Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01rj4307716
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dc.contributor.authorMusolff, Leon Andreas
dc.contributor.otherEconomics Department
dc.date.accessioned2022-06-16T20:33:51Z-
dc.date.available2022-06-16T20:33:51Z-
dc.date.created2022-01-01
dc.date.issued2022
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp01rj4307716-
dc.description.abstractThis dissertation explores issues of competition in the digital economy. In the first chapter, joint with Kwok-Hao Lee, we evaluate the problem of firms operating platforms matching buyers and sellers, while also selling goods. By guiding consumer search through algorithmic recommendations, these firms influence market outcomes. To analyze, we combine data about sales and recommendations on Amazon Marketplace with a structural model of intermediation power. Recommendations are highly price elastic but favor Amazon. Many consumers only consider recommended offers. By preferring Amazon, the recommendations raise consumer welfare by \$4.5 billion. However, consumers are made worse off if self-preferencing makes the company raise prices by more than 7.8%. Finally, we find no evidence of self-preferencing reducing entry. Nevertheless, entry matters. Algorithmic recommendations raise consumer welfare by stimulating demand and intensifying price competition. However, these gains are mostly offset by reduced entry. The second chapter considers that, as the economy digitizes, menu costs fall, firms' ability to monitor prices increases, and automatic pricing tools ('repricers') are becoming common. We employ novel e-commerce data to examine the implications. An RDD shows that repricers initially cause a decline in prices. However, 'resetting' strategies (regularly raising prices) effectively coax competitors to match price increases. While the resulting patterns are reminiscent of Edgeworth cycles, a model of delegated strategies fits better. If repricers remain at their current capability level, cycling will increase, and prices could rise significantly. Welfare under automated repricing is comparable to welfare under monopoly. The third chapter, joint with Bruno Baranek and Vitezslav Titl, studies collusion in the e-procurement market in Ukraine. We document suspicious bidding patterns in our data and build a model of competitive equilibrium. Frequently, we observe bids inconsistent with this equilibrium: when initial bids are close, suppliers should have similar costs and be willing to undercut each other. If firms only engage in undercutting when facing some opponents (but not others), we conclude that these firms are part of a collusive ring. Finally, we successfully validate this novel structural collusion test's soundness on a sample of 863 prosecuted collusive firms.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherPrinceton, NJ : Princeton University
dc.relation.isformatofThe Mudd Manuscript Library retains one bound copy of each dissertation. Search for these copies in the library's main catalog: <a href=http://catalog.princeton.edu>catalog.princeton.edu</a>
dc.subjectalgorithmic pricing
dc.subjectcompetition
dc.subjectdigital economy
dc.subjecte-commerce
dc.subjectindustrial organization
dc.subjectplatforms
dc.subject.classificationEconomics
dc.titleEssays on Competition in the Digital Economy