Essays on Pricing and Learning in Bertrand Markets

The thesis studies sellers’ pricing and learning behaviour in Bertrand oligopoly markets using a bounded rational approach. It consists of four chapters. Chapter 1 develops a quantal response adaptive learning model which combines sellers’ bounded rationality with adaptive belief learning in order to explain price dispersion and dynamics in laboratory Bertrand markets with perfect information. In the model, sellers hold beliefs about their opponents’ strategies and play quantal best responses to these beliefs. After each round, sellers update their beliefs based on the information learned from previous play. Maximum likelihood estimation suggests that when sellers have full past price information, the learning model explains price dispersion within periods and the dynamics across periods. The fit is particularly good if one allows for sellers being risk averse. In contrast, Quantal Response Equilibrium does not organize the data well. Chapter 2 proposes a generalized payoff assessment learning model of Sarin & Vahid (1999) for the perfect information Bertrand experiments we studied in Chapter 1. The model contains the quantal-response adaptive learning model of Chapter 1 and the original payoff assessment learning model as special cases. A main feature of the model is that it stresses the importance of forgone payoffs for unselected prices in driving the price adjustments. Maximum likelihood estimation shows that the model substantially outperforms the quantal-response adaptive learning model with respect to fitting the data. Chapter 3 studies the effects of increasing number of sellers on Quantal Response Equilibrium (QRE) prices in homogeneous product Bertrand oligopoly markets. We show that the comparative statics properties of QRE can be very sensitive to the specification of the quantal response function. With the power-function specification, an increase in the number of competing sellers leads to a decrease in the average QRE market price. In stark contrast, with logistic specification, having more sellers may