Welcome! I am an Assistant Professor in the Department of Economics at Bocconi University. Before joining Bocconi, I completed my PhD at the University of Mannheim. Please find my CV here.
My research interests lie primarily in the field of Applied Microeconomic Theory. In particular, I am interested in dynamic incentive problems and the effects of learning in dynamic environments.
I am also interested in Empirical Industrial Organization; so far, I have been working on the estimation of auction models and the analysis of merger policy.
Abstract: I study a continuous-time moral hazard problem with learning about a two-stage project of unknown quality. The first-stage arrival time is informative but not conclusive about the project’s quality. Due to the informativeness, the optimal contract features a combination of continuation value and intermediate bonus payments as a reward. There is a negative correlation between the first success time and the share of bonus payments in the reward. Second-stage deadlines adjust to the first-stage success time: early successes are rewarded with longer deadlines in the second stage. When agent replacement between stages is possible, the principal will replace the agent if the first success arrives late.
(with Stefan Weiergraeber)Abstract: We develop a structural empirical model of procurement auctions with private and common value components and bidder asymmetries in both dimensions. While each asymmetry can explain the dominance of a firm, they have opposite welfare implications. We propose a novel empirical strategy to quantify the two asymmetries using detailed contract-level data on the German market for railway passenger services. Our results indicate that the incumbent is slightly more cost-efficient and has substantially more information about future ticket revenues than its competitors. If bidders’ common value asymmetry was eliminated, the median probability of selecting the efficient firm would increase by 61%-points.
(with Johannes Schneider)Abstract: We study optimal problem solving under deadlines. An agent dynamically allocates effort between a trial-and-error approach and a structural approach. The trial-and-error approach requires only a single step but may be infeasible. The structural approach is always feasible but requires more steps. The unique optimal policy can have the switching-forth-and-back property: the agent switches back to trial and error after she left it for the structural approach. We identify three drivers of that optimal policy: (i) costly effort, (ii) finite deadlines, and (iii) observability of intermediate progress. Our model applies to questions in organizational economics, innovation, and education.
(with Andre Stenzel and Peter Schmidt)Abstract: We consider dynamic price-setting in the presence of rating systems and asymmetric information about product quality. A long-lived monopolist sells a product of privately known and fixed quality to a sequence of short-lived consumers. In each period, the price charged determines the taste characteristics of purchasing consumers who leave reviews after purchase. Individual reviews are aggregated into ratings observable to future consumers. The price has two effects on future ratings: (i) a direct price effect on reviews, and (ii) an indirect selection effect by determining the tastes of reviewing consumers. Inference is conducted by looking for the inferred quality and cutoff taste such that purchase decisions are individually rational and the current aggregate rating is matched. We show that rating systems are effective as consumers correctly infer the quality of the product in the long run. However, the design of the rating system affects long-run prices, profits and consumer surplus. If the direct price effect dominates the selection effect, consumers benefit from a rating system which is more sensitive to newly arriving reviews. In contrast, they prefer a more persistent system if the selection effect dominates. Firms are unambiguously better off the more sensitive the rating system.
Supplementary Mathematica file: Mathematica_PftS
(with Matthias Hunold)Abstract: We study competitive awarding procedures of short haul railway passenger services in Germany from 1995 to 2011 by means of a newly collected data set. In particular, we use regression techniques to investigate the determinants of the number of bidders, the identity of the winning bidder and the subsidy level. We find that there are more bidders when the contract duration is high and the revenue risk low. The dominant operator is more likely to win contracts if it is the incumbent, the network is large, the contract duration is high, when used rolling stock is admitted and when there are few other bidders.
Department of Economics
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