Lecture 9 Flashcards
(25 cards)
Who are data brokers (DB)?
Firms that specialize in collecting, merging, and selling data.
What did the 2014 US FTC report on data brokers reveal?
It highlighted the size and scope of the industry, sources of data, types of products, and made legislative recommendations.
How large can a data broker’s database be?
One broker had 3000 data segments per US consumer, 1.4B transactions, 700B data points, and added 3B records monthly.
What are the main sources of data for brokers?
Government records (e.g., census, court data), publicly available sources (e.g., social media), and commercial sources (e.g., other brokers).
What types of products do data brokers offer?
1) Marketing and analytics, 2) Risk mitigation (fraud, identity), 3) People search services.
Why are data brokers’ incentives considered distortionary?
They focus solely on maximizing profit from data, often facilitating price discrimination and reducing downstream competition.
How can data brokers negatively impact consumer surplus?
By enabling firms to charge higher prices or reduce competition, they reduce consumer surplus.
In a duopoly, what happens when both firms can price discriminate?
Profits are symmetric (πA = πB = 1/4), and aggregate consumer surplus remains unchanged.
What happens if only one firm has data?
That firm gains a competitive advantage, raising its profits (πA = 7/16, πB = 1/8), but consumer surplus drops due to inefficient outcomes.
What is the optimal strategy for data brokers in selling data?
Sell to only one firm to extract the highest value by creating asymmetry and playing firms against each other.
How does the broker’s data selling strategy affect competition?
It softens competition and leads to reduced consumer surplus.
How does selling exclusive access affect the social value of data?
It creates value for the broker from socially useless information, illustrating the gap between private and social value.
What did Bounie et al. (2021) show about selective disclosure?
Disclosing only high-WTP consumers and selling to one firm helps reduce competition.
What did Bimpikis et al. (2019) find about strategic substitutes?
With substitutes like price competition, brokers restrict information; with complements, they share it more freely.
What are the three types of digital businesses in terms of data?
1) Data-driven (e.g. weather app), 2) Ad-driven (e.g. Meta, Google), 3) Usage-driven (e.g. Uber, Tinder).
What did Fainmesser et al. (2022) conclude about data collection and protection?
They are complements, especially in data-driven models; impact on consumers depends on data benefits.
How does Amazon’s dual role affect consumer welfare?
It steers consumers to Amazon products even when less relevant, reducing recommendation effectiveness and consumer surplus.
What evidence shows Amazon steers recommendations?
Amazon products are more recommended; stockouts reduced third-party visibility by 8 percentage points.
What is the conflict in ad targeting platforms like Google?
Better targeting increases competition and lowers ad prices, but platforms prefer less precise matching to maximize revenue.
What strategy might Google use to reduce matching precision?
Using tools like ‘quality score’ and ‘broad match’ to increase consumer indecisiveness and raise click fees.
Why do social media platforms prioritize engagement?
It increases ad revenue and data collection, even at the cost of user welfare.
What content increases engagement but reduces welfare?
Toxic content (Beknazar-Yuzbashev et al.) and addictive features (Ichihashi & Kim, 2022).
How do attention platforms create addiction?
By using notifications, infinite scrolling, and autoplay to prolong usage and reduce service quality.
Do service providers have better incentives than data brokers?
Not necessarily – they may reduce welfare through steering, inefficient ad targeting, or addictive designs.
