Loss aversion

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In prospect theory, loss aversion refers to the tendency for people to strongly prefer avoiding losses than acquiring gains. Some studies suggest that losses are as much as twice as psychologically powerful 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.

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.

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[edit] Can loss aversion ever be rational?

There is an important critique of the view held by economists that this behaviour is irrational. The implicit assumption of conventional economics is that the only relevant metric is the magnitude of the absolute change in expenditure. In the above example, saving 5% is considered equivalent to avoiding paying 5% extra. This is not the only rational interpretation. Another view is that the most important metric is the magnitude of the relative change in wealth of the decision-maker. Again, referring to the above example, a 5% discount is then not equivalent to avoiding a 5% surcharge. The reasoning is as follows.

Take a hypothetical item with a base cost of $1000, and consider two possible scenarios:

  • In the first scenario, the buyer expects to pay $1000, but then is offered a 5% discount. The price is then $950. The change represents a 5% saving.
  • In the second scenario, there is a surcharge of 5%, or $50. The buyer expects to pay $1050. Avoiding the surcharge would mean a price of $1000. Buyers see this as a savings of $50 on what they expected to pay: $1050. Thus, the perceived savings is 50/1050 x 100% = approx. 4.76%.

When the savings relative to the remaining wealth (or stock of money) is different, the value of the transaction changes accordingly. When using this interpretation, decisions made by consumers are not necessarily irrational.

Taking this to an extreme, if a person has only $1000, getting $1000 simply doubles their wealth (which would be desirable), but losing $1000 would wipe them out completely (which might be a matter of life and death). In this case, given the need for money for food and shelter in order to survive, the individual will be far more motivated to avoid losing $1000 than to try to gain $1000.

In addition, it has been asserted that the effect of relative evaluation is more pronounced the greater the potential amount saved is relative to the total amount the decision-maker has to spend.

All of the above effects can be expressed in terms of the utility function of money, and, in particular, not regarding money as a linear measure of utility.

[edit] An Alternative Example

Imagine that your country is preparing for an outbreak of a disease which is expected to kill 600 people. Given the choice between two vaccination schedules, Program A which will save 200 and Program B which will save all 600 with probability 1/3, most will choose Program A.

However, if the question is framed as:

Imagine that your country is preparing for an outbreak of a disease which is expected to kill 600 people. Given the choice between two vaccination schedules, Program C which will allow 400 people to die and Program D which will let no one die with probability 1/3 and all 600 will die with probability 2/3, most people will choose option D.

This is an example of loss aversion: the two situations are identical in quantitative terms, but in the second one the decision maker is losing instead of saving lives, thus setting 0 lives lost as the status quo from which losses are measured, making the sure loss of 400 people more loathsome than the probable loss of 600.

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