Simulating markets using agent-based models must consider pricing. However, the strategic nature of prices limits the development of agent-based models with endogenous price competition. I propose an agent-based algorithm based on Game Theory that allows us to simulate the pricing in different markets. I test the algorithm in five theoretical economic models from the industrial organization literature. In all cases, the algorithm is capable of simulating the optimal pricing of those markets. It is also tested in two more cases: one in which the original work fails to predict the optimal outcome, and another one that is quite complex to solve analytically. Lastly, I present two potential extensions of this algorithm: one dynamic, and another one based on quantity competition. This algorithm opens the door to the extensive inclusion of pricing in agent-based models, but also, it helps to establish a link between the industrial organization literature and the agent-based modeling.
Simulating markets using agent-based models must consider pricing. However, the strategic nature of prices limits the development of agent-based models with endogenous price competition. I propose an agent-based algorithm based on Game Theory that allows us to simulate the pricing in different markets. I test the algorithm in five theoretical economic models from the industrial organization literature. In all cases, the algorithm is capable of simulating the optimal pricing of those markets. It is also tested in two more cases: one in which the original work fails to predict the optimal outcome, and another one that is quite complex to solve analytically. Lastly, I present two potential extensions of this algorithm: one dynamic, and another one based on quantity competition. This algorithm opens the door to the extensive inclusion of pricing in agent-based models, but also, it helps to establish a link between the industrial organization literature and the agent-based modeling. Read More
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