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Decision Theory. Lecture 2. Decision Theory – the foundation of modern economics. Individual decision making under Certainty C hoice functions Revelead preference and ordinal utility t heory Operations Research , Management Science under Risk
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DecisionTheory Lecture 2
DecisionTheory – thefoundation of modern economics • Individualdecisionmaking • under Certainty • Choicefunctions • Reveleadpreference and ordinalutilitytheory • Operations Research, Management Science • under Risk • ExpectedUtilityTheory (objectiveprobabilities) • Bayesiandecisiontheory • ProspectTheory and otherbehavioraltheories • SubjectiveExpectedUtility (subjectiveprobabilities) • under Uncertainty • Decisionrules • Uncertaintyaversionmodels • Interactivedecisionmaking • Non-cooperativegametheory • Cooperativegametheory • Matching • Bargaining • Group decisionmaking (Socialchoicetheory) • Group decisions (Arrow, Maskin, etc.) • Votingtheory • Welfarefunctions
Individualdecisionmaking • under Certainty • Revealedpreference and utilitytheory Choice Choicefunction Utility U(TheTruth) > U(TheMatrix)
Individualdecisionmaking • under Certainty • Choicefunctions Weakaxiomof revealedpreference (WARP) NOT ALLOWED
??? You go to a restaurantinwhileyouare on vacationinTuscany and youaregiventhefollowing menu: • bistecca • pollo The cookanouncesthat he canalsoserve • trippaalla fiorentina
Individualdecisionmaking • under Certainty • Reveleadpreference and ordinalutilitytheory Choice Preferencerelation Utilityfunction ≻ U(TheTruth) > U(TheMatrix) If u() is a utilityfunction, thenanystrictlyincreasingtransformationg∘u() is a utilityfunctionrepresentingthe same preferences
The doctrine of utilitarianism saw the maximization of utility as a moral criterion for the organization of society. According to utilitarians, such as Jeremy Bentham (1748–1832) and John Stuart Mill (1806–1873), society should aim to maximize the total utility of individuals, aiming for "the greatest happiness for the greatest number of people". Another theory forwarded by John Rawls (1921–2002) would have society maximize the utility of those with the lowest utility, raising them up to create a more equitable distribution across society
Choicefunction Preferencerelation ≻
Individualdecisionmaking • under Certainty • Operations Research, Management Science
DecisionTheory – thefoundation of modern economics • Individualdecisionmaking • under Certainty • Choicefunctions • Reveleadpreference and ordinalutilitytheory • Operations Research, Management Science • under Risk • ExpectedUtilityTheory (objectiveprobabilities) • Bayesiandecisiontheory • ProspectTheory and otherbehavioraltheories • SubjectiveExpectedUtility (subjectiveprobabilities) • under Uncertainty • Decisionrules • Uncertaintyaversionmodels • Interactivedecisionmaking • Non-cooperativegametheory • Cooperativegametheory • Matching • Bargaining • Group decisionmaking (Socialchoicetheory) • Group decisions (Arrow, Maskin, etc.) • Votingtheory • Welfarefunctions
Individualdecisionmaking • under risk • Objectiveprobabilities (ExpectedUtility) • Subjectiveprobabilities (SubjectiveExpectedUtility)
ExpectedutilityTheory • Cardinalutilityfunction • Thisisthefoundation of gametheory – mixedstrategies • Thisisthefoundation of decisiontheory under risk – enablesmodelingriskattitudes If u(.) is a utilityfunction, thenanyaffinetransformation(au(.)+b, where a>0) isalso a utilityfunctionrepresentingthe same preferences
Normativevspositivedecisiontheory • Behavioral (positive) economics • Experiments • Psychology • Empiricalresults • Behavioraltheories • Traditional (normative) economics • Mathematics • TraditionalMacro and Micro
DecisionTheory – thefoundation of modern economics • Individualdecisionmaking • under Certainty • Choicefunctions • Reveleadpreference and ordinalutilitytheory • Operations Research, Management Science • under Risk • ExpectedUtilityTheory (objectiveprobabilities) • Bayesiandecisiontheory • ProspectTheory and otherbehavioraltheories • SubjectiveExpectedUtility (subjectiveprobabilities) • under Uncertainty • Decisionrules • Uncertaintyaversionmodels • Interactivedecisionmaking • Non-cooperativegametheory • Cooperativegametheory • Matching • Bargaining • Group decisionmaking (Socialchoicetheory) • Group decisions (Arrow, Maskin, etc.) • Votingtheory • Welfarefunctions
Individualdecisionmaking • under uncertainty • DecisionRules(in a while) • Uncertainty/ambiguityaversionmodels, e.g. Multipleprior/maximin model of Gilboa, Schmeidler Subjectiveprobabilitymay not exist
DecisionTheory – thefoundation of modern economics • Individualdecisionmaking • under Certainty • Choicefunctions • Reveleadpreference and ordinalutilitytheory • Operations Research, Management Science • under Risk • ExpectedUtilityTheory (objectiveprobabilities) • Bayesiandecisiontheory • ProspectTheory and otherbehavioraltheories • SubjectiveExpectedUtility (subjectiveprobabilities) • under Uncertainty • Decisionrules • Uncertaintyaversionmodels • Interactivedecisionmaking • Non-cooperativegametheory • Cooperativegametheory • Matching • Bargaining • Group decisionmaking (Socialchoicetheory) • Group decisions (Arrow, Maskin, etc.) • Votingtheory • Welfarefunctions
Zero-sum games • In zero-sum games, payoffsineachcell sum up to zero • Movement diagram
Zero-sum games • Minimax = maximin = value of thegame • Thegamemayhavemultiplesaddlepoints
Zero-sum games • Or itmayhave no saddlepoints • To findthevalue of suchgame, considermixedstrategies
Zero-sum games • Ifthereismorestrategies, youdon’tknowwhich one will be part of optimalmixedstrategy. • LetColumnmixedstrategy be (x,1-x) • Then Raw will try to maximize
Zero-sum games • Column will try to choose x to minimizetheupperenvelope
Zero-sum games • TranformintoLinearProgramming
Fishing on Jamaica • In the fifties, Davenport studied a village of 200 people on thesouthshore of Jamaica, whoseinhabitantsmadetheirliving by fishing.
Twenty-six fishing crews in sailing, dugout canoes fish this area [fishing grounds extend outward from shore about 22 miles] by setting fish pots, which are drawn and reset, weather and sea permitting, on three regular fishing days each week … The fishing grounds are divided into inside and outside banks. The inside banks lie from 5-15 miles offshore, while the outside banks all lie beyond … Because of special underwater contours and the location of one prominent headland, very strong currents set across the outside banks at frequent intervals … These currents are not related in any apparent way to weather and sea conditions of the local region. The inside banks are almost fully protected from the currents. [Davenport 1960]
Strategies • Therewere 26 woodencanoes. Thecaptains of thecanoesmightadopt 3 fishingstrategies: • IN – putallpots on theinside banks • OUT – putallpots on theoutside banks • IN-OUT) – putsomepots on theinside banks, somepots on theoutside
Advantages and disadvantages of fishingintheopensea Disadvantages • Ittakesmore time to reach, so fewerspotscan be set • Whenthecurrentisrunning, itisharmful to outsidepots • marksaredraggedaway • potsmay be smashedwhilemoving • changesintemeperaturemaykillfishinsidethepots Advanatages • Theoutside banks producehigherqualityfishbothinvariaties and insize. • If many outsidefishareavailable, theymaydrivetheinsidefishoffthe market. • The OUT and IN-OUT strategiesrequirebettercanoes. • Theircaptainsdominatethe sport of canoe racing, whichisprestigious and offerslargerewards.
Collecting data • Davenport collected the data concerning the fishermenaveragemonthly profit depending on the fishingstrategiestheyused to adopt.
Zero-sum game? Thecurrent’s problem • Thereis no saddle point • Mixedstrategy: • Assumethatthecurrentisvicious and playsstrategy FLOW withprobability p, and NO FLOW withprobability 1-p • Fishermen’sstrategy: IN with prob. q1, OUT with prob. q2, IN-OUT with prob. q3 • For every p, fishermenchoose q1,q2 and q3 thatmaximizes: • And theviciouscurrentchooses p, so thatthefishermenget min
Graphicalsolution of thecurrent’s problem Solution: p=0.31 Mixedstrategy of thecurrent
Thefishermen’s problem • Similarly: • For everyfishermen’sstrategy q1,q2 and q3, theviciouscurrentchooses p so thatthefishermenearntheleast: • Thefishermen will try to choose q1,q2 and q3 to maximizetheirpayoff:
Maximin andminimax Optimalstrategy for thefishermen Value of thegame Optimalstrategy for thecurrent
Forecast and observation Gametheorypredicts Observationshows No fishermenrisksfishingoutside Strategy69% IN, 31% IN-OUT [Payoff: 13.38] Current’s „strategy”: 25% FLOW, 75% NO FLOW • No fishermenrisksfishingoutside • Strategy67% IN, 33% IN-OUT [Payoff: 13.31] • Optimalcurrent’sstrategy31% FLOW, 69% NO FLOW The similarity is striking Davenport’s finding went unchallenged for several years Until …
Currentis not vicious • Kozelka 1969 and Read, Read 1970 pointed out a seriousflaw: • The currentis not a reasoningentityand cannotadjust to fishermenchangingtheirstrategies. • HencefishermenshoulduseExpected Value principle: • Expectedpayoff of the fishermen: • IN: 0.25 x 17.3 + 0.75 x 11.5 = 12.95 • OUT: 0.25 x (-4.4) + 0.75 x 20.6 = 14.35 • IN-OUT: 0.25 x 5.2 + 0.75 x 17.0 = 14.05 • Hence, all of the fishermenshouldfishOUTside. • Maybe, theyare not welladaptedafterall
Currentmay be viciousafterall • The currentdoes not reason, but itisveryrisky to fishoutside. • Evenif the currentruns 25% of the timeON AVERAGE, itmight run considerablymoreor less in the short run of a year. • Suppose one yearit ran 35% of the time. Expectedpayoffs: • IN: 0.35 x 17.3 + 0.65 x 11.5 = 13.53 • OUT: 0.35 x (-4.4) + 0.65 x 11.5 = 11.85 • IN-OUT: 0.35 x 5.2 + 0.65 x 17.0 = 12.87. • By treating the current as theiropponent, fishermenGUARANTEEthemselvespayoff of atleast13.31. • Fishermenpay 1.05 pounds as insurancepremium
Decisionmaking under uncertainty Regretmatrix
Decisionmaking under uncertainty Regretmatrix
Father: “I want you to marry a girl of my choice” Son: “I will choose my own bride!” Father: “But the girl is Bill Gates’ daughter.” Son: “Well, in that case…ok” Next, the father approaches Bill Gates. Father: “I have a husband for your daughter.” Bill Gates: “But my daughter is too young to marry!” Father: “But this young man is a vice‐president of the World Bank.” Bill Gates: “Ah, in that case…ok” Finally the father goes to see the president of the World Bank. Father: “I have a young man to be recommended as a vicepresident.” President: “But I already have more vice‐ presidents than I need!” Father: “But this young man is Bill Gates’s son‐in‐law.” President: “Ah, in that case…”