I am a postdoctoral researcher at the Institute for Microeconomics of the University of Bonn.
My research interest is Microeconomic Theory with a focus on Mechanism Design, Game Theory and Auction Theory.
I investigate the decision problem of a player in a game of incomplete information who faces uncertainty about the other players' strategies. I propose a new decision criterion which works in two steps. First, I assume common knowledge of rationality and eliminate all strategies which are not rationalizable. Second, I apply the maximin expected utility criterion. Using this decision criterion, one can derive predictions about outcomes and recommendations for players facing strategic uncertainty. A bidder following this decision criterion in a first-price auction expects all other bidders to bid their highest rationalizable bid given their valuation. As a consequence, the bidder never expects to win against an equal or higher type and resorts to win against lower types with certainty. Extended Abstract
Imitation perfection - a simple rule to prevent discrimination in procurement, R&R American Economic Journal: Microeconomics (first author, joint with Nicolas Fugger, Vitali Gretschko and Achim Wambach)
Procurement regulation aimed at curbing discrimination requires equal treatment of sellers. However, Deb and Pai (2017) show that such regulation imposes virtually no restrictions on the ability to discriminate. We propose a simple rule – imitation perfection – that restricts discrimination significantly. It ensures that in every equilibrium bidders with the same value distribution and the same valuation earn the same expected surplus. If all bidders are homogeneous, revenue and social surplus optimal auctions which are consistent with imitation perfection exist. For heterogeneous bidders however, it is incompatible with revenue and social surplus optimization. Thus, a trade-off between non-discrimination and optimality exists.
Endogenous worst-case beliefs in first-price auctions (joint with Vitali Gretschko)
Bidding in first-price auctions crucially depends on the beliefs of the bidders. We analyze bidding behavior in a first-price auction in which the knowledge of the bidders about the distribution of the values of their competitors is restricted to the range and the mean. To model this situation, we assume that under such uncertainty a bidder will expect to face the distribution of values that minimizes her expected payoff, given her bid is an optimal reaction to the bids of her competitors induced by this distribution. This introduces a novel way to endogenize beliefs in games of incomplete information. We find that for a bidder with a given valuation her worst-case belief just puts sufficient probability on lower valuations of her competitors to induce a high bid. The rest of the probability is distributed between a higher valuation and zero in a way that keeps the mean constant and minimizes the winning probability of the bidder. This implies that even though the worst case beliefs are type dependent in a non-monotonic way, an efficient equilibrium of the first-price auction exists.