estimators for the hazard rate and the survivor function to multivariate censored data with a censored random regressor. It is an Akritas (1994) type estimator which adapts the nonparametric conditional hazard rate estimator...

"Unemployment information in individual level register data depends on institutional settings, administrative procedures and which registers are merged. In this paper we suggest different implementation strategies for common international and German legal unemployment definitions for the Sample...