Abstract

Modern scholarship on decision behavior dates from the late 1940s. But that scholarship has been preoccupied with two ideas that are much older. One is the notion of expected utility, first articulated in the scholarly literature by Daniel Bernoulli in 1738. In its simplest form, the expected utility concept applies to monetary gambles. Imagine you are asked to choose between two gifts, either gamble G, which you would then play and get either $9 or nothing, or else a simple, direct payment of $3. As shown in the decision tree in figure 10.1, you receive gamble G's $9 payoff if the toss of a fair die yields one or two pips, but you receive nothing otherwise. (In decision trees, choice points are represented by square nodes, chance points by circular nodes.) The expected value or expectation of a gamble is the sum of its payoffs, each weighted (i.e., multiplied) by its probability. Thus, the expected value of G is EV(G) = (1/3)($9) + (2/3)($0) = $3, the same as the direct payment. So, if you generally make decisions like this one so as to maximize expected value, you would be indifferent between the present options. However, if you are like most people, you are not indifferent. Instead, you are risk‐averse, preferring the guaranteed $3. Why?