Hi - Thanks for visiting!
I am a Lecturer (Assistant Professor) in Economics at the University of Edinburgh. I am affiliated with the Düsseldorf Institute for Competition Economics, where I obtained my PhD in Economics in 2025.
My research interests lie in the field of behavioral economics, industrial organization and microeconomic theory. I am particularly interested in issues that arise around digital and platform markets.
You can find my CV here.
Working Papers
Abstract: Digital platforms act as intermediaries that control how agents are matched using detailed user data. In many matching markets, however, user and platform incentives are misaligned: users prefer fast, high-quality matches, while platforms profit from prolonged search. This paper characterizes the matching rule of a profit-maximizing platform under misaligned incentives. I show that two commonly studied matching rules, random matching and positive assortative matching (PAM), can be suboptimal. When surplus extraction through prices is constrained, due to advertising-based business models or pricing frictions, the platform strategically delays matches, generating excessive search and inefficient mismatch relative to the social optimum.
Abstract: Users have an incentive to join large platforms, and hence platforms want to convince users that they have a large user base. I consider a monopolist platform's incentive and ability to signal its user base when there is uncertainty regarding the amount of potential users. The platform can signal using either fake accounts or prices. When --- as in some real-world examples --- users are naive regarding the platform's ability to use fake accounts, small platforms use them to profit from the artificial increase in demand. If users are sophisticated, larger platforms use fake profiles to differentiate themselves from smaller ones, and --- in contrast to the case of naive consumers --- platforms would benefit from a ban on such business practices.
Abstract: We study how market competition interacts with the design of buyers' information about product quality when sellers privately choose quality. We characterize seller-optimal information under monopoly and in symmetric equilibria of Bertrand competition. Under competition, optimal disclosure is partially informative and sustains randomization over quality. It differentiates the buyer's beliefs about competing products, softening price competition. Under monopoly, full disclosure is seller-optimal: it sustains efficient quality provision and allows the seller to extract the resulting surplus. We therefore highlight that, when disclosure is designed in sellers' interests, competition can lower quality and total surplus.
Downstream Foundations of Upstream Collusion (with Matthias Hunold, Johannes Muthers, and Alexander Rasch)
Abstract: Retailers’ expectations can determine whether a cartel among their suppliers takes hold. We study manufacturer collusion under secret two-part tariffs with competing retailers. Retailer beliefs can create a barrier to collusion distinct from manufacturers’ incentive constraints: beliefs that sustain an established cartel may prevent its formation. Belief adjustment in response to observed conduct can overcome this barrier, but faster adjustment also makes coordinated deviations more attractive. Under suitable conditions, the cost of rebuilding retailer confidence after deviations can sustain collusion without an explicit punishment phase. Our results distinguish cartel formation from cartel persistence.
Abstract: This paper examines the use of fake profiles by two-sided platforms to stimulate demand and increase profits. By deceiving naïve users, platforms invest into an artificial increase of the network size on one side of the market. Whereas firms are caught in a prisoner’s dilemma if users single-home on both sides of the market, users are protected by platform competition. If users on one side of the market multi-home, firms can increase their prices for the multi-homing side, and they lower their prices for the single-homing side. Investments into fake profiles stimulate demand, such that multi-homing demand and profits increase. Platforms and users as a group can profit from investments under these circumstances.
