What is it?
Prospect theory describes how people evaluate risk and make decisions under uncertainty. There are four elements of prospect theory: 1) reference dependence, 2) loss aversion, 3) diminishing sensitivity, and 4) probability weighting.
Reference dependence - People derive utility from gains and losses, measured relative to some reference point, rather than from absolute levels of wealth.
Loss aversion - People are much more sensitive to losses - even small losses - than to gains of the same magnitude. Informally, loss aversion is generated by making the value function steeper in the region of losses than in the region of losses rather than in the region of gains.
Diminishing sensitivity - Third, as shown in Figure 1, the value function is concave in the region of gains but convex in the region of losses. This element of prospect theory is known as diminishing sensitivity because it implies that, while replacing a $100 gain (or loss) with a $200 gain (or loss) has a significant utility impact, replacing a $1,000 gain (or loss) with a $1,100 gain (or loss) has a smaller impact.
Probability weighting - The concavity over gains captures the finding that people tend to be risk averse over moderate probability gains: they typically prefer a certain gain of $500 to a 50 percent chance of $1,000. However, people also tend to be risk seeking over losses: they prefer a 50 percent chance of losing $1,000 to losing $500 for sure. This motivates the convexity over losses.
Why is this theory important for behaviour change?
It demonstrates that people systematically violate the predictions of expected utility theory, economists' workhorse model of decision making under risk. It demonstrates that people think in terms of expected utility relative to a reference point (e.g. current wealth) rather than absolute outcomes. It indicates that people are loss averse and are more willing to take risks to avoid a loss. Prospect theory has implications for decision making and the cognitive processes which impact preferences in the context of risk and uncertainty.
How could you apply this theory?
When studying what motivates a decision, keep in mind that their decisions will most likely be made based on the potential value of losses and gains rather than the final outcome. People would prefer a certain small win over taking a risky bet for a potentially better outcome. Frame choices in terms of the certain small wins rather than chances. For example, sign up to our newsletter and get $10 off your next purchase, rather than sign up to our newsletter for the chance to win a $500 voucher.
Example of theory applied
Sydnor (2010) studies the insurance decisions of 50,000 customers of a large home insurance company. The main decision that these households have to make is to choose a deductible from a menu of four possibilities: $100, $250, $500, and $1,000. Sydnor finds that the households that choose a $500 deductible pay an average premium of $715 per year. In choosing this policy, these households all turned down a policy with a $1,000 deductible whose average premium was just $615 per year. Given that the annual claim rate is approximately 5 percent, these households agreed to pay $100 a year to insure against a 5 percent chance of paying an additional $500 in the event of a claim! In an expected utility framework, this choice can only be rationalized by unreasonably high levels of risk aversion.