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Non-competing Data Intermediaries

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I study a model of competing data intermediaries (e.g., online platforms and data brokers) that collect personal data from consumers and sell it to downstream firms. Competition in this market has a limited impact in terms of benefits to consumers: If intermediaries offer high compensation for their data, then consumers may share this data with multiple intermediaries, and this lowers its downstream price and hurts intermediaries. As intermediaries anticipate this problem, they offer low compensation for this data. Competing intermediaries can earn a monopoly profit if and only if firms’ data acquisition unambiguously hurts consumers. I generalize the results to include arbitrary consumer preferences and study the information design of data intermediaries. The results provide new insights into when competition among data intermediaries benefits consumers. It also highlights the limits of competition in terms of improving efficiency in the market for data.

Topic(s): Economic models
JEL Code(s): D, D4, D42, D43, D8, D80, L, L1, L12