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Uncertainty effect

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For example, in the original work on the uncertainty effect by Uri Gneezy, John A. List, and George Wu (2006), individuals were willing to pay $38 for a $50 gift card, but were only willing to pay $28 for a lottery ticket that would yield a $50 or $100 gift card with equal probability.

This effect is considered to be a violation of "internality" (i.e., the proposition that the value of a risky prospect must lie somewhere between the value of that prospect’s best and worst possible realizations) which is central to prospect theory, expected utility theory, and other models of risky choice. Additionally, it has been proposed as an explanation for a host of naturalistic behaviors which cannot be explained by dominant models of risky choice, such as the popularity of insurance/extended warranties for consumer products.

Origins

Research on the uncertainty effect was first formally conducted by Uri Gneezy, John A. List, and George Wu in the early 2000s, though it follows in the footsteps of a large body of work devoted to understanding decision making under risk. As their starting point, Gneezy, List, and Wu noted that most models of risky choice assume that when presented with a risky prospect individuals engage in a balancing exercise of sorts in which they compare the best possible outcomes they might realize to the worst possible outcomes they might realize (e.g., in a gamble that gives a 50-50 chance to win $500 or $1,000, individuals might compare these two outcomes to one another). Within this type of schema, individuals are also expected to weight the value (or utility) of each of these discrete outcomes in accordance with the probability that each will occur.

While expected utility theory and prospect theory differ in terms of how outcomes are evaluated and weighted, they both nonetheless rely upon what Gonzalez, List, and Wu term as the "internality axiom." This axiom specifically posits that the value of some risky prospect must lie between the value of that prospect's best and worst possible outcomes. Formally, for some risky prospect L=(x,p,y) which offers p probability of earning x and 1−p probability of earning y (where x is strictly greater than y), individuals' elicited values for x, y, and L should satisfy the following inequality: V(x)≥V(L)≥V(y).

In a series of studies conducted by Gneezy, List, and Wu, and in follow-up work conducted by Uri Simonsohn (among others), individuals were repeatedly shown to violate this assumption. For example:

  • In an initial laboratory study which compared the willingness to pay (WTP) values for an even chance at winning a $50 giftcard or a $100 giftcard to the values of a $50 or $100 giftcard in isolation (all restricted for use at a local bookstore), individuals were – on average – willing to pay $26.10 for the $50 giftcard, $45.00 for the $100 giftcard, but only $16.12 for the lottery
  • In follow-up laboratory studies with a modified elicitation format, and which also compared items with different use cases (e.g., a $100 giftcard for use at a restaurant versus a $50 giftcard for use at a bookstore; a voucher which yielded a free meal for four at a restaurant versus a $50 giftcard for use at a bookstore; etc.), individuals ascribed lower WTP values to a lottery that yielded one of two positive outcomes with equal probability than they did to the relevant positive outcomes in isolation
  • In a field study with experienced baseball card traders, individuals were willing to pay significantly less for a lottery that yielded either a low-value card or a high-value card with equal probability ($34.09) than they were for the low-value card ($52.72) or the high-value card ($65.02) in isolation

Within this body of work, the uncertainty effect was also shown to extend to choice and to consideration of delayed outcomes; it was also shown not to be a consequence of poorly comprehending the lottery.

Among other explanations, it has been proposed that the uncertainty effect might arise as a consequence of individuals experiencing some form of disutility from risk.

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