The purpose of this project is to analyze the effects on market prices and market efficiency of learning on the part of individuals participating in that market. There is good evidence that suppliers and demanders eventually learn enough about the market to form rational expectations about the market they participant in, in the sense that they do not persist in making predictable errors that reduces market efficiency. The way in which market participants learn about a market can affect its efficiency; first by affecting how quickly participants learn about the market, and second by affecting equilibrium prices and quantities. An important part of learning about a market is learning about other suppliers and demanders in the market. This project will analyze learning by the use of experimental markets in which suppliers determine output before any trades occur. This production before sale situation mimics agricultural markets as well as many other markets in which supplies' forecasts of market prices have an important effect on market prices. The most precise learning models are the statistically-based models of Bayesian learning and regression learning. In this study the implications of both types of learning are examined. This research is important because it will give us a better understanding of how learning affects the efficient functioning of markets.
