InformationSystemsunderPrincipal-agentModelingDr.Chak-TongChau仇澤棠博士U.S.FulbrightProfessor中美交流富布萊特教授Dr.Chak-TongChauFulbrightGuestLectureMaterials2WhatIsInformation?Broadlydefined,informationisanydevicethathelpstoreduceuncertainty.Alternatively,informationshouldbehelpfulin:detectingthecurrentstateoftheworld,orforecastingthefuturestateoftheworldDr.Chak-TongChauFulbrightGuestLectureMaterials3GoodInformationShouldbeUsefulin:Improvingproductiondecisions–tellingustodotherightthings.Optimizingthescopeforrisksharing–sothatsomepeoplecannotmakeprofitsbyharmingotherpeople.Eliminating“informationasymmetry”–sothatexante(before-the-act)privateinformationcanbeknownexpost(after-the-act).Dr.Chak-TongChauFulbrightGuestLectureMaterials4TimelineofatypicalagencycontractContractagreedEffortselectedPayoffrevealedPre-contractinformationPre-effortselectioninformationPost-effortinformationPost-payoffinformationTimingInformationAvailabilityToagentonly(private)Toallparties(public)Pre-contractAgent’sproprietaryknowledgeHistoricalinformationPost-contract,pre-effortInformationsetunderdecentralizationPost-effort,pre-payoffVoluntarydisclosure–relevationprinciplePostpayoff(expost)NotinterestingFinancialreportingDr.Chak-TongChauFulbrightGuestLectureMaterials5UsefulnessofInformationHowdoweknow,apriori,thatinformationis“useful”?Considerthefollowingpayoffstructure(knowntoall):EffortS1S2S3S4S5S6ExpectedPayoffe1=102334553.67e2=52234453.33Dr.Chak-TongChauFulbrightGuestLectureMaterials6UsefulnessofInformationNow,wehaveaninformationsystemthatwillgeneratethesesignals:{S1,S2,S3}{S4,S5,S6}Y1Y2Signal:Y1Y2S1S2S3S4S5S6e1=10233455e2=5223445Inasense,theinformationsystempartitionsthematrixasfollowsQuestion:Arethesignals,Y1andY2,useful?Dr.Chak-TongChauFulbrightGuestLectureMaterials7UsefulnessofInformationNow,wehaveanotherinformationsystemthatwillgeneratethesesignals:{S1}{S4,S5,S6}Y1Y3Signal:Y1Y2Y3S1S2S3S4S5S6e1=10233455e2=5223445ThisnewinformationsystempartitionsthematrixasfollowsQuestion:Arethesignals,Y1,,Y2andY3useful?{S2,S3}Y2Dr.Chak-TongChauFulbrightGuestLectureMaterials8CanPrivateInformationtoAgentBenefitthePrincipal?Considerthefollowingpayoffstructure(knowntoall):S1S2S3S4ExpectedPayofftoPrincipalbeforePaymenttoAgentProb.0.250.250.250.25e1=000000e2=520,00020,00025,00030,00023,750e2=620,00030,00030,00035,00028,750Agent’sUtilityFunction:U=X½-e2100where:X=agent’scompensationse=theeffortlevelusedbytheagentIfthePrincipalcanobserveeffort,howwouldhepaytheagent?X½-62=100X=18,496Dr.Chak-TongChauFulbrightGuestLectureMaterials9CanPrivateInformationtoAgentBenefitthePrincipal?Now,ifthePrincipalcannotobserveeffort,howwouldhepaytheagent?Howaboutthiscompensationcontract(afixedsalaryof$18,496)toagent?Wouldthiswork?S1S2S3S4ExpectedUtilitytoAExpectedPayofftoPProb.0.250.250.250.25e1=018,49618,49618,49618,496e2=518,49618,49618,49618,496e3=618,49618,49618,49618,496136111100-18,4965,25410,254Thus,afixedsalarytosomeonewhomyoucannotobservewon’twork.A“moralhazard”problemwillcomeintoplay.Dr.Chak-TongChauFulbrightGuestLectureMaterials10CanPrivateInformationtoAgentBenefitthePrincipal?Nowthen,whataboutacontingentsalaryof$18,496toagent?WouldthisimprovethePrincipal’spayoff?S1S2S3S4ExpectedUtilitytoAExpectedPayofftoPProb.0.250.250.250.25e1=00000e2=518,49618,496018,496e3=618,49618,49618,49618,49607710009,87810,254Now,thecontingentsalarycontractwillimprovebyforcingtheAgenttogive(e3=6).Letusnowlookatthe“privateinformationtoagent”issue!Dr.Chak-TongChauFulbrightGuestLectureMaterials11CanPrivateInformationtoAgentBenefitthePrincipal?Thisprivateinformationsystem(onlyobservabletotheagent)generatesthesesignals:{S1,S2}{S3,S4}Y1Y2Wouldthecontingentsalaryof$18,496toagentstillwork?Signal:Y1Y2ExpectedUtilitytoAgentwithPrivateinfoExpectedPayofftoPrincipalwithPrivateinfoS1S2S3S4Prob.0.250.250.250.25e1=00000e2=518,49618,496018,496105.5(100)7,754(10,254)e3=618,49618,49618,49618,496Dr.Chak-TongChauFulbrightGuestLectureMaterials12CanPrivateInformationtoAgentBenefitthePrincipal?Now,thenewprivateinformationmakesiteasyfortheagenttocheat.So,whatshouldtheprincipaldo?Considerthisnewcontingentcontract(correspondingpayoffs):S1S2S3S4Prob.0.250.250.250.25e1=00000e2=514,722(20,000)14,722(20,000)0(25,000)20,544(30,000)e3=614,722(20,000)20,544(30,000)20,544(30,000)18,496(35,000)Wouldthenewplanwork?Letuscalculatetheagent’sutilityandtheprincipal’spayoff.Dr.Chak-TongChauFulbrightGuestLectureMaterials13S1S2S3S4ExpectedUtilitytoAExpectedPayofftoPProb.0.250.250.250.25e1=00000e2=514,722(20,000)14,722(20,000)0(25,000)20,544(30,000)e3=614,722(20,000)20,544(30,000)20,544(30,000)18,496(35,000)071.51000n/a10,173.5Summaryofresults:TypesofcontractPrincipal’sPayoffsAgent’sUtilityFixedsalary,effortobservable10,254100.0Fixedsalary,effortunobservable-18,496136.0Contingentsalary,noprivateinformation10,254100.0One-amount,withprivateinformation7,754105.5Multiple-amount,withprivateinformation10,173.5100.0Dr.Chak-TongChauFulbrightGuestLectureMaterials14Pre-effort“Public”Information?Thistime,itisdifferentinthattheinformationisavailableto
本文标题:InformationSystemsandPrincipalAgentModels
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