Opitmal Contract and Organizational Design under Moral Hazard and Adverse Selection

Beschreibung

Contracts play a crucial role in the organization of economic activity. Insurance contracts, sales contracts, procurement contracts or employment contracts are some examples of these. Thereby, contracts serve as a tool to solve the conflict of interests between the contractual parties, i. e. principal and agent. The solution of this conflict is often rendered more difficult due to the asymmetry of information between the contracting parties. Two kinds of asymmetric information are distinguished. A situation in which the principal cannot control the agent ist called moral hazard, a situation in which the agent possesses more information than the principal is called adverse selection. From contract theory it is well-known that the first problem can be reduced by the inclusion of incentives for the agent, and that in the second situation, a menu of contracts allows the principal to extract some of the agent's information. In the present book the following situations are analysed based on these results. Firstly, what the optimal contract under simultaneous moral hazard and adverse selection looks like, and secondly, how the existence of contractual relationships between one principal and several agents affects the optimal contract design. It is demonstrated that such a situation offers an argument for lean production and team-orientated working structures, and that the possibility for the principal to extract information crucially depends on substitutability in production. Furthermore, the multi-agent context allows the analysis of hierarchical structures. It is shown by the example of a production enterprise and a maintenance firm that solely due to different informational situations some hierarchical organizations are superior to others. It is especially this last result which contributes to our understanding of the entity "the firm" as a nexus of contractual relationships between its members, who may pursue different aims.

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Bernd Theilen

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