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...

Quantile regression provides sports economists with a powerful research tool. Unlike least squares, it is not tied to restrictive assumptions about the distribution of the error term, which makes it particularly valuable in settings with highly skewed distributions, like sports labor markets. It...

Many social scientists believe that dumping long lists of explanatory variables into linear regression, probit, logit, and other statistical equations will successfully “control†for the effects of auxiliary factors. Encouraged by convenient software and ever more powerful computing,...

The recent financial crisis has raised numerous questions about the accuracy of value-at-risk (VaR) as a tool to quantify extreme losses. In this paper we develop data-driven VaR approaches that are based on the principle of optimal combination and that provide robust and precise VaR forecasts...

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...

In this paper, we consider the existence of a sequence of convex sets that has an approximation property for the equilibrium sets in the bounded rational environments. We show that the bounded rational equilibrium multivalued map is approximated with arbitrary precision in the abstract...