# ch6.docx - Imperfect information the situation in which...

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Imperfect information: the situation in which consumers face uncertainty when making their consumption decisions Real World Examples: Weather related decisions Dating Insurance Job-related issues Imperfect information makes it harder to make ex-ante (based on forecasts or expected results) rational consumption decisions. Expected value: the sum of all possible outcomes, weighted by its respective probability of occurrence. Lottery: a simple way to identify or characterize the choices available to an individual under uncertainty. We denote lotteries by the vector: L=(x1, prob1; x2, prob2;……xn, probN) Where X is winnings experienced under option I and prob is its probability of occurring

Unformatted text preview: Multiply X and prob and add all the occurrences together. Gamble 1(coin flip 50/50): win \$100, prob ½; lose \$.50, prob ½ Gamble 2: win 200, prob ½, lose \$100, prob ½ Gamble 3: win 20,000, prob ½; loss 10,000, prob ½ Expected utility: the expected value of utility over all possible outcomes. Expected utility= P1U(X1) + P2U(X2) etc etc Initial Income= M0 EU of coin toss game= P1*U(M0+X1)+ P2*U(M0-X2) First probability*utility*(initial income+winnings)+ second probability*utility*(initial income – potential loss) Utility= square root of initial income...
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