ABSTRACT
Complex modern societies are composed, biologically, of individuals with the same intellectual, practical and creative capabilities as our hunter-gatherer forebears. Policymakers therefore need to be acutely aware of the way our minds work, honed as they are by tens of thousands of years of co-operative living in small bands, surrounded by lethal natural hazards and hostile neighbours. Neglecting this simple fact when formulating economic policy leads to unexpected outcomes, often negating the anticipated benefits. Taking human nature fully into account leads to better results.
Dr Gordon R Clarke
Managing Director, Monetics Pte Ltd, Singapore
Based on a conference presentation at ICBEF, University of Brunei Darussalam
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CONTENTS
introduction: 2
How to determine what is true 2
The dilemma of alternative facts or how can we find the wildebeest? 2
Applying scientific methods to the softer sciences 3
Evolutionary Psychology: How we got to be what we are 4
What are the real drivers of human economic behaviour? 5
Human Action and its Drivers 5
Resourceful, Evaluative, Maximisers 5
Incentive – what’s in it for me ? 6
Altruism – Why I might do you a favour 7
cognitive biases – unconsciously adrift 7
The keys to human behaviour are incentive, altruism and intrinsic morality 9
Why we should base economic policy on evidence rather than opinions 9
Devising effective strategies and policies in a scientific way 10
Individual level 10
Financial literacy 10
Informal microfinance 11
Policies to optimise financial success 11
Institutional level – critical success factors 11
Institutional Level – The Agency Dilemma 12
the case of the sub-prime mortgage crisis 13
the revolution in Wealth Management 13
National level – Economic Policy 14
The Invention of Government 14
A new look at helping the poor 14
The impoverishment of Greece 15
The bizarre case of Brexit 15
Destruction of Correspondent Banking 16
Policy impacts on small companies 16
Building an economic environment that works 17
INTRODUCTION:
Complex modern societies are composed, biologically, of individuals with the same intellectual, practical and creative capabilities as our hunter-gatherer forebears. Policymakers therefore need to be acutely aware of the way our minds work, honed as they are by tens of thousands of years of co-operative living in small bands, chasing prey across the plains, surrounded by lethal natural hazards and hostile neighbours. Neglecting this simple fact when formulating economic policy leads to unexpected outcomes, often negating the anticipated benefits. Taking human nature fully into account leads to better results.
Making policy decision also requires policymakers to understand the facts of the situation they are addressing very clearly. In today’s environment, with the prevalence of instant communication by social media, and the replacement of considered commentary, all too often, by the “sound-bite”, understanding the truth of a situation and the facts that underlie the concerns and complaints of individuals and groups has become more challenging. Although getting at the truth has never been easy, we have better tools today to reach approximations to facts which were inaccessible to our forebears even a few decades ago. We have a good understanding of statistics, for example, and interviewing methods, with extensive experimental research in evolutionary psychology and behavioural economics. However, policymakers are often not aware of either the tools or of the results of relevant research that has already been conducted, and decisions are still frequently made in the dark.
The discipline of evolutionary psychology has made a substantial impact on our understanding of the basic facts of human psychology en masse – how people make decisions in society, and especially how they respond to change, stress and persuasion. Some of these results are surprising, revealing cognitive biases in our unconscious decision-making that confound rationality.
So, for policymakers, the first question is how to ascertain true facts about the problems of society we are trying to address; and secondly, how do we apply our improved knowledge of human nature in order to make better policy decisions which will successfully deliver the solutions we seek. In this paper, we are primarily focussed on economic decision making, so it is economic policy formulation that is in the spotlight.
HOW TO DETERMINE WHAT IS TRUE
THE DILEMMA OF ALTERNATIVE FACTS OR HOW CAN WE FIND THE WILDEBEEST?
To make good decisions about national strategy, business plans or indeed our own everyday lives, we need good information. Unfortunately, the accuracy of much of what we hear cannot be relied upon, and the propagation of “Alternative facts” or denial of well-attested information is a common phenomenon. Notorious examples include (1):
South African view on Aids in 1990s, which held back treatment for many victims
Climate change denial, which flies in the face of well-controlled studies and international consensus
Misleading stories about vaccination risks, which endanger childrens’ lives – and indeed everyone’s lives during a pandemic
Terrorism scare stories – in fact, the threat from terror in eg Europe is no higher than it has been historically
The impact of immigration – it is not well known that the benefits of immigration on national GDP are highly positive in most cases
Countless dangerous rumours and hoaxes on social media.
How can we deal with the huge potential for misinformation – not only via mainstream media and plain word of mouth but also via social media, which is arguably many people’s main source of information ?
It is important to remember that this is not a new problem. There has always been rumour, misinformation and plain lying. We are very experienced as a species in working with imperfect information. When our hunter-gatherer ancestors were chasing the wildebeest herds across the African plains, they were not doing it with perfect knowledge. They could make intuitive judgements from the signs they saw around them based on cultural learning supported by having the necessary mental apparatus. The human brain has been honed by evolutionary change to handle incomplete and inaccurate information. We can harness these abilities in making effective decisions in the modern world – especially financial decisions. Finding ways to make good economic decisions at individual, institutional and national level, is a modern equivalent of cornering the wildebeest.
So how have we learned to harness human intellectual abilities and understand accurately the mechanisms of the world ? Primarily we have learned to use the scientific method – the techniques of observation, deduction and controlled experimentation. We observe, try things and watch what happens. We draw conclusions and try again to see if the conclusions are correct. This is how the “hard sciences” (physics, chemistry etc) progress – by observation, hypothesis, experiment, and falsification (2).
A hypothesis that is not open to falsification, by the potential to discover a counter-example, is not a valid scientific hypothesis. So, for example, Newtons’ Laws of motion work perfectly well on the human scale, but at the scale of sub-atomic particles or on the scale of the universe, they do not. This does not mean Newton’s Laws are not useful, just that beyond our human scale, additional elements must be added to complete the picture. We need the adjustments to Newton’s laws identified in Einstein’s theory of relativity to get a closer approximation to reality – without this, for example, GPS would not work (3).
Hence, scientific knowledge moves forward by successive approximation. Once we have a good working model we can make deductions, harness the knowledge and test further hypotheses.
APPLYING SCIENTIFIC METHODS TO THE SOFTER SCIENCES
It has been the view of practitioners that medicine, sociology and economics are less easily accessible to the scientific method because they involve too many variables to be readily reduced to mechanical hypotheses. Hence, these disciplines have often been addressed on the basis of opinion and authority. Nevertheless, they are open to statistical treatment and to experiment using large number of examples. Since the mid-nineteenth century, therefore, medicine has been put more and more onto a scientific basis, and now scientific medicine is becoming the norm in most developed societies (4).
For the social sciences, progress has been more difficult. However, once the errors of behaviourism were overcome in the mid-20th century (5), scientific advances in the study of human behaviour have been brought about by the discipline of evolutionary psychology, among others (6). Now, the application of evolutionary psychology, and other disciplines analysing human behaviour, has started to put even economics onto a firmer scientific basis (7).
We can identify when something is not scientifically sound in the softer sciences in a similar way to physical science – by observation, hypothesis and testing. The problem is that human beings have a strong tendency to seek cause and effect relationships intuitively, even when they do not exist and when insufficient data is available to make testable predictions. The kind of cause-and-effect relations that are determined by solid science are different from those generated by intuitive “folk wisdom,” although folk wisdom can be very compelling. We can call this the “cause and effect paradox.” Folk wisdom relies for its authority on techniques such as:
Relying on a non-specific source – “everybody knows that … “
Shifting ground when evidence changes or predicted events do not materialise eg predictions of the “end of the world”
Denial of the authority of out-groups (as in climate change or vaccination debates)
Conspiracy theories.
Instead, solid science is based on measurement – quantitative facts gleaned from observation and experiment. Although we should be wary of “Lies, damn lies and statistics,” without good statistics, we can’t protect ourselves from the lies and damn lies. This is especially true when gathering measurements in the social sciences, but now we can claim to have confidence in proven methods; we have learned to apply the scientific method in the humanities, as in evolutionary psychology, as well as physics. Thus, applying scientific methods to the study of human behaviour has revealed much about human nature that we did not know, say, 30 years ago (8).
EVOLUTIONARY PSYCHOLOGY: HOW WE GOT TO BE WHAT WE ARE
Evolutionary theory can aid our understanding not only of the human body, but also of the human mind. Careful research has shown that human beings and societies are remarkably similar in behaviour everywhere. The evolutionary reason behind this may be that we have a very narrow gene pool due to a population bottleneck (c70000 BCE), caused by the “supervolcano” eruption of Mt Toba in Indonesia. Some researchers believe that this event reduced human populations drastically to a small number of isolated groups. As a result, between any two humans, the amount of genetic variation is about 0.1 percent; most of the great apes show twice as much diversity (9)
Genes drive behavioural as well as physical characteristics because behaviour is driven by brain processes. Although the human brain is probably the most complex thing in the known universe, it is built from instructions in our DNA. Our bodies and brains evolved in a very tough hunter-gatherer environment and there has not been enough time for much genetic evolution to take place since the Ice Ages ended and urban civilisation as we know it began around 7000 years ago. We are mentally equipped with much the same tool kits as our ancestors from the distant past.
However, even with the same basic mechanisms, our behaviour is so adaptable that cultural evolution has diversified our societies, with gene-culture co-evolution (10): Consider MasterChef – the kitchen and its utensils are the same, but we can cook anything at all given the right ingredients.
Since we all possess the same mental apparatus, certain common behavioural traits exist universally. Policy-making must take this into account or it will fail. But what are the characteristics of our common ways of thinking that present a challenge to policy makers ? The “universals” found by research in evolutionary psychology include some rather obvious points, but the science has enabled their power and effect to be more closely understood. For example:
Human beings and societies thrive on interaction and gossip – hence the advent of faster communications, including the explosive growth of social media, affects deeply how we function – we love information! And we process and interpret it largely unconsciously. When events do not fit our beliefs or wishes we readily embrace conspiracy theories to ‘backfit’ undesirable data to our preferred version of events or narrative (11).
This can cause trouble when combined with another universal – that we have limited trust in Institutions. The most trusted institutions are not always the most knowledgeable but those that are perceived to have the subjects’ interest at heart (like friends and family) (12). Hence, for example, conspiracy theories propagate because denial by untrusted authorities only serves to increase the plausibility –” well they would say that wouldn’t they.” Authorities therefore risk reinforcing a false belief by denying it. (e.g. the truth of the moon landing, the death of Elvis, the disappearance of MH 370, the value of mask-wearing in a pandemic).
Friends and family can reinforce conspiracy theories, sometimes to comfort a person in distress. If the news being given by the authorities is unpalatable, then we may seek a more desirable narrative. We often opt for beauty rather than truth.
This happens because of built-in human cognitive biases that have developed as evolutionary survival tools (13). A cognitive bias is any phenomenon that causes us to react rapidly to a situation in a way that is not fully rational in an objective sense. Falling in love is an obvious one ! This is not at all rational, but if we did not do it, our reproductive success as a species would be undermined. Hence it is an evolutionary mechanism with survival value.
Understanding cognitive biases helps us to anticipate reactions and hence to apply a factual approach to economics and financial behaviour. So, the next step is to explore how cognitive biases affect our economic decision-making. If policymakers take cognitive biases into account, there will be less unexpected outcomes from economic policy decisions.
WHAT ARE THE REAL DRIVERS OF HUMAN ECONOMIC BEHAVIOUR?
HUMAN ACTION AND ITS DRIVERS
We can determine facts in social science and economics using the same methods as the hard sciences, but looking at statistical results rather than individual experiments, as in scientific medicine. Until recently this was not readily possible because of limited evidence, ineffective methods, lack of analytical computer power and too much emphasis on traditional ideas with no factual basis – a bit like 19th century medicine.
What about economics ? Economics is about the aggregate of human actions (14). Every small decision that we make has an impact on the economics of our societies and the world. If we decide to buy a can of beans in Cape Town, that could lead to a chain of effects which might culminate in the opening of a new steel plant in China.
Traditionally, economic theorists have made various assumptions, without experimental proof, about human economic behaviour being driven by:
Perfect rationality
Perfect information
Logical, conscious decision-making.
But, in the light of evolutionary psychology, these ideas are clearly misleading – the results of both biological evolution and cultural evolution do not bring about those attributes. People are indeed smart and rational, but far from perfectly and not in a mechanical sense. From birth, we can be described as Resourceful, Evaluative, Maximisers (REM) (15), and thus able to apply unconscious reason to our behaviour, but we can make big mistakes when making consumer and financial decisions because our behaviour is driven by evolutionary factors, honed while chasing the wildebeest, as well as conscious, rational decision-making.
RESOURCEFUL, EVALUATIVE, MAXIMISERS
So, people are smart and rational, but far from perfectly so (16). We are influenced by mood, emotions, chemical compounds, and the environment as well as our genes. Decisions are influenced by the continuously changing chemistry of our body and brain and our external environment. And we respond to specific benefits that we perceive as valuable to us – incentives – which affect our behaviour and decisions, including consumer and financial decisions.
Our economic decision making therefore, is rationality mixed with personality, emotional behaviour and our sensitivity to incentives. All these factors impact decision-making. Hence as individuals, we need to understand our personal predispositions in order to refine our financial decision making. This implies that behavioural education as well as information about financial matters is needed to help us make better financial decisions. We need help to develop the ability to understand and deal with our own financial (and potentially other) behaviour, to minimize its periodic destructiveness.
It may well be true that hard work, frugality, education, and smart investing are primary sources of wealth, and they are routinely listed as such in surveys of wealthy people. However, the key is the smart part, and that is about understanding our own behavioural drivers and managing them well.
So, on the one hand, we have rational skills – positive traits such as responding to incentives that motivate us to behave in an effective way to achieve goals, for example financial goals. Here is a list derived from Zytek et al (private communication):
We are economic optimists (entrepreneurs especially (16))
We use mental accounting – we aim to maximise our resources and dislike losing money. People will always try to minimise costs unless they are using expenditure to impress
People differ across cultures and between individuals, but not unpredictably – we have different genetics (within a limited range) and different environments.
Personality type drives many traits such as attitudes towards money and desire for financial security; attitudes towards ambiguity; time preference (pleasure now versus more pleasure later if we wait); life stage differences
On the other hand, we suffer from cognitive biases (17), for example we routinely underestimate big risks in the modern world (eg car accidents, economic crises and pandemics) and overestimate ones that are extremely unlikely to have a personal effect (eg terrorism, murder, snakes). Furthermore, our mental procedures, which evolved in the hunter-gatherer world, routinely fail when we are handling large amounts of technical information, so we make simple computational errors.
Overlaying this is intrinsic morality (18) – notably “reciprocal altruism” – put simply, ‘I will do something for you now in the (often unconscious) expectation that you will do something for me in the future’. This phenomenon is a powerful incentive in human interactions including financial ones; and the related sense of fairness and justice.
So, can we fairly be described as “rational human beings” ? Whether we are policy-makers or the objects of policy, our decisions are driven by both rational decision-making based on conscious analysis and intuitive responses based on evolutionary predispositions – both genetic and cultural. Thus, formulating successful policies must take into account not only the rational responses that people will have to a change or stress, but also their intuitive reactions. The intuitive reactions are extremely forceful in circumstances where we feel threatened, or we see an opportunity. The calculations are subconscious, highly complex, and largely inaccessible to conscious processing other than through our subjective feelings – “qualia”(19). However, they are to a considerable extent predictable once we take evolutionary psychology into account.
Our behaviour is highly sensitive to fundamental evolutionary incentives – survival and reproduction; which in our world translate into security, wealth, family success and other quality of life factors. Much of our subconscious processing is about interactions and relationships with other humans, driven by factors such as altruism, among others. Furthermore, our subconscious processing is biased in certain ways due to its origins in human evolution. We were engineered by successful survival and reproduction in a hunter-gatherer environment, not to handle complex modern choices while beset with massive information overload.
To understand the way in which these factors influence our decision-making, let’s look further at incentive, altruism and cognitive biases
INCENTIVE – WHAT’S IN IT FOR ME ?
People want to be able to maximize their control of resources because controlling resources gives us a better chance in the battle for survival and reproduction. The development of this skill is evolutionarily based and emerges in the way we assess value – gain versus loss – and how this is affected by time horizons. Here we face the observation that the value of having something today versus having more tomorrow is much higher than traditional economic models would predict. Most people value a good thing today to be very much better than a potentially better thing at some time in the future. This is why it is much more difficult to persuade people to save than traditional economic theory would have us believe. Economists call this ‘hyperbolic discounting’.
A powerful tool to assess our response to incentives emerged in the application of game theory (20) to evolutionary biology (21). Through studies in this area, we have been able to formulate a biological basis for altruism – how fitness of the group may be improved even at a cost to the individual, whereas evolutionary advantages normally accrue at the individual level.
This leads on to the idea of Evolutionarily Stable Strategies, explaining why species (including humans) behave as they do in everyday trading/conflict situations, especially decision making under uncertainty (22). Hence our reactions to the prospect of gain or loss – our response to positive and negative incentives – can be understood, and to some extent predicted, at least on a statistical basis.
Incentives are not mysterious and understanding them should enable policymakers to predict whether a strategy will succeed or not – in the long and short term.
ALTRUISM – WHY I MIGHT DO YOU A FAVOUR
Natural selection acts at the individual level on survival and reproductive success, so how come animals, including humans, are altruistic some of the time ? In fact, altruism has a basis in the genes via natural selection through two distinct mechanisms:
Kin altruism – sacrificing your own interests for those individuals who share many of your genes can result in that behaviour being passed on through their success, even if you die in the attempt to save them (23).
Reciprocal altruism (see above) – helping an unrelated individual on the expectation that they will help you back at some later stage. Reciprocal altruism drives human behaviour in societies but is mainly subconscious; you see it also in primate groups, dog packs and elephant herds among others.
Modern “global” society “expands the circle” of reciprocity and tends to increase the range of reciprocal altruism – we seem to be getting nicer to each other, and to other species (24). We also have many devices to make reciprocal altruism work smoothly – for example the institution of “promising”. Similarly, money can be regarded as a cultural device to make reciprocal altruism work more effectively in large groups where the honesty of other parties is unknown – hence economists John Moore and Nobuhiro Kiyotaki’s delightful suggestion that “Evil is the root of all money” (25).
However, one man’s reciprocal altruism is another man’s corruption. In small societies such as the level of the village, where unrelated individuals must live together in mutual collaboration, the idea of trading favours is an important feature of everyday life. However, when that idea expands into the word of modern states, it becomes labelled as corruption. Nothing is cut and dried in human interactions, and we must understand the evolutionary basis of the mechanisms before we attempt to legislate away certain behaviour.
Similarly, it is now becoming clear from a wide range of archaeological and anthropological studies that hunter-gather life was pretty violent – mainly as regards relations between different groups (26), especially those with different languages. Feuds would break out regularly, leading in some cases to a perpetual state of war between neighbouring human bands. An example would be the head-hunters of Borneo, who became locked into a cycle of inter-group violence, which could not be broken until external parties imposed the rule of law (27). Thus, modern societies institutionalize alliances and vendettas – I don’t have to beat up my neighbour for damaging my car or moving his fence into my land, the law does it for me.
COGNITIVE BIASES – UNCONSCIOUSLY ADRIFT
The inventory of human cognitive biases is large. Over 100 have been documented and many can affect the effectiveness of policy decisions, as well as the formulation of policy. Some of the more important ones are listed here (some we have already mentioned in passing):
Risk assessment – human beings routinely assess risk incorrectly and can become very frightened about extremely low risk possibilities (such as terrorist attacks), while being casual about serious and immediate risks (such as road accidents).
Assessment of value – we assess potential losses as having far more impact on decision making than potential gains, and the time-value of reward is for most people heavily biased towards the present (hyperbolic discounting, as mentioned above).
Availability bias – we tend to call to mind events and anecdotes we heard recently and discount the value of more substantial information we have heard in the past. People estimate the likelihood of a (usually bad) event or the frequency of (scary) instances by the ease with which they come to mind. This is the bias that helps to sell newspapers when bad things happen.
Confirmation bias – perceptions of cause and effect create Illusory correlations; once an incorrect hypothesis gets established in our thinking, we discount contrary evidence and build up faith in the hypothesis by readily taking on board confirmatory evidence.
Cognitive dissonance and biased assimilation effect – wrong beliefs are not easily debunked; this is related to confirmation bias but also to the fact that we create a narrative about people and events and anything that does not fit with the narrative gets ignored.
Illusion of external agency – we are very quick to assume that someone or something is responsible for events that happen, very often due to natural causes. This is the basis of many hard-to-shift superstitions like belief in ghosts.
Insensitivity to sample size – anecdote effect. We are inclined to accept very limited evidence that supports our prejudices rather than seeking a larger number of examples and counter-examples in order to establish a broader view of what is true.
Vulnerability to persuasion – can you lie and still be trusted ? Certain charismatic individuals can be caught telling untruths and half-truths or even committing crimes and yet their followers still believe that they will deliver their promises .
Illusion of control – we tend to over-analyse and over-control. We take small amounts of information and use this to determine a control strategy. This is related to false correlations and is often applied to avoiding diseases – don’t sit in a draught, don’t go out without your hat on. These may be good pieces of advice, but do not automatically determine whether or not you will get sick.
Ambiguity effect – some people are much more comfortable with holding contradictory views at the same time than others. Similarly, some are capable of handling the surprises and unmanageable events of life in a far more sanguine way than others.
Bandwagon effect – and false memory. People will follow the opinions of the herd and will invent, quite unconsciously, a rationale for doing so which they fully believe.
Authority biases – false consensus effect; “it’s on Facebook, it must be true.” This also applies to systems delusions which appear when a group of people, such as senior managers, discuss matters only among themselves and do not seek sufficient facts from outside. Illusory conclusions commonly arise .
Outgroup homogeneity bias – “All x’s are the same” – a form of trait ascription bias. We tend strongly to ascribe the attributes of one member of a class to the whole class. This has a serious impact on, for example, the immigration debate.
It is only in very recent years that the way our brains work in assessing information and making decisions has been understood as driven by evolutionarily developed strategies, which may have been (indeed must have been) good for survival in our ancient past but cause incorrect logic in todays’ context. This becomes a serious problem when we talk about the logic that affect societies as well as individuals. Until these biases were properly studied, it was hard to make progress in any kind of scientific sociology.
The influence of post-modernism on sociology in the second half of the 20th Century, especially structuralism – the view that there is little or no objective reality so that much of our perception is socially generated – revealed that much of the way we think is driven by tacit knowledge, which can indeed be biased by upbringing and especially peer pressure and how the brain sees the world. However, the loss of faith in objective reality has held back sociology enormously and the discipline has only recently been able to shrug off these misperceptions and return to a scientifically tenable track.
In short, the general appreciation that behaviour is strongly driven by our evolutionary nature – chasing the wildebeest; impressing potential mates – has won through, and enabled progress to be made in understanding the complex web of tacit knowledge, biases and capabilities that enable the brain to act as a thinking mechanism (28).
Cognitive biases are important because powerful individuals can exploit them to persuade people to behave in certain ways (29). For example:
Rhetoric – link of two unrelated concepts – the “wicked step-mother” effect; for example, Trump’s “wicked Hilary” and “fake media” statements; narratives about risks of Covid vaccines tied to world domination conspiracy theories.
Media – good TV is persuasive; confirmation bias in newspapers; for example, UK polarisation re Brexit – each side becomes entrenched and ignores counter-arguments.
Hypnosis – inputs produce outputs; by careful use of language and environment, the human mind can be made to operate like a machine.
Charismatic individuals – the Big Man effect: powerful speakers and people with particular personality types have the ability to engender a following with seemingly little effort.
Good persuaders understand how human psychology works – at an individual, group and institutional level – for example, Steve Jobs had a great grasp of how people respond to certain incentives regarding fashion and design. Hence, Apple owes much of its success to Jobs’ understanding that the way a product makes users feel beats most other factors, even price. This phenomenon is behind the success of a lot of designer brands.
On the downside, however, good manipulators who understand psychology can lie and get away with it – but they are still trusted.
The reluctant conclusion is that conscious reason is not the driver of behaviour, including voting behaviour and consumer choices, about finance as well as other topics. Furthermore, reason has a longer time frame than intuitive judgements (30). Hence, we are persuaded now that head-hunting is not a good idea but if you lived in Sarawak in the 18th Century it would have been hard to see an alternative. Only pressure imposed from outside brought the cycle of violence to an end.
However, reason used in specific ways can overcome cognitive biases (31). Moral arguments – certain moral intuitions about right and wrong – can have strength and this is based on hard-wired reciprocal altruism.
THE KEYS TO HUMAN BEHAVIOUR ARE INCENTIVE, ALTRUISM AND INTRINSIC MORALITY
Studies in neuroscience demonstrate that people’s choices are the result of interactions between cognitive and affective systems – both consciously controlled and automatic processes (32). Much of our behaviour is influenced by the calculations of the unconscious mind as well as conscious decision-making.
Game theory helps us to understand the incentives that drive motivation, how we collaborate altruistically and can also reveal that our intrinsic sense of justice, although distorted at times, is an important determinant of behaviour under stress.
“Intuitive morality” and fairness is demonstrated by experiments such as the “Ultimatum Game” and the “Dictator Game“ (33). This strongly suggests that humans are not the ultimately “rational” animals that economics traditionally assumes but allow the concept of fairness to influence their behaviour.
It is therefore vital for politicians and business leaders to understand when and if they have started to play the ultimatum game. In 2016, British PM David Cameron, for example, inadvertently started playing the ultimatum game when he called the public vote on Brexit. He asked the public to endorse membership of the EU when it seemed to many that the EU favoured a small, privileged minority of bankers and service industries in London, but had disadvantaged many in other sectors (small manufacturers, unskilled workers) who found housing increasingly unaffordable and were finding wages under pressure from cheaper immigrants in certain sectors. The result was that when given the ultimatum of ‘approve the unequal wealth and income situation that favours the minority, or lose it all’, many people in the UK voted to lose it all, as they felt they had less to lose than the elite. This is why the shortage of facts on the Leave side did not undermine their case.
WHY WE SHOULD BASE ECONOMIC POLICY ON EVIDENCE RATHER THAN OPINIONS
You might think it would be self-evident that policy decisions should be based on facts, but many examples of failed interventions by government in economics reveal that wild optimism, ideology and persuasion drive economic policies more than facts do (34). The policy failures are of two kinds and often both are evident:
Policy formulation: Policies based on opinions, ideology or hunches rather than solid research about how people actually behave, of which vast amounts are available.
Policy results: The way in which human beings actually respond to pressure and change, rather than how policymakers wish them to, have a profound effect on the success or failure of economic policy.
Economists have tended to assume that human beings act rationally in making political and economic decisions, but evolutionary psychology shows this is often not the case – it is emotional and subconscious reactions that often shape behaviour. This explains why many government interventions in economic/business matters fail and/or have dramatic unexpected consequences, especially when they stray beyond government’s role as a referee and vital infrastructure provider. This applies particularly to economic policies that interfere with the price mechanism. These will distort the metrics of real demand and create behaviours that arbitrage the result .
An example is consumer behaviour in the Eurozone in the face of negative interest rates. Spending contracted with the fall in interest rates and companies and individuals deleveraged rather than increasing borrowing. Perceptions of future wealth and income prospects outweighed cheaper interest rates (35).
The lesson is that Policies fail because they do not take human nature into account, so miss the importance of incentives, altruism and cognitive biases, including the opportunism of criminals (and ordinary folk).
DEVISING EFFECTIVE STRATEGIES AND POLICIES IN A SCIENTIFIC WAY
To illustrate the challenges and then propose some ways in which the acquisition and deployment of experimental facts can direct policy in constructive ways, we will consider examples at three levels
individual
institutional, and
national or global
INDIVIDUAL LEVEL
FINANCIAL LITERACY
Understanding how national policies can help improve financial literacy requires a thorough understanding of the challenges individual human beings face in making financial decisions. For much of this section I am indebted to research conducted by Roman Zytek and colleagues at the Brunei Darussalam Ministry of Finance (16). To set the scene, it is salutary to consider a quote from the MIT Economist Dan Ariely: “We are not cool calculators of self-interest who sometimes go crazy; we’re crazies who are, under special circumstances, sometimes rational” (36).
This is the very reverse of conventional economic theory regarding how human beings make financial decisions, especially as increased availability of discretionary income exposes more people to the need to make them. Financial literacy assessments tend to overlook the behavioural determinants of individual financial knowledge and success, and their impact on financial decisions. What we must recognise in determining policy is that reason alone does not drive behaviour. People may know it’s good to save but that will not make them do it. Hence schemes such as eg Singapore’s Central Provident Fund (CPF) have positive results because they are effectively mandatory, but the savings belong to the individuals not to the government, so they are less open to abuse than conventional social security taxation.
Governments are very keen to help their people become better at making these crucial decisions for their future because it reduces costs, but government interventions to address specific problems in other spheres can impose large, long-term financial and social costs that retard economic growth and social development (37). To avoid these traps, policymakers must draw on the vast research now available in economics, finance, neuroscience, behavioural economics, psychology, sociology, medical sciences, education, etc. to understand human financial decision making and develop sound measures to help people to improve their financial behaviour.
INFORMAL MICROFINANCE
Governments are very concerned about the availability and management of credit. However, most of the attention goes on the formal side of credit, which in many countries is not where the action is as far as the majority of the rural and urban poor are concerned. In many countries, especially in Asia, informal credit co-operatives abound and do an effective job of keeping the economy moving at the grass roots (38).
In Thailand for example, it is common for a group of people enter into an informal arrangement to pay into a fund, which is made available to any of the members to borrow according to certain rules. If you borrow you pay interest, and if you don’t, the interest others pay reduces the amount you pay in. The scheme provides a mechanism both for saving and getting micro-credit (say a few hundred up to a few thousand dollars). The scheme is administered by an individual, who takes the risk of a member defaulting and gains the cash flow advantage of holding the funds. Anyone who fails to pay back a loan would be effectively ostracised, and in Thai society that is a very strong incentive not to default.
There are no government rules about these arrangements, and the people involved base their involvement on a set of conventions that everyone knows. In effect, people arrange microfinance and savings among themselves with no bank, microfinance institution or government involvement. Interest rates, at around 30%pa are higher than a microfinance institution might ask(10-12%pa), but not as high as individual informal lenders (50%pa) or a loan shark (150%pa).
The unregulated, informal nature of these arrangements, based on intuitive morality among a group of people known to each other and the inter-personal incentives, are an effective control on risk. Any outside control would likely be counterproductive. The lesson for policymakers is don’t try to overcontrol informal systems that work.
POLICIES TO OPTIMISE FINANCIAL SUCCESS
Government policies play a large role in our financial well-being, but setting up the right environment for financial success is more valuable than micro-management of economic variables. So, for example, Governments should pursue policies that promote good general education, focussed on problem solving not just rote learning, including financial matters, from an early age. However, for such education to be effective, economic policies must encourage competitive markets and preserve social and economic incentives for value-creating entrepreneurship, saving and investment, including in human capital. Policies should not create incentives for the types of entrepreneurship that redistribute or destroy value. Likewise, they should avoid encouraging moral hazard – creating opportunities for people to abuse the system just because they can. As human beings, we will take advantage when we are aware that the government is willing to redistribute, bail us out or equalize outcomes across the population.
Hence, to maximise economic benefits from improvement in financial literacy, policies need to support savings and investment, including investment in human capital, as well as productive entrepreneurship and innovation (39). There is simply no viable alternative to good macro- and micro-economic policies and regulations that ensure stable and low inflation, and therefore preserve the value of money. In this way, governments can help individuals manage their money and entrepreneurs make the best use of the larger pool of savings. Government can also help by not attempting to regulate informal arrangements which people manage naturally via the mechanism of reciprocal altruism and intuitive morality.
INSTITUTIONAL LEVEL – CRITICAL SUCCESS FACTORS
Institutions, including those in the financial sector, succeed and fail because of the survival needs of organisations in a competitive environment. These factors include:
Quality of ideas
understanding customer needs and how they evolve – how customers compare institutions governs their success eg Apple
Understanding the impact of technology and how technology will change
Quality of leadership
Human capital and especially management capital
Managing productivity and costs
Quality of the regulatory environment
Effectiveness of regulations as a means of limiting both cheating and the cost of compliance.
The survival characteristics of organisations are those that enable them to be profitable, innovative and hence sustainable. Institutions behave differently from individuals because their survival characteristics, and hence incentives, are different. Primarily, commercial organisations will focus on profit and little else. It is profitability that drives the preparedness of shareholders to invest and hence to keep the business viable long-term. Unfortunately, being realistic rather than cynical, focuses on customers and staff benefits are there only because they are profitable.
Now, this profit-focus of businesses is key to the effectiveness of regulatory policies. If policymakers do not think carefully about this, they will suffer from the law of unintended consequences. This is why, for example:
Interest rate policy rarely achieves the expected results because banks will act to avoid loss of profit and so will not lend at all if the lending is too risky or not profitable enough.
Small businesses do not conform to regulatory threats – the risk of getting caught out may well be perceived as less than the cost of compliance (eg compliance with Data Protection Rules).
Businesses regard incentives similarly to the way in which individuals regard subsidies – hyperbolic discounting. Businesses have a short-term view of costs; individuals have a short-term view of benefits. Hence, businesses will not bother to claim government incentives that involve any short-term effort.
Policymakers need to ask themselves how businesses react to change and stress just as they do for individuals. For example, it is instructive to think through whether companies/groups are more rational than individuals ? Are very small businesses (eg MSME’s) different from large businesses in this respect ? What about publicly listed companies versus privately held companies ?
The key factor is that if it is in their interests to do so, people and institutions will get around laws even when they don’t plan to break them – there can still be massive, unexpected consequences. As a result, statistical measures that appeared to be sound and useful suddenly lose their value as metrics. This is enshrined in the saying of Bank of England economist Charles Goodhart: Goodhart’s Law – “any financial variable used for control will become meaningless.”
INSTITUTIONAL LEVEL – THE AGENCY DILEMMA
As an example of institutional behaviour that illustrates the problem, many institutions, the financial sector being no exception, make bad mistakes when using agents to carry out some aspects of their services. This problem is known as the Agency dilemma. Examples include Lehman Brothers’ management not knowing what their teams of traders were actually doing; many otherwise savvy individuals allowing people like Bernie Madoff to manage their money; the ignorance of Barings’ management to the activities of rogue trader Nick Leeson. To prevent these problems, you have to understand motivation. Incentives are different for the agents doing the trading or investing and for those who are effectively the investors. There will always be a crisis in the long run when you are trading with other people’s money.
This problem extends to the situation in modern banking, especially in large multi-functional institutions where the management and operational staff are not generally shareholders, and so do not have an interest in the long-term financial success of the company. Hence, the ongoing scandal of Western banks failing to distinguish between trading on the instructions of customers (eg hedging positions) and trading on their own account using customers’ money. When management and staff are driven only by their short-term bonuses or promotion prospects, a financial firm is in peril, let alone its customers.
THE CASE OF THE SUB-PRIME MORTGAGE CRISIS
The Global Financial Crisis of 2008-9 is a classic case of institutional behaviour getting out of the control of the regulators, because certain regulators did not understand what was happening and were too invested in the system to stop the rot.
Leading up to the 2008 crisis, loan-originating institutions set up sub-prime mortgages via brokers and then commoditised the loan and risk and sold it to investors, so that they had no further responsibility for outcomes. The institutions who bought the debt repackaged it into complex and opaque instruments – why? Because financial institutions are motivated by profit above other considerations (40).
This is a classic example of the Agency Dilemma, but also illustrates other common cognitive errors:
Vulnerability to persuasion:
Poor borrowers inveigled into debt by unscrupulous salespeople.
Institutional investors fooled by negligent rating agencies into believing that they were buying cast-iron instruments that were in fact junk.
Authority biases – false consensus effect; systems delusions:
Trust in the rating agencies, who in fact did not understand what they were rating (40). It was not the end users who were paying fees to the rating agencies in order to get ratings that related to their interests; the issuing entities were, so the ratings followed the issuers’ interests – this is still the case.
Reputation of the originating and repackaging institutions, which at the inception of the crisis were still cast-iron.
Internal belief among regulators and participants that the financial system was working well (41).
Many the risks could have been foreseen if policy makers had been more aware of the motivations and objectives of financial institutions and rating assessors. Increased regulation of the financial sector has not addressed the agency dilemma in this respect, and many of the same abuses could happen again if investors and management of financial institutions fail to learn by their mistakes.
THE REVOLUTION IN WEALTH MANAGEMENT
The impact of regulation re “tax havens” has changed the way in which ultra-high net worth and high net worth individuals behave but has also affected a much larger market of savers and investors, with unintended consequences (42):
Grey-market activities have grown: Low-profile service providers willing to take the risk of gaming the system have become more successful.
Shadow Banking: Transaction platforms, financial instruments and other arrangements designed to circumvent regulatory straitjackets, by-passing conventional banking institutions and financial services providers have emerged.
Digital currencies Some believe that Bitcoin and similar instruments will evolve into parallel monetary systems, despite their volatility and high cost. Their anonymity, although limited in practice, can permit large scale abuse and money laundering.
Semi-covert inter-jurisdictional tax competition – despite agreements to the contrary, individual countries will seek to entice the wealthy with:
Lax application of rules;
Self-serving interpretations of the “substance over form” principle;
Disparity between headline tax rates and actual tax imposed (hidden abatements and exemptions).
Again, Resourceful, Evaluative, Maximisers will find a way to overturn the intentions of the regulators when policy consequences are not properly thought through.
NATIONAL LEVEL – ECONOMIC POLICY
THE INVENTION OF GOVERNMENT
To understand how policy formulation tends to lose touch with human behavioural characteristics, it is instructive to review how process of governance in society evolved. Basically, ancient societies did not need a lot of management, but as human societies transitioned from hunter-gatherer to herder and settled agricultural communities, groups started to accumulate surpluses that had to be safeguarded – grain, livestock, and to require the management of vital resources such as water (43). This led to the emergence of a ruling class, and although rulers may have started out as protectors of society, some, gradually or by force, asserted ownership and control over mutual assets – resulting in extractive institutions.
Extractive governments promulgate the myth that people need to be organised or controlled for the good of society. In fact, like the immune system or an ant colony, human societies are self-adapting complex systems and do not need to be over-managed (44). This is why most European empires failed in the industrial age, suppressing industry because middle-class wealth would make countries harder to govern. The influence of an individual ruler has a profound effect. Compare, for example, the rulers of Zimbabwe vs those of Botswana in and after the colonial period, which have led to closed versus open societies and the obvious consequences in terms of economic success (45).
Excessive bureaucracy is rife in extractive economies and is both a cause and result of corruption. Corruption arises for two reasons – at high level (rent-seeking extraction of the value of production by the powerful); at a low level (the need to cut corners on byzantine paperwork). Hence, no matter what type of government, reduction in bureaucracy and encouragement of open economic institutions will enable innovation, effective education and wealth creation to flourish (46). All human societies have the capability because they consist of remarkably similar human beings.
We have the necessary genetic make-up, intrinsic skills and mix of personality to run successful large-scale societies – government can help it blossom by enabling an open, fair and just economic environment.
A NEW LOOK AT HELPING THE POOR
When we study the results of overseas aid since the second world war, a sorry picture emerges, especially cross sub-Saharan Africa. The failure of the aid programmes to generate successful development are an object lesson in misunderstanding at the international government level of the way human behaviour works. In short, conventional government to government lending and direct aid at government level causes corruption, loss of incentive and disruption to markets (47).
Market-driven forms of capital raising – trade, the bond markets, bank lending, microfinance – are far more effective than aid in supporting economic development, as has been demonstrated in many other parts of the world including Asia.
Microfinance institutions have been seen as a panacea for development, working at the grass roots level, but the circumstances have to be just right to make this successful (48). Microfinance institutions that just capitalise on informal microfinance that exists on most Asian countries may not be adding much value and indeed we can ask whether the institutionalisation helps or hinders. This needs to be studied objectively. Similarly, one-off loans or crowdfunding may give a kick start but does not provide the long-term skills to make an enterprise successful.
Successful development emerges not from aid or lending alone but from managerial capital – people who can make an enterprise successful. There are fewer of these than is often assumed. Not every beneficiary of a microfinance loan or a crowdfunding grant wants to be a long-term entrepreneur, or indeed is capable of being one. In any kind of financing, support for enterprise must be long term, must involve a visionary and obsessive entrepreneur and must be integral to the enterprise. This is because human abilities vary and human reactions to financial injections vary too – a blanket approach will always have more failures than successes. There are few who can pick up the ball and run with it all the way to the goal.
THE IMPOVERISHMENT OF GREECE
Greece, a country in which I have lived on and off for many years, has a colourful political and economic history, with at least seven major crises since the inception of the modern Greek state in the 1820s. The country has suffered from decades of extractive government and corrupt economic institutions (49). The handling of the 2010 financial crisis in Greece, set off by the failures of Western financial institutions, led to a crisis for the whole Eurozone and is another object lesson for policymakers about how human behaviour reacts to pressure.
Before the 2008 crisis, Greece was in a strong phase of economic growth. The crisis began as the extent of misreporting by previous governments, lack of transparency and shocking governance emerged in 2008-9 (49 chapter 6) with the immediate result that Greek government bond spreads rose from 35bps to over 1000. The solutions imposed by the international community were conventional – bail-out, austerity. This, inevitably, drove the economy into a steep decline from which it is still slowly recovering. The international community seemed surprised by these results, but they were completely predictable when you think about human behaviour under change and stress. How did people react?
Vicious spiral – reduction in spending, causing closure of businesses, resulting in much emigration; people always try to optimise their financial position.
General strikes – clearly worthless as there is no option for change but they will punish a government that is seen as unfair or cheating the public.
35% increase in suicide rates – there is a point beyond which the human psyche cannot cope.
Innovative informal solutions – barter; people organise themselves when government fails them.
The IMF is recognising that meeting the Greek (or any sovereign-debt) crisis by piling on more interest-bearing debt has been counter-productive (50), whereas a participative shared equity approach would incentivise the lenders to promote economic growth in the loan recipient rather than austerity driven stagnation.
THE BIZARRE CASE OF BREXIT
Looked at from the point of view of economics, the UK decision to leave the European Union is probably one of the worst errors ever committed by a democratic government. The negative effects are not remotely surprising to anyone who understands the first thing about business and economics in the modern world. The results were starting to bite even two or more years away from the actual exit (51).
5 years on from the decision, 2 years after the exit and 1 year after the ‘transition period’, the outcome is dramatically bad. Shortages of goods and medicines; shortages of staff – truck drivers, nurses and midwives, hotel and leisure staff, agricultural workers; loss of trade and reduced GDP; the intractable problem of the Irish border; fishing disputes; and the potential break-up of the United Kingdom as Scotland plans to secede.
Richard Hughes, the chairman of the Office for Budget Responsibility, has explained to journalists that the negative impact on GDP caused by Brexit is likely to be twice as great as that of the pandemic (52). Hence, it is clear, from the government’s own figures, that the drop in trade and GDP has been primarily caused by Brexit. A recent poll indicates that 44% of voters now think Brexit is harming the economy as opposed to 25% that think it has a good effect. 53% believe shop prices have risen because of Brexit, whereas only 13% think there has been beneficial effect on prices (53). Inflation is now forecast to be 4% in 2020.
The present grim situation follows from a profoundly flawed referendum fuelled by misinformation (and foreign interference via social media, we now realise) on one side and failure to grasp intuitive morality on the other – that the incumbent government will always be kicked when people have the chance. The referendum excluded on arbitrary grounds, by the way, between 800,000 and 1 million expatriate British voters – many of those with the most direct interest in the outcome.
The referendum result was down to the predictable irrationality of human beings individually and en masse. It beautifully illustrates several of the key cognitive biases that arise from our evolutionary past:
Assimilation of traits to out groups – fuelling the debate on immigration
Behavioural manipulation using information bias via social media
Confirmation bias on all sides
Taking the opportunity to attack the incumbent leadership’s policies
Preparedness to suffer in order to punish leadership perceived as ineffective
This should not have been surprising, and if the right specialists had been consulted in advance was entirely predictable. Research in evolutionary psychology suggests that populism will gain ground when governments lose touch with their support base and begin to focus on their re-election as an end in itself – they become extractive. Intuitive morality affects economic outcomes – people will punish unfairness even at great cost to themselves. This is why the UK vote on the EU was lost, even though Remain had vastly better rational arguments: incumbent government was being punished.
DESTRUCTION OF CORRESPONDENT BANKING
Here we see an example of the Law of Unexpected Consequences at a global level. After the 2008 financial crisis, regulators, especially in the US, have come down heavily on any apparent misdemeanours of major banks, eg compliance to AML/CFT standards. Banks have reacted to minimise the impact of the negative incentives, passing on costs to the customers and withdrawing correspondent banking relationships for many banks in developing countries.
When your key incentive is optimisation of profit, this result is predictable, and policy-makers should have recognised this. Furthermore, the provision of banking services for small businesses in developing countries has also been hit, as global banks attempt to apply mainly US-driven rules to all customers, regardless, in an attempt to avoid further punishment by authorities (54).
Hence, in an attempt to secure the banking system, regulators have damaged the trade of poor countries.
POLICY IMPACTS ON SMALL COMPANIES
Many countries try to encourage small businesses, but there are differing types of small business all with a sound rationale for existence, which require different handling; at a simplified level, there may be:
Small businesses that are founded with the intention of growth, such as a Fintech start–up or retail chain.
Small businesses which are intended to be purely a vehicle for small-scale operations – such as a local mini-market, a farmer, a plumber or a ferryboat operator.
The key issue here is the personality of the proprietor:
In the first case, the owner(s) is a true entrepreneur, and is looking at long term development of the company from a bright idea. He or she will seek government grants and subsidies and be capable of presenting ideas to the market. In the second case, however, the owner is not really an entrepreneur. He/she may be compelled into starting a company when regulators are trying to formalise the informal economy. Forming a company and complying with regulations is a dead weight.
The reason that these two types of small business are different is that their leadership is different in terms of objectives, which is driven by personality as well as circumstances. True entrepreneurs, with their obsessive personalities, will react differently to the pressures of regulation and the opportunities afforded by government schemes. Hence, in small business, one size does not fit all.
BUILDING AN ECONOMIC ENVIRONMENT THAT WORKS
Human beings have evolved in their economic behaviour as well as all other behavioural and physical respects. When we understand the drivers of evolution in the ancient past, we can understand better how human beings (in almost all societies) will react to challenges. Like every natural system, human beings are conservative in the sense that they will resist change unless they perceive (often unconsciously) a substantial benefit.
Economic policy is particularly rich in blunders due to the failure of leaders to grasp how human beings react to change and stress – because they are human beings. When we make policy, we are in peril if we do not take into account these key natural drivers of behaviour, and indeed if we understand them well, we can use them to advantage.
Given our innate psychology, then, we can suggest some principles for a stable economic environment (from the biological point of view rather than purely that of economists). Hence, in setting policy, consider:
What incentives and rewards (or disincentives) will be created for the people who the policy is intended to affect … and for everyone else (including criminals) ?
Will these incentives foster the success of the policy, or will they work against it ?
How does the policy match up to our sense of natural justice (for example, Margaret Thatcher’s proposed poll tax which caused extensive rioting in the UK was described after the event in a PwC report as “inconsistent with people’s natural sense of fairness”) ?
Could the results adversely impact some other area of policy or some other group in society who are not the primary subject ?
How can unscrupulous (or sensible) people create their own rewards by exploiting the policy in unexpected ways (see 34) ?
How can we minimise the impact of the unscrupulous on the rest of us with minimal violence ?
Will the policy play well to the sense of co-operation and collaboration in society ?
To answer such questions as these, It is vital to test opinions and prejudices against facts, using the abundant literature available from experiment and observation in social and evolutionary psychology, and to devise further experiments that can be conducted. Only then can reliable predictions about results of policy be made.
We have learned so much about ourselves in the past half century, and there is so much more still to explore. Policymakers must make the effort to gain a well-informed understanding of individual and mass human psychology if they are to design initiatives which will produce the desired benefits for their communities and for those with whom they trade.
Human behaviour is a game of countless players, with governments and the governed interacting at many levels, harnessing reciprocal altruism, and balancing incentives to innovation, opportunism or cheating, all guided by intuitive morality as well as rational thought. Nevertheless, the material to formulate good governance and effective policies for the benefit of all can be revealed if we look for it.
.
References
1. Examples of misinformation:
a. the threat from terror in Europe is no higher than it has been historically – http://www.bbc.co.uk/news/world-europe-3954037
b. The impact of immigration (New Scientist 9 April 2016 – the Truth about Migration) and recent evidence of contribution of immigrants to the German economy
c. Wikipedia hoaxes- http://www.bbc.co.uk/news/uk-northern-ireland-37523772
d. Numerous Covid-19 hoaxes fact-checked on eg Reuters, Associated Press or Snopes.com
2. Karl Popper: “Conjectures and Refutations”, Routledge Classics, 1963-2002
3. Re GPS and relativity: See eg http://physicscentral.com/explore/writers/will.cfm
4. Ben Goldacre: “Bad science“, Farrar, Straus and Giroux, 2010
5. Steven Pinker: “The Blank Slate“, Penguin Books; Reprint edition, 2003
6. See eg:
a. Edward O Wilson: “Sociobiology – the new Synthesis,” Harvard University Press, 1975;
b. Edward O Wilson: “Consilience – the Unity of Knowledge,” Abacus, 1998
c. John Tooby and Leda Cosmides: “Evolutionary Psychology: A Primer,” http://www.cep.ucsb.edu/primer.html. See also http://www.iep.utm.edu/evol-psy/
7. Thomas Brennan and Andrew Lo: “The Origin of Behaviour”, http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1506264, 2009
8. Gillian Brown and Peter Richerson: “Applying evolutionary theory to human behaviour: past differences and current debates,” Springer Science+Business Media, New York, 2013
9. Prado-Martinez, Bonet et al: Nature 499, 471–475, 25 July 2013; and see https://www.upf.edu/cexs/news/genetica.html
10. Jerome Barkow, John Tooby and Leda Cosmides: “The Adapted Mind: Evolutionary Psychology and the Generation of Culture,” Oxford University Press, New York, 1992
11. Cass R Sunstein and Adrian Vermeule: “Conspiracy Theories”, University of Chicago Law School, Law & Economics Research Paper Series, Paper No. 387
12. Tom Stafford: “For argument’s sake – evidence that reason can change minds” location 319, University of Sheffield,
13. Amos Tversky and Daniel Kahneman: “Judgement under uncertainty,” Science 185(4157), 1974; see also Scott Adams” “How to fail at almost everything and still win big”, Penguin, 2014, chapter 21 ‘The Math of Success’
14. Ludwig von Mises: “Human Action,” Ludwig von Mises Institute, Auburn Alabama, 1998 – this is the defining work of the Austrian School of Economics first published in German in 1940
15. Michael Jensen and William Meckling: “The Nature of Man,” Journal of Applied Corporate Finance, Summer 1994, V. 7, No. 2, 1994
16. Roman Zytek et al: “The Financial Literacy Challenge”, p27, as presented at 38th Federation of ASEAN Economic Associations Annual Conference, Nanyang Technological University, Singapore, November 27-29, 2013
17. Eg John Cartwright: Evolution and Human Behavior: Darwinian Perspectives on Human Nature, MIT Press, 2008
18. Robert L. Trivers: “The Evolution of Reciprocal Altruism”, Quarterly Review of Biology, Vol. 46, No. 1 (March 1971), pp. 35-57. University of Chicago Press: http://www.jstor.org/stable/2822435
19. The term was coined by the American Philosopher C. I. Lewis. See definition in Michael Tye: “Qualia”, The Stanford Encyclopaedia Of Philosophy (Fall 2021 Edition), Edward N. Zalta (ed.), <https://plato.stanford.edu/archives/fall2021/entries/qualia/>.
20. John von Neumann and Oskar Morgenstern: “Theory of Games and Economic Behaviour”, Princeton University Press,1944
21. John Maynard Smith: “Evolution and the Theory of Games,” Cambridge University Press, 1982
22. Zhang, Brennan and Lo: “The origin of risk aversion”, Proceedings of the National Academy of Sciences of the USA, December 16, 2014, vol 111 no 50
23. William D. Hamilton: “The Genetical Evolution of Social Behaviour. II”. Journal of Theoretical Biology. 7 (1): 17–52, 1964
24. Peter Singer: “The Expanding Circle: Ethics, Evolution, and Moral Progress”, Princeton University Press, 1981. See also Steven Pinker: “Enlightenment Now”, Penguin, 2018, especially chapter 11.
25. John Moore – “Evil Is the Root of all Money”. Lecture at University of Edinburgh, 2019. An idea developed by Moore with his colleague Nobuhiro Kiyotaki at the London School of Economics, that money is a device that enables trust between parties who would otherwise be wary of trading with each other. See https://www.jstor.org/stable/3083378
26. Jared Diamond: “The World Until Yesterday”, Penguin 2012, Chapters 3 and 4
27. Her Highness the Renee of Sarawak: “The Three White Rajas”, Opus Publications, Kota Kinabalu, 2012. First published by Cassell and Co, London, 1939
28. Michael Polanyi: “The Tacit Dimension”, University of Chicago Press, 1966. For a more modern view, see Daniel Kahneman, “Thinking Fast and Slow”, Penguin, 2012
29. Robert Cialdini: “Pre-suasion – a revolutionary way to influence and persuade”, Simon and Schuster, New York, London, 2016
30. Paul Bloom (Professor of Psychology at the University of Toronto): “The war on reason”. https://www.theatlantic.com/magazine/archive/2014/03/the-war-on-reason/357561/
31. Peter Singer: “Ethics and Intuitions”, The Journal of Ethics, Vol. 9, No. 3/4, 2005
32. Colin F Camerer, George F. Loewenstein, and Drazen Prelec: “Neuroeconomics: Why Economics Needs Brains,” Scandinavian Journal of Economics, Volume 106, No. 3, pp 555-579, 2004
33. Marc D. Hauser: “Moral Minds,” HarperCollins e-books, 2006
34. Anthony King & Ivor Crewe: “The Blunders of our Governments”, One World Publications, 2013
35. See Mervyn King: The End of Alchemy, Abacus, 2017
36. Dan Ariely: “Predictably Irrational – The Hidden Forces That Shape Our Decisions,” Harper Perennial, 2010
37. Abhijit V. Banerjee and Esther Duflo: “Poor Economics – A Radical Rethinking of the Way to Fight Global Poverty“, PublicAffairs, 2012
38. Personal experience – savings and loans cooperatives, especially in Asia, are an effective way in which communities manage funding between themselves
39. Sandra J. Huston: “Measuring Financial Literacy”, 2009, available at: http://ssrn.com/abstract=1945216.
40. Michael Lewis: “The Big Short – Inside the Doomsday Machine”, W. W. Norton & Company, 2011
41. Alan Greenspan: “The Age of Turbulence”, Penguin Books, 2008
42. Andreas Acavalos (former PwC partner) – personal communication
43. See eg Steven Mithen: “After the Ice,” Harvard University Press, 2006; Francis Fukuyama: “The Origins of Political Order”, Profile Books Ltd, London, 2012
44. Melanie Mitchell: “Complexity – a Guided Tour,” Oxford University Press, 2009
45. Dambisa Moyo: “Dead Aid,” Penguin, 2009
46. Daren Acemoglu and James A Robinson: “Why Nations Fail”, Crown Business, New York, 2012
47. Dambisa Moyo, ibid
48. Banerjee and Duflo, ibid
49. Stathis Kalyvas: “Modern Greece” Oxford University Press, 2015
50. Maurice Obstfeld and Poul M. Thomsen: “The IMF is Not Asking Greece for More Austerity,” https://blogs.imf.org/2016/12/12/the-imf-is-not-asking-greece-for-more-austerity/, 12 Dec 2016
51. “ ’Brexit is already starting to make families poorer’, Bank of England warns”: The Independent 12 May 2017, reporting Bank of England Press Conference 11 May 2017
52. In October 2021, Richard Hughes said that leaving the EU would reduce the UK’s potential GDP by about 4% in the long term and that forecasts showed the pandemic would reduce GDP “by a further 2%”. His conclusion was that: “In the long term it is the case that Brexit has a bigger impact than the pandemic”. See https://www.bbc.com/news/business-59070020
53. 30 October 2021 https://www.theguardian.com/politics/2021/oct/30/brexit-is-harming-the-uk-economy-say-44-of-voters
54. Michaela Erbenova et al: “The Withdrawal of Correspondent Banking Relationships: A Case for Policy Action”, IMF Staff Discussion Note, June 2016