Personal financial management is easier than it has ever been. Digital technologies that allow consumers to easily, affordably, and conveniently track, move, and monitor their debts, investments, payments, and personal financial accounts are increasingly ubiquitous. Financial Technology (FinTech) companies represent many facets of the digital finance industry, including personal banking, digital payments, remittances, lending, investing, insurance, and cryptocurrency.
Compared with traditional banking methods, digital solutions provide a wider range of services and more accessibility, often at a cheaper cost. With the numerous benefits of FinTechs over traditional financial management, they are quickly becoming the dominant way for consumers to handle their finances.
Despite their advantages, FinTech companies today still face big practical challenges when it comes to their users, including motivating new users to adopt their platforms and encouraging existing users to uptake their premium services.
The report explores three of the most common behavioural barriers to FinTech adoption and the uptake of premium services, some of the key psychological and behavioural contributors to those barriers, and examples of behaviourally-informed interventions to overcome them.
Key behavioural barriers for FinTech companies
For example, users are often overwhelmed by the amount of information presented to them when evaluating whether a FinTech service is useful. Presenting information in a more digestible, easy-to-understand way can increase conversion rates and increase the number of users who purchase premium services. One way to accomplish this is to communicate the features of a product through benefit appeals, which present benefits in a broader, more relatable way than attribute appeals, which simply provide long lists of jargon-filled features.
Examples of behaviourally-informed interventions
The Behavioural Science of FinTech report is full of behavioural insights that you can use to gain an advantage in the FinTech marketplace, and many of the insights within are applicable to a range of other industries as well. If you’d like to download the full report for free, you can do so here.
This report provides powerful suggestions for product improvement, however for optimal outcomes we recommend consulting with expert behavioural scientists. If you would like to understand how you can apply behavioural science in your work, we can assist you and discuss personalised solutions — please contact us at info@behive.consulting or read more on our website.
5 Cognitive Biases that Affect the Healthcare Experience
Among service providers, healthcare is unique: patients are often placed in vulnerable situations with their doctors and other health professionals. Health is a private, sensitive topic requiring an awareness and understanding of the underlying mechanisms of patient care. Although healthcare professionals often do their best to provide the best care, psychology can often affect the ways in which they treat their patients, and the ways their patients perceive that treatment. For example, roughly 25% of nurses have reported being “repulsed” by an obese patient (Puhl & Brownell, 2001), adding 3 extra minutes to a colonoscopy can actually make it a more pleasant experience (Redelmeier et al., 2003), and doctors who have had personal experiences with uncommon diseases are more likely to prescribe screenings related to those diseases for their patients (Ragland et al., 2018). These are not the only examples of seemingly “irrational” behaviours and perceptions that influence the healthcare space. Cognitive biases play a large role in healthcare and understanding these biases is important for improving the healthcare experience.
This article presents 5 cognitive biases influencing the seemingly irrational behavioural trends in healthcare.
The Peak-End Rule
For many children, going to the dentist seems like a scary, painful and unpleasant experience; scarier and more painful than it probably truly is. However, at the end of the visit, when the dentist praises them for being so brave and gives them a sticker or a sweet, it makes the whole experience more bearable. With such a great ending to an otherwise unpleasant experience, the child may remember these visits as bearable, better-than-expected occasions, and be more willing to return in the future. Adults undergo similarly unpleasant medical procedures, for instance the dreaded colonoscopy. Luckily, just as a sweet treat can make the dentist a less intimidating place, there are strategies that can improve an adult’s perception of the pleasantness of an uncomfortable colonoscopy. One study found that patients who underwent what was otherwise a normal colonoscopy procedure, except with the addition of three slightly less unpleasant minutes added at the end, rated their experience as less unpleasant overall than patients who underwent the standard, shorter procedure (Redelmeier et al., 2003). Why?
The peak-end rule changes the way individuals remember and evaluate a treatment. According to this bias, individuals judge their experience based on how they felt at its (emotional) ‘peak’ and at its end (the final stimulus), rather than by the average comfort of the visit. The better experience the individuals had at the end of the treatment, the less likely it is that they will remember it as unpleasant. Not moving the medical scope for three minutes at the end of the colonoscopy created a sensation that was uncomfortable, but was less painful than the rest of the procedure. Despite this 3 minute extension, patients remember it as a more bearable visit and are more likely to return in the future because the last thing they experienced was more pleasant.
The Licensing Effect
If you’ve ever been on a diet, you’ll be familiar with cheating. After days of maintaining your diet, eating salads and forgoing desserts, your friend asks if you want a piece of birthday cake and you think to yourself “I’ve been good recently, it’s ok if I have just one piece!” This feeling is not just found in dieters. Everyone feels that their past good actions warrant a small forbidden reward from time to time, and patients are no different. A study investigating people with a rare, terminal lung disease found that patients who previously engaged in “good” behaviour, such as improving their diet, were on average 17% more likely to engage in “bad” behaviour, for example not beginning their prescribed treatment (Genentech). But why do we feel entitled to a forbidden treat, or to disregard our doctor’s orders, after we’ve been good?
The licensing effect (also known as self licensing or moral licensing) describes the phenomenon whereby people feel entitled to engage in some “bad” behaviours after they have done something they perceive as “good”. Being good reinforces a person’s positive self-image and “balances” the perceived morality of their actions, allowing them the room to justify an action they know is not good for them, or one that is not in their best interest. The terminal lung disease patients mentioned above maintained their positive self-image by improving their health through keeping a proper diet, then used that enhanced self-image to justify delaying their doctor’s prescribed treatment.
The Horn Effect
“He must be lazy and probably eats too much!” We often hear that obese people can be judged in a very harsh way by society. They can be perceived as unmotivated or depressed, not having enough self-control, and are often blamed for their extra kilos. Several studies have shown that the prejudice about overweight people is common among medical professionals too, which can result in poorer patient care. 24% of the nurses said they are “repulsed” by an obese person, 66% of physicians thought obese people have a lack of self-control (Puhl & Brownell, 2001). Based on another study, the majority of the doctors preferred not to treat overweight patients and did not expect success when they were responsible for their management. This attitude can affect the quality of patient care, for instance not believing overweight individuals when they express pain, or by assuming that their weight is the root cause of all of their medical problems. Why are even experts prejudiced?
The horn effect is about the tendency to have prejudicial assumptions about someone based on a single negative trait, in this case, the assessment of the person as being overweight or obese. As a result of this cognitive bias, society (and even medical professionals!) automatically endows the overweight with more negative personality traits and characteristics. The stigmatization of obesity results in widespread discrimination, including in patient care. Moreover, it demotivates people to go for regular preventive medical check ups. This bias appears in other areas of our lives as well. For example, parents of overweight children tend to provide them less support for college than parents do for their thinner children (Puhl & Brownell, 2001).
Overconfidence Bias
If you drive a car, you might be surprised how many bad drivers are on the road, and you might consider yourself as a better-than-average driver. You are not alone. 93% of people also believe they are better than average drivers (Svenson, 1981). But, if you’re doing the math, then you know that not all of these people can be correct. If we all had an accurate idea about our abilities, only 50% of us could say that we are above average (or, more accurately, the median)! People often have a skewed perception of their own abilities, believing themselves to be better than they really are. But this phenomenon is not only prevalent on the street.
In the realm of healthcare, the majority of people do not follow the medical recommendation and do not go to regular preventive medical check-ups, at least not as often as is recommended by the medical community. It is well-known that prevention is particularly important as diagnosing a disease in time makes the treatment more effective and increases the chances of being cured. Still, many people believe that they are unlikely to develop medical problems, and this is especially true of younger people, and those who are not actively experiencing symptoms (Sandroni & Squintani, 2004). And people who believe going to a preventive screening is unnecessary, are much less likely to go. This overly confident attitude is not uncommon among health workers either; according to a study, about one third of them overestimate their own abilities relative to their peers (Kovacs et al., 2020). Why?
Overconfidence bias is a form of miscalibration of subjective probabilities. It is about the tendency that an individual’s subjective confidence in his or her judgments is consistently larger than the objective accuracy of those judgments. People are less likely to go to the doctor for medical checkups because they are overconfident. In addition, healthcare workers with overconfidence bias are 26% less likely to manage patients correctly and exert less effort in clinical practice (Kovacs et al., 2020).
Availability bias
There are ways in which this overconfidence can diminish. One event that can reduce overconfidence is personal experience with medical problems. After someone from our social circle is diagnosed with a certain disease (especially if that person is of our age), the perceived probability that it can happen to us too increases, even when the objective probability of the disease has not changed. This personal experience makes medical problems more salient and more top-of-mind, leading to heightened awareness and heightened perception that we may be vulnerable as well. Particularly salient life events, such as a friend or family member becoming seriously ill, increases the “availability” of thoughts related to serious illness in our minds, making them more common, and making them seem much more likely. This cognitive bias can affect medical professionals too; as according to a study, it can influence physicians’ cancer screening recommendations. Doctors with personal cancer experience, such as cancer among friends, family, or coworkers are 17% more likely to act against the established guidelines and recommend ovarian cancer screening to low-risk women (Ragland et al., 2018). Why do we overestimate the probability of a disease as a result of personal experience?
Availability bias is about the tendency to judge probabilities and use information on immediate examples that come to mind when evaluating a specific topic, concept, method or decision. When there is more “available” information about personal experience with a particular disease, people tend to overweight judgements (probabilities) of that disease based on more recent, or impactful, information.
These cognitive biases are only a few examples of how our judgements, as patients or as medical providers, are influenced by our psychology. In order to improve the way healthcare is delivered, understanding these many “irrationalities” is important.
Genentech, (2018). Retrieved from https://www.gene.com/stories/cognitive-biases-in-healthcare?topic=respiratory-health
Kovacs, R., Lagarde, M. and Cairns, J. (2020). Overconfident health workers provide lower quality healthcare. Journal of Economic Psychology, 76, p.102213.
Puhl, R., and Brownell, K. D. (2001). Bias, discrimination, and obesity. Obesity research, 9(12), pp.788–805. https://doi.org/10.1038/oby.2001.108
Ragland, M., Trivers, K. F., Andrilla, C., Matthews, B., Miller, J., Lishner, D., Goff, B., and Baldwin, L. M. (2018). Physician Nonprofessional Cancer Experience and Ovarian Cancer Screening Practices: Results from a National Survey of Primary Care Physicians. Journal of women’s health (2002), 27(11), pp.1335–1341. https://doi.org/10.1089/jwh.2018.6947
Redelmeier, D., Katz, J. and Kahneman, D. (2003). Memories of colonoscopy: a randomized trial. Pain, 104(1), pp.187-194.
Sandroni, A., & Squintani, F. (2004). A survey on overconfidence, insurance and self-assessment training programs. Unpublished report, 1994-2004.
Svenson, O. (1981). Are we all less risky and more skillful than our fellow drivers?. Acta psychologica, 47(2), 143-148.
Oliver Ujvarossy ·
July 25, 2022
3 Strategies to Fight Procrastination
I cannot even count how many times I have picked up my phone to play a game while working on this blog. It wasn’t even a conscious act; I mindlessly picked up my phone and started playing with it after writing each sentence or two. With each distraction, the writing process became slower and more torn apart. Each time I put down my phone I had to re-enter the writing process, picking the line of thought back up again. It could have been less stressful if I had been able to keep myself focused, or had not waited until the last moment to finish this piece. I procrastinated moment-to-moment and pushed my work up against the deadline, even though I knew it would be better for me in the long run to get it done sooner rather than later. Why is it that we procrastinate, even though we do not want to? Is procrastination our fault, the manifestation of some innate human weakness, or something else? Is it possible to prevent ourselves from procrastinating, and if so, how?
What is procrastination? And why do we do it?
There is still no universally accepted definition of procrastination in academia. While some define it as a dysfunctional form of delay, others propose that it is a voluntary and unnecessary postponing of an action (Klingsieck, 2013). The lack of a mutually accepted definition and the subjectivity of these terms makes it difficult for researchers to investigate procrastination; however, in surveys, they can ask people directly about their experiences with procrastination. For instance, Nguyen et al. (2013) write that every fourth adult believes that procrastination defines their personality. Steel (2007) found that 75% of college students consider themselves procrastinators and 95% of these procrastinators wish to reduce the amount of time they procrastinate. They don’t wish to reduce it without reason: Berber Celik and Odaci (2020) write that procrastination increases stress, anxiety, and self-blame, which then leads to a decrease in performance at the workplace or in school, and ultimately leads to a decrease in subjective well-being.
Procrastination is an act that we recognize doing, we are aware of its negative consequences, and theoretically, we have the willingness to reduce it. However, as the previous statistics show, procrastination still exists on a large scale. So, the question arises: for what reason do we continue to procrastinate? How is it possible that we behave in this irrational way, and is procrastination predictable?
O’Donoghue and Rabin (1999) showed that people have a strong, irrational preference toward present benefits, even if future costs become higher as a result. This phenomenon is called the ‘present bias’, meaning that we are biased towards present outcomes. This is the reason why we prefer watching one more YouTube video instead of writing our paper, or smoking one more cigarette instead of going for a run. This is the mechanism of procrastination as well. We prefer small, present benefits (scrolling Instagram) and future costs (worse results, stressful finishing), instead of present costs (working or studying) and future benefits (stress-free relaxation).
Moreover, O’Donoghue and Rabin (1999) showed that the naivety of people also influences procrastination. If people are more optimistic regarding their future behaviour and believe that after one YouTube video they will definitely start their work, there is a higher chance of repetitive procrastination, as this optimism is false most of the time. Therefore, excessive optimism and self-assurance increases the chance of procrastination. However, if people are more pessimistic about their capability of doing things on time and without delay, there is a higher chance of avoiding procrastination, therefore breaking the bad pattern of behaviour. The takeaway message is to be cautious about our future behaviour, otherwise we fall into the classic trap: “I am going to start working, but only after this last video.” We know the last video is never really the last one.
What can we do to prevent procrastination?
Procrastination arises because of our preference for present benefits. Problems related to this present bias are usually answered by economics, and economists usually refer to this phenomenon as intertemporal choice or hyperbolic discounting. However, the presence of systematic irrationality in situations like this does not allow standard economics to offer helpful solutions, therefore, we need to turn to behaviorally-informed solutions to counter procrastination. So, what kind of strategies exist to avoid procrastination? Well, first of all, we need to be aware of our tendency to procrastinate. We need to accept the fact that we will not be productive after the “last” YouTube video. This is the starting step because otherwise, we will not feel the urge to beat procrastination. But what can we do next? The idea is to prevent present-biased behavior by making benefits that won’t appear until the future more relevant to ourselves in the present. How is that possible?
Visualization
One strategy is to visualize the results of the procrastinated action. For instance, imagine how nice it would be to have clean plates and an empty dishwasher, or how relaxing would it be to hand in that difficult assignment. Find a way to bring to mind your future benefits in the case you are not procrastinating. A key aspect about visualization is to serve your future interests too. This might seem difficult to realize at first, but scientists showed that if people have a good strategy to visualize future costs/benefits, their present bias decreases.
Ersner-Hershfield et al. (2009) showed that people feel connected to their future self or future situation in differing amounts. This means that some of us are more “carpe diem”, while others might be consistently focused on their distant future. Ersner-Hershfield et al. (2009) showed that if this connection to one’s future self is increased, there is a higher chance that their present behavior will serve their future interests. In other words, if we have a visualization technique to somehow emotionally invest ourselves in the future benefits of an action, then it can help to reduce procrastination as well.
Commitment Devices
Another strategy is to create a commitment device. The idea behind a commitment device is to take advantage of our optimism about the future to make commitments in the present. For instance, we may want to start saving for retirement, but each time our friends ask us if we want to go have a fun night out, we can’t resist the temptation to spend our money now and go with them. The solution is to set a commitment to save in the future, ideally one that is difficult to break. By setting a future date when money will automatically be transferred to a savings account, for example, we take our present desires out of the equation. Another commitment device is the use of an accountability partner: someone who helps you to keep your commitment. The social pressure imposed by other people can be a strong motivator for behaviour change, and choosing someone to keep you accountable to your commitments can really help to do so.
There are also many ways in which technology utilizes commitment devices to help fight procrastination. In the Forest app, for instance, the user commits themselves to a certain amount of time when they do not use their smartphone. If they succeed, they will see a blossoming tree, and regular use can yield a beautiful animated garden. However, if the users break their commitment, then trees will wither and die. Although there are no real costs involved in the use of this application, users experience stronger self-discipline, as it helps them to visualize the benefits of their commitment. Another alternative designed to help people dealing with commitment and procrastination is Stickk. Stickk is an online platform that allows people to create an agreement with themselves, where they define their goal, the period in which they want to achieve it, and the ability to add other people to help monitor their progress. Stickk also allows users to self-impose punishments for failing their commitments, such as automatically donating to causes that they disagree with, giving an extra incentive to avoid procrastination.
Implementation Intentions
The last strategy I will mention here is the use of implementation intentions. An implementation intention is a strategy that most often takes the form of an ‘if-then’ plan. You define a time, place, and context (the ‘if’) and a behaviour that you will do when you find yourself in that context (the ‘then’). Making a specific plan for how you will behave in a particular context increases the likelihood of doing so. Jaine (2020) proposes that if people have a detailed plan of how to deal with the procrastinated action, then when the time comes, the plan will trigger the desired behavior, meaning that people will act like their plan and will be less tempted to, for instance, procrastinate. In other words, it helps if we plan beforehand how to write our assignment, and ask questions about the task at hand, for example, on which day we should start or how many words we need to write. If we have the answers to these questions before starting the task, then, when the time comes we will act according to our plan..
Procrastination is a good example of our inherent irrationality: we continue to pursue a harmful activity of which we are aware and that we are willing to change, but we find ourselves unable to do so. There are several strategies available for fighting procrastination. Firstly, we can try visualizing future benefits: this helps to feel future benefits at the current time. Secondly, we can create commitment devices, ensuring that we keep ourselves or others accountable to their commitments. Lastly, we can use implementation intentions: by preparing a detailed plan of action, the existence of the plan can trigger us to implement the plan instead of procrastinating. By utilizing these techniques you can live a life free of procrastination.
Ariely, D., & Wertenbroch, K. (2002). Procrastination, Deadlines, and Performance: Self-Control by Precommitment. Psychological Science, 13( 3 ), 219–224. https://doi.org/10.1111/1467-9280.00441
Berber Çelik, I., & Odaci, H. (2020). Subjective well-being in university students: what are the impacts of procrastination and attachment styles? British Journal of Guidance & Counselling, 1–14. https://doi.org/10.1080/03069885.2020.1803211
Ersner-Hershfield, H., Garton, M., Ballard, K., Samanez-Larkin, G., & Knutson, B. (2009). Don’t stop thinking about tomorrow: Individual differences in future self-continuity account for saving. Judgement and Decision Making, 4( 4 ), 280–286.
Frederick, S., Loewenstein, G., & O’donoghue, T. (2002). Time Discounting and Time Preference: A Critical Review. Journal of Economic Literature, 40( 2 ), 351–401. https://doi.org/10.1257/jel.40.2.351
Jaine, R. (2020, May 21). Nudge or be nudged: Tricks of the trade from a behavioural scientist. Medium. https://medium.com/from-the-exosphere/nudge-or-be-nudged-tricks-of-the-trade-from-a-behavioural-scientist-d5a4bea020d2
Klingsieck, K. B. (2013). Procrastination. European Psychologist, 18( 1 ), 24–34. https://doi.org/10.1027/1016-9040/a000138
Nguyen, B., Steel, P., & Ferrari, J. R. (2013). Procrastination’s Impact in the Workplace and the Workplace’s Impact on Procrastination. International Journal of Selection and Assessment, 21( 4 ), 388–399. https://doi.org/10.1111/ijsa.12048
O’Donoghue, T., & Rabin, M. (1999). Doing It Now or Later. American Economic Review, 89( 1 ), 103–124. https://doi.org/10.1257/aer.89.1.103
Steel, P. (2007). The nature of procrastination: A meta-analytic and theoretical review of quintessential self-regulatory failure. Psychological Bulletin, 133( 1 ), 65–94. https://doi.org/10.1037/0033-2909.133.1.65
Vera Rapp ·
June 28, 2022
Why you buy: The neuroscience of luxury goods
The feathers of the male peacock are beautiful, but they are costly. It takes a lot of energy to grow and carry the train of feathers, making the animal vulnerable to predators. So why do they have these large tails? This seems like a perplexing, possibly counterintuitive evolutionary mystery, but there is an explanation for this phenomenon. Peacocks with larger feathers are more likely to attract potential mates, hence the large and showy plumage.
Humans are not that different to peacocks. Why do we spend money on luxury goods when a cheaper option would do the job just as well? We also partake in the phenomenon of costly displays to attract mates and signal social status. This article will explore several advances in neuroscience that have helped uncover the psychological and biological secrets as to why people buy expensive products to improve their social standing.
What is conspicuous consumption?
When customers make purchasing decisions based on the product’s ability to signal wealth and social status rather than simply for its inherent functional value, it is known as conspicuous consumption. Be it a sports car, a designer bag or just a shirt with an embroidered logo, many people display their social status by buying expensive items.
Scientists have been trying to explore conspicuous consumption for a long time. The most common research techniques to investigate consumer behaviour are surveys and questionnaires, but these have their pitfalls. Studies based on self-report rely on the participant’s ability and willingness to accurately recall and report their attitudes and/or past actions. But the problem is that when people describe their own behaviour, they often forget, misreport, or lie. The latter is especially significant in the research of conspicuous consumption and similar phenomena when one could feel ashamed of their attitudes or past behaviours.
Since humility is a virtue, many people like to think they do not flaunt their wealth and make irrational purchasing choices just to signal their high social status. Thanks to the advancement of neuroscientific research, brain imaging and physiological measurements provide a more objective technique to assess human decision-making. Thanks to these advances, researchers can explore the inherent mechanisms that facilitate conspicuous consumption.
Why do we like luxury brands?
There are a few factors that influence whether a consumer will purchase a product for its functional value rather than its social and material value: The product or brand needs to be recognisable, it has to be known as expensive, and the conspicuous consumer needs to be observed by others.
The phenomenon of people developing an affection for something that they are repeatedly exposed to is called the mere-exposure effect (Zajonc, 1968). This is the case for brands and products as well. A brain imaging study found that familiar brands activate the pallidum which is a brain region associated with positive emotions. On the other hand, unfamiliar brands activate the insula, a brain region associated with negative emotions (Esch et al., 2012). Luxury brands benefit from this phenomenon as the logos and designs are often well known. Most people can recognise the shape of a Birkin bag or the prancing horse of a Ferrari and it yields positive emotions in them.
While the positive emotions stemming from the recognisability of luxury brands could benefit value brands too, customers have other positive biases toward luxury brands. A study has found that seeing logos of luxury brands activates brain regions connected to positive emotions that are not activated when seeing logos of value brands (Schaefer & Rotte, 2007). Schaefer and Rotte (2007) have demonstrated with the use of functional magnetic resonance imaging (fMRI) that luxury brands activate self-relevant processing pathways in the brain. This suggests that customers make associations with themselves when viewing luxury brands. Schaefer and Rotte also explored what brain regions are active while seeing logos associated with value products. Value brands activate cognitive control pathways, the pathways that are responsible for evaluating actions and consequences, suggesting that luxury brands elicit emotions and associations to self, while value brands elicit pragmatic thinking and evaluation.
Conspicuous consumption gives people joy and satisfaction via the reward mechanisms in the brain. There is evidence that pictures of luxury cars elicit activation of the same reward-related brain areas that are activated by cocaine or an image of an attractive potential mate (Erk et al., 2002). Studies have shown that social rank and dominance are connected to the same reward mechanisms (Morgan et al., 2002). This connection is not a surprise as conspicuous consumption is inherently connected to social status.
We like luxury brands because they elicit positive emotions. These emotions are partly due to the mere-exposure effect and also because luxury brands activate the reward mechanisms of the brain. Contrary to value brands, these expensive brands are processed more emotionally with self-relevant thoughts rather than a pragmatic evaluation of consequences.
How do we overcome price aversion?
Although we have an inherent affection for luxury brands, why would we buy their products if there are cheaper options on the market? A conscious consumer would want to get the best quality for the lowest price. How come this is not the case in conspicuous consumption? It is because the price of the item signals that the consumer is wealthy. Therefore, the higher the price the stronger the signal.
There are many self-reported studies and pieces of anecdotal evidence that people rate the same item as better when it costs more. And neuroscientific research backs up that research as well, finding that people actually perceive more expensive products as better. Brain imaging studies have shown that when someone perceives the price of wine as higher, their experienced pleasantness increases as well, regardless of the quality of the wine (Plassmann et al., 2008). Perceived quality increases utility, therefore this is an example of how a higher price carries utility.
Neuropsychological research demonstrates that the recognisability of luxury brand logos carries utility too. A study has shown that the more recognisable a luxury brand’s logo, the more likely customers are to accept the high price of their products and purchase them (J. Wang, 2018). This is because the more recognisable a luxury brand is, the more likely that people will draw the conclusion that the user of the product is wealthy. This highlights the social aspect of conspicuous consumption as well.
Is it all about sex?
Conspicuous consumption could not exist in a vacuum, it only makes sense in a social context. One would not flaunt their wealth if there were no one to envy them and acknowledge their dominance in the social hierarchy. There is evidence that being observed changes customers’ behaviour.
Neuroscience research has shown that being in the company of others increases people’s tonic alertness in a resting state (Verbeke et al., 2014). Researchers have recorded the brain activity of women while viewing luxury branded products in isolation or in a group. Women in the study who were in the company of others had more late positive potential (LPP), which is a brain activity indicative of an intense emotional response. This suggests that luxury brands have even more emotional value in a social context (Pozharliev et al., 2019).
The social context of conspicuous consumption is more nuanced than simply being observed or not; it also depends on the role of the observer as a potential mate or as a competitor. Conspicuous consumption is in essence about attracting mates by advertising one’s high social status and dominance. Evolution has wired our brains based on certain drivers, one of which is reproduction. Our inclination for conspicuous consumption has developed in order to find a partner and procreate. As such, it is inherently connected to sex hormones like testosterone and estrogen.
Testosterone is linked to many hierarchical social interactions, and also has a connection to conspicuous consumption. Administering testosterone to men has increased their preference for status brands and products (Nave et al., 2018). Men also have higher testosterone levels when driving a luxury car than non-luxury cars. Saad and Vongas (2009) investigated how men’s testosterone levels change when their social status is threatened in front of a woman by the presence of a conspicuous consumer, finding that mens’ testosterone levels significantly increased. For men, testosterone plays a role in both the conspicuous consumers and those that observe them.
While research has not explored the connection of female hormones to conspicuous consumption as much as testosterone, it is seen that conspicuous consumption plays a role in relationships for women too. A study has found that conspicuous consumption in women is a means to deter competitors from their partners (Y. Wang & Griskevicius, 2014). Researchers have found evidence that the ovulatory cycle, and therefore female hormone levels, affect customer behaviour. Preovulatory women seek status goods to improve their position among competitors (other women) (Durante et al., 2014). These findings show that high estrogen levels correlate with conspicuous consumption in women.
Conspicuous consumption has evolved as a means to find mates and deter competition. As a phenomenon that is connected to reproduction, it is affected by the levels of female and male sex hormones, estrogen and testosterone respectively.
Conspicuous consumption
Much like the feathers of the peacock, luxury products and other wealth-signalling goods make people appear high-status and desirable to mates. With the help of neuroscience, conspicuous consumption behaviour can be objectively studied and eventually understood. The seemingly irrational behaviour of buying unnecessarily expensive luxury products makes more sense when brain imaging studies show how luxury brands are processed. The high price of these products serves the purpose of signalling the wealth of the consumer.
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Alex Moog ·
May 6, 2022
Measuring success: The road to hell is paved with good intentions
Snakes and Incentives
In the 1800s, when Britain occupied India, the British officers in Delhi wanted to reduce the number of dangerous venomous cobras slithering through the streets. Wanting a simple solution, they devised a standard economic incentive for the Indian public: the British officers offered a cash payout for every cobra head brought forth. The logic behind this scheme is clear, if you want to encourage a behaviour, in this case killing cobras, make that behaviour more valuable and market forces will solve the problem.
In some ways this scheme was very successful; it produced a huge number of cobra heads, indicating that people in Delhi were in fact killing a huge number of cobras. But the British officers’ reliance on using dead cobras as a measure of success meant that there was an obvious way to game this system. If one could get their hands on lots of cobras, they could be sold to the British for a small fortune.
Finding an efficient way to produce and kill cobras was now a viable career opportunity. As a result, many Indian citizens became cobra farmers, raising and slaughtering cobras to sell to the British. When the officers discovered that people were farming the snakes they promptly ended the programme, eliminating the incentive for the farmers to continue keeping the cobras in captivity. The conclusion was a mass release of cobras in the streets of Delhi, creating a problem much larger than before.
The British officers’ programme is an example of a perverse incentive, an incentive that results in an unintended or undesirable outcome. Perverse incentives demonstrate how choosing the wrong metric with which to measure a goal can cause a misalignment between intention and consequence. In the case of the British cobras-for-cash programme the outcome was a clear result of the incentive, but this is not always the case. Sometimes focusing on a single, narrow outcome can obscure the impact of an incentive or intervention on the system as a whole.
Plastic Bags and the Behavioural Ecosystem
Behaviour is always part of a larger system. The economic, social, and cultural forces that shape a behavioural ecosystem are complex and interrelated. A change in one behaviour can, and often does, cause related changes in different behaviours somewhere else in the system, a process known as spillover. Take, for example, one of the most celebrated recent examples of behavioural science implemented in public policy, the plastic bag tax.
The prevalence of single-use plastic products like straws, cups, and plastic shopping bags is a persistent environmental problem. Reducing the number of single-use plastics is therefore an important and worthwhile goal. To help curb the use of single-use plastic bags, many municipalities, cities, and countries have implemented programmes to incentivize shoppers to bring their own reusable shopping bags to the grocery store.
The initial idea to encourage people to reduce their reliance on plastic bags was to give a small discount on their grocery purchase if they didn’t take one. This turns out not to be particularly effective, as people don’t tend to respond enthusiastically to small monetary gains. However, using the principle of loss aversion, whereby people are more motivated to avoid losses than to earn equivalent gains, governments implemented a small fee for each plastic bag used at stores. One of the most well known implementations of this programme reduced the uptake of single-use plastic bags by 42% (Homonoff, 2018).
For years the plastic bag tax has been held as an example of the success of behavioural science, and to some extent this is true. Within the context of single-use plastic bag usage, it successfully improved on the metric with which it was measured. However, it turns out that many people also use these bags as liners in small trash cans in their homes, a behaviour you might recognize in yourself. By motivating people to reduce the number of plastic bags they bring home from the grocery store, the behaviour of using these ‘single-use’ bags for this secondary purpose was also reduced. As a consequence, people now needed to find another way to line their small trash cans. A recent study has found that in cities where there are taxes or bans on plastic grocery bags there is a related increase in the sale of similarly-sized plastic trash bags (Huang and Woodward, 2022).
While the bag tax showed the power of behavioural science to influence behaviour, measuring the success of the tax through the narrow focus on one kind of plastic obscured the lessened effect on plastic consumption in general. An understanding of the larger system at play is an important part of ensuring that the behaviour you aim to change is really going to have the intended impact on the outcome that matters.
Presumably, the designers of the cobra programme and the plastic bag tax had positive motivations, wanting safer streets and less environmental waste. However, as a consumer it is important to recognise when a system, and what it chooses to measure, are designed without your best interests at heart.
Daily Streaks and Satisfaction
Sometimes the misalignment resulting from an improper measurement is not between intention and consequence, but between the motivation of the designer and the desires or welfare of the recipient. Often, businesses measure the success of their products through metrics that do not align with what is best for their customers, clients, or users.
Take, for example, Duolingo – the language learning app. Learning a language is difficult work and requires consistent practice, a fact of which Duolingo is well aware, and which they push repeatedly to their users. The app encourages its language learners to complete at least one lesson every single day, and their primary motivational tool for doing so is the daily streak. Duolingo’s daily streaks keep track of the number of days in a row that a user completes a lesson. This tool is highly motivating, shown by the fact that some users have maintained streaks hundreds, or even thousands, of days long.
Seemingly this is a brilliant success for both Duolingo and its users – Duolingo’s metric of daily active users remains high, while their users practice languages consistently. The problem is that maintaining a daily streak on Duolingo doesn’t actually require the user to improve their understanding of a language, only to engage with the app. In order to tick your daily streak one notch higher you can repeat the same basic lesson every day, never progressing further in competency.
Therein lies Duolingo’s misalignment. The company is incentivising and encouraging daily engagement at the cost of helping their users learn a language. If a daily streak can keep someone coming back day after day, it doesn’t matter to Duolingo whether that streak leads to their users’ self-improvement.
Duolingo’s reliance on a feature detached from actual language learning causes users to feel a sense of pointlessness and dissatisfaction, and can even cause users to completely drop the app once their streak is broken (Mogavi et al., 2022). This isn’t to say it is impossible to learn a language using Duolingo, only that the motivational tools that they use can encourage behaviours that do not align with their users’ best interests.
Measuring Success
The simple act of measuring a behaviour will change how and how often it is performed. If you incentivise a behaviour, such as killing cobras, people will do what they can to maximise that outcome. Encouraging or discouraging a behaviour, like using reusable bags or not using plastic ones, will cause changes to related behaviours. And designing a system that measures behaviours that do not align with the goals of its users will ultimately cause dissatisfaction and disengagement.
As the cases of cobras, plastic bags, and daily streaks show, when designing a system, product, or service it is important to carefully consider what you measure and how you measure it, and to be conscious of how the products and services you use measure your behaviour.
So how can you avoid measuring the wrong behaviours?
Maximisation
Avoid measuring behaviours that can be maximised in unhealthy or unhelpful ways. This can be difficult to do from the outset, so checking in with your users to see how they have changed their behaviour in response to your incentives and interventions is important.
Spillover
Keep a wider focus on the behavioural ecosystem as a whole to make sure that the behaviour you measure does not have any negative spillover effects. Before implementing an intervention, investigate how the product, service, or system you intend to change interacts with other products, services, and systems to gain a better understanding of how the intervention will affect related behaviours.
Alignment
Align your measurements with your users’ goals to encourage long-term satisfaction. Ask your users or customers why they are using your product, and what they hope to achieve, and help them to measure those outcomes and behaviours.
Homonoff, T. A. (2013). Can small incentives have large effects. The Impact of Taxes versus Bonuses on Disposable Bag Use. Princeton University.
Huang, Y. K., & Woodward, R. T. (2022). Spillover Effects of Grocery Bag Legislation: Evidence of Bag Bans and Bag Fees. Environmental and Resource Economics, 1-31.
Mogavi, R. H., Guo, B., Zhang, Y., Haq, E. U., Hui, P., & Ma, X. (2022). When Gamification Spoils Your Learning: A Qualitative Case Study of Gamification Misuse in a Language-Learning App.
Catalina Grosz ·
October 15, 2021
How Our Behaviour Changes Through Dating Apps
At this time and age it is most likely you have heard of dating apps, at least in passing, if you have not already tried them out yourself. You may be familiar with Tinder, Hinge, Bumble or even Coffee Meets Bagel, the offer is overwhelming.
Using a Dating App: Motivations and Effects
All these apps were designed to allow us instant access to other bachelors in our area by the simple mechanism of swiping right on the faces we deem attractive, and left on those which we don’t. In theory, this sounds like an easy way to find a suitable partner. However, Hinge has reported that 81% of its users have not found a long-lasting relationship (Beck, 2016).
It is interesting to take a look at what draws us to dating apps in the first place. In a study by Sumter, Vandenbosch and Ligtenberg (2017), researchers took a closer look at what motivates us to use dating apps. They found that users have a variety of motivations when engaging with these apps, including love, casual sex, and self-worth validation.
It is with this last motivation that users may find that dating apps can lead to psychological distress and anxiety. As demonstrated by Holtzhausen et al. (2020), continuous use of social networking sites (SNSs) as means of seeking validation and comparison with others increases the pain of rejection. By putting ourselves “out there” on dating apps, we are welcoming disappointment and may therefore feel as if we have failed (Her & Timmermans, 2020). So why do we keep coming back to them?
Behaviour and Reinforcements
The reason may lie in the way that these apps are designed. The simple swiping motion opens the door to countless possible matches, giving the feeling of instant reward.
In order to reinforce swiping behaviour, dating apps make use of intermittent reinforcement. Just like a slot machine, dating apps aid themselves by presenting users with randomly placed reinforcers – a match. This form of reinforcement has been shown to work best when shaping new behaviours, since it produces longer-lasting habits (DeRusso et al., 2010). The idea being that the learner does not know when the reinforcement will appear. In the case of the slot machine, one can pull on the lever countless times before getting a reward. But simply knowing that the possibility of a reward exists makes one continue to pull on the lever since the next pull could be a jackpot. In a similar way, dating apps encourage their users to keep swiping in the hope that the next profile may be the love of their life.
We can take this behavioural analysis a step further by looking more closely at what happens inside our brains when we engage with dating apps. The secret lies in dopamine, a neurotransmitter involved in memory consolidation (Arias-Carrión et al., 2010). Dopamine fires when we are faced with the opportunity to receive a reward, incentivising us to repeat behaviours that have previously rewarded us. In the case of dating apps, dopamine fires whenever you get a match.
Moving Forward: Dating Apps and the Pandemic
It appears that dating apps are built to encourage habitual engagement from their users. However, what does the future hold for them? Over the past year, due to the pandemic, dating has increasingly moved towards online platforms. This move online has helped formalise what was formerly thought of as a ‘game’ (Hobbs, Owen & Gerber, 2016).
During this time, big online dating platforms such as Tinder have modified their platform, providing users with greater opportunities to express themselves (Shearing, 2021). Changes include the possibility of starting up a conversation with another user without a need to match with them. At a glance, it appears that the dating app has decided to adopt a more “realistic” approach to dating.
In an interview with the BBC, Tinder’s CEO Jim Lanzone explained that dating during lockdown has ceased to be linear. He explained that Tinder users were no longer following the well-known path of “swiping, matching, meeting for a date, having a relationship and getting married” (Shearing, 2021). Nowadays, we are getting to know each other better through the app by engaging in video calls, and when finally meeting up, going on adventures, as opposed to sitting down for coffee.
Helen Fisher (2020), a biological anthropologist who is Chief Science Adviser for Match.com, advocates for the addition of video calls. According to her analysis, this change of behaviour has actually removed many pressures that came with traditional dating. For instance, dating over video call removed the money debate. We no longer need to wonder whether we are expected to pay or to split the bill, letting us relax and enjoy the other person’s company. Another example lies with the sexual expectancies of a date. Once again we are free to relax instead of asking ourselves what the night holds. Like Fisher puts it, “You might have some sexy banter during a video chat but real sex is off the table.”
So what can we expect from dating apps moving forward? It is safe to say that dating apps are here to stay. Even if we don’t always find “the one”, dating apps still provide a good space where you can meet new people and share new experiences. The shift towards online dating has certainly helped in promoting dating apps and it will be very interesting to see how these new attitudes develop with time.
Arias-Carrión, O., Stamelou, M., Murillo-Rodríguez, E. et al. (2010). “Dopaminergic reward system: a short integrative review”. Int Arch Med 3(24). https://doi.org/10.1186/1755-7682-3-24
Beck, J. (2016). “The Rise of Dating-App Fatigue”. The Atlantic. Accessed via: https://www.theatlantic.com/health/archive/2016/10/the-unbearable-exhaustion-of-dating-apps/505184/
DeRusso, A. L., Fan, D., Gupta, J., Shelest, O., Costa, R. M. and Yin, H. H. (2010). “Instrumental uncertainty as a determinant of behavior under interval schedules of reinforcement”. Frontiers in Integrative Neuroscience 4(1). https://doi.org/10.3389/fnint.2010.00017
Fisher, H. (2020). “How Coronavirus Is Changing the Dating Game for the Better”. The New York Times. Accessed via: https://www.nytimes.com/2020/05/07/well/mind/dating-coronavirus-love-relationships.html
Her, Y. and Timmermans, E. (2020). “Tinder blue, mental flu? Exploring the associations between Tinder use and well-being”. Information, Communication & Society 24(9). https://doi.org/10.1080/1369118X.2020.1764606
Hobbs, M., Owen, S. and Gerber, L. (2016). “Liquid love? Dating apps, sex, relationships and the digital transformation of intimacy”. Journal of Sociology 53(2). https://doi.org/10.1177/1440783316662718
Holtzhausen, N., Fitzgerald, K.,Thakur, I. et al. (2020) “Swipe-based dating applications use and its association with mental health outcomes: a cross-sectional study”. BMC Psychol 8(22). https://doi.org/10.1186/s40359-020-0373-1
Rochat, L., Bianchi-Demicheli, F., Aboujaoude, E. and Khazaal, Y. (2019). “The psychology of ‘swiping’: A cluster analysis of the mobile dating app Tinder”. Journal of Behavioral Addictions 8(4). https://doi.org/10.1556/2006.8.2019.58
Shearing, H. (2021). “Tinder boss says Covid changed how we swipe right”. BBC News. Accessed via: https://www.bbc.co.uk/news/technology-57557180
Sumter, S. R, Vandenbosch and L., Ligtenberg, L. (2017). “Love me Tinder: Untangling emerging adults’ motivations for using the dating application Tinder”, Telematics and Informatics 34(1).https://doi.org/10.1016/j.tele.2016.04.009
Catalina Grosz ·
September 8, 2021
Fresh Start Effect: The Science Behind New Beginnings
Have you ever felt more motivated at the start of a new season or school year? Does the beginning of a new week give you the feeling of starting over? There are many reasons for you to be experiencing a renewal in your goal-driven attitudes at the passing of certain calendar dates or temporal landmarks. Here we will take a closer look at what researchers have coined the “fresh start effect” and how it affects our everyday behaviours.
What is a temporal landmark?
Before diving into the topic of fresh starts let us take a look at what researchers refer to as “temporal landmarks”. Temporal landmarks are a way of organizing experiences and memories. Up until recently, temporal landmarks were believed to include only given calendar dates, namely the start of a new year, a new month or even a new week. However, Dai, Milkman and Riis (2014) stated that the feeling of starting anew encapsulates more than simply specific calendar dates. According to their findings, temporal landmarks should also include relevant life events, “such as developmental milestones, life transitions, first experiences, and occasions of recurrent significance” (Dai, Milkman and Riis).
Dai and Li (2019) furthered this definition by defining two types of temporal landmarks. On one side they introduced those landmarks that provide us with the chance to renew our energy and motivation through breaks and relaxation, such as the day after a holiday or Mondays after the weekend. On the other side, there are those landmarks associated with changes in our environment. These include moving to a new place or transferring schools and are linked with establishing new, positive habits by breaking old ones.
Underlying Cognitive Mechanisms
The idea behind the fresh start effect is that a temporal landmark or special calendar date gives us a motivational boost. The two main reasons for this boost are the separation of our current selves from our past selves and the disruption of our focus on day-to-day minutiae.
By generating separate mental accounts for each time period, we relegate past mistakes to our former selves. As laid out by Peetz et al. (2014) “Individuals can selectively and spontaneously highlight temporal landmarks to regulate connections between temporal selves, typically to create distance with an undesirable version of themselves”. This psychological separation of selves gives us the feeling of starting over on a clean slate which in turn boosts our motivation. The feeling of starting over nudges us towards more goal-driven behaviours. In addition, we actively attempt to stay on track in order to avoid ruining the clean slate.
With this in mind, it is important to make a small disclaimer regarding fresh starts. If the chapter we are currently closing was a particularly good one our motivation levels may drop when we face a fresh start. For example, on the Monday after a particularly productive week, we may feel demotivated and think that we are not capable of repeating the same feat.
The second way in which fresh starts aid us is by allowing us to take a step back and see the bigger picture. Taking a step back changes the way we analyze our goals and objectives. By putting everything in perspective we are able to change from a bottom-up approach, in which we look only at the smaller pieces of our behaviour, to a top-down approach, where the main goal is the true driver of our decision-making. In this way, a top-down approach allows us to start breaking our bigger goals into more manageable chunks.
Applying the fresh start effect
The fresh start effect can actually affect our behaviour through our anticipation of the event. Simply knowing that a future landmark is coming up has an effect on our current motivation, since it reminds us of an ideal future state which we would like to achieve. Future landmarks also provide a dissociation between selves and allow us to compare our pre-landmark self with our desired post-landmark goal. The anticipation of an upcoming landmark also allows us contemplation of future hurdles which in turn makes it easier to prepare the necessary strategies for working around them.
In their article on the economics of personal plans, Beshears, Milkman & Schwartzstein (2016) list some ways in which the fresh start effect can be used to our advantage. For instance, they emphasize that if we simply prompt ourselves to “form concrete plans of action regarding when, where, and how [we] will implement [our] intentions” then we are already on track towards an improvement in follow-through. By making plans we are changing our behaviour for the better since planning helps us when it comes to overcoming barriers and following through on our intentions. Briefly put, “the simple act of planning to take an action can increase the likelihood of taking that action.”
Takeaways
As we look at a new school semester or a new season in the face, we would like you to take away some useful tips to make the best of this fresh start and of many more to come.
Firstly, remember that you can create your own fresh starts. You don’t need to wait until the turn of the month to make use of the fresh-start momentum. Find those moments that are unique to you which allow you to refill your aspirational batteries.
Secondly, remember that anticipation also builds a motivational drive. In order to be prepared to make the best of an upcoming temporal landmark make sure you plan ahead, as “contemplating logistical hurdles in advance makes it easier to develop strategies for working around them.” (Beshears, Milkman & Schwartzstein 2016).
Finally, understand that not all fresh starts will fill you with motivational energy. Fresh starts after a particularly good run can actually be hard, as can be anticipating a fresh start for a future self whom you hope to avoid. Remember that it is okay and that fresh starts not only come around often, but that you also have some control over when you start over.
Beshears, J., Milkman, K. L., & Schwartzstein, J. (2016). “Beyond Beta-Delta: The Emerging Economics of Personal Plans”. American Economic Review, 106 ( 5 ), 430-434. http://dx.doi.org/10.1257/aer.p20161100
Costall A. (2017) “1966 and all that: James Gibson and bottom-down theory”. Ecological Psychology. 29(3):221-30.
Dai, H. and Riis, J. (2019) “How experiencing and anticipating temporal landmarks influence motivation”. Current Opinion in Psychology (26)44–48. https://doi.org/10.1016/j.copsyc.2018.04.012
Dai, H, Milkman, K. L., Riis, J. (2014) “The Fresh Start Effect: Temporal Landmarks Motivate Aspirational Behavior”. Management Science 60(10):2563-2582. https://doi.org/10.1287/mnsc.2014.1901
Peetz J, Wilson AE (2014) “Marking time: selective use of temporal landmarks as barriers between current and future selves”. Pers Soc Psychol Bull, 40:44-56.
BeHive Consulting ·
May 27, 2021
A Behavioural Perspective on Lying – Part 2: How Modern Life Boosts Dishonesty
In the cost of lying part 1, competing models from economics and psychology battled it out to explain lying behaviour. Comparing these models to our actual behaviour, the psychological model incorporating other-regarding preferences and self-image concerns won out, as in reality we tend to lie surprisingly little. Rather than dishonest behaviour being the result of dishonest people, generally it depends more on the environment surrounding decision-making. Everyone is prone to impulsively taking advantage of an opportunity to benefit through lying. So then, having answered why we lie, the key question then becomes: when do we lie and how can we stop it?
This question can be tackled by examining the specific conditions that boost dishonesty, including a lack of self-control, increased psychological distance, and dishonest workplace cultures. What becomes apparent from looking at the whole picture is that the demands of modern life have created the perfect storm for these conditions to flourish. By identifying instances in daily life where dishonest behaviour might be more prevalent, this offers targets for intervention to tackle this growing epidemic.
Condition 1: Self Control
Contrary to the typical view of honesty as our default behaviour, when we are in tempting situations where it is easy to lie, it has been argued that we actually default to dishonesty (Bereby-Myer & Shalvi 2015). For example, you receive more change than you were supposed to and the waiter has already left. Would you really call them back over to give the change back? In these situations, honesty requires self-control to resist temptation, as people must override their automatic urge to behave dishonestly for selfish gain.
Following on from this, this means that one’s capacity for self control influences the way people respond to opportunities for dishonesty. The strength model of self control argued that self control is a limited resource that gets depleted when you have to inhibit your urges. So when you make future decisions after having your self control depleted, you are then less likely to make the self controlled decision (Baumeister et al 1998). This extends to dishonest behaviour, as those who had their self-control depleted were then more likely to be dishonest in a later problem solving task (Gino et al 2011).
There is a clear link between lowered self control and sleep deprivation. As a result, a lack of sleep is associated with higher levels of unethical behaviour (Barnes et al 2011). Explanations for this have also been linked to the idea of ‘moral awareness’, which is people’s ability to determine that a situation contains moral content. One study found that individuals who slept the least were also the least morally aware and worst at recognising unethical behaviour in others as well. Translating this numerically, 2.1 hours less sleep was equivalent to a 10% reduction in moral awareness (Barnes et al 2015). This effect is present even over the course of one day, as Kouchaki and Smith highlighted that we are more unethical in the afternoon than the morning due to decreased self control and moral awareness.
The trend of reduced sleep has been worsened over time, with one survey estimating around two thirds of the UK population are sleep-deprived (Princess Cruises 2019). We juggle multiple demands on our time such as long work hours and family commitments, meaning many of us are short on sleep on any given day. Worryingly, this may impact on our ability to make moral decisions and may lead to an increase in unethical decisions and dishonesty.
Solutions to a Lack of Self Control:
One general intervention to improve self control would be to lower levels of sleep deprivation, which would have the added bonus of boosting people’s mental and physical health as well. This could be done by altering work schedules, tailoring stress reduction programmes, or even creating nap facilities which has already been embraced by companies such as Google (The Guardian). Another way to overcome people’s depletion of self-control would be to give them time to deliberate. When time is limited, this limits people’s cognitive resources and reduces their ability to exert self-control. One study found that when people were under time pressure they were more dishonest compared to people who were given time to deliberate (Shalvi et al 2012). So, introducing an extended cooldown period for decisions will give people this deliberation time. Doing this would have the dual benefit of delaying payoff from the dishonest act. As people make more impulsive decisions if the reward from them is immediate, this might also help to increase honesty.
Condition 2: Psychological Distance
The second condition shown to boost dishonesty is psychological distance, which refers to a cognitive separation between the self and other events. This can be widened in a number of ways such as digital interactions, cashless transactions, and anonymity. Starting with digital interactions, one study found that people would cheat 3 times more on average when interacting with a machine rather than a person (Marechal et al 2018). The pandemic has forced the majority of our interactions online and in many instances they may not be coming back offline. This may be creating opportunities for deception as when interacting with a machine we don’t have the same social image concerns that we would for a human, so are more willing to lie.
Also, digital interactions often preserve anonymity of users. The more anonymous a decision maker feels the easier it is for them to psychologically distance themselves from their behaviour (Zhong et al 2010). When online, we don’t feel connected to what we are doing and have less of a chance of being caught, so find it easier to lie.
Finally, transactions are now moving away from tangible representations of money towards digital ones. Although convenient, this creates psychological distance between the act of dishonesty and the reward. One study demonstrated that this increased dishonesty through an experiment where they paid participants either in money directly, or in tokens that were then exchanged for money. They found participants were twice as likely to cheat and ask for a higher number when they were requesting tokens as opposed to money directly (Mazar et al 2008). So, this suggested that people were able to justify their dishonesty due to the psychological distance created by cheating to get more tokens instead of cheating to get more money directly. Applying this to modern life, we are moving towards a cashless society which may have implications for dishonest behaviour. People may find it easier to cheat and overestimate when transactions are digital and no money is exchanged, or if stock options and shares are used instead of money.
Solutions to Psychological Distance:
Psychological distance in both the public and private sector is widening quickly due to digitalisation and looks unlikely to slow down. Companies must be aware that this may have implications such as increased levels of attempted fraud and other dishonest behaviour. It will require interventions rooted in behavioural science to mitigate this risk. For example, psychological distance can be minimised by having users require accounts with names and profile photos attached. During interactions, referencing customers by name and getting them to verify the truthfulness of their answers prior to filling them in may help them take individual responsibility for their actions and reduce dishonesty (Jacobsen et al 2017). Going further, it has been shown that the presence of a mirror induces self-awareness and forces people to look at themselves, which could be used in interactions where humans aren’t present, such as ATMs or online with a camera image (Vincent et al 2013).
Condition 3: Culture & Social Norms
For dishonest behaviour to impose a strong psychological cost on liars requires a strong internalised social norm against lying, which is created by the culture one is in. As mentioned in part 1, there is substantial variation in lying depending on the country, which may be partially due to these differences in norms. But, more specific than country-wide variation is cultures within industries. The seemingly constant cycle of unethical scandals in the financial sector suggests there is a norm of dishonesty. If this norm continues, the financial sector may struggle as it relies on customers having confidence and trust in them.
One study investigated this by first priming people’s occupations and then having them report their number of heads in a coin flip game. People were compensated according to this number, meaning there was an incentive to lie and report a higher number. They found employees in the banking sector who were reminded of their professional identity behaved more dishonestly than ones from other industries. More worryingly as it can’t be explained by self-selection into the industry, they also behaved more dishonestly than banking employees who weren’t reminded of their occupation (Cohn et al 2014). This suggested the simple act of thinking of themselves as bankers led to more dishonest behaviour, providing support for the hypothesis that cultural norms within the banking industry directly contributes to dishonest behaviour.
The norm can be attributed to a problematic business culture favouring profit above all else. This likely created a self-fulfilling norm as well, since when we see the unethical behaviour of others go unpunished and even rewarded, we change our assessment of the likelihood of being caught cheating as well as our understanding of the social norms related to dishonesty (Gino et al 2009a). To quantify this, one study suggested that the addition of one cheater to a group ‘creates’ roughly 3 new cheaters (Carrell et al 2008). Therefore, the issue of dishonest behaviour within certain workplaces is only likely to grow over time without any intervention.
Solutions to Social Norms:
Changing the social norms surrounding dishonesty is a difficult task as once norms are in place they are relatively resistant to change. These norms would need to be internalised by individuals so that the choice to lie came with greater psychological costs. Most of us inherently have these personal morals or ethics but may not have moral awareness when we are making decisions. To fix this, explicit moral cues can be used to put people into a moral mindset before decision-making. This could be as simple as telling people ‘do not be a cheater’ before they make their decision. One study showed this reduced cheating behaviour, suggesting it worked through an explicit reference as to how cheating would affect people’s identity, as people who chose to cheat wouldn’t just be cheating, but they would become a cheater (Bryan et al 2013).
Conclusion
Overall, since the majority of dishonest behaviour appears to be a product of the environment, the issue of dishonest behaviour seemingly has a relatively straightforward solution: change the environment. Identifying situations where there is an easy opportunity to be dishonest means we can target these for intervention and monitoring. Although you could argue that we as a society are more sleep-deprived, morally bankrupt, and psychologically distant than ever, these are things that we can change. The first step is to bring awareness to them, and then it is up to governments and corporations to implement these low cost and easy changes from the top-down. As the cost of dishonesty to society builds up collectively over many small lies, so to can the solution be built on numerous small but effective changes.
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BeHive Consulting ·
April 29, 2021
A Behavioural Perspective on Lying – Part 1: Why do People Lie?
You would be hard pressed to find someone who says they’ve never been dishonest, and if they do – they’re probably lying. We all regularly engage with dishonest behaviour at various levels, often involving small acts of everyday dishonesty such as lying on a CV, calling in sick, taking office supplies, or returning used goods as new. Some of us go further and commit intellectual property theft or tax deception. Individually, they appear as relatively innocuous and victimless crimes, but on aggregate the cost of these behaviours add up significantly for organisations and society as a whole. For example, it is estimated that stealing from the workplace costs around $52 billion annually in the US alone (Weber et al 2003). The tax gap in the US, which is the difference between what the IRS estimates taxpayers should pay and what they actually pay, is over $300 billion a year which would translate to an overall noncompliance rate of 15% (Mazar & Ariely 2006). Therefore, these individual everyday small-scale deceptions contribute to the economy losing billions which has a knock on effect on wages, jobs, and investment.
Honest behaviour is a necessity for economic life, as it is expected when we report private information such as taxes and uphold contracts. If people stop trusting each other, society will no longer function as normal. Yet still, it is clear that dishonesty is a pervasive part of human nature. This blog is the first in a two-part series that examines why and when people lie, and based on this offers insight into potential interventions to boost honest behaviour. In this part, we will take a macro-level view of conflicting models from economics and psychology to answer the first question: why do people lie?
The Economic Perspective
Here, the classical economic perspective and psychological perspective are at odds with how they model dishonest behaviour and as a result how they suggest to combat it. Economic models of lying are based on rational self interest and the assumption of ‘homo economicus’ – a perfectly rational, selfish human being that is only interested in maximising their own payoffs. Models such as Becker’s rational theory of crime suggest that a cost-benefit analysis is conducted when deciding whether to be dishonest, weighing up the expected costs based on probability and severity of punishment against the benefits of the lie (Becker 1968). It argues that rational agents will opt for dishonest behaviour when the expected costs are lower than the gain. Under this model, the strategy to combat dishonesty would be to increase the probability of being caught as well as the magnitude of punishment. Historically, the economic perspective has informed how organisations and governments have tried to tackle the issue of societal dishonesty, but the evidence is mounting that the assumption of rational self interest that the economic perspective takes may not be how we actually behave. As a result, large and costly interventions using this approach may be ineffective.
The Reality
In reality, we are quite a lot better than this assumption! Not everyone cheats, even when they can get away with it and the punishment is non-existent. Most people either prefer not to, or cheat a little but don’t maximise their gains. One meta-analysis found that in fact people lie surprisingly little, and on average forgo about 75% of the potential gains from lying (Abeler et al 2019). This is far from the assumption of payoff-maximisation that the economic model would predict. Therefore, it is apparent that there are other motivations at play.
The Psychological Perspective
Psychological models of dishonesty have tried to explain these findings by integrating other-regarding preferences and self-image concerns. For example, the self concept maintenance theory suggests that people may act dishonestly as long as their behaviour doesn’t require them to negatively update their own self image of being good and honest people (Mazar et al 2008). This can be illustrated by the counterintuitive finding from a large scale field study that found citizens were actually more likely to return lost wallets containing more money than less. The authors suggested that this was in part due to citizens having concerns of theft aversion, which is not wanting to update their self-image as a thief (Cohn et al 2019).
Other models have suggested that we also suffer a cost of lying due to going against social norms. It has been suggested that we have internal reward mechanisms that reward or punish us depending on compliance with these norms and values (Mazar & Ariely 2006). Under this view, people’s preferences for dishonesty are shaped by their environment and interactions. Evidence for this can be found by looking at how behaviour varies across societies. One study conducted the same task in 23 countries where people could misreport their results for monetary gain. They then compared the average outcomes on this task to countries’ prevalence for rule violations indexed by the general level of political fraud, tax evasion and corruption. They found a clear correlation between high levels of rule violations in countries and more dishonest behaviour (Gachter & Schulz 2016). Therefore, the psychological perspective suggests that one way to combat dishonesty is by enhancing the psychological costs of acting dishonestly, such as through highlighting morality, self-image and social norms. Looking at actual human behaviour, it is clear that there is a lot more going on in people’s decisions to lie than just how bad it would be if they got caught.
Crucially, both the economic and psychological literature suggest that whether or not we are dishonest largely depends on the decision making environment we find ourselves in rather than who we are as people. As the psychological model incorporates, nobody likes to see themselves as a liar or cheater, but rather sometimes we take advantage of a tempting opportunity where it is easy to be dishonest to boost our personal gain. Therefore, knowing the conditions that increase the likelihood of dishonest behaviour enables us to identify environments where interventions might be the most effective in changing behaviour. This is the question we will explore in part 2 coming next week by taking a deeper dive into specific conditions that have been shown to enhance dishonesty. This includes ones that are rampant in our modern life – a lack of self-control created by sleep deprivation and time pressure, as well as digitalisation and the anonymity and psychological distance it brings with it.
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BeHive Consulting ·
March 26, 2021
The Illusion of Freedom of Choice: Why Less is Often More
In modern Western societies today, living with freedom is something that we highly value and advocate for. We praise democratic governments and condemn authoritarian leaders. We protest for important causes such as abortion rights, gay marriage, and the elimination of racism. We demand more variety in everything we consume, from food to clothes to entertainment. From everyday decisions such as choosing what restaurant to eat at, what phone to buy, and what clothes to wear; to more life-changing decisions such as choosing which career path to take, who to date, and when to start a family, we evaluate between countless of decisions every single day.
These ideas are all construed around the idea that having freedom of choice is something beneficial. With freedom of choice, we should be increasingly satisfied with our lives as we can choose whatever option we think will make us happiest. However, despite the number of choices we have today being ever-increasing, our happiness might not be. Since 1960, the US divorce rate has doubled, teen suicide rate has tripled, the prison population has quintupled, and serious clinical depression has increased tenfold. With an ever-expanding number of options, we are feeling increasingly stressed about all the different decisions we could take, which is consequently making us even unhappier. In other words, perhaps having more options is not as satisfying as we think it is, and our modern democratic society is making us prefer an escape from freedom to avoid feeling the burden of having excessive options.
Shopping for Jam
Findings in behavioural science support this controversial idea that we seek an escape from freedom. In a now-famous study, Iyengar & Lepper (2000) demonstrated this phenomenon through a fascinating experiment. At a busy supermarket, the researchers set up a table selling different jams over consecutive weekends. Customers could sample and buy jams at the tables. The only difference was that on one weekend, they displayed 24 different varieties of jam on the table; on the other, they displayed only 6.
The results from this study were striking. 60% of passers-by stopped at the table with 24 jams, indicating people are attracted to the prospect of having many options to choose from, but only 3% of customers purchased anything. In contrast, only 40% of passers-by stopped at the table with 6 jams, but 30% of these customers went on to purchase something.
What does this study tell us? Clearly, people were attracted to the idea of having many choices, but when it came down to the point of making a decision, in the face of many options most consumers preferred not to make a purchasing decision. This is what is known as the choice overload effect: people feel overwhelmed from having to evaluate many options and prefer not to purchase anything at all.
In addition, Iyengar & Lepper (2000) conducted a similar follow-up study, but this time with Godiva chocolates and students in a lab rather than jams in a supermarket. Students in this study chose to purchase chocolate from a large assortment or a small assortment and could rate their satisfaction with their selected Godiva chocolate if they made a purchasing decision. The researchers found that those who purchased chocolates from a large assortment were typically more unsatisfied with their choice as compared to those who purchased chocolates from a smaller assortment. When choosing from a large number of options, participants felt more regretful that they did not choose an alternative or had higher expectations for their selected chocolate, which consequently led to participants feeling dissatisfied with their selection.
Therefore, not only are consumers less likely to make any purchasing decisions from a large sample, but they are also more likely to be dissatisfied with their purchase if they did make one. These findings should come as no surprise. How many times have you gone to the candy section of a corner store, looked through all the different options of candy, and decided to not buy something? Or how often have you gone to a restaurant and ordered something, only to immediately wish that you had ordered something else?
Big Life Decisions
Of course, these experiments show us how people can feel dissatisfied when buying products like jams and chocolates, but what about bigger life decisions? Further studies conducted by Iyengar and colleagues also found similar results when choosing between options for 401(k) retirement plans and jobs. Having a lot of choices for these big life decisions can have drastic consequences to one’s livelihood and greatly diminish happiness, as people come to regret their own decisions. Apparently, having more options not only makes us more dissatisfied with small decisions like deciding which jam to buy, but also with big life decisions. Intriguingly, an experiment conducted by Steven Levitt (the well-known UChicago Professor and co-creator of the Freakonomics podcast) found that flipping a coin to make certain life decisions such as deciding to quit a job or end a relationship led to participants being substantially happier than those who had to actually make those tough decisions. Rather than having to make these important decisions, simply leaving it to chance may even be more conclusive to our happiness.
More is Less?
In a similar fashion to the jams experiment, we are attracted to the prospect of having freedom, but what ends up happening with too much freedom is that it ultimately causes us to experience choice overload, where we eventually prefer to avoid making decisions or feel dissatisfied with the decisions we do make. Indeed, Barry Schwartz, renowned psychologist and author of the book The Paradox of Choice: Why More Is Less, argues precisely this idea. Endlessly having to make decisions means having to live with the regret and disappointment from what could have been, and this can lead us to become increasingly dissatisfied with our own choices and consequently become increasingly unhappy with our lives.
Business Implications
Consumers clearly demand choice and enjoy the prospect of evaluating different options, but unknowingly to them, they are also more likely to be indecisive and dissatisfied with more options. Through understanding consumer psychology and decision-making strategies, businesses are able to overcome choice overload by altering the decision-making in a way that takes advantage of unconscious psychological biases and guide consumers to make certain choices. This is what behavioural scientists call choice architecture: presenting options in a way which can guide consumers into making more satisfactory decisions. Consumers unconsciously behave in systematically predictable ways, and behavioural scientists can design effective choice architecture to take advantage of our psychological biases and reduce the choice overload effect. For instance, reducing the number of options offered, comparing promoted options to less desirable alternatives, or providing defaults are all effective ways to reduce the choice overload effect and influence consumer decision-making. With good choice architecture, customers will experience less indecision and ultimately be more satisfied with their purchasing decisions, giving businesses a strong incentive to invest considerable time and effort into deciding how to present their options.
Chernev, A., Böckenholt, U., & Goodman, J. (2015). Choice overload: A conceptual review and meta-analysis. Journal Of Consumer Psychology, 25(2), 333-358. doi: 10.1016/j.jcps.2014.08.002
Fromm, E. (1941). Escape From Freedom. New York, NY: Farrar & Rinehart
Iyengar, S. S., Wells, R. E., & Schwartz, B. (2006). Doing better but feeling worse: Looking for the “best” job undermines satisfaction. Psychological Science, 17(2), 143-150.
Iyengar, S., & Lepper, M. (2000). When choice is demotivating: Can one desire too much of a good thing?. Journal Of Personality And Social Psychology, 79(6), 995-1006. doi: 10.1037//0022-3514.79.6.995
Levitt, S. D. (2021). Heads or tails: The impact of a coin toss on major life decisions and subsequent happiness. The Review of Economic Studies, 88(1), 378-405.
Myers, D. G. (2000). The American paradox: Spiritual hunger in an age of plenty. New Haven: Yale University Press.
Schwartz, B. (2005). The Paradox of Choice – Why More is Less (p. 4). New York: Harper Perennial.
Sethi-Iyengar, S., Huberman, G., & Jiang, W. (2004). How much choice is too much? Contributions to 401 (k) retirement plans. Pension design and structure: New lessons from behavioral finance, 83, 84-87.
BeHive Consulting ·
March 10, 2021
International Women’s Day: The Double Bind Bias; Empowering Women Leaders in the Workplace
Responding to the call
International Women’s Day is celebrated around the world on the 8th of March, a staple in Women’s History Month that makes women’s issues a focal point for all.
The theme for 2021 is #ChooseToChallenge; based on the premise that a challenged world is an alert world. We all have the individual responsibility to choose to challenge and call out gender bias and inequality. Perhaps uniquely, behavioral science has the means to provide insight into the biases that women face. Retrospectively, we see that the most insensitive decisions and harsh judgements are often made under the influence of behavioural biases, which leads to the continued battle for the recognition of women’s issues from a global perspective in your very own office environment.
Framing the issue
More women are working than ever before. As of June 2020, more than two-thirds (72.7%) of women aged 16–64 are employed in the UK, a percentage that has risen from 52.8% in 1971, when the Office for National Statistics first began recording this data. However, during the pandemic, women were 5% more likely to have lost their jobs due to Covid-19 than men. In addition, 60% of essential workers are women, and women comprise 77% of the labor force which is at high risk of contracting Covid-19. Furthermore, the majority of mothers are now able to work, with the number of mothers, and non-mothers participating in the workforce almost equal (74.1% and 75% respectively).
So, we are all good, right?
This all changes when we shift our perspective to look at the percentage of women in senior leadership roles. In 2018-2019, not so long ago, women represented 18.6% of executive committee members, 29.5% of direct reports, and 27.9% of both roles combined in the FTSE 250. If we climb even further up the ladder, these numbers become even more dismal, where only 8 women (3.2%) held CEO roles in the FTSE 250 as of October 2019. This lack of women leaders creates a scarcity of role models that can inspire other women to enter and, importantly, stay in the workforce.
So why is there a mismatch?
Studies have shown that unconscious bias is rife in the workplace. Gender stereotypes, in particular, permeate the environments in which women work. This has very much been seen by research. Experiments have shown that the brain categorizes people by race in less than one-tenth of a second, about 50 milliseconds before determining sex. If that wasn’t enough, a Yale University study found that male and female scientists, trained to be objective, were more likely to hire men, consider them more competent than women, and pay them $4,000 more per year than women.
“Superwomen in a Double Bind”
Unlike their male counterparts, for women, success in the workplace takes more than just job competency and ambition. Female leaders are not just expected to lead, but are often tasked with additional emotional labor. They need to be both direct and authoritative while maintaining a likable image. This often leads to them ending up in a bit of a bind.
The Double Bind Bias:
This can be described as a problem of a mismatch between what is expected of a leader, and what is expected from a woman. This is often as a result of biases that affect women. Research has shown that there are two primary kinds of gender bias that affect women, the descriptive and prescriptive bias.
We can define a descriptive bias as the labels we attach and associate with certain social groups and communities, and prescriptive bias is how they are expected to behave. When someone does not conform to these prescribed roles and behaviors they can be penalized or punished. There is the expectation for women to be caring, warm, emotional, among other traits, and men are expected to be assertive, rational, competent and objective. So, when it comes to promotion, these traits are sometimes automatically prescribed to people due to their gender without consideration of other factors, like their individual personalities; therefore, in general, men are assumed to be a better fit as a leader.
When a woman does not fit the role that is traditionally assigned to her, and attempts to claim what is seen to be a male position is seen as breaking the norm, this is a prescriptive bias. So, when a woman is decisive, she might be perceived as “brusque” and “abrupt”, or even “bossy”. Therefore, for the same kind of leadership behavior, women might be penalized while a man is commended.
This brings us to the problem of “likability”, where women who are not assertive and fit the gender stereotype of a woman as being gentle and caring tend to be liked more but not considered as leadership material. On the other hand, women who display traditional “masculine” qualities such as assertiveness, forcefulness, and ambition are labeled as “bitchy”, unfeminine and aggressive, and hence generally disliked. In both cases, women are then less likely to be promoted than a man. Men do not face the same problem, because what is considered “bossy” in a woman are considered leadership qualities in a man. Thus the double-bind effect.
As a man gets more successful, he is better liked by men and women, and as a woman gets more successful, she is less liked by men and women.
– Sheryl Sandberg, Lean In
Consider this:
A Fortune study found that while 58.9% of men’s performance reviews contain critical feedback related to their skills, 87.9% of women’s reviews focus on critical feedback and references to their personalities. So we can see that women not only have to work harder at their jobs to be taken seriously, but they’re expected to adjust their behavior to avoid seeming emotional or confrontational. Meanwhile, men can exhibit dominant, competitive behaviors in leadership roles without having to walk the tightrope between their gender and their job.
Overcoming biases to work towards an equal society
The long-held assumption that women take care and men take charge seems to persist, even though women today comprise more than half of the talent. Women hold some 60% of graduate degrees, and the majority (64% of senior women, according to Center for Talent Innovation) are eager to be promoted.
It is important that we are aware of these biases that can exist unknowingly, recognize and acknowledge them, since by naming these biases we can alleviate their power over the system at large. There is no point saying that we are all unbiased and unprejudiced, because these are unconscious biases that are shaped by our cultural and social conditioning.
For both men and women, it is important to speak out and interrupt if they notice any remarks that demonstrate this kind of prejudice, such as “she is emotional” or that “she is not very caring”, as these can affect how competence is perceived, and these are usually not labels that would be assigned to men in the same situation.
Appropriate bias training is important for all members of a group so that they are aware of not only their actions but also the language and words that they employ. Words, even when meant as a joke or banter, can create a feeling of mistrust rather than a positive workplace. It is really important that we create a culture where men are entered into this debate as much as women, and are seen as ambassadors for equality and female leaders. Likewise, it is also important to consider that it is not only men who carry these biases, women can discriminate against women too, and penalize other women for being successful, or aspiring to be.
Most importantly, companies and organizations have to take a closer look at their workplace policies and redefine what a “leader” really means. We need to renew our perspective on the traditional gender norms, and the way we assign leadership qualities.
From challenge comes change, so reflecting on this International Women’s Day and Women’s History Month, let’s all choose to challenge. Raise awareness against bias.
Going From No to Yes: Utilizing Insights From Behavioural Science to Increase Vaccination Uptake
The COVID-19 pandemic is continuing at an increased pace to disrupt economic and societal order while imposing enormous burdens of morbidity and mortality. Although the newly developed vaccines by Pfizer & BioNTech, Moderna, and AstraZeneca are celebrated by many in anticipation of the eventual loosening of COVID’s grip on their lives, another subtle, yet profound, challenge remains to be resolved to go back to the new normal – mass vaccination.
Figure 1: Attitudes towards vaccination | Source: IPSOS, 2020, p.1.
Governments need not only to provide ready access to nationwide vaccination against COVID-19, but also to develop strategies that increase public confidence in and acceptance of the developed vaccines. Alas, in many countries, vaccine hesitancy, that is, the “delay in acceptance or refusal of vaccines despite availability of vaccination services” (WHO, 2020, p.1), manifest itself as a substantial obstacle to achieve community immunity that protects the whole population. Specifically, current levels of willingness to accept a COVID-19 vaccine are insufficient to meet the requirements to attain mass coverage in most of the countries surveyed worldwide. Globally, roughly one-third of people are either undecided or against vaccination, many of them indicating concerns about potential side-effects (Milkman, 2020 & Ipsos, 2020).
The situation is even direr in countries whereby there is a low level of trust in government and the public healthcare system – as trust plays an enormous role in the willingness to get vaccinated (Lazarus et al. 2020). As such, almost 50% of the Hungarian population do not have an either negative or positive stance towards vaccination, with people aged 18-24 being most likely to oppose the vaccine while people over 65 the most likely to accept, and only 14.9% of the population indicate their intent to get vaccinated (KSH, 2020). These, together with the significant decline between August 2020 and October 2020 in the number of people indicating that they will receive vaccination, suggest a challenge of behaviour change that can be overcome through the effective application of behavioural science, encouraging more people to do the right thing for both themselves and the society in general.
As in many cases, showing why people do not behave as they should, can also shed light into, by implication, how to reorient mass behaviour. With regard to COVID-19 inoculation, overcoming vaccine hesitancy is an outcome behaviour that arises from the interaction of a multitude of factors that can potentially influence an individual’s decision to search for and get vaccination. Although many think that communicating the reasons for vaccination should suffice for an average individual to get vaccinated, vaccine hesitancy has numerous, context-specific root causes that are not knowledge related – the causes that are grouped as complacency, confidence, and convenience by the SAGE Working Group on Vaccine Hesitancy.
Complacency: Why do young adults not feel the need to get vaccinated?
Vaccination behaviour is traditionally viewed as an individual decision-making task whereby the risks of being unvaccinated are evaluated against the risks of the disease the vaccine prevents. Complacency occurs when there is a lack of perceived risk of the vaccine-preventable disease to the extent that vaccination is not regarded as a necessary preventive action by the decision-maker.
Figure 3: COVID-19 Mortality Rate by Age Group | Source: OurWorldinData, 2020
There exists a risk asymmetry between age groups for COVID-19 contraction. Whereas the mortality rate is between 0.2% and 0.4% for people aged below 50, the death rate is significantly higher – 3.6% in the 60-69 age bracket, 8% among those aged 70-79, and 14.8% for people aged 80 or more (Ourworldindata, 2020). Unpredictability of adverse reactions to the vaccines, together with the increased susceptibility to misinformation, lead people to exaggerate concerns about potential side effects, which are contingent and exotic and result in people perceiving the risks of getting vaccinated to be greater than they actually are, negatively affecting the willingness to get inoculated. Accordingly, vaccine-related events are perceived as man-made risks that can be avoided through bypassing inoculation, whereas COVID-19 contraction is perceived as a natural-risk that can only be avoided by taking that extra risk posed by the vaccines. Viewed through this lens, the low levels of intention to get vaccinated in young adults becomes a natural result due to the fact that the risks associated with vaccination outweigh those of not vaccination.
So how can behavioural science help to counteract this phenomenon? Every individual has something at stake in regard to the pandemic. For some it is their health, whereas for others it is their social lives that they want to protect and take back. However, what has been done hitherto has been unsatisfactory in the sense that the authorities have taken a one-size-fits-all approach to communicate the potential risks and benefits of not getting vaccinated. What matters the most for young adults is to continue their normal lives, and for this group, the benefits of vaccination, rather than the risks of not vaccinating should be communicated, establishing the causal link among vaccination, community immunity, and the new normal; thereby overcoming the lack of perceived risk via shifting the focus to benefits.
Confidence: The trust in the system
In almost every decision we make, trust is a key factor, and COVID-19 vaccination is no exception to this rule. Confidence comprises the “trust in the effectiveness and safety of vaccines, the system that delivers them, and the motivation of policy-makers who make vaccine decisions” (Macdonald & SAGE Group on Vaccine Hesitancy, 2015, p. 2). The most recent global survey found that high level of trust in the government was the most reliable determinant for vaccination intention, overshadowing population mortality, age, education, and even family sickness with COVID-19 (Lazarus et al., 2020). It is also interesting to observe that perceived safety of vaccines by the region is lowest in Eastern Europe (GallupWorldPoll, 2018). These might suggest that there exists an uncomfortable echoing of the past regimes and experiences, whereby individuals bring in their negative past experiences with government-related authorities whilst evaluating the information that emanate from them. But it is notable that anti-vaxxer groups gain support as well, a global trend which is also observable in the surrounding countries. In addition, the widespread concerns about lack of due diligence in developing the vaccines further exacerbate the problem by decreasing the intention to get vaccinated.
Behavioural science suggests that the value of information depends on the source of it. Evidence shows that people look to their peers for hints about how to behave. To reach specific target groups, community leaders in social circles can act as messengers. In addition, providing tangible, social cues, such as ‘I received vaccination’ stickers can and will not only instil a new social norm of getting vaccinated but also address the fears and concerns about safety, increasing the intention to get inoculated. However, governments and health authorities should also be proactive to turn over the problem by addressing the widespread concerns publicly. It is equally important not to become aggressive with communicating, as it might scare away those who are hesitant. In short – information flow and communication should be consistent, reassuring, adequate in its content, but not overused, and should always come from a person with authority and of reputation.
Convenience: When intention does not follow action
When people make decisions, despite the inner intention they possess, seemingly small factors hinder their ability and desire to follow-through. Apropos of COVID-19, convenience captures the potential negative effects of physical availability, hassle factors (e.g. paperwork), required mental effort, affordability, and time on the vaccination decision. In this case, affordability and availability do not appear to be important considerations, except for developing countries. Yet, given that to get the sufficient number of antibodies people need to receive two inoculations several weeks apart, possible adverse experiences with the initial shot, together with people’s tendency to forget, postpone, and change their decisions can negatively affect the desired vaccination behaviour.
Luckily, behavioural science has proved to be highly effective in bridging the gap between intention and action. Previous randomized experiments reveal that even the simplest techniques such as sending a reminder to individuals about their upcoming appointment increased vaccination by 36% (Chapman et al, 2010). Providing flexible options to people and accounting for their tendency to forget also proved to be highly effective. After all, it all boils down to understanding people and creating the most convenient ways to follow their intention, sometimes giving them a nudge in the back by sending them clear guidelines and reminders. Communicating these guidelines in a simple, yet memorable way can also help – in the case of the BioNTech-Pfizer vaccine, communicating the recommended 3-week interval can be highly effective.
Looking Ahead
The existing prevalence of wide variation – both in sociodemographic and health characteristics in willingness to accept vaccination delays not only the elimination of the pandemic but also the expected societal and economic recovery. According to the experts, between 60-80% of the population needs to get vaccinated to overcome the pandemic (Fox et al., 2020). Yet, with one-third of people being hesitant or rejecting vaccination, there remains a significant gap to reach the goal and to attain herd immunity. The increased susceptibility to misinformation, lack of perceived risk in certain age groups, mistrust in the government and healthcare system, and exaggerated concerns about the side effects of vaccines further exacerbate the problem. The insights of behavioural science, through pinpointing the most effective messenger channels that guide behaviour, instilling trust within the healthcare system, and nudging people to follow-through with their intentions, would be of seminal importance in developing a new conceptualization of vaccination for hesitant subgroups and to bring the pandemic to an end.
Since the beginning of the pandemic, 4883 people, on average, have lost their lives each day due to COVID-19. The potential to save lives has never been higher before. Yet, this potential can only be achieved if there is a mass behaviour change, for which, the insights of behavioural science would be critical to obtain community immunity in the shortest period of time. It is vaccination, not vaccines by themselves, that saves lives.
Chapman, B. G., Li, M., Colby, H. and Yoon, H. (2010). Opting in vs Opting out of influenza vaccination. JAMA The Journal of the American Medical Association, 304(1), pp. 43-44.
Fox, J. S., Potu, P., Lachmann, M. Srinivasan, R. and Meyers, A. L. (2020). The COVID-19 herd immunity threshold is not low: A re-analysis of European data from spring 2020. MedRxiv. doi: 10.1101/2020.12.01.20242289
GallupWorldPoll. (2018). Attitudes to vaccines [Online]. Available at: https://wellcome.org/reports/wellcome-global-monitor/2018/chapter-5-attitudes-vaccines
IPSOS. (2020). COVID-19 vaccination intent is decreasing globally [Online]. Available at: https://www.ipsos.com/en/global-attitudes-covid-19-vaccine-october-2020.
KSH. (2020). HSCO Weekly Monitor [Online]. Available at: http://www.ksh.hu/weekly-monitor/covid.html.
Lazarus, V. J., Ratzan, C. S., Palayew, A., Gostin, O. L., Larson, J. H., Rabin, K., Kimball, S. and El-Mohandes, A. (2020). A global survey of potential acceptance of a COVID-19 vaccine. Nature Medicine. doi: /10.1038/s41591-020-1124-9.
Macdonald, E. N. and the SAGE Working Group. (2015). Vaccine Hesitancy: Definition, scope, and determinants. Vaccine, 33(34), pp. 4161-4164.
Milkman, K. (2020). Katy Milkman on how to nudge people to accept a COVID-19 vaccine. The Economist [Online]. Available at: https://www.economist.com/by-invitation/2020/11/30/katy-milkman-on-how-to-nudge-people-to-accept-a-covid-19-vaccine.
OurWorldInData. (2020). Statistics and Research: Coronavirus Pandemic [Online]. Available at: https://ourworldindata.org/coronavirus.
WHO. (2020). Vaccine Hesitancy: what it means and what we need to know in order to tackle it [Online]. Available at: https://www.who.int/immunization/research/forums_and_initiatives/1_RButler_VH_Threat_Child_Health_gvirf16.pdf?ua=1.
Noemi Molnar ·
January 2, 2021
5 cognitive biases contributing to COVID-19 vaccine hesitancy
At least 4 out of 10 people don’t want to be vaccinated. Why? Because of vaccine hesitancy, which is driven by cognitive biases.
Researchers worked tirelessly to find the ultimate way out of the pandemic: vaccination. Now that the vaccine(s) is ready and approved, our lives have the chance to turn back to normal. However, there seems to be another roadblock: vaccine hesitancy. Vaccine hesitancy refers to “delay in acceptance or refusal of vaccines despite availability of vaccination services” (ECDC, 2020, p.1). In this article we will explore the five most likely biases that can contribute to this phenomenon.
I. Omission bias
Omission bias is a preference for inaction even when taking action is substantially more beneficial.
In the context of vaccination, people tend to give disproportionate weight to harms of receiving a vaccination and dismiss harms that accrue from not receiving a vaccination – such as getting infected with COVID-19, infecting others, life not returning back to normal, or not being able to travel. Many people are concerned with the long-term consequences of the vaccines and fear that they have not been tested long enough. However, they often don’t consider (or not as much) the potential long-term negative side effects of COVID-19, even though researchers have already found many: higher chance of developing diabetes, depression, etc.
How can people’s omission bias be eliminated/counteracted?
Compare risks directly, focusing separately on short-term and long-term (side) effects (e.g. vaccine’s long-term side effects vs. possible COVID-19 long-term consequences/ complications).
Highlight the unique benefits of vaccination and what those who do not get vaccinated miss out on (e.g. highlight events with emotional connections such as: seeing friends/family without the fear of getting infected, having a good time while traveling, etc.).
Have a public Q&A where doubts are addressed by experts and provide tangible examples from messenger channels that can influence the perception of the decision maker.
Availability bias is the human tendency to think that examples that come easily to mind are more representative than they actually are for a given population. This hampers individuals’ critical thinking and, as a result, the validity of their decisions.
In the context of vaccination, media and social circles are much more likely to bring up rare occurrences (e.g. allergic reaction to the vaccine (“2 Alaska Health Workers Got Emergency Treatment After Receiving Pfizer’s Vaccine”)). Therefore, an individual is much more likely to have these cases in mind and think that this could happen to him/her. As a result, the perception of the safety of vaccines can decrease disproportionately.
How can people’s availability bias be eliminated/counteracted?
Highlight the positive changes the vaccine brought to people, give voice to individuals who received it and are happy with the results (share personal stories). Companies can encourage their employees as well by giving advocates a voice and by implying that this is the new norm.
Show easy to understand statistics that highlight the general positive trend.
Require media to report the cause of a side effect and to emphasize that the side effect is a rare occurrence, which specific populations can be affected by.
III. Optimism bias
Optimism bias is a cognitive bias that causes someone to believe that they are less likely to experience a negative event.
As time flies, people are getting more and more reassurance that they are not going to catch the disease, that they are part of the lucky group. This can lead to a fake optimism bias which can explain why many people are not taking precautions such as social distancing, wearing masks, or hand-sanitizing. In the context of vaccination, people can show the same confidence in their perception of not needing the vaccines due to not catching the virus or even if infected, having light symptoms. They can also underestimate the likelihood of infecting others causing harm/difficulties in their social circle, therefore they might not feel the need to get vaccinated to protect others or society as a whole.
How can people’s optimism bias be eliminated/counteracted?
Continuously remind people about the risks of COVID-19 and the presence of the disease in their environment.
Make it personal – highlight personal stories, show how older people have to live due to disease.
Tailor the message to each generation, target group. Some examples: – e.g.: the younger generations are least likely to feel the need for vaccination, therefore they can be encouraged by taking responsibility for other people, such as their grandparents – ask them “who are they getting vaccinated for”. – Good examples of messages for healthcare workers can be found here: https://www.cdc.gov/vaccines/covid-19/health-systems-communication-toolkit.html
Confirmation biasis the tendency to search for, interpret, favor, and recall information in a way that confirms or supports one’s prior beliefs or values.
In the context of vaccination, if people believe that vaccination can be harmful, when they read the news or talk to other people, they will only focus on information which highlights real or even false evidence confirming/reassuring their original beliefs. Many people rely on others to make their decisions, such as parents, friends, doctors; therefore, people can easily take on other’s belief system and not think critically on their own.
How can people’s confirmation bias be eliminated/counteracted?
Create cognitive dissonance in people – make them think about it or use humor to highlight flaws in their decision making (e.g. Jimmy Kimmel: A Message for the Anti-Vaccine Movement: https://www.youtube.com/watch?v=QgpfNScEd3M).
Utilize social identity – show that respected identities within the group to which an individual belongs are acting contrary to their beliefs. This, in return, makes people consider the validity of their own judgments and reevaluate their choice.
Make people consider the alternatives themselves, i.e. the null hypothesis.
V. Natural risk bias
Natural risk bias in the context of vaccination is when a risk of disease is more acceptable than man-made risks.
Just as we expect self-driving cars to make no mistakes at all, but watch thousands of people die due to man-caused accidents, a man-made vaccine has to meet the highest standards. Any small side-effects or negative news will probably be taken out of proportion.
How can people’s natural risk bias be eliminated/counteracted?
Help people understand that (medical) experts support the current vaccines and why they should trust them.
Address key concerns of the public on several occasion (e.g. vaccines cause autism in children).
Highlight the success of prior vaccinations, how they made our lives safer even though we do not realize it now.
***Another psychological factor that is important to know***
As we mentioned the importance of the right messenger for specific groups, it is useful to know more about the messenger effect.
Messenger effect
We are heavily influenced by who communicates information. Some people we listen to, some we don’t, and some we question.
In the context of vaccination, people are heavily influenced by who communicates information about the safety/importance of vaccines. The question is who do people trust and turn to for advice: their doctors, researchers, government officials, family, or just their friends?
Who can be the right messenger?
The country’s leaders should be one of the first to be vaccinated to show people they are confident in the vaccine(s).
Doctors and other health professionals can be a reliable, expert source of information.
People should be encouraged to become advocates in their social circle (e.g. “I am vaccinated” stickers, Facebook covers could be passed around).
Influential people should address specific target groups.
All in all, one of the biggest challenges of 2021 is going to be gaining public acceptance of COVID-19 vaccines. Countries that can effectively and efficiently vaccinate their citizens can get back to ‘normal’ and thus recover quicker from the pandemic. Behavioural science can provide great advantage in vaccination efforts as people can be nudged towards better decisions. Some governments/companies are already utilizing behavioural science tools as we speak.
2 Alaska Health Workers Got Emergency Treatment After Receiving Pfizer’s Vaccine. (2020). Retrieved 29 December 2020, from https://www.nytimes.com/2020/12/16/health/covid-pfizer-vaccine-allergic-reaction.html
Brewer, N. T., Chapman, G. B., Rothman, A. J., Leask, J., & Kempe, A. (2017). Increasing Vaccination: Putting Psychological Science Into Action. Psychological Science in the Public Interest: A Journal of the American Psychological Society, 18(3), 149–207.
Browne, M., Thomson, P., Rockloff, M. J., & Pennycook, G. (2015). Going against the Herd: Psychological and Cultural Factors Underlying the “Vaccination Confidence Gap.” In PLOS ONE (Vol. 10, Issue 9, p. e0132562). https://doi.org/10.1371/journal.pone.0132562
Connolly, T., & Reb, J. (2003). Omission bias in vaccination decisions: Where’s the “omission”? Where’s the “bias”? In Organizational Behavior and Human Decision Processes (Vol. 91, Issue 2, pp. 186–202). https://doi.org/10.1016/s0749-5978(03)00057-8
Covello, V. T. (1988). Informing people about radiation risks: a review of obstacles to public understanding and effective risk communication (No. INIS-XN–148). https://inis.iaea.org/search/search.aspx?orig_q=RN:20016912
Dolan, P., Hallsworth, M., Halpern, D., King, D., & Vlaev, I. (2010). MINDSPACE: influencing behaviour for public policy. 96.
Klayman, J. (1995). Varieties of Confirmation Bias. In J. Busemeyer, R. Hastie, & D. L. Medin (Eds.), Psychology of Learning and Motivation (Vol. 32, pp. 385–418). Academic Press.
Long-term effects of COVID-19. (2020). Retrieved 29 December 2020, from https://www.who.int/docs/default-source/coronaviruse/risk-comms-updates/update-36-long-term-symptoms.pdf?sfvrsn=5d3789a6_2
Sharot, T. (2011). The optimism bias. Current Biology: CB, 21(23), R941–R945.
Tversky, A., & Kahneman, D. (1973). Availability: A heuristic for judging frequency and probability. Cognitive Psychology, 5(2), 207–232.
Vaccine hesitancy. (2020). Retrieved 29 December 2020, from https://www.ecdc.europa.eu/en/immunisation-vaccines/vaccine-hesitancy
Cover photo taken from: https://www.pharmaceutical-journal.com/news-and-analysis/opinion/editorial/were-running-out-of-time-to-tackle-covid-19-vaccine-hesitancy/20208464.article?firstPass=false
Atakan Erdogdu ·
November 20, 2020
Behavioural Economics from a Moral Perspective: Is Nudging Ethical?
In our previous articles, we have shown that a choice architect, i.e. the person who organizes the context in which people make decisions, can alter individuals’ behaviour in a predictable way through utilizing so-called nudges. Although nudges are extensively used to induce people to save more, eat healthier, and rely on renewable energy sources, problems arise when one considers that nudges have a paternalistic aspect in that the choice architect decides what is good for the people, rather than allowing them to choose what is best for themselves. Accordingly, in this blog post, we will address the most common problems associated with behavioural policies from an ethical perspective and will strive to answer the question: How can choice architects know what is in the people’s best interest?
Do nudges interfere with freedom and autonomy?
Nudges are essentially built on the libertarian paternalism ideology, that is, the design of policies that push individuals towards better choices without limiting their freedom to choose. In his classic critique of paternalism, John Stuart Mill objects to paternalism through stating that it interferes with individual liberty. However, this critique is dependent on how liberty is defined. If we define liberty as an aspect of freedom, the ability to choose from available alternatives without having any restrictions, then coercion is the feature that would distinguish paternalistic policies from policies that aim at making people better off. In the canteen example, whereby healthy fruits were placed at the eye-level and cakes were placed in the back side of the shelves, the children still had the opportunity to choose chocolate cakes, they just needed to exert more effort to do so. In this vein, nudges do not appear to be morally problematic as they do not change nor limit the set of alternatives among which decision-makers can choose.
However, as per Hayek, liberty is a broader term than coercion or choice set; it also comprises autonomy – the command a person has over his or her own assessments and choices. There is a significant difference between what a choice architect does when he or she introduces fruits and salads to the school canteen, and when, owing to his understanding of innate psychological tendencies of people, devises a plan to promote individuals to consume a certain type of product. Although the latter intervention can induce people to consume more healthy food, it can also make people choose one option over another. From this perspective, nudges appear to be morally problematic as they diminish the extent to which individuals have control over their own actions. In this case, instead of reflecting their own evaluations, people’s behaviour reflect the tactics of the choice architect.
However, in many cases, regardless of whether there is a nudge, people’s choices will still be shaped by certain factors, i.e. a product will be placed at the eye-level in the canteen. Accordingly, as per Hausman and Welch, when choice shaping is unavoidable, it must also be permissible. In the nudge case, nudges help people to provide the means by which one’s own goals, such as having higher savings and not forgetting deadlines, are attained. This brings the question whether we should respect the non-autonomy of people who want to live more healthily but who cannot follow through or utilize nudges to help them actualize their goals. The latter appears to be more socially desirable.
Should choice architects let people err?
Adam Smith thought that adversity was the best school to develop the respectable virtue of self-command and experience-based learning. As nudges help people to avoid making errors in decision-making contexts for which they have incomplete or incompetent level of information to make the optimal decision for themselves, the cost of nudges may be that individuals forgo the chance to learn from their mistakes and therefore become reliant on them in the long-term. It might be the case that to warrant long-term success, one should let people make their own decisions while providing minimal aid, as nudging is similar to teaching a new-born how to run without teaching him or her how to crawl, creating the moral problem of infantilization in decision making.
Indeed, nudges are not always the best solution. In certain decision-making contexts where trial-and-error learning can happen, the choice architect has a primary reason to avoid nudging individuals. However, learning is most likely to happen when people get immediate, clear feedback subsequent to the engagement in a certain behaviour. In doing so, they would be able to create a causal link between their activities and the results they obtain, enabling them to adjust their behaviour in the desired direction. Alas, many of life’s most important decisions are not only infrequent but also have time discrepancy between costs and benefits. For instance, someone can continue to smoke for years without having any warning signs until symptoms of cancer arise, after which, modifying action will have a minimal impact. For these types of decisions, the delay in the required feedback might be too late to act, implying that individuals can indeed benefit from nudges.
How can choice architects know what is in the people’s best interest?
As choice architects effectively promote a certain type of behaviour, the question is whether the promoted course of action is in line with the decision-makers interest. Nudging is extremely effective when people’s ends are relatively clear, such as helping people to lead longer lives and increasing savings for retirement. However, when people’s ends are relatively unclear, a good criterion of judgment is proposed by Jean-Jacques Rousseau in his Social Contract doctrine. He postulated that although people differ in their interests, there exists a common interest, i.e. general will, on which all humankind can agree in principle, even though not all would wish to pursue it. According to his doctrine, the realization of general will is a deliberative means of seeking outcomes that satisfy the preferences of individuals and render the interventions as legitimate. Similarly, nudging aims to uphold the realization of the general will. As nudges account for the divergent private interests by keeping the choice set intact, one can assess whether behavioural interventions are in the best interest by questioning their alignment with the realization of the general will.This is the primary reason why the transparency test suggested by Thaler and Sunstein, the creators of nudge theory, is of utmost importance, since people, when communicated about interventions, are indirectly asked whether the proposed intervention conforms to the general will, which is their own will reflecting themselves in a rational fashion on their long-term interests.
Hausman, M. D. and Welch, B. 2010. Debate: To Nudge or Not to Nudge. The Journal of Political Philosophy 18(1): 123-136.
Hayek, F. A. 1960. The Constitution of Liberty. London: Routledge & Kegan Paul.
Mill, J. S. 1859. On Liberty. London: Longman, Roberts & Green.
Thaler, R. H. and Sunstein, C. R. 2008. Nudge. London: Yale University Press.
Atakan Erdogdu ·
September 7, 2020
The Behavioural Economist’s Most Valuable Tool: Nudge
Neoclassical economics posits that economic agents are rational, that is, they are purely self-interested individuals, who, after analyzing all available sets of information and evaluating probabilities and risks in a mathematically articulate manner, base their decisions according to their well-defined utility functions. However, economic agents are principally and primarily people. They are humans whose decisions are highly affected by psychological, cognitive, and social factors, who have non-selfish, social motives as shown by their altruistic acts, and who usually forget, procrastinate, and make errors. Therefore, whereas neoclassical economics provides a view on ‘what needs to be done’ by perfectly rational people, as it treats people as if they were someone else, it falls short of explaining ‘what is actually being done’ by people.
In our previous articles, we have already demonstrated that people continue to stick with their current options, even if choosing an alternative could make them considerably better off. We have also described how heuristics – the decision making tricks people use – lead decision makers into making errors. It appears that people make suboptimal – and often irrational – decisions due to their lack of psychological and cognitive capabilities, creating a gap between normative behaviour prescribed by mainstream economics and actual human behaviour. Nudge, in its essence, is about identifying the ‘human’ factors that cause the deviation from the optimal outcome, and modifying the decision making environment by accounting for these factors so as to guide (or nudge) people towards options that are thought to be in their own best interest.
Applied Behavioural Economics: A Cafeteria Experiment
In certain decision-making environments people are least likely to make good choices for themselves. Problems arise when people need to make decisions that test their akrasia, i.e. self-control. These issues are most likely to arise when costs and benefits from engaging in a certain kind of behaviour are time spatial. As such, for sinful goods, such as smoking and unhealthy eating, the benefits are obtained now and the costs are incurred later. The behavioural problem with these goods lies in the fact that people might continue to consume them without having any warning signs for years, after which, modifying behaviour will either become too difficult or have a minimal impact. It is of no coincidence that the worldwide obesity rate has nearly tripled since 1975, being responsible for 4.7 million premature deaths each year. These numbers not only validate that people over consume sinful goods, but also suggest that they might benefit from a nudge to eat more healthily.
In a field experiment, researchers analyzed food choices of students. Unsurprisingly, they have observed that there is an excessive intake of saturated fat and sugar among students, along with low fruit and vegetable consumption, suggesting that there is a room for improvement. Utilizing the insights from food choice architecture – people have a tendency to choose products that are placed at their eye level and in the middle of the menu – researchers made modifications to the decision-making environment such that these tendencies will lead to an increase in healthy eating, rather than preventing it. As such, whereas chocolate cakes and fast grab-and-go foods were placed in the eye level initially, the researchers switched their placement with fruits, vegetables, and other nutrient rich meals, thereby changing the promoted choice of decision making environment. The results of this simple rearrangement were highly significant and successful with fruit and sugar consumption increasing and decreasing, respectively, by 46 and 15 percent.
This relatively simple example is of high importance in the sense that it captures the notion of nudging: organizing the context in which people make decisions so as to alter people’s behaviour in a predictable way without significantly changing economic incentives. The beauty of nudging lies in its flexibility. Instead of forcing people, nudges solely smooth out the process of people reaching the desired end state of themselves by aligning the choices with underlying psychological foibles that govern human behaviour.
Business Implications
The canteen example also hinted at some business implications that are, alas, very often overlooked by practitioners. In many cases, people’s choices are shaped by behavioural factors (e.g. framing, status quo bias, and availability bias) that are extensively used by nudges. This implies that for any decision making environment there exists a promoted choice or option, which can align or contradict with a given company’s products and services. It might be the case that the interplay of these psychological factors endorse choosing the competitors’ products, thereby necessitating a behavioural market analysis to counteract – and if necessary overrule – the current situation. As as a given arrangement of choices can make some options more or less likely to be chosen, with meticulous analysis, the decision making environment can be modified to promote a business’s products and services.
Thaler, R. H. and Sunstein, C. R. (2008). Nudge. London: Yale University Press
Olivier, M. M., Pearson, R., Ruparell, A., Horne, P. J., Viktor, S. and Erjavec, M. (2019). A low-cost behavioral nudge and choice architecture. International Journal of Behavioral Nutrition and Physical Activity 16(1), pp. 1-9.
Bhargava, S. and Loewenstein, G. (2015). Behavioral economics and public policy 102: Beyond nudging. American Economic Review 105(5), pp. 396-401.
Lefebvre, C. R. and Kotler, P. (2011). Design thinking, demarketing, and behavioral economics. In: G. Hastings, K. Angus, and C. Bryant eds.,The Sage Handbook of Social Marketing. California: Sage Publications.
Atakan Erdogdu ·
July 20, 2020
From Toddler to Adult: How Do We Make Decisions?
We know that not only our brain circuits dictate what we do, but also our cognition and ability to control impulses increase with age. Indeed, there are remarkable changes in behaviour for a given situation over the span of development. For instance, it has been demonstrated that unlike pre-schoolers who mainly use deception to their own benefit, school-aged children increasingly start to use deception to protect other’s feelings. Furthermore, when distributing resources, 8-12-year-olds, compared to toddlers who prefer rewards to be solely given to themselves, are willing to incur costs to avoid unequal outcomes, suggesting that people have a concern for other people’s outcomes – a significant deviation from the predictions of game theory. How can we explain these stark differences? Is the change in behaviour due to prosocial concerns or strategic considerations?
Sticker Experiment: Probing into the minds of children
A recently conducted experiment by Smith, Blake, and Harris (2013) attempted to answer the aforementioned questions. Children, separated into three age groups (3-4, 5-6, and 7-8), were asked to indicate their favourite colours from a choice of 6, received 4 smiley stickers with different odour of that colour and were told that they can share their stickers with another child. Two experimental groups were formed. In the Self-Share group, the number of stickers each child shared with another was recorded; children in the Other-Norm group were asked how much another child should have shared in the same situation.
The figure demonstrates that toddlers (3-4 years old) are much more reluctant to show prosocial behaviour when they have to give up some of their own possessions to benefit another person. In contrast, around 70% of 7-8 year olds were willing to give half of their possessions, suggesting the presence of a developmental increase in costly sharing. The interesting thing is that although all age groups (65% aggregate average) mentioned that equal sharing is ‘what one should do’, the effect of established norms on behaviour was almost absent between the ages of 3-7 years, implying that the developmental change in costly sharing is not caused by the differences in the extent of explicit knowledge about fairness or equality.
What is even more interesting, perhaps humorous, is that it is the toddlers who act in line with the economic theory as they choose to keep all the resources for themselves, thereby fulfilling the definition of self-interested, rational economic man proposed by John Stuart Mill. This might mean that we grow ‘dumber’ in an economic sense or it might also indicate that there are other factors, besides monetary ones, that govern our decisions. We choose to elaborate on the latter.
Social Behaviour: Impulse Control, Perspective Taking, and Identity Building
We have mentioned that people, by definition, are social constructs, in the sense that our decisions are governed not only by our own judgment, but also the judgment of others. Furthermore, in our previous blog on theory of altruism we have delineated that people have other-regarding preferences, may it be equality for others, following social norms, or looking for social approval. The sticker experiment was of high importance as it captured these seminal, yet overlooked, aspects of decision theory via demonstrating that the effects of these factors on our decisions become more apparent over time. What if we turn out to be socially ‘smarter’, feeling virtuous about our previous actions and creating better conditions for our future economic transactions?
How we are seen and how we want to be seen from the perspective of others can and do affect our decisions. To move from the current towards the desired image, we engage in perspective taking and evaluate our possible future actions from other people’s point of view. If the possible action is not in line with our desired image – which is usually the case for purely monetarily motivated actions – we defer from doing so. This judgment hints the unique influence of perspective taking on behaviour, as its power lies not in the actual consequences it brings, but rather in the prospective consequences it can bring on the individual provided that he/she does not act in accordance with the desired image. This leads the individual to internalize the costs without even engaging in a certain behaviour. Accordingly, for situations in which a selfish behaviour can be punished (may it be monetarily, emotionally, or socially) we tend to choose courses of action that does not deteriorate our built social image, thereby building a social identity.
This is a highly strategic act, both economically and socially, since having a well-regarded social identity can have effects in future transactions. For instance, within institutional economics, the implementation of credible contracting hinges on trust and repeated transactions between counterparties, and there is an abundance of information demonstrating that building a corporate identity does build trust, decrease transaction costs, and expand the opportunity set. A similar argument can be made for individual-level interactions: “Do you remember the difference in treatment towards you and the others when you went to a restaurant where you are known?” This difference was the manifestation of positive effects of built identity.
Reverting back to our sticker experiment, children as early as 3-4yrs were aware of the importance of equality and fairness. Yet, these factors did not have a material impact on their behaviour. How can we account for this? Evidence from neuroeconomics and developmental functional magnetic resonance imaging (fMRI) studies suggest that children at that age have not fully developed the ability control their impulses; therefore, for them the impulse to ‘have it all’ overrides social concerns.
Akerlof, G. A. and Kranton, R. E. (2000). Economics and Identity. The Quarterly Journal of Economics, 115(3), pp. 715-753.
Guroglu, B. van den Bos W, Crone E. A. (2009). Fairness Considerations: Increasing Understanding of Intentionality During Adolescence. Journal of Experimental Child Psychology, 104(1), pp. 398-409.
Smith, C. E., Blake, P. R., and Harris, P. L. (2013). Why Young Children Endorse Norms of Fair Sharing but Do Not Follow Them. PloS ONE, 8:e59510.
Williamson, O. (1993). Calculativeness, Trust, and Economic Organization. The Journal of Law and Economics, 36(1), pp. 453-486.
Antal Ertl ·
July 6, 2020
The Economics of Racism
In the recent weeks, racism has been on the headlines, and each time we have to realize how seriously harmful the situation is. We could write about a number of things regarding racism. For example, we could cite papers which found that the more intelligent you are, the lesser the chances that you will be racist; however, there are a number of problems with these assessments. Firstly, they could be misinterpreted, and such papers could be found to support either of the ‘agendas’. Secondly, it is counterproductive – informing some of such evidence simply will not stop racism. Thirdly, and perhaps most importantly, it’s such a complex issue, that one cannot possibly grasp the entirety of the matter. We do not aim to shed light on all the faults of society: from ethical issues to problems regarding moral relativism throughout the history of slavery and racism is something that cannot be cut in half, like the Gordian Knot.
Racism as distorted heuristics: identity economics and stigmatizing
First, we need to assess the origins of racism. Sociologists and psychologists keep examining the question whether we are born racist, or it’s something we learn. This raises the question whether racism is a social or a biological construct. If it is the latter one, we might have a harder time tackling it, while if it is a completely social function, great effort and educating ourselves on these “norms” could lead to progress in the foreseeable future. Research shows that we have an innate tendency to make group-based distinctions, particularly, in the form of “us” and “them”. This evolutionary behavioural tendency appears from our past. In tribal culture, groups comprised of loyal members succeeded more often than groups comprised of non-loyal members, leading to a natural selection process in which the human mind has been sculpted to be tribal. Yet, group cooperation is a double-edged sword, as it implicitly implies that there is a tendency to be hostile towards other groups.
As such, racism could be interpreted as a textbook-example for in-group favoritism, where we become more receptive towards those who belong to the same group as we do, while disregarding – or, in certain cases, taking a stance against – the ones we do not associate with. This, however, does not necessarily explain the notion of being predatory towards only certain groups, and not all of them. Why do we like one group, and hate the other? That is where the social context comes into the picture. This could be influenced by a number of things, may that be cultural, religious, or relating to any sort of value differences. Most of these can be traced back to past experiences – personal, or even historical differences among groups – similar to what Romeo and Juliette were forced to face.
Ergo, although racism has its roots in our past, it is also a social construct. Essentially, we are born with an ingroup bias, but the fact that we are not acting hostile against every other group emphasizes that as we get more social, our preferences – and therefore our disposition towards the other group – are adjusted in a selective manner.
The irrationality of racism – how it limits our “playground”
As Adam Smith said: “Every nation lives by exchange” – may it be exchange of articles, ideas, goods or services. In institutional economics, institutions are defined as the “rules of the game”: any factor that restricts these rules, may that be formal rules set by the government, or informal institutions in play in smaller communities. It’s important to note that these institutions – while restrictive of our ground of play – are incredibly useful, as they reduce uncertainty during our conduct of action. When in traffic, you do not need to think about whether it is your turn to go or not – the green light signals to you that it’s safe for you to drive on.
One could argue that racism is such an institution; yet, nothing could be further from the truth. Institutions are there to help coordinate decision-making. Appealing to one’s gender, race, or religious affiliation does not have this property; rather, it is a generalizing, heuristical way of thinking, which is vulnerable to representative bias, selection bias and availability bias, to name a few. Consequently, not only does it reduce the number of potential transactors, it also signals false probabilities. Every transaction that is lost due to the presence of aforementioned in- and out-group preferences is detrimental to the economy, having a deadweight loss as the economy is not in its optimal state. Such distinctions could also undermine trust between economic transactors, which was shown to be a relevant factor in the economy, as it lowers transaction costs – while still being a crucial factor for all democracies. That is why Eurostat, PEW Research Center and the World Values Survey also conduct research in the field.
Another topic to elaborate here concerns the impact of in-group bias on the job market, referred to as favouritism in the literature. Within the labour market, it is not uncommon to observe that jobs, contracts, and resources are offered to one’s social group at the expense of other, outside groups. From an economical perspective, favoritism entails costs as it usually leads to inefficient allocation of resources. This phenomenon is most common in family-owned enterprises, since people at higher level positions in these businesses are usually chosen based on social relations. And do not let us go into politics, where as we all know, favouritism, instead of meritocracy, is the primary factor to get into the White House, implying that in-group bias is rampant, having an indirect effect on all of us.
While it sounds odd, diversity programs at big companies may not be the solution, as it is just going overboard on in-group favouritism. Taking this approach, the problem associated with not hiring applicants based on their qualifications still persists – and so does hiring based on the colour of one’s skin. In economic terms, it is still not the most efficient way of hiring. One might argue that different backgrounds entail different ideas, leading into enhanced creativity. But shouldn’t the way of thinking be a merital factor?
Race preferences and the changes in neighbourhoods
We can put a spin to this whole thing and say: what if there is no such thing as racism (which in itself is irrational and oversimplifying), but rather if there is a preference for races? This is not an unusual thought: we like to surround ourselves with people who are much alike us from a certain point of view, may that be religion, core values held, social standing, and race. Rich people do not really like to live close to poor people. The same thing can be said to followers of opposing religions. Race is no exception.
Have you ever wondered why certain groups have a tendency to live in certain neighbourhoods? This idea of how neighborhoods change originates from Thomas Schelling. Consider a neighborhood where every person has a preference on what proportion of their own race (or political or religious affiliation, mind you) should inhabit the surroundings. We cannot say that white people prefer their neighborhood to consist of at least 50% whites (although certain agent-based models would operate so); however, we can deal with individual preferences: some prefer the neighbourhood where 80% of the population is the same race as them, while some prefer it to be 75%, 70%, 50%, etc. Some, however, have no preference over race. This is very interesting if we want to look at the dynamics of a given area: in the beginning, there seems to be a stable balance. Later on, slowly, those who have no preference may start moving from the neighbourhood. When we hit the threshold of the proportion of given race (in this situation being 80% or less), we arrive at the “tipping point”, where the number of families moving out from the neighborhood grows exponentially. First, the families with 80% threshold move out, then the ones with 78%, and so on.
Note that this example does not imply racism (strictly speaking), only race preference. However, with some adjustments in this “agent-based model”, we can set the rules for discriminating neighbourhoods, as well. After a few turns of play, you could model how the neighbourhood changed, but also you could analyze each dweller’s situation, and how happy and content they are when considering the race of their neighbours. One implication is almost certain: if you put race as a priority to your choice of dwelling, you might not have a content life in the long run.
Stangor, C.: Principles of Social Psychology – 1st International Edition, chapter 11, Stereotypes, Prejudice, and Discrimination.
Tajfel, H., Billig, M., Bundy, R., & Flament, C. (1971). Social categorization and intergroup behavior. European Journal of Social Psychology, 1, 149–178.
Atakan Erdogdu ·
June 23, 2020
Old Habits Die Hard: What Happens When The Thinking Stops?
Have you ever found yourself checking your phone every few minutes for no particular reason? When was the last time you purchased a gallon of milk or a box of eggs only to find out that you have already purchased them previously? These are just simple instances whereby you can relate the extent to which habits govern our daily lives. Almost 43 percent of what we do every day is habitual, meaning that we do not even think whilst conducting roughly half of our daily activities. We continue to follow our habits even when not doing so would make us considerably better off. Yet, in stable contexts, our mind, as if it were programmed by some invisible force, prompts us to behave the way as we are used to behave. In many instances, we are not even cognizant of the fact that we are being guided by this inconspicuous, yet compelling, force.
Habits, as they are the residue of past goal pursuit, reflect our past experiences and the strategies we have devised to reach certain rewarding end-states. However, as our habits become more and more deeply-seated, our behaviour for given situations become automatic, and it persists even in the cases which we incur costs from doing so. Let’s have a look at what exactly happens when the thinkings stops.
The Popcorn Experiment
A recent experiment conducted by Neal et al. (2011) sheds light on how persistent habits are, even when the outcome from performing a given activity is detrimental for the decision-maker. In the experiment, participants were placed in a cinema and were given a free drink together with a popcorn. However, they were not told that the popcorn was either fresh or 7 days old and decidedly stale. There were distinct differences (shown below) in the amount of popcorn consumed among people grouped by the strength of their habit.
The figure demonstrates that participants who occasionally ate popcorn liked the stale popcorn less than the fresh and ate less of it. However, participants who habitually ate popcorn showed a significantly different type of behaviour: their consumption did not change between stale and fresh popcorn scenarios, and it slightly decreased for the fresh scenario. What is even more interesting is that they demonstrated this type of behaviour only within the cinema context, and they reacted the same way as non-habitual eaters when the experiment was conducted in a meeting room showing music videos.
The popcorn experiment captures the fundamental component of habitual behaviour: context-dependency. In other words, as people devise strategies to attain desired end states in particular contexts, the context, by itself, regardless of the presence of a positive or negative feedback from acting so, can directly trigger the response. Accordingly, when the experiment was replicated in a meeting room, the cognitive link between cinema and eating popcorn of habitual popcorn eaters was not activated, and therefore, they were able to change their behaviour.
Do we trick ourselves?
Habits when viewed through the lens of the popcorn experiment might appear to have limited potential in assisting us to meet our goals and acting upon our preferences. However, they reflect our past wisdom, meaning that our brain forms the links between stable contexts and certain actions on purpose. These neurological cravings, i.e. habitual links, are the coping mechanisms that allow us to meet everyday demands and divert our limited attention to things that matter the most in our daily routine. Imagine how time consuming it would be to re-think the route to your office every time you are commuting. Alternatively, imagine that you need to re-experiment every time eating nuts with a beer while watching a football match is a rewarding experience for you. Accordingly, we do not necessarily trick ourselves; instead, by utilizing associative learning we form habits and reach our desired end states in a fast and relatively effortless manner.
However, these come at a cost. The habitual shortcuts may initially serve to attain a particular goal; yet, once the mind enters into ‘automatic’ state, it loses the sight of the importance of goals, and instead focuses on performing the action assuming that the goal will ensue as a result. Alas, if the link between the desired end-state and the actions to achieve it is too strong, our mind can disregard the negative feedback we receive from performing an activity, and implicitly force us to continue what we are doing, which was exactly the case for habitual popcorn eaters.
Another interesting question related to habits is about the ways they govern our purchase behaviour, which is of particular interest to businesses. The implications can range from resistance to innovation to obtaining a behavioural lock-in. We will address the importance of considering habits in business decisions in one of our upcoming blogs.
Graybiel, A. M. (2008). Habits, rituals, and the evaluative brain. Annual Review of Neuroscience 31(1), pp. 359-387.
Neal, T. D., Wood, W., Wu, M. and Kurlander, D. (2011). The Pull of the Past: When do habits persist despite conflicting with motives?. Personality and Psychology Bulletin 37(11), pp. 1428-1437.
Wathieu, L. (1997). Habits and the anomalies in intertemporal choice. Management Science 43(11), pp. 1552-1563.
Wenzlaff, R. M. and Wegner, D. M. (2000). Thought suppression. Annual Review of Psychology 51(1), pp. 59-91.
Antal Ertl ·
June 8, 2020
The Tipping Point, Or: How Micro-Behaviour Turns To Macro
A question a number of economists ask themselves is what effects does society have on the economy? While this question may strike you as mundane, consider this argument: the market economy and capitalism works as it is because all the transactions happening are voluntary in nature. When you need something, you go to the market and consider your options and the different deals you encounter. If you don’t like the deal you have been given – may it be because of price, quantity, or quality – you can reject the offer and go search for other options. If you don’t find the goods you were looking for, then you might be inclined to search for substitutes.
Many philosophers and economists questioned the nature of these transactions, whether it is intrinsic evaluation and rational thinking that drives us, or something else. Rousseau had his famous argument that civilization had awakened amour propre (or: self-love) in people, leading to pride, vanity and envy. While in the old, natural environment, people were searching for things that were intrinsically good for them, moving to cities caused people to determine their own individual well-being as a comparison to their neighbours, friends and family. This lead to people looking for extrinsic values, instead of focusing on intrinsic ones.
Considering social choices, Veblen (1899) argued that there are two kinds of goods: one that is intrinsically good, and you find “utility” consuming it, while the other is a “social good”, which is good for signaling your social status (while you cannot enjoy it directly, you can enjoy the consequences coming from owning/consuming it). Herd behavior is also something worth considering, as it’s one of the most well-known habits among people in a social (and often economic) context. But what might induce herd behavior? And how do we get to certain social decisions?
A nuclear scientist and an economist walk into a bar
Many economists and economic thinkers from the 20th century had inspirations from various scientific theories, or had come from different scientific backgrounds. John von Neumann, for example, who with Morgenstern created the expected utility theory, was a mathematician and a physicist, and is known as one of the fathers of computers. Similarly, Thomas Schelling was an economist who also happened to be an expert in foreign policy and national security (and inspired Stanley Kubrick’s famous picture “Dr Strangelove”).
Schelling made a great contribution to economics by analysing conflicts as well as cooperational problems using game theoretical analysis, for which he received a Nobel-prize. He had an idea built on the concept of “critical mass”, which is used in nuclear physics. Critical mass denotes the smallest amount of material needed to induce nuclear fission. He used this as an analogy to why certain electable seminars at Harvard are doomed to fail.
He came to the conclusion that there are two points which are of stable equilibrium when considering voluntary, after-hours seminars – one where (nearly) everyone is present for a long period of time, and one where the whole thing dies out. Going back to nuclear fission, the more fissile material there is, the higher the probability that nuclear fission will occur. Translating this to social context: the more likely a certain group of people act in a way, the more likely people will follow this trend. If you see that less and less people attend a seminar, you might be inclined to not go next time. Later you could rationalize that it’s because you think that other people have some excess information (that the seminar is not that useful), but in reality, it matters little – you just know it is not as popular as it should be.
He also argued that there are exactly two kinds of people in these sort of “transactions”. Firstly, those, who have some sort of intrinsic evaluation of the situation, and they will act accordingly. Or in plain english: they know whether the course they are currently sitting is valuable to them or not. The second group, however, are those who look at the social environment – to them, the amount of people present is an important signal of quality. Consider the members of the second group. They all have a somewhat individual threshold where they consider a seminar “popular”; for some, it is 80 people present out of 100, for some it is 65, etc.. If we take this (and the knowledge we acquired by studying herd behaviour), we can quickly realize that it takes only a couple of people to leave class to quickly start a domino-effect.
Micromotives and macrobehaviour – the concept of tipping point
Thus, Schelling used this argument to define the so-called “tipping point” in social contexts – the point where the steady state of such social or cooperative games gets defined. It can be best depicted as an “s-curve” shown below:
The part depicted as “hypergrowth” is the most interesting part, where an exponential growth occurs. From the point of the dying seminar: until the tipping point, one or two students leave. After hitting a threshold, those who just go to the seminar because others go as well start to drop out – and suddenly, the majority of the students leave in a relatively short period of time. It also has an interesting implication: if everyone in the population does something only because everyone else is doing it, this will become a social norm, since theoretically nobody will go against it. If, however, a loud minority started arguing against such an action, it might change the whole environment. Others argue that in this area, with little additional added work, great impact could be achieved: if you are currently at a tipping point in your project, one little extra effort could change everything.
This is also a key concept when considering COVID-19. The tipping point in this case is the start of an exponential growth in the number cases. Of course, this is a completely different context, as in this case, it is rather the parameters of pandemics that define this exponential growth rather than individual properties (however, the speed of the virus being transmitted can be affected by reducing personal interactions – the idea behind social distancing).
The previous examples show that the concept of tipping-point has been widely used. It has been used in economic growth models, as well as in social settings, such as the growth in the number of people attending church. More recently, as mentioned before, it has been used for analysis of the coronavirus: not only with how it spreads, but also its potential economic effects. In an analysis done by Christian Aid, they warned that in third-world countries where health-institutions are basically non-existent, COVID-19 could cause a humanitarian disaster not seen in decades. That is why developed countries should help prevent these countries reaching the tipping-point of a disaster involving both economic well-being and health.
Church Growth Modelling: https://www.churchmodel.org.uk/enhancerevival.html
Christian Aid (2020): Tipping Point: How the Covid-19 pandemic threatens to push the world’s poorest to the brink of survival. https://reliefweb.int/sites/reliefweb.int/files/resources/tipping-point-covid-19-report-May2020.pdf
Schelling, Thomas C. Micromotives and macrobehavior / Thomas C. Schelling Norton New York 1978
Veblen, T. (1899). The theory of the leisure class. New York: MacMillan.
Atakan Erdogdu ·
May 26, 2020
The Mystique of Value: Why Small Things Can Have a Big Price
Markets are concerned with exchange, the purpose of which is to access resources that have value potential. What’s fascinating about value, however, is that it’s subjective. Auctions are perfect examples for this, as the huge discrepancy between the bid prices signify the presence of value subjectivity. But what exactly drives value or our willingness to pay?
Value is a multidimensional, cognitive construct in the sense that factors affecting it range from social contexts to the emotional state of the decision maker. There are different theoretical viewpoints to account for this multidimensionality of value. Whereas the classical economic theory emphasizes that value is solely derived from the instrumental and functional aspects of goods, evidence from sociology and behavioural economics suggest that hedonic attributes, i.e. attributes providing fun, pleasure, excitement, also affect value. To put it into context, for a car, the utilitarian features would be gas mileage and safety ratings, and the hedonic attributes would be sporty design, brand, or the enjoyment derived from driving a supercar. Yet, the utilitarian and hedonic aspects of value do not necessarily explain why a rather mundane cigar box, once owned by John F. Kennedy (JFK), sold for a small fortune at a closed auction, or why even the most ordinary sculpture comes to be worth millions if it is discovered to be made by Michelangelo, but worthless again if it turns out to be a counterfeit. These are the exact cases we would like to delineate in this week’s blog, thereby allowing us to probe into another dimension of value that is usually overlooked, and yet profound.
Conspicuous Consumption
In our earlier blog entry we have mentioned Thorstein Veblen’s (1899) theory of conspicuous consumption, in which, the purchase decisions of the majority of people (individuals living above the subsistence level) are made to signal wealth to outside observers. In a Veblen world, consumers communicate their social status through engaging in ‘wasteful purchases’, signalling their social standing through showing that they can afford to purchase those products with relatively low functional value. Although this might contribute to the explanation of why people pay significantly high amounts ($210) for a simple clay brick branded by Supreme, it still falls short of explaining the sudden change in value when an article is found to be related to someone well-known, as it was in the case of Michelangelo’s sculpture. This is due to the fact that Veblen would have predicted exactly the reverse, since purchasing a counterfeit sculpture poses more opportunity to signal the society of having higher capacity to waste. Accordingly, the explanation should lie elsewhere, leading us to the concept of social status.
Status Value
Napoleon, in stating “A soldier will fight long and hard for a bit of coloured ribbon” remarked how much value individuals can assign to goods improving their social status, which, in his case, was equivalent to the value of one’s life. One might wonder what do we mean by status, exactly. Although Weber regarded status as the social honour attached to a group of people, in contemporary sociology literature, it refers to one’s standing in a social hierarchy, as dictated by respect, deference, and social influence. Accordingly, evidence from economic sociology implies these status characteristics have a significant impact on value perception. In particular, it has been shown that people assign higher values to goods that are previously owned by respected figures not because they derive higher utilitarian or hedonistic value from its usage, but because they derive higher self-esteem or honour from acquiring it. As such, people act as if the status of the respected figure is divided among the articles he/she had previously used or created. Therefore, they treat the purchase as a mechanism to transfer and capitalize upon the respected figure’s status, which is the case for Veblen goods. This is the exact case in the JFK cigar box example as people treated it as a tool to capitalize on the status value that the box represents due to its association with Kennedy. Furthermore, in the Michelangelo sculpture example, the reason for the sudden shift in the value arises from the fact that once it’s realized to be a counterfeit, the link between the sculpture and the associated status is broken. Thereby, the status value that could be obtained from acquiring the good eradicated, resulting in the substantially lower willingness to pay.
Ball, S. and Eckel, C. C. (1998). The economic value of status. Journal of Socio-Economics 27(4), pp. 495-514.
Thye, R. S. (2000). A status value theory of power in exchange relations. American Sociological Review 65(3), pp. 407-432.
Veblen, T. (1899). The theory of leisure class. New York: MacMillan.
Weber, M. (1946). Essays in sociology. New York: Oxford University Press.
Antal Ertl ·
May 11, 2020
Game Theory and Feelings: The Secret Behind Interactions
In one of our previous blogs, we mentioned that game theory is very important for behavioral economics in general, as it provides a framework where we can explain how interactions happen, and why certain outcomes are dominant. The idea is very simple: by having knowledge of the possible outcomes and the preferences of the other person, taking those into account can lead us to choose from a set of alternative actions. Assigning probabilities to actions can help us to calibrate our choices further.
In short: game theory provides us with the means to model interactions. This is especially useful, as a lot of experiments done by behavioral economists could be interpreted as some sort of game – may that be simultaneous, where choices are made for each person at the same time, or as an action-reaction game.
The Ultimatum Game
One of the more well-known games and experiments is the ultimatum game, created by Güth et. al. (1982). The basic version of the game is pretty simple: there are two players, one sender and one receiver. In the beginning of the game, the sender is given $10, and he needs to decide on how to divide it between himself and the other person. However, there is a twist: the receiver has to accept the offer in question, otherwise nobody will receive anything.
This puts a number of interesting factors into play. First, the sender has to offer an amount that the receiver will surely accept. Ask yourself: playing as the receiver, what would be the minimum amount that you would accept in this case? If your answer is anything greater than $0.01, I’ve got news for you: in economic sense, you are not a rational being. Why? Because you should not care about what the other person receives, you should only consider your own well-being: and as things stand, by only receiving $0.01, you are still better off compared to not receiving anything. In contrast, what you, dear reader, most likely had in mind is a fair division (which does not necessarily mean egalitarian division): maybe you consider that you are entitled to at least $3, and anything below that is just not fair.
This brings us to the second point: by rejecting an offer, you are punishing the other person for being unfair; however, at a cost: the amount of money that you won’t receive. In one interpretation, this means that the“enjoyment” of punishing the other person outweighs the negative utility from not receiving the money offered.
Another aspect which is important to consider is the information the receivers are endowed with – whether they know the amount that is being divided or not. It is somewhat trivial that your perception of the money offered can be altered if you know the budget of the sender. In a behavioural economic sense, this can be interpreted as whether you provide a reference-point to the receiver or not. As we already know from the prospect theory, a negative difference from the reference-point is interpreted as a “loss” by the decision-maker, and since most, or rather, all of us are being dominated by loss-aversion, we want to avoid this. If we tell the receiver that he is being offered $3 out of $10, in his mind he already created a reference-point which is “fair” (let’s say: $4): any negative deviances from that will be instantly rejected. In contrast, by not having any information on the total amount, one can’t really decide whether the offer is fair or not, generous or not, and will likely accept offers which are lower nominally.
Cultural differences are also significant across countries and communities. A great example to this are the findings of Henrich et. al. (2006), which was an enormous project consisting of 17 researchers. Anthropologists, behavioral and social experts conducted ultimatum games, dictator games and public goods games in 15 different small-scale societies. One highlight of their finding was, that in tribal societies, the rate of rejection was smaller than usual, leading the researchers to believe that these societies were “rejection-averse” rather than loss-averse. From interviews, they found out that a lot of senders offered more because they did not want the offer to be rejected – which could have led to conflict in the tribe. In hunter-gatherer societies of Paraguay and Indonesia, senders offered much more than the average, which is due to their lifestyle. Oversharing in these societies is common, because the hunters cannot consume their game privately, so they tend to share it. However, when other members accept these generous offers, it incurs a certain obligation to them to do better in the next hunting party.
You might be inclined to say that if the money in question would be greater, outcomes would differ. Certainly, experiments have been conducted where the stakes were much higher; for instance, a couple of months worth of salaries. These experiments caused the decision-makers to block, because they could not cope with the stress and pressure of the stakes being that high. However, Hoffmann, McCabe and Smith (1996) played the ultimatum game with a budget of $100, and found that the results were remarkably similar to the original experiment. They also found that when people “earned” the role of the sender through competition (for example: by participating in a quiz), their offers tended to be less generous. This was due to a feeling of entitlement from the sender’s side: by being smarter, they felt that they were entitled to earn more money than the receivers. However, and perhaps more interestingly, the receivers were not willing to accede to this sense of entitlement, and the rejection rates were greater as well.
As the saying goes: “It’s the thought that counts”. This can be shown in the case of the ultimatum game as well: Falk, Fehr and Fischbacher (2000, 2002), as well as Andreoni et. al. (2002) showed that intentions do matter. They tested this by modifying the ultimatum game: senders had to choose from two options of distribution. The first one was the same in all conditions: give themselves $8 and offer the receivers $2. The second option varied from the following distributions: offer nothing (selfish option), offer $5 (egalitarian option), and offer $8 (generous option). They found that, for example, the 8/2 offers were rejected 27% of the time in the “2/8 game” and only 9% of the time in the “10/0 game”. The variations in these rejection rates suggest that intention-driven reciprocal behaviour is a major factor behind decision-making. As such, the alternatives did matter: if the sender offered 8/2 instead of 10/0, he was considered to be generous, and was more likely to get the payments. Simultaneously, the unfair 10/0 offers were rejected 90% of the time.
And finally, the last case we want to introduce to you today is “the battle of the sexes”. The situation is simple (and all-too familiar): a wife and a husband want to spend time together, but they have different activities in mind. The wife wants to go to the theatre, while the husband wants to go see a boxing match. If they can come to an agreement, they will both benefit from it – if they agree to go to the theatre, the wife obviously will be happier, but the husband is happy as well, as he gets to spend time with his significant other (and vice versa if they end up going to the boxing match together). If, however, they cannot come to an agreement, both will be worse off due to the absence of each other’s company. Traditional game theory declares that the latter (going to the theater and boxing match alone) would be the outcome in most cases.
However, Rabin (1993) considered an alternative. In the model outlined in his article (which incorporates fairness into decision-theory), economic agents, besides having their own interest, also have social interests and goals. In order to achieve more social acceptance, they are willing to sacrifice their intrinsic, individual well-being and help others. Applying this to the battle of the sexes: suppose that the husband chooses boxing. The wife then concludes that choosing the theatre would hurt both players, and is therefore willing to go to the boxing match.
Andreoni, J., Brown,, PM., Vesterlund L (2002): What makes an allocation fair? Some experimental evidence Games and Economic Behavior 40 (1), 1-24
Falk, Armin and Fehr, Ernst and Fischbacher, Urs, Testing Theories of Fairness – Intentions Matter (September 2000). Zurich IEER Working Paper No. 63.
Falk, A., Fehr, E. and Fischbacher, U. (2002) “Appropriating the commons: a theoretical explanation”, in E. Ostrom, T. Dietz, N. Dolsak, P. C. Stern, S. Stonich and E. U. Weber (eds), The Drama of the Commons, Washington: National Academy Press
Güth, W., Schmittberger, R. and Schwarze, B. (1982) “An experimental analysis of ultimatum bargaining”, Journal of Economic Behavior and Organization, 3: 67–388.
Henrich, Joseph & Boyd, Robert & Bowles, Samuel & Camerer, Colin & Fehr, Ernst & Gintis, Herbert & McElreath, Richard & Alvard, Michael & Barr, Abigail & Ensminger, Jean & Henrich, Natalie & Hill, Kim & Gil-White, Francisco & Gurven, Michael & Marlowe, Frank & Patton, John & Tracer, David. (2006). “Economic man” in cross-cultural perspective: Behavioral experiments in 15 small-scale societies. The Behavioral and brain sciences. 28. 795-815; discussion 815.
Hoffman, E., McCabe, K. and Smith, V. (1996) “On expectations and the monetary stakes in ultimatum games”, International Journal of Game Theory, 25: 289–301.
Rabin, M, 1993. “Incorporating Fairness into Game Theory and Economics,” American Economic Review, American Economic Association, vol. 83(5), pages 1281-1302, December.
Atakan Erdogdu ·
May 4, 2020
Why Knowing Behavioural Economics is Important: On COVID-19, Biases, and Decisions
Coronavirus has caused an upheaval, creating unstable and unprecedented decision-making conditions around the world. As the disease continues to spread, so does the necessity of taking appropriate and timely actions. Yet, retrospectively, we see that the most sensitive decisions were made under the influence of behavioral biases, which, alas, contributed to the disease becoming a pandemic. In this week’s blog, we analyze specific behavioral biases in the context of the COVID-19 outbreak and demonstrate the negative impacts that stemmed from the inconsideration of these biases. In particular, we address the following questions: Why do governments and people behave as they do? What were their mistakes, which behavioral biases were fomenting those mistakes, and what are the consequences?
The Ostrich Effect
‘Ostrich Alliance’ is the nickname given to the world leaders who, despite the presence of evidence suggesting otherwise, deny the coronavirus threat and bury their heads in the sand. We can view this behavior through the lens of normalcy bias – the observed tendency of people to believe that things will function the way they normally have and thus significantly underestimate threat warnings. To put it into a relatable context, in a series of investigations, Ripley (2008) identified the underlying response mechanism of people to natural disasters, and revealed that the first response is denial of the problem, followed by deliberation, and decision. This emphasizes that in response to disastrous events, our ability to react fast and implement forward-looking policies are rather limited, since at first, we tend to deny the occurrence of the event. It is no coincidence that after the spread of the first cases in Europe, the international flights continued, since governments were under the influence of the normalcy bias, and therefore denied even the possibility that the virus can become a worldwide phenomenon. What is more interesting, however, is that the governments did not take strict measures until the evidence suggesting the virus as a threat became highly formidable, implying the difficulty in transition from denial stage to deliberation. Unfortunately, the difficulty in transition further manifested itself in the latency in the responses to the coronavirus outbreak and, therefore, indirectly contributed to the spread of the virus.
Overconfidence
Overconfidence is a bias that seems to come back over and over; however, it is especially important in the context of coronavirus – as there’s a lack of information on the effects, and the transition-mechanism of the virus and a lot of other factors are unknown. There are working theories, but there are a lot of contradictions. There still is, for example, debate on whether we should wear masks in public or not.
One of the consequences of overconfidence is the optimism-bias, and we’re sure that you already experienced it before. In short, optimism-bias is when you tend to say: “Sure, this is a really bad thing, but it won’t happen to me!”. It demonstrates that people tend to think that dangerous or harmful events at work are less likely to occur to themselves compared to others doing the same exact job. Note that it does not have the prerequisite of underestimating the danger – one can acknowledge it, but for their own safety, they could still disregard it as a potential threat.
The unique thing with pandemics such as this is that if people disregard these threats, it could be potentially harmful to those who they come in touch with – or externalities, as it is being referred to as in economics. For non-econ majors: externalities are effects which are being inflicted upon others, which decision-makers do not include in their cost-benefit analysis. Obviously, in this case, we are talking about negative externalities (although there exist positive ones as well). Bethune and Korinek (2020) measured the magnitude of these externalities. They developed an epidemiological model, where economic agents had to choose their social and economic activities, while also considering a statistical mortality risk value of $50,000. Individual agents weigh the private gains from still engaging in social and economic actions with the growing cost of being infected. In their result, they showed that people severely underestimate their individual risks compared to social risks.
The Shifting of Social Norms, or: How I Learned to Stop Worrying and Love the Virus
Within the realm of social sciences, what never ceases to amaze us is how dynamic everything is. Something that was thought to be correct by everyone in one day is criticized by everyone in another day. The case with coronavirus is not exempt to this observation.
If you think about it, if you have seen someone with a mask and a glove in the beginning of the year, you would have treated them with much caution and, perhaps, antipathy. Nowadays, you would treat them in such a way if they were not wearing masks and gloves. This is a prime example of how norms, how institutions, change in a society.
The economic definition of institutions according to North (1990) is “humanly devised constraints that structure political, economic and social interactions”, or to put it simply: the rules of the game. While they are a set of rules (often formalized by legislation) which restrict how we can conduct transactions, they also make life easier – by reducing uncertainty, transaction-costs, and the cost of cooperation. In a lot of cases, social distancing and mask-wearing started as an informal institution, and was later formalized by governmental actions. While it is an inconvenience for sure, these arrangements help to make our interactions safer (at least perceive them as safer, thus tending to our gross uncertainty). While there is a debate whether it is useful or not, it is in line with the human tendency to follow each other and herd, thereby giving people some sort of rule-book that they can apply, inducing mental comfort.
This phenomenon underscores an insight that we are all aware of, but often forget the implications of: People, by definition, are social constructs, in the sense that our decisions are governed not only by our own ideas, but also the ideas of others. It is of seminal importance to remember that whenever there is a decision to be made with high consequences, independent thinking should be facilitated, since waiting for the mass to realize the importance of the problem might cause significant delays in addressing the issue at hand, which, in the case of coronavirus is exactly what happened.
Bethune, Z A and A Korinek (2020), “COVID-19 Infection Externalities: Pursuing Herd Immunity or Containment?”, Covid Economics, Vetted and Real-Time Papers 11, 29 April.
North, D. (1990): Institutions, Institutional Change and Economic Performance, London: Cambridge University Press.
Ripley, A. (2008). The Unthinkable: Who Survives When Disaster Strikes – and Why. New York: Crown Publishers.
Omer, H. and Alon, N. (1994). The continuity principle: A Unified Approach to Disaster and Trauma. American Journal of Community Psychology 22(1), pp. 273-287.
Atakan Erdogdu ·
March 9, 2020
Status Quo Bias: Why do customers stick to the option they have already chosen?
As Samuel Jackson remarked, “To do nothing is within the power of all men”, individuals have a significant tendency to stick with the decisions they have already made. To put it into a real-life context, imagine your current cell phone plan. If a competitor offered a better option that provides exactly the same benefits at a lower price, imposes no costs of switching, and maintains your current cell phone number, would you switch to the alternative provider? Many people (76 percent), when asked, seemed to disregard the extra benefits that can be obtained from switching and articulated that they would not switch their plan. This occurrence is not limited to the cell phone payment plans, it is also widespread in the realms of saving and investment plans, brand choices, and insurance plans. For some reason, individuals have a strong tendency to prefer a familiar choice with less benefits over other alternatives, rendering them as having a bias towards the status quo.
Coca-Cola learned the importance of this bias the hard way. During the 1980s, the company’s market share was continuously falling, and it was forecasted that Pepsi would become the market leader in the soft-drink industry by 1990. To tackle this problem, Coke II was developed and in the blind taste tests, consumers preferred the new Coke over the older by a significant margin of 53 percent. Yet, when the product was finally released to the market, it was a disaster. The company was being flooded with angry phone calls that indicated the dissatisfaction with the product. In the course of three months, the new coke was taken off from the shelves, but the farcical decision costed the company around $34 million. Viewed through the lens of status quo bias, the result is unsurprising: the strong preference to stick with the familiar product lead customers into disregarding the enhanced taste experience that the new Coke offered. However, if the challenge of status quo bias is so influential, the fundamental question presents itself: How can we overcome it?
The Rationalist Explanation
The rationalist will posit that transaction costs can explain the status quo bias. The presence of transaction costs that is associated with switching between different alternatives can offset the benefits derived from the superior option. In addition, in the absence of explicit costs, uncertainty will have a similar effect. From the perspective of consumers, as they have not tried the better alternative, the benefits that can be gained from it are uncertain. Solely the usage of the service/product will make them gauge the quality of gains. Accordingly, the consumers react to this ambiguity by reactively devaluing the extra benefits the product offers. The costs associated with re-analyzing the offers can further explain this rationalist choice. It might be the case that customers are saving the cost of reanalysis as they stick to their previous choice, assuming that they have initially made the right decision. Therefore, these costs associated with choosing an alternative can indeed offset the to-be-obtained benefits, which, are inherently uncertain and devalued accordingly. As a result, the customer becomes actively and rationally biased towards the status quo. The implications for the practitioners within the rationalist point of view are twofold: (i) transaction costs associated with switching should be eliminated or reduced, and (ii) the effects of uncertainty ought to be alleviated using techniques such as free trials. Yet, reflecting from our life experiences, it becomes blatant that the factors rationalists suggest, except for transaction costs, are not the primary drivers behind the status quo bias, indicating that the answer lies elsewhere.
The Behaviouralist Explanation
The behaviouralist will divert the attention into perception, instead of monetary, values associated with switching. Think about the illustrated value function that depicts how differently losses and gains are perceived.
Graph 1. The Prospect Theory Value Function (source: Kahneman & Tversky, 1979).
The depiction reveals that an equivalent amount of loss is perceived as significantly higher, almost twice as much, then a similar amount of gain, which is referred to as loss aversion. Within the context of switching between alternatives, reference point represents the current choice of the customer and as the losses have more effect, the customer focuses on what can be lost by choosing the alternative, instead of what can be gained. This leads to a strong innate preference towards the status quo. In addition, the presence of sunk costs that represent the previous investment can provide another perspective. Sunk costs induce people to continue to choose suboptimal, or even failing, options because of the fact that they have already invested significant amount of their resources in it and giving up will be felt as admitting failure. Indeed, in choosing between alternatives, the loyalty to the brand and previous payments to receive the service can represent a sunk cost.
More important, but perhaps more subtle, is the effect of cognitive dissonance. In the domain of choices, consumers are characterized by their motivation to have consistency in their decisions, and they tend to justify past and current actions. Accordingly, cognitive dissonance, in itself, is the common observation of consumers behaviour of mentally discarding or suppressing information that contradicts correctness of their past decisions. Reverting back to the telephone plan example, as the customer received a contradictory information that indicated (s)he is making an inferior decision, the information is disregarded to preserve cognitive consistency.
Therefore, the behaviouralist explanation highlights a different and more effective part of the observed tendency of sticking to the initial choice. The combined effect of loss aversion, sunk costs, and cognitive dissonance is similar to a transaction cost. The difference, however, is that the costs are perceived by the customers. That is, these costs are non-existent in economic terms, but are borne in the minds of customers. Hence, behaviouralist explanation suggests that practitioners should also consider the mechanisms of the consumers’ mind, and, if necessary, take steps such as framing the action of switching as a gain instead of a loss to overcome this subtle, yet substantially strong bias towards the status quo.
Kahneman, D. (1992). Reference Points, Anchors, Norms, and Mixed Readings. Organizational Behavior and Human Decision Process, 51(2), pp. 296-312.
Kahneman, D. and Tversky, A. (1979). Prospect Theory: An Analysis of Decision Under Risk. Econometrica, 47(2), pp. 263-291.
Khedhaouria, A., Thurik, R., Garau, C. and Heck, V. E. (2016). Customers’ Continuance Intention Regarding Mobile Service Providers – A Status Quo Bias Perspective. Journal of Global Information Management, 24(4), pp. 1-21.
Samuelson, W. and Zeckhauser, R. (1988). Status Quo Bias in Decision Making. Journal of Risk and Uncertainty, (1), pp. 7-59.
Thaler, R. (2016). Behavioral Economics: Past, Present, and Future. American Economic Review, 106(7), pp. 1577-1600.
Antal Ertl ·
March 2, 2020
Are We Right to Panic?
After what some called the worst week since the 2008 crisis, we felt that we should address some of the behavioural effects in the financial markets. More than 3 trillion dollars have just disappeared in the global economy. According to Bloomberg news, the world’s 500 richest people lost approximately $444 billion dollars, and as of February 28th, the Dow Jones Industrial Average lost more than 12%, while the S&P500 index lost 11.5% of its value. While this tumble in the financial markets is as appalling as it is baffling, economists, financial experts and investors try to find out whether such a decline is justified.
The story behind the decline is pretty straightforward: as the potential consequences of the COVID-19 virus began to be perceived as direr, the market reacted. Due to the precautious actions taken by both governments and companies, such as reduced working hours, travel bans, and, in some cases, closed factories, a decline of yield and production is expected. Such market corrections occurred 26 times after the Second World War (Goldman Sachs), and further corrections could be expected in the following months.
The key word in the last paragraph is expectations. Now, obviously, financial experts and economists have calculations and models on the effects of such external shocks (in economics terms).
Efficient markets, with inefficient agents
It is worth talking about one hypothesis in particular: The Efficient Market Hypothesis (EMH), proposed by Eugene Fama. In short, EMH is a model for the financial and capital markets which states that the current prices on the market reflect all available information on that particular stock. As such, the recent surge of Tesla stocks means that some meaningful information surfaced, thus expectations towards Tesla sky-rocketed. It is important to note, however, that not even Eugene Fama thinks that markets are perfect in the short run: he does, however, emphasize that this is a model, and models are always wrong (as George Box famously put it: all models are wrong, but some of them are useful).
Fama received a Nobel-prize for his theory in 2013. Funnily enough, that year he shared the economics Nobel-prize with Robert J. Schiller, who regarded his theory as “one of the most remarkable errors in the history of economic thought”. He is one (if not the) key figure of behavioral finance, along with Richard Thaler. In his work, he analyzed markets and tried to find behavioral patterns on the markets. Along with writing the book “Animal Spirits” with George Akerlof, he is most famous for the behavioral analysis of market bubbles and the creation of the Case-Schiller repeat-sales index for the real-estate market.
Schiller’s proposition of the market is quite different of Fama’s – in his theory, markets are inefficient, and mostly driven by psychology – as such, you can easily beat the market as an investor (watch his case against EMH here: https://www.youtube.com/watch?v=Tn-A7eCUrYk). Interestingly enough, he and Fama seem to agree on a lot things. But one of the key aspects that they disagree on is the existence of “bubbles”, that is: whether over-pricing of an information can occur on the markets. If it comes down to the individuals – especially during turbulent times – Schiller might have got a point.
During a crisis or a panic, risk aversion comes into play. We know from Kahneman and Tversky (1979) that not only we are bad at probabilities, but we also perceive them incorrectly. This was depicted in their weighting-function, which can be seen below:
In short, this states that we overvalue the occurrence of low-probability events, and relatively undervalue certain effects. For us in this context, the overvaluation of low-probability events is key, as such it can be utilized to explain the recent unprecedented movement that occurred in the markets. Accordingly, as the market participants overestimated the probability of the coronavirus being a pandemic event, which, based on past occurrences, is highly improbable, market overreaction that does not necessarily reflect the economic reality might have ensued. This, in the context of Fama’s hypothesis, might imply that markets can be emotionally efficient, meaning that information by itself is not reflected in the market, instead, it is the information after being filtered by emotions and biases that the market reflects.
The availability bias is another aspect that might be involved, relating to the tendency to determine the likelihood of an event’s occurrence by the simplicity to retrieve it from the memory. To give you an example: people are more afraid of travelling by plane than they are of travelling by car. Why? If there is a plane accident, it is all over the news. Car accidents are more likely to be reported in traffic news. Because of this, in our mind and in our memories, plane accidents were more impactful than car accidents. In the context of markets, wide coverage of coronavirus news gives the market participants perception that the situation is exacerbating, leading to the overestimation of the possible effects. Yet, when one realizes that total flu deaths every year worldwide is around 389 000, the 2942 deaths caused by coronavirus appear strikingly low. However, the market acts as if it were exactly the reverse. It is a common observation that markets realize this overreaction sooner or later, and a strong retracement follows. Observation of similar past virus outbreaks reveals that twelve months after the overreaction occurred, the markets increased, on average, by 13.62%, emphasizing that the initial concerns were significantly overestimated. Of course an argument can be made that the market is pricing the current expectation of decrease in production, but historically this is still an overreaction – maybe this is the market’s way of “better safe than sorry”.
Clearly, making investments in such a volatile environment depends on your time-horizon: if you are a short-term investor, you might be inclined to invest in safe-havens. If you are a long term investor, however, you might see this as an opportunity, as you are able to buy stocks at a lower price, thus your long-term returns might increase. And, of course, risk appetite is key in both cases.
Panics, safe-havens and animal spirits
But what do investors do when there is panic in the markets? They turn to so-called “safe haven” investments. Investors buy these assets to reduce their exposure to losses during volatile times on the market. Examples include gold (and other commodities), treasury bills (considered to be risk-free, due to the government being the debtor), and defensive stocks. Defensive stocks include companies whose products’ demand can be described as rigid – food, medicine, and all sorts of FMCG markets, all due to the simple fact that there is constant demand for these goods. Most of these are coming from rational expectations, that in the future the demand for these is still going to be high. Investing in gold, however, might not seem as practical as the other ones. One can argue that this is just a “reflex” – after all, coming from a philosophical question: why does gold have such an important intrinsic value, even if it’s not as widely used as it once was? And we have yet to talk about the elephant in the room: cash.
During major economic downturns, people liquidate their investments and try to get as much cash as possible. This was mainly true during major uproars and bank-panics in the 19th and 20th centuries. A famous example is the Bank Panic of 1907. In short, what happened there is that during a recession, one of the largest trust companies of New York, called Knickerbocker Trust Company, was filed for bankruptcy – immediately, people lost their confidence in trust companies, and they tried to gain as much cash as possible. The consequences were decimating, and later it served as a reason to introduce the final lender, the Federal Reserve System in the United States.
Now, we can argue that this story bares some similarity to some of the department stores being overrun, and a lot of sustainable food being purchased. Due to the fear of the spread of the virus, everyone is preparing for a worst-case-scenario. Obviously, Keynes’ Animal Spirits is in play here – there is a sudden decrease of trust, and an increase in uncertainty. This mentality of the market, however, may be completely unsupported by fundamentals. As such, information asymmetry plays a huge role: we do not have complete information about the situation (reading every news article about the effect does not provide us with actual understanding on the effects, rather just the mood of society and the markets). Some actors might have better information on the topic, but it is very hard do distinct these in the noise generated by events.
Confirmation bias is also an important factor in this situation. Confirmation bias is when you start to interpret every information that you gather in a way which supports your prior beliefs. Basically what this means is that you decide on how to interpret a situation, and then you frame every new information so that you think that your “hypothesis” is more and more probable, thus leading to inductive reasoning. You can, however, defend yourself against this, but you have to be extremely conscious about how you interpret information.
And lastly, from a game-theoretical point of view, it might be worth to make some precautions. If everyone else is making these precautions, you might as well do it – the (perceived) possible losses by not participating in herd behavior might be greater than the gains by not complying – leading to a perverted “fear of missing out”. Again, the “better safe than sorry” argument can be made, with the condition that buyer’s remorse is actually more probable than one might imagine (think back on the weighing-function of Kahneman and Tversky).
So what happens?
Funny you should ask – no one knows. Unfortunately, no economist has the abilities of the Old Testament prophets, nor of Nostradamus. We cannot say what will happen – we have models, and some fundamental changes that we can rely on, but ultimately, behavior of the stock market can be very hectic and sometimes inexplicable, due to animal spirits and herd behavior – as Schiller and Akerlof elaborated on it ten years ago. But such great, sudden changes should be perceived and interpreted with caution – as explained, after such market corrections, there were other corrections in the following months.
As for forecasts and expectations, and old joke comes to mind: why did God create economists? To make weather forecasters look good.
Akerlof, G.A., Shiller, R.J. (2009): Animal Spirits: How Human Psychology Drives The Economy and Why It Matters for Global Capitalism. Princeton University Press, 2009.
Fama, E.F. (1970): Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance Vol. 25, No. 2, Papers and Proceedings of the Twenty-Eighth Annual Meeting of the American Finance Association New York, N.Y. December, 28-30, 1969 (May, 1970), pp. 383-417.
Kahneman, D, Tversky, A. (1979) Prospect Theory: An Analysis of Decision under Risk. Econometrica, Vol. 47, No. 2. pp. 263-291.
Loewenstein, G., and O’Donoghue, T. (2004). Animal Spirits: Affective and Deliberative Influences on Economic Behavior. Pittsburgh, PA: Carnegie Mellon University.
Moen, J.R., Tallman, E. W : The Panic of 1907. Federal Reserve History; https://www.federalreservehistory.org/essays/panic_of_1907
Tversky, A., Kahneman, D. (1991), ‘Loss aversion in riskless choice: A reference-dependent model’, Quarterly Journal of Economics, vol. 56, pp. 1039-1061.
Veblen, T. (1899/1979): The theory of the Leisure Class. Penguin Books, Harmondsworth.
Antal Ertl ·
February 16, 2020
Game Theory and Behaviour
Tim Harford in his recent blog told a joke about a pianist getting caught by the KGB in the Soviet Union. In his suitcase, the pianist was carrying a copy of Beethoven’s Moonlight Sonata, which the KGB thought was some sort of code western intelligence used. They put him into an interrogation room, where he waited. After an hour, the interrogation officer came in and said to the pianist: “You better start talking, comrade! Your partner, Beethoven, has already told us everything.”
This story aimed to serve as a demonstration to one of the great classics in economics – the Prisoner’s Dilemma. The background is: two thieves successfully complete a robbery; however, after a couple of days, both are caught by the police. Each of them is transported to their own separate cells, where they are disconnected from everyone and everything. Later, the interrogator offers each of them a deal: they can make a deal with the police and tell on the other thief, or they can stay silent. If they tell on the other thief while the other stays silent, they get to walk, and the other gets 5 years. If both of them tell on each other, they each get 4 years. If no one tells on the other, they only get charged for minor misdemeanor, each getting 1 year in prison.
Folsom Prison Blues
Classical Game Theory is a tool which aims to predict the outcomes of interactions between two (or more) parties. Mostly building on the Expected Utility Theory, developed by Neumann and Morgenstern (1947), it is founded upon a straightforward idea: how should I act towards someone in order to maximize my well-being? As such, the decision-maker evaluates the other person’s perspective, their choices, and, if applicable, identifies his or her dominant strategy. Based on that knowledge, our economic agent decides what their actions should be, and will act accordingly. However, it is important to note, that in order to evaluate other agents’ possible actions and make relevant judgements about them, an agent requires some information – which could be the outcome probabilities or perhaps some knowledge of their preferences.
In the Prisoner’s Dilemma – a simple and symmetric game – the model suggests that they will always tell on each other. This is depicted in the figure bellow: inside the boxes, the first and the second number defines payoffs for prisoner “A” and “B”, respectively. To see why we arrive at this conclusion, we can attempt to reason from the perspective of A:
If B chooses not to tell on me, then I should tell on them (because my payoff will be higher than if I do not tell on them)
If B chooses to tell on me, then I also should tell on them.
As such, based on rational decisions, the outcome should always be both telling on each other. This is called a “Nash-equilibrium”, named after Robert Nash. However, if they both chose not to tell on the other, a better result could be achieved. How can this be achieved, if they do not have any means of communication at their disposal? Well, the answer is trust.
The battle of the sexes
Another case is “the battle of the sexes”. The situation is simple (and all-too familiar): a wife and a husband want to spend time together, but they have different activities in mind. The wife wants to go to the theatre, while the husband wants to go see a boxing match. If they can come to an agreement, they will both benefit from it – if they agree to go to the theatre, the wife obviously will be happier, but the husband is happy as well, as he gets to spend time with his significant other. If, however, they cannot come to an agreement, both will be worse off due to the absence of each other’s company. Traditional game theory declares that the latter would be the outcome in most cases.
However, Rabin (1993) considered an alternative. In the model outlined in his article (which incorporates fairness into decision-theory), economic agents, besides having their own interest, also have social interests and goals. In order to achieve more social acceptance, they are willing to sacrifice their intrinsic, individual well-being and help others. Applying this to the battle of the sexes: suppose that the husband chooses boxing. The wife then concludes that choosing the theatre would hurt both players, and is willing to choose boxing.
Alternatively, if she perceives going for a boxing match as unfair (as they went there for the past 5 weeks straight), she chooses theatre in order to agitate her husband. We covered this topic recently in our blog regarding unfairness. Rolling with this might not have the best outcome for the relationship – but barely anything, that is driven by our emotions, does.
Games we like to play
As you probably guessed by now, this blog-post is not strictly about behavioral economics, as it is more about how it applies methodology to validate or model its findings. In this blog, I wanted to give you a glance into the world of game theory, which can model a wide range of situations and agent interactions.
Camerer (2003) provides a great example of how behavioral economics got integrated to game theory, and thus creating “behavioral game theory”. For the vast majority, this is a formal alteration of classical, rational game theory, using validations from experiments provided by behavioral economics. If we take a look at the Trust Game mentioned a couple of weeks ago, the results from the experiments inspired parameterization of preferences, as well as the “new” homo reciprocus and homo equalis. As such, even institutional economics started to use these “calibrated” models as standards.
Why is game theory so interesting for us? Because it is exceptionally good at modelling things like uncertainty, environmental effects, as well as emotions and feelings in interpersonal settings. In the 18th and 19th century, these factors had a pivotal importance in the political economy. But later, general economics wasn’t really dealing with problems arising from the economy being interpersonal (while justifiably giving a very important role to uncertainty). With the rise of experimental economics, experiments conducted could and should be analyzed in game theoretic settings, cutting away some of the complexities, and decomposing the important factors. In order to do this, behavioural economists have to quantify the effects of these rather qualitative factors; and while it is very complex and difficult to do, there are examples – such as the Trust Game – where this has been successful.
Camezer, C. (2003). Behavioral game theory: Experiments in strategic interaction. Princeton, NJ: Princeton University Press.
Rabin, M, 1993. “Incorporating Fairness into Game Theory and Economics,” American Economic Review, American Economic Association, vol. 83(5), pages 1281-1302, December.
von Neumann, J.& Morgenstern, O. (1947) Theory of Games and Economic Behavior Princeton, NJ: Princeton University Press, 194.
Atakan Erdogdu ·
February 9, 2020
Theory of Incentivizing: A Double-Edged Sword
Incentives are a vital element of economics. As such, their usage is widespread in many areas, such as education, health, and pro-social behaviour. The seminal importance of incentives arises from the fact that they are the mechanisms by which the individuals’ interests are aligned with the public interest. This is primarily achieved through giving monetary incentives that increases (decreases) the benefit an individual obtains from a socially beneficial (detrimental) activity e.g. providing financial incentives to individuals who use renewable energy. Accordingly, as provision of monetary incentives recalibrates the relationship between costs and benefits, one would expect it to work effectively. However, a quick glance into evidence provided by behavioural economics suggests that it rarely does, and in many cases, it even backfires.
In the study of Mellström and Johannesson (2008), authors tested the effectiveness of monetary incentives on blood donations, a great example of pro-social activity. To achieve this purpose, the authors conducted randomized field experiments in blood donation centres located in Sweden. The three treatment groups were offered different incentives for blood donation: no payment, $7 cash payment, and cash payment of $7 with charity option. Traditional economics predicts the willingness to donate to be the lowest for the first and highest for the second group, since in addition to the intrinsic reward of helping someone else, the second group receives further monetary reward, rendering the highest utility. Contrary to what is expected, the willingness to donate has actually decreased by 73.3% in the second group, and the charity-incentivised group’s willingness to donate blood was highest at 54%, followed by 47% for the non-incentivised group.
Explaining the Phenomenon: Image Motivation, Overjustification Effect & Decision Frames
The key insight for understanding this seemingly idiosyncratic phenomenon is to understand the fact that, in line with the tenets of sociology, our behaviours act as a signalling mechanism of our motives. While the price effect of incentives, i.e. decreasing cost or increasing benefits, can increase the take-up of an activity, this signalling effect may act as a barrier, and it is the relationship between these factors that determine the outcome for the incentivised economic activity. Reverting back to the blood donation example, regarding the monetary reward group, the presence of extrinsic monetary reward tainted the intrinsic image motivation of signalling the society that the individual is doing good for the sake of doing good. Accordingly, the addition of monetary incentive distorted the signal effect of this prosocial activity and made it unclear whether the activity is undertaken ‘to do good’ or ‘to do well’. Therefore, as the cost of sending the wrong signal to the society surpassed, i.e. overjustified, the additional monetary benefits, a decrease in the willingness to donate ensued. This occurrence is illustrated in the graph below (Figure 1), whereby the inclusion of incentive y decreases the aggregate supply of an activity to the point at which it is lower than it would have been without providing any incentives (the top polynomial curve).
Figure 1: Relationship between monetary incentive and activity uptake | Source: Bénabou & Tirole, 2006.
Another important, yet subtle inference is that if the signalling effect is non-present, then the monetary incentives will work as predicted by mainstream economics. The conducted experiment of Ariely, Bracha, and Meier (2009) tested this hypothesis through providing monetary incentives to donators privately. In doing so, they have directly tested whether the overjustification effect that is widespread in social contexts can be overcome. The results reveal that monetary incentives do work in private contexts for prosocial activities, yielding a linear relationship between incentives and activity uptake, similar to the one depicted in the graph. This implies that the change in the framing of the decision-making context, i.e. from social to private, was the driving factor behind behavioral change.
A very important conclusion arises at this exact point: “The framing of the decision-making situation has a crucial impact on the activity uptake”.
Implications for Public Policy and NGOs
The inferences do not imply a doom scenario whereby it is virtually impossible to incentivise uptake of prosocial activities. Instead, they imply that careful consideration, planning, and execution can provide the desired outcome. Demonstrated through the blood donation example, the effect of incentives depends on their design, the form in which they are given, and the behavioural context (social/private) in which the activity occurs. The statistically significant increase in willingness to donate of the charity-incentivised group implies that the form of incentive should be in parallel with the form of intrinsic motivation, which were both social and altruistic in the blood donation example. In addition, the framing of decision-making context should be a function of the selected incentive form. Accordingly, the framing should be social if the form is altruistic, and private if the form is monetary to increase or reduce, respectively, the effect of incentives on image motivation.
Ariely, D., Bracha, A. and Meier, S. (2009). Doing Good or Doing Well? Image Motivation and Monetary Incentives in Behaving Prosocially. American Economic Review, 99(1), pp. 544-555.
Bénabou, R. and Tirole, J. Incentives and Prosocial Behaviour. American Economic Review, 96(5), pp. 1652-1678.
Gneezy, U. Meier, S. and Rey-Biel, P. When and Why Incentives (Don’t) Work to Modify Behaviour. Journal of Economic Perspectives, 25(4), pp. 191-210.
Mellström, C. and Johannesson, M. (2008). Crowding Out in Blood Donation: Was Titmuss Right?. Journal of European Economic Association, 6(4), pp. 845-863.
Titmuss, R. M. (1970). The Gift Relationship. London: Allen and Unwin.
Antal Ertl ·
February 2, 2020
Un(Fairness) – Part 2
In last week’s blog, we introduced the concept of fairness in economic decision-making, how we perceive it, and how it distorts rational, self-interested mentality. Traditionally, our well-being should not be dependent on the fairness of others, but rather on how well we perceive ourselves to be. As it turns out, during the evaluation of our status and well-being, we tend to compare ourselves to others – using them as reference-points.
A number of emotions can occur when we perceive unfairness, but most importantly – envy. Envy, according to Rawls (1971), occurs when we look at other people’s well-being with malevolence, despite the fact that their superior endowments do not restrict us from enjoying our benefits. Also, we wish to deprive them of their advantages, even if it costs us to do so. Some of the literature calls this “egalitarian” view as malicious envy. Regardless of its name, it is easy to realize that this kind of noxious behavior cannot exactly be called rational, in the sense that acting so, one does not listen to reason, but rather to their emotions.
I can feel it in my guts
The role of emotions in economics was already clear and acknowledged before the creation of behavioural economics. One example for such acknowledgment is Keynes’ “animal spirits”, which was mentioned in his work The General Theory of Employment, Interest and Money (1936). In short: according to Keynes, Animal Spirits are meant to explain all the animal-like “instincts” or intuitions, which affect behaviour, and as such, the whole economy (however, there was never an elaboration on the idea from Keynes.)
A relatively new decision-making model was made by Loewenstein, Weber, Hsee and Welch (2001) called “Risk-as-Feelings Hypothesis”. Standard models, such as Expected Utility Theory and Prospect Theory, expect decision-makers to act rationally at any given point. This theory, however, stresses the importance of emotions in given situations. When decisions under risks are being made under emotional influence, these decisions might be significantly different than those under “rational behavior”. As such, we can differentiate between “hot” and “cold” statuses, the first being the emotional, while the latter being the “rational” state. For which condition will be dominant during the decision is dependent on (among a lot of other, external and environmental factors) how significant visceral factors (“gut feelings”) are at that specific time of the judgment and decision.
Loewenstein (2000) argued that these gut feelings may distort decisions from that made under quasi-rationality.
First it may lead decision-makers in situations where economic or social inequalities and injustice is perceived, to act in a way which contradicts their own interests.
Second, it has implications on changes in preferences in inter-temporal choice. In a given situation, one might be in a “cold” state, while three months later in a “hot” state – even if their supposed “core preferences” did not change – the outcome might significantly differ. Thus, emotional effects could be looked at as “standard deviations”, which can explain inconsistencies in decisions.
Finally, Loewenstein points out that feelings can have serious implications for decisions under risk. Under visceral effects such as frustration, a seemingly risk-free prospect might be evaluated as risky. Similarly, while in an optimistic, euphoric state, risky prospects might be evaluated as more secure ones.
It is also important to note that these visceral factors can be a) controlled by individuals, if able, or b) individuals can turn this to their advantages if they “learn” how to use this in heuristic decisions. But in this blog, I would like to concentrate on one particular topic – revenge.
Trust game – with a twist
In economic terms, we can be vengeful in many ways, starting from boycotting a particular brand or store to being malicious towards them (or in more academic terms: us being an actor in decreasing their utility, their profits).
Standard trust game is pretty common amongst experiments in psychology and behavioral economics. The rules are pretty simple: there are two players in separate rooms, with no connections whatsoever. The first one receives $10, and is told that s/he can give “x” amount to the second player. For every dollar, the second player receives four times the money that was originally sent. Then, the second player can decide how much to send back to the first player. Simple enough, right?
There exists, however, a version of the game where upon the second player acting unfairly, the first player has the option to have their revenge, paying from their own wallets. For every dollar they pay to the experimenter, the second player loses twice as much. The results were shocking: a lot of people were very keen on paying even absurd amount of money in order to divest the other player from their prize (de Quervain et. al., 2004). What was even more interesting, that during the games, players were wearing MRI sets monitoring their brains: upon taking revenge (for some, perhaps not surprisingly), the part of the brain which is responsible for the perception of rewards was very active. As such, neurologically, we treat malicious acts coming from envy and feelings of injustice as “making things right”.
“Revenge, the sweetest morsel to the mouth that ever was cooked in hell.” (Walter Scott)
Revenge, or the urge to be vengeful, in economic terms usually occurs when we feel that we have been hurt in a transaction, or we perceived the outcome to be unfair – that is, effort and gains were not in balance. While I do not want to go into how people perceive fairness, and what serious implications it has on economic decisions – this was already discussed in last week’s post – I do want to mention that the trade-off between fairness, redistribution and efficiency has been under heavy research in the field of welfare economics (Atkinson, 2015). But welfare economics primarily takes into account the macroeconomic consequences, and perhaps not so much the emotional and economic-behavioral implications to the individual (which is, by the way, completely fine – that is not the main goal of the topic).
Is taking revenge good? Well, it certainly feels that way. But if we take a look at these examples, it is easy to see that most of the time it costs us, leaving us worse off than before (objectively speaking). Maybe that is why moralists, philosophers, and the Bible speaks at lengths against acting revengefully. But maybe revenge will help us to avoid such situations later (by using the tit-for-tat strategy, which will be discussed in a future blog). Whether we deem it good or bad, when emotions – our “hot” state – come to play, we might not be able to have that firm of a grasp on our decisions.
Atkinson, A. B. (2015): Inequality: What can be done? Harvard University Press, 2015.
Keynes, J. M. (1936). The General Theory of Employment, Interest and Money. London. Macmillan. pp. 161-162.
Loewenstein, G. (2000). Emotions in Economic Theory and Economic Behavior. American Economic Review, 90 (2): 426-432.
Loewenstein, G. F., Weber, E. U., Hsee, C. K., & Welch, N. (2001). Risk as feelings. Psychological Bulletin, 127(2), 267–286.
Rawls, J. (1971): A Theory of Justice. Harvard University Press, Cambridge, MA, 1971
Weber, E. U., & Milliman, R. A. (1997). Perceived risk attitudes: Relating risk perceptions to risky choice. Management Science, 43 (2), 123–144.
de Quervain D., Fischbacher U. , Treyer V., Schellhammer M., Schnyder U., Buck A., & Fehr E. (2004): The Neural Basis of Altruistic Punishment Science 305, no. 5688 (2004): 1254–1258.
Antal Ertl ·
January 26, 2020
(Un)Fairness – Part 1
Economists and social scientists have always been fascinated by fairness, and what defines our perception of it. As straightforward as it seems to talk about fair behaviour, defining it, however, is rather complex: after all, it all depends on individual perception. The radical view is more of an egalitarian point of view, where deviations from the norm are considered to be unfair. However, we do have to keep in mind that fairness and justice are two very different things. I do not wish to give you a “true” definition on fairness (philosophers way more knowledgeable than me have failed to do so), but rather, how important our perception is on fairness, how it affects economics, and whether a fairness-seeking behaviour is rational.
I’m going to make him an offer he can’t refuse: Ultimatum Game
One of the most commonly used games in economics is the ultimatum game. The rules are simple: two players have to divide $10 among themselves. The first player does the division, which the second player can either accept or refuse. However, each of them will only receive their part of the money if the second player accepts the offer. Because of this, the first person has to offer a reasonable amount of money to the second player in order to get anything.
Stop for a second and think: If you were the first player, how much would you offer to the other player?
Unless your answer was 0.01$, your expectations are not rational. If they were, then you would assume that the second player’s actions won’t change whether he gets one cent or nine dollars: in each case, he would be better off than he was previously. However, results show that modal offers are, in fact, 50% of the pie, while the mean of the amount offered is around 40%. Two things come from this: first, people tend to make fair offers, fearing that it might be refused otherwise. And indeed, offers where the offered money was less than 25% of the total, being perceived as inequitable, were commonly rejected. However, if one is aware of the fact that receiving $1 should not be relative to the other person’s gain, then people tend to accept smaller amounts of money. This is why, for example, in one version of the game, economics students (being primed to be more self-interested) offered less and were willing to accept less money in ultimatum games (Carter and Irons, 1991).
Second is that one of the important factors during the division is entitlement and legitimacy, meaning – for what reason, and who is the one with the power to make the offer. In one version of the game, the roles were decided on the basis of performance in a trivia quiz, with the winners becoming the proposers. The proposers were told that they won this right by being smarter, thus gaining public entitlement. When it came to games where people “earned” the right to be proposers, offers were more parsimonious. The proposers appeared to believe that the responders would be willing to accept more modest offers. Surprisingly, however, the receivers were not willing to succumb to this newly-given-authority, resulting in a rise in rejection rates. This has been tested with games played with $10 and $100, and the results were nearly the same (Hoffman et. al. 1996).
Ultimatum game has a very interesting implication: those who were making the offers were doing so to maximize their own expected payoffs (which is consistent with mainstream economics’ self-regarding preferences and “selfishness”). However, those players who rejected had not concentrated on themselves, but rather the difference between their payoffs and that of the other player. Instead of benefiting from receiving some money, they chose to punish the other person for not being fair.
Fair play in the markets
According to Okun (1981), a failure to conduct business in a fair manner could distort consumer markets, which in turn leads consumers to reduce their expenses due to loss of trust in the market. In his view, the supply side has the power to set the prices, and at times it can even have monopolistic power (although he does not mention it, demand side obviously has tools to indirectly affect prices). In essence, Okun found that consumers react in a hostile way to all price-increases which are not justified with some cost-increase. However, they tend to accept “fair” increases if supply stagnates or decreases, due to realizing that otherwise, the business would go bankrupt.
In their research, Kahneman, Knetsch and Thaler (1986) aimed to find patterns in the perception of fairness using survey data. They wanted to find “social norms” in fairness regarding pricing, wage negotiations and rent changes. Also, they were interested in quantifying the effects of unfair behaviour in the markets. They used reference-transactions as anchoring in order to define a superficial “norm”, then they tested how people react to the deviations from this norm. They were curious whether price-changes can be justified in three situations. Are these changes fair, when:
the firm’s profits increase,
the firm’s profits decrease, or
due to structural changes in the market, the firm’s profits increase.
Results, though not exhaustive, suggested that:
Increases in prices (even significant ones) are considered to be fair when it is preceded by increases in commodity prices, making production costs and costs in general higher. But the firm can only “defend itself” from cost-increases related to the transaction at hand.
Consecutively, if the previous point is accepted, it is generally considered to be unfair when benefits from decreasing costs are not shared with other stakeholders.
Increases in profits are deemed fair if it isn’t related to the losses suffered by the consumer.
One of the key findings regarding the perception of fairness is the phenomena of “dual entitlement”. In short, this states that the sellers have an entitlement to achieve their reference-profits, while customers are entitled to the conditions of the reference-transactions. Consecutively, the transactions deemed “fair” are not necessarily fair from an objective point of view – that is, they are not necessarily “just”.
I’m having what he’s having
As we can see, preferences commonly used in economics might not work in certain situations such as the ones presented by the ultimatum games. Due to this, institutional and behavioural economists came to the idea of using “social preferences” and the concept of “homo equalis”, which can still be mathematised, but can explain a number of economic choices within social context. This will be elaborated on in our next blog, stay tuned!
Carter, J., & Irons, M. (1991). Are economists different, and if so, why? Journal of Economic.
Franzini, M. (2017): Institutional Economics – lecture notes. Universitá di Roma “La Sapienza”.
Hoffman, E., McCabe, K. and Smith, V. (1996) On expectations and the monetary stakes in ultimatum games. International Journal of Game Theory, 25: 289–301.
Kahneman, D., Knetsch, J, L. & Thaler, R. H. (1986): Fairness as a Constraint on Profit Seeking: Entitlements in the Market. American Economic Review, February 1986.
Okun, A. (1981): Prices And Quantities, A Macroeconomic Analysis, Washington: The Brookings Institution, 1981.
Atakan Erdogdu ·
January 19, 2020
The License to Vice
It’s 4 p.m. in the office, you hear the growling sounds coming from your stomach. As you are aware of the fact that it is too late for lunch and too early for dinner, you decide to take a walk to the vending machine, where you are confronted with an assortment of unhealthy, yet tasty, chocolate bars alongside relatively healthier items including fruits and granola bars. As you contemplate which product to purchase, you recall that you have eaten healthy food and exercised regularly in the preceding days, and decide to purchase the chocolate bar thinking that you have earned enough ‘credits’.
The given scenario evinces an overlooked aspect of decision-making: previous virtuous actions granting the right to do otherwise, an effect referred to as moral licensing in the literature. The converse effect, where the evocation of previous immoral actions/selves/intentions induces individuals to behave socially responsible, is widespread in prosocial contexts. In a famous experiment, Sachdeva et. al. (2009) asked participants to list nine morally positive or negative traits, after which participants were given a chance to donate some of the amount of the received money from participating in the experiment to a charitable organization. It is remarkable that, consistent with the moral licensing effect, the average donation of individuals listing their positive traits was $1.07, whereas for the control group it was $2.71. What is more remarkable, however, is the observation that individuals listing negative aspects chose to donate $5.30, as if they were compensating for feeling immoral, i.e. morally cleansing themselves.
The provided examples reveal that, unlike the assumption of traditional economic theory, in which past decisions do not have an effect in the evaluation of current choices, people are significantly affected by them. However, the question regarding the underlying mechanisms that explain the delineated tendencies still persist.
Looking Under the Hood: Our Moral Bank Accounts
The explanation provided by the experts state that it does not pose a big problem to commit immoral actions as long as it is offset by prior virtuous actions of similar magnitude. Accordingly, individuals have a cognitive moral bank account in which previous good deeds establish credits that can be withdrawn to ‘purchase’ the right to do otherwise. The vending machine exemplifies this phenomenon, whereby, the individual knows that eating tasty chocolate bars is unhealthy, but previous deeds of exercising regularly and eating healthily have substantially increased the health accounts’ value such that the individual has earned the right, i.e. the license to do vice, to eat unhealthily. The effect of behaviours on the account’s value is illustrated below (Graph 1).
The graph emphasizes that previous virtuous actions increase the value of the account, and if the account value reaches above the expected average, the individual perceives him/herself to have a moral license and can perform activities that decrease the account value. Conversely, if the recollection of previous deeds gives the perception of underperforming in virtuous activities (the trough in the graph) in relation to his/her self-assessment of the correct amount (the average line in the graph), the underlying cognitive process induces the individual to partake in activities that increase the account value, i.e. cleanse him/herself. This occurrence is discernible in the self-trait example, where individuals who listed negative traits of themselves were given the perception that they are not as virtuous as they should be. Hence, to cleanse themselves they decided to donate almost twice as much as the control group. In a similar vein, for the positive trait group, the perception that they are overperforming in terms of virtuousness provided them a moral license, leading into a considerable decrease in the donation amount.
However, there remains yet another more general, though perhaps more important, question to be addressed: why did the donation amount change by so much more (35%) for the negative trait group? As we have highlighted in our post on valence-framing, the weights individuals give to negative and positive signs are skewed towards negative values, implying that negative values have the characteristic of being perceived as higher than an equivalent amount of positive value. In the pro-social experiment, the listing of negative traits can be thought of having a similar effect, increasing the donation amount disproportionately for positive and negative participants.
Adjusting the Sails: Implications for Non-Profit Organizations
When utilized correctly, the effects of moral licensing on pro-environmental and pro-social decisions can be influential. The examination of the underlying mechanism of licensing reveals that, since the past morally-laudable behaviour is perceived as providing a license to do otherwise, previous pro-environmental behaviour can inhibit future pro-environmental behaviour. Series of conducted experiments (Gholamzadehmir, 2019) concluded that people who received weekly feedback on their water consumption have substantially lowered their water use, however, they have also increased their electricity consumption, highlighting that moral licensing is in effect between categories of virtuous activities.
The key is to realize that there is not necessarily a trade-off in play, but actually a great potential for integration. The reason for individuals granting themselves licenses is that they view behaviours as an achievement of a goal, and the licensing provides them an opportunity to reward themselves. However, through effective framing and account integration, if the past behaviour is communicated in a way that it evokes that it is a progress towards the goal of sustainability, not the achievement of it, the problem of increasing pro-environmental behaviour in one category while decreasing it in another can be alleviated. However, whereas tackling moral licensing is useful for existing environmentalists, utilization of moral-cleansing will most probably be of high influence in actuating individuals who do not take part in pro-environmental actions.
Gholamzadehmir, M., Sparks, P. and Farsides, T. (2019). Moral licensing, moral cleansing, and pro-environmental behaviour: The moderating role of pro-environmental attitudes. Journal of Environmental Psychology, 65(), pp. 101-134.
Merritt, C. A., Effron, A. D. and Monin, B. (2010). Moral Self-Licensing: When Being Good Frees Us to Be Bad. Social and Personality Psychology, 4(5), pp. 344-357.
Sachdeva, S., Iliev, R. and Medin, D. L. (2009). Sinning saints and saintly sinners: The paradox of moral self-regulation. Psychological Science, 20(4), pp. 523-528.
Wilcox, K., Vallen, B., Block, L. and Fitzsimons, J. G. (2009). Vicarious goal fulfilment: When the mere presence of a healthy option leads to an ironically indulgent decision. Journal of Consumer Research, 36(3), pp. 380-393.
Antal Ertl ·
December 21, 2019
Conspicuous Consumption
In mainstream macroeconomic theory, the consumer is an actor who can choose from at least three possible options: make investments in the economy, save a portion of their disposable income, or consume available goods on the market. While both savings and investments in the economy are crucial, in this blog, we would like to concentrate on consumption – specifically, conspicuous consumption.
There is hardly any human behaviour that isn’t influenced by social interactions, and consumption is no exception. One would expect purchase decisions to be based solely on the utility derived from a given article, i.e. the intrinsic value of it. Yet, a simple observation can reveal that it is the extrinsic value that determines the majority of consumption choices. The value derived from the consumption of an article comprises a signal value that evinces wealth and social status to the observers. It is of no coincidence that two articles – such as a Casio and a Rolex watch – satisfying the same need, are valued differently. This phenomenon, the desire to display social status which guides consumption decisions, has been coined as conspicuous consumption. Evidence from sociology indicates that the need for conspicuous consumption is so high, that it becomes the prevailing decision driver after the subsistence level. The vanguard of this theory, Thorstein Veblen, believed that “No class of society, not even the most abjectly poor, forgoes all customary conspicuous consumption”. A quick glance around will reveal that Veblen was right: it is by no means an uncommon spectacle to find a relatively low-income individual working with the utmost effort to purchase the latest iPhone or a designer bag.
Status goods and opportunism – an experiment
While there are many experiments where consumption choices are at the center of investigation, there is one in particular that is of interest to us. Damianov (2009) created an experiment where subjects had to make budgetary decisions on the division of consumption goods. This experiment is exceptionally great and has been devised to be interpreted in economics classes; however, it heavily involves behavioral economics.
In the experiment, subjects have a $1000 budget constraint, and they need to make a decision on whether to buy standard consumption goods, or “status goods”. The two goods have different functions: in economic terms, consumption goods are the ones which objectively increase one’s utility – if you choose to buy $1000 worth of consumption goods, then your base utility will equal 1000 (but it’s not your ‘final utility’).
Status goods, however, is where it gets interesting: investing in these goods – let’s say, jewelry – will measure your social ranking in society. There are four options:
1) If a person has the highest investment in status goods, s/he becomes the ‘Elite’, and his/her consumption utility gets multiplied by 10;
2) If there is more than one person with the highest investment in status goods, they become the ‘Upper class’ ; their multiplicator is 4;
3) If one invests $100 less than the ‘Elite’ or the ‘Upper Class’, one will become ‘Middle class’, and their multiplicator will be 2;
4) Finally, if one’s investment lags behind by $200 or more than the ‘Elite’ or the ‘Upper Class’, one will become ‘Lower class’, and their multiplicator will be 0.5.
Students then have to make simultaneous choices on their consumption. For example, if there are two players, and the first invests his money 50-50, and the second person invests only in consumption goods, then the first student becomes the elite (his utility becomes 500 x 10 = 5000) while the second student will become lower class (thus their utility is 1000 x 0.5 = 500). What would be the rational choice to make while budgeting?
If the whole society would only invest in consumption goods, everyone would be upper class, thus they would achieve the highest social utility possible – this choice being Pareto-optimal. However, this would also give the option to certain people to ‘go rogue’, and play an opportunistic turn by investing into status goods, making them the Elite. This move, however, starts a vicious circle: everyone starts to invest more and more into status goods, turning the whole game into something similar than that of the problem of commons. This experiment provides a great example on how a supposed social maximization can be achieved and in reality, how fragile it really is.
Instagram – the very definition of conspicuous consumption
As we have delineated, conspicuous consumption satisfies the need to communicate the relative standing of an individual, i.e. the social status, to the general public. Subsequently, which platform can be better to achieve this purpose than Instagram, with over 1 billion users, to display the possessed status and image? It is not an uncommon phenomenon to see pages such as ‘Rich Kids of Instagram’ posting pictures with helicopters and race cars in the background. Research conducted by Krause et al. (2019) validates this assertion: in the devised model, the driving factor behind 43% of Instagram posts was found to be predictable by conspicuous consumption.
Conclusion
The role of conspicuous consumption in our daily lives is often indiscernible; yet, it is one of the primary forces that directs our purchase decisions. The effects of conspicuous consumption can be drastic, since it necessitates individuals to consume continuously for displaying their social status to others, creating a vicious circle that has already trapped Millennials.
It should be remembered that Veblen introduced this in 1899 – at an era where conspicuous consumption was much harder to have a grasp on. Today, more than 120 years later, his theory is more relevant than ever.
Damianov, D. S. (2009): A Classroom Experiment on Status Goods and Consumer Choice. University of Texas—Pan American, June 8, 2009.
Han, Y. J., Nunes, J. C. and Dreze, X. (2010). Signaling Status with Luxury Goods: The Role of Brand Prominence. Journal of Marketing, 74(4), pp. 15-30.
Krause, V. H., Krasnova, H., Baumann, A., Wagner, A., Deters, F. and Buxmann, P. (2019).
Keeping up with the Joneses: Instagram use and its Influence on Conspicuous Consumption. Darmstadt Technical University.
Veblen, T. (1899). The theory of the leisure class. New York: MacMillan.
Atakan Erdogdu ·
December 15, 2019
The Financially Illiterate Public: Causes, Effects and Implications
‘Generation X is not saving enough’, ‘baby boomers are out of retirement savings’, ‘the student debt is at an all-time high and is continuing to increase’, and many similar headlines appear in the news every day. Have you ever wondered why the general public tends to continuously face financial problems? Or why financial problems persist despite the advances in the average quality of education? In this week’s post, we will explore some of the reasons for why such problems occur and provide potential ways to tackle them.
It turns out that economics is infamously hard to comprehend, and the human mind is not particularly equipped to think about the prevailing cause and effect relationships in the macroeconomy. Even then, the understanding of it does not translate into rational decisions. Furthermore, despite the apparent difficulty of understanding economics and utilizing the concepts in one’s decisions, the information provided to the public conveys that people are expected to understand it. There can hardly be an engineer found explaining to the public the precise technicalities that caused a building to collapse on the news, and yet, the newscasts continuously discuss economic matters such as daily stock returns and economic consequences of the US-China trade war, expecting people to understand and make significant life decisions based on the provided information.
Making sense of the unknown
Confronted with the implicit expectation to understand the intricacies of economics and take corresponding actions, individuals attempt to cohere information. In particular, they superimpose economic concepts into acquainted structures and utilise simple heuristics to understand unknown information. In doing so, distorted information – characterized by misconceptions and oversimplifications – is derived.
As Dan Ariely remarked, in this case, the mechanism used by the public to understand incongruous information follows a pattern, which, is predictably irrational. On the one hand, to provide a ground for their judgment, individuals consider changes in economic variables to be either good or bad. Subsequently, if one economic variable is perceived as bad, such as unemployment, people expect it to have a causal relationship with the other ‘bad’ variables. This thinking, good-begets-good heuristic, leads to drastic conclusions. For instance, since people dread unemployment and believe it is the result of inflation, undue support is given to erroneous political campaigns. On the other hand, individuals utilise metaphors – such as perceiving inflation as a ‘monster eating up the purchasing power of money’ – to assimilate unknown information.
Effects of having the wrong judgments
When one makes the wrong judgment, it is highly probable that an erroneous action will ensue. In the case of the general public, the piecemeal understanding of economic events translates into drastic financial decisions. It is of no coincidence that after the shift from Defined Benefits to Defined Contribution Plans, which gave the financial management authority to the individual, the number of Americans who are predicted to not have enough retirement savings increased from 49% to 64%. Reasonably, this will lead to increased borrowing in the future as individuals will want to preserve their standard of living, and create a debt-spiral, which, has already started to take place.
How to alleviate the problem: policy implications
Individuals give high importance to having freedom in their choices, and yet, when given the autonomy in the financial domain, they tend to make the wrong decisions. One solution proposed by academics to alleviate this problem is to increase the public’s financial literacy through educational programmes. Although education certainly needs to be promoted, the results of comprehensive academic research challenges the effectiveness of an educational approach in improving financial capacity. This is instantiated by the behaviour of Nobel Laureate Harry Markowitz, who has devised the modern portfolio theory of investing. When asked about his investment decision, he said that he doesn’t engage in high level stochastic mathematical calculations, but simply purchases certain stocks. In addition, as Thaler and Sunstein indicated, even the economics professors in the University of Chicago are not saving enough for their retirement. Hence, it can be deduced that financial education does not necessarily translate into correct financial decisions; statistical reports suggest that the translation is as low as 0.1%.
Therefore, another approach that – instead of going against – understands human nature should be taken. This will necessitate reverting back the way people make sense of the unknown. Even though the utilisation of metaphors can increase the level of understanding, this needs to be combined with the action stage. Accordingly, evidence from behavioural economics suggests that the best approach is to ‘nudge’ people, using different techniques such as default options, towards the right decision. In the upcoming blog post we will shed light on the nudge theory of behavioural economics.
Ariely, D. and Jones, S. (2008). Predictably Irrational. New York: HarperCollins.
Caplan, B. (2002). Systematically biased beliefs about economics: Robust evidence of judgemental anomalies from the survey of Americans and economists on the economy. The Economic Journal 1112(479), pp. 433-458.
Cheng, W. and Ho, J. A Corpus study of bank financial analysts reports semantic fields and metaphors. International Journal of Business Communication 54(3), pp. 1-25.
Thaler, R. H. and Sunstein, C. R. (2008). Nudge: Improving Decisions About Health, Wealth, and Happiness. Hew Haven: Yale University Press.
Antal Ertl ·
December 8, 2019
The Remnants of Feelings in Mainstream Economics: Animal Spirits
From the dawn of economic thinking, economists were fascinated by emotions and their role in the economy. The father of economics, Adam Smith, was also fascinated by it. In his idea, the invisible hand – which is perhaps the most misused and misunderstood metaphor in economic thinking – originally applied to distribution problems, where societies did not wish to unjustly distribute the goods and profits in the market. The presence of an invisible hand lead the people to act according to the benefits of society. Numerous economist thinkers were interested in moral and distributive questions, let that be Smith, Mill, Hayek, or Thornton.
However, during the marginalist and neoclassical revolutions, when economists were busy trying to create mathematical models for decision-making processes, emotional factors were omitted. This was due to them being too erratic and way too complicated to include in such models (yet, they still believed that emotions have powerful effects on the economy). Nonethless, a number of economists continued to contribute to the literature of the effects of emotions on the economy: Edgeworth, Scitovsky, Katona, Simon – just to name a few. But perhaps the most widely accepted view came from one of the most influential figures in economic thought – Keynes.
A Brief Story on Animal Spirits
In macroeconomics, there’s a theory for business cycles, which aims to understand why the booms and busts happen in an economy. One of the first written business cycles – as Thomas Sedlacek observed – is documented in the Bible, when Joseph deciphered the dream of the Pharaoh:
(Genesis 41:29-30) Behold, seven years of great abundance are coming throughout the land of Egypt, but seven years of famine will follow them. Then all the abundance in the land of Egypt will be forgotten and the famine will devastate the land. (Genesis 41:34) Let Pharaoh take action and appoint commissioners over the land to take a fifth of the harvest of Egypt during the seven years of abundance.
Thus, the economy is a constant circle of “abundance” and “famine”, booms and busts. First, economists considered these business cycles to be completely exogenous: external shocks that affect an economy. According to this view, fluctuations in an economy can only be attributed to random changes in external variables.
Later, economists began to analyze if these fluctuations can occur even when macroeconomic fundamentals are relatively stable overtime. The first explanation says that in this case, distortions occur when endogenous factors in an economy fail to reach and remain at a stationary state while the fundamentals are intact (For more information, see Hicks (1950) on full-employment equilibrium).
The second view can be traced back to John Maynard Keynes. He argued that our decisions “(…) depend on spontaneous optimism rather than mathematical expectations, whether moral or hedonistic or economic…” (Keynes ,1936, pp. 161-162.) Keynes called this phenomenon Animal Spirits, however, he never exactly specified or elaborated on what he meant by it (in this sense, Keynes was like Einstein: they both had marvelous ideas, thus giving ‘homework’ for economists and mathematicians alike for the next century to come). Generally, Animal Spirits tend to be understood as the ‘mood of the market’, whether the perceived prospects tend to be positive or negative.
From a macroeconomic point of view, economists try to use the theory of Animal Spirits by applying it to the labor market: when spirits are high, employment will rise, and with greater labor force, an increase in output with follow, validating the original perception of the economic prospects, thus creating a self-fulfilling prophecy. What can be a nuisance, however, is that with the increase of the labor market competitiveness, companies will have to compete for the workers, thus increasing the hiring costs (but this factor is usually simplified or completely neglected). Similarly, in the case of low spirits, the demand for labor will decrease, and consequently, the output is expected to decrease as well.
Another area of macroeconomics where Animal Spirits is present is in the consumption functions, namely the measurement of ‘consumer confidence’. For example, for the 1990-1991 recession, Blanchard (1993) blamed mainly the nature of the business cycles, but also the loss of optimism among the consumers, deriving from the negative experience coming from the recession itself. This will suffice to go back to the recent crisis of 2008, where in the coming years, confidence (and trust) in banks severely declined, and this can be observed even today.
Economist argue that these heuristic expectations can, in fact, be rational. Howitt and McAfee (1992) argue that “people may rationally anticipate the waves of optimism and pessimism that keep employment fluctuating forever” (pp. 498). One would argue that this is not the case. Remember the Monte Carlo fallacy? In the case of a roulette-game, after 49 consecutive plays where the winner was red, we tend to think that the 50th round will surely be black. Why? Because we tend to give probabilistic balance a great role when dealing with uncertainty. Rationally, the 50th round would still be a 50% chance of being black as opposed to red (supposing that the roulette-table is in fact not rigged).
Turning to a more micro-centered approach, Loewenstein and O’Donoghue (2004) applied Animal Spirits in a different way. In their view, people have “dual minds”, two parallel systems in decision-making based on psychological and neuro-scientific research. They call the first one the “deliberative system”, which in essence is along the lines of standard rational economic thinking. The second one is called “affective system”, which accounts for the emotional thinking (or rather the emotional reactions).
This two-sided decision-making system has several important implications. First, they note that external stimuli can have great effects on activating the affective system. Another interesting factor is individuals’ intrinsic (or endogenous) willpower, which accounts for the deliberative system’s oppression over the affective system. In other words: how effective can one’s rationality be in repressing their own gut feelings. This hypothesis also carries in itself the motion of cognitive dissonance, for when a decision is made based on emotions or gut feelings, often times we long for choosing the rational way, and vice versa. Finally, the model manages to explain how in seemingly indifferent situations people often manage to make extremely different actions.
Homo Erraticus rather than Homo Oeconomicus?
With the ever-growing dissatisfaction of complete rationality in economic models, alternatives like behavioral economics are in their Renaissance. Some economists turned to Sociology, Psychology, Neural Sciences and several other fields to resolve the problem of emotions in economics. New theories, such as bounded rationality and reference point-based decision-models, try to explain the effects emotions bring to the table. The purpose of this article was not to critique behavioral-macroeconomics methods; its goal was to address that maybe we should dig even deeper, back to the fundamentals of macroeconomics. Creating a new consumption function, or adding a couple more parameters might not do the trick, as we may have to go back to the micro level. Whether you agree with this or not, one thing is for certain: we still need to do our homework that Keynes and a number of other great economic thinkers left for us.
Blanchard, O. J. (1993). Consumption and the Recession of 1990-1991. American Economic Review 83 (2): 270-74.
Keynes, J. M. (1936). The General Theory of Employment, Interest and Money. London. Macmillan. pp. 161-162.
Hicks, J. (1950): A Contribution to the Theory of the Trade Cycle, Oxford: Clarendon Press.
Howitt, P. and McAfee, Randolph, (1992), Animal Spirits, American Economic Review, 82, issue 3, p. 493-507.
Loewenstein, G., and O’Donoghue, T. (2004). Animal Spirits: Affective and Deliberative Influences on Economic Behavior. Pittsburgh, PA: Carnegie Mellon University.
Sedlacek, Thomas (2011): Economics of Good and Evil. The Quest for Economic Meaning from Gilgamesh to Wall Street. Oxford University Press.
Antal Ertl ·
November 10, 2019
Does Morality Have a Place in Economics?
There is a joke that whenever someone asks an economist about the prospective effects of a policy in question, a good economist should always reply with: ‘it depends’. Why? Because the number of outcomes in theory are limitless. Let’s take a simple example: an increase in taxes. If we want to oversimplify, an increase in taxes – ceteris paribus – will demand taxpayers to pay more money, which decreases their disposable income, in parallel with increasing the government’s tax revenue. One could argue that if the government invests this tax revenue, for example, into education or healthcare – thus increasing the citizens prospects for higher social standing or for longer and healthier life – ‘lifetime utility’ can increase. However, a problem arises: higher taxes can result in higher tax evasion, therefore creating a free-rider problem, while also potentially decreasing the tax revenues of the state.
The purpose of this example was to demonstrate that economists’ take on a problem very much depends on their assumptions on society. You want to use tools for policymaking that concurs with your view on how the economy and the respective agents would react to it. But how can we define what’s good for society? Is it fair to overtax the rich to support the poor? Should we pursue a more egalitarian approach, or should we just go with ‘every man for himself’?
The values that define us
From the earliest days, economics and philosophy have been intertwined when dealing with complex problems. The economy operates between people, therefore interpersonal connections, fairness and justness are key when deciding on what is acceptable and what is not. Ancient Greek philosophers, such as Aristotle or Socrates, gave great importance to what should be the goal of economic decisions or transactions. For example, how should we approach the problem of money lending? Aristotle says that there should be no interest on money lent, not just from a moral point, but also from a metaphysical one. By asking for an interest, we price the time-value of the money lent by us, however, time itself does not belong to us.
The core problem arises from intrinsic and extrinsic values. We can consider something as intrinsically good based on whether it has value on its own. On the contrary, we can assign extrinsic value to things that are valuable for the sake of something else. This brings up one of the greatest questions in philosophy (and thus comes up in economics as well): is there such a thing as intrinsic value at all?
Some philosophers argue that, by the world being so complex, nothing has wholly intrinsic value, and there may be a possibility where something has only extrinsic value. Beardsley (1965), however, argues that nothing has intrinsic value. According to him, whatever has value has extrinsic value, but also nothing has intrinsic value by itself. He argues that intrinsic value is “inapplicable”, so even if something has such a value, we would not be able to distinct it. This may be a strong statement, but it could be right in economic terms. For example, regarding prices: Assuming that we’re not historians, we do not know the value of 10 drachmas from ancient Greece. However, if we have information on the purchasing price of it – we know the amount of goods it could buy – then we are on the right track.
Is there even a morality-problem in economics?
Bentham assumes that anyone can estimate the pleasure they experience based on factors such as intensity, duration, certainty, propinquity and purity. Bentham stated that the intensity of pleasure cannot be measured, thus interpersonal comparability is limited and cannot be based on facts; however, he insisted that institutions should try to evaluate these regardless.
According to Bentham, every person shares certain vital concerns, such as certainty, abundance or equality between people, thus making higher utility inseparable from legal codes (e.g. right to sustenance or right to have disposal over one’s goods (property laws)). He argued that property rights should support egalitarian distribution of income and wealth; however, Bentham gave priority to security (as to secure one’s consumption, sustenance) over equality. This should be achieved in a way where incentives guide society to maximize general welfare of the society as a whole. Sidgwick (1877) concluded that, according to Bentham, self-interest and self-centered behaviour should be in harmony with moral goodness and virtue, thus creating a better society.
Mill believed that cooperation with others and the pleasure that comes from the “security” or “sense of freedom” of the cooperation, which generates a certain moral sentiment of justice, is one of the highest pleasures. This high pleasure can be such a powerful motive that it can even subdue selfishness.
Immanuel Kant stated that if our ‘moral’ decision was built on quasi-rational basis of economic calculus, based on our expectations of later pleasure coming from it, the morality of the action is lost. The increase of our well-being (expected or experienced) negates the morality of our acts. If we accept this reasoning, then consequently, true altruistic behavior should be such that does not calculate with pleasure coming from the consequences of our actions, but it should have strictly intrinsic value to it.
In the 1930s the ordinalist revolution began, spearheaded by Lionel Robbins, John Hicks, Paul Samuelson, Abram Bergson and R.G.D. Allen. They redefined the concept of utility in a more simplistic way: utility represents only what the economic agent chooses, similar to a numerical ordering of choices (which are to be consistent), without taking into account the reasoning behind it. In short: utility represents the preferred choices in order, without taking into account morality or psychological explanations. This makes the calculations easier, and also allows useful ways to gather information regarding preferences. However, one might argue that with this simplification, we lost a lot of meaningful information on the processes behind decision-making.
A mathematician, a statistician and an economist all apply to a job. The interviewer calls in the mathematician and asks him: ‘what does two plus two equal?’ The mathematician asks for a paper and pen, begins to calculate, and says: ‘There exists a solution to the problem.’ Then the interviewer asks for the statistician, and proceeds to ask him the same question. The statistician replies ‘with a certainty of 95% I can state that the solution is somewhere between 3 and 5’. Finally, the economist comes in, and is given the same problem. He stands up, approaches the interviewer, and whispers: ‘What do you want it to equal?’
Beardsley, Monroe C., 1965, “Intrinsic Value”, Philosophy and Phenomenological Research, 26: 1–17.
Bentham, Jeremy, 1789, An Introduction to the Principles of Morals and Legislation(several editions).
Mill, John Stuart, 1863, Utilitarianism
Plato, Philebus
Sedlacek, Tomas (2011): The economics of Good and Evil. The Quest for Economic Meaning of Gilgamesh from the Wall Street”. Czech Centre London.
Sidgwick, H (1877).Bentham and Benthamism in Politics and Ethics.
Atakan Erdogdu ·
November 3, 2019
Anticipation and Time: The Greatest Warriors of Decisions?
What is the nature of time? Not the space-time of general relativity, but the time we perceive. Which factors induce us to choose $100 today over $200 in a year? Is it the desire for immediate gratification? If so, why do we prefer to store a bottle of expensive champagne instead of consuming it right away? These are some of the questions that will be answered in this blog.
Of the various assumptions underlying economic analysis of intertemporal choice (choices differing in payoffs and time), perhaps, the assumption of preference for today over tomorrow is the most widespread and non-controversial one. It makes logical sense to appraise more value to $100 today compared to $200 at a later time, since we do not know what goods and services can be bought next year with that amount. Our short-term preference for positive events bespeaks that we are maximizing our utility through the elimination of uncertainty. Likewise, we have a long-term preference for events incurring us costs, i.e. preferring paying $150 in 1 year over $100 today. However, it requires little effort to think of examples of behaviour in which the converse is apparent. The pleasurable deferral of a vacation, the speeding up of a dental appointment, and the prolonged storage of wines are all instances of this phenomenon. Therefore, the traditional economics approach misses an imperative element of intertemporal choices: anticipation of future events.
Anticipation in the Form of Present Utility
It is unequivocally correct that individuals, in their choices, attempt to attain the highest utility. However, the key is to understand that the sensation of the present is affected by the anticipation of the future. We often get positive feelings from anticipating an imminent event. In an experiment conducted by renowned behavioural economist, George Loewenstein, subjects were asked to specify the amount that they would pay now to obtain or avoid each of five outcomes, which were further grouped into time delays. The outcomes were: ( 1 ) obtain four dollars; ( 2 ) avoid losing four dollars; ( 3 ) avoid losing one thousand dollars; ( 4 ) avoid receiving a non-lethal 110-volt electric shock; and ( 5 ) obtain a kiss from the movie star of your choice. Time delays were: ( 1 ) immediate; ( 2 ) in twenty-four hours; ( 3 ) in three days; ( 4 ) in one year; and ( 5 ) in ten years. The subjects were also told that the outcomes were certain to occur at the designated time. The results are illustrated in the following graph.
Figure 1. Maximum payment to obtain/avoid outcomes at selected times. Taken from Lowenstein (1987).
It can be inferred that the two non-monetary items, the kiss and the shock, exhibit unusual patterns. The short-term preference implies that individuals would prefer to obtain positive outcomes as soon as possible. This prediction, however, is contradicted by the kiss item, for which, the highest value appraised to occurrence was 3 days. In like manner, the economist assumption asserts that negative outcomes are delayed whenever possible. Yet, in the shock outcome, subjects preferred to pay slightly more to avoid a shock that was delayed by 3 hours than 3 days.
Explaining the Phenomenon
The ostensibly contradictory phenomenon becomes unambiguous if we consider the affect of anticipation of future events on the present utility. In the experiment, the most valued time for the kiss was three days, as there was also a value from expecting the event to occur. Individuals actually increased their inner pleasure through savouring utility of both the event and the expectation of the event. Likewise, in the shock case, a negative utility arises from expectation of the event, exacerbating the total pain felt by the individual. These negative anticipatory feelings can be acute; researchers have found that in some cases the anticipation of an event may be worse than the event itself.
Evolutionary biology traces the source of this tendency to the aspects of innate mammalian system. In the acknowledged fight-or-flight response system that prepares the body to stay and fight or to flee, negative anticipation of a future event induces people to take the flight response. However, in the cases which the drastic future event cannot be avoided, the individual is propelled to fight now, as in the experiment subjects preferred the shock now instead of having it in three days.
In essence, the determinants of intertemporal choices are not limited to time preferences, and the feelings associated with expectation of a future event further affects individual choices. As the avant-garde economist Alfred Marshall remarked, “When calculating the rate at which a future benefit is discounted, we must be careful to make allowance for the pleasures of expectation.”
Caplin, A. and Leahy, J. (2001). Psychological Expected Utility Theory and Anticipatory Feelings. The Quarterly Journal of Economies, 116(1), pp. 55-79.
Loewenstein, G. F. and Prelec, D. (1992). Anomalies in intertemporal choice: Evidence and Interpretation. The Quarterly Journal of Economies,107(2), pp. 573-597.
Loewenstein, G. F., Weber, U. E., Hsee, K. C. and Welch, N. (2001). Risk as Feelings. Psychological Bulletin, 127(2), pp. 267-285.
Ortony, A., Clore, G. and Collins, A. (1988). The Cognitive Structure of the Emotions. Cambridge: Cambridge University Press.
Antal Ertl ·
October 27, 2019
Why do we have difficulty bearing the ‘other’ group
Have you ever thought, while watching a sport event and the camera showing the fans of the rival team: ‘Gosh, how can they be such animals! Look at our supporters, how well they behave!’ (chances are they behave just the same). Have you ever wondered why you always look favourably to members of parliament close to your political affiliation, while you almost always disagree with the other party? If you did, then this is the blog for you.
Us and Them
Orthodox economics has a tendency to concentrate only on the individual, disregarding the environment. However, the economic environment can have powerful effects on the individual’s preferences as well as their perceived utility. One could argue that there are two parts to your well-being. The first one is earned happiness or well-being that you get from – in economic terms – consumption of certain goods, let them be food, services, or just your free-time. The second one is more abstract, it being the perceived well-being with respect to others. What this means is that you compare yourself (occasionally, regularly or constantly) to others. This can lead to many outcomes, including jealousy or envy, but it can also lead to altruism.
From the point of social sciences though, we can identify ourselves as part of groups, organizations and social classes, respectively to our endowments or our ideologies. We have an urge to belong somewhere, because – as Aristotle elegantly put it – “Man is by nature a social animal”. In the event of transactions by social categorizations, however, we no longer think of people as individuals, but as members of groups or embodiments of moral codes. By this, we often disregard other people’s individual traits and the available information that we previously obtained from them. If your friend supports FC Barcelona, and you are a hard-core Real Madrid fan, then come game day and you are sworn enemies; for a short time, you put aside your personal friendship, and by identifying as parts of a football club, you two are also competing.
From this comes the concept of in-group favouritism: “the tendency to respond more positively to people from our in-groups than we do to people from out-groups” (Stangor, 2011). In other words: We become more receptive to the needs of the groups we belong, while disregarding or even taking a stance against the other groups.
In an experiment designed by Tajfel et al. (1971), boys were assigned to two groups based on their preferences on paintings by two artists. Subjects had information on which groups they were assigned to, but not of the memberships of any of the other boys. Following the division, they had to divide payoff matrices between two individuals. They were told whether the division was between two ‘out-group’ members, two ‘in-group’ members or between one in-group and one out-group member. The results showed that between two individuals from the same group, the subjects tended to divide the payoffs more evenly. However, when the boys were from different groups, fairness was not the predominant choice; instead, the decision-maker gave larger endowments to the in-group members. The subjects not only displayed in-group favoritism, but they did so by having such a marginal distinction as taste in paintings. This can be shown in groups created on ad hoc, trivial, and random basis as well (Hogg et al. 1986).
Is this good or bad?
As any economist would say: “it depends”. While at first, we would think of the negative effects to be more severe, it is useful to take into account the possible positive effects as well.
It most certainly leads to more emotionally-driven decision-making, both in transactions inside the group and outside of it. In these cases, we use heuristics to define our level of trust to individuals. You are more likely to prefer doing business with an ‘insider’. This of course comes from a supposed feeling of connection with and understanding of the other person: you theorize that because the other person is in the same social group as you are, he must share some of the same traits, values, or preferences with you, thus making transactions seem easier!
As stated earlier, in-group favouritism can also have negative effects, even only on the level of possible transactions. You can squander mutually beneficial transactions by regarding your own group as superior to others and reject any kind of interaction with people from other groups. From a rational point of view, this is a net loss, at least as options go. It can also lead to institutionalized distrust.
It can also disrupt seemingly easy decisions. In an experiment conducted by Gneezy et. al. (2010), they asked people trivial questions framed in two different ways. The control group was asked: “Camels are bigger than dogs. Do you agree?”, while the other group received a framed question: “According to the Democrats, camels are bigger than dogs. Do you agree?”. From the first group, 100% of the people agreed that yes, indeed, camels are bigger than dogs. However – as you probably guessed by now – people from the second group started asking questions. “It depends – what kind of dog are we talking about?” “Maybe the dog is a Saint Bernard, while the camel is only a baby!” People began to question trivial things – which can be harmful, as far as decision-making is considered.
There can also be cases where individuals do not look at certain people favorably from their own groups. This is called the black sheep effect, where a particular individual is at stake of threatening the values of the group in question (Pinto, Marques, Levine, & Abrams, 2010). In other words: in order to reduce cognitive dissonance within the group, members disregard these ‘rebel members’. Alternatively, they can act according to the sociocentric bias, where they only credit the group for its successes, but in cases of failure, members blame external factors, leading to self-justification. Sounds familiar?
Can we avoid these kinds of distinctions? Hardly. Some argue that it is in our nature to make comparisons and to make distinctions based on ideologies, ideas and convictions, let them be political, religious, or just unquestioned fanaticism towards a football club. What we can do is to be aware of these biases and flaws and try to be more open to opinions from other groups. After all, who knows? Maybe having universal healthcare is the way to go in economic policy, the dress is in fact blue and not gold, and maybe Messi is the greatest football player in the world.
Ayelet Gneezy, Stephen Spiller, and Dan Ariely, “Trust in the Marketplace: A Fundamentlly Disbelieving State of Mind,” Working Paper, Duke University (2010).
Hogg, Machael, Turner, John, Nascimento-Schulze, Clelia, Spriggs, David: Social Categorization, Intergroup Behavior and Self-Esteem: Two experiments. Revista de Psicología Social, 1986, I. 23-38.
Stangor, C.: Principles of Social Psychology – 1st International Edition, chapter 11, Stereotypes, Prejudice, and Discrimination.
Tajfel, H., Billig, M., Bundy, R., & Flament, C. (1971). Social categorization and intergroup behavior. European Journal of Social Psychology, 1, 149–178.
BeHive Consulting ·
October 19, 2019
How Behavioural Economics can Help Fight Global Poverty and Win a Nobel Prize in Economics
In 2019, more than 700 million people still live with extremely low incomes. Half of the world’s children still leave school without basic literacy and numeracy skills. Every year, around 5 million children under the age of five still die of diseases that could often have been prevented or cured with inexpensive treatments.
Several studies focus on understanding the causes that drive poverty and developing theories and policies to tackle them. Take, for instance, child mortality and health, the problems of which could, in theory, be tackled by empowering women. However, theory doesn’t tell us which policy would be most effective and efficient to boost women’s empowerment thereby decreasing child mortality: it could be a policy focused on educating mothers, new marital age legislation, or better access to healthcare.
All great ideas, in theory, but what about practice? Which policy would bring the best outcome? Which could save the lives of the largest number of children?
This is where Behavioural Economics and the 2019 Nobel Prize come into the picture.
The 2019 Nobel Prize for Economics has been awarded to Abhijit Banerjee, Esther Duflo and Michael Kremer “for their experimental approach to alleviating global poverty”.
In a nutshell, the Laureates divided the global poverty issue into smaller, more manageable questions at individual or group levels. They then looked for the most accurate answer to those questions by using specially designed field experiments. As a result, they noted that a lot of people in low-income countries were not taking advantage of the benefits offered and they asked themselves: ‘why?’. That is, they attempted to pinpoint the causal pathways, through which changes in incentives, constraints and information influence the outcomes of interest via human behavior.
Accordingly, to find an answer, they incorporated economic theories of incentives and development economics – the branch which deals with studying the causes of global poverty and how to combat it – by using direct experiments to design adequate policies based on the behavioral responses of all the experiment participants.
Let’s get a closer look at what they did.
They asked themselves: How can we improve pupils’ learning outcomes?
To answer this question, the Laureates took (let’s say) 250 schools and randomly divided them into different groups of 50. These groups received extra resources in different forms: 50 schools got free school meals, 50 received more textbooks, 50 got extra teachers, 50 schools got a different length of contract for the same number of teachers, and finally the last group received no extra resources, in order to control and credibly link later differences in learning outcomes to the various forms of support provided.
The experiment showed that neither more textbooks, nor free school meals, nor extra teachers per pupil made any difference to educational outcomes. The only change that significantly improved the learning outcomes was employing teachers on short-term contracts, which could be extended through good performance. This intervention increased teachers’ motivation and presence at school and, as a consequence, improved learning outcomes…and yes, among others, it is also the only cost-free solution!
At a first glance, most people would assume that the problem of poor educational outcomes in low-income countries are related to the facility (schools), the tolls (textbooks), parents not enrolling their children in schools, or the poor quality and lack of teachers. The Laureates, however, understood that much of what we want to achieve (such as better educational outcomes) reflects multiple individual decisions – including teachers, parents and pupils. Effective improvements, thus, require an understanding of why people make the decisions they do and what drives those decisions. Among others, Behavioral Economics studies the incentives, restrictions, information and distortions that motivates people’s decisions.
The experiment on education in low-income countries revealed that adding resources (meals, textbooks, teachers) is, in general, of limited value and expensive. Instead, adjusting the existing resources – by understanding why they are creating limited value – can help to efficiently address investments rather than crowd them out.
Let’s look at another finding. Why, in spite of the available subsidies on vaccinations, the percentage of immunized children remains so low?
Healthcare in poor countries is a well-known problem, despite the heavily subsidized vaccines provided by the governments (<1$). Millions of children in low-income countries die from preventable diseases each year. Today’s discussion about reducing child mortality in low-income countries, therefore, largely revolves around human behavior and around what stops people from taking advantage of subsidized vaccinations.
Low-income people are extremely price-sensitive regarding investments of any kind, even healthcare. The experiment implemented by the Laureates was once again to randomly divide the sample into 3 groups of villages:
The first group of villages is the control group offering only the subsidized vaccination;
The second group of villages was provided with a mobile clinic with specialized staff always on site;
The last group had the mobile clinic and families were receiving a bag of lentils as a bonus to vaccinate their children.
As shown in the picture, compared to the first control group, vaccination rates grew by 300% in the villages selected to have access to mobile clinics and by 650% in villages with mobile clinic and the bag of lentils as a bonus. As a specialized facility, the mobile clinics carry high fixed costs, independent of the number of vaccinations. Therefore, the more vaccinations performed by the clinic, the lower the cost per vaccination will be. Accordingly, adding the bag of lentils (a cost) increases the number of vaccinations in such a way, that the final cost per vaccination will be halved compared to the case in which the bag of lentils is not offered (28$ per vaccination and 56$ per vaccination, respectively).
Picture from Press release: The Prize in Economic Sciences 2019. NobelPrize.org. Nobel Media AB 2019. <https://www.nobelprize.org/prizes/economic-sciences/2019/press-release/>
However, mobile clinics and extra incentives did not solve the immunization problem, as 61% of children did not vaccinate. The causes must stem from people’s irrationality. One explanation is the so-called present bias, which is based on the assumption that the present takes up a great deal of people’s awareness, so they tend to delay investment decisions. When tomorrow comes, they once again face the same decision, and again choose to postpone investments, which would be beneficial in the long-term. If individuals are present-biased, then temporary subsidies are better than permanent ones: space-and-time limited offer reduce incentives to delay investments. Besides, it is more cost-effective.
The work of Banerjee, Duflo and Kremer has dramatically increased the practical, quantitative knowledge necessary to isolate key mechanisms behind poverty, which was investigated through the prism of the behavioural responses to various policy interventions. Their work has significantly deepened our understanding of poverty in the developing world. It has already helped in alleviating global poverty and has great potential to further improve the lives of many around the world.
Watch and read more about 2019 Nobel Prize in Economics:
Imagine the following situation: a nun has just left the monastery and commenced her journey to the city centre to make weekly purchases. After she finished her shopping, on her way back to the monastery, she stumbled upon a homeless man sitting on the pavement, a small cup placed in front of him and a sign in his hands saying: ‘Homeless single father, need money for family’. The nun, placing her hands in her purse, hears the tinkling of change and decides to give it to him. She then accepts the blessings of the man with a slight nod and continues her way back.
In this article, we will explore the forms of altruism, leveraging insights from philosophy, behavioural economics and neuroeconomics, and probe into the motives of the nun to determine whether her act of giving was indeed selfless.
Defining Altruism
Prior to taking a stance in the debate on altruism, providing a definition of it is imperative. De Quervian et. al. (2004) distinguish between the biological and psychological definitions of altruism. The biological definition treats altruistic behaviour as ‘any costly behaviour that confers an economic benefit to other individuals’, regardless of the motives behind such behaviour. The psychological definition, in contrast, requires that such behaviour is driven by non-hedonic motives, i.e. without any benefit perceived or expected by the giver. In the given situation, even if the act of giving was motivated by the expectation of immaterial or spiritual reward, the nun’s act would still be altruistic under biological, but non-altruistic under psychological interpretation. However, we are concerned with altruism viewed through the lens of psychology, i.e. pure altruism.
Altruism – Egoism Dichotomy
One way to understand whether pure altruism can exist is to think about its antithesis – egoism, the motivational state with the ultimate goal of increasing one’s own welfare. The famous philosophers, Hobbes’ and Nietzche’s views concerning the dichotomy weigh heavily towards egoism. Nietzche, in his book Human, All Too Human, stated that “any social instinct (behaviour performed to help another) is said to be derived from the communal seeking of pleasure and elimination of pain”. A strong resemblance to this idea can be seen in Hobbes’ philosophy. In his classic work Leviathan, he indicated that “no man gives but with the intention of good to himself, because gift is voluntary… and the object is to every man his own good.” Therefore, motives, not consequences, must be used to differentiate altruism from egoism. The two main types of altruism on the basis of motives are warm-glow giving and pure altruism.
Warm-Glow Theory: The recipient’s well-being is a means to benefit the donor
Pure Altruism: There are no motives, intrinsic or extrinsic, benefiting the donor
In behavioural economics literature, the concept of egoism is accounted through warm-glow theory, in which the act of giving is a reward to the donor. This can be a mechanism that signals wealth, depicts the donor’s character under a positive light, satisfies the desire for self-assertion, overcomes the fear of retribution of God, or reduces guilt. In our nun example, the last two motives might be the dominant reasons for giving. Accordingly, the most fundamental question of our debate arises: How can we know if there are rewarding motives behind altruistic acts – whether the donor perceives internal or spiritual rewards from the act of giving?
What We Do Know: Insights from Neuroeconomics
Neuroeconomics attempts to answer our questions through investigating neural mechanisms in the human brain. Through the usage of functional magnetic resonance imaging (fMRI), we can identify the parts of the brain whose activity increases during the execution of an act. Therefore, if the activity of a reward centre increases whilst performing an altruistic act, we can argue that pure altruism does not exist.
The illustrated graph is taken from Harbaugh et.al. (2007) neuroeconomics experiment. The two contexts of giving were tax payments (red bars) and voluntary giving (orange bars) to a charity organization.
On the x-axis three parts of the brain (caudate, nucleus accumbens, and insula) are shown, which comprise the reward centre. On the y-axis, the standardized coefficients of activity are depicted. The researchers regard the condition of tax payment as pure altruism since they argue that the motives, in this case, are highly non-hedonic. This is due to both the emotional and physical disconnection between the donor and the recipient. However, a compromise could not be reached in the neuroeconomics literature, since other researchers argued that the incurrence of costs is what caused the activity of the reward centre. In the voluntary case, the increase in the reward centre’s activity emphasizes that the donor has received an intrinsic reward from the act of giving, which can be explained by the warm-glow theory.
Conclusion: Revisiting Motives of the Nun
In conclusion, although insights from numerous science branches concur that warm-glow giving exists, a conclusion has not been reached concerning pure altruism, as it would require the ability to know intrinsic motives behind altruistic acts. Hence, apropos of the nun, the determination of her altruistic stance is as elusive as ever. Hitherto, we do not have the tools which can determine whether she has engaged in the behaviour of giving due to intrinsic rewards or she has given for the sake of helping without expecting anything in return. Neither scientists nor philosophers could agree whether true altruism really exists; maybe it all comes down to your own perceptions of human nature.
Batson, C. D. (2011). Altruism in humans. Oxford University Press, Oxford.
De Quervain, D.J., Fischbacher, U., Treyer, V., Schellhammer, M., Schnyder, U., Buck, A. and Fehr, E. (2004) The neural basis of altruistic punishment. Science, 305, pp. 1254-1258.
Dickert, S. Vastfjall, D. and Slovic, P. (2015). Neuroeconomics and dual information processes underlying charitable giving. In: Neuroeconomics, judgment, and decision making, pp. 181-199. Psychology Press, New York.
Harbough, W. T., Mayr, U. and Burghart D. R. (2007). Neural responses to taxation and voluntary giving reveal motives for charitable donations. Science 316, pp. 1622-5.
BeHive Consulting ·
October 4, 2019
Monte Carlo Fallacy: Don’t Look for Patterns Where They Don’t Exist
Casino de Monte-Carlo, August 18, 1913. The crowds, sitting around tables and having their drinks in common rooms, are getting more and more intrigued. Like a swarm of bees clustering around a hive, they are watching spinning roulettes with pure excitement. It seems, these are not ordinary hours in the lavish casino this evening. The gamblers’ attention is especially focused on one particular roulette wheel, in which the ball is falling into the black pockets again and again, eighteen times in a row by now. Every time the croupier collects the accumulating fortune – piles of chips laying on the red zone – more and even greater sums land on the table, as if tonight the players had unlimited cash in their pockets.
That day, the ball eventually fell into a red pocket after twenty-six blacks in a row. In the meanwhile, gamblers have lost millions of francs in just a few hours.
In the following weeks, this highly unlikely occurrence has remained in the highlights; it has been the topic of discussion at all the banquets and gleaming dinner tables: how could such an unlikely event happen? Well, if we dive into the mystery, even with a very basic knowledge of probabilities, we can understand that what happened is nothing supernatural; in fact, we should not even be surprised. The chances of having a 26-turn-long streak of red or black outcome is around 1 in 67 million – which is low indeed – comparable to the likelihood of winning the jackpot with a single lottery ticket.
However, what is even more interesting than the occurrence of a lot of subsequent blacks, is the behavior of the gamblers that night.
As the streak of blacks was persisting, more and more gamblers were betting against black in the deep conviction that the outcome of the next spin needed to be red – holding the belief that temporary imbalances must always equalize in the long run.
This is a famous example of the gambler’s fallacy, or to be consistent, the Monte Carlo fallacy: a misbelief that if something happens more often than expected during a given period, it will happen less in the future”.
The fallacy arises from the false interpretation of the properties of a roulette. Every time the croupier spins the wheel, the previous outcomes become completely irrelevant as they have absolutely no impact on the present turn. To phrase it more technically, each turn is independent of one another, and there is no such thing as ‘equalizing imbalances’.
Then why are gamblers so easily fooled by historical data? Our brain seems to struggle when dealing with independent events, since the majority of events in our lives can be closely related and are seen as a sequence of connected episodes. Being good at recognizing patterns in this complex world has always been the competitive edge for us in evolution, so it is no surprise that we often desperately look for patterns, even where they do not exist. This phenomenon is commonly known as apophenia.
Amos Tversky and Daniel Kahneman proposed that the gambler’s fallacy is a cognitive bias produced by the representativeness heuristic, which states that people evaluate the probability of a certain event by assessing how similar it is to their prior experiences. According to this view, “after observing a long run of red on the roulette wheel, for example, most people erroneously believe that black will result in a more representative sequence than the occurrence of an additional red”. People expect a short sequence of random outcomes to share properties of a long run sequence, believing that deviations from the average should balance out.
However, this expectation is quite wrong. Take a look at the table below to better understand the meaning of relative and absolute deviations from the average. The table represents the results of a simulation of 10, 100 and 1000 spinning with the roulette wheel 5 times, where the most extreme outcomes of each sample size have been highlighted.
Imagine you always bet on black. In the first pillar, you‘ve got 7 blacks – 70% of all the outcomes – but you’ve got only 4 more gains than losses in absolute terms. On the other hand, you’ve got 449 blacks according to the third pillar, which is 44.9% of all the outcomes. Nevertheless, since you have much fewer gains than losses, you will most probably be disappointed. As the sample size is increasing, imbalances are indeed equalizing in relative terms (percentages of black and red outcomes are closer to the theoretical expected value – 48.65%), but the absolute deviation is getting bigger and bigger – and this is what eventually counts when you have to pay the bills.
Afterword. Roulette is a game, where falling into the trap of gambler’s fallacy is actually not a handicap. The crowds, who were so persistently and irrationally betting against the black, had the same chances of doubling their fortunes than losing everything! As we know, the probability of all the outcomes are equal, regardless of what historical data suggests. Therefore, it turns out that the biggest mistake was not favouring the red to the black or vice versa, but taking part in a game with negative expected value.
BBC. Why we gamble like monkeys? (2015, January 2). Retrieved from http://www.bbc.com/future/story/20150127-why-we-gamble-like-monkeys
Tversky, A. and Kahneman D. (1971). Belief in the law of small numbers. Psychological Bulletin. 76 ( 2 ): 105–110.
Tversky, A. and Kahneman D. (1974). Judgment Under Uncertainty: Heuristics and Biases”. Science. 185 (4157): 1124–1131.
Antal Ertl ·
September 27, 2019
I am searching for the perfect match – until I just get tired
Suppose that this morning, when trying to stop the alarm, you accidentally dropped and shattered your beloved phone. After collecting the pieces of the phone (and yourself from the trauma), you realize that you now have to buy a new one. So, you head to the mall: in possession of all the information in the world, based on your preferences (after weighting all the important characteristics of the product), you choose the phone which maximizes your utility with respect to your budget constraint – your wallet. At least that is what the theory of consumer choice and rational decision theory suggest (in which an agent’s goal is to maximize their utility). While there are obvious advantages of this take on the decision theory, let’s see what a non-homo economicus does.
The first problem comes from lack of information. In the classical theory, all the choices are in a given pool, where the decision-maker can decide objectively, for the outcomes are known to them. Simon (1959) argues, however, that perception and cognition play a huge part in decisions. For instance, in different environments, we might perceive the same information in very different ways. Similarly, being savvy within the product category plays a huge role in decisions: maybe we are up-to-date with the new mobile phone trends, or perhaps you just gather information when you are actually planning on buying a new one. It may also be the case that your perceived knowledge can differ from objective knowledge (i.e. when you don’t know how lacking your knowledge really is).
In one of our previous blogs, we talked about the concept of “satisficing utility”; that is, we do not wish to maximize our utility, but rather we just want to keep ourselves “satisfied”. According to Simon, when one cannot reach their desired satisfaction, they turn to search behavior – trying to reach the desired point by searching for alternatives with greater levels of satisfaction.
A significant amount of research papers were dedicated to finding the “Holy Grail” of search behavior. A number of models were proposed, differing mainly in their perspective of the human decision-makers.
John D. Hey (1982) formulated some of the widely-known rules in search behavior. For example, he identified the reservation rule. It states that whenever the search for alternatives yields a price which is lower than some reservation price, it results in a sudden stop of the search, if the product requirements are met. However, there exists a number of rules that, after a number of searches, result in high prices (or to put it simply: after a bunch of unsuccessful search attempts), subjects just stop looking for alternatives and accept the most recent price. In other words – they give up. Perhaps, they realize that the cost of searching is greater than accepting a non-optimal price, or they just simply get tired of it.
Brucks (1985) found that the greater a-priori objective knowledge you have on the subject, the more effective you are in your search for new information. Based on their experimental method, they concluded that basic knowledge helps in prioritizing search for the relevant information, and subjects, who had previous experience, searched for less irrelevant alternatives than their counterparts. This supports Miyake and Norman (1979): “To ask a question, one must know enough to know what is not known”.
The following search behaviour model was designed by Punj and Staelin (1983), which describes the process of information search when buying a new car, Fig.1.
Based on the rational assumptions of this model, the outcome of the search behavior can be called effective when the cost savings from gaining information (e.g. finding lower-priced deals) outweigh the cost of searching (the latter can be interpreted as transaction costs).
Importantly, the search behavior can differ between fast-moving consumer goods and durable goods: indeed, it is not the same to buy an Apple iPhone, as opposed to just an apple. Some would argue that, when the potential risks of bad decisions are apparent, people want to take a safer route: when buying an iPhone, some people might search scrupulously for weeks. In contrast, buying a small item, like an apple, does not come with the same weight. In such a case, we might simply use heuristics to choose. For instance, last time the red ones were better than the greens, so I might just take a bunch of red apples – even though they are from a different producer, or even a completely different apple cultivar.
Regardless of the purchase at hand, whether it be a phone or an apple, search behaviour occurs in almost any of our decisions – it appears to be innate to humans and its existence is irrefutable.
Girish N. Punj and Richard Staelin (1983): A Model of Consumer Information Search Behavior for New Automobiles. Journal of Consumer Research, Vol. 9, No. 4 (Mar., 1983), pp. 366-380
John D. Hey (1982): Search for Rules for Search. Journal of Economic Behavior & Organization Volume 3, Issue 1, March 1982, Pages 65-81
Merrie Brucks (1985): The effects of product class knwoledge on information search behavior. Journal of Consumer Research, Vol 12, No.1, pp. 1-16
Riitta Katila, Gautam Ahuja (2002): Something old, something new: a longitudinal study of search behavior and new product introduction. Academy of Management Journal Vol 45, No. 6, 1183-1194
BeHive Consulting ·
September 13, 2019
Stranger Things: The Role of Behavioural Economics in Political Elections
Stranger Things is a Netflix series set in the fictional rural town of Hawkins, Indiana, during the early 1980s. The nearby Hawkins National Laboratory ostensibly performs scientific experiments, but in reality secretly studies the paranormal and supernatural, including human test subjects. Inadvertently, they have created a portal to an alternate dimension, “the Upside Down”. The influence of the Upside Down starts to affect the unknowing residents of Hawkins in pernicious ways.
Somehow similarly to the awarded Duffer brothers’ fiction, stranger things happened in the real coal-mining town of Ebbw Vale, South Wales, in June 2016. The famous social network, Facebook, performs research on human emotions, and secretly feeds fake news into the users’ profiles. Advertently, Facebook created a portal to a fake dimension, whose influence starts to affect the unknowing residents of Ebbw Vale in pernicious ways. However, this fake dimension was only the first stage of Ebbw Vale’s “Upside Down”.
Until the 90s, Ebbw Vale was famous for its coal and steel; however, with globalization and advancing technology, coal mines and steelworks began to shut down, leaving the town devastated. In June 2016, Ebbw Vale was once again in the public eye, regaining its fame for reaching one of the highest “Leave” votes in the UK (62%). The reportage of Carole Cadwalladr, a Pulitzer Prize finalist, sparked further interest in the town and its inhabitants (see here). Cadwalladr investigated the reasons behind why the majority of the residents wanted to leave the EU. Some of the popular answers were the following: they wanted to take back control of their (public) money, immigrants were stealing their jobs, and the EU has done nothing for them. Paradoxically, among other things, she has found a newly-built £33MM college of further education, a £350MM sports centre, new roads, bridges, and railway stations – all funded by the EU! Even more, there were noticeable signs showing EU’s involvement in these projects (see below).
Besides, Ebbw Vale has one of the lowest immigration rates in the Country. Stranger things.
According to the interviewees, the locals were getting their information discrediting the EU through Facebook.
A research made by Robert Epstein of the American Institute for Behavioural Research and Technology estimated that Google may be able to affect 25% of the votes worldwide through selectively informing users about a candidate’s positive or negative doings. Moreover, Epstein explains the power of the Search Engine Manipulation Effect (SEME), being able to move the preferences of an uncertain elector toward a candidate by simply tweaking the ranking algorithm of a search engine.
Interestingly, Cadwalladr discovered that a company called Cambridge Analytica – which has worked both for Trump and Brexit Campaigns – exploited a similar effect. It profiled people politically, in order to understand their individual fears, and consequently targeted voters more efficiently through Facebook ads. According to the Guardian, this was done illicitly by harvesting the profiles of 87 million people from Facebook. People’s fears were then fuelled by the related fake news appearing in their feed, an example of which can be seen below.
The above information is completely fake; there were certainly no discussions about Turkey joining the EU! Yet, the individuals who might have been afraid of losing their jobs or of seeing their wage drop, were likely paying much attention to this fake news.
According to Cadwalladr, the entire Brexit Referendum “took place in darkness, because it took place on Facebook”. For her, the “Upside Down” of Ebbw Vale (and respectively of Brexit) was Facebook.
However, the aim of this paper is not to blame high tech companies, nor is it to call for higher protection of personal data they possess. Indeed, they are not the main culprits. Instead, we should ask ourselves: why were We, and the citizens of Ebbw Vale blindly trusting in such fake news?
Behavioral Economics explains how irrational and limited the behaviour of an individual can be. According to R.H. Thaler, the human brain can be seen as a hardware, which involves 2 softwares: “System 1” and “System 2”. The former is fast, effortless, impulsive and used in everyday decisions, while the latter is slower, effortful, thoughtful and used in more complex and important decisions (just like an electoral choice is supposed to be, since it is going to affect the future of both the individual and the collectivity).
According to behavioral economists, human beings tend to minimize their effort, naturally causing frequent mistakes that are independent of the quantity of available information. Humans are often selectively unfocused, discharging information deemed unimportant, while preferring information that confirms existing beliefs (referred to as usually as cognitive dissonance).
In other words, by nature, people are ‘lazy’ and follow the law of exerting the least effort necessary, especially for topics they perceive to be far from them, such as politics. As a consequence, in politics, we can expect a variety of people to use the effortless System 1 way of thinking over the thoughtful System 2, thereby becoming “the lazy controller”, as referred to as by Kahneman.
Laziness leads to biases and heuristics. Biases are systematic and predictable errors, while heuristics are shortcuts that allow us to jump to adequate but imperfect answers to challenging questions. An example of a heuristic is the so-called alone effect, which causes an individual to form a full opinion of someone (or something) based on the judgement of his/her singular features. For instance, by acknowledging the entrepreneurial skills of a candidate, an individual may be led to consider this person to be skilled in politics as well, without paying adequate attention to the electoral program proposed.
So far, we have established that people are innately prone to some level of ‘laziness’, leading to the usage of mental shortcuts, i.e. heuristics and cognitive biases. As a result, the afore-mentioned System 1 becomes the predominant mode of behavior, in which even some of the most important decisions are delegated to a disproportionally fast and impulsive thinking. Indeed, people will blindly rely on short slogans, new titles, repeated messages, which, as explained above, are usually displayed ad-hoc on Facebook news feed. And although they are not always reliable news, System 1 mode of behavior will ultimately stymie people’s motivation, discouraging any further search for the truth.
Biases have been widely discussed by Dan Ariely, professor of behavioral economics at Duke University, in his famous book “Predictably Irrational”. Ariely asserts that consumers are irrational, which he demonstrated through several experiments. One of the experiments consisted of the following setup. A sample of consumers were given a choice between two sorts of pralines; the first (Lindt, $0.26) of a far higher quality than the second (Hershey, $0.1). Under these conditions, most consumers chose Lindt, the price-quality ratio of which was more attractive. However, by decreasing the price of both products by $0.1, thereby making Lindt pralines even more attractive in terms of price and Hershey pralines free, the number of consumers choosing Hershey more than doubled. This predictably irrational behavior can be explained through a feature of the Prospect Theory: the loss aversion. Loss aversion is a cognitive limitation which brings an individual to select the risk/loss free condition, instead of the rationally better choice (see more experiments from Ariely here).
A fundamental question is then: How can we expect individuals to make rational choices in political elections if they do not even act rationally when selecting pralines?
By applying the above experiment in the context of political elections, where a rational and sensible politician promises efficient public services with a fee, while another, less rational, promises free public services, Ariely’s experiment would suggest that the electorate would irrationally go for the second one.
The heart of the problem in political elections, the “Upside Down”, is not only fake news but also laziness, lack of serious and thoughtful reflection, and the tendency of System 1 to supersede System 2.