The Effects of Framing, Reflection, Probability, and Payoff on Risk Preference

Abstract (Via Kuhberger @Schulte-mecklenbeck.com)

A meta-analysis of Asian-disease-like studies is presented to identify the factors which determine risk preference. First the
confoundings between probability levels, payoffs, and framing conditions are clarified in a task analysis. Then the role of framing, reflection, probability, type, and size of payoff is evaluated in a meta-analysis. It is shown that bidirectional framing effects exist for gains and for losses. Presenting outcomes as gains tends to induce risk aversion, while presenting outcomes as losses tends to induce risk seeking. Risk preference is also shown to depend on the size of the payoffs, on the probability levels, and on the type of good at stake (money/property vs human lives). In general, higher payoffs lead to increasing risk aversion. Higher probabilities lead to increasing risk aversion for gains and to increasing risk seeking for losses. These findings are confirmed by a subsequent empirical test. Shortcomings of existing formal theories, such as prospect theory, cumulative prospect theory, venture theory, and Markowitz’s utility theory, are identified. It is shown that it is not probabilities or payoffs, but the framing condition, which explains most variance. These findings are interpreted as showing that no linear combination of formally relevant predictors is sufficient to capture the essence of the framing phenomenon.

Probabilities can exert their influence on the framing effect via the following three ways:
1. Probabilities can be influential in a direct, unmediated way: the higher the probability of winning, the more attractive is the risky option for gains, and the higher the probability of losing the more unattractive is the risky loss.

2. The second, and related, way for probabilities to influence choices is by making the anticipation of winning or losing more or less salient. A high probability of winning may make it easier to imagine getting the gain than a low probability.

3. A third way for probabilities to influence choices is by the confoundings discussed above.

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27. June 2009 by Miguel Barbosa
Categories: Behavioral Economics, Curated Readings | Leave a comment

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