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.

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.

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.

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.

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).

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:

https://www.nobelprize.org/uploads/2019/10/advanced-economicsciencesprize2019.pdf

Esther Duflo in a TED talk about her research: Social Experiments to Fight Poverty www.ted.com/talks/esther_duflo_social_experiments_to_fight_poverty/transcript

Michael Kremer in a YouTube lecture: The Origin and Evolution of Randomized Experiments in Development www.youtube.com/watch?v=YGL6hPgpmDE

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.

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.