Memory and Markets

Abstract

In many environments, including credit and online markets, past records about participants are collected, published, and erased after some time. We study the effects of erasing past records in a dynamic market where sellers’ quality follows a Markov process and buyers leave feedback about sellers to an information intermediary. When the average quality of sellers is low, unlimited records lead to a market breakdown in the long run. We consider the general information design problem and characterize information policies that can sustain trade and that maximize welfare. These policies hide some information from the market in order to foster socially desirable experimentation. We show that these outcomes can be implemented by appropriately deleting observable past records. Crucially, positive and negative records play opposite roles with different intensity and must have different length: negative records must be sufficiently long, and positive records sufficiently short.

Keywords: Limited records, rating systems, credit registers, privacy, data retention, online reputation, market experimentation, right to be forgotten.

JEL Classification: D82, D53, G20, G28, K35, L14, L15