Limited memory of decision-makers is often neglected in economic models, although it is reasonable to assume that it significantly influences the models' outcomes. The hidden-action model introduced by Holmström also includes this assumption. In delegation relationships between a principal and an agent, this model provides the optimal sharing rule for the outcome that optimizes both parties' utilities. This paper introduces an agent-based model of the hidden-action problem that includes limitations in the cognitive capacity of contracting parties. Our analysis mainly focuses on the sensitivity of the principal's and the agent's utilities to the relaxed assumptions. The results indicate that the agent's utility drops with limitations in the principal's cognitive capacity. Also, we find that the agent's cognitive capacity limitations affect neither his nor the principal's utility. Thus, the agent bears all adverse effects resulting from limitations in cognitive capacity.
We introduce an agent-based model of delegation relationships between a principal and an agent, which is based on the standard-hidden action model introduced by Holmström and, by doing so, provide a model which can be used to further explore theoretical topics in managerial economics, such as the efficiency of incentive mechanisms. We employ the concept of agentization, i.e., we systematically transform the standard hidden-action model into an agent-based model. Our modeling approach allows for a relaxation of some of the rather "heroic" assumptions included in the standard hidden-action model, whereby we particularly focus on assumptions related to the (i) availability of information about the environment and the (ii) principal's and agent's cognitive capabilities (with a particular focus on their learning capabilities and their memory). Our analysis focuses on how close and how fast the incentive scheme, which endogenously emerges from the agent-based model, converges to the solution proposed by the standard hidden-action model. Also, we investigate whether a stable solution can emerge from the agent-based model variant. The results show that in stable environments the emergent result can nearly reach the solution proposed by the standard hidden-action model. Surprisingly, the results indicate that turbulence in the environment leads to stability in earlier time periods.
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