I am a post-doc at Universität Wien and junior research associate at ZEW Mannheim. I earned my PhD in Economics at Universität Mannheim in the Spring of 2024. My main research interests lie in Industrial Organization, specifically digital economics, platform and information design, consumer search, and innovation. I sometimes dabble with privacy as well.
I promise that I am more fun than this description would suggest.
Old affiliations:
Universität Mannheim
CRC TR 224 - EPoS
MaCCI
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Abstract: The consumer search literature mostly considers independently distributed products. In contrast, I study a model of directed search with infinitely many products whose valuations are correlated through shared attributes. I propose a tractable, systematic, history-dependent scoring system based on nests of correlated products that leverages the predictability of the optimal search process along different paths. This scoring system generates an optimal search policy conceptually equivalent to the familiar optimal search policy with independently distributed search products. The policy instructs the consumer to inspect unrelated products until an attribute the realization of which surpasses the added informational value of inspecting two new attributes is found. The search paths emerging from this policy match recent evidence of consumer learning through search, and can rationalize backtracking to a previously abandoned attribute.
Abstract: I analyze a model of directed search in which a consumer inspects products that share attributes with each others. The consumer discovers her valuation for the attributes of the inspected products and adapts her search strategy based on what she has learned. The consumer anticipates the optimal paths that arise after different realizations; this generates a search rule that accounts for learning systematically. In this search environment, a multiproduct seller commits to a menu of horizontally differentiated products. The seller can exploit the fact that the emerging search paths reveal the consumer's preferences: by setting different prices for \textit{ex ante} identical products, the seller can encourage specific paths to arise and exploit the information that the consumer learned through search. In some cases, the seller optimally limits the set of available products.
Abstract: We analyze consumers’ voluntary information disclosure in a platform setting. For given consumer participation, the platform and sellers tend to prefer limited disclosure of consumer valuations, in contrast to consumers. With endogenous consumer participation, seller and platform incentives may be misaligned, and sellers may be better off when consumers can disclose their valuations. A regulator acting in the best interest of consumers and/or sellers may want to intervene and force the platform to employ a disclosure technology that enables consumers to voluntarily disclose information from a richer message space.
Abstract: In this study, we analyze the incentives of a streaming platform to bias consumption when products are vertically differentiated. The platform offers mixed bundles of content to monetize consumer interest in variety and pays royalties to sellers based on the effective consumption of the generated content. When products are not vertically differentiated, the platform has no incentive to bias consumption in equilibrium. With vertical differentiation, royalties can differ, and the platform biases recommendations in favor of the cheapest content, hurting consumers and high-quality sellers. Biased recommendations, if unconstrained, eliminate sellers' incentives to increase the quality of their content, but if constrained, may lead to the inefficient allocation of R&D efforts.
Abstract: The EU General Data Protection Regulation (GDPR) of 2018 introduced stringent transparency rules compelling firms to disclose, in accessible language, details of their data collection, processing, and use. The specifics of the disclosure requirement are objective, and its compliance is easily verifiable; readability, however, is subjective and difficult to enforce. We use a simple inspection model to show how this asymmetric enforceability of regulatory rules and the corresponding firm compliance are linked. We then examine this link empirically using a large sample of privacy policies from German firms. We use text-as-data techniques to construct measures of disclosure and readability and show that firms increased the disclosure volume, but the readability of their privacy policies did not improve. Larger firms in concentrated industries demonstrated a stronger response in readability compliance, potentially due to heightened regulatory scrutiny. Moreover, data protection authorities with larger budgets induce better readability compliance without effects on disclosure.
Part of: Data Privacy Protection and the Conduct of Applied Research: Methods, Approaches and their Consequences, edited by Ruobin Gong, V. Joseph Hotz, and Ian M. Schmutte - University of Chicago Press, forthcoming