Behavioral Economics - Script Summary

7/29/2019 Behavioral Economics - Script Summary

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BehavioralEconomics

Lecture1IntroductionBehavioralEconomicsTheoreticalEconomics=bodyofnormativetheoriesaboutrationalbehaviorofanidealizedindividualRationality=maximization(orminimization)ofagoalfunctionundercertainrestrictions

Person/household:utilityfunction(e.g.happiness) Firm:profitorlossfunction

Socialtheoryofnormativeeconomics=GameTheoryandrationalitydefinedbyanyofseveralequilibrium(ausgleichende)conceptswhichhavetobeselected

Descriptivemodels+empiricalevidence:behaviorinconsistentwithcanonic(traditional)model=irrationalbehavior Decisionsdependonreferencepoint Systematicbiasorerrorduetoheuristics

Experimentaleconomics:observedbehaviordeviatesfrompredictionsincanonicmodel(notplayingNashequilibriumstrategies)BehavioralEconomics

Howhumandecisionsmaysystematicallydepartfromthosepredictedbystandardeconomictheory

Extensionstoclassicaltheoriesincludesocial,reciprocal,altruistic,environmental,cognitivefactors

Cross-disciplinary,blendingneoclassicaleconomics(rationalchoicetheory),socialsciences,puresciences(biology..)

Collectionofdescriptivetheoriesofhumanbehavior Closelyakintocognitivepsychology Evolutionarypsychologyfordecisionmaking,becausecognitiveabilitiesof

altruismandnotmodernmarketexchange

1. Coreassumptionsofeconomicshomooeconomicus(HO):sophisticatedHOcanbesocial,cansolveeverywell-definedproblemincludingthousandsofgoods

andtechnologies,fullyinformed,perfectstatistician2. Simplifyingassumptionshomooeconomicussimplicissimus(HOS)goal=maximizingwealth,orconsumptionofmarketgoods=egoistic,notinterestedinenvironment,canbeendowedwithpreferencesandinformation

3. Socialplanner:notmaximizenationalincome,takeintoaccountmoraldistributionalandenvironmentalissues

BoundedRationality:HOSwithplainrationalbehavior

Describinglessperfectindividuals,limitedabilitiestocompute,limitedmemories Userulesofthumb,simpleheuristicstoachievesolutionsclosetooptimal

solutions Often:dreadfulmistakes


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HigherRationality:HOwithhigherrationalityderivedfromsophisticatedmodelsandboundedrationality

Modesofbehaviorareintelligent Perfectlyadapted,rational,efficienttocopewithspecialenvironment Evolutionnotperfect:functionsthroughincrementalimprovements,alsomakes

mistakes Irrationalbehaviormayhavestrategicvaluechangeinenvironment,orpoint

ofview,maytransformsuboptimalmodeofbehaviortoahighlyefficientstrategy modesofbehaviorcircumventingdemands9ofinfinitelysophisticated

optimizationDutch-bookingbyintransitivepreferences,theoretical,notinreality

A>B,B>C,C>A A=B+e B=C+e 3efornothinginreturn,moneypump C=A+e

Lecture2EconomicsAxiomsandBehavior

EconomicAssumptionsandAxiomsProbability(Kolmogorov)Axioms

Probability(P)ofanevent(E)isnon-negative,realnumber Probabilityofsomeelementaryeventoccursis1,needtopreciselydefinewhole

samplespace Additivityofevents


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ConsequencesandDeterministicTransitivityCombiningeventprobabilitiesDeterministicTransitivity(strong): P(A)>P(B)&P(B)>P(C)P(A)>P(C)DeterministicTransitivity(weak): P(A)P(B)&P(B)P(C)P(A)P(C)

Experimentalintransitivityduetoassumingprobabilisticchoices:ProbabilisticTransitivity P(A>B)>12&P(B>C)>12P(A>C)>12BayesTheorem

Fordecisionmaking,incorporatenewinformationinspecificevent Conditionalprobabilities(likelihood)ofoneeventgivenanotherevent Priorprobabilitycanbetransferredintoposteriorprobabilitybyincorporating

furtherknowledge

P(A)isthepriorprobabilityofAmeaningitdoesnottakeintoaccountany

informationaboutB. P(A|B)istheposteriorprobabilityofAgivenB. P(B|A)istheconditionalprobabilityofBgivenA. P(B)=P(B|A)P(A)+P(B|A)P(A)isthemarginalprobabilityofB,actingasa

normalizingconstant.Example:BaseRateNeglectcitywith100terrorist,1.000.000non-terroristsImaginethatall1,000,100peoplepassinfrontofthecamera.About99ofthe100terroristswill

triggeraringandsowillabout10,000ofthemillionofnon-terrorists.Therefore10,099peoplewillberungat,andonly99ofthemareterrorists.So,theprobabilitythatapersonwhotriggersthealarmisactuallyaterroristis99in10,099.P(terrorist)=0.0001P(alarm|terrorist)=0.99P(alarm)=0.010098 [P(alarm|terrorist)P(terrorist)+P(alarm|non-terrorist)P(non-terrorist)=0.99x0.0001+0.01x0.9999]P(terrorist|alarm)=(0.99x0.0001)/0.010098=0.0098039Theprobabilitythatwhenthealarmistriggeredthepersonisaterroristis0.98%.In99.02%ofthecasesthepersonisnotaterrorist( falsepositive).

Whatistheprobabilityofthealarmnotbeingtriggered,butthepersonpassingbeingaterrorist(falsenegative)?PreferenceofChoice

Preferences=fundamentalsofdecisions,describingourgoals Impossible:completeandconsistentsetofpreferences(not:irrational) Requirements:existenceandtransitivity Optimalx*fromasetofx,wherenothingisbetter Sometimesdifferentpreferencesdependingonpointoftime Makeassumptions:1.Specifyit,2.Testit,toexplainobservedbehavior Preferences=presentedbyutilityfunctionU(x)x1>x2ifU(x1)>U(x2)

o Cardinal(grundlegend)instrumento Ordinaldescription(Rangliste)ofsatisfactionorhappiness


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SubjectiveExpectedUtilityTheory(SEU)integratesthesubjectiveexpectation(probability)andtheindividualutilityintoavaluetodescribepreferencesortopredictchoiceschoseaction(alternative,option)withhighestSEU

Multi-AttributeUtility(MAU)integratesthedifferentfeaturesofanoption.Itrepresentstheoverallutilityofthisoption.ProbabilitiesofSEUreplacedwithweightsrepresentingindividual,situationalpreferences

DominanceRuleisastrongerassumptionthanMAU.Itpredictsthatalwaystheoptionischosenwhichisbetterononeattributeandatleastasgoodonallotherattributes.AxiomsofExpectedUtility

Comparability=twooptionscanbecompared Transitivity Independence=therelationbetweejn2optionsisindependentoftheexistenceof

furtheroptionsXY[X,p;Z][Y,p;Z] Continuity=mustalwaysbeapthatmiddleoptionisindifferenttobothother

optionsforallXYZexistsapthatY~[X,p;Z,1-p]

RevealedPreferences=directtestsofutilitymodelsofpreferences

http://de.wikipedia.org/wiki/Revealed_Preference Utilityfunctionrationalizestheobservedbehavior(pt,xt)fort=1,...,Tifu(xt)

u(x)forallxsuchthatpt*xtpt*x.(u(x)rationalizestheobservedbehaviorifitachievesitsmaximumvalueonthebudgetsetatthechosenbundles)

Utilitymaximizationxtisdirectlyrevealedpreferredtox(xtRDx)o xtRDximpliesu(xt)u(x)o Localnosatiation:pt*xt>pt*ximpliesu(xt)>u(t)o Pt*xtpt*xxtisstrictlydirectlyrevealedpreferredtoxwritextPDx

SequenceofrevealedpreferencesxtPDxj,xjPDxk,...xnPDxxtisrevealedpreferredtox(xtRx) R=transitiveclosuretotherelationPDxtRximpliesu(xt)u(x)

GeneralizedAxiomofRevealedPreferences(GARP)

Ifxtisrevealedpreferredtoxs,thenxscannotbestrictlydirectlyrevealedpreferredtoxt(thatisxtisneverstrictlyinthebudgetsetwhenxsischosen)

xtRxsimpliesnotxsPDxtxtRxsimpliesps*xsps*xt.(Wenn ,danngiltnicht ).

WeakAxiomofRevealedPreferences(WARP)

Ifxtisdirectlyrevealedpreferredtoxs,thenxscannotbedirectlyrevealedpreferredtoxt(Wenn ,danngiltnicht )


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ExamplesSocialExample:TheCommonsDilemma=herdsmandecisionaboutaddinganotheranimalwith2utilities

Positive:saleofadditionalanimal,utility=+1 Negative:overgrazing,butsharedbetweenallherdsman,utility=onlyafraction

of-1 Increasehisherdwithoutlimit-inaworldthatislimitedruin

LogicalExample:WasonSelectionTask=logicpuzzlewhichcardstoturntotesttruthofaspecificproposition

Demonstratingtheinconsistencyofapplyingthelogicalrulesbythepeoplewhentheproblemissetintwodifferentcontextsbutwithverysimilarconnectionbetweenthefacts

Ifacardshowsanevennumberononeface,thenitsoppositefaceshowsaprimarycolor

Choosecard8andbrowntotesttherule Aresponsewhichidentifiesacardwhichneednotbeinverted,oraresponsewhichfailstoidentifyacardwhichneedstobeinverted

arebothincorrect

BehavioralObservations(contradictingexpectedvalueorSEU)StPetersburgParadoxYouenteredinthePetersburgcasino.Yourentrancefeeis20dollarsineachgame.Inonegame,acoinisthrownrepetitivelyuntilitshowsnomorehead.Youwin2(^n)-20Dollars,ifntimesHeadappeared,thebankgetsineachgame20-2^ndollars.Youwillexperiencethatwiththisentrancefee,youareloosingmoney.Inreality,itisamathematicalfactthatyouareexpectedto

win:youwinwithprobability2^-ntheamountof2^nDollars.Summingoverallngivesaninfiniteexpectationforyourwin.Whateverentrancefeeyouwouldpay,youwouldwin.Theparadoxisthatthisdisagreeswithyourexperiencetoloose.(http://www.mathematik.com/Petersburg/Petersburg.html)

Gamewithcoins,entrancefee,winning2^(k-1)dollarsifthecoinistossedktimesuntilfirsttailappears

Expectedpayoutvalueis ,infiniteamountofmoney Rarelywinmuchbutwhenyouwinalotinthelongrunthanrepayhowever

muchmoneytheyhavealreadypaidtoplay

Accordingtotheusualtreatmentofdecidingwhenitisadvantageousandthereforerationaltoplay,youshouldthereforeplaythegameatanypriceifofferedtheopportunity,butwronginreality

ViolationsofIndependence

Decisionpeoplemakedependingonsetofchoicespeoplehave Alsodependoncommonconsequencesofthechoices

EllsbergParadox

Urncontaining30redballsandthesum60ofblackandyellowballs Choice1:GambleA($100drawredball)andGambleB($100drawblackball) Choice2:GambleC($100drawredoryellow)andGambleD($100drawblackor

yellow)http://de.wikipedia.org/wiki/Ellsberg-Paradoxon Theory:Ifdrawingaredballismorelikelythandrawingablackball,then


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drawingaredoryellowballisalsomorelikelythandrawingablackoryellowball(preferGambleAtoGambleB,itfollowspreferringGambleCtoGambleD

Survey:violationoftheaxiomsofexpectedutility,mostpeoplestrictlypreferAtob,andDtoC

AllaisParadox

Reality:mostpeoplechose1Aand2B Theory:peopleshouldchose1Aand2Aor1Band2B Difficultieswithexpectedutilitytheoryalternatives

o Prospecttheoryo Rank-dependentexpectedutilityo Framingtheory(Identicalitemswillresultindifferentchoicesif

presentedtoagentsdifferently(i.e.asurgerywitha70%survivalratevs.a30%chanceofdeath))

Independenceaxiomofexpectedutilitymaybenotnecessary, Independenceaxiom:2identicaloutcomeswithinagambleshouldbetreatedas

irrelevanttotheanalysisofthegambleasawhole Butinthisgame:complementarities(choiceinonepartofagamblemaydepend

onthepossibleoutcomeintheotherpartofthegamble)disappointmentwhengettingnothinginGamble1B

Wedon'tactirrationallywhenchoosing1Aand2B,ratherexpectedutilitytheoryisnotrobustenoughtocapturesuch"boundedrationality"choicesthatinthiscasearisebecauseofcomplementarities

PapervonFlo:ProspectTheoryReasonBasedDM

Explainobservedviolationsbyextremenessaversionandtradeoffcontrast Describecompromiseandattractioneffects(attractivenessofanoptionenhances

ifitisanintermediateoptioninthechoicesetandisdiminishedifitisan

extremeoption) Oftenthecompositionofthealternativesmatters


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PreferenceReversals

CertaintyEquivalent(CE)leadstootherresultsthanchoicebetweenprobableoutcomes(AllaisParadox)

Viloationstoutilitytheoryalsobypresentationformatandformoftask WillingnesstoPay(WTP)contradictsWillingnesstoAccept(WTA)

o Willingnesstoaccept(WTA)istheamountthatpersoniswillingtoaccepttoabandonagoodortoputupwithsomethingnegative,suchaspollution

o Willingnesstopay(WTP)isthemaximumamountapersonwouldbewillingtopay,sacrificeorexchangeinordertoreceiveagoodortoavoidsomethingundesired,suchaspollution

Framing(Tversky,Thaler)AlsFraming-Effekt(deutschetwa:Einrahmungseffekt)wirddasPhnomenbezeichnet,dassunterschiedlicheFormulierungeneinerBotschaftbeigleichemInhaltdasVerhaltendesEmpfngersunterschiedlichbeeinflussen.BeiManahmenzurGesundheitsvorsorgewirdoftaufdieschdlichenFolgenetwavonRauchen,ungeschtztemSex,bergewichtusw.hingewiesen(vgl.Furchtappell).IndiesemFallsprichtmanvonVerlust-Framing(engl.lossframe).MehrErfolghabenjedochBotschaften,dieineinenGewinnrahmeneingebettetsind(engl.gainframe),alsodiepositivenFolgendergewnschtenVerhaltensnderunghervorheben.Willmanjedocherreichen,dassbereitsvorhandeneKrankheitenoderRisiken(Raucher,bergewichtige)mehrbeachtetwerden,sindBotschaftenimVerlust-Rahmeneffizienter.AuchbeiBefragungen,etwaanhandvonFragebgen,kanndieserEffektauftreten.DeshalbsolltederFormulierungeinerFragebesondereBeachtunggeschenktwerden,umdieErgebnissederBefragungnichtzuverzerren.Eswurdefestgestellt,dassbeiBefragungenwesentlichrisikoreicherentschiedenwurde,wennnurvonVerlustendieRedewar.WurdedagegenvonGewinnengesprochen,entschiedensichmehrBefragtefreinerisikormereLsung.

Example:2Programsreducingnumberofpeoplekilledintrafficaccident(from600) ProgramA:Reductionto570,costs$12Mio ProgramB:Reductionto500,costs$55Mio

Differentresponseswhengivingalternatives,orchangepeoplekilledinpeoplesaved$-versusp-betsExperimentsondecisionsunderrisk:Whichlotteryispreferable,HorL?H:8/9chanceofwinning$4,otherwise0.L:1/9chanceofwinning$40,otherwise0.MostsubjectspreferHtoL(71%).Askedwhattheywouldpayforparticipatinginoneofthegambles(WTP),mostsubjectsattachedahigherpricetoL(67%).

Priceofgamblesaremainlydeterminedbypayoffs($-bet) Choicebetweengamblesaremanlydeterminedbyprobabilitiesofwinning

(p-bet)

Payoffsareweighedmoreheavilyinpricesthaninchoice(scalecompatibility)

Lecture3BoundedRationalityandHeuristics

BoundedRationalitywithSatisficing

Boundedrationality=explainingbehavioraldeviationsfromthenorm Conceptofsatisficingdecisions:decisionshavetobesatisfyingandsufficient MostpowerfulprincipleofBR:imitationofsuccessfulbehavior


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GeneralProblemSolver(computerprogramtobuilduniversalsolvermachine) Solvinganyformalizedsymbolicproblem Separationbetweenitsknowledgeofproblemsandstrategytosolveproblem Cognitiveprocessesassolvingprocesses Generatingheuristicsbymeans-endsanalysis(Zweckmittelanalyse) SolvingproblemsliketheTowersofHanoi(sufficientlyformalized) Performedpoorlyinanyreal-worldproblems

BoundedRationalityandProblemSolving

Thetwocentralproblemsofdecision-makingare: Limitedinformation Limitedresources(time,informationprocessingability)

Consequences: Maximizationisusuallyimpossible!Alternatives? Optimallearningisusuallyimpossible!Alternatives? Alternativesimplybiases,orcleverness

CostBenefitTrade-Off=economicprincipledescribingusageofinformationWeighingadvantages(profits)ofmoreinformationagainstcostsofdevelopingsensesandintellectualcapacity(e.g.inherithouse,collectinginformationonthequestionwhethertolivethere,sellit,lentit,leaveit)

SatisficingConcept

Satisficing=contrarytomaximizing

Limitedinfoprocessingabilities

preventiondeterminationofmaxima(prefersmalllossestoinfinitesearch) Goal:reachingasufficientlevelofutility,profit=aspirationlevel


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Aspirationlevelsareoftenreadjustedaccordingtotheexperienceswhiletryingtoreachthem

Decidewhethertoworkfurtheronacertainproblem,giveup,orregardthecurrentsolutionassatisfactory

Satisfactory=dependingonenvironmentandknowledgeaboutvaluefunction Unknownprofitfunction,experiencemayguesshowflatthemaximumis,

whetherismuchtogaino HuntersProblem:Howgoodtoshoot?o FarmersProblem:Howmuchseed?o MonopolistsProblem:Whichprice?

Companiesuseseveralaspirations,correlated:profit,marketshare,shareprice,creditratingratinganddecisionsbasedonimportance,changes,dependence,partialrealizations

Goaldiversityexistsforindividuals,teams,governments

Example:10-weekjobsearchYouhavelostyourjob.In10weeksfromnowonyouhavenojobandnopayment(simplified),exceptyoufindanewjob.Everyweekyougetanewjobofferandtilltheendoftheweekyouhavetodecidewhethertoacceptit.Youareonlyinterestedinmoney,youareriskneutral,andyouknowthatthehighestofferofaweekisuniformlydistributedontheinterval[10,20].Inthelastweekyouwillacceptanyoffer.

Othervariantsoftheproblem:

Noobvioustimehorizoninfinite?,setatimehorizon(aspirationlevel)? Noknowledgeaboutdistributionofjoboffers(e.g.SecretaryProblemtofind

optimalstoppingsolutions) Searchcosts,infoquality,evaluationofjoboffers


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HeuristicsandBiases Findingviolationsofutilitytheorydeterminingexplanatoryconcepts

describingsystematicbiases Trialanderrormethodstoapproximateasolution Methodtodirectattentionfruitfullyinlearning,decision-making(rules,

suggestions,guides,techniques) Basedonexperienceandcommonsense,improveitsownperformance Ruleofthumb,helpbutnotguaranteedsolution

ExplanatoryConcepts

Representativeness:WhenpeopleareaskedtoratetheprobabilityofAbelongingtoaclassB,theyoftenrefertotheprototypeoftheclass.Standardprobabilisticpointofview,thisisfalse:conjunctionfallacy(occurswhenitisassumedthatspecificconditionsaremoreprobablethanasinglegeneraone),neglectingpriorprobabilities,insensitivitytosamplesize,misconceptionof

chance(gamblersfallacy),insensitivitytopredictability,illusionofvalidity(confidencewhenredundantdataalthoughredundancydecreasesaccuracy),misconceptionofregression

Availability:Inmanysituationspeoplehavetoratethefrequencyofaclassortheprobabilityofanevent.Hereitisoftenrelieduponinstancesoroccurrences,whichcanbeeasilybroadtomind.Instancesoflargeclassesarerecalledbetterandfasterthaninstancesoflessfrequentclasses.Oneinterestingcorollaryfindingtothisheuristicisthatpeopleaskedtoimagineanoutcometendtoimmediatelyviewitasmorelikelythanpeoplethatwerenotaskedtoimaginethespecificoutcomebiases:duetoretrievabilityofinstances(e.g.morefamousmen,falseratethatmoremennameswereinthelist),duetoeffectivenessofasearchset(letterrfirstorthird),biasofimaginability(easilyimagineddisastersnotreflectlikelihood),illusorycorrelation(of2events)

AnchoringandAdjustment:Whenmakingestimations,peopleoftenstartfromaninitialvaluetoderivetheanswer,therebythementalstartingpointoftendeterminestheoutcomeoftheprocess.Thiscanbethecase,eveniftheinitialstartingpointisinnowayconnectedtothetask/outcome.InsufficientAdjustment,overestimateprobabilityofconjunctiveevents,underestimateprob.Offailureincomplexsystems

SomeBiases

Overconfidence(optimism):peopleseemtosystematicallyoverestimatetheirabilitieswhenconfrontedwithgeneralknowledgequestionandaskedfortheirjudgmentconfidence.(cardrivers,chanceofsurviving,winnerscurse=beoptimistic,gotlicense,makelosses=thewinningbidderisoverpaying)illusionofvalidityinconsistencyandextremetypersistalthoughdifferentexperiences(lackofsearchforanduseofdisconfirmingevidence,lackofawarenessofenvironmentaleffectsonoutcomes,useofunaidedmemoryforcoding,storing,retrievinginformation)ContextDependency:evaluationofobjectsnaturallytakesplacerelativetocomparableobjectsandabsolutejudgmentsaredifficultorcanstronglybeinfluencedbyits

environment(i.e.,framing,decisionsetdependency,informationsampling)SunkCosts:pastexpenditures(investment,up-frontpayment,etc.),whicharenot


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recoverable.Economictheory(aswellasconventionalwisdom)tellsusthatsunkcostsshouldnotberelevantfordecisions.Cannotquitbecausefeelingstrongregret(highexpendituresfornothing).Higherrationality:so.doesnotwanttodestroyhisreputationasasuccessfulbusinessman,thenhisdecisiontostayinthebusinessmayhaveanadditionalvalueandneednot

beirrational,ourtendencytohonorsunkcostsbeneficialinsomecases(instrumentofpre-commitment)Sunkcostsandquasi-rents:Honoringsunkcostsmayhelptopreventexpropriation(Endeignung)evenwithouthightransactioncosts.LimitedDepthofReasoning:peopleinprincipleplanonlywithlimitedforesight(e.g.gameofchess).Itisimportanttoguesswhatothersdo,butiftheydothesame(guesswhatwedo)wefindourselvesininfiniteregressatypicalprobleminGameTheory

SimpleHeuristicsthatMakeUsSmart

HeuristicsfortheEvaluationofAlternatives/BinaryChoiceRecognitionHeuristic:existenceversusnon-existenceofknowledgecanbeinformationitself(e.g.whichcityhasthelargerpopulation?SanDiegoorSanAntonio)Takethebest(TTB):Inordertodecideforoneoftwoalternatives:

1. Lookforrelevantattributesofthealternatives2. Ranktheattributesaccordingtotheirimportance3. Comparethealternativeswithrespecttothemostimportantattribute4. Ifonealternativeisbetterwithrespecttothisattribute,decideforit5. Otherwisecomparethealternativeswithrespecttothenextmostimportant

attributeandasin4.

Minimalistic:step2=randomorder,orfirstcheckdimensionwhichdiscriminatedinthepreviouschoiceConcern:learningofcuevalidations,decisionwhichkindofheuristicinanenvironmentDecisionsunderUncertainty:AlternativetoUtilityModels?

ThePriorityheuristic:approachforintegratingvaluesandprobabilitiesingambles Fundamentaldiscussionsaboutmakingchoiceswithouttrade-offs Incorporatessmallsetifassumptions,enablingpredictionofbehaviorinmost

gambles Consistingof3rules

(a)PriorityRule:Gothroughreasonsintheorder:minimumgain,probabilityofminimumgain,maximumgain,probabilityofmaximumgain(b)StoppingRule:Stopexaminationifthegainsdifferby1/10(ormore)ofthemaximumgain;otherwise,stopexaminationifprobabilitiesdifferby1/10(ormore)oftheprobabilityscale.(c)DecisionRule:Choosethegamblewiththemoreattractivegain(probability)

FurtherHeuristicsandBiasesofThinkingTheGazeHeuristic:HowtoCatchaBall?

Difficulttocomputetrajectory(Flugbahn)ofaballbecauseofdistance,velocity,projectionangle,speed,directionofwind


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Gazeheuristic:ballhighupinair,fixgazeonball,startrunning,adjustspeedsothatangleofgazeremainsconstant

Nocalculationwheretheballwillland,heuristicleadstolandingpointCognitiveBiases

=DistortioninthewayhumansperceiverealityDecision-MakingandBehavioralBiases

Bandwagoneffectthetendencytodo(orbelieve)thingsbecausemanyotherpeopledo(orbelieve)thesame

Choice-supportivebiasthetendencytorememberone'schoicesasbetterthantheyactuallywere

Mereexposureeffectthetendencyforpeopletoexpressunduelikingforthingsmerelybecausetheyarefamiliarwiththem

BiasesinProbabilityandBelief Ambiguityeffecttheavoidanceofoptionsforwhichmissinginformation

makestheprobabilityseem"unknown" Optimismbiasthesystematictendencytobeover-optimisticaboutthe

outcomeofplannedactions Hawthorneeffectreferstoaphenomenonwhichisthoughttooccurwhen

peopleobservedduringaresearchstudytemporarilychangetheirbehaviororperformance

SocialBiases Haloeffectthetendencyforaperson'spositiveornegativetraitsto"spillover"

fromoneareaoftheirpersonalitytoanotherinothers'perceptionsofthem Herdinstinctcommontendencytoadoptopinionsandfollowthebehaviorsof

themajoritytofeelsaferandtoavoidconflict Projectionbiasthetendencytounconsciouslyassumethatotherssharethe

sameorsimilarthoughts,beliefs,values,orpositions Self-fulfillingprophecythetendencytoengageinbehaviorsthatelicitresults

whichwill(consciouslyornot)confirmourbeliefsMemoryBiasesandErrors

Beneffectance:perceivingoneselfasresponsiblefordesirableoutcomesbutnotresponsibleforundesirableones

Hindsightbias:filteringmemoryofpasteventsthroughpresentknowledge,sothatthoseeventslookmorepredictablethantheyactuallywere;alsoknownasthe'I-knew-it-all-alongeffect'

Selectivememory

Lecture4GameTheoryandExperimentalEconomics

GameTheoryandEquilibriaGameTheory:mathematicallycapturebehaviorinstrategicsituations(successinmakingchoicesdependsonchoicesofothers)

NormalformgamesOR(versus)Extensiveformgames Cooperativeversusnon-cooperativetheory Staticversusdynamictheory Gameswithcompleteversusincompleteinformation

Equilibrium:setsofstrategiesinwhichindividualsareunlikelytochangetheirbehavior


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EquilibriumConcepts(suchasNashEquilibrium):makepredictionsofoptimalbehaviorParlorGames:representationofsocialproblemsNormalFormGames

Representingasocialproblem,describetwoplayers,eachhavingthesametwostrategiesofwhichtheyhavetochooseone

Smallnumberofdecisionmakers(notone,notmany) Utility(profit,costs)ofadecisionmakerdependsnotonlyonownactionsbut

alsoontheactionsofothers Everyplayerihasa(finiteorinfinite)setSiofstrategies(=completelydescribed

planofbehavior) Allplayerschoosestrategiesatthesametime

2x2normalformgameswithpurestrategies

PrisonersDilemma


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Rationality:goal=utilitymaximizationSocialconcept:Ifastrategysikofplayeriimpliesastrictlylowerutilityunderallstrategycombinationsofotherplayersthansij,thensikiscalledastrictlydominatedstrategy.sikiscalledweaklydominatedifitimpliesanequalorstrictlylowerutilitythansij.

Noplayerchoosesastrictlydominatedstrategy,theplayerchoosesthedominantstrategy(sij)PD:bothplayerschoosedefect((4,0)istschlechterals(5,2))

Player2:strictlydominantstrategyDPlayer1:strategyisNOTstrictlydominatedPlayer1:eliminatestrategyCChooseD(Cisstrictlydominatedafterthiselimination)Successiveeliminationofstrictlydominatedstrategies

NOstrictlydominatedstrategiesSuccessiveeliminationmaycauseproblemswithdifferentresultsAnothersolutionconceptBestReply(RationalExpectationsaboutstrategiesofotherplayers)

Arrowdiagram:ifplayer1playsDthenplayer2s

bestreplyisDWeimmediatelyseethat(C,C)and(D,D)areNashequilibria.Cooperationgame

Example:thebestreplyofplayer1toCofplayer2isC

NashEquilibrium(NEinpurestrategies):pairofstrategies,whicharebestrepliestooneanother

TofindNE:checkallstrategycombination Ina2x2game:usearrowdiagram

BattleofSexesCouplewithdifferentpreferencesbutdominatingdesiretobetogetherCoordinationinterestswithdifferentandcommoninterests

O=OperaF=Football


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GameofChicken(Hawk-Dove-Game)Carsoncollisioncourse,whodeviatesloosesSymmetric(BattleofSexes)vsasymmetric(Chickengame)consequencesforout-of-equilibriumbehavior(fightfordominance)

P=peaceful(deviate)A=aggressive(neverdeviate)

MatchingPenniesPlayer1choosesheadortail,player2guesses,if2isrighthereceivesapennyfrom1andviceversaNONashequilibriuminpurestrategies(newproblemH=headT=tail

2x2normalformgameswithmixedstrategiesMixedstrategy:thepurestrategieswillbechosenwithprobabilityp(player1).

p=1/2,q=1/2


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Counterintuitiveattributesofsuchmixedstrategyequilibria:

Aplayersrewarddoesnotdependonhisownstrategychoice. Aplayersequilibriumstrategydoesnotdependonhisownvalues

ProblemswithNashequilibriainmixedstrategies: Beingindifferent,whyshouldplayerschoosetheirequilibriumstrategies? Howcanweimaginetherealizationofamixedstrategy?

Generalizations

1. Finitenumberofplayersandfiniteumberifstrategies:gamehasatleastoneequilibriuminmixedstrategies

2. Finitenumberofplayersandinfinitenumberofstrategies:a. Cournotoligopolywithhomogenousgoods:nsuppliers,xiquantitiesofa

homogenousgood,pmarketpriceprofitG=xi(p-ci),NE:allxibestrepliestooneanotherminimaxfunction

b. Cournotoligopolywithinhomogeneousgoodsc. Bertrandoligopolywithinhomogeneousgoods

CounterEquilibriumarguments

BertrandDuopolywithhomogeneousgoodsanddifferentconstantmarginalcostsnobestreply

JewishPoker:everyonethinksofanumber,thehighernumberwinsProblemswithNashequilibriumasasolutionconceptSometimesnon-existenceofequilibria(notsevere)Coordinationofchoices

- Ifthereisoneequilibriuminpurestrategies(notsevere)- Ifthereismorethanoneequilibrium(equilibriumselection)- Inmixedstrategyequilibria

ExtensiveFormGames

Gametreeindifferentvariations,orderofchoices(moves)DetermineinitialnodereachingeveryothernodeonauniquepathStrategy:completeplanofbehavior=determinedecisionineverynode(moves)


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ArgentinaS1:oinnodeA;S2:finnodeAGreatBritain:S1:kinnodeGB,Subgame:isthatpartofthegametree,whichstartsfromacertainnodewhichisnotaterminalnode.LetI-'beasubgameofI-.TheneverystrategysofI-inducesastrategys'ofI-'accordingtotherulethatallmovesofswhichdefinebehaviorinanodeofI-'arealsomovesofs.

Nashequilibrium=subgameperfect,iftheequilibriumstrategiesinduceaNashequilibriumoneverysubgameMethod:BackwardInduction(DemnachwirdimLaufedesVerfahrensrckwrts,alsoinRichtungdeserstenEntscheidungsknotens,derjenigePfadhervorgehoben,welcher

frdenAkteurdiemaximaleAuszahlunggenerierensoll.DadieserPfadeinNash-GleichgewichtinjedemTeilspielinduziert,istdasresultierendeGleichgewichtauchteilspielperfekt)


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DieRckwrtsinduktionsschritteinExtensivform:

Schaubild1:DasletzteTeilspiel(GRN)wirdbetrachtet:

Schaubild2:DaszweiteTeilspielwurdevereinfacht(ROTmitrationalerAuszahlungausGRN):

Schaubild3:DaskomplettinduzierteSpiel(BLAUmitrationalenAuszahlungenausROTundGRN):

http://de.wikipedia.org/wiki/R%C3%BCckw%C3%A4rtsinduktionTheUltimatumGame:Proposersplitsamountofmoney,respondercanacceptorreject

TheGameofTrust TheCentipedeGame

Generalization1:infinitelymanystrategies(InvestmentGame,GiftExchangeGame)Generalization2:infinitelymanyperiodsGeneralization3:incompleteinformation(esp.signalinggames)


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ExperimentalResultsGenerally,thereismorecooperativebehaviorinTrust,Investment,andCentipedeGamesthanyouwouldexpectunderegoisticpreferences.2x2NormalFormGames

PrisonersDilemmacooperationduetodifferentmonetarypayoffsandpreplaycommunication(noeffectintheory),nocooperationwhenrematching(repeatedgameswithrandomstrangers)Matchinggamewith2equilibria(ResultsofMatchingGameswithCommonInterest),selectionmaybefocalorphysicalprominent,differencebetweenmatchingandpicking(salience)Gameswithdifferentinterests:BOScommoncoordinationfailure(likepredictedinmixednash

equilibrium),solution:one-waycommunicationbutnottwo-waycommunication,effectoftiming(lowermismatchwhenknowingthatrowplayedfirstbutnotknowingwhatrowdid)ChickenGame:AggressiveStrategychosenmoreoftenthanpeacefulstrategybutIthinknotsignificantly(39:33)CournotExperiments

Furtherresultsofameta-studybyEngel(2007)emphasizethattherearemanyinteractioneffects,i.e.oftenitisnotpossibletolinearlydisentangletheeffectsofdifferentvariables:

competitionwith(in-)homogenousgoodsand(a-)symmetricplayersyieldlowerpricesandprofits(-)orhigherpricesandprofits(+)thantheNashequilibrium,accordingto:

competitionwith(in-)homogenousgoodsandplayerswhoarere-matchedeveryround(partners)orgetnewco-playersineveryround(strangers)yieldlowerprices

andprofits(-)orhigherpricesandprofits(+)thantheNashequilibrium,accordingto:

Furtherinteractioneffects:2competitors=partnerscolludemoresuccessfullythanstrangers;morethan2:strangerscolludemorethanpartners.Thisresultchangesiffeedbackinformation(aboutbehaviorinpreviousrounds)isgivenalsoforstrangers.UltimatumExperiment

Proposeroffers30to50percent,offersbelow20percentarerejectedhalfofthetimeoftenoptimum:give50%


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Vendettas(Rachefeldzug)

=lesscooperationthantheorypredicts 2playerswithcertainprobabilitytowinaprize,probabilitytostealfromone

anotherwithanefficiencylosssumofprobabilitiesdecreases SubgameperfectNashequilibrium:nostealing Experiment:60-80%ofthegamesendedwithprobabilitiessmallerthan10%

Lecture5TemporalEffectsandSelf-Control

DiscountinganTemporalDistortionIntertemporalConsumption

Jahr1:1000Jahr2:1000*(1+r);r=interestrateJahr1:1000/(1+r)Jahr2:1000;r=discountrate(presentvalueof1000tomorrow)1/(1+r)=discountfactordr=(1-d)/dIfdiscountfactorishigh(closetoone,ordiscountrateisverylow)whathappensinthefuturemattersagreatdeal,youdonotdiscountfutureverymuch=patience.Ifdiscountfactorislow(closetozero,ordiscountrateisveryhigh)whathappensinthefuturematterslittle,youdiscountyourfutureheavily=impatience.

Exponentialdiscounting Hyperbolicdiscounting

AgentsbehavioristimeconsistentE.g.Youpreferatoballtimesorbtoaalltimesoryouareindifferent

asaparametergoverningthedegreeofdiscountingAgentsbehavioristimeinconsistentverycommon

ChoicebetweensmallerearlierawardandlaterbiggerawardimpulsivitySourcesofinformationaboutdiscountratesare:

Fieldstudies/observationsofrealdecisions(revealedpreference) Questionnairestudies(hypotheticaldecisions) Experiments(realdecisions)

Often:Preferenceforpresentpleasures(lowdiscountfacto,highdiscountrate)Seefuturepleasuresonadiminishedscale


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ResearchingDiscountRates

Implicitdiscountratesarelarger(futurematterslittle)forsmallthanforlargesumsofmoney.(MagnitudeEffect)explainedbyperceptionsofabsoluteamountsandmentalaccounting

Discountratesarelargerforgainsthanforlossesofequalmagnitude.(SignEffect)explainedbydebtorlossaversion

Discountratesdeclinewithtimehorizon.(Non-ExponentialorQuasi-HyperbolicDiscounting)dynamicinconsistenciesinchoicesovertime


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Hyperbolicdiscounting:profitabilityofinvestmentseemstobedifferentdependingonthetimewhenyouevaluateiti.ediscountingwith1/kinperiodkExamples

Weaknessofwill Myopia Timeinconsistencies

PlanningandSelf-Control=self-controlmechanismtosticktopreviouslyset(planned)goalsovertimeObservingChoicesovertime

1.EndowmentEffectWillingnesstopay(WTP)vs.Willingnesstoaccept(WTA)

Economictheory:WTP=WTA

Experiments:WTP


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Reasonsforarationalendowmenteffect Ownerspenttimeormoneyforthegood(honoringsunkcosts) Asymmetricinformationriskaversionofferless(lowerWTP) Differentqualitiesandasymmetricinformation:betterqualityissoldlessoften

ornotatall

2.StatusQuoBias=Donothingormaintainyourcurrentorpreviousposition

Example:Notquittingonesjob,notchangingonesfieldofstudies,ornotmakingadivorce,notdroppingoutofbusiness(maybestrategic)

Reason(mayberational):incompleteinformationaboutalternativesbutcompleteinformationaboutstatusquo,hightransactioncosts

3.PreferenceoverProfiles

Notonlyprefernowoverlaterbutalsoutilitystreamsovertime

Preferred:utilityspreadandincreasingutilityprofiles(e.g.cleaningnowandgoingtothemovieslaterisbetter)negativetimepreferences

Peakendrulespecifiesordersofeventshighestutilitytooccurlast

MeansofSelf-control(3strategies)

1. Possiblephysicalormentalrestrictionofthedecisionspace:actsofpre-commitmentorpersonalrules(e.gbudgeting)

2. Manipulationofenvironmentalstructurea. Addingsituationalcomponentswhichsupportdesiredactivityb. Removingdeviationevokingstimulic. Perceptionofeventscostsandbenefits(elaboration,grouping,temporal

factors)3. Changethecontingency(Zufall)structure:sidebetswithpenaltiesandrewards

PrecommitmentIndividualhaschoseninthepresenttodo(ornottodo)somethinginordertocontrolthewayinwhichitwillrespondtoparticularsituationsinthefuture.Socialsettings:Signalingprecommitmentiscrucial,e.gcuttingcreditcard

MentalaccountingStructuringcreditsanddebits,distinguishingdifferenteventcategoriessourceofmoneyaffectshowitisspentMentalaccountsconstrainoptimization,restrictfungibility(bertragbarkeit)

Savingforahousewith2,5interestrateonbankaccountandatthesametimebuyingacarwithaloanat5%

Getmoneyforbirthdayanddon'tspenditforpayingelectricbillProcrastinationorchoosingnottochooseNaifs(hyperbolicdiscounters)notawareofanyself-controlproblems

Sophisticatedhyperbolicdiscouners:areawarebutoftenovercompensateorpreproperate(doingsthearlywhichwouldbebetterdoinglater)


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Lecture6IndividualDifferencesandEmotions

IndividualCharacterizations

Psychology:manyindividualdifferences Economy:focusonriskypreferences Learning=oneprocessleadingtoindividualpreferences,+corresponding

strategyselection=fundamentalcriterionforoptimaldecisionsBehaviorunderRiskandUncertainty(keyfeaturesofmost(complicated)decisions)AssumptionsofSEU(Subjectiveexpectedutility)

Risk=nottoknowtruestateoftheworld,butprobabilities Uncertainty=notknowtheprobabilitiessubjectiveprobabilities Maximizeexpectedutility

Composelotteries:allowingx,yalsotobelotteries=allowingtodealwithmorethantwostatesoftheworld

Neumann/Morgenstern/Savage-Axiomsfordecisionunderrisk:assumptionsof

behaviorwhichguaranteeexistenceofutilityfunctionusedmaximizeEURiskSeekingandLossAversionApersonisgiventhechoicebetweentwoscenarios,onewithaguaranteedpayoffandonewithout.Intheguaranteedscenario,thepersonreceives$50.Intheuncertainscenario,acoinisflippedtodecidewhetherthepersonreceives$100ornothing.Theexpectedpayoffforbothscenariosis$50,meaningthatanindividualwhowasinsensitivetoriskwouldnotcarewhethertheytooktheguaranteedpaymentorthegamble.However,individualsmayhavedifferentriskattitudes.Apersonissaidtobe:

risk-averse(orrisk-avoiding)-ifheorshewouldacceptacertainpayment(certaintyequivalent)oflessthan$50(forexample,$40),ratherthantakingthegambleandpossiblyreceivingnothing.

risk-neutral-ifheorsheisindifferentbetweenthebetandacertain$50payment. risk-loving(orrisk-seeking)-iftheguaranteedpaymentmustbemorethan$50(forexample,

$60)toinducehimorhertotaketheguaranteedoption,ratherthantakingthegambleandpossiblywinning$100.

Theaveragepayoffofthegamble,knownasitsexpectedvalue,is$50.Thedollaramountthatthe

individualwouldacceptinsteadofthebetiscalledthecertaintyequivalent,andthedifferencebetweentheexpectedvalueandthecertaintyequivalentiscalledtheriskpremium.Forrisk-averseindividuals,itbecomespositive,forrisk-neutralpersonsitiszero,andforrisk-lovingindividualstheirriskpremiumbecomesnegative.


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ThedifferencebetweentheutilityoftheexpectationvalueandexpectedutilitydependsonthecurvatureofU(x).(ErwarteterNutzenausSpielE(U)istgreralsNutzenE(EW)deseigenenErwartungswertdesSpielsE(W)zb50riskseeking)Wedonotwantthemeasuretodependonlineartransformationsofx(seeabove).

Arrow-Pratt-Measure(ofabsolute/relativerisk-aversion)Themoststraightforwardimplicationsofincreasingordecreasingabsoluteorrelativeriskaversion,andtheonesthatmotivateafocusontheseconcepts,occurinthecontextofformingaportfoliowithoneriskyassetandonerisk-freeasset.Ifthepersonexperiencesanincreaseinwealth,he/shewillchoosetoincrease(orkeepunchanged,ordecrease)thenumberofdollarsoftheriskyassetheldintheportfolioifabsoluteriskaversionisdecreasing(orconstant,orincreasing).Thuseconomistsavoidusingutilityfunctions,suchasthequadratic,whichexhibitincreasingabsoluteriskaversion,becausetheyhavean


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unrealisticbehavioralimplication.Similarly,ifthepersonexperiencesanincreaseinwealth,he/shewillchoosetoincrease(orkeepunchanged,ordecrease)thefractionoftheportfolioheldintheriskyassetifrelativeriskaversionisdecreasing(orconstant,orincreasing).

r(u)=independentofabsolutemagnitudeofutilityandunitofutilityr:locallydefined=measurelocalriskaversionThestrongertheconcave(convex)curvatureofU(x)thehigherisriskaversion(riskseeking)Utilityonitsownisnotabletocapturedifferencesingeneralriskaversion.

ProblemswithscaleMustpeopleberiskneutralwithrespecttosmallbets?(Rabin2000)

Whatwouldbetheconsequenceifsomeonealways,i.e.foreverywealthx,rejectsthefollowinglottery(L)againstthealternativewin/lose0Euro?L=win11withprobability0.5;loose10withprobability0.5.Therejectionofthelotteryimplies:0.5U(x10)+0.5U(x+11)


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ProspectTheory

Kahneman/Tverskydifferenceinchoicesunderuncertaintyavoidanceoflossesorseekingofrisk

ImportantElements:o Referencepointfromwhich

gainsandlossesaredetermined(makethebestoutofsituation,adapttocomfortableoruncomfortablesituations)

o Valuefunctionovergainsandlosses(S-shaped,risk-averseforgains,riskseekingforlosses,atRP:steeperforlossesthanfor

gains)o Transformationofobjectiveprobabilities(lowprobabilitiesareoverweighted(ziehenesmehrindieEntscheidungsfindungein),highpareunder-weighted)

Differentutilitycurvesforgains,losses,probabilities,varyingreferencepoints Alwaystransformsituationinprospecttheorylanguagedescribedecisions

andreferencepoint

EndowmentEffect

FramingshiftofreferencepointCase1:Scenariosdescribedthatlivescanbesavedriskaverse(gains)Case2:Scenariosdescribedthatlivesarelost riskseeking(losses)Advantages DisadvantagesProspectTheorycanexplainanumberofphenomena,oftencontradictingstandard

economictheory.

Thereissomearbitrarinessinexplainingthesituation,inparticularwithrespectto

thereferencepoint.Itistoosimple:realevaluationsare(sometimes)morecomplex.


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DecisionswithEmotionsDefiningEmotions

1. Emotionsarenecessarytoeducatestatesanddecisions;theyprovideuswithourgoalfunction.

2. Emotionshelptoselectandstoreimportantinformation.3. Emotionsprovideuswithtoolsofself-commitment,whichhelptocopewith

othersandwithourselves. Classifiedinacontinuumorasdistinct(basic)states

RobertPlutchiksclassificationin8primaryemotionsPrimaryemotionsblendtogethertoformfullspectrumofhumanemotionalexperience.

Relatingeachbehaviorwithsurvivalvalue,partofbiologicalheritage.Ekmanslist(1)anger(2)fear(3)sadness(4)happiness(5)disgust

(Experiments)

EmotionsandEvaluation(Lazarus) TaxonomyofCoreRelationalThemesforvariousemotions,helpdefinefunction

andelicitingconditions Offenseagainstmeandmineforanger Immediate,concrete,overwhelmingphysicaldangerforfear Irrevocablelossforsadness Takinginorbeingtoclosetoanindigestibleobjectfordisgust Reasonableprogresstowardrealizationofagoalforhappiness Example:marriagepartner,chosefood,crossingstreet

EmotionsandExperience

Emotionscarryexperienceswisdom Speciesandindividualexperiences,(e.gfoodtaste,landscapepreferences,fearof

certainanimals,prejudicecopingwithpeople) Prejudice:tooyoungandoldpartners,ugly=illnessadvantageous Betterlearningwheninformationaccompaniedbystrongemotionsselect

appropriatereactionincertainsituation(i.e.self-commitment,Herdplatte) Iftheothersteals,theangrypersonisworseoffthantherationalpersonbutthe

otherwontstealifyouareanangrytype.


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RegretTheory

Feelregretwhenyoumakedecisionandfindoutitwaswrongdecision. Takeanticipatedregretintoaccountwhentheydecidelossaverseness Powerfuldissuaderorcreatespecificmotivationtodoonethingtoavoid

somethingelse Modifiedutility=contextdependent

andavailablealternativescaninfluencethechoicebyanticipatedregret

LearningandAdaptionStrategySelectionandLearning

Learning=fundamentaldriverofoptimization Learningcurvesindifferentdomainsexpectsteepcurveatbeginning,

flatteningoutoverrepetitions Learningofstrategiesindifferentenvironmentsoptimizationstrategy

selection(adaptiontodifferentenvironmentaltaskcharacteristics) 2differentstrategiesrelyonlearningperformancesticktostrategyor

switchtotheotherone Example:TakeTheBest(TTB)vs.WeightedAdditive(WADD)=formoflinear

informationintegrationo TTB:inanon-compensatoryenvironmentfromprob.=0,5to0,7after

severaltrialblockso WADD:inacompensatoryenvironmentfromprob.0,5to0,75after

severaltrialblocks


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ImitationandAdaption

Copyingandimprovementofexistingstructuresdevelopmentofnewdesignforsolvingproblems

Catchinganaircraftwithtailhookandarrestingwires,plusradiocommunication,lightssignalsindifferentcolorsfromdifferentangles

Bionics(biology+electronics):applicationofmethodsandsystemsfoundinnaturetothestudyanddesignofengineeringsystemsandmoderntechnology

Imitationdesirableevolutionpressureforcesnaturalsystemstobecomeoptimizedandefficient

E.g.lotuseffect,sonar,radar,hullsofboatsfromdolphins,artificialneuralnetworks

Implementingfunctionfoundinnatureratherthanjustimitatingbiologicalstructureformofappliedcase-basedreasoning(natureasdatabaseofworkingsolutions)

Modelingtechnologybasedon3biologicallevelo Mimickingnaturalmethodsofmanufactureo Imitatingmechanismsfoundinnature(velcro)o Studyingorganizationalprinciplesfromsocialbehavioroforganisms,such

asflockingbehaviorofbirdsoremergentbehaviorofbeesandants E.g.Velcro,catseyereflectors,morphingaircraftwings,pineconeclothing,

architecturebasedonstructureofhumanbonesorplantsExamplesandboundedrationalityareconnectedontwolevels:

1. Natureinventedallthesecleverdesignswithoutanyplanning:trialanderror,i.e.variationbythemixingofgenesormutationandevaluationbydeathorsurvival.

2. Menimitatenature,eitherbyadoptingitssolutionsorbyadoptingitsmethods(geneticalgorithms,forexample).

Noteagainthatimitation(ofsuccessfulbehavior)isoneofthemostpowerfulprinciplesofboundedrationality.

Lecture7SocialBehavior

SocialMotives

Peopletakesocialconsequencesintoaccount Careaboutownwell-beingandalsoaboutthatofotherpersonsFairness

Concerningdivisionofresourcesallrecipientsreceivefairamount ProportionalDivision:Eachplayergetsatleasthis/hershare. ExactDivision:Everyplayerassumesthateveryonereceivedexactly(neither

morenorless)theirfairshare. EquitableDivision:Thereceivedproportion,bytheirownevaluation,isthesame

foreveryplayer. Envy-FreeDivision:Noonewantssomebodyelsessharemorethantheirown. EfficientDivision(Pareto-Optimal):Nootherallocationwouldmakesomeone

betteroffwithoutmakingsomeoneelseworseoff.


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TheContestedGarment:Twoholdagarment;oneclaimsitall,theotherclaimshalf.Thentheoneisawarded34,theother14.Theprincipleisclear.Thelesserclaimantconcedeshalfthegarmenttothegreaterone.Itisonlytheremaininghalfthatisatissue;thisremaininghalfisthereforedividedequally.Notethatthisisquitedifferentfromproportionaldivision

Spite:Phenomenonoccurringwhenaplayer'svalueofanallocationdecreaseswhenoneormoreotherplayers'valuationincreasesplayerwithspiteprefersallocationinwhichotherplayerreceiveslessthanmore.(30pfelvs2Bananen(toll))Avoidanceofinequality:specificformoffairness,differencesnegativeutilityforplayerAltruism

Explainingaltruisticbehavior:KinSelectionandMemes Example:beegivinglifewhenstinging,human:religion(common>individual)

DictatorGame(Dictatorendowedwithmoney,cangiveasmuchashelikestobeneficiary)1. PureAltruism(mostfrequentlyuseintheory):dictatorsutilityisinfluencedby

thebeneficiarysincomea. UDictator=fD(xDictator,xBeneficary),xi=incomeofi

2. BeckerianAltruism(Becker):dictatorsutilitydependsonthebeneficiarysutilityUndercompleteinformationitcanbesolvedtogetPurealtruism

a. UDictator=fD(xDictator,UBeneficary)b. UBeneficary=fB(xBeneficary,UDictator)

3. WarmGlow:actofgivingmakesthedictatorhappya. UDictator=f(xDictator)+g(YDB),b. Y(DB)=transferfromDictatortoBeneficiary,c. IfxBeneficiary=YDB,then(3)isaspecialcaseof(1).

4. ReciprocalAltruism:dictatorsaltruismdependsonthebeneficiarysaltruismtowardher

a. UDictator=f(xDictator,xBeneficary,aBD)b. aBDmeasuresthebeneficiarysaltruismtowardthedictator.

5. AltruismasInequityAversion:wherethedictatorsutilityisinfluencedbythedifferencebetweenhisownandthebeneficiarysincome(thesearespecialcasesofpurealtruism

o Standardgame:hardlyanydifferencesbetweenapproaches Restrictiontotransferhalftheendowment(hardlygivenmorethanhalf)dueto

altruismasinequityaversion Morecomplicatedsituationsmaybegovernedbyalternativeoradditionalsocial

motives,suchasconditionalcooperationorreciprocity

Cooperation ColemandescribesCalculativetrust.Valuetrust>valuemistrust


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ColemanHypothesis:rationalexpectationsabouttrustworthinessincreasingfrequencyoftrustwithaveragenetprofitabilityoftrust

Mostcases:reciprocity(wecooperatewhenothercooperate)Reciprocity

Respondingtopositive(negative)actionwithanotherpositive(negative)action Positivereciprocalactionsaltruisticactions Involvesimplicitexpectationoffuturepositiveactionsbybeneficiary Explainsmaintenanceofsocialnorms(maintainnorminabsenceofformal

sanctions)punishingaction(negativewordssocialostracism) Cheaterdetectionandpunishmentinfluencedbythecontextdefiningsocialnorm

CheaterDetectionWasonSelectiontask:Ifsomeonestaysovernightinthecabin,thenthatpersonmustbringalongabundleofwoodfromthevalley.

A. Cheatingversion:cabininthealps,rumorsthatnotallhikeswhostayovernightcarryownshareoffood89%selectedrightcardstosolvelogicpuzzleB. Nocheatingversion:hikersbringwoodormembersofalpineclub,samecards

only53werecorrect(alternativeversiondecreasecorrectness)IfcuedbytherulesofonepartyA(i.e.employees)ortheotherpartyB(i.e.employers)theresultscanchangeconsiderably.Ifanemployeeworksontheweekend,thenthatpersongetsadayoffduringtheweek.

Amainlyturnedthefollowingcards:workedontheweekendanddidnotgetadayoff

Bmainlytheothercards:didnotworkontheweekendanddidgetadayoffTitforTatStrategy(=Exampleforreciprocity,heuristic)

1. Unlessprovoked,theagentwillalwayscooperate.2. Ifprovoked,theagentwillretaliate.(Rchtsich)3. Theagentisquicktoforgive.4. Theagentmusthaveagoodchanceofcompetingagainsttheopponentmorethan

once.Despitethefactthatthetit-for-tatsneverwonamatchandthedefectorsneverlostamatch,thetit-for-tatsstillcameoutahead,becausethefinalscoreisnotdeterminedby

thewinnerofmatches,butthescorerofpoints.Thetit-for-tatgainedmorepointstyingwitheachotherthantheylosttothedefectors.Themoretit-for-tatsthereareinthegame,themoreadvantageitistobeone.Reciprocityandconditionalcooperationisastrategyagainstfreeriders,whencheaterscannotbepunishedotherwise.Butnotethatoftenalsothelevelofdefectorshastoreachaspecificleveltobeadvantageousforthereciprocalagent.Furthercriticismisthealternationproblemandfinitegames.Example:2malebaboon,onedistractingalphamale,theothercopulatewithfemalereversedrolesforpaybackConditionalCooperation

Peoplewouldliketocooperateifotherscooperate(providingapublicgood Notrelevantfordictatorgame(asymmetricpower)butforPublicGoodsand

Solidaritygame


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ConditionalCooperationwithPublicGoodsPotentialforreciprocalactionsbyplayersincreasestherateofcontributiontothepublicgood,providingevidencefortheimportanceofreciprocityinsocialsituationsPublicGoodGameasgeneralizationofPrisonersDilemma(>2player)

AllnparticipantsendowedwithincomeE InvestpartxiofEresultinginatotalinvestmentx Allparticipantget(with1/n


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Lecture8ExperimentalEconomics

ExperimentalDesign

Rapidgrowthoflaboratoryexperimentsconfidence Carefullycontrolledexperimentsdrawbetterinferencesthanavailablenon-

experimentaldata Questions:howandwhatdetailtoreportexperimentalprocedures,whatdata,

howtoaggregateforreportingpurposes,howtoanalyze Pitfalls:misinterpretthesignificanceandrobustnessofreportedresults Divergentpracticesamongexperimentaleconomistsaboutwhatunitofdatais

called"anexperiment."(amatterofterminology,sometimesmasksdifferencesinreportingpracticesambiguityaboutwhatisbeingreportedandpublished

StrictGuidelinesInducedvaluetheory:3necessaryexperimentalconditionstoinduceanagentscharacteristic.(Alwaysbesatisfiedtoensureeconomicallyvalidbehavior)

Monotonicity(Monotonie)-prefermorerewardtolessandnotbecomesatiated Salience(Hervorspringen)-rewardmustdependonactions Dominance(berlegenheit)-subjectsutilitycomespredominantlyfromthe

rewardmediumandotherinfluencesarenegligible +Procedureastransparentaspossible +Experimentreplicable

FactorialDesign

Differentinfluencesareseparatedintoseveralfactors,investigatedincombination

Usuallyfullfactorialdesignextensiveexperiments Alllevelsofeachfactorarecombinedwithalllevelsoftheotherfactors Example:3factors(2with3levels,1with2levels)3x3x2(18trials) Allpossibleinteractioneffectsarecaptured Keyparadigms:

o Independenttrialsasseparatesessionso Realismandcontrolledeconomicenvironmentso Parallelism(transferabilitytorealworlddecisions)o Understandresearchquestionsandpitfalls(instructions,payments,learning,setup,samplesize..)

Simplifications:crossoverdesign,dualtrial,fractionalfactorialdesign..VariablesofInterest

Dependent(focusvariables,hopetofindaneffect)andindependentvariables(varysystematically)

Decisionexperiments:Process(decisionprocessitself)andoutcomevariables(describeresultofprocess)investigatedincombinationtofosteratheory

E.g.TTB:predictionsaboutchoicebetween2alternativesandassumptionsabouttheprocessleadingtoresult Betweensubjectsdesign:effectondependentvariablesiscomparedfordifferentsubjects(oversubjects)


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Withinsubjectsdesign:effectofdifferentlevelsofvariablesforonesubjectAdvantage:additionalnoise(individualpreferences)doesnotinfluencetheeffectofdifferentmeasures

Withindesignismorepowerful,butpronetodemandeffects(esp.learning) Both:randomizationindirectcontroloveruncontrollablevariableslike

demographicsorlearning

ExperimentalStudies Experiment=goldenpathofscientificdiscovery Strongvariationsinwaysofcontrolledinvestigation,strongerrestrictionsin

experimentaleconomics Mainfocusonexperimentalgames,individualdifferencesorunderlyingcognitive

processes Laboratoryvs.fieldstudies

Methods1. Classroomexperiments:simplyruninlectures2. Laboratorysetting:standard,bestcontrolofvariousvariablesofinterest(ViaLab

atEUV)3. Fieldstudies:increaseecologicalvalidity

a. Reducedrandomizationinfavoroforiginalityofbehavior(subjectpool,infolevel,commodity,norms)innaturalenvironment

b. Artificial:decisionsituationsimulatedinthelaboratorywithspecificsubjectpool

c. Framed:specificcharacteristicsaretakenintothelaboratoryd. Natural:takeplaceweredecisionsareusuallymade,participantsnot

informedaboutmonitoringe. Quasineutral:describesituationsinnaturalenvironmentwhichare

slightlymanipulatedtotesteffectofspecificchange4. Meta-analysis:investigateresultsfromdifferentstudies

a. Aim:identifyunderlyingpatterns,relationofdifferentobservations(e.gthroughcommonmeasureofeffectsize)

b. Identifycharacteristicsexplainingdifferencesinresultsc. Oftenimportantcomponentsofasystematicreviewprocedure

Measurements

Weber-Law +otherhypothesizedinterindividualregularities=resultofearlyresearchofuniversalcharacteristicsofperception

Otherapproaches:interestedininterindividualdifferences(questionnairessurveys,testbatteries)

Economics:regularitiesandvariationsinregardtobehavioralbiases,motives,attitudesimprovemodelsofsocialbehavior(e.g.includedifferenttypesofpeoplewithsocialmotives)

Strategymethod:evaluatingfulldecisionspaceofapersonRiskMeasure

Bestresearchedindividualcharacteristic:riskpreferences Attitudestowardsriskscanbeinferredbasedonindividualchoicesbetween

lotteries


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Systematicallyuseproposedsetofparedlotterychoices(AandB)classificationofriskaversion(loving)

Majorityofsubjectisriskaverse Riskaversionincreaseswithstakesbutnotwithhypotheticalpayment

RelativeOverconfidence Welldocumentedandeasytoresearchexperimentally Example:Viadrinastudents:mathematicalabilitiesrangeofothers,ownrange Averagestudentsrateshisownabilitieshigherthanthoseoftheaverage

comparablestudent =Optimismbias

Intrinsicversusextrinsicmotivation

Introductionofpayment:canreducesupplyofvoluntaryservices,crowdingoutmightresult

Manypeoplelikework,strongintrinsicincentivestodelivergoodresults Introductionofadditionalextrinsicincentivesmayreduceworkeffort Reasonsforcrowdingout(Verdrngungseffekt):

o Feelingofdiminishedself-determinationoro Compensationforsocialvalueofanactivitymaybedisappointinglylow

Thedestructionofintrinsicmotivationisusuallyirreversible,i.e.theabandoningofextrinsicmotivationdoesnotre-establishintrinsicmotivation

Crowding-in:introductionofextrinsicrewardsfosteranactivityifthepriceforasocialactivityishigherthanexpected(signalingtheory)

Negativepricestopunishunsocialbehavior:notworking

Relationshipbetweenpositive/negativeincentivesandsocialbehaviorillustratedbyW-Effect(Adecreaseinproductivityisobservedforsmall,butnotforlargeincentive)

Motivationofothersisimportantfortheownevaluation

StiftungWarentestoderBIldZeitung?

Lecture9DecisionofandWithinGroups

GroupDecisions Mostdecisionsmadebygroupofpeople(family,firmsetc.) Decisionprocessdependingoninteractionswithothermember

TendenciesofGroups

Socialperception:processofacquiring,interpreting,selectingandorganizingsensoryinformationinfluencedby2factors


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Structuralfactors:drivingsolelyfromthenatureofthephysicalstimuliandthenaturaleffectstheyevokeinthenervoussystemoftheindividual

Functionalfactorsofperceptualorganizationderiveprimarilyfromtheneeds,moods,pastexperience,andmemoryoftheindividual(hungry)

Allfunctionalfactorsinperceptionaresocialintheusualsenseoftheterm Differentperceptionsofthehungryandnot-hungrystudentscouldnotbedueto

structuralfactors,sincethesamepictureswerepresentedtobothgroupsbutcouldbedueonlytothedifferencesinneedormotivationofthemembersofthetwogroups

Social(functional)factorsreflectingthedemand(Bedrfnisse)ofthegroupcanstronglyguidegroupdecisionsandleadtogroupthink

BehavioraltendenciesresultingfromsharedvaluesandreciprocalreinforcementGroupPolarization

Observedtendency:riskyshift=lessconservativeandmoreriskydecisionsthanthosebyindividuals

Groupactionmoreextremeversionofeachindividualspreferredaction Universalconfirmationbias=tendencytosearchfororinterpretinformation

thatconfirmspreconceptions,avoidancewhichcontradictpriorbeliefs Anotherexplanation:supporttheory

SupportTheory(Tversky)

Explainjudgmentsbytheaggregationlevelofinformation P(packed)P(unpacked)P(constituent) Judgingprobabilityofdescriptiondependingon

o Whatmemberspeoplebringtomindgivenadescriptiono Howsupportgetsaggregatedacrossthesemembers(supportvalue)

Groupdecision:unpacksupportiveinformationandpackedcounter-supportiveinformation

=Explanationfortheconjunctionfallacyandinvolvedheuristics(representativeness,availability)

AdaptionofGroups

Groupsadapttogether=specificstrategiesprevail Evolutionarilystablestrategy(ESS):adoptedbyapopulationofplayers,cannot

beinvadedbyanyalternativestrategythatisinitiallyrare =EquilibriumrefinementoftheNashequilibriumthatisevolutionarilystable

oncefixedinapopulation,naturalselectionaloneissufficienttopreventalternative(mutant)strategiesfromsuccessfullyinvading

E(S,S)>E(T,S)orE(S,S)=E(T,S)andE(S,T)>E(T,T)(ThisdefinitionisthedefinitionofweakESS(oranevolutionarilysteadystate)

ThestrongversionofESSis:E(S,S)E(T,S)andE(S,T)>E(T,T) Inmostsimplegames,ESSandNashequilibriumcoincideperfectly

Strategy ESS

Both(A,A)and(B,B)areaNashequilibrium.OnlyBisanESS.Bcan

neutrallyinvadeapopulationofAstrategists,whereuponitwillcometopredominatesinceBscoreshigheragainstAthanAdoesagainstB.E(A,A)=E(B,A),butitisnotthecasethatE(A,B)>E(B,B).


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WhileDstrategistsmaytemporarilyinvadeapopulationofCstrategistsbyscoringequallywellagainstC,theypayapricewhentheybegintoplayagainsteachother:CscoresbetteragainstDthandoesD.SoherealthoughE(C,C)=E(D,C),itisalsothecasethatE(C,D)>E(D,D).AsaresultCisanESS.

Definition:xundysindzweiStrategienE(x,y)istderReproduktionserfolgeinesIndividuumsmitStrategiexineinerUmwelt,inderalleanderendieStrategieyausfhren.xistnurdanneineESS,wennfrallegilt:E(x,x)>E(y,x),oderE(x,x)=E(y,x)undE(x,y)>E(y,y)DerersteTeilderDefinitionistquivalentzumsogenanntenstriktenNash-Gleichgewicht,d.h.:xistbesteAntwortaufsichselbst.KeineandereStrategieschneidetgegenberxbesserab,alsxselbst.DerzweiteTeilsiehtvor,dass,wennStrategieyinreinerx-Umgebungnichteliminiertwird,dasiegleicherfolgreichist,xinreinery-Umgebungsichgegenberydurchsetzenkann-somitkanndiePopulationnichtvonxnachykippen.BeispieleIneinemPokerclubspielenalleSpielerdieStrategieX.NunkommteinfremderSpielerzuBesuch.WennseineandereStrategieYnichterfolgreichistunderkeinGeldgewinnt,dannisteswahrscheinlich,dasserzurStrategieXwechselt(ESSistwirksam).WennseineY-Strategieabergewinnbringendist,dannwechselnalleMitgliedervonStrategieXaufY.YistalsodieESS;einzweitesNeumitgliedmitStrategieYwrdenichtbesserfahrenalsdiejetzigenClubmitglieder.Angenommen,inEuropagbeeseineVogelart,diejedenHerbstnachSdenzieht.WennnuneinIndividuumauftritt,dassichinmildenWinterndazuentscheidet,inEuropazubleiben,dannhatesdenVorteil,dassesimFrhlingschondie(Nahrungs-)Ressourcenanzapfenkann,bevordieanderenVgelzurckkehren.MitbesserenFettreservenimKrperausgestattetistdasIndividuumnunfhig,besseralsalleanderenNachkommengrozuziehen.JeneVgel,dieimmernachSdenziehen,sterbenlangfristigaus,dasiesichschlechterfortpflanzen.EbensoistesfreineVogelartvonNachteil,immerinEuropazubleiben;derWinterknnteeinmalsokaltsein,dassvielevonihnensterbenunddanndievomSdenzurckkommendenVgeleinevielbessereAusgangslagebesitzen.DieESSderVogelartbestehtalsodarin,

jenachMildedesWintersinEuropazubleiben.DasLehrbuch-BeispielderESSdasHabicht-Taube-Spiel:IndividuendergleichenPopulationwerdenalsHabichte(aggressiv,stark)undTauben(friedlich,ausweichend)eingeteilt.StteineTaubezueinerreinenTauben-Population,verndertsichnichts.Dasgleichegilt,wennsicheinHabichtzuanderenHabichtengesellt.EsgibtabervierbesondereFlle:EineTaubesttzuHabichten:DadieTaubedenKonfliktenzumBeispielumsFutterausweichtundsoKraftundKrperverletzungeneinspart,fhrtsieeineerfolgreicheStrategie.DazukannsiemittelsDrohgebrdenAggressivittvortuschenundkrftesparendHabichtenRessourcenabluchsen.EinHabichtsttzuTauben:DieTaubenmachendemNeuankmmlingPlatzundberlassenihmkampflosalleRessourcen.DerHabichtisterfolgreich.EineTaubeodereinHabichtsttzueinergemischtenPopulation,inderTaubenundHabichteimkorrektenZahlenverhltnis(entsprichtderESS!)vorkommen.FrdenNeuankmmlingspieltesnuneineRolle,oberhufigeraufeineTaubeoderaufeinenHabichttreffenwird.HatsichdiePopulationaufdie

geeigneteMischungeingependelt,kannesihregalsein,obsichderEindringlingalsTaubeoderalsHabichtverhlt.DiesogenannteBrger-Strategie(engl./franz.bourgeois)entwickeltsichzurESSundsieistweitgehendimmungegenbereinerunausgewogenenHabicht-Taube-ZusammensetzungderPopulation.AlsBrgergilt:Wennmansichverteidigt,istmaneinHabicht;greiftmanjemandenan,verhltmansichwieeineTaube.ImwiederholtenGefangenendilemmaisteinePopulationausTit-for-tat-Strategiennichtevolutionrstabil.WhrendsieresistentgegenberDefektiere-Immer-Strategienist,kannsievonKooperiere-Immer-Strategienunterwandertwerden,wieeinfachanhandderDefinitionmitx=Tit-For-Tatundy=KooperiereImmernachgeprftwerdenkann:TFTgegenKooperiereImmerfhrtzugleichenAuszahlungenfrbeideSpieler,dahergiltBedingung1(E(x,x)>E(y,x))nicht.JedochgiltauchTeil2derBedingung2(E(x,y)>E(y,y))nicht,daauchindiesemFallbeideStrategienzugleichhoherAuszahlungfrbeideSpielerfhren.EinePopulationausKooperiere-Immer-StrategienkannwiederumvonDefektiereImmerunterwandertwerden.


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Determineevolutionarystablesets:gamesplayedagainandagainwithdifferentpartnersinapopulation

Strategiesnotchosenbyforesightandcalculationbutbyevolutionaryselectionbasedonfitnessandreproduction

DecisioninGroups Socialaspects=largerole,decisiondependingonotherdecisionsresults

dependonbehaviorofthegroupasawhole Searchforoptimalresultsingames:matchingmarket,publicgood,beauty

contest,penaltygameMatchingMarkets

Classicalproblem:matchspecificgoodsandpeople,esp.inseparablegoods Marriageproblem,allocationsofsitestofirms,employerandemployeeallocation Important:sharedfairnessperception Optimalallocationwouldyieldthehighesttotalresultforthegroup Mainlyresearched:optimalmatchinginstitution(centralizedorauctiondesign)

PublicGoodsGame

Inorderforcontributionstobeprivately"irrational"thetokensinthepotmustbemultipliedbyanamountsmallerthanthenumberofplayersandgreaterthanone.Otherthanthis,thelevelofmultiplicationhaslittlebearingonstrategy,buthigherfactors

producehigherproportionsofcontributors.ParticipationratesdifferoverculturesandoversocialrewardsandpunishmentsBeautyContestGame

nplayerschooseanumberbetween0and100.Thatplayerwhoisclosestto2/3oftheaveragewinsacertainamountofmoney.Inthecaseofdrawsthemoneyisdistributedrandomlytothewinners.Nash:Choose0.Stepsofreasoning:LeadingtoNash.

Level0,whichwouldbethepreliminarystepofanyreasoning,translatesintonumbersthatarearbitrarilydistributedovertheinterval,resultinginexpectedvalueof50(50.5ifnumbersarefrom1to100)

Level1reasoningis(2/3)50=33.33 Level2reasoningis(2/3)33.33=22.22 Level3reasoningis(2/3)22.22=14.8(...)


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ThePenaltyGame

Mostdifficulttoactrandomly Example:jumpdirectionofgoalkeeperandkickdirectionofthescorer Randomizedkicksbutgoalkeepernotoptimizing

Reciprocity Keysocialperceptionfactors:trust,reciprocityandpunishment Reciprocity=responsiblefordevelopmentandstabilityofhumansocieties Expressionsinalllanguages:totfortat(wiedumir,soichdir),onehandwashes

theother(positive),AugeumAuge(negative) Needadynamicenvironment,peopleactsequentially,repeatedly(contrastto

altruism)SequentialGames

Extensiveform,decisionsmadeoneaftertheotherwhileplayersmakemorethanonedecision(e.gcentipedegame)

Choicedependsonsomeoneelseschoice,firstdecisiononlaterdecisions

Reciprocalbehaviorasformofcooperationorsomeofaltruismmodels(inequityaversion)

UltimatumGame:utilitiesderivedfromthematerialoutcomeswithinequityaversion(formula)describesactualobservation

Gameoftrust:nash:Awouldnottrust,butwithinequityaversionformula

trustandcooperation,butspecificlevelie.a.necessary(smallissometimesnotenough)

Atrustbecauseheknowsbwillcooperate Atutwasgutesweilbauchwasgutestut.

DassiehtauswiereziprozittRepeatedGames

Describefrequentsocialbehavior,oftensamesituationoverandover(e.gcooperationattheworkplace,helpneighborsprisonersdilemma)

GametheoreticequilibriumifPDplayed1000times? Nocheatsinrepeatedgame,alwaysdenynocooperationfromtheotherplayer Bothdecidetocooperatebutonlyiftheothercooperates Titfortat:mostsimpleandusefulstrategystartwithcooperationandproceed

bycopyingotherplayerschoicefromthepreviousperiodAltruisticpunishment

Prosperifallcontributetopublicgood(e.g.obeyrules,keepcommonapartmentclean,donotsteal,donothurtsomeone)

Nocontributionpunishment(verbal,material,beating,exclusion Punishmentatacostforpunisher,believablethreatmayfostercontributions(=altruisticpunishment)Membersofthegroupcontributemoreinpublicgoods Butcounterpunishmentpossiblelessfirstpunishmentlesscontributions


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EfficiencyWagesunderTitforTat Firmspaymorethanminimumwagesmoreandbetterapplicantsandworkers

voluntarilychooseahighereffortlevelehigherprofitforfirmp(e) Chooseefficientwagewhichmaximizesprofit Highereffortlevelswithhighercostswhenpaidhigherwagesprovedbyhigh

stakeexperimentsinRussiastrongpositivecorrelationHowtoreciprocate?

Reciprocity=fundamentalbehaviorinhumansocietiesbutverycomplex! Basicruleissimple,applicationisnot Behaviorkindorhostile,howkind,howtomeasure,favorbychance,favoras

unintendedsideeffect,well-meantcontraryofwell-done? Strictdistinctionbetweenintendedandnon-intendedharmsinlawas

prototypicalsocialinstitution(helpandbreak) WhatdoesBbelieveaboutAsintentions?WhatdoesAbelieve,Bwillbelief

aboutAsintention?Thelatterdetermines,whatAisgoingtodo!(Beliefsoverbeliefs!!!!)

Notoftenpossibletofindoutintentionsandkindnessofaperson Repeatedinteractions:measureintentionsontheachievedresults Chancetotalkincommondilemmasituationsincreasedcooperationrate

Lecture10DecisionAnalysisandResearchTechniques

ExperimentalDataAnalysis Objective,aggregationinfair,neutral,clearmanner Documentsupportiveandopposingresultswithappropriatemeasures Datagathering:processvs.outcomedata,sortsofmeasures Correspondinganalysestodifferentsortsofdata

Typesofdata

Datacharacteristicsappropriatewayofdataanalysis 4Differentmeasurementscales(dataaggregationpossibilities)andstandard

numericalmeasures Statisticaltestssortofdistributionofthedependentvariable

DecisionLabs

Differentdevelopeddecisionlabs:measuringprocessvariables Prominent:Mouselabdecisionprocessiscapturedbytheactualbehaviorof

thedecisionmaker(e.g.eyetracker,chemicalmarkers) Choiceandprocess:compensatorystrategieslikeWADDassumemorecue-wise

processingandnoncompensatorystrategieslikeEBAorTTBassumemore

alternative-wiseprocessing Supportassumptionofanadaptivedecisionmaker Objection:onlysuccessfulimplementationsreported,nodescriptionoffailures


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WaysofDataAnalysis

Testdifferentrelationsbetweenindependentanddependentvariables Linear,parametricandnonparametricmodels Linearrelations:simplecorrelationorregressionanalysis Nonparametric:usedforotherdistributionalrequirements Qualitymeasures:leastsquares,maximumlikelihoodestimation(evaluateand

comparefitinregardtoobservationaldata) Standardproblemsinmodelselection:dataoverfittingandflatmaxima

OccamsRazor

Universalscientificprincipleformodelfrugalityandsimilarsayings Pluralityisnottobepositedwithoutnecessity Possibleexplanationsbecomeneedlesslycomplex,toomanyspecifics Lesspredictivepower/universalityofthemodel Evaluation:AikakeInformationCriterionorBayesInformationCriterion

ForecastingwithBiases

Behaviorisbasedonexpectationsabouttheconsequencesofbehavior Rationalexpectations:makeunbiasedforecasts,ifothersarebetterinformed

askorbuyinformation/advice Distinguishbetweenexpectationsdevelopedbythedecisionmakersthemselves

andforecastsorprophecies(fromothers,inparticularfromthosenotaffectedbythedecisionsofthedecisionmaker)

Difficult:formationofexpectations(GameTheory:expectationsareendogenized) Often:Behaviorbasedonroutine,onlypartlyaccountedconsequences,sourceof

expectationsmaybeobscure,donotknowthatwereceivedinformationthatguidedourbehavior,impressionsaboutabilitiesandtrustworthiness Explicitforecastbyothersessentialroleforourdecisions(beliefinsuch

propheciesmaychangeourbehaviorinawaywhichmakestheprophecycometrueorpreventitbecomingtrue)

RationalExpectations(RE)useallavailableinformationefficiently?

1. Microeconomictheory:REinvolvingefficientinformationprocessingasfundamentalassumption,peoplehaveperfectforesightorknowdistributionoffuturevariablesidealtheories

2. Realdecisionmakers:noHO,haveanalteregoexperimenterREridiculousbuthowfaraway?Istherebetteralternative?

3. Macroeconomics:realworlddevelopmentsandnotindividualbehavioraggregatedexpectationsfromREtoEfficientMarkethypothesis(weakerrequirement)individualcanrelyonthemarketbecauseofprofessionalspeculatorsresponsibleforefficiencyofpricestructure(marginaltraders)HayekHypothesis;+societyasawholeusesallinformation(decentralizedinformationprocessing)

ImplicitTestsofREandotherHypothesesofExpectationFormation

1. TestREinmacroeconomics:mixedresultsbutstilldominanthypothesis2. Existenceofbubbles(TulipMania,crashes)asargumentagainstREbuttypicallyfoundinassetmarketswithinexperiencedsubjects


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3. ArgumentforEMH:non-existenceofsuccessfulspeculationmethod,somestudiesrevealpossibilityofsmallprofitsusingappropriatespeculationrulebutdecreasingwithtransactioncost

DirectTestbyAnalyzingExpertForecasts

Noaccurateforecasts,onlyinregionofnearcertainty(weatherfortomorrow) Rule:Naturally,thelongertheforecastingperiodtheworsetheforecasts. Notaccuratenotrational,rationalitydependingoninformationavailableand

properlyandcompleteusage Tounderstandingprocessofexpectation,informationavailablehastobeknowin

advanceandrelevantcriteriafordecisionproblemandinfluencingawardstructure,lossfunctions,goalfunctionalltypicallyunknown

Differentinlaboratoryexperiments:subjectsgetexactlydefinedsetofinformationandwell-definedaward-structure

TheBoundsandLikelihoodHeuristic Modelingofaverageforecasts,basedontimeseriesgestaltcharacterisitics Twocharacteristicsoftimeseriesimportantfortheforecasts:averagevariation

andturningpoints Actuallypredictedchangedependsonlikelihoodthatxtisaturningpoint

o Upswingcasext>xt-1probabilitythatxtisalocalmaximum(Ifinperiodtalllocalmaximaabovext,lowprobabilitythatxtisturningpointIfalllocalmaximabelowxt,i.e.xtverylikelytobeaturningpoint)

o DownswingCase:xt


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Self-Fulfillingprophecies Predictionthatdirectlyorindirectlycausesitselftobecometrue Falsedefinitionofthesituationnewbehaviororiginalfalseconceptiontrue Perpetuatesareignoferror,prophetseeseventsasproofthathewasrightfrom

thebeginning Thomastheorem:Ifmendefinesituationsasreal,theyarerealintheir

consequenceshowsituationsareperceivedandthemeaningassignedratherbysituationsthemselves

Example:CartwrightMillingvilleBankbreakcyclebyredefiningthepropositionsonwhichthefalseassumptionsareoriginallybased

Roleofself-fulfillingprophecies

Inevitabilityofwar(TheWilltoBelieve):forexampleOedipus Fakeittillyoumakeit(actasif):imitateconfidencesothatastheconfidence

producessuccess,itwillgeneraterealconfidence,methodofovercoming

depression(forcehappinesstobecomereal) MooresLaw:computerhardwaretransistorsincreaseexponentially,doubling

everytwoyearsdescribingdrivingforceoftechnologicalandsocialchange-industrystrugglestokeepupwithit(goalforentireindustry)

PygmalionEffect(Rosenthaleffect,teacher-expectancy-effect):studentsperformbetterbecausetheyareexpectedtoandreverse

CleverHansEffect:horseperformingintellectualtasksbywatchingreactionofhumanobserversrespondingtoinvoluntarycuesinthebodylanguagemakeexperimentsdouble-blind(neitherexperimenternorthesubjectknowswhatconditionthesubjectisinandresponses)orreplacingwithcomputer

Lecture11DecisionSupport

ProcessModels Processvariablescandistinguishbetweendifferentmodels(e.gcompensatoryvs

non-compensatory) Theoreticmodels:processholdsvaluableinformationforempiricalsupport Heuristics=descriptionsofprocesswithsearchrule,stoppingrule,decisionrule Oftenprocessheuristicsasexplanationforobservedbehavior,w/o

predictivevalueincontrasttoforexampleprospecttheory Gamblersfallacy:repeatedtossofacoinoutcomesarestatistically

independent(sameprobability)butmaybelieveafterarowofsuccessiveheadsthatthenexttossmustbeatail

Fallacy:Reasoningthatitismorelikelythatthenexttosswillbeatailthanaheadduetothepasttosses-thatarunofluckinthepastsomehowinfluencestheoddsinthefuturerepresentativenessheuristic

LawofAverages:assumptionthatinsmallsamplestheoutcomesofarandomeventshouldevenout(didntoccursometime,mustoccurnext)

Mostnaturallyobservedsequencesarenotindependent,probabilityofthefuturecanchangebasedontheoccurrenceofpastevents

Probabilitymatching=strategysuboptimaloutcomesservesastheoreticalconceptforbehavior(hastwasbeobachtetVersuchschwaris>rotaberin


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echtgibtesmehrrotekugelninderurne,verlierstdeswegen)subjectsrespondtothelightsinthesameproportionastheyoccur

Animalsandhumansoftenmatchbaseratesintheirbehavior(Peoplecategorizeeventsaccordingtotheiroccurrenceinatrainingphase,althoughtheywouldachievebetterresultsiftheyalwaysgoforonecategoryifitsbaserateishigher)

ProcessModelswithassumptionsaboutprocessandresultingchoicepredictionsEliminationbyAspects

EliminationbyAspectsHeuristic(EBA)=decisionruleunderboundedrationality Recurringevaluationstilloneonalternativeleftforchoice Canbecombinedwithcompensatorystrategiesafterthechoicesetisinstructed EBA=lexicographicstrategyandnoncompensatory(likeTTB)quick

decisionswithoftensameaccuracyascomplexcompensatorystrategies TTBforbinarychoices(only2alternatives) Concerns:rankingofattributesandsettingoftresholds1. Eachalternativeisviewedasasetofaspects2. Ateachstageanaspectisselected(themostimportantattribute)3. Allalternativesthatdonotincludethataspect(minimumforthisattribute)are

eliminated4. Processstopswhenallbutonealternativeareeliminated

DecisionFieldTheory(DFT)

Computationalmodelofdecisionmaking,modelingdeliberation(berlegungen)asadiffusion(Streuung,Verbreitung)process

Describeshowaperson'spreferencesevolveacrosstimeuntiladecisionisreachedratherthanassumingafixedstateofpreference

Predictdecisionmakingunderuncertainty,resultingbehavior,alsoresponsetimesandcontexteffects

Explainviolationsofstochasticdominance,violationsofstrongstochastictransitivity,violationsofindependencebetweenalternatives,serialpositioneffectsonpreference,speedaccuracytradeoffeffects,inverserelationbetweenprobabilityanddecisiontime,changesindecisionsundertimepressure,aswellaspreferencereversals

Intuitively,ateachmomentintime,thedecisionmakerthinksaboutvariouspayoffsofeachprospect,whichproducesanaffectivereaction,orvalence,toeachprospect.Thesevalencesareintegratedacrosstimetoproducethepreference

stateateachmoment. Thestoppingruleforthisprocessiscontrolledbyathreshold Choiceprobabilityisdeterminedbythefirstoptiontowintheraceandcrossthe

upperthreshold,anddecisiontimeisequaltothedeliberationtimerequiredbyoneoftheprospectstoreachthisthreshold.

Konsequenzenwerdensequentiellberdachtundintegriert,KontinuierlichwerdenmomentanePrferenzstadiengebildet,Aufmerksamkeitschwankt,bersteigteinPrferenzstatuseinenSchwellenwert,wirdeineEntscheidunggetroffen

DFTnicelyexplainscontexteffects(i.e.,attraction,compromise,orsimilarityeffectscompareSessionII)byattentionshifts.


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DecisionbySampling(DbS)

AsalternativedecisionprocessmodelwithnounderlyingpsychoeconomicscaleslikeinProspectTheory

Anattributessubjectivevalueisconstructedfromaseriesofbinary,ordinalcomparisonstoasampleofattributevaluesdrawnfrommemoryandisitsrankwithinthesample

Samplereflectsimmediatedistributionfromattributevaluesfromcurrentcontextandbackground,real-worlddistribution

Concaveutilityfunctions,losseslargerthangains,overestimatingofsmallprobabilities,underestimationoflargeprobabilities

Evaluationsvaryfromoccasiontooccasion(accordingtoavailableitemsandmemorizedsamples)

Alsoeventsoftimeappeartobeexponentiallydistributed,thus,explainingdiscountingeffectsbytherelativecomparisonsample

DecisionSupportSystems Provideusefulinformationwhenneededandallowquickandefficientdecision

making Questions:Howmuchinformationisavailable,howmuchshouldweuse DataCompression:Informationcanoftenbecompressedwithoutlossandis,

then,easiertoprocess Frogandtoad:trytoeatallkindoflittlemovingobjects,don'tneedmore

informationabouttheirprey,informationusedwhennecessaryandprocessedbysimplereinforcementlearning

FundamentalprobleminDS:questionregardingindividualdemandhelpwithoutdemand=paternalism

Well-being=multidimensionalandconditionsforhappinessdifficulttodefine Onorganizational/expertlevel:criteriaforoptimadecisioneasiertodefine


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DecisionTrees

Usedinoperationsresearch,decisionanalysiswithgraphormodelofdecisionsandpossibleconsequences

IdentifystrategymostlikelytoreachagoalORtreeasdescriptivemeansforcalculatingconditionalprobabilities

Easytounderstandandtoimplement,simplifieddecisionproblems Example:teachingofstatisticsandusingfrequenciesinsteadofprobabilities Medicaldecisions:strategywithhighsensitivity(e.gsendmostpatientsactually

havingseriousheartproblemincareroom)andhighspecificity(e.gfewpatientsincareroomunnecessarily),fastdecision,transparencyofdecisionsystem

Decisiontreesarefast,transparent,easytoteach,andtheycanbesurprisinglyaccurate

CreditMonitoring:fastdecisionstoavoidlosses,transparent,easilycommunicatedelectroniccreditratingsystemsinloandecisionsinformofhierarchicaldecisiontreesoptimizeandformalizedecisionprocess

Decisiontreepathallowsresultstobescroredagainstcreditpolicy,peergroup Electronicmonitoring:employeeperformancetracking,companyperformance Datamining:decisiontreeaspredictivemodel=mappingobservationsaboutan

itemtoconclusionsabouttargetvalueclassificationtree,regressiontree(leavesrepresentclassificationsandbranchesrepresentconjunctionsoffeaturesthatleadtothoseclassifications)

ErrorsandLearning

Behavior=goal-orientedguidedbylearning(mostimportantmentalfunction) Errorlearninghypothesis:economicvariablescanbepredictedonthebasisof

previousvaluesanderrormargin(adaptiveexpectationsprincipleforecastandrevisionaccordingtonewandcurrentinformation)

Manydifferentformsoflearningascrucialroleforimprovingbehavior Errorsandcorrespondingcopingmechanisms:strengtheneconomicoutputs

Non-associativeLearning

Habituation:progressivediminution(Verminderung)ofbehavioralresponseprobabilitywithrepetitionofastimulus=integrationyoufirstreacttoastimulibutwhenitisneitherrewardingnorharmfulyoudon'trespondafterasecondstimuli(veryspecific)

Sensitization:progressiveamplificationofaresponsefollowsrepeatedadministrationsofstimulus(e.g.rubarmwarmsensationpain(reminderthatitisharmful))adaptiveandmaladaptivelearningprocesses

AssociativeLearning

Classicalconditioning:repeatedlypairingunconditionalstimulus(evokesparticularresponse)withpreviouslyneutralstimulusconditionedresponse

Operantconditioning(Lawofeffect):useofconsequences(reinforcementorpunishment)tomodifytheoccurrenceandformofbehaviordealswithmodificationofvoluntarybehavior

Exploration(play) Behaviorwithnoparticularendinitself,improvingperformanceinsimilarfuture

situations(e.g.catandmice)


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Involvescost(foranimals):increasedvulnerability,riskofinjury,possibleinfection,energyconsuming

Oppositeofexploitation(Nutzung)learnedability Usedinbeginningofnewtasktofindpossiblesolutions,adaptiveinchanging

environments Importantforeconomicexperiments:allowforlearning,resultingbehaviorcould

substantiallyimproveObservationalLearning

Imitation:repetitionofobservedbehavior Humanscancopythreetypesofinformationsimultaneously:thedemonstrators

goals,actions,andenvironmentaloutcomestuneintosurroundingcultureavoidlosses

Imitation=mostpowerfulprinciplesofboundedrationality Learningbyimitationundervaluedinanimals(instinctswereassumedasdrivers

forbehavior) Neednottoknowwhymodeofbehaviorissuccessful,canstillachieveitanyhow Centralquestions:WhomshouldIimitate?HowshouldIimitate? Rulesofthumb:http://rulesofthumb.org/

Lecture12AppliedDecisionScience

BehavioralFinance Behavioraleconomicsandfinance=closelyrelatedfieldsapplyingscientific

researchonhumanandsocial,cognitiveandemotionalfactorstobetterunderstandeconomicdecisionsandhowtheyaffectmarketprices,returns

Behavioralanalystsconcernedwitheffectsofmarketdecisions,publicchoice(biasespromotingself-interest)

ConsumerBehavior

Variationsinindividualdecisionmakingfindmeansforimprovement Examplesofindividuallyguidingprinciples:self-controlandmentalaccounting Applicationstospecificchoicesituations

BehavioralLifeCycleHypothesis Incontrasttolife-cycletheory(stablelifestyle)enrichedbyself-control,mental

accountingandframing Keyassumption:householdstreatcomponentsoftheirwealthasnonfungible

(nichtaustauschbar,ersetzbar),evenintheabsenceofcreditrationing Wealthdividedincurrentincome(I),currentassets(A),futureincome(F) Temptationtospend:greatestforIandleastforF(behavioralobservation:

saving,bonustreateddifferentthanregularincome,retireddonotdissaveenough)

Plannerconcernedwithmaximizingfunctionoflifetimedoerutilities(U)withZ=pleasureandpain,W=willpower(psychiccosts) Zt=Ut+Wtnosingleutilityfunction(accountspecific),irrelevantfactors(i.e.formofpayment)canmatter,choicescanbestrictlyinthebudgetset


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Naveruleinassetallocation:1/n-rulethemorechoicesareavailablethemoreassetsareselected,theamountisroughlythesameforall

allocations(VerteilungBetraginetwagleich)

Contradictiontoportfoliotheorywhereassetsshouldbeallocatedtoriskyandnon-riskyprospects

BehavioralPortfolioTheory:efficientdiversificationofinvestmentismeasureddependentonnumberofmentalaccounts

Differentimplicationsofsingleandmultipleaccounts

portfolioresembleslayeredpyramidswherelayersareassociatedwithdifferentaspirations

(Bestrebungen,Erwartungen)EffizienteverteilungvonInvestmentsaufverschiedeneSchichtenzbArmutvermeiden,undindemanderenMentalAccountaufReichtumerabzuzielen.

Anotherapplicationforconsumerdecisionmaking:DoubleEntryMentalAccountingSystemconsumptionexperienceisdecreasedbythepaymentexperienceovertimedifferenttimelydistributionsofpaymentsleadtodifferentlyexperiencedutility

Insomecircumstancescoupling(i.e.,fixedfeeforhealth)andinothersdecoupling

(i.e.,buyersusingcreditcards)increaseoverallexperiencedutility.Hence,hyperbolicmentaldiscountingisoftenexploitedbyofferswithdelayedpaymentswithhighpainsofthepayment

experienceanddepletedutilityofconsumptionexperiencelater.


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PolicyImplications

Behavioralobservationswithstrongimplicationsforappliedpolicies(applicationpotentials)

ProminentapproachLibertarianPaternalism(formofeconomicguidance) Influencingbehaviorandalsorespectingfreedomofchoice Oftenpeople'spreferencesareunclearandill-formed,andtheirchoiceswill

inevitablybeinfluencedbydefaultrules,framingeffects,andstartingpointspaternalismcannotbeavoided

Steerchoicesinwelfare-promotingdirectionsw/oeliminatingfreedomofchoice(tools:boundedrationality,boundedself-control)

Itisalsopossibletoshowhowalibertarianpaternalistmightselectamongthepossibleoptionsandtoassesshowmuchchoicetooffer

Subjectsratedmeanportfolioequallytoownportfolioandmedianportfoliosignificantlymoreattractivepeoplenotgainmuchbychoosingportfoliosforthemselves

SafeMoreTomorrowPlan:influenceretirementsavings

1. Employeesareapproachedaboutincreasingtheircontributionratesaconsiderabletimebeforetheirscheduledpayincrease.Becauseofhyperbolicdiscounting,thelagbetweenthesign-upandthestart-updateshouldbeaslongasfeasible.(Automaticenrollmentlater)

2. Ifemployeesjoin,theircontributiontotheplanisincreasedbeginningwiththefirstpaycheckafteraraise.Thisfeaturemitigatestheperceivedlossaversionofacutintake-homepay.(Nocomparableloss)

3. Thecontributionratecontinuestoincreaseoneachscheduledraiseuntilthecontributionratereachesapresetmaximum.Inthisway,inertiaandstatusquo

biasworktowardkeepingpeopleintheplan(defaultrule).4. Theemployeecanoptoutoftheplanatanytime.

Mostpeople(78%)whowereofferedtheSMTplanelectedtouseit;virtuallyeveryone(98%)whojoinedtheplanremainedinitthroughtwopayraises,andthevastmajority(80%)remainedinitthroughthethirdpayraise;andtheaveragesavingratesforSMTplanparticipantsincreasedfrom3.5to11.6%overthecourseof28months.

Consider:willingnesstotakeprecautionsdecisiontobuyinsuranceisproductofrecenteventsandnotsystematicinquiryofcostsandbenefits(peopledonot

chooseoptimallyevenwhenthestakesarehigh) Defaultplansaffectoutcomes,existingarrangementisoftenrobustillustration

byautomaticenrollmentphenomenonincontrasttoopt-inmodelsthereisahigherenrollmentinopt-outmodels(onlyfewopt-out)

ActualbehaviorishighlysensitivetoplandesignfeaturesMinimalpaternalismistheformofpaternalismthatoccurswheneveraplanner(privateorpublic)constructsadefaultruleorstartingpointwiththegoalofinfluencingbehavior.Solongasitiscostlessornearlycostlesstodepartfromthedefaultplan,minimalpaternalismismaximallylibertarian.Thisistheformofpaternalismthatisdescribedasinevitable.

Unsureofwhatchoiceswillpromotewelfare,aplannermightrejectdefaultplansorstartingpointsentirelyandforcepeopletochooseexplicitly(requiredactivechoices).


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MoreAggressiveformsofPaternalism Defaultplanaccompaniedbyproceduralconstraintsdesignedtoensurethatany

departureisvoluntaryandentirelyrationalitisnotcostlesstodepartfromthedefaultplan

Justificatio