Berlin IO Day

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Program

Program

Speakers & Papers

Luís Cabral (New York University):

Switching Costs with Asymmetric Information
(co-authored with Boyan Jovanovic)
Abstract: We study competition between an "incumbent" and a "challenger" seller when sellers can offer personalized prices and the incumbent holds private information about the consumer's switching cost s. We develop an infinite-period duopoly model and show that, if firms interact frequently enough, then consumers are better off when sellers are asymmetrically informed, compared to when neither incumbent nor challenger know the value of s. Starting from the asymmetric-information equilibrium, giving the challenger knowledge of s has no effect on consumer welfare. Under the asymmetric information, a reduction in s improves consumer welfare, but this gain vanishes as the discount factor tends to 1. Finally, we show that, if firms interact frequently enough, then a ban on personalized pricing reduces consumer welfare.

Marleen Marra (KU Leuven):

The Geography of Market Power: Firm Location, Spatial Rents, and Their Social Costs
(co-authored with Florian Oswald)
Link to the recent draft
Abstract: The location decisions of spatially competing firms are intertwined, trading off proximity to customers against the cost of intensified competition near rivals, while economies of density across multiple plants add a further complication. We study these economic forces with new data on garage ownership since the 1994 privatization of London’s bus market. Exploiting the time dimension together with the exclusive use of garages by single operators, we model locations as choosing firms, rather than the reverse, yielding a tractable estimator despite rich spatial spillovers. Simulations show the highlighted trade-off is economically meaningful: each nearby competitor cuts the private return to capacity expansion by at least 10%. An optimal reassignment of garages yields up to 24.3% in welfare gains, though building restrictions and garage exclusivity leave non-zero local monopoly rents. When also pricing the externalities of empty “dead-mile” travel between garage and route, concentration reduces less, as large operators are best placed to economize on dead miles across their network.

Z. Eddie Ning (The University of North Carolina at Chapel Hill):

Is Platform-Led Pricing Pro or Anti-Competitive?
(co-authored with Jinzhao Du and S. Neda Ahmadi Amiri)
Abstract: Digital platforms increasingly recommend or set prices for sellers, raising concerns that delegating pricing to a common intermediary may soften competition. We study the competitive implications of platform-led pricing using a game-theoretic model and complementary Q-learning simulations. In the model, competing sellers can delegate pricing to a platform that maximizes commission revenue, saving the cost of setting prices independently. Delegation introduces two opposing forces: the platform internalizes substitution across sellers, which softens competition, but does not bear sellers’ marginal costs, which creates an incentive to lower prices. Holding other factors fixed, platform-led pricing is pro-competitive (lowering prices relative to decentralized pricing) when competition from outside the platform is su!ciently strong, sellers on the platform are su!ciently di"erentiated, marginal costs are su!ciently high, or the market is su!ciently small. Crossing the corresponding thresholds in the opposite direction makes platform-led pricing anti-competitive. The equilibrium proportion of sellers who delegate pricing decisions is non-monotonic in these market parameters. When decentralized sellers sustain supracompetitive prices through repeated interaction, platform-led pricing is pro-competitive over a broader range of market conditions. When sellers di"er in baseline demand, platform-led pricing can lower the high-demand firm’s price while raising the low-demand firm’s price relative to decentralized pricing. These findings show that the competitive implications of platform-led pricing depend on market structure, sellers’ incentives to delegate, and the extent of coordination under decentralized pricing.

Dongsoo Shin (Santa Clara University):

Demand Management in Distribution Channels
(co-authored with Roland Strausz)
Abstract: Demand expansion need not benefit a manufacturer. We show that demand-enhancing activities that would raise profit under direct distribution can reduce profit when the manufacturer sells through an independent retailer. The mechanism operates through segment-specific incentive costs: demand expansion affects manufacturer profit not only by increasing sales at the intended retail price, but also by strengthening the retailer's incentive to target other demand segments. We identify these costs by casting a double-marginalization problem as an incentive-design problem. In discrete demand models, demand at the implemented mass-market price raises manufacturer profit, whereas demand at a binding niche-deviation price lowers it by increasing the rents needed to sustain mass-market coverage. The mechanism extends to general demand structures: proportional demand expansion benefits the manufacturer, whereas niche-specific expansion can destroy manufacturer value. The analysis implies that, under retail distribution, manufacturers optimally avoid intermediate niche appeal by either suppressing niche appeal or committing fully to the niche. As a result, retail distribution polarizes product positioning toward clearly mass-market or clearly niche designs, whereas direct distribution is most valuable for intermediate positioning.

Hannes Ullrich (DIW Berlin & University of Copenhagen):

Career Concerns and Managerial Risk Taking: Evidence from Professional Football
(co-authored with Paul Bose and Florian Schuett)
Abstract: Risky decisions in organizations may be distorted away from owners’ objectives if managers care about their reputation, i.e., public perceptions of their ability. Because reputation is hard to measure, documenting such distortions is di!cult in most contexts. We provide evidence that the decision making of head coaches in the National Football League is distorted by reputation concerns. Using sentiment analysis on text data from millions of coach-related posts on Twitter, we construct a high-frequency reputation measure and show that it is predictive of coach dismissals. We link this reputation measure to coaches’ decisions whether to attempt 4th down conversions, a routinely made in-game choice involving risk. We show that coaches’ decisions respond not only to expected win probabilities but also to expected reputation changes. The evidence is consistent with a model of career concerns in which coaches have private information about conversion probabilities, generating conservatism in decision making. Studying teams’ staggered adoption of data analytics, we find that having an analytics division exacerbates conservatism.

About Berlin IO Day

The Berlin IO Day is a one-day workshop supported by the Berlin's leading academic institutions, including DIW Berlin, ESMT Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, and Technische Universität Berlin which takes place twice a year, in the Spring and in the Fall.

For each Berlin IO Day, we will invite four or five speakers to present their recent work on a variety of IO topics, followed by a general discussion. The aim is to create an international forum for high quality research in Industrial Organization in the heart of Berlin, one of Europe's most vibrant and intellectually lively cities.

Organizers:

• Tomaso Duso, Jo Seldeslachts, Hannes Ullrich (DIW Berlin)
• Michał Grajek, David Ronayne (ESMT Berlin)
• Andreas Asseyer, Anja Prummer (Freie Universität Berlin)
• Daniel Guhl, Daniel Klapper, Roland Strausz (Humboldt-Universität zu Berlin)
• Radosveta Ivanova-Stenzel (Technische Universität Berlin)