Christoph Bühren and Marco Pleßner, “The Trophy Effect.” Journal of Behavioral Decision Making 27: 363-377, 2014 [pre-publication version pdf here].
• For everyday (convenience) goods, the endowment effect is reflected in about a 2-to-1 ratio of willingness-to-accept (payment to relinquish a good) to willingness-to-pay (to acquire the good). But for environmental goods or tickets to a basketball game, the ratio could be much higher. The gap is smaller when folks are in a good mood and larger when folks are in a bad mood, though sadness (as opposed to a bad mood) tends to reduce the gap.
• The authors conduct a series of experiments involving endowing half of the subjects with a pen, under four treatment conditions. All the subjects know that the pen, though a nice one, could be purchased at a nearby shop for 2.10 euro.
• In the Baseline treatment, half the subjects are given pens, then, willingness-to-accept (wta) and willingness-to-pay (wtp) are assessed. In the Trophy treatment, there is a 15-minute math quiz. Those who score above the median receive a pen, and become potential sellers in the exchange game to follow.
• In the Work treatment, sellers are chosen randomly, but then they must take the math quiz before being given their pen. (They worked for their pen, they are told, though their performance on the quiz is immaterial.) In the Lottery treatment, everyone is informed that there is a lottery for pens, and the half who win the lottery are given pens.
• The baseline treatment results in the usual (but weird!) endowment effect, with wta about twice as high as wtp. The Lottery treatment results in a slightly higher, but statistically equivalent, ratio. (Losers in the lottery don’t have a wtp that is lower than in the baseline treatment.) The Work treatment gives similar results, though the average wta (for those diligent workers!) is enhanced.
• The broader “winning” condition (Trophy plus Lottery Treatments) yields a higher wta (compared to the other two treatments). The broader “work” condition (Trophy plus Work) yields a jump in wta, too. The Trophy treatment has a huge impact on wta, which went to 4.40 euro – and also dropped wtp from 1 euro to .5 euro; the wta/wtp ratio assessed at the medians is 9.6! It looks like the work element (taking the test) is slightly more important than the winning element in driving the trophy effect. And math quiz “losers” don’t like having the pen around to remind them of their failure.
• The authors replicate a standard finding, that people do not anticipate the endowment effect. In the Work condition, they expect their wta to be less than 2 euro, but it is over 3.5 euro after the 15-minute quiz.
• In one study, participants are asked how likely they think it is that their math test had been mis-graded. Trophy winners seem to decrease their wta when doubt of their deserving creeps into their mind. In yet another study, there’s (1) a two-hour delay or (2) a one-week delay before the wta and wtp valuations are assessed. With a one-week delay, we are back at the baseline endowment effect: the trophy effect evaporates. And the two-hour delay is statistically equivalent to the one-week delay.
Wednesday, January 18, 2017
Monday, January 16, 2017
Morewedge and Giblin (2015) Look to Explain the Endowment Effect
Carey K. Morewedge and Colleen E. Giblin, “Explanations of the Endowment Effect: An Integrative Review.” Trends in Cognitive Sciences 19(6): 339-348, June, 2015 [pdf].
• Endowment effects tend to be demonstrated in one of two ways: (1) the “exchange paradigm,” where people who are endowed with a good are less willing to trade it for another good than pre-endowment preferences would suggest; and, (2) differences between the willingness to pay (wtp) for a good by a non-owner and the willingness to accept payment (wta) by an owner – differences which seem to materialize about the time the non-owner becomes an owner.
• Loss aversion is a standard underlying explanation for the endowment effect; once you own a good (or even expect to), your ownership becomes your reference point, and situations where you no longer own it are evaluated as losses relative to the reference point.
• The authors look at five underlying mechanisms that are claimed to give rise to loss aversion and endowment effects, and offer a more general framework: “attribute sampling bias.”
• Buyers and sellers pay attention to reference prices (low for buyers, high for sellers) that will increase their transactional utility. Prices are just one example of how buying and selling activate different cognitive frames that direct attention and recall to different pieces of information. Buyers and sellers do not have the same information readily in mind, so the endowment effect does not arise because they value identical attributes differently. People even have trouble recalling frame-inconsistent information.
• Psychological ownership raises wta for two reasons: (1) ownership creates a connection between your identity and the good; the better that you feel about yourself, the better you will feel about the good. Losing the good can seem like a threat to your identity. (2) ownership helps you remember good feelings about the good, which otherwise might be harder to access.
• Their attribute sampling bias explanation resembles the well-known phenomenon where people seek out information that confirms their current beliefs.
• Sadness tends to reduce or reverse the endowment effect – it creates an implicit interest in changing your circumstances, so non-owners are more willing to acquire a good and owners are more willing to sell a good. But most frames in the exchange setting (other than sadness) tend to bias people towards maintaining the status quo.
• People are eager to trade away a “bad”, which can’t be explained by some other approaches to endowment effects, where whatever you own you value more highly. Further, endowment effects are higher for those goods (like environmental goods) that have vague attributes, giving more room for attention to a biased sample of attributes to take effect.
• Endowment effects tend to be demonstrated in one of two ways: (1) the “exchange paradigm,” where people who are endowed with a good are less willing to trade it for another good than pre-endowment preferences would suggest; and, (2) differences between the willingness to pay (wtp) for a good by a non-owner and the willingness to accept payment (wta) by an owner – differences which seem to materialize about the time the non-owner becomes an owner.
• Loss aversion is a standard underlying explanation for the endowment effect; once you own a good (or even expect to), your ownership becomes your reference point, and situations where you no longer own it are evaluated as losses relative to the reference point.
• The authors look at five underlying mechanisms that are claimed to give rise to loss aversion and endowment effects, and offer a more general framework: “attribute sampling bias.”
• Buyers and sellers pay attention to reference prices (low for buyers, high for sellers) that will increase their transactional utility. Prices are just one example of how buying and selling activate different cognitive frames that direct attention and recall to different pieces of information. Buyers and sellers do not have the same information readily in mind, so the endowment effect does not arise because they value identical attributes differently. People even have trouble recalling frame-inconsistent information.
• Psychological ownership raises wta for two reasons: (1) ownership creates a connection between your identity and the good; the better that you feel about yourself, the better you will feel about the good. Losing the good can seem like a threat to your identity. (2) ownership helps you remember good feelings about the good, which otherwise might be harder to access.
• Their attribute sampling bias explanation resembles the well-known phenomenon where people seek out information that confirms their current beliefs.
• Sadness tends to reduce or reverse the endowment effect – it creates an implicit interest in changing your circumstances, so non-owners are more willing to acquire a good and owners are more willing to sell a good. But most frames in the exchange setting (other than sadness) tend to bias people towards maintaining the status quo.
• People are eager to trade away a “bad”, which can’t be explained by some other approaches to endowment effects, where whatever you own you value more highly. Further, endowment effects are higher for those goods (like environmental goods) that have vague attributes, giving more room for attention to a biased sample of attributes to take effect.
Viscusi and Gayer (2015) on Reasons to Distrust Government Nudges
W. Kip Viscusi and Ted Gayer, “Behavioral Public Choice: The Behavioral
Paradox of Government Policy.” Harvard Journal of Law & Public Policy
38(3): 973-1007, 2015 [pdf].
• Behavioral departures from full rationality are often used as justifications for government interventions in markets. But the resulting government policies can institutionalize, not rectify, the rationality shortfalls.
• Regulators themselves possess rationality shortfalls, and there are features of the environment in which regulators operate that push them away from pursuing first-best policies.
• If the median voter possesses biases, then a democratic government is likely to share those biases.
• Less-than-rational individuals tend to bear the costs of their errors themselves – not so with regulators. Further, individuals might have enhanced incentives (relative to bureaucrats) to acquire relevant information. Regulators, like all of us, can be overconfident in their abilities.
• Can we trust the claims that people are less-than-rational, or at least the universality of the claims? People are heterogeneous, and what looks like a mistake might reflect specific, reasonable preferences.
• Many consumer durables now have energy efficiency mandates, justified by internalities. But the energy-efficiency misjudgment is far from a proven problem. The claims of energy savings tend to be engineering-based, unavailable in practice, while individual circumstances can rationalize seemingly myopic choices.
• We could be more confident in an even-handed use of behavioral economics if a lot of pre-existing mandates were being replaced by non-coercive nudges. But instead, we see behavioral economics being used to tighten regulation, not to loosen it. Notice that the less-than-complete (narrow) self-interest that behavioralists often emphasize implies that even externalities might be internalized without government policy.
• The EPA instituted a fuel economy labelling requirement that seems intended to remedy all the problems that their later efficiency mandates also targets – don’t they trust their own labelling regulation?
• In dealing with health and safety risks, government does not seem to be more rational than individuals. In practice, worst-case scenarios are over-weighted in regulatory policy; EPA methodology leads to cascading of conservative estimates so that extremely low-likelihood problems can dominate policy. Further, the number of people exposed to a risk, which should be central in formulating policy, is ignored.
• Increases in risk are a sort of loss, and loss aversion kicks in – in the form of alarmist regulatory responses to ebola, terrorism, etc.
• The FDA fears errors of commission much more than errors of omission. [Nonetheless, the evidence base is weak – look how often risks are revealed only after approval; then there are off-label uses, which are quite legal, despite not having been tested in the usual sorts of controlled trials.]
• If organic veggies carry less risk than non-organic vegetables, but they cost more, it could still be better health-wise for people to eat more, non-organic veggies.
• For people to accept a small increase in risk often involves a payment some six times larger than they would pay for the same reduction in risk – a reflection of loss aversion. The “first, do no harm” principle leads to a similar effect in policy. It is often hard to identify victims of the FDA’s failure to approve a useful drug.
• Agencies can have tunnel vision, treating their issue in isolation. In OSHA, for example, regulators are not even allowed to look at the costs of fixing a hazard. One result: costs per life saved vary widely across domains, in ways that seem to be far from optimal.
• Behavioral departures from full rationality are often used as justifications for government interventions in markets. But the resulting government policies can institutionalize, not rectify, the rationality shortfalls.
• Regulators themselves possess rationality shortfalls, and there are features of the environment in which regulators operate that push them away from pursuing first-best policies.
• If the median voter possesses biases, then a democratic government is likely to share those biases.
• Less-than-rational individuals tend to bear the costs of their errors themselves – not so with regulators. Further, individuals might have enhanced incentives (relative to bureaucrats) to acquire relevant information. Regulators, like all of us, can be overconfident in their abilities.
• Can we trust the claims that people are less-than-rational, or at least the universality of the claims? People are heterogeneous, and what looks like a mistake might reflect specific, reasonable preferences.
• Many consumer durables now have energy efficiency mandates, justified by internalities. But the energy-efficiency misjudgment is far from a proven problem. The claims of energy savings tend to be engineering-based, unavailable in practice, while individual circumstances can rationalize seemingly myopic choices.
• We could be more confident in an even-handed use of behavioral economics if a lot of pre-existing mandates were being replaced by non-coercive nudges. But instead, we see behavioral economics being used to tighten regulation, not to loosen it. Notice that the less-than-complete (narrow) self-interest that behavioralists often emphasize implies that even externalities might be internalized without government policy.
• The EPA instituted a fuel economy labelling requirement that seems intended to remedy all the problems that their later efficiency mandates also targets – don’t they trust their own labelling regulation?
• In dealing with health and safety risks, government does not seem to be more rational than individuals. In practice, worst-case scenarios are over-weighted in regulatory policy; EPA methodology leads to cascading of conservative estimates so that extremely low-likelihood problems can dominate policy. Further, the number of people exposed to a risk, which should be central in formulating policy, is ignored.
• Increases in risk are a sort of loss, and loss aversion kicks in – in the form of alarmist regulatory responses to ebola, terrorism, etc.
• The FDA fears errors of commission much more than errors of omission. [Nonetheless, the evidence base is weak – look how often risks are revealed only after approval; then there are off-label uses, which are quite legal, despite not having been tested in the usual sorts of controlled trials.]
• If organic veggies carry less risk than non-organic vegetables, but they cost more, it could still be better health-wise for people to eat more, non-organic veggies.
• For people to accept a small increase in risk often involves a payment some six times larger than they would pay for the same reduction in risk – a reflection of loss aversion. The “first, do no harm” principle leads to a similar effect in policy. It is often hard to identify victims of the FDA’s failure to approve a useful drug.
• Agencies can have tunnel vision, treating their issue in isolation. In OSHA, for example, regulators are not even allowed to look at the costs of fixing a hazard. One result: costs per life saved vary widely across domains, in ways that seem to be far from optimal.
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