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We introduce an agent-based model of delegation relationships between aprincipal and an agent, which is based on the standard-hidden action modelintroduced by Holmstr\"om and, by doing so, provide a model which can be usedto further explore theoretical topics in managerial economics, such as theefficiency of incentive mechanisms. We employ the concept of agentization,i.e., we systematically transform the standard hidden-action model into anagent-based model. Our modeling approach allows for a relaxation of some of therather "heroic" assumptions included in the standard hidden-action model,whereby we particularly focus on assumptions related to the (i) availability ofinformation about the environment and the (ii) principal's and agent'scognitive capabilities (with a particular focus on their learning capabilitiesand their memory). Our analysis focuses on how close and how fast the incentivescheme, which endogenously emerges from the agent-based model, converges to thesolution proposed by the standard hidden-action model. Also, we investigatewhether a stable solution can emerge from the agent-based model variant. Theresults show that in stable environments the emergent result can nearly reachthe solution proposed by the standard hidden-action model. Surprisingly, theresults indicate that turbulence in the environment leads to stability inearlier time periods.

An Agent-Based Model of Delegation Relationships With Hidden-Action: On the Effects of Heterogeneous Memory on Performance