Cycling and Categorical Learning in Decentralized Adverse Selection Economies

We study learning in a decentralized pairwise adverse selection economy, where buyers have access to the quality of traded goods but not to the quality of non- traded goods. Buyers categorize ask prices in order to predict quality as a function of ask price. The categorization is endogenously determined so that outcomes that are observed more often are categorized more finely, and within each category beliefs reflect the empirical average. This leads buyers to have a very fine understanding of the relationship between qualities and ask prices for prices below the current market price, but only a coarse understanding above that price. We find that this induces a price cycle involving the Nash equilibrium price, and one or more higher prices.