Prospect Theory: Difference between revisions
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For instance, Kahneman and Tversky's (1979) lottery experiment. | For instance, Kahneman and Tversky's (1979) lottery experiment. | ||
25% chance of winning $3,000 | Candidates were given the two following choices: | ||
20% chance of winning $4,000 | 25% chance of winning $3,000 and | ||
20% chance of winning $4,000 | |||
65% chose latter | 65% chose latter | ||
But | But | ||
100% chance of winning $3,000 | 100% chance of winning $3,000 and | ||
80% chance of winning $4,000 | 80% chance of winning $4,000 | ||
80% chose former | 80% chose former | ||
Prospect Theory similar to Expected Utility Theory in that | Prospect Theory similar to Expected Utility Theory in that each possible outcome is weighted. However, they are not weighted with corresponding probabilities determined by a utility function. Instead, the utility of each outcome is determined by what is called a "value function." This value function is based on the idea that "people behave as if they regard extremely improbable events as impossible and extremely probable events as certain." (Shiller 1997, 4). Thus the model assigns a zero probability to extremely improbable events and a one (hundred percent) probablity to extremely probable events. | ||
Thus | |||
Latest revision as of 15:43, 9 May 2006
Prospect Theory is a mathematically-formulated alternative to the theory of expected utility maximization.
Expected Utility theory is based on rational behavior of agents and yet has "systematically mispredicted human behavior in at least certain circumstances." (Schiller, 1997)
For instance, Kahneman and Tversky's (1979) lottery experiment.
Candidates were given the two following choices:
25% chance of winning $3,000 and 20% chance of winning $4,000
65% chose latter
But
100% chance of winning $3,000 and 80% chance of winning $4,000
80% chose former
Prospect Theory similar to Expected Utility Theory in that each possible outcome is weighted. However, they are not weighted with corresponding probabilities determined by a utility function. Instead, the utility of each outcome is determined by what is called a "value function." This value function is based on the idea that "people behave as if they regard extremely improbable events as impossible and extremely probable events as certain." (Shiller 1997, 4). Thus the model assigns a zero probability to extremely improbable events and a one (hundred percent) probablity to extremely probable events.
