We focus on the learning dynamics in multiproduct price-setting markets, where firms use past strategies and performance to adapt to the corresponding equilibrium

Garcia-Gallego, Aurora

Georgantzis, Nikos

Using data obtained from experiments reported in García-Gallego (1998) and García- Gallego and Georgantzís (2001), we estimate a simple model of adaptive behavior which could describe pricing in a market whose demand conditions are unknown to the firms. Divergence between the limit of observed prices over time and theoretical predictions concerning multiproduct firms could be partially explained as a result of learning limitations associated with multiple task-oriented problem solving. However, optimal multiproduct pricing requires that subjects use two different kinds of rules: one concerning responses to prices charged by other players and another concerning pricing of own products. Even in a simple environment like the one studied here, subjects seem to be far more successful in learning a number than learning a rule

Adaptive behavior by single-product and multiproduct price setting firms in experimental markets

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