Traditional choice models assume that observable behavior results from an unspecified evaluation process of the observed individual. When it comes to the revelation of this process mere choice models rapidly meet their boundaries, as psychological factors (e.g., consumers’ perception or...

Der vorliegende Beitrag beschäftigt sich mit der Dimensionsstruktur sowie der Verwertbarkeit des Fortune-Reputationsrankings in der wissenschaftlichen Forschung und liefert Erkenntnisse über seine Aussagefähigkeit. Nach Erörterung der theoretischen Grundlagen von Unternehmensreputation als...

Recently, Diebold and Li (2003) obtained good forecasting results for yield curves in a reparametrized Nelson-Siegel framework. We analyze similar modeling approaches for price curves of variance swaps that serve nowadays as hedging instruments for options on realized variance. We consider the...

We develop a sequential trade model of Iceberg order execution in a limit order book. The Iceberg-trader has the freedom to expose his trading intentions or (partially) shield the true order size against other market participants. Order exposure can cause drastic market reactions (“market...

A central issue in climate policy is the question whether long-term targets for green- house gas emissions should be adopted. This paper analyzes strategic effects related to the timing of such commitments. Using a two-country model, we identify a redistributive effect that undermines long-term...

The quality of newly constructed single-family houses is usually homogeneous in and heterogeneous between neighborhoods. Such quality-clustering will be caused by the variation of natural amenities throughout a suburban area. Clustering will be enforced if the quality of neighboring buildings...

The widening of the working hour distribution complicates the coordination of social leisure. This paper examines the short- and long-run impact of unusual working schedules on social life using German Time Use Data for 2001/02. I find evidence that younger workers with higher than median...

Principal component analysis (PCA) is a widely used dimension reduction tool in the analysis of many kind of high-dimensional data. It is used in signal process- ing, mechanical ingeneering, psychometrics, and other fields under different names. It still bears the same mathematical idea: the...

I construct risk-corrected approximations of the policy functions of DSGEmodels around the stochastic steady state and ergodic mean that are linear in the state variables. The resulting approximations are uniformly more accurate than standard linear approximations and capture the dynamics of...

In this paper we develop several regression algorithms for solving general stochastic optimal control problems via Monte Carlo. This type of algorithms is particularly useful for problems with a highdimensional state space and complex dependence structure of the underlying Markov process with...