The Coconut Model with Heterogeneous Strategies and Learning
This work addresses the limitations of homogeneous rationality assumptions in economic models for researchers in agent-based computational economics, though it is incremental as it extends an existing framework.
The paper tackles the problem of modeling economic agents with heterogeneous and adaptive expectations in the Coconut Model, showing that when agents use temporal difference learning, the system converges to a stable equilibrium matching the original model's fixed points.
In this paper, we develop an agent-based version of the Diamond search equilibrium model - also called Coconut Model. In this model, agents are faced with production decisions that have to be evaluated based on their expectations about the future utility of the produced entity which in turn depends on the global production level via a trading mechanism. While the original dynamical systems formulation assumes an infinite number of homogeneously adapting agents obeying strong rationality conditions, the agent-based setting allows to discuss the effects of heterogeneous and adaptive expectations and enables the analysis of non-equilibrium trajectories. Starting from a baseline implementation that matches the asymptotic behavior of the original model, we show how agent heterogeneity can be accounted for in the aggregate dynamical equations. We then show that when agents adapt their strategies by a simple temporal difference learning scheme, the system converges to one of the fixed points of the original system. Systematic simulations reveal that this is the only stable equilibrium solution.