Berno Buechel

The dynamics of closeness and betweenness

Although both betweenness and closeness centrality are claimed to be important for the effectiveness of someones network position, it has not been comprehensively studied which networks emerge if actors strive to optimize their centrality in the network in terms of betweenness and closeness. We study each of these centrality measures separately, but we also analyze what happens if actors value betweenness and closeness simultaneously. Network dynamics differ considerably in a scenario with either betweenness or closeness incentives compared with a scenario in which closeness and betweenness incentives are combined. There are not only more stable networks if actors’ betweenness and closeness are combined, but also these stable networks are less stylized.

Nobody’s Innocent The Role of Customers in the Doping Dilemma

Customers who boycott an organization after some scandal may actually exacerbate the fraud problem they would like to prevent. This conclusion is derived from a game-theoretic model that introduces a third player into the standard inspection game. Focusing on the example of doping in professional sports, we observe that doping is prevalent in equilibrium because customers undermine an organizer’s incentives to inspect the athletes. Establishing transparency about doping tests is necessary but not sufficient to overcome this dilemma. Our analysis has practical implications for the design of anti-doping policies as well as for other situations of fraudulent activities.

The Swing Voter's Curse in Social Networks

We study private communication in social networks prior to a majority vote on two alternative policies. Some (or all) agents receive a private imperfect signal about which policy is correct. They can, but need not, recommend a policy to their neighbors in the social network prior to the vote. We show that communication can undermine effciency of the vote and hence reduce welfare in a common interest setting. We test the model in a lab experiment and find strong support for the predicted effects.

Black Sheep or Scapegoats? Implementable Monitoring Policies Under Unobservable Levels of Misbehavior

An authority delegates a monitoring task to an agent. Thereby, it can observe the number of detected offenders but not the monitoring intensity chosen by the agent or the resulting level of misbehavior. We provide a necessary and sufficient condition for the implementability of monitoring policies. When several monitoring intensities lead to an observationally identical outcome, only the minimum of these is implementable, which can lead to underenforcement. A comparative-statics analysis reveals that increasing the punishment can undermine deterrence, since the maximal implementable monitoring intensity decreases. When the agent is strongly intrinsically motivated to curb crime, our results are mirrored, and only high monitoring intensities are implementable. Then, higher monetary rewards for detections lead to a lower monitoring intensity and to a higher level of misbehavior.

Condorcet winners on median spaces

We characterize the outcome of majority voting for single-peaked preferences on median spaces. This large class of preferences covers a variety of multi-dimensional policy spaces including products of lines (e.g. grids), trees, and hypercubes. Our main result is the following: If a Condorcet winner (i.e. a winner in pairwise majority voting) exists, then it coincides with the appropriately defined median (“the median voter”). This result generalizes previous findings which are either restricted to a one-dimensional policy space or to the assumption that any two voters with the same preference peak must have identical preferences. The result applies to models of spatial competition between two political candidates. A bridge to the graph-theoretic literature is built.