I am an Assistant Professor at the Institute of Economics at the Corvinus University of Budapest. My research interests are in applied microeconomic theory, with a focus on behavioral and information economics. While most of my work is theoretical, I also use empirical methods, drawing on experiments and field data.
I received my PhD from the University of Vienna in 2023.
Here are links to my CV, my Google Scholar, and my Linkedin profile.
Research Interests:
Microeconomics
Industrial Organization
Information Economics
Behavioral Economics
Working Papers:
Online reviews affect consumer choices and are therefore frequently faked. Not all consumers are aware of this. In a model with fake reviews and naive consumers, the unique equilibrium is characterised by partial pooling, where fake reviews are persuasive and blend in with real ones. Raising consumer awareness has opposing effects on the naive and aware consumer groups. If real reviews are written strategically, they are not always truthful. Under favourable market conditions, the equilibrium with all strategic reviewers is outcome equivalent to one with all aware consumers. Thus, awareness campaigns can yield similar outcomes, regardless of their target audience.
Misinformation in consumer markets - like fake reviews or biased endorsements - poses a challenge for consumers that can be conceptualized as a two-step problem. First, they need to form a belief about the probability that the information is biased. Second, they need to update their beliefs conditional on receiving information. Understanding how these two channels contribute to suboptimal decisions has direct implications for consumer protection policies. This paper reports on an experiment that disentangles both channels utilizing a novel approach which relies neither on theoretical predictions nor on belief elicitation. We find that inability to correctly compute posterior probabilities drives suboptimal decisions and that this effect is heterogeneous across gender.
Work in Progress:
We study the effects of a rent control policy when enforcement relies on tenant complaints rather than government monitoring. We show theoretically that when tenants differ in their ability to enforce the rent cap, adverse selection arises: landlords set rents anticipating how enforcement risk depends on the composition of tenants. Higher listed rents deter tenants who are unlikely to enforce the cap, increasing enforcement risk and inducing further rent increases. The resulting equilibrium rents are higher than in the no regulation benchmark and depend negatively on the rent cap level. Using rental listings data from Vienna between 2012 and 2022, we test the model's predictions by exploiting policy changes and institutional variation in rent caps. We find that tighter rent control leads to 76 EUR higher posted rents on average, consistent with our theoretical predictions.
We consider a monopoly model in which the current demand depends positively on the excess demand in the previous period, and solve the monopolist’s dynamic optimization problem. When the demand-boosting effect and/or the discount factor are small enough, the monopolist clears the market every period. When both are sufficiently high, the optimal policy is cyclical, consisting of periods with low prices and low supply, during which demand is built up, followed by a period with high price and high supply, during which the monopolist ‘cashes in’ on the hype he has created. The length of the optimal cycle is unique and depends positively on the demand-boosting effect and discount factor. We also study welfare effects in the case where the demand-boosting effect is part of consumer surplus, and in the case where it is not. A stronger demand-boosting effect can increase total welfare in both cases.
A sender has private information about a monopolist's marginal cost. Under which conditions is informative communication possible? How much information is optimal with respect to social welfare?
