Home CV Research Teaching

Florian Dendorfer

Email florian dot dendorfer at utoronto dot ca
LinkedInLinkedIn
GitHubGithub
OrcIdOrcId

Welcome to my web page! I am an assistant professor of economics (teaching stream) at the University of Toronto.

My research focuses on industrial organization. In particular, I am interested in the digital economy and platform markets.

Publications

First-Party Selling and Self-Preferencing, International Journal of Industrial Organization, 97, 2024, 103098.

Abstract In this paper, I analyze the welfare effect of a vertically integrated gatekeeper platform selling its own first-party product, i.e., first-party selling, as well as the platform's incentive to favor the first-party product in the product recommendations it makes, i.e., self-preferencing. I find that, irrespective of self-preferencing, both consumer welfare and platform revenue are higher under first-party selling because first-party selling mitigates double marginalization. Additionally, third-party product prices are lower in expected terms under first-party selling, either because the platform reduces the commission fee (with self-preferencing) or downstream competition is fiercer (without self-preferencing). Finally, I show that both consumers and the platform are better off if the platform commits not to engage in self-preferencing.

Working Papers

The Cost Of The Cold-Start Problem On Airbnb (with Regina Seibel) [Replication code]

Abstract In digital markets with peer-to-peer reviews, new products encounter the so-called "cold-start" problem: Little-known products are bought too rarely and remain little known. While consumers benefit from observing reviews written by others, they do not account for the benefit they generate from trying a new product and revealing the product's quality to everyone else. In this paper, we examine the inefficiency linked to social learning on Airbnb, including its implications for hosts' price, entry and exit decisions. We estimate a dynamic structural model of demand and supply for Airbnbs in Manhattan, New York, from 2016 to 2019. We then introduce a counterfactual tax-subsidy scheme aimed at changing the relative price of listings with few compared to many reviews, thereby shifting demand and addressing the cold-start problem. In our main counterfactual, we find that the average price decreases by around 17% for listings with at most one review, but increases by almost 10% for listings with more than 15 reviews, which leads to 14% higher demand for the former. Furthermore, the number of listings with at most one review declines by 18%, although the total number of listings increases by 5%. Based on our conservative estimates, widening the price gap between new and established listings leads to a welfare increase amounting to roughly 8.5% of total host revenue on Airbnb in Manhattan.

Fall 24

ECO380H1F Markets, Competition, and Strategy (syllabus)

L5101 Thursdays 5:00 PM - 7:00 PM (lecture) and 7:00 PM - 8:00 PM (tutorial), room MS2172

Demand estimation code

Fall/Winter 24/25

ECO204Y1Y Microeconomic Theory and Applications (for Commerce) (syllabus)

L0301 Wednesdays 11:00 AM to 1:00 PM (lecture) and Thursdays 1:00 PM to 2:00 PM (tutorial), room SS2118

L0401 Wednesdays 3:00 PM to 5:00 PM (lecture) and Thursdays 1:00 PM to 2:00 PM (tutorial), room SS2117

Winter 24

ECO380H1S Markets, Competition, and Strategy (syllabus)

L5101 Thursdays 5:00 PM - 7:00 PM (lecture) and 7:00 PM - 8:00 PM (tutorial), room MC252

Fall/Winter 23/24

ECO204Y1Y Microeconomic Theory and Applications (for Commerce) (syllabus)

L0301 Wednesdays 11:00 AM to 1:00 PM (lecture) and Thursdays 1:00 PM to 3:00 PM (tutorial), room SS2118

L0401 Wednesdays 3:00 PM to 5:00 PM (lecture) and Thursdays 1:00 PM to 3:00 PM (tutorial), room SS2117