14127_lec1_pt1

14127_lec1_pt1 - 14.127 Behavioral Economics (Lecture 1)...

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14.127 Behavioral Economics (Lecture 1) Xavier Gabaix February 5, 2003
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1O v e r v i e w Instructor : Xavier Gabaix Time 4-6:45/7pm, with 10 minute break. Requirements: 3 problem sets and Term paper due September 15, 2004 (meet Xavier in May to talk about it)
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2 Some Psychology of Decision Making 2.1 Prospect Theory (Kahneman-Tversky, Econometrica 79) Consider gambles with two outcomes: { with probability s ,and | with probability 1 3 s where { D 0 D | .
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Expected utility (EU) theory says that if you start with wealth Z then the (EU) value of the gamble is Y = sx ( Z + { )+(1 3 s ) x ( Z + | ) Prospect theory (PT) says that the (PT) value of the game is Y = < ( s ) x ( { )+ < (1 3 s ) x ( | ) where < is a probability weighing function. In standard theory < is linear.
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In prospect theory < is concave frst and then convex, e.g. < ( s )= s / s / +(1 3 s ) / For some / M (0 @ 1). The fgure gives < ( s )Fo r / = ? 8 1 0.75 0.5 0.25 0 1 0.75 0.5 0.25 0 p
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2.1.1 What does the introduction of the weighing function < mean? < ( s ) Bs for small s . Small probabilities are overweighted, too salient. E.g. people play a lottery. Empirically, poor people and less educated people are more likely to play lottery. Extreme risk aversion. < ( s ) As for s close to 1. Large probabilities are underweight. In applications in economics < ( s )= s is often used except for lotteries and insurance
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2.1.2 Utility function x We assume that x ( {
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14127_lec1_pt1 - 14.127 Behavioral Economics (Lecture 1)...

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