Publications
Külpmann, Philipp, and Christoph Kuzmics. "Comparing theories of one-shot play out of treatment." Journal of Economic Theory 205 (2022): 105554.
We collected data on one-shot play for a representative selection of two-player two- and three-strategy games with unique and completely mixed strategy predictions and propose a new method to compare theories of one-shot play “out of treatment” that allows a direct likelihood comparison: Competing theories are calibrated with pre-existing data using different games and subjects. Most theories in most treatments have predictive power. No theory is uniformly best. Considering risk aversion significantly improves predictive power. Nash equilibrium with risk aversion is among the best predictors of play in four of six treatment groups: the exceptions are the behavior of individuals in the asymmetric own-payoff player positions in games of a matching pennies and rock-scissors-paper variety.
Tiwisina, Johannes, and Philipp Külpmann. "Probabilistic transitivity in sports." Computers & Operations Research 112 (2019): 104765.
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.
Working Papers
Identifying the Reasons for Coordination Failure in a Laboratory Experiment (with Davit Khantadze)
We investigate the effect of absence of common knowledge on the outcomes of coordination games in a laboratory experiment.
Using cognitive types, we can explain coordination failure in pure coordination games while differentiating between coordination failure due to first- and higher-order beliefs.
In our experiment, around 76% of the subjects have chosen the payoff-dominant equilibrium strategy despite the absence of common knowledge.
However, 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 commonly used models of higher-order beliefs.
Rational Delay of Effort in Projects with Uncertain Requirements
We 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 a breakthrough is unknown but players have a common prior about its distribution. This makes the model very flexible, since the distribution over the required effort for a breakthrough can model different types of projects.
We characterize the equilibrium and the welfare-maximizing effort path for general distributions of this breakthrough effort and show that three effects are at work: free-riding (i.e., working less), an encouragement effect (i.e., working more), similar to Bolton and Harris (1999), and a delay of effort (i.e., working later).
This encouragement effect increases or decreases the amount of work players put into the project depending on the type of uncertainty faced. Furthermore, the delay of effort explains the frequently observed last-minute rush before a deadline as a result of the actions of not only rational but also welfare-maximizing players.
Work in Progress
Purifying Randomness? Testing Harsanyi's Idea in the Lab
with Wieland Müller and Alexander K. Wagner
Trade Network Formation in Cournot Markets
with Yu Chen