Pure Nash Equilibrium Market Recommendations

Abstract

New business models help sellers make better decisions by communicating information about market prices. However, sellers' inability to coordinate greatly reduces the efficacy of this information and can lead to market failures. We study the feasibility and benefits of providing equilibria as recommendations in economies where sellers face price uncertainty, information scarcity, and an inability to coordinate.

We describe a general model in which sellers wish to sell some quantity of a good at one of several markets with elastic prices, and show that while a pure Nash equilibrium may not necessarily exist, an approximate equilibrium always exists under mild assumptions on the market concentration. We describe an algorithm that a market planner can use to recommend approximate  equilibria to sellers, and compare the recommended (approximate) equilibria to selling strategies identified from a survey of onion and potato farmers in India. Using real data on India's agricultural markets, we show that the recommended strategy outperforms the other strategies in terms of seller welfare, geographic price dispersion, market volume concentration, and several metrics of individual farmer welfare improvements. We use parameterized data to show that the framework is robust to imperfect market penetration, is fair to smaller farmers, and captures nearly all of the welfare from a welfare-maximizing allocation.

Keywords: Service Operations; Empirical Research; Game Theory; OM-Information Technology Interface