1、1,Principal-agent Modeling 責任代理模式,Dr. Chak-Tong Chau 仇澤棠博士U.S. Fulbright Professor中美交流富布萊特教授,Dr. Chak-Tong Chau,Fulbright Guest Lecture Materials,2,我請您們考慮一些問題,A small medical insurance scenario 一個醫療保健的問題When you have a small illness, do you normally see your doctor? 當你有小病的時候，你會不會自費看醫生？What about, if
2、 your firm pay for your expense?但是，如果是單位付錢呢，那又怎樣？,Dr. Chak-Tong Chau,Fulbright Guest Lecture Materials,3,我請您們考慮一些問題,A car maintenance scenario 一個汽車維修的問題Your car is being rented for 2 months. Supposedly, it needs oiling every month. How likely you will remember to do so?你的汽車是租來用兩個月的，它需要每月潤滑上油一次。你會不會依
3、時地去上油？How about if this is your own car?如果這是你自己的汽車，你又會不會去做？,Dr. Chak-Tong Chau,Fulbright Guest Lecture Materials,4,我請您們考慮一些問題,A medical insurance problem 自費醫療保險的問題When we purchase medical insurance, the insurance company usually requires that you disclose your medical history. Pre-conditions are usu
4、ally excluded from the coverage.購買保險的時候，它們通常要求你列出你的病歷。但是如果你有大病的話，很可能保險公司不愿意受保。,Dr. Chak-Tong Chau,Fulbright Guest Lecture Materials,5,我請您們考慮一些問題,If you do in fact have some major medical problems that require expensive treatments, would you disclose these problems?如果你真的有大病, 你會不會真實地上報？What do all the
5、se tell us about certain human behavior?這些問題表明了一些什么的人性行為？,Dr. Chak-Tong Chau,Fulbright Guest Lecture Materials,6,Agency Problems and Behavior代理人的行為与問題,A moral hazard problem (道德危机問題)when an individual has an incentive to deviate from the contract and take self-interested actions because the other pa
6、rty has insufficient information to know if the contract was honored.醫療保健 雖然我知道我与雇主的契約明确列出我不要浪費公司的資源。但是用公司的好過用我的嘛！而且公司又不會知道我未能遵守契約。,Dr. Chak-Tong Chau,Fulbright Guest Lecture Materials,7,Agency Problems and Behavior代理人的行為与問題,A horizon problem 水平界線問題If one partys risk or compensation is not the same
7、as the other partys, the one with a shorter horizon will tend to secretly maximize the short-term benefits, at the expense of the other longer-term party.汽車維修 我明白汽車不維修壽命不會長。但是，兩個月以后這車子變成怎么樣与我無關了吧。,Dr. Chak-Tong Chau,Fulbright Guest Lecture Materials,8,Agency Problems and Behavior代理人的行為与問題,An adverse
8、 selection problem 逆向選擇問題The tendency of individuals with private information about something that affects a potential trading partners benefits to make offers that are detrimental to the trading partner.自費醫療保險:雖然我知道保險公司需要知道我的病歷從而決定保險費。但是誠實的代价是較高的費用。此外，我不說，誰知道。,Dr. Chak-Tong Chau,Fulbright Guest Lec
9、ture Materials,9,誰是代理人？什么是代理成本？,An agent is someone who has certain special expertise that is desired by the principal to use for his/her benefits. The agent is usually risk adverse, has decision rights to manage, but does not own, the organizations assets. 代理人(agent) 是任何人在公司有決策權力，但是并非產權的最終所有者。代理人通常
10、有較佳的專長，更好的資訊，和對風險抱保守的態度(risk adverse)。,Dr. Chak-Tong Chau,Fulbright Guest Lecture Materials,10,誰是代理人？什么是代理成本？,There are three (3) types of agency costs. 代理成本有三類：設計限制性契約的成本 (bonding costs)建立監督制度的成本 (monitoring costs)剩餘的損耗 (residual loss)Note that some costs are bornt by the principal but some are bor
11、nt by the agent.注意的是，有時這些成本是由委托人(principal)負擔。不過有時這些成本是由代理人自己負擔的。,Dr. Chak-Tong Chau,Fulbright Guest Lecture Materials,11,Agency Costs,Bonding costs costs incurred, before entering the contract, to convince the principal that such agency relationship will not result in the above-mentioned agency pro
12、blems. Examples are: reputation building, 3rd party guarantor, etc.,Dr. Chak-Tong Chau,Fulbright Guest Lecture Materials,12,Agency Costs,Monitoring costs costs incurred, after entering the contract, to ensure that such agency problems will not arise. Examples include auditing and inspection costs.,D
13、r. Chak-Tong Chau,Fulbright Guest Lecture Materials,13,Agency Costs,Residual loss loss unavoidably arise, despite the bonding and monitoring costs, the contract still cannot yield the utmost benefits, because:the agency problems do arise, ordue to the suspicion of the agency problems, the principal
14、refuses to pay the agent compensations that fully reflect his/her efforts.,Dr. Chak-Tong Chau,Fulbright Guest Lecture Materials,14,Examples of the Principal-agent Model,Dr. Chak-Tong Chau,Fulbright Guest Lecture Materials,15,Examples of the Principal-agent Model,Agents Utility Function: Xa - e2 100
15、where: Xa = agents compensationse = the effort level used by the agent,Question 1: If you were the principal in entering the contract, which level of effort (e1, e2, or e3) would you demand?,Question 2: If you, the principal, can closely monitor and observe the agent at all time, what are the amount
16、 andcondition of payment? And, what is the expected payoff for the principal?,Dr. Chak-Tong Chau,Fulbright Guest Lecture Materials,16,Now, lets assume that you cannot monitor and observethe agent directly. What would you, as the agent, do?,Now, can you see the agency problems here?,Is it likely to h
17、ave the “adverse selection” problem?,How about the “moral hazard” problem?,And, the horizon problem? Residual loss?,Dr. Chak-Tong Chau,Fulbright Guest Lecture Materials,17,What can we say, up to this point?,Under condition of unobservability (incomplete information), fixed payments to agents (i.e. w
18、orkers, employees) most likely do not work.What are then the alternatives?We can give the principal a fixed payment instead.Or, we can come up with an “incentive compatible” conditional contract.,Dr. Chak-Tong Chau,Fulbright Guest Lecture Materials,18,Fixed Payment to the Principal,Consider this new
19、 contract under which the principal gets$32,750 no matter what happens and the agent keeps therest. Will this work?,Dr. Chak-Tong Chau,Fulbright Guest Lecture Materials,19,Fixed Payment to the Principal,Thus, numerically this will work to ensure that the agent gives the highest effort.However, there
20、 is nonetheless a loss to the principal (33,504-32,750)=754 which is in a sense a monitoring cost (maximum cost to pay for an information system to reveal the agents effort level).But the most fundamental problem is that this type of contracts violates the “risk adverse” nature of the agent. Now the
21、 agent becomes the principal!,Dr. Chak-Tong Chau,Fulbright Guest Lecture Materials,20,Incentive Compatible Contract Problem Setup,Maximize (55,000 R55)55(e1) + (40,000-R40)40 (e1),Subject to:,R5555(e1) + R4040(e1) - e12 = 100,R5555(e1) + R4040(e1) - e12 R5555(e2) + R4040(e2) e22,R5555(e1) + R4040(e1
22、) - e12 R5555(e3) + R4040(e3) e32,Dr. Chak-Tong Chau,Fulbright Guest Lecture Materials,21,Incentive Compatible Contract Specific Solutions,Maximize (55,000 R55)0.8 + (40,000-R40)0.2,Subject to:,R55(0.8) + R40(0.2) - 36 = 100,R55(0.8) + R40(0.2) - 36 R55(0.6) + R4040(0.4) 25,R55(0.8) + R40(0.2) - 36
23、R55(0.3) + R40(0.7) 16,Solutions:R55 = 21,609 R40 = 8,464Expected payoffs:Principal = 33,020Agent = 18,980,Dr. Chak-Tong Chau,Fulbright Guest Lecture Materials,22,Summary of Different Contracts,Dr. Chak-Tong Chau,Fulbright Guest Lecture Materials,23,What do we know from these?,The best case scenario
24、 for the principal is when he can observe the agents effort level directly.The worst case scenario to the principal appears to be simply charging a fixed rent.The difference between the two ($754) represents the maximum amount to pay for an information system to reveal the agents effort.The middle,
25、2nd best solution (incentive compatible contract) may not always be the next best thing though!,Dr. Chak-Tong Chau,Fulbright Guest Lecture Materials,24,Lets say that we set the two variables, R55 and R40, to be18,769 and 11,449 respectively.,Now, the principal is telling the agent NOT to work hard!,
26、The $33,159 is actually better than the $33,020 under “incentive compatible” contract!,Dr. Chak-Tong Chau,Fulbright Guest Lecture Materials,25,A Few Cautionary Remarks,This model presented here is a single-period model. Multiple-period (repeated games) can give very different answers.There can be mu
27、ltiple principals as well as multiple agents in the model. Such models, however, become extremely complex.Information systems are not considered here.,Dr. Chak-Tong Chau,Fulbright Guest Lecture Materials,26,Concluding Remarks,The Principal-agent model is theoretical elegant but mathematically tediou
28、s to use.Empirical (real-life) evidence seems to support the model well.The challenges, in my opinion, include: to come up with useful, testable hypotheses;to extend the model to more complex, but real business situations;to encourage researchers to teach newcomers the basic skill in understanding the model rather than simply to publish in “ivory-tower” type of journals.,
