Sophie Kreutzkamp
Welcome!
I am a postdoctoral research fellow in Economics at the University of Oxford. I received my PhD from the University of Bonn.
My primary research interests are in Microeconomic theory and its applications, particularly information design, search and matching theory, and mechanism design.
Secondarily, I am interested in statistics.
My CV
Email: sophie.kreutzkamp@economics.ox.ac.uk
Research
This paper studies costly information acquisition and transmission. An expert can communicate with a decision-maker about a state of nature by sending a cheap-talk message. I establish a version of the recommendation principle, meaning that the sender generally reveals all acquired information to the decision-maker in efficient equilibria. Furthermore, I show existence of efficient equilibria under general conditions. For the class of posterior separable cost structures, I derive properties of efficient experiments. Under posterior-mean preferences, any cheap-talk problem is solved by a convex combination of two bi-pooling policies. Beyond that, I characterize the best bi-pooling policies for the uniform-quadratic case. Contrary to existing cheap-talk models, monotone partitions are not always optimal.
We study a search-and-matching model with heterogeneous agents that continue to search on-the-match. In deciding with whom to match, agents must trade-off the flow utility provided by a partner against the stability of a match, i.e., the rate at which the partner leaves for another agent. Thus, stability determines and is determined by the agents' behavior, and consequently, there are multiple steady state equilibria. In almost every equilibrium, agents coordinate on payoff-dominated behavior. However, if there is match-specific productivity growth, i.e., if flow utility increases in the duration of a match, agents no longer fail to coordinate. We characterize the set of steady state equilibria that survive a perturbation with match-specific productivity growth. In some equilibria, less productive agents prefer to match with other less productive agents, suggesting an alternative explanation for assortative matching. In general, productivity growth can significantly alter equilibrium outcomes and sorting patterns: any match now becomes stable in the long run, but there is an incentive to foster growth in matches that are stable to begin with; either effect can dominate the agents' trade-off.
This paper studies the k-means clustering problem with one additional constraint: The distance between any two cluster centroids is bounded below by some constant. Specifying the minimum distance between cluster means determines the optimal number of clusters. I characterize analytical properties of the solution to the constrained clustering problem. The classical k-means clustering algorithm extended by the minimum distance constraint typically converges to an outcome that is a local solution, but cannot be the global solution to the clustering problem. Moreover, I propose a hypothesis test on uniformity of the underlying distribution of the original data based on the clustered data.