代理人自利行为下的最优激励契约

在线性契约委托代理框架中引入代理人的自利行为,主要从隐藏收益和在职消费两种自利行为视角分析代理人的自利行为对最优激励契约设计的影响.通过理论模型和数值分析发现,代理人隐藏、转移收益自利行为降低了最优激励契约业绩薪酬系数.代理人在职消费自利行为提高了最优激励契约业绩薪酬系数.说明代理人不同自利行为下,委托人提供的最优激励契约是不同的.从代理人的最优努力程度来看,代理人的自利行为不同程度地提高了自身的努力水平.研究表明在当前我国企业薪酬激励制度背景下,代理人的自利行为可能表现为一种自我激励机制.研究结论为我国企业目前薪酬激励扭曲的后果和未来薪酬制度的改革提供了有意义的参考.     

信息不对称下委托代理契约纳什实施性研究

针对代理人逆向选择导致委托人无法将契约与代理人类型状态直接关联的矛盾,研究了信息不对称下委托代理契约的纳什实施性问题。通过建立信号空间上的纳什均衡与有效配置的映射关系,将委托人契约与代理人状态联系起来,并以完全信息下委托人的最优契约和逆向选择下的次优契约为例,研究分析委托人契约纳什实施的性质,当且仅当委托契约满足激励相容约束时,才具备纳什实施的惟一性,该结果为实务契约设计逼近激励可行契约提供了新的途径。     

委托─代理理论中自然状态的不确定性对最优契约影响的研究

本文考虑了委托─代理理论中代理人和委托人对于不确定的自然状态可能会有不同的概率,另外还考虑了自然状态对代理人努力负效用的影响,对委托─代理模型进行了拓展研究,使原有模型成为一个特例。通过一个简化的委托─代理框架进行分析,结果表明,代理人对自然状态的概率与代理人可能付出的努力水平有正相关关系,而且代理人和委托人对自然状态的概率对最优契约有不可忽视的影响。     

道德风险模型中代理人公平敏感性对契约影响

在传统的道德风险模型中引入公平偏好同时糅合公平敏感性,通过公平敏感性系数刻画代理人对公平理解的差异性.以这类引入了代理人公平偏好及公平敏感性系数的委托代理模型,研究委托代理契约的设计方法并分析公平敏感性对契约结构及代理人最优努力水平的影响.研究表明:完全信息下委托人设计的契约只需支付与公平敏感性系数正相关的固定支付;在努力水平不可观察时,当公平敏感性系数大到一定程度时,委托人会通过调节固定支付消除不公平的存在;而当公平敏感性系数也不可观察时,委托人则根据期望公平敏感系数做决策.     

信号对契约设计及福利的影响研究

与代理人类型有一定程度相关性的信号能够改变委托人的初始信息结构并因此影响委托人的契约设计.现有文献很少讨论事前不可验证的信号对契约参与者事前福利的影响.相比对事后福利的研究,对事前福利的研究在契约设计中更具有现实意义.文章研究了信号对契约参与者事前福利的影响.结果表明:委托人通过对信号的观察改进契约会提高委托人的事前期望剩余;委托人的初始信息结构和信号的信息量是影响代理人事前期望剩余的关键因素;在一定的严格条件下,委托人对信号的观察能够增加代理人的事前期望剩余,即实现事前期望福利的帕累托改进.     

基于Rubinstein讨价还价的激励契约研究

传统的激励契约理论通过假设委托人提供一个"要么接受,要么走人"的契约给代理人,从而搁置了委托人与代理人就契约进行的讨价还价问题.这种假设下,委托人能获得最大收入,但代理人只能获得保留收入.本文假设代理人可以与委托人就激励契约进行Rubinstein讨价还价,从而得到一份均衡的契约.在均衡契约中,代理人的收益往往会高于传统契约.     

代理人信息租金抽取的贝叶斯优化与配置效率均衡分析

研究逆向选择下,委托人通过信号辅助改善信息结构后所面临的代理人信息租金抽取与配置效率的均衡决策问题。首先,分析讨论了完全信息下的最优契约和逆向选择下先验分布基础上的次优契约;之后,基于贝叶斯规则,将与代理人相关的外部信号及信号搜集成本纳入委托人的最优规划问题,对后验分布下的均衡变动进行了分析,给出了信号搜集成本可行预算集。研究表明,贝叶斯方法有利于委托人在信息租金与效率扭曲冲突中优化决策,为复杂环境下的实务契约设计逼近激励相容契约提供了量化参考依据。     

基于代理人过度自信的委托-代理关系模型研究

本文研究代理人过度自信条件下的委托-代理关系以及过度自信对委托-代理关系的作用机理.研究结果表明,当代理人的效益工资和委托人的监督成本都不为0时,代理人的最优努力水平将随着其过度自信程度的增大而提高,委托人的最优监督力度将随着代理人过度自信程度的增大而减弱;当代理人没有效益工资时,代理人的过度自信在委托-代理关系中不发挥作用.另外,代理人的最优努力水平和委托人的最优监督力度都将随着委托人监督成本的增大而降低,而且前者还将总是随着代理人固定报酬和效益工资的增加而提高,后者虽然也将随着代理人固定报酬的增加而提高,但并不总是随着代理人效益工资的增加而加强.     

不同风险偏好的过度自信代理人薪酬合同设计

本文将过度自信心理特征纳入到经典委托代理框架,从代理人过度自信程度、代理人的风险偏好、努力-产出不确定性、努力可观测性、保留效用几个角度,构建了多个不同的委托代理情景,分别分析了委托人提供不同形式合同、代理人付出不同努力水平时他们的期望效用,从而考察在各种情景下委托人应怎样为不同类型代理人设计薪酬合同,激励代理人付出努力,以实现委托人和代理人决策组合的帕雷托最优.结果表明,对不同过度自信程度及风险偏好的代理人,委托人提供的合同形式大不相同.这不仅从行为的角度拓展了经典委托代理框架,而且为委托人设计薪酬合同提供了非常有益的参考.     

逆向选择下供应链业务外包中的最优合约配置

研究了委托人(业务购买方)对于承包人(业务供应方)生产成本具有非对称信息时的最优合约设计问题.基于委托人视角,给出了委托人如何诱导代理人报告自己真实成本信息的逆向选择模型,并刻画了最优合约的特征.结果表明:给出的合约能够达到诱导代理人讲真话的目的;在信息非对称条件下,委托人由于信息缺乏受到了损失,而低成本类型的代理人获得了额外的信息租金;在非对称信息条件下,最优合约的参数配置受到委托人事前信念的影响.     

GETTING IT DONE: DYNAMIC INCENTIVES TO COMPLETE A PROJECT

A principal wants an agent to complete a project. The agent undertakes unobservable effort, which affects in each period the probability that the project is completed. We characterize the contracts that the principal sets, with and without commitment. With full commitment, the contract involves the agent's value and wage declining over time, in order to give the agent incentives to exert effort. The best sequentially rational equilibrium for the principal also involves the agent's wage declining over time, while the worst sequentially rational equilibrium for the principal has a constant wage (and is in fact the unique stationary equilibrium). The best (weakly) renegotiation‐proof equilibrium for the principal is achieved by a constant wage that maximizes the principal's payoff, conditional on wages being constant. We compare these solutions to the efficient outcome.     

A Polynomial Optimization Approach to Principal–Agent Problems

This paper presents a new method for the analysis of moral hazard principal–agent problems. The new approach avoids the stringent assumptions on the distribution of outcomes made by the classical first‐order approach and instead only requires the agent's expected utility to be a rational function of the action. This assumption allows for a reformulation of the agent's utility maximization problem as an equivalent system of equations and inequalities. This reformulation in turn transforms the principal's utility maximization problem into a nonlinear program. Under the additional assumptions that the principal's expected utility is a polynomial and the agent's expected utility is rational in the wage, the final nonlinear program can be solved to global optimality. The paper also shows how to first approximate expected utility functions that are not rational by polynomials, so that the polynomial optimization approach can be applied to compute an approximate solution to nonpolynomial problems. Finally, the paper demonstrates that the polynomial optimization approach extends to principal–agent models with multidimensional action sets.     

Progressive Learning

We study a dynamic principal–agent relationship with adverse selection and limited commitment. We show that when the relationship is subject to productivity shocks, the principal may be able to improve her value over time by progressively learning the agent's private information. She may even achieve her first‐best payoff in the long run. The relationship may also exhibit path dependence, with early shocks determining the principal's long‐run value. These findings contrast sharply with the results of the ratchet effect literature, in which the principal persistently obtains low payoffs, giving up substantial informational rents to the agent.     

Robustness and Separation in Multidimensional Screening

A principal wishes to screen an agent along several dimensions of private information simultaneously. The agent has quasilinear preferences that are additively separable across the various components. We consider a robust version of the principal's problem, in which she knows the marginal distribution of each component of the agent's type, but does not know the joint distribution. Any mechanism is evaluated by its worst‐case expected profit, over all joint distributions consistent with the known marginals. We show that the optimum for the principal is simply to screen along each component separately. This result does not require any assumptions (such as single crossing) on the structure of preferences within each component. The proof technique involves a generalization of the concept of virtual values to arbitrary screening problems. Sample applications include monopoly pricing and a stylized dynamic taxation model.     

Persistent Private Information

This paper studies the design of optimal contracts in dynamic environments where agents have private information that is persistent. In particular, I focus on a continuous‐time version of a benchmark insurance problem where a risk‐averse agent would like to borrow from a risk‐neutral lender to stabilize his utility. The agent privately observes a persistent state variable, typically either income or a taste shock, and he makes reports to the principal. I give verifiable sufficient conditions showing that incentive‐compatible contracts can be written recursively, conditioning on the report and two additional state variables: the agent's promised utility and promised marginal utility of the private state. I then study two examples where the optimal contracts can be solved in closed form, showing how persistence alters the nature of the contract. Unlike the previous discrete‐time models with independent and identically distributed (i.i.d.) private information, the agent's consumption under the contract may grow over time. Furthermore, in my setting the efficiency losses due to private information increase with the persistence of the private information, and the distortions vanish as I approximate an i.i.d. environment.     

BUILDING REPUTATION FOR CONTRACT RENEWAL: IMPLICATIONS FOR PERFORMANCE DYNAMICS AND CONTRACT DURATION

We study how career concerns affect the dynamics of incentives in a multi‐period contract, when the agent's productivity is a stochastic function of his past productivity and investment. We show that incentives are stronger and performance is higher when the contract approaches its expiry date. Contrary to common wisdom, long‐term contracts may strengthen reputational effects whereas short‐term contracting may be optimal when investment has persistent, long‐term effects.     

Measurement Error and Incentive Pay

Abstract. We will analyse the optimal incentive scheme when the risk‐neutral principal contracts with many risk‐averse agents. Each agent produces an individual contribution which jointly form a total output. Agents’ efforts are unobservable and the principal cannot observe individual outputs without an error. Neither the observed individual output of an agent nor the observed total output of the whole team are then sufficient statistics for the actual individual output in the sense of Blackwell. We show that the mixed contract of the pure piece‐rate contract and of the pure team contract then dominates the pure contracts from the principal's point of view.     

Motivating Retail Marketing Effort: Optimal Contract Design

We study a distribution channel where a manufacturer relies on a sales agent for selling the product, and for investing in the most appropriate marketing effort. The agent's effort is hard to monitor. In addition, the cost of effort is the agent's private information. These impose challenges to the manufacturer in its endeavor to influence the agent's marketing effort provisions and to allocate profit between the two parties. We propose two contract forms. The franchise fee contract is a two‐part price schedule specifying a variable wholesale price and a fixed franchise fee. The retail price maintenance contract links the allowed retail price that the agent charges customers with total payment to the manufacturer and sales level. Under information asymmetry, for implementing either contract form, the manufacturer needs to offer a menu of contracts, hoping to invoke the “revelation principle” when the agent picks a certain contract from that menu. We show that the two contract forms perform differently, and each party's preference toward a particular contract form is linked with the total reservation profit level and/or the sales agent's cost type. We provide managerial guidelines for the manufacturer in selecting a better contract form under different conditions.     

Zero Expected Wealth Taxes: A Mirrlees Approach to Dynamic Optimal Taxation

In this paper, I consider a dynamic economy in which a government needs to finance a stochastic process of purchases. The agents in the economy are privately informed about their skills, which evolve stochastically over time; I impose no restriction on the stochastic evolution of skills. I construct a tax system that implements a symmetric constrained Pareto optimal allocation. The tax system is constrained to be linear in an agent's wealth, but can be arbitrarily nonlinear in his current and past labor incomes. I find that wealth taxes in a given period depend on the individual's labor income in that period and previous ones. However, in any period, the expectation of an agent's wealth tax rate in the following period is zero. As well, the government never collects any net revenue from wealth taxes.     

Robust Contracts in Continuous Time

We study a continuous‐time contracting problem under hidden action, where the principal has ambiguous beliefs about the project cash flows. The principal designs a robust contract that maximizes his utility under the worst‐case scenario subject to the agent's incentive and participation constraints. Robustness generates endogenous belief heterogeneity and induces a tradeoff between incentives and ambiguity sharing so that the incentive constraint does not always bind. We implement the optimal contract by cash reserves, debt, and equity. In addition to receiving ordinary dividends when cash reserves reach a threshold, outside equity holders also receive special dividends or inject cash in the cash reserves to hedge against model uncertainty and smooth dividends. The equity premium and the credit yield spread generated by ambiguity aversion are state dependent and high for distressed firms with low cash reserves.