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Daniel Kahneman, who won the 2002 Nobel Memorial Prize in Economics for his work developing prospect theory. Prospect theory is a theory of behavioral economics, judgment and decision making that was developed by Daniel Kahneman and Amos Tversky in 1979. [1]
where is the value function (typical form shown in Figure 1), is the weighting function (as sketched in Figure 2) and ():=, i.e. the integral of the probability measure over all values up to , is the cumulative probability. This generalizes the original formulation by Tversky and Kahneman from finitely many distinct outcomes to infinite (i.e ...
In 1979, Daniel Kahneman and his associate Amos Tversky originally coined the term "loss aversion" in their initial proposal of prospect theory as an alternative descriptive model of decision making under risk. [5] "The response to losses is stronger than the response to corresponding gains" is Kahneman's definition of loss aversion.
In line with prospect theory (Tversky and Kahneman, 1979 [24]), changes that are framed as losses are weighed more heavily than are the changes framed as gains. Thus an individual owning "A" amount of a good, asked how much he/she would be willing to pay to acquire "B", would be willing to pay a value (B-A) that is lower than the value that he ...
Daniel Kahneman (/ ˈ k ɑː n ə m ə n /; Hebrew: דניאל כהנמן; March 5, 1934 – March 27, 2024) was an Israeli-American psychologist best known for his work on the psychology of judgment and decision-making as well as behavioral economics, for which he was awarded the 2002 Nobel Memorial Prize in Economic Sciences together with Vernon L. Smith.
Tversky & Kahneman (1986) illustrated the certainty effect by the following examples. First, consider this example: Which of the following options do you prefer? A. a sure gain of $30; B. 80% chance to win $45 and 20% chance to win nothing; In this case, 78% of participants chose option A while only 22% chose option B.
In their 1992 paper, Kahneman and Tversky found the median coefficient of loss aversion to be about 2.25, i.e., losses hurt about 2.25 times more than equivalent gains reward. [ 25 ] Non-linear probability weighting: Decision makers overweigh small probabilities and underweigh large probabilities—this gives rise to the inverse-S shaped ...
Local representativeness is an assumption wherein people rely on the law of small numbers, whereby small samples are perceived to represent their population to the same extent as large samples (Tversky & Kahneman 1971). A small sample which appears randomly distributed would reinforce the belief, under the assumption of local representativeness ...