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AddressUniversity of MannheimDepartment of EconomicsL7, 3-5, Room 3.0468131 Mannheim, Germany
E-Mailandre.stenzel[at]uni-mannheim[dot]de
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Publications

Model-Based Evaluation of Cooling-Off Policies
joint with Christian Michel
Games and Economic Behavior, vol. 129, 2021, 270-293
DOI: https://doi.org/10.1016/j.geb.2021.05.012
Supplementary Material:
[Web Appendix] [Mathematica]

Security Design with Interim Public Information
Journal of Mathematical Economics, vol. 76, 2018, 113-130
DOI:
https://doi.org/10.1016/j.jmateco.2018.02.005


Conference Proceedings

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
DOI:
https://doi.org/10.1145/3391403.3399522



Working Papers

Pricing for the Stars [PDF] [Mathematica]
joint with Christoph Carnehl & Peter Schmidt, R&R Management Science

Maintaining 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. We provide conditions under which the latter effect dominates so that ratings management leads to an upward pressure on prices. This upward pressure increases in the sensitivity of the aggregate rating to incoming reviews. As a consequence, recent changes to rating systems may have harmed consumers by increasing long-run price levels.
[Exemplary Applied Modeling Track Paper at EC'20] [Extended Abstract published in Conference Proceedings EC'20]

Value for Money and Selection: How Pricing Affects Airbnb Ratings [PDF]
joint with Christoph Carnehl, Maximilian Schäfer and Kevin Tran

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.

Strategic Pricing and Ratings [PDF]
joint with Christoph Carnehl, Anton Sobolev and Konrad Stahl

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.

Can you trust the Blockchain? The (limited) power of peer-to-peer networks for Information Provision [PDF]
joint with Benedikt Franke and Qi Gao, resubmitted to Management Science

We investigate the potentials and limits of privacy-preserving blockchain technology for information provision. In our model, heterogeneous firms can adopt a privacy-preserving blockchain or rely on traditional institutions. The blockchain leverages its peer-to-peer architecture to disseminate an aggregate signal about each firm's valuation. The firm-specific information provision depends on two factors: (i) the blockchain's fit for analyzing a given firm's data, and (ii) its reach into the economy. The technology can improve information provision in two ways. The adoption decision itself may serve as a credible signal of a firm's valuation, and the blockchain may generate more information than traditional institutions when its reach is sufficiently high. However, we characterize an equilibrium in which high-value and low-value firms are present both inside and outside the blockchain, which limits both channels' ability to generate information. The overall information provision can even fall below the benchmark case in which blockchain technology is not available.

Opacity, Liquidity and Disclosure Requirements [PDF]
joint with Wolf B. Wagner, resubmitted to Journal of Business Finance & Accounting

We present a model that links the opacity of an asset to its liquidity. We show that while low opacity assets are liquid, intermediate levels of opacity provide incentives for investors to acquire private information, causing adverse selection and illiquidity. High opacity, however, benefits liquidity by reducing the value of a unit of private information. The cross-section of bid-ask spreads of U.S. firms is shown to be broadly consistent with this hump-shape relationship between opacity and illiquidity. Our analysis suggests that uniform disclosure standards may be suboptimal; efficient disclosure can instead be achieved through a two-tier standard system or by subsidizing voluntary disclosure.

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.


A simple framework to analyze data requirements for policy evaluation [PDF]
joint with Christian Michel

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