Summary: In economics and decision theory, loss aversion refers to people’s tendency to strongly prefer avoiding losses to acquiring gains. Some studies suggest that losses are twice as powerful, psychologically, as gains. Loss aversion was first convincingly demonstrated by Amos Tversky and Daniel Kahneman.

This leads to risk aversion when people evaluate a possible gain; since people prefer avoiding losses to making gains. This explains the curvilinear shape of the prospect theory utility graph in the positive domain. Conversely people strongly prefer risks that might possibly mitigate a loss (called risk seeking behavior).

Loss aversion may also explain sunk cost effects.

Loss aversion implies that one who loses $100 will lose more satisfaction than another person will gain satisfaction from a $100 windfall. In marketing, the use of trial periods and rebates try to take advantage of the buyer’s tendency to value the good more after he incorporates it in the status quo.

Note that whether a transaction is framed as a loss or as a gain is very important to this calculation: would you rather get a $5 discount, or avoid a $5 surcharge? The same change in price framed differently has a significant effect on consumer behavior. Though traditional economists consider this “endowment effect” and all other effects of loss aversion to be completely irrational, that is why it is so important to the fields of marketing and behavioral finance. The effect of loss aversion in a marketing setting was demonstrated in a study of consumer reaction to price changes to insurance policies.[1] The study found price increases had twice the effect on customer switching, compared to price decreases.

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Experimental Tests of the Endowment Effect and the Coase Theorem

Contrary to theoretical expectations, measures of willingness-to-accept greatly exceed measures of willingness-to-pay. This paper reports several experiments that demonstrate that this “endowment effect” persists even in market settings with opportunities to learn. Consumption objects (e.g., coffee mugs) are randomly given to half the subjects in an experiment. Markets for the mugs are then conducted. The Coase theorem predicts that about half the mugs will trade, but observed volume is always significantly less. When markets for “induced-value” tokens are conducted, the predicted volume is observed, suggesting that transactions costs cannot explain the undertrading for consumption goods.

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