Taylor Swift tickets and the endowment effect

The Wall Street Journal reported last month (paywalled, but see here for an alternative):

Taylor Swift ended the European leg of her Eras tour on Tuesday at London’s Wembley Stadium, delighting nearly 100,000 cheering “Swifties”—but leaving many who couldn’t snag a ticket disappointed. One reason: the failure of the secondary market in tickets. Swifties have the same mental biases as the rest of us, making them reluctant to sell even at eye-watering prices.

Markets work on the basis of supply and demand setting a price. If there is more demand than supply, the price rises until fewer people are willing to buy and more are willing to sell. The basic problem is that Swifties mostly aren’t willing to sell, so the price soars until demand is destroyed—hitting well over $1,000 for many tickets...

I have firsthand experience: My eldest offspring snagged tickets months ago to take my besequinned wife (but not me) to the latest Eras concert. By this week the tickets were changing hands at more than eight times face value, and both agreed they wouldn’t buy them at such a high price.

Given they wouldn’t buy at this price they ought to be, on traditional economic assumptions, willing sellers. But both dismissed the idea out of hand—and not merely because trading tickets is trickier than trading shares. There probably would be some ludicrous price at which they would have parted with the tickets, but even a quick profit of eight times their outlay in a matter of months wouldn’t do it.

The WSJ rightly offers up loss aversion and the endowment effect as explanations for this behaviour. Loss aversion is the idea that decision-makers value losses much more than otherwise-equivalent gains. The pain of giving something up is worth much more than the pleasure of gaining that same thing. One consequence of loss aversion is the endowment effect. Since giving something up makes people very unhappy (because they are loss averse), people prefer to hold onto the things that they already have. That means that, when a person owns something, like a Taylor Swift ticket, they have to be given much more to compensate them for giving it up than what they would have been willing to pay to get it in the first place.

This applies to lots of things, not just Taylor Swift tickets (although, honestly, Taylor Swift tickets was the exact example that I used in my ECONS102 class earlier this trimester). The original research example that described endowment effects, by Daniel Kahneman, Jack Knetsch, and Richard Thaler, used free coffee mugs to demonstrate the effect. People given a free coffee mug were generally unwilling to exchange it for a pen, and people given a free pen were generally unwilling to exchange it for a coffee mug.

Returning to concert tickets, tickets to the Oasis reunion tour sold out fairly quickly this week - I bet those who have those tickets also wouldn't be willing to give them up cheaply. A further interesting implication of the endowment effect arises in the case of Oasis tickets, since according to this tweet from the band's official X account:

Tickets can ONLY be resold, at face value, via @TicketmasterUK and @Twickets.

If the endowment effect applies, few ticket-holders will be willing to part with their tickets at face value. These secondary markets are unlikely to help many people who originally missed out to secure tickets. I guess we will see.

[HT: Cyril Morong at The Dangerous Economist, for the WSJ article]

How much is your job worth to you?

A rational decision-maker weighs up the cost and benefits of the alternatives available to them before they decide which alternative is the best option for them. When faced with a 'yes or no' decision, 'yes' is the best alternative when the benefits outweigh the costs (and 'no' is the best alternative when the costs outweigh the benefits). When choosing between mutually exclusive alternatives, the best alternative is the one that provides the greatest net benefit (the difference between benefits and costs).

The costs and benefits might be monetary, but not necessarily. And even if the costs and benefits are not directly monetary, they may still be measurable in dollars. For example, how much is your job worth to you? It seems like an odd question to ask. You didn't 'buy' your job, after all (I hope!). But, as we will come to a bit later, this question has some important policy implications.

How can we work out how much a job is worth to the worker? Since the worker has their job already, we can't use how much they are willing to pay to get a job. However, we can try to find out how much the worker would be willing to accept in order to quit their job. So, how much would you have to be paid to quit your job?

That is the question that Soumaya Keynes asks in this recent article in the Financial Times (paywalled):

A new working paper by researchers at the Centre for Economic Policy Research and Stanford University, deploys this approach, asking Europeans what they would do if they received sums ranging from €5,000 to €100,000.

Below around €25,000, people say they would plough on with work. But for sums between that threshold and €100,000, their likelihood of working falls by 3 percentage points on average. Women, as well as people who are older, who have less debt or who are close to retirement are more likely to drop out.

What does that imply about the value of a job? If paying someone €100,000 reduces their likelihood of working by three percentage points on average, then reducing their likelihood of working by 100 percentage points would cost €3.33 million (about NZ$5.85 million). [*]

Why does this matter? Keynes notes that:

The question of how one might respond to a financial windfall of this sort is a fun thought experiment. But for policymakers it carries more weight. They have to consider whether a stimulus cheque or a tax break could encourage people to quit their job, or make them deaf to pleas from desperate employers. They have to ask how much money it takes to turn someone idle.

It seems like it would take a substantial windfall to cause most people to quit their jobs, beyond the scope of what a stimulus cheque, or even a universal basic income, would provide. That doesn't mean that no one will quit after receiving even a modest windfall, but policymakers can probably rest easy about the labour market disincentive effects of windfalls.

*****

[*] Now, my ECONS102 students should recognise that this amount is probably an overestimate of the 'true value' of a job to a worker. Like all decision-makers, on average workers are loss averse - they value losses much more than otherwise-equivalent gains. One consequence of loss aversion is the endowment effect - decision-makers require more in compensation to give something up than what they would have been willing to pay to obtain it in the first place. This applies to jobs, as it does to other things. So, we might expect people to need to be paid more to give up a job, than what they would have been willing to pay to get the job in the first place. So, the estimate of €3.33 million is probably an overestimate of the 'value' of a job to a worker.

You're fooling yourself if you think you can land that plane

Almost everyone has thought about it at least once. You're on a plane, minding your own business when suddenly and unexpectedly, an announcement comes over your entertainment system that the pilots have been incapacitated and they are urgently looking for someone to land the plane. Would you put your hand up for this heroic task? Surely, with the aid of modern instruments and the guidance of air traffic control, you could do it. How hard could it be?

Very hard, it turns out, as Guido Carim Junior and co-authors outlined in this recent article in The Conversation:

We’ve all heard stories of passengers who saved the day when the pilot became unresponsive. For instance, last year Darren Harrison managed to land a twin-engine aircraft in Florida – after the pilot passed out – with the guidance of an air traffic controller who also happened to be a flight instructor.

However, such incidents tend to take place in small, simple aircraft. Flying a much bigger and heavier commercial jet is a completely different game...

Both takeoff and landing are far too quick, technical and concentration-intensive for an untrained person to pull off. They also require a range of skills that are only gained through extensive training, such as understanding the information presented on different gauges, and being able to coordinate one’s hands and feet in a certain way.

If you think you can land a plane, you're not alone. As the authors note:

Survey results published in January indicate about one-third of adult Americans think they could safely land a passenger aircraft with air traffic control’s guidance. Among male respondents, the confidence level rose to nearly 50%.

What this demonstrates is the positivity bias, or the Dunning-Kruger effect (both related to what some psychologists call self-enhancement), where people overestimate their ability. This is also why 12 percent of men think that they could score a point off Serena Williams (see here). One interesting point is that men appear to be more susceptible to positivity bias than women (at least, based on these two examples), which probably reflects over-confidence (which men may be more likely to exhibit - see here, for example).

Positively bias is another example of how real-world decision-makers are not purely rational, but quasi-rational. A purely rational decision-maker would never be tricked into thinking that they could fly (or land) a plane without any prior training. In contrast, a quasi-rational decision-maker times that they are much better at activities than they really are. It's not all bad though. Without positivity bias, we wouldn't be able to enjoy some of the funniest (or cringiest) moments on reality television:

Sometimes even economists get mixed up about the sunk cost fallacy

In an interesting article in The Conversation this week, Aaron Nicholas (Deakin University) wrote:

Have you ever encountered a subpar hotel breakfast while on holiday? You don’t really like the food choices on offer, but since you already paid for the meal as part of your booking, you force yourself to eat something anyway rather than go down the road to a cafe.

Economists and social scientists argue that such behaviour can happen due to the “sunk cost fallacy” – an inability to ignore costs that have already been spent and can’t be recovered. In the hotel breakfast example, the sunk cost is the price you paid for the hotel package: at the time of deciding where to eat breakfast, such costs are unrecoverable and should therefore be ignored.

The problem is, the example of the subpar hotel breakfast doesn't necessarily illustrate the sunk cost fallacy at all. At least, just because some people choose the subpar hotel breakfast, it doesn't mean that those people have fallen victim to the sunk cost fallacy.

To see why, let's first consider what a purely rational decision-maker might do. A purely rational decision-maker considers only the costs and benefits of each of the alternatives available to them. As Nicholas notes, sunk costs are unrecoverable and therefore ignored. In the case of the subpar hotel breakfast, the benefits of the hotel breakfast are low, but the costs are effectively zero (since it has already been paid for). The benefits are greater than the costs. However, going down the road to a cafe has greater benefits (better food), but also comes with greater costs (the time and effort to get to the cafe, plus the monetary cost of the breakfast). It's not certain that the net benefit (benefits minus costs) would be greater for the cafe breakfast than for the hotel breakfast, even for a purely rational decision-maker. So, just because someone chooses the subpar hotel breakfast, it doesn't mean that they have fallen victim to the sunk cost fallacy.

Now consider a quasi-rational decision-maker. Quasi-rational decision-makers are loss averse (they value losses greater than monetarily-equivalent gains), and engage in mental accounting. Mental accounting suggests that we keep 'mental accounts' associated with different activities. Quasi-rational decision-makers put all of the costs and benefits associated with the activity into that mental account, and when they stop that activity, they close the mental account associated with it. And since they are loss averse, they are reluctant to close an account where the costs are greater than the benefits. In the case of the hotel breakfast, the mental account for breakfast has the cost of the breakfast in it (even though it is a sunk cost), so a quasi-rational decision-maker is more likely to stay for the subpar hotel breakfast than a purely rational decision-maker, because the quasi-rational decision-maker wants benefits (however modest) to offset the cost of the breakfast before they close the breakfast mental account. It is mental accounting (and loss aversion) that makes quasi-rational decision-makers susceptible to the sunk cost fallacy.

Taken altogether, this suggests that quasi-rational decision-makers are more likely to stay for the subpar hotel breakfast. It does not mean that staying for the subpar hotel breakfast means that a decision-maker is quasi-rational (and falling victim to the sunk cost fallacy), since a purely rational decision-maker could decide on the subpar hotel breakfast as their better option, even ignoring the sunk cost.

The other examples that Nicholas uses are better. The best examples of the sunk cost fallacy involve decision-makers continuing an activity they have started, even though the remaining costs will outweigh the remaining benefits. The sunk cost fallacy (arising from mental accounting and loss aversion) keeps us in unpromising projects for too long, as well as unhappy relationships, and bad jobs. 

Most real-world decision-makers are susceptible to the sunk cost fallacy. That's why it's sometimes more notable when we see decision-makers not falling victim to it (see here and here, for example). However, when economists explain sunk costs and the sunk cost fallacy, we need to make sure that we are using examples that unambiguously illustrate the problem.

New results on the bat-and-ball problem

A bat and a ball cost $1.10 in total. The bat costs $1.00 more than the ball. How much does the ball cost?

If you guessed ten cents, you would be in the majority. You would also be quite wrong. The correct answer is five cents. This 'bat-and-ball' problem is quite famous (and you may have seen it, or a question like it, before - a variant was in a pub quiz that I competed in a few weeks ago, for example). The problem is one of three questions included in the Cognitive Reflection Test, which purports to measure whether people engage in cognitive reflection, or are more prone give into 'intuitive thinking'. It also relates to what Daniel Kahneman referred to in his book Thinking Fast and Slow as System 1 and System 2 thinking. System 1 is intuitive and automatic (and gives a ready answer of ten cents to the bat-and-ball problem), while System 2 is slower and reflective (and is more likely to lead to the correct answer of five cents).

However, a new article by Andrew Meyer (Chinese University of Hong Kong) and Shane Frederick (Yale University), published in the journal Cognition (open access), may give us reason to question the theory of System 1 and System 2 thinking (or reason to question the validity of the bat-and-ball question). Frederick is the author who introduced the Cognitive Reflection Test, so the results reported in this paper should be considered especially notable.

Meyer and Frederick conducted a number of studies of the bat-and-ball problem, showing a number of increasingly disquieting results. First:

...verifying the intuitive response requires nothing more than adding $1.00 and $0.10 to ensure that they sum to $1.10 (they do) and subtracting $0.10 from $1.00 to ensure that they differ by $1.00 (they don't). Since essentially everyone can perform these verification tests, the high error rate means that they aren't being performed or that respondents are drawing the wrong conclusion despite performing them.

If respondents aren't attempting to verify their answer, encouraging them to do so may help. We tested this in five studies involving a total of 3219 participants who were randomly assigned to either a control condition or to one of four warning conditions shown below. Two studies were administered to students who used paper and pencil. The rest were web-based surveys of a broader population...

The warnings improved performance, but not by much... This suggests that they failed to engage a checking process, or that the checking process was insufficient to remedy the error...

Specifically, only 13 percent of research participants in the pure control group got the bat-and-ball problem correct. In the treatment group that received the simplest warning (which simply warned: "Be careful! Many people miss this problem"), this increased to 23 percent. There were modest increases in performance across other studies that Meyer and Frederick report (with various different wordings of the warning), ranging from -9 percentage points to +17 percentage points. They don't report a measure of statistical significance, but the magnitude of the change is not large, and warnings to check the answer don't eliminate the intuitive response. Evidently, research participants aren't great at checking their answer. Or maybe, they simply don't perform any check at all. What about being more directive that research participants should check their answer if their original answer was ten cents:

Since these warnings were ineffective, we next tried an even stronger manipulation by telling respondents that 10 cents is not the answer. We conducted eight such experiments, with a total of 7766 participants. In five studies (three online and two paper and pencil), participants were randomly assigned to either the control condition or to a Hint condition in which the words “HINT: 10 cents is not the answer” appeared next to the response blank...

In three other studies (two online and one in-lab), we used a within-participant design in which the Hint was provided after the participant's initial response. In those studies, respondents could revise their initial (unhinted) response, and we recorded both their initial and final responses...

The hint that the answer wasn't 10 cents helped substantially, but, more notably, many – and sometimes most – still failed to solve the problem...

Receiving the hint increased performance in the bat-and-ball problem by between +17 percentage points and +23 percentage points in a between-subjects comparison (comparing research participants who received the hint with those that didn't receive the hint), and between +16 and +22 percentage points in a within-subjects comparison (where research participants could change their answer after they received the hint). The latter results lead Meyer and Frederick to note that:

Though the bat and ball problem is often used to categorize people as reflective (those who say 5) or intuitive (those who say 10), these results suggest that the “intuitive” group can – and should – be further divided into the “careless” (who answer 10, but revise to 5 when told they are wrong) and the “hopeless” (who are unable or unwilling to compute the correct response, even when told that 10 is not the answer).

Why would so many research participants still maintain that the answer is ten cents, even when they are explicitly told that ten cents is not the correct answer? Meyer and Frederick suggest that:

This result has hallmarks of simultaneous contradictory belief (Sloman, 1996), because respondents who report that $1.00 and $0.10 differ by $1.00 obviously do not actually believe this. It is also akin to research on Wason's four card task showing that participants will rationalize their faulty selections, rather than change them (Beattie & Baron, 1988; Wason & Evans, 1974). It could also be considered as an Einstellung effect (Luchins, 1942), in which prior operations blind respondents to an important feature of the current task or as an illustration of confirmation bias, in which initial erroneous interpretations interfere with the processes needed to arrive at a correct interpretation (Bruner & Potter, 1964; Nickerson, 1998).

I would put a lot of this down to motivated reasoning. However, it gets even worse:

...we ran two studies on GCS in which we asked respondents to either consider the correct answer (N = 2002) or to simply enter it (N = 1001)...

Asking respondents to consider the correct answer more than doubled solution rates, but only to 31%. Asking them to simply enter the correct answer worked better, as 77% did so, though, notably, the intuitive response emerged even here.

So, when research participants are asked to consider if the answer could be five cents, more than half still get it wrong. And even when research participants were told that the answer is five cents, and directed to write down five cents as the answer, nearly a quarter of research participants still get the answer wrong. That leads Meyer and Frederick to conclude that:

...the very existence of such manipulations (and their lack of complete efficacy) undermines a conclusion many draw from dual process theories of reasoning: that judgmental errors can be avoided merely by getting respondents to slow down and think harder...

Meyer and Frederick use all of these results (and others) to suggest that people engage in an 'approximate checker' process, wherein if the intuitive result provided by System 1 is approximately correct, then the more deliberative System 2 doesn't go through a complete process of checking. They demonstrate this with some further results that show that:

As the price difference between the bat and ball decreases, participants slow down... and solution rates rise markedly – from 14% to 57%...

So, perhaps these results are not fatal for the idea of System 1 and System 2 thinking, but psychologists and behavioural scientists need to re-think the conditions under which System 2 operates, and whether it always operates optimally. The results also suggest that the bat-and-ball problem may not actually show quite what it purports to - at least, it doesn't necessarily show cognitive reflection, as even when such reflection is explicitly invoked (through asking research participants to check their answer, or telling them to consider if the answer might be five cents), many do not exhibit such reflection (or else, they reflect and still get the answer wrong. Meyer and Frederick finish by noting that:

...the remarkable durability of that error paints a more pessimistic picture of human reasoning than we were initially inclined to accept; those whose thoughts most require additional deliberation benefit little from whatever additional deliberation can be induced.

[HT: Marginal Revolution. back in September]

Drip pricing and quasi-rational behaviour

In an interesting article in The Conversation last month, Ralf Steinhauser (Australian National University) explains the idea of drip pricing:

You see a fantastic offer, like a hotel room. You decide to book. Then it turns out there is a service fee. Then a cleaning fee. Then a few other extra costs. By the time you pay the final price, it is no longer the fantastic offer you thought.

Welcome to the world of drip pricing – the practice of advertising something at an attractive headline price and then, once you’ve committed to the purchase process, hitting you with unavoidable extra fees that are incrementally disclosed, or “dripped”.

Drip pricing – a type of “junk fee” – is notorious in event and travel ticketing, and is creeping into other areas, such as movie tickets. My daughter, for example, was surprised to find her ticket to the Barbie movie had a “booking fee”, increasing the cost of her ticket by 13%.

Steinhauser then goes on to explain why consumers are susceptible to drip pricing, blaming present bias and loss aversion:

In the case of booking that hotel room, you could abandon the transaction and look for something cheaper once the extra charges become apparent. But there’s a good chance you won’t, due to the effort and time involved.

This is where the trap lies.

Resistance to the idea of starting the search all over again is not simply a matter of laziness or indecision. There’s a profound psychological mechanism at play here, called a present-bias preference – that we value things immediately in front of us more than things more distant in the future...

Beyond the challenge of starting over, there’s another subtle force at work when it comes to our spending decisions. Drip pricing doesn’t just capitalise on our desire for immediate rewards; it also plays on our innate fear of losing out.

This second psychological phenomenon that drip pricing exploits is known as loss aversion – that we feel more pain from losing something than pleasure from gaining the same thing...

Imagine you’re booking tickets for a show. Initially attracted by the observed headline price, you are now presented with different seating categories. Seeing the “VIP” are within your budget, you decide to splurge.

But then, during the checkout process, the drip of extra costs begins. You realise you could have opted for lower-category seats and stayed within your budget. But by this stage you’ve already changed your expectation and imagined yourself enjoying the show from those nice seats.

Going back and booking cheaper seats will feel like a loss.

In my view, Steinhauser is absolutely correct that drip pricing exploits consumers' quasi-rationality (that is, that consumers are subject to biases in their decision-making). However, he is not fully correct about the sources of the quasi-rational behaviour.

First, present bias would tend to work against drip pricing, because (using Steinhauser's example) consumers are weighing up the cost of the tickets (which they face now) against the benefit of the concert they will attend (which is in the future). If consumers weigh the present more heavily than the future, then the costs weigh more heavily than the benefits, which would work against the consumers paying the junk fees.

Second, Steinhauser is correct about loss aversion, but for the wrong reason. Nobel Prize winner Richard Thaler noted that people engage in mental accounting related to particular decisions. People like to keep their mental accounts in positive balances, and are reluctant to give up on something if the mental account has a negative balance, because that would result in 'booking a loss'. Since people are loss averse, they will only want to close mental accounts that have a positive balance.

What does that mean for a consumer buying a concert ticket? They have spent some time and effort selecting their seats and completing most of the booking process. That puts their mental account for the concert into a negative balance. So, facing a small additional fee seems like a good deal, when compared to closing the mental account with a loss. The consumer pays the fee. They don't necessarily feel happy about it, but it is better than the alternative. The only way to get their mental account for the concert into a positive balance is to attend the concert.

A related way of thinking about the process of buying concert tickets with junk fees is the concept of switching costs. Switching costs are the costs of switching from one seller to another, or from one good or service to another. In this case, for a quasi-rational consumer who is running a mental account for the concert, giving up on buying the ticket when they are faced with the junk fees creates a switching cost - the loss in their mental account. When consumers face high switching costs, they can become locked in to buying a product. The seller can then take advantage of their locked in consumers by increasing the price (which is what the junk fees effectively do).

If you are a strong believer in the tenets of neoclassical economics, then the consumer response to drip pricing seems somewhat at odds with rational behaviour. For a purely rational consumer, the time and effort spent on the booking process up to the time that they face the additional of the junk fees is a sunk cost. It shouldn't affect the decision about whether to proceed with buying the ticket or not, because that decision should depend only on the costs and benefits of attending the concert. If the junk fees increase the costs of attending the concert to such an extent that they are higher than the benefits of attending the concert, a purely rational consumer would stop the ticket-buying process at that point. However, a quasi-rational consumer, who is running a mental account for the concert, would be more likely to proceed with the purchase even when presented with the junk fees.

So, overall, drip pricing leads to more sales if consumers are quasi-rational than if consumers are purely rational. It's lucky (and very profitable) for the ticket sellers that so many of us are not purely rational consumers.

The Victorian government shows they can avoid the sunk cost fallacy

You may have seen the news last week. The Victorian state government in Australia has cancelled the 2026 Commonwealth Games. As Jack Anderson (University of Melbourne) wrote in The Conversation:

The cancellation of the 2026 Commonwealth Games by Victorian Premier Daniel Andrews took all stakeholders – Commonwealth Games officials, athletes, sports bodies and local government officials – by surprise.

The Andrews administration will likely deal with the political fallout from not honouring its contract to host the games, but there may be legal and reputational damage ahead.

The decision was a surprise, but not for the reason many people think. Once a government has decided to hold a big event, they will usually be loath to change their mind. Behavioural economics suggests that quasi-rational decision-makers are susceptible to the sunk cost fallacy. Sunk costs are costs that have already occurred and that cannot be recovered, like the millions the Victorian government has already spent on the Commonwealth Games. Sunk costs should not affect decisions because, regardless of what the decision-maker chooses to do, those sunk costs have already been incurred. Any money that the government has already spent on the Games has already been spent, and will have been spent regardless of whether or not the Commonwealth Games goes ahead. So, at this point, the government should make the decision about whether to go ahead with the Games should be made on the basis of costs and benefits that are to come. Essentially, the Victorian government weighed up the billions of dollars they would face in the future against the benefits from hosting the Games. The costs must have outweighed the benefits.

The sunk cost fallacy typically occurs because of mental accounting, which suggests that we keep 'mental accounts' associated with different activities. We put all of the costs and benefits associated with the activity into that mental account, and when we stop that activity, we close the mental account associated with it. At that point, if the mental account has more costs in it than benefits, it counts as a loss. And because we are loss averse, we try to avoid closing the account. If the Victorian government were affected by mental accounting, they may have still gone ahead with the Games, trying their hardest to avoid banking a loss on the Games. Mental accounting is responsible for keeping us in unpromising projects for too long, as well as unhappy relationships, and bad jobs.

So, the Victorian government were not affected by mental accounting (just like Warner Bros, when they cancelled the release of the Batgirl movie). Even the prospect of bad publicity (of which there has been plenty, and which must have been anticipated) was not enough to dissuade them from the cancellation.

The evolutionary roots of folk economic beliefs?

'Folk economic beliefs' are the widespread beliefs about economic and policy issues, which are held by members of the public untrained in economics. This includes beliefs about trade, unemployment, the operation of markets, the effects of monetary policy, and so on. Many of these beliefs are incorrect, at least compared with the views and models of the majority of economists.

What leads people to adopt incorrect folk economic beliefs? That is the topic of this 2018 article by Pascal Boyer (Washington University in St. Louis) and Michael Bang Petersen (Aarhus University), published in the journal Behavioral and Brain Sciences (ungated version here). Boyer and Petersen focus on eight particular examples of folk economic beliefs, and then link those beliefs to evolutionary psychology. They argue that:

...many folk-views on the economy are strongly influenced by the operation of non-conscious inference systems that were shaped by natural selection during our unique evolutionary history, to provide intuitive solutions to such recurrent adaptive problems as maintaining fairness in exchange, cultivating reiterated social interaction, building efficient and stable coalitions, or adjudicating issues of ownership, all within small-scale groups of foragers.

The eight folk economic beliefs (FEBs) that Boyer and Petersen focus on are:

1. FEB 1: International trade is zero-sum, has negative effects;
2. FEB 2: Immigrants “steal” jobs;
3. FEB 3: Immigrants abuse the welfare system;
4. FEB 4: Necessary social welfare programs are abused by scroungers;
5. FEB 5: Markets have a negative social impact (“emporiophobia”);
6. FEB 6: The profit motive is detrimental to general welfare;
7. FEB 7: Labor is the source of value; and
8. FEB 8: Price-regulation has the intended effects.

The particular aspects of evolutionary psychology that Boyer and Petersen invoke are: (1) detecting free riders in collective action; (2) partner choice for exchange: (3) exchange and assurance by communal sharing; (4) coalitional affiliation; and (5) ownership psychology. As they explain:

In any exchange, it is crucial to monitor whether the implicit or explicit terms of the exchange are being followed. For example, if two individuals take turns helping each other forage, does one person provide less help than he receives? To solve this problem, human exchange psychology needs to contain specific mechanisms for detecting and responding to free-riders...

To engage in exchange, one needs to choose among available social partners. Given the possibility of choice, human exchange and cooperation from ancestral times have taken place in the context of competition for cooperation... as each agent could advertise a willingness to cooperate (and signal how advantageous cooperation would be), and could choose or reject partners depending on their past and potential future behavior...

Competition for cooperation has specific consequences on fairness intuitions in the context of collective action. Given that two (or more) partners contribute equal effort to a joint endeavor, and receive benefits from it, an offer to split the benefits equally is likely to emerge as the most frequent strategy – anyone faced with a meaner division of spoils will be motivated to seek a more advantageous offer from other partners. So, to the extent that people have partner options, the constraints of partner-choice explain the spontaneous intuition that benefits from collective action must be proportional to each agent’s contribution...

One important form of social relations is founded on communal sharing, where resources are pooled...

Humans are special in that they build and maintain highly stable associations bounded by reciprocal and mutual duties and expectations. Such groups – called alliances or coalitions – may be found at many different levels of organization...

The psychology underlying coalitional strategies include the following assumptions: (a) relevant payoffs to other members of the coalition are considered as gains for self (and obviously, negative payoffs as losses to self); (b) payoffs for rival coalitions are assumed to be zero-sum – the rival coalition’s success is our loss, and vice-versa; and (c) the other members’ commitment to the common goal is crucial to one’s own welfare...

These assumptions reflect two crucial selection pressures operating on human groups: First, that alliances are competitive and exclusive, because social support is a rival good. Second, that resources, status, and many other goods are zero-sum and, hence, the object for rivalry between alliances...

For exchange to happen over human evolutionary history, our ancestors needed an elaborate psychology of ownership. Who is entitled to enjoy possession of a good, and to exchange it?...

Adults and even very young children have definite intuitions about who owns what particular good, in a specific situation. For instance, they generally assume that ownership applies to rival resources (that is, such that one person’s enjoyment of the resource diminishes another person’s); that prior possession implies ownership; that extracting a resource from the environment makes one the owner; that transforming an existing resource confers ownership rights; and that ownership can be transferred, but only through codified interactions...

Then, taking each FEB in turn, Boyer and Petersen first link FEB 1 to coalitional affiliation. On that point, I found this most interesting:

...we should expect the view that trade is bad to be particularly attractive when the trading crosses perceived coalitional boundaries. It is predicted to invariably occur in the context of, precisely, debates about trade between countries. American consumers may find it intuitive that the United States might suffer from Chinese prosperity, but, on this theory, they would find it less compelling that development in Vermont damages the economy of Texas.

That explains why my usual counter-point to non-economists' negative views of international trade, which is to note that perhaps Hamilton should close its' borders to trade from the rest of New Zealand, often fails to hit the mark.

Boyer and Petersen then link FEB 2 and FEB 3 (which seem on the surface to be contradictory, as immigrants can't both steal jobs and abuse the social security system), to coalitional affiliation and detection of cheaters, reasoning that:

Immigrants are by definition newcomers to the community. Psychological research has shown that newcomers to groups activate this connection between coalitional cognition and cheater-detection, in particular, in situations where group membership is construed as conferring particular benefits. In such situations, newcomers are typically regarded with great suspicion...

The tight relationship between the concepts of nation and coalition... may explain the attractiveness of the statement that immigrants must be free-riders, scrounging on the past efforts of the host community. But, at the same time, the involved psychological systems leave open whether it is on job creation or on the welfare system that immigrants free-ride. 

FEB 4 is related to free-rider detection and notions of communal sharing, while FEB 5 and FEB 6 are linked to partner choice and the impersonal nature of markets:

In small-scale interactions, the balancing of costs and benefits occurs over reiterated exchanges, and, in order to predict these long-term outcomes, information about the partner’s reputation and past exchanges are key. Impersonal transactions, in contrast, are often anonymous, and therefore make it more difficult to track the reputation of one’s partners. To a psychology designed for partner-choice, this is likely to trigger an alarm signal, indicating that such a situation should be avoided. Second, strictly impersonal exchange goes against motivations to generate bonds of cooperation with particular individuals, as a form of social insurance. This may reinforce the intuition that impersonal transactions involve, if not danger, at least a missed opportunity. Finally, systems for partner-choice are set up to avoid engaging in exchange relationships with individuals who are much more powerful, in order to avoid exploitation... In modern markets, however, many exchanges take place with corporations or business that seem exceptionally powerful from the perspective of the individual.

FEB 7 on the labour theory of value is linked to ownership psychology, where Boyer and Petersen note that:

Ancestrally, most valued and owned goods were previously unclaimed natural resources that time and effort turned into something useable (whether food, tools, or shelter). In such situations, labor is indeed the exclusive generator of both “value” and ownership.

Finally, FEB 8 is not linked to any of the previous aspects, but instead:

To explain this FEB, we need to take into account the fact that unintended consequences of this kind are second-order effects that occur in large-scale social systems. They reflect aggregate market responses to changes in costs and benefits (e.g., if the price of the good is regulated downwards, the market responds by decreasing quantities supplied). But our psychology of social exchange is designed for small-scale social systems, for personal exchanges between oneself and one or more identified others. The intuitive inference systems that evolved to deal with such situations do not, because of the small-scale nature of the situations, include any conceptual slots for aggregate dynamics such as origins of supply. In this way, FEBs about regulation do not emerge from a single set of intuitive inference systems. Rather, they emerge from the failure of particular pieces of information to be processed by any intuitive inference system.

Boyer and Petersen's arguments are interesting, but not all their explanations are equally convincing, especially the last one. There is an excellent debate (called 'open peer review') over the subsequent pages of the journal version of the article (not the ungated one, sadly), which is well worth reading. However, the whole exercise smacks of exactly the problems that Jason Collins noted about behavioural economics in this article (which I discussed here) - the explanations are very ad hoc, and there is no real unifying framework that demonstrates which aspects of evolutionary psychology should apply to which folk economic beliefs. Without something more systematic, we are simply left with some interesting explanations that may or may not hold in a wider context.

Jason Collins on behavioural economics and heliocentrism

When I teach the concept of rational decision-making in my ECONS102 class, we quickly move onto talking about many of the ways in which rationality fails to represent 'real-world' decisions made by real people. This draws on decades of insights from behavioural economics, and I group those insights together into four areas: (1) heuristics (or rules of thumb); (2) present bias; (3) loss aversion; and (4) framing. Within each category there are several biases that we can discuss. However, that barely scratches the surface of the hundreds of biases that psychologists, behavioural scientists, and behavioural economists have identified (see this list on Wikipedia).

Yet, despite all of these biases that are known, the rational behaviour model persists in economics. The reason why the model persists is because there isn't a better single model that captures the biases, as well as the occasions when people do act rationally. We need a better model.

On the Works in Progress site, Jason Collins has an incredibly insightful article along these lines. He draws a fascinating parallel with early astronomy:

From the time of Aristotle through to the 1500s, the dominant model of the universe had the sun, planets, and stars orbiting around the Earth.

This simple model, however, did not match what could be seen in the skies. Venus appears in the evening or morning. It never crosses the night sky as we would expect if it were orbiting the Earth. Jupiter moves across the night sky but will abruptly turn around and go back the other way.

To deal with these ‘anomalies’, Greek astronomers developed a model with planets orbiting around two spheres. A large sphere called the deferent is centered on the Earth, providing the classic geocentric orbit. The smaller spheres, called epicycles, are centered on the rim of the larger sphere. The planets orbit those epicycles on the rim. This combination of two orbits allowed planets to shift back and forth across the sky.

But epicycles were still not enough to describe what could be observed. Earth needed to be offset from the center of the deferent to generate the uneven length of seasons. The deferent had to rotate at varying speeds to capture the observed planetary orbits. And so on. The result was a complicated pattern of deviations and fixes to this model of the sun, planets, and stars orbiting around the Earth.

Instead of this model of deviations and epicycles, what about an alternative model? What about a model where the Earth and the planets travel in elliptical orbits around the sun?

By adopting this new model of the solar system, a large collection of deviations was shaped into a coherent model. The retrograde movements of the planets were given a simple explanation. The act of prediction became easier as a model that otherwise allowed astronomers to muddle through became more closely linked to the reality it was trying to describe...

Behavioral economics today is famous for its increasingly large collection of deviations from rationality, or, as they are often called, ‘biases’. While useful in applied work, it is time to shift our focus from collecting deviations from a model of rationality that we know is not true. Rather, we need to develop new theories of human decision to progress behavioral economics as a science. We need heliocentrism.

Once you hear it explained, the parallel between early astronomy and current economic theory is obvious. As Collins observes (and I encourage you to read his entire article), we need a new model. We can continue to investigate cognitive biases, and make minor ad hoc adjustments to models and policies to try to take account of the latest biases. However, as long as the underlying model is rational behaviour, we are going to continue to lack a proper understanding of human decision-making.

We need a model where cognitive biases are no longer exceptions to the model, but are instead explained by the model itself. It sounds obvious, but it's going to take a spark of genius. Where is the Copernicus of economics?

The endowment effect in the trading of professional sports draft picks

If we believe that decision-makers are loss averse (and until recently, that seemed reasonably clear), then one consequence of loss aversion is the endowment effect. The explanation is fairly simple. When people are loss averse, they value losses much greater than otherwise equivalent gains. Giving something up therefore makes people very unhappy, and so people prefer to hold onto the things that they have. That means that, when a person owns something, they have to be given much more to compensate them for giving it up than what they would have been willing to pay to get it in the first place.

With the NFL regular season starting later this week, I was interested to read this new article by Jeff Hobbs (Appalachian State University) and Vivek Singh (University of Michigan), published in the journal Economic Inquiry (open access), because it looked at the endowment effect in professional sports. Specifically, Hobbs and Singh investigate whether draft picks in the NBA, NFL, and NHL over the period from 1988 to 2017 demonstrate an endowment effect. Their data set includes nearly 17,000 draft picks. For a little more context for those unfamiliar with professional sports drafts, Hobbs and Singh explain that:

Every year, each of the major professional sports leagues in the United States holds what is known as its “entry draft.” During the entry draft the teams select, in inverse order of success from the previous season such that the worst teams get the first picks, amateur players with a view toward signing them to professional contracts. In most of these leagues, teams can trade draft picks (before they are used to select players) at least as freely as they can trade players who are already under contract.

So, teams are initially endowed with a certain number of draft picks. They can choose to keep those picks (which they can use to select young players who are eligible to be drafted), or they can trade picks to other teams (and those teams can use the picks instead). Teams trade picks for a variety of reasons, often trading picks for players. Teams can also trade picks that they themselves acquired in some other trade. However, the nature of the trade doesn't matter for Hobbs and Singh's analysis. They are only interested in whether teams are more or less likely to trade draft picks that they originally endowed with, than other draft picks.

To do this, they look at what happens after a pick is first traded. If there is an endowment effect, then the team that originally had the pick should be less willing to trade than a team that acquired the pick in a trade. They do this by comparing the proportion of times that a traded pick is 're-traded', compared with the pick just before or just after that pick in the draft order. They find that:

After we control for the frequency of selling, we find that non‐endowed picks for all three leagues combined were 12%-15% more likely to trade again than were their adjacent, endowed counterparts from the same point in time afterward. These results are statistically significant, but we notice some differences when we look at each league individually. Regardless of whether we attempt first to match the once‐traded pick with the pick directly below it or above it, the results for the NFL become insignificant. However, the results for the other two leagues remain significant in both a statistical and economic sense. In the NBA, the average once‐traded and non‐endowed pick is between 24.5% and 29.2% more likely to trade afterward than is its match. In the NHL, the once‐traded, non‐endowed pick is between 14.8% and 23.6% more likely to trade.

In other words, there is a substantial endowment effect for draft picks in the NBA and NHL, but it appears not for the NFL. However, Hobbs and Singh aren't willing to let the NFL off completely, noting in their conclusion that:

The relative rationality of the NFL documented here pertains only to the endowment effect with respect to the trading of draft picks; other studies have found examples of other irrationalities in professional football.

Fair enough, but it seems like a bit of a cheap shot. I'm sure there's a lot of other irrationalities in basketball and hockey as well. As one example, the endowment effect probably doesn't just play out in the draft. It is likely to be present when considering free agent players as well (as I noted in this 2017 post). The sabermetrics revolution may have increased the use of analytics in sports, but it doesn't appear to have eliminated quasi-rationality entirely.

Read more:

• Free agents, the draft, and the winner's curse

The cancellation of Batgirl shows Warner Bros are not fooled by mental accounting

The Guardian reported earlier this week:

The previously announced Batgirl film starring In the Heights actor Leslie Grace, Michael Keaton and Brendan Fraser will not be released at all, Warner Bros Discovery has unexpectedly announced, despite shooting already being completed and the film being in post-production.

Directed by Ms Marvel directors Adil El Arbi and Bilall Fallah, the film was initially greenlit in 2021 as part of a wider move at Warner Bros to create feature films specifically for the streaming service HBO Max. But the studio confirmed on Tuesday that the film would never get any release, either theatrically or on HBO Max...

The Hollywood Reporter said Batgirl’s budget was a factor in the decision, having risen to nearly $90m (£74.1m, A$130m) due to costs relating to it being shot during the Covid-19 pandemic. While the budget is lower than the average DC superhero film, it was reportedly decided that it did not have the “spectacle that audiences have come to expect from DC fare” and would not recoup its losses from being released.

However, the New York Post, which broke the story on Tuesday, cited an unnamed source who said the budget had actually exceeded $100m and that the film had performed so poorly during early test screenings that Warner Bros decided to cut its losses.

“They think an unspeakable Batgirl is going to be irredeemable,” the source told the New York Post.

Behavioural economics suggests that quasi-rational people are susceptible to the sunk cost fallacy. Sunk costs are costs that have already occurred and that cannot be recovered, like the US$90 million or more already spent on the Batgirl movie. Sunk costs should not affect decisions because, regardless of what the decision-maker chooses to do, those sunk costs have already been incurred. Since the US$90 million has already been spent, it has been spent if the movie is released, and it has been spent if the movie is not released. So, at the point of post-production the decision about whether to go ahead and release the movie should be made on the basis of costs and benefits that are to come. Essentially, Warner Bros was weighing up the further costs they would face (on additional post-production, marketing, etc.) against the benefits they would receive (box office receipts, and other revenue). The costs must have outweighed the benefits.

The sunk cost fallacy typically occurs because of mental accounting, which suggests that we keep 'mental accounts' associated with different activities. We put all of the costs and benefits associated with the activity into that mental account, and when we stop that activity, we close the mental account associated with it. At that point, if the mental account has more costs in it than benefits, it counts as a loss. And because we are loss averse, we try to avoid closing the account. If Warner Bros were affected by mental accounting, they may have released the movie anyway, trying their hardest to avoid banking a loss on the movie. Mental accounting is responsible for keeping us in unpromising projects for too long, as well as unhappy relationships, and bad jobs.

So, Warner Bros were not affected by mental accounting, and it appears that the viewing public will be saved from a terrible Batgirl movie. It's a pity that didn't happen to the truly horrible Moonfall (my movie ticket was a sunk cost on that one), or everyone's favourite superhero move to hate, Green Lantern.

[HT: Mark from my ECONS102 class]

Only a minority of real people may actually be loss averse

I've written a couple of posts this week about loss aversion (see here and here). However, loss aversion is not uncontested in the research literature. In fact, the research by Gal and Rucker that I discussed in this 2018 post argued that there was "little evidence to support loss aversion as a general principle". One way of thinking about this is that Gal and Rucker are arguing that not everyone is loss averse. And that is likely true, in the same way that not everyone is risk averse, and not everyone is averse to pineapple on pizza.

A new working paper by Jonathan Chapman (University of Bologna), Erik Snowberg (University of Utah), Stephanie Wang (University of Pittsburgh), and Colin Camerer (Caltech) provides some more evidence for this. In fact, they don't just show that some people are not loss averse. They show that about half of people may in fact be 'loss tolerant'.

Chapman et al.'s main results are based on a sample of 1000 people who completed a survey with the survey panel provider YouGov in 2020. The specific method that they used is quite detailed, but essentially involved 20 different 'gambles', with each gamble using information from the earlier gambles to provide a nuanced understanding of each research participant's attitudes towards risk and towards loss. This Dynamically Optimized Sequential Experimentation (DOSE) method provides estimates for both risk aversion and loss aversion for each research participant.

Importantly, the sample of research participants in the YouGov survey is representative of the underlying US population. Chapman et al. contrast the results from the representative sample with those from a smaller sample of 437 students from the University of Pittsburgh. This comparison is important, because most experimental economics samples are based on student populations (and it has been shown before that student samples are meaningfully different to representative population samples in economics experiments - for example, see here).

For the Chapman et al. paper, the key results are demonstrated in their Figure 3:

Looking at the blue distribution, there are some people in the general population sample who are loss averse (λ>1), but also a lot of people who are loss tolerant (λ<1), as well as some people in the middle. In terms of raw numbers, 57% of the general population sample is loss tolerant. For the student sample, again there is a distribution where some are loss tolerant, but a far higher proportion are loss averse. In the student sample, just 32% are loss tolerant.

So, what is it that makes the student population so much more loss averse than the general population? Chapman et al. show that:

...more educated and more cognitively-able individuals - both characteristics of student samples... - tend to be more loss averse and also less risk averse.

So, university students may be more loss averse because they have higher cognitive ability than the general population and are more educated. That may be good reason to think carefully about whether student samples are necessarily always the best choice to economics experiments.

However, Chapman et al. don't stop there. They then look at why it is that less cognitively-able and less educated people are more loss tolerant, hypothesising that:

...the groups that tend to be more loss tolerant - the less educated, lower income, and less cognitively able - are also those that we might expect to have encountered more losses in life. This raises the intriguing possibility that loss tolerance is shaped by everyday experiences.

And that is what they find:

...loss-tolerant individuals appear more likely to gamble, commit a greater portion of their assets to equities, experience financial shocks, and have lower overall wealth...

So, what should we take away from this research? First, not everyone is loss averse. In fact, a majority of people may be loss tolerant. That doesn't mean that loss aversion is irrelevant for understanding individual decision-making. It just means that we should not assume that everyone is loss averse. Second, we need to take care in extrapolating from student samples in economics experiments to the general population. This is not a new finding (as I noted above), but it is important that we don't lose sight of it. Third, and probably most important, when people routinely experience losses as part of their everyday life, they become more loss tolerant (and less loss averse). That may or may not be a good thing. After all, we talk about loss aversion as a deviation from purely rational decision-making. Being less loss averse may not be a bad thing. On the other hand, if loss tolerance leads to greater losses in the future, that may require a policy response. On this last point, we really need more research.

[HT: Ranil Dissanayake]

Loss aversion and the endowment effect in health-seeking behaviour

When I teach loss aversion in my ECONS102 class, I raise one of the consequences of loss aversion as the endowment effect. The explanation is fairly simple. When people are loss averse, they value losses much greater than otherwise equivalent gains. Giving something up therefore makes people very unhappy, and so people prefer to hold onto the things that they have. That means that, when a person owns something, they have to be given much more to compensate them for giving it up than what they would have been willing to pay to get it in the first place.

However, it turns out that loss aversion may not be the best (or only) explanation for the endowment effect. In a new NBER Working Paper (ungated version here, with a non-technical summary here), Emily Beam (University of Vermont), Yusufcan Masatlioglu (University of Maryland), Tara Watson (Williams College), and Dean Yang (University of Michigan) look at how people respond to a $50 incentive to attend a health service provider, when it is framed as a loss versus when it is framed as a gain. More specifically:

In this study, we implement a randomized field experiment that compares loss versus gain framing to promote preventive health care utilization. We offer individuals in and near Dearborn, Michigan, an incentive to visit a health clinic run by our partner organization, the Arab Community Center for Economic and Social Services (ACCESS). In the “Visa gift card” (loss framing) treatment, participants are given a Visa gift card of either $50 or $10 that can be activated by visiting the clinic; they will effectively lose the value of the card if they choose not to visit a clinic. In the “reminder card” (gain framing) treatment, participants are given a physically similar generic reminder card with the promise that it will be exchanged for a gift card if they visit the health clinic, but they are not given the gift card up front. In both cases, any individual who went to the health clinic would receive an active Visa gift card, and any funds remaining after the visit could be spent elsewhere. Because of random assignment to the treatments, differences in responsiveness to the incentives are attributable to the differences in the frames.

Research participants who were given a Visa gift card essentially face a loss if they choose not to activate it. That's because, once they finish the initial survey, they have the card in hand and choosing not to activate it is like losing $50. The other participants only receive a reminder card, which can be converted into a gift card. So, if they don't go to the clinic, they aren't losing in the same way. So, if there is an endowment effect, we'd expect those who received the gift card to be more likely to visit the clinic.

However, that isn't really what Beam et al. are looking at. They are investigating why there is an endowment effect. So, in the initial survey, they ask questions that are designed to provide an estimate of how loss averse people are. If the endowment effect is related to loss aversion, then the effect should be larger for people who are more loss averse. However, the endowment effect might also arise because of trust. As Beam et al. explain:

A second possible explanation for the effectiveness of loss framing is that giving an incentive up front induces an individual to have more confidence that the incentive will be provided as promised. The perceived probability of receiving a reward is likely higher for someone who has a tangible reward in hand relative to someone hearing about a promised reward. This trust‐related response is likely more relevant in field contexts outside the lab, and it is expected to be most relevant when individuals do not initially trust the person or institution offering the incentive.

If the endowment effect arises because of trust issues, then it should be larger for people who report less trust in the health care organisation, ACCESS. So, armed with measures of trust and loss aversion for around 1500 people (whose gift card was worth $50, and ignoring a smaller group whose gift card offer was only $10), and knowing which of the research participants visited the clinic (to receive or activate their Visa gift card), Beam et al. then find that:

The overall average difference in take‐up between those who receive the $50 Visa gift card (loss frame) and $50 reminder card (gain frame) is about 2.2 percent... The differences between Visa gift card and reminder card redemption rates are 4 to 5 percentage points for more loss‐loving participants and 1 to 2 percentage points for more loss‐averse participants. These results are not statistically significant... There is no clear pattern linking loss aversion to take‐up rates, nor to the gap in take‐up rates between gift card and reminder treatments.

So, there is a small endowment effect, but it isn't related to loss aversion. What about trust? Beam et al. find that:

Participants without trust of the organization at baseline are much more responsive to the gift card treatment (loss frame); the impact of the gift card is 7.2 percentage points for this group... The statistically significant interaction term... suggests that there is no comparable effect for those who do trust ACCESS at baseline.

In other words, there is an endowment effect for research participants who do not trust ACCESS, but no endowment effect for research participants who do trust ACCESS. When I first read those results, I was a little concerned that they arose only because Beam et al. combined people who reported low trust with people who had no opinion because they hadn't heard of ACCESS before. However, when those categories are separated, the results remain similar.

So, it really does seem that it is trust, and not loss aversion, that likely explains the endowment effect in this context. That doesn't necessarily mean that loss aversion is never a source of the endowment effect though, so I think I am safe (for the moment) in continuing to teach it as closely related to loss aversion.

The Beam et al. paper is also interesting in noting some of the real-world difficulties in research, especially this bit:

During our first survey wave, we encountered several safety issues: some interviewers were harassed by residents; on another day, interviewers witnessed gunfire a few blocks away. After these experiences, we excluded tracts that reported relatively high recent crime levels, and we contacted the Dearborn police department to exclude any additional tracts that they considered to be unsafe...

 Yikes! And slightly more mundane, this bit on how they had to adapt the measurement of loss aversion:

Although these questions are typically worded as a gamble, we adjusted the wording to be an “opportunity” after pilot testing revealed many subjects would reject all gambles because of religious objections to gambling.

Real-world field research is often not as straightforward as we hope it would be.

[HT: Ranil Dissanayake]

Loss aversion may affect how students answer multiple choice questions

In my ECONS102 class this week, among other things we covered a bunch of concepts in behavioural economics. One such concept was loss aversion - the idea that people value losses much more than equivalent gains (in other words, they like to avoid losses much more than they like to capture otherwise equivalent gains). Loss aversion seems to explain a lot of quasi-rational behaviour (however, as a concept, loss aversion is contested - more on that in another post later this week). People do seem to adjust their behaviour to try and avoid losses.

One example is the answering of multiple choice questions in tests and exams, but only where a wrong answer results in a penalty (subtracting marks from the overall test or exam score). I never grade multiple choice in that way, but many academics do. The argument they put forward is that, when incorrect answers are penalised, it creates a disincentive to students guessing. However, because the penalty creates a loss, it may be that loss averse students avoid answering when they are a little bit unsure, even if their not-quite-sure guess would have been the correct answer.

So, how much does loss aversion affect students' multiple choice answering behaviour? That is the question that this recent article by Heiko Karle (Frankfurt School of Finance and Management), Dirk Engelmann (Humboldt-Universität zu Berlin) and Martin Peitz (University of Mannheim), published in the Scandinavian Journal of Economics (ungated earlier version here), sets out to answer. Karle et al. use data from 646 students, combining an experimental-based measure of loss aversion (that the students completed early in the semester) with the results of a 30-question multiple-choice examination (held some three months later), where:

There are four possible answers to each question: a correct answer gives three points, no answer one point, and an incorrect answer gives zero points, as in the exam in our data set.

Notice that, on the face of it, there is no penalty for an incorrect answer, since an incorrect answer receives zero points. However, choosing not to answer yields one point, so considering not answering as the status quo reference point, choosing an incorrect answer makes a student worse off by one point (a loss, which they would try to avoid). Karle et al. hypothesise that students who are more loss averse will answer fewer questions, and will get more of the questions that they do answer correct. Both hypotheses are obvious from loss aversion - students try to avoid the loss, so are more likely not to answer questions when they are unsure, so more loss averse students will answer fewer questions. That means that the questions that more loss averse students do answer are those that they are surer about, and so they are more likely to get those answers correct. Karle also test a related hypothesis, that students who are more loss averse get fewer questions correct overall, which depends on how many the students answer (fewer, when the students are more loss averse) and how many of the ones they do answer are answered correctly (more, when the students are more loss averse). What to expect for this overall hypothesis is unclear.

In addition to loss aversion, Karle et al. measure students' self-confidence, which is based on the difference between students' estimates of the percentage of their own correct answers to a set of general interest questions and the average percentage of other students’ correct answers. Students who are more self-confident can be expected to be more likely to answer questions in the multiple choice exam.

Now, using their data, Karle find that:

...loss aversion and confidence have a negative and positive effect, respectively, on the number of answered questions... This effect is statistically significant at the 1 percent level... Our estimates suggest that loss neutral students answer approximately two questions more than otherwise identical students in the highest category of loss aversion (and 5/3 more than those in the middle category).

So, more loss averse students answer fewer questions than less loss averse students, as expected. Next:

We do not find a statistically significant effect (at the 5 percent level) of loss aversion or confidence on the ratio of correct answers per questions answered. However, the coefficient of loss aversion (but not strong loss aversion) turns positively significant at the 10 percent level when considering loss aversion and confidence together...

This is very weak support (or, rather, no support) for the hypothesis that more loss averse students get more of the questions that they do answer correct. Combining the two hypotheses, I'm sure you can guess for the overall hypothesis, that Karle et al. find that:

...loss aversion and confidence have a negative and positive effect, respectively, on the dependent variable [the number of correct questions overall]... Our estimate suggests that, ceteris paribus, students in the highest category of loss aversion give approximately 1.5 fewer correct answers than otherwise identical students who are loss neutral.

Karle et al. then spend a bit of effort trying to determine whether the effect of loss aversion on question answering behaviour is causal or not, and their results suggest that it is causal for some, but not all, students. I don't find those results as convincing as the overall takeaway that students' loss aversion is related to how they answer questions.

Nevertheless, these results are interesting even putting aside the question of causality. Loss aversion isn't something that is easy to change, so even a correlation between loss aversion and question answering behaviour is potentially important. And it may be even more important given that Karle et al. show that female students in their sample are more loss averse than male students. So, the effect of this style of grading multiple choice questions is a bias against female students, decreasing female grades relative to male grades. That's the last thing we need in economics. That may have contributed to this:

In our setting, according to a university directive, the differential treatment of wrong responses and no responses was no longer allowed after the academic year 2013/2014, which is the exam year we used in this paper.

Coming back to my earlier point, many academics like the style of grading that doesn't award 'free' marks to student guessing. However, there is a trade-off. If students are penalised for guessing, they are likely also penalised based on how loss averse they are. So, if multiple choice questions come with a penalty, the exam score will be more precise for each question (in terms of telling the grader whether students actually were confident in the answer) but also more biased overall (because more loss averse students will get fewer questions correct than less loss averse students). The trade-off seems untenable to me. I'll continue to use multiple choice marking that implicitly includes a reward for guessing.

Is it time to reconsider nudge theory?

In a surprising recent working paper, Nick Chater (University of Warwick) and George Loewenstein (Carnegie Mellon University) outline a case against 'nudges' as a policy tool. As you may know, nudges take advantage of insights from behavioural science, psychology, and behaviour economics, to change individual behaviour for the better. This idea was popularised in Richard Thaler and Cass Sunstein's 2008 book Nudge. Chater and Loewenstein have been at the forefront of the nudge movement, as members of the advisory board of the U.K.'s Behavioural Insights Team (popularly known as the 'nudge unit').

What is surprising about the working paper is that this is a well-reasoned critique of using nudges to address policy issues, written by two nudge policy 'insiders'. Their main argument is best summarised in the long abstract to the paper:

An influential line of thinking in behavioral science, to which the two authors have long subscribed, is that many of society’s most pressing problems can be addressed cheaply and effectively at the level of the individual, without modifying the system in which individuals operate. Along with, we suspect, many colleagues in both academic and policy communities, we now believe this was a mistake. Results from such interventions have been disappointingly modest. But more importantly, they have guided many (though by no means all) behavioral scientists to frame policy problems in individual, not systemic, terms: to adopt what we call the “i-frame,” rather than the “s-frame.”

Chater and Loewenstein distinguish between 'i-frame' interventions and 's-frame' interventions throughout the paper. They explain the difference as:

The behavioral and brain sciences are primarily focused on what we will call the i-frame: that is, on individuals, and the neural and cognitive machinery that underpins their thoughts and behaviors. Public policy, by contrast, is typically focused on the s-frame: the system of rules, norms and institutions by which we live, typically seen as the natural domain of economists, sociologists, legal scholars and political scientists.

The difference is important, because:

Unlike traditional policies, i-frame interventions don’t fundamentally change the rules of the game, but make often subtle adjustments that promise to help cognitively frail individuals play the game better.

However, the problem that Chater and Loewenstein see is not limited to the modest effects of i-frame interventions when compared to potential alternative s-frame policy or institutional change. They note that:

We have begun to worry that seeing individual cognitive limitations as the source of problems may be analogous to seeing human physiological limitations as the key to the problems of malnutrition or lack of shelter. Humans are physiologically vulnerable to cold, malnutrition, disease, predation and violent conflict, and an i-frame perspective on these problems would focus on hints and tips to help individuals survive in a hostile world. But human progress has arisen through s-frame changes---the invention and sharing of technologies, economic institutions, legal and political systems, and much more, which created an intricate social, political and economic system that has led to spectacular improvements in the material dimensions of life. The physiology of individual humans has changed little over time and across societies; but the systems of rules we live by have changed immeasurably. Successful s-frame change has been transformative in overcoming our physiological frailties.

Chater and Loewenstein also worry that i-frame interventions get in the way of potentially successful s-frame changes:

There is, moreover, a more subtle way in which i-frame interventions undermine s-frame changes: through shifting standards of what counts as good quality evidence for public policy. For many i-frame policies, randomized controlled trials have been widely viewed as a gold-standard method for evaluating and incrementally improving policy... But the gold-standard of experimental testing provides a further push towards i-frame interventions (where different individuals may be randomly assigned distinct interventions) and away from s-frame interventions, where it is rarely possible to change the “system” for some subset of the population...

And that corporations have actively weaponised the i-frame to prevent s-frame solutions. In their view, this has played out following a common pattern:

1. Corporations with an interest in maintaining the status quo put out PR messages that the solution to a problem they are associated with lies with individual responsibility, and that people need to be helped to exercise that responsibility more effectively. That is, the challenge of fixing the social problem is cast in the i-frame...

2. Behavioral scientists enthusiastically engage with the i-frame...

3. There are hopes that proposed i-frame interventions (including nudges, and providing better individual-level incentives, information and education) might provide cheap and effective solutions to conventional s-frame policy levers, such as regulation and taxation. This hope distracts attention from the s-frame...

4. The i-frame interventions show at best modest, and often null, effects, and are sometimes even counterproductive...

5. Corporations themselves relentlessly target the s-frame, where they know the real leverage lies. They spend substantial resources on media campaigns, lobbying, funding think-tanks and sponsoring academic research, to ensure that the “rules of the game” reinforce the status quo.

Chater and Loewenstein outline a number of problems where i-frame interventions have been tested, but where s-frame policy or institutional change would be much more effective. This includes climate change (e.g. i-framed individual carbon footprint calculators vs. s-framed carbon taxes), obesity (i-framed motivational interventions, tray-less cafeterias, etc. vs. s-framed sugar taxes or regulations), retirement savings (e.g. i-framed individual retirement savings vs. s-framed universal retirement saving or public pensions), and plastic waste (e.g. i-framed individual responsibility for recycling vs. s-framed regulations banning single-use plastics). They also point in lesser detail to a number of other applications where i-frame thinking gets in the way of s-frame solutions, including healthcare reform, educational inequality, discrimination, online privacy, misinformation on social media, the opioid epidemic, and gun violence.

Not everyone will agree with Chater and Loewenstein's critiques. However, they are all the more forceful and worth paying attention to, having come from within the advocates of behavioural interventions. That makes this paper potentially much more consequential than previous libertarian critiques, such as those in the book Nudge Theory in Action (which I reviewed here). It will be interesting to see how the advocates of nudge theory respond.

[HT: Tim Harford]

Autism vs. the sunk cost fallacy

One of the many ways in which 'real world' decision-makers fall short of the purely rational ideal is that decision-makers in the real world are subject to the sunk cost fallacy. Sunk costs are costs that have already occurred and that cannot be recovered. In his book Misbehaving: The Making of Behavioral Economics (which I reviewed here), the 2017 Nobel Prize winner Richard Thaler argues that the sunk cost fallacy arises because of a combination of loss aversion and mental accounting.

In general, people are loss averse because we value losses more than we value equivalent gains. Gaining $10 makes us happier, but losing $10 makes us unhappier to a greater extent than gaining $10 makes us happier. So, we generally try to avoid losses.

Mental accounting suggests that we keep 'mental accounts' associated with different activities. We put all of the costs and benefits associated with the activity into that mental account, and when we stop that activity, we close the mental account associated with it. At that point, if the mental account has more costs in it than benefits, it counts as a loss. And because we are loss averse, we try to avoid closing the account.

Part of the issue with susceptibility to the sunk cost fallacy is that real world decision-makers are thinking emotionally. If they were dispassionate logical-thinking robots, they wouldn't take sunk costs into account in their decisions. But although decision-makers are not all equally susceptible to the sunk cost fallacy, the costs in terms of sub-optimal decision-making may be substantial. So, studies of the sunk cost fallacy in different population groups are important.

One interesting new study by Nicky Rogge (KU Leuven), published in the Journal of Economic Psychology (sorry I don't see an ungated version online), looks at the difference between people with autism spectrum disorder (ASD) and neurotypical people. Rogge first reminds us of 'Dual Process Theory', which posits that:

...reasoning and decision making can be described as a function of two processing or reasoning systems: the intuitive reasoning system and the deliberative analytic-logical reasoning system. The intuitive reasoning system involves an implicit, unconscious reasoning process that is independent of cognitive ability and working memory, and that is rapid and automatic. The deliberative analytic-logical reasoning system involves an explicit (controlled), conscious reasoning process that depends strongly on cognitive ability and working memory, and is slower and more effortful.

Some of you may recognise this as the 'System 1' and 'System 2' thinking processes that 2002 Nobel Prize winner Daniel Kahneman outlined in his book Thinking, Fast and Slow. Rogge then outlines some of the literature on thinking processes among people with ASD, and notes that:

Brosnan et al. (2016, 2017) and Lewton et al. (2019) argued that the pattern of reasoning and decision-making styles adopted by individuals with ASD is more biased away from intuitive reasoning and more towards deliberative reasoning styles, as compared to what is observed in neurotypicals.

That suggests that, to the extent that the sunk cost fallacy arises from decision processes occurring within the intuitive 'System 1', that people with ASD may be less susceptible to the sunk cost fallacy (as well as potentially other heuristics and biases that together define 'quasi-rational' behaviour).

Rogge then tests a number of hypotheses related to this, using data collected from an online survey of 332 people from Belgium, 187 of whom self-reported as having been diagnosed with ASD, while 34 reported a strong suspicion of ASD but no diagnosis, and 111 'neurotypicals', who reported no ASD. Rogge doesn't just take the research participants' word for it - he administers to AQ-Short test to derive a quantitative measure of where each research participant (self-reported ASD or neurotypical) fits on a scale (the AQ-10 scale). The survey asked participants about six problems, where:

Each of the six sunk-cost decision tasks presents a hypothetical decision scenario which involves a sunk cost...

For each decision task, research participants rated how relatively likely they were to choose between two options, one of which involved accepting a sunk cost. Rogge then uses the responses from the six decision tasks to derive a score for susceptibility to the sunk cost fallacy. He also knows how long each research participant spent on each decision task, which he uses to proxy for how thoughtfully they considered the options (i.e. how much 'System 2' thinking was involved). Then, he uses propensity score matching to create a matched sample of research participants with ASD and neurotypicals, and analyses the differences in sunk cost score between the groups. He finds that:

...(a) the sunk cost did impact the decision made by the average participant across the six sunk-cost decision tasks... (b) participants with ASD were generally less subject to the sunk-cost bias as compared to neurotypical participants... (c) participants with ASD and more autistic traits (as measured by the AQ10-score) were generally less subject to the sunk-cost bias as compared to individuals with ASD and less autistic traits (and neurotypical individuals)... (d) the time to complete a sunk-cost decision task related negatively to the sunk-cost bias for participants with ASD... and (e) this negative relation between time spent in the decision task and the sunk-cost bias was more pronounced for individuals with more autistic traits as compared to their counterparts with less autistic traits (both ASD and neurotypical)...

So, score a win for people with ASD. They are less susceptible to the sunk cost fallacy, and consistent with that, they spend more time on the decision tasks than neurotypicals do. That doesn't answer the bigger question of 'why', but it does demonstrate that people with ASD have more rational decision-making processes in this context.

Of course, there are some problems with this study, and it needs replication in other samples. The biggest issue is the nature of the hypothetical scenarios. It would be interesting to see if similar results would be found in an experimental setting, rather than in an online survey. Also, this type of study could easily be extended, as Rogge notes in his conclusion:

It would be interesting for future studies to measure and compare the sunk-cost bias of individuals with ASD and neurotypical individuals in real-world decision scenarios involving sunk costs and explore the role of, for instance, social and communication skills in sunk-cost bias. Another research question consists in exploring whether individuals with ASD take hypothetical and experimental tasks more seriously and, if so, whether this explains for why they make more consistent and less biased decisions than neurotypical individuals.

Both of those options would be worthwhile additions to the growing research literature on decision-making among people with ASD.