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Preprints, Working Papers, ... Year : 2020

Digital Privacy

Abstract

We study the incentives of a digital business to collect and protect users’ information. The information the business collects improves the service it provides to consumers, but it may also be accessed, at a cost, by third strategic parties in a way that harms users, imposing privacy costs. We characterize how the revenue model of the business shapes the equilibrium data policy. We compare the equilibrium data policy with the social optimum and show that a two-pronged policy, which combines a minimal data protection requirement with a tax proportional to the amount of data collected, restores efficiency.
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Dates and versions

hal-02896509 , version 1 (10-07-2020)

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Itay Perah Fainmesser, Andrea Galeotti, Ruslan Momot. Digital Privacy. 2020. ⟨hal-02896509⟩

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