What Motivates Us?
Does money really make the world go round? Many economists model the world as if money is the key thing that motivates us, and many economic policies certainly assume that's the case. But in 1970 Richard Titmuss published The Gift Relationship, noting that paying people for their blood donations, as in the US health-care system, actually reduces the quality and quantity of blood donated, whereas in the British system there is no payment, aside from a cup of tea and a biscuit. Titmuss argued that the British system was superior because it did not rely on monetary reward. For a long time, the hypothesis went untested until, in 2008, Mellström and Johannesson published the results of an experiment. The unsuspecting volunteers ‒ undergraduate students from Gothenburg University ‒ responded to an advertisement for participants in a study relating to ‘attitudes to blood donation’. The results were telling. Of those to whom payment was not offered, 43 per cent agreed to become blood donors. When payment was offered, the donation rate was lower, at 33 per cent. However, when the researchers offered a payment option that was more flexible, allowing the money to be donated to charity, the donation rate jumped back up to 44 per cent.
What is interesting is that when analysed in terms of pure rationality, there should be no difference in the last two scenarios: if you receive payment, you can still donate to charity, whether or not you are directly presented with the option. Clearly, however, people were put off by the idea that they might be seen by others to be giving blood for financial benefit. Behavioural economists have therefore distinguished between intrinsic and extrinsic motivations, where intrinsic motivations represent our attitudes and internal goals and extrinsic motivations represent the incentives we are given from outside sources to do something we might not otherwise wish to do (such as financial payment for our time, or public gratitude for a good deed). They note that extrinsic motivations such as money can crowd out intrinsic ones, meaning that money is not always the best motivator.
In addition to being motivated by more than money, experiments have shown that human beings also have an inherent sense of fairness. Perhaps the most famous example is the ultimatum game, a ‘game’ played between two individuals. Each individual is anonymous in the sense that they are not able to see each other or interact. The intention is to remove any social influence on the outcome of the game in an effort to reveal how we behave as isolated individuals. One individual (the ‘proposer’) is given a set amount of money (say, US$100) and has responsibility for deciding how to split that money between themselves and the other individual (offering anything between US$1 and US$100 to the other party). This other individual (the ‘responder’) can then either accept the proposed split or reject it; if they reject it, neither person receives any money.
Now, if proposers act in a purely rational, money-driven way, they would propose a split in which they keep US$99 and give the other party a miserly US$1 (or whatever the minimum possible figure is). This is because, if you believe people are rational, self-interested and calculating, it would not be sensible for the responder to reject any positive pay off (no matter how small); something is always better than nothing. However, the most common offer is a split much closer to US$50:US$50, and offers of less than US$30 to the second party are regularly rejected when the game is played.2 In other words, people are happy to reject low offers – to effectively accept a financial loss – in an effort to punish someone they think is behaving ‘unfairly’. The implication is clear: people do not only value money; they value fairness, and they want to feel respected.
Another popular game ‒ the public goods game ‒ also serves to reveal that we are much less self-interested and more ‘pro-social’ than economists have assumed. Suppose five volunteers are each given an initial sum of US$10 and have the option of contributing to a common pool (think of it as being a pot in the centre of the table). As in the ultimatum game, the volunteers cannot see each other and do not know the decisions being made by anyone other than themselves. However, what they are told is that any money added to the common pool will be multiplied by three and then shared out equally five ways. Faced with this situation, how much would you decide to contribute to the common pool? Well, if you acted as an economist supposes, you would likely reason that for every US$1 you put in the pot, you will receive only US$3/5 (i.e. 60 cents). As a result, the rational and self-interested thing to do is to keep the initial US$10 and contribute nothing. Of course, if everyone donated the whole of their US$10 to the common pool, they would all leave with the maximum amount possible: US$30. However, on an individual level, it is not rational to donate your own money but instead to hope that others will do so. The result is a ‘free-rider’ problem, where no one contributes and everyone is worse off as a result. As it turns out, when the game is played, people regularly donate around half of their initial sum to the common pool.3 Furthermore, if the game is played multiple times with the same people, and they are each given the option of punishing anyone who does not ‘cooperate’ ‒ but at a cost to themselves ‒ they regularly do so.4 In other words, within human groups there seem to be strong incentives to cooperate ‒ and to punish those who do not. We need to go beyond money if we are to understand human behaviour.
How Rational and Calculating are We?
Economists’ starting point is that we all know what is good for us and are capable of achieving it. We don't need a ‘nanny state’ to help us make decisions. If we overeat, under-save or partner up with the ‘wrong’ person, the problem is simply one of too little information. All the state needs to do is to make sure that we have the right information. By assuming that we can all behave in a rational and calculating way, there is no additional need for intervention; the state cannot possibly be expected to lead to better decisions than those which we can make on our own behalf.
Herbert Simon argued that in the real world people possess neither the full set of information nor the time required to make the ‘best’ choice.5 Furthermore, the human brain is limited in terms of its ability to process and weigh up all available options. Rather than being fully rational, Simon proposes that we are ‘boundedly rational’. In the words of one writer, we should ‘[t]hink of the human brain as a personal computer, with a very slow processor and a memory system that is both small and unreliable’.6 As a result, people often fall back on ‘rules of thumb’, what are known as heuristics, which render all the decisions in our daily lives much less complicated and time-consuming. However, whilst these heuristics make our lives easier, they are often not perfect and can lead to fallible decisions. For example, rather than going through the mental effort of working out which is the best-value supermarket, visiting each one to weigh up the various offers, we tend to return to the same supermarket we visited last time. This rule of thumb creates what has become known as the ‘status quo bias’. Other rules of thumb were revealed in a series of experiments conducted by Daniel Kahneman and Amos Tversky. These show our natural tendency to jump to conclusions, to place excessive weight on our own experiences and to look only for evidence which confirms our beliefs (ignoring evidence which does the opposite).7 The implication of these biases – biases created by the mental shortcuts that are hard-wired into our brains – is that we tend to be resistant to change, overconfident and stubborn and, as such, make decisions and act in a way that is not always in our own best interests.
We all know that sometimes our ‘heart’ tells us one thing and our ‘head’ tells us another. Daniel Kahneman argues that our thinking processes involve two ‘systems’.8 System 1 in the limbic region of the brain performs the ‘thinking fast’ part of our activity; it is associated with emotional (‘hot’) activity – it is intuitive, happens with little or no consciousness and is effort-free. System 2 in the prefrontal cortex is the ‘thinking slow’ part of the brain, where conscious and calculating activity takes place. For most of the time, System 1 – and not System 2 – is in charge, which accounts for why we so often fail to behave in the way economists predict.
To see the everyday battle in action, neuroscientists like to scan our brains. One group of researchers wired up volunteers to examine how the brain reacted when faced with the choice of receiving a US$20 voucher to spend today or a US$30 voucher in two weeks’ time.9 The results were revealing. The offer of US$20 today stimulated activity in the emotional part of the brain, but the option of US$30 in two weeks’ time stimulated action in the calculating part of the brain, leading to an internal conflict. One option delivers instant gratification, satisfying our ‘emotions’, but the other seems more sensible from the point of view of the calculating part of our brain.
Two important findings have resulted from this work. The first is that we sometimes make decisions automatically, without really thinking about them. The second is we are strongly influenced by our emotions. There are, however, times when automatic and emotional behaviour can be helpful.10 Although our System 1 brain is responsible for many of our mistakes, it is also responsible for much of what we get right. After much experience, it can produce ‘expert intuition’ of the kind that is invaluable to medics and firefighters who need to react to complex situations with great speed. Making decisions automatically and with emotion can have benefits, which might explain why our brains have developed to work in this way. Many common psychiatric disorders, such as obsessive-compulsive disorder, arise when we employ too much careful calculation and deliberation. Furthermore, individuals who lack the emotional – relative to cognitive – input in decisions often find decision making more difficult and are not always very good at it. If we can't ‘feel’ an outcome, we can end up making decisions that we see in retrospect are wrong.
Why Behavioural Economics Matters
Behavioural economics has become all the rage in policy circles and has resulted in a number of recent Nobel prizes in economics. Policy makers have also begun to adopt its policy implications, in terms of ‘nudging’ us out of behaviour that is bad for us. However, whilst such interest might lead one to think that economists’ way of thinking about individual behaviour is being transformed, according to David Levine, Professor in Economics at Washington University, ‘nothing could be further from the truth’. In fact, he has written a whole book on the matter, asking ‘Is behavioural economics doomed?’11 So why, despite all of the evidence, has mainstream economics not embraced a more realistic set of assumptions about human behaviour in an effort to build a better understanding of the economy?
The typical answer is that building models will always require some form of simplification. Assuming human beings are self-interested, rational and calculating might be a little far-fetched, but it at least captures some important aspects of human behaviour. To assume the opposite would seem foolish. As the Nobel prizewinning economist Milton Friedman once famously noted, if we want to formulate a model which helps us to explain the actions of a snooker player, we will arrive at the most accurate predictions if we build the model assuming that the snooker player has a good grasp of physics, meaning the ability to calculate the trajectory and speed needed for each shot. A more realistic assumption would likely lead to worse – not better ‒ predictions about how the game would be played. What matters, in other words, is not whether a model has realistic assumptions but how accurate its predictions are relative to alternative models.
In the real world, emotions, irrationalities and fallibility certainly exist, as any economist will happily admit, it's just that they don't think that those elements of behaviour are particularly relevant to understanding the economy. Economists, after all, focus mostly on markets, and it's commonly thought that in markets there is no place for emotions, vulnerabilities and weaknesses – the market compels everyone to behave in a selfish, rational and calculating way; otherwise, they will be swept under ‒ they will be bankrupt.
The ultimate test, therefore, of whether economics should embrace real human psychology is whether it would make a substantial enough difference to the way we think about the economy. As we will see below, it is in fact impossible to answer many of the big questions that economists face without relaxing the homo economicus assumptions.
1 The causes of economic growth
The market is where most economists begin when they seek to explain the creation of economic prosperity. Markets are argued to harness our self-interest, encouraging us to invest and invent. This works in the form of carrots and sticks: markets create potential customers and therefore a potential financial reward in the form of profit; the competition they bring pushes entrepreneurs to keep costs low and increase their productivity, meaning we get the best product at a reasonable price. Perhaps naturally, therefore, rational, calculating and self-interested behaviour has come to be seen as an important driver of economic prosperity.
Now, at the very centre of economic growth is technological change. Typically, we think of this as a response to the potential financial reward on offer in terms of higher profits or a valuable patent. However, as Joel Mokyr has pointed out, many of the technologies associated with the Industrial Revolution would not have taken place had inventors been purely driven by financial self-interest.12 The patent system was expensive and cumbersome and few inventors actually profited from it. It was only in view of the fact that we overestimate our own chances of success that the system stimulated invention. It is not cool, calculating robotic behaviour that leads people to start new businesses and develop new technologies or new ideas; it is the (irrational) human element. As Keynes neatly summarized it, ‘[i]f human nature felt no temptation to take a chance, no satisfaction (profit apart) in constructing a factory, a railway, a mine or a farm, there might not be much investment merely as a result of cold calculation’.13
In fact, non-financial motives are just as important as financial ones. Technological change rests on improvements in science. Rather than private financial gain, scientific advances often have at their roots a desire to wipe out pain and suffering, simple curiosity, or the hope of recognition from colleagues. These motives can represent a much more powerful inducement and reward than money, bringing the social regard and ‘warm glow’ that would not have surprised Smith. The Enlightenment movement – commonly seen as giving birth to modern science – involved scientists coming together, cooperating to help make the world a better place, not for financial gain but for the public at large. Still today, this motivation drives the efforts of many scientists. Private-sector activity might rely on profit-driven self-interested behaviour, but it draws upon the ideas and innovations of scientists working with very different motives. Interestingly, as psychologist Teresa Amabile has shown, attempts to incentivize creativity and independent thought through financial rewards, regular evaluations and competition can in fact hinder rather than help.14 Although conventional economics can teach us the importance of science and technology (and who would be surprised by that), its simple conception of human behaviour cannot explain it, or indeed help us to encourage it. That's a big problem, given that science and technology are so central to economic growth.
In addition to the sphere of production, there is another sphere which is equally as important for economic growth but which economists increasingly chose to ignore: reproduction.15 Although economists regularly talk about the ‘accumulation of capital’, the accumulation of people – which combines with capital – also requires attention. In macro models, people need to be treated as an output as well as input, as in the pioneering feminist macro model constructed by Elissa Braunstein, Irene van Staveren and Daniele Tavani, which integrates unpaid work ‒ that generates people ‒ with the more usual paid work.16 An economy can only thrive if it has a stock of well-functioning and productive individuals, historically the product of good parenting and women's reproductive and nurturing work, much of which takes place within the home. Here, money is not the driving force; rather, as Sabine O’Hara argues, it is care, altruism and love. By reducing human beings to robots, economists have ignored all of the work which goes on behind the scenes, outside of the market. T
hey have taken for granted women's hard labour and devalued work within the home, where it is not carried out for financial reward.17 As Folbre notes, whilst behavioural economists study norms of trust and reciprocity, they would do well to also look at norms of care and obligation.18
2 From boom to bust: explaining the business cycle
Most explanations of the business cycle revolve around the idea of ‘shocks’. The assumption is that, left to its own devices and without interference from government, the economy will be more or less stable. Markets should clear, ensuring that everyone who wants a job has a job and that every firm is able to sell whatever it wishes to produce. If the economy goes into ‘recession’, it is assumed to be the result of an outside shock on either the demand or supply side ‒ to the amount people spend or to what the economy is capable of producing. The best way of insulating our economy from boom and bust is, therefore, to make sure that markets are flexible so that they can adjust quickly to such shocks.
John Maynard Keynes, Cambridge's most famous economist, is also often associated with the ‘shock’ explanation, particularly demand-side shocks: changes in investment, consumer spending, export demand or government spending. His most significant idea was that economies can fall into recession as a result of a reduction in any of these components of demand. Since Keynes put forward his theory of the business cycle in his General Theory of Employment, Interest and Money, economists have turned his insights into a mathematical model. They have shown that so long as prices and wages are free to adjust, the economy should quickly return to ‘equilibrium’ following a shock to demand.
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