In this paper, we use a laboratory experiment to investigate the effect of absence of common knowledge on the outcomes of coordination games. We introduce cognitive types into a pure coordination game in which there is no common knowledge about the distribution of cognitive types. In our experiment, around 76% of the subjects managed to coordinate on the payoff-dominant equilibrium despite the absence of common knowledge. However, around 9% of the players had first-order beliefs that lead to coordination failure and another 9% exhibited coordination failure due to higher-order beliefs. Furthermore, we compare our results with predictions of different models of higher-order beliefs, commonly used in the literature.

Rational Delay of Effort in Projects with Uncertain Requirements (SSRN)
In this paper, I analyze a dynamic moral hazard problem in teams with imperfect monitoring in continuous time. In the model, players are working together to achieve a breakthrough in a project while facing a deadline. The effort needed to achieve such a breakthrough is unknown but players have a common prior about its distribution. Each player is only able to observe their own effort, not the effort of others.
I characterize the optimal effort path for general distributions of breakthrough efforts and show that, in addition to free-riding, a delay of effort and an encouragement effect arises.
In this model, the encouragement effect increase and decrease the work players put into the project, depending on the type of uncertainty faced. Furthermore, the delay of effort is also a result of rational and even welfare-maximizing behavior.

Probabilistic Transitivity in Sports (SSRN) with Johannes Tiwisina
We seek to find the statistical model that most accurately describes empirically observed results in sports. The idea of a transitive relation concerning the team strengths is implemented by imposing a set of constraints on the outcome probabilities. We theoretically investigate the resulting optimization problem and draw comparisons to similar problems from the existing literature including the linear ordering problem and the isotonic regression problem. Our optimization problem turns out to be very complicated to solve. We propose a branch and bound algorithm for an exact solution and for larger sets of teams a heuristic method for quickly finding a "good" solution. Finally we apply the described methods to panel data from soccer, American football and tennis and also use our framework to compare the performance of empirically applied ranking schemes.

Work in Progress:

An Experimental Investigation of Anti-Coordination Games with Christoph Kuzmics

Can we Trust the Experimenter?

Projects with Uncertain Objectives