The computation of robust regression estimates often relies on minimization of a convex functional on a convex set. In this paper we discuss a general technique for a large class of convex functionals to compute the minimizers iteratively which is closely related to majorization-minimization...

The paper analyzes the risk disclosure quality in the prospectus of IPOs in Germany between 2006 and 2008. Quality of risk information is measured as precision and comprehensibility. The relationship between risk disclosure quality and earnings power is tested.

The change of regimes in former Soviet Bloc provides an opportunity to study the neoclassical growth theory in a region of the world that was excluded before because of the presence of centrally planned economies. A concern is whether these newly formed economies are converging to a unique...

The change of regimes in former Soviet Bloc provides an opportunity to study the neoclassical growth theory in a region of the world that was excluded before because of the presence of centrally planned economies. A concern is whether these newly formed economies are converging to a unique...

The German meat market is facing considerable changes. Along with the boom of case-ready and discount stores, butchers and smaller retailers loose market shares, and private labels become widely accepted. The consumers' preferences are often neglected by these trends. This contribution discusses...

"This paper discusses methodological problems of standard errors and treatment effects. First, heteroskedasticity- and cluster-robust estimates are considered as well as problems with Bernoulli distributed regressors, outliers and partially identified parameters. Second, procedures to determine...

We consider the problem of estimating the first k coeffcients in a regression equation with k + 1 variables.For this problem with known variance of innovations, the neutral Laplace weighted-average least-squares estimator was introduced in Magnus (2002).We investigate properties of this...

High breakdown-point regression estimators protect against large errors both in explanatory and dependent variables.The least trimmed squares (LTS) estimator is one of frequently used, easily understandable, and thoroughly studied (from the robustness point of view) high breakdown-point...