Model-Based Evaluation of Cooling-Off Policies
joint with Christian Michel
Games and Economic Behavior, vol. 129, 2021, 270-293
Supplementary Material: [Web Appendix] [Mathematica]
Security Design with Interim Public Information
Journal of Mathematical Economics, vol. 76, 2018, 113-130
Pricing for the Stars - Dynamic Pricing in the Presence of Rating Systems (Extended Abstract)
joint with Christoph Carnehl & Peter Schmidt
EC'20: Proceedings of the 21st Conference on Economics and Computation, July 2020, 273-274
Working PapersMaintaining good ratings increases the profits of sellers on online platforms. We analyze the role of strategic pricing for ratings management in a setting where a monopolist sells a good of unknown quality. Higher prices reduce the value for money, which on average worsens reviews. However, higher prices also induce only those consumers with a strong taste for the product to purchase, which on average improves reviews. Our model flexibly parametrizes the two effects. This parametrization can rationalize the empirical heterogeneity in the relationship between reviews and prices and highlights the dependence of outcomes on the dominant effect. We analytically characterize a seller's optimal dynamic pricing strategy, long-run profits and consumer surplus, and consumers' speed of learning. We show that dynamic pricing benefits the seller, but may harm consumers when higher prices lead to better reviews. Recent changes to rating systems, which have increased the sensitivity of rating systems, may have harmed consumers by increasing prices and by reducing the speed of learning.
[Exemplary Applied Modeling Track Paper at EC'20] [Extended Abstract published in Conference Proceedings EC'20]
We investigate the impact of prices on seller ratings. In a stylized model, we illustrate two opposing channels through which pricing affects overall ratings and rating subcategories. First, higher prices reduce the perceived value for money which worsens ratings. Second, higher prices increase the taste-based valuation of the average traveler which improves ratings. Using data from Airbnb, we document a negative relationship between prices and ratings for most rating subcategories indicating that the value-for-money effect dominates the selection effect. In line with our model, we find that hosts of low-rating listings exert more effort than those of high-rating listings. Finally, an empirical assessment of the dynamics in the market suggests that taking the effect of prices on future ratings into account pays off: entrants who set low entry prices obtain better ratings and higher revenues in the medium run. A median entry discount of 8.5 percentage points increases medium-run monthly revenues by approximately 50 euros.
A seller serving two generations of short lived heterogeneous consumers sells a product under uncertain demand. We characterize the seller's optimal pricing, taking into account that the current period's price affects the information transmission to the next period consumers via consumer ratings. While the seller always prefers to generate more information, it is not necessarily in the consumers' interest. We characterize situations in which consumer surplus and welfare are decreasing in additional information. We provide conditions under which aggregate consumer surplus and welfare are lower with than without a rating system.
The (limited) Power of Blockchain Networks for Information Provision [PDF]
joint with Benedikt Franke and Qi Gao, R&R Management Science
Loan Sales and Screening with Two-Dimensional Borrower Types [PDF]We consider a model of lending with subsequent loan sale opportunities. Market participants observe a public signal about the creditworthiness of each borrower. Lenders additionally have the opportunity to privately screen potential borrowers at a cost. The model rationalizes empirically documented discontinuities in lending and default rates around a FICO credit rating score of 620, while providing a foundation for the endogenous emergence of a cutoff rule-of-thumb. We show that loan sale opportunities have a positive impact on borrowers' access to credit contingent on screening revealing positive information whenever the public information about a borrower's type is relatively bad. At the same time, average borrower quality for intermediate borrower types decreases as gains from trade via loan sales increase the relative profitability of loans to unscreened borrowers compared to loans to screened borrowers which imply significant risk retention. Loan sale opportunities can lead to adverse effects on borrower welfare while strictly increasing lender profitability.This note formalizes a framework to analyze whether for given data a theoretical economic model can lead to unambiguous predictions regarding economic outcomes of interest. Instead of structurally estimating demand and supply, we focus on whether the set of model parameters consistent with observed data uniquely determines the considered outcome. The framework can be applied to a large variety of economic models, and is of particular relevance for policy introductions when consumers potentially exhibit non-standard preferences. We discuss several applications to competition and consumer policy.
Work in Progress
Contracting with Type-Dependent Naivete
joint with Matteo Foschi