Bonus or flat wage? An experiment into the principal-agent problem

We conduct a simple principal-agent experiment in order to find the effects of information asymmetry on compensation. Our aim is the analysis of the appropriate compensation and its impact on employee’s effort. Furthermore we want to compare the offered compensation and the supplied effort in the version without communication and we want to know whether the experimental observations are consistent with the theoretical considerations.The experimenters found out that compensations observed during the experiment were different from those suggested by the theory and although they were theoretically not enough to induce high effort, we could observe high performance supplied by the agents.     

具有私人信息的道德风险的委托—代理人模型的合约分析

本文对存在的不对称信息的环境下的具有私人信息道德风险的委托—代理人模型的合约问题进行了详细的讨论,并得出一些有新意的结论.此讨论问题的方法很值得推荐和推广,特别是在最优激励合同中,比如投资激励,管理机制中的激励,销售激励,保险激励等合同的设计,都可以借鉴此方法来研究和分析.     

Random sampling within the framework of a multivariate principal-agent approach

In this paper, we analyze a specific class of principal-agent models which seems to be sufficiently general to cover applications in environmental economics with upstream-downstream problems as an example. In our basic model, the observation outcome is ann-dimensional random vectorx and only the first and second moments ofx are common knowledge. We study the effects of random sampling in the presence of costly signals. For this purpose, we assume that the principal and the agent use a simple statistical procedure, i.e. their contract will be based on the mean of a random sample with sampling costs dependent on the sample size. It is shown that there exists an optimal sample size. We investigate the relationship between the optimal sample size, the marginal sampling costs, and the agent's risk aversion.     

Dynamic principal agent model based on CMDP

Dynamic principal agent models are formulated based on constrained Markov decision process (CMDP), in which conditions are given that the state space of the system is countable and the agent chooses his actions from a countable action set. If the principal has finite alternative contracts to select, it is shown that the optimal contract solution and the corresponding optimal policy can be obtained by linear programming under the discounted criterion and average criterion. The paper is supported by Zhejiang Provincial Nature Science Foundation of China (701017) and by Scientific Research Fund of Zhejiang Provincial Education Department.     

Optimal Compensation with Hidden Action and Lump-Sum Payment in a Continuous-Time Model

We consider a problem of finding optimal contracts in continuous time, when the agent’s actions are unobservable by the principal, who pays the agent with a one-time payoff at the end of the contract. We fully solve the case of quadratic cost and separable utility, for general utility functions. The optimal contract is, in general, a nonlinear function of the final outcome only, while in the previously solved cases, for exponential and linear utility functions, the optimal contract is linear in the final output value. In a specific example we compute, the first-best principal’s utility is infinite, while it becomes finite with hidden action, which is increasing in value of the output. In the second part of the paper we formulate a general mathematical theory for the problem. We apply the stochastic maximum principle to give necessary conditions for optimal contracts. Sufficient conditions are hard to establish, but we suggest a way to check sufficiency using non-convex optimization.     

基于委托—代理下的模糊报童问题

在委托-代理关系中.代理人的私人信息对委托人的决策会产生重要影响.因此,为了获取代理人的真实信息.设计一个有效的激励机制是委托人的核心问题.本文基于需求依赖于代理人的努力水平和模糊市场条件的假设,利用委托一代理相关理论,探讨了模糊报童问题的激励机制问题.首先讨论了委托人最优产量的确定问题.然后分别给出了可观测和不可观测两种努力水平下的最优激励机制,最后分析了模糊市场条件对委托一代理双方利益的影响.     

Induction over constrained strategic agents

In a new learning paradigm called Induction over Strategic Agents, the principal anticipates possible alteration of attributes by agents wishing to achieve a positive classification. In many cases, agents are constrained on how an attribute can be modified. For example, attribute values may have upper and lower bounds or they may need to belong to a certain set of possible values such as binary valued attributes like “pays bills on time” or be linearly dependent like the relationships between accounting entries in an income statement. In this paper, we explore Induction over Strategic Agents for a class of problems where attributes are binary values.     

Optimal benchmarking for active portfolio managers

Within an agency theoretic framework adapted to the portfolio delegation issue, we show how to construct optimal benchmarks. In accordance with US regulations, the benchmark-adjusted compensation scheme is taken to be symmetric. The investor’s control consists in forcing the manager to adopt the appropriate benchmark so that his first-best optimum is attained. Solving simultaneously the manager’s and the investor’s dynamic optimization programs in a fairly general framework, we characterize the optimal benchmark. We then provide completely explicit solutions when the investor’s and the manager’s utility functions exhibit different CRRA parameters. We find that, even under optimal benchmarking, it is never optimal for the manager, and therefore for the investor, to follow exactly the benchmark, except in a very restrictive case. We finally assess by simulation the practical importance, in particular in terms of the investor’s welfare, of selecting a sub-optimal benchmark.     

On coordination of supply chain based on information asymmetry of effort level and fuzzy market environment

The agent’s private information contributes greatly to a person to make principal decision in the supply of a chain coordination. Therefore, it is a great issue for him to design an effective incentive mechanism in order to get the true information from the agent in his principle making. Assuming that the demand depend upon an agent’s effort level and the fuzzy market condition, the author in this paper researches and analyzes the principle-agent problem under fuzzy information asymmetry condition by using the theory of principal-agent as well as incentive mechanism.