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Market Power Possibilities on Digital Platforms

Paper Session

Monday, Jan. 5, 2026 1:00 PM - 3:00 PM (EST)

Philadelphia Marriott Downtown, Room 310
Hosted By: Econometric Society
  • Chair: Alexander MacKay, University of Virginia

Sources of Market Power in Web Search: Evidence from a Field Experiment

Hunt Allcott
,
Stanford University
Juan Camilo Castillo
,
University of Pennsylvania
Matthew Gentzkow
,
Stanford University
Leon Musolff
,
University of Pennsylvania
Tobias Salz
,
Massachusetts Institute of Technology

Abstract

We evaluate the economic forces that contribute to Google’s large market share in web search. We develop a model of search engine demand in which consumer choices are influenced by switching costs, quality beliefs, and inattention, and estimate it using a field experiment with US desktop internet users. We find that (i) requiring Google users to make an active choice among search engines increases Bing’s market share by only 1.1 percentage points, implying that switching costs play a limited role; (ii) Google users who accept our payment to try Bing for two weeks update positively about its relative quality, with 33 percent preferring to continue using it; and (iii) after changing the default from Google to Bing, many users do not switch back, consistent with persistent inattention. In our model, correcting beliefs and removing choice frictions would increase Bing’s market share by 15 percentage points and increase consumer surplus by $6 per consumer-year. Policies that expose users to alternative search engines lower Google’s market share more than those requiring active choice. We then use Microsoft search logs to assess the impact of additional data on search result relevance. The results suggest that sharing Google’s click-and-query data with Microsoft may have a limited effect on market shares.

Algorithmic Steering and Advertising on Platforms

Justin P. Johnson
,
Cornell University
Andrew Rhodes
,
Toulouse School of Economics
Matthijs R. Wildenbeest
,
University of Arizona

Abstract

We analyze steering/self-preferencing by a retail platform, using both economic theory and simulations of AI algorithms. When the platform does not sell advertising slots to merchants (which guarantee the merchant will be displayed to consumers), the platform has incentives to exclude merchants when its commission rate is in a lower range, but not when its commission rate is higher. Facing the threat of not being displayed, the merchant’s optimal response is to raise its price on the platform, so as to reduce the substitution threat it poses to the platform’s own product. Thus, even when the equilibrium outcome is for the merchant to be displayed, the self-preferencing possibility raises overall prices and harms competition. We then introduce an advertising option, and show that this can lead to lower prices while still ensuring the merchant is displayed to consumers. However, the merchant need not gain from the introduction of advertising. Various extensions are considered.

The Effects of Return Policies in E-commerce

Peter Newberry
,
University of Georgia
Xiaolu Zhou
,
Xiamen University

Abstract

We quantify the welfare effects of return policies in a large online retail platform. Utilizing variation in return policies across sellers of tablets on Alibaba's Tmall, we estimate a model of demand and supply where the consumer has the option to return the product after purchasing it. We find that a more lenient return policy impacts demand through a reduction of the risk to the consumer, but does not serve to provide a strong signal of seller quality. On the supply side, estimates suggest that returns are costly for sellers, as they are approximately equal to the cost of proving a brand new tablet to the buyer. We use the model to estimate the effect of platform-level return policies, with a focus on the impact of the leniency of the uniform rule. As policies become more lenient, consumer surplus decreases and firm profit increases. The reduction in consumer surplus comes from the price response of firms, as they pass through increases in return cost to consumers. This suggests that the leniency of a platform-level return policy can work to undermine the goal of improving the customer experience.

Vertical Integration and Consumer Choice: Evidence from a Field Experiment

Chiara Farronato
,
Harvard University
Andrey Fradkin
,
Boston University
Alexander MacKay
,
University of Virginia

Abstract

Platforms, retailers, and other firms often offer their own products alongside products sold by competitors, but this form of vertical integration has become a target of regulation in digital markets. We study the effects of this practice through a field experiment that hides brands owned by Amazon (i.e., private labels) from shoppers on Amazon.com. We first consider the effects of this removal on three aspects of consumer behavior: substitution to other products, changes in search effort, and substitution to other retail websites. In the absence of Amazon brands, our results indicate that consumers substitute toward products that are similar along most observable dimensions. We find no evidence that treated consumers change their search effort, nor that they shift their shopping behavior to other retail websites. To evaluate a fourth mechanism---how the presence of Amazon brands affects equilibrium prices---we estimate a structural model of demand and simulate counterfactual prices when removing such products. Our estimates imply that, for the categories we study, removing Amazon brands would reduce consumer surplus by 3.8 percent in the short run, and roughly one quarter of the impact is due to equilibrium price increases by other products. The effects are heterogeneous, with consumer surplus reductions exceeding 10 percent in some categories, while other categories realize no change or even positive increases in consumer surplus when Amazon brands are removed.
JEL Classifications
  • L13 - Oligopoly and Other Imperfect Markets
  • L40 - General