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  5. The Value of Data
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The Value of Data

Paper Session

Monday, Jan. 4, 2021 3:45 PM - 5:45 PM (EST)

Hosted By: Industrial Organization Society
  • Chair: Marco Ottaviani, Bocconi University

The Editor versus the Algorithm: Targeting, Data and Externalities in Online News

Jorg Claussen
,
Munich School of Management
Christian Peukert
,
Catholic University of Portugal
Ananya Sen
,
Carnegie Mellon University

Abstract

We run a field experiment with a major news outlet to quantify the economic returns to data and informational externalities associated with algorithmic recommendation. Automated recommendation can outperform a human editor in terms of user engagement, though this crucially depends on the amount of training data. Limited individual data or breaking news leads the editor to outperform the algorithm. Additional data helps algorithmic performance but decreasing economic returns set in rapidly. Investigating informational externalities highlights that personalized recommendation reduces consumption diversity. Moreover, users associated with lower levels of digital literacy and more extreme political views engage more with algorithmic recommendations.

Competition in Pricing Algorithms

Zach Y. Brown
,
University of Michigan
Alexander MacKay
,
Harvard University

Abstract

Increasingly, retailers have access to better pricing technology, especially in online markets. What are the implications for price competition? We develop a model where firms choose algorithms that automate responses to rivals’ prices, and we allow firms to differ in their pricing technology. Even with simple (i.e., linear) algorithms, competitive equilibria can have higher prices than in the standard simultaneous price-setting game. Using high-frequency data from major online retailers, we document asymmetric technology and pricing patterns consistent with the model. A counterfactual simulation suggests that pricing algorithms lead to meaningful increases in markups, especially for firms with superior pricing technology.

Data for Service

Dirk Bergemann
,
Yale University
Alessandro Bonatti
,
Massachusetts Institute of Technology
Tan Gan
,
Yale University

Abstract

We consider a model with many consumers and data intermediary who provides
services to generates information in an incentive compatible manner. In turn the data
intermediary does not sell the information directly, but rather indirectly, bundled with
another good. For example, together with a query through a sponsored search auction,
or display advertising on a social network. The data intermediary is not compensating
the individual directly for the information, but provides services whose bene…ts are
naturally increasing in the amount of information they generate.
The key economic question is how to optimally procure information from consumers
through their engagement with the platform.

Privacy and Market Concentration: Intended and Unintended Consequences of the GDPR

Garrett Johnson
,
Boston University
Scott Shriver
,
University of Colorado Boulder
Samuel Goldberg
,
Northwestern University

Abstract

We show that the European Union's General Data Protection Regulation (GDPR) reduced data sharing online, but had the unintended consequence of increasing market concentration among technology vendors that provide support services to websites. We collect panel data on the web technology vendors selected by more than 27,000 top websites internationally. The week after the GDPR's enforcement, website use of web technology vendors for EU users falls by 15%. Websites that would face greater penalties under the GDPR drop more vendors. Websites are more likely to drop smaller vendors, which increases the relative concentration of the vendor market by 17%. Increased concentration predominantly arises among vendors that use personal data such as cookies, and from the increased relative shares of Facebook and Google-owned vendors, but not from website consent requests. This suggests that increases in concentration are driven by website vendor choices rather than changes in user behavior.
Discussant(s)
Gary Biglaiser
,
University of North Carolina-Chapel Hill
Fernando Luco
,
Texas A&M University
Marco Ottaviani
,
Bocconi University
Avi Goldfarb
,
University of Toronto
JEL Classifications
  • L0 - General
  • D4 - Market Structure, Pricing, and Design