Information Precision and Asymptotic Efficiency of Industrial Markets

Abstract

Online market places have an unprecedented power of bringing together a large number of buyers and sellers and aggregating information. Despite its benefits, this scale of aggregation of private information may bring about adverse effects that can cause ine±ciencies, which can be ignored by conventional analysis. In this paper, I present a strategic model of a large industrial market with asymmetric information to examine (i) the validity of the conjecture of price-taking behavior in such markets as the number of agents becomes large; (ii) the effect of the rate that individual information precision decreases with increased number of agents on convergence to price-taking and e±ciency. I show that in an industrial market with downstream competition, increasing the number of sellers may make all participants price-takers in the limit, but increasing the number of buyers may not. When the total precision of information in the market is high, price taking and full social e±ciency is achieved in the limit with large numbers of buyers and sellers. However, if the total precision of information in the market is poor, large ine±ciencies, including full ine±ciency, can occur in the limiting outcome. The rate of decrease of individual information precision with increased number of agents determines the rate of convergence to efficiency, and the convergence is slower than that predicted by the single unit trading models in the literature.