The mechanisms by which information is traded help shape the creation and the distribution of surplus in many important markets. Information about individual borrowers guides banks’ lending decisions, information about consumers’ characteristics facilitates targeted online advertising, and information about a patient’s genome enhances health care delivery. In all these settings, information buyers (i.e., lenders, advertisers, and health care providers) have private knowledge relevant to their decision problem at the time of contracting (e.g., independent or informal knowledge of a borrower, prior interactions with specific consumers, access to a patient’s family history). Thus, potential data buyers seek to acquire supplemental information to improve the quality of their decision-making. In this project, we seek develop a canonical framework to analyze the sale of supplemental and hence incremental information.
Requisite Skills and Qualifications:
Students need strong background in mathematics at the level of real analysis, probability theory and convex optimization. Advanced knowledge of Matlab is required.