Contemporary financial stochastic programs typically involve a trade-offbetween return and (downside)-risk. Using stochastic programming we characterize analytically (rather than numerically) the optimal decisions that follow from characteristic single-stage and multi-stage versions of such...

We propose a multi-stage stochastic trading cost model in optimal portfolio selection. This strategy captures uncertainty in implicit transaction costs incurred by an investor during initial trading and in subsequent rebalancing of the portfolio. We assume that implicit costs are stochastic as...

We study the regional distribution of primary care physicians in Germany to learn about the extent and possible reasons of geographic maldistribution. For this aim, we apply a greedy capacitated algorithm on very fine spatial data. We compare this reference allocation of primary care physicians...

We study the regional distribution of primary care physicians in Germany to learn about the extent and possible reasons of geographic maldistribution. For this aim, we apply a greedy capacitated algorithm on very fine spatial data. We compare this reference allocation of primary care physicians...

In this paper I develop a consistent estimator of the population average treatment effect (PATE) which is based on a nonstandard version of the Oaxaca-Blinder decomposition. As a result, I extend the recent literature which has utilized the treatment effects framework to reinterpret this...

In this paper, we consider a detailed decomposition method for limited dependent variable models. That means, we propose a method to decompose the differential in the (limited dependent) outcome variable between two groups into the contributions of the explanatory variables. We provide a...