Behavioral heuristics and market patterns in a Bertrand–Edgeworth game

This paper studies Bertrand price-setting behavior when firms face capacity constraints (Bertrand–Edgeworth game). This game is known to lack equilibria in pure strategies, while the mixed-strategy equilibria are hard to characterize. We explore families of heuristic rules for individual price-setting behavior and the resulting market patterns, through simulations of agent-based models and laboratory experiments. Overall, the individual pricing strategies observed experimentally can be represented approximately by a sales-based simple rule. In the experiments, average market prices tend to converge from above and approach a state resembling a steady state, with slow aggregate price variations and low price dispersion around an average near the competitive level. However, that configuration can be disturbed occasionally by excursions triggered by discrete price raises of some agents. Salient features of experimental results can be described by simulations where agents use sales-based heuristics with parameters calibrated from the experiments. The results obtained here suggest the existence of useful complementarities between analytical, experimental and agent-based simulation approaches.