Trading Service for Data
Award:Fred ZhangGina Markov Jack Hirsch
Digital platforms such as facebook, google, etc. frequently trade information indirectly, bundled with another good. For example, Google sells information about the searcher together with a query through the sponsored search auction. Similarly, Facebook matches advertisers and individual consumers with certain characteristics. In those instances, the data intermediary is not compensating the individual directly for the information, but provides services whose benefits are naturally increasing in the amount of information they generate.
This theoretical and analytical project develops a model of bartering services for information. The intermediary (“the platform”) provides valuable services to the consumer at no charge, and sells the information so-gained to multiple downstream parties. The key economic question is how to optimally procure information from consumers through their engagement with the platform.
Requisite Skills and Qualifications:
Advanced mathematical and programming skills in linear and nonlinear programming, probability theory, game theory, information theory, market design