Copycats & Contrarians

Why We Follow Others . . . and When We Don't

Michelle Baddeley

• Publisher: Yale University Press
• Year: 2018
• ISBN:
  9780300231823
• Topic: Psychology
• Subtopic: Social Psychology
• Index: Psychology

"Why we run with—or avoid—the crowd, and why it matters, from choosing a restaurant in a tourist trap to believing fake news. I learned a lot" (Tim Harford, author of The Undercover Economist ). Rioting teenagers, tumbling stock markets, and the spread of religious terrorism appear to have little in common, but all are driven by the same basic instincts: the tendency to herd, follow, and imitate others. In today's interconnected world, group choices all too often seem maladaptive. With unprecedented speed, information—or misinformation—flashes across the globe and drives rapid shifts in group opinion. Adverse results can include speculative economic bubbles, irrational denigration of scientists and other experts, seismic political reversals, and more. Drawing on insights from across the social, behavioral, and natural sciences, Michelle Baddeley explores contexts in which behavior is driven by the herd. She analyzes the rational vs. nonrational and cognitive vs. emotional forces involved, and she investigates why herding only sometimes works out well. With new perspectives on followers, leaders, and the pros and cons of herd behavior, Baddeley shines vivid light on human behavior in the context of our ever-more-connected world. "Her observations on how both risk-taking and conformism contributed to Donald Trump's election, and on how social media affects 'copycats, ' make for a well-timed and valuable study." — Publishers Weekly "This might well become the defining book, for this decade and more, on the topic of herding and social influence." —Cass Sunstein, co-author of Nudge

1

Clever copying

Are copycats clever? Or is it mindless and irrational just to do what others are doing without using our own initiative and mental energy to decide for ourselves? And how might we distinguish blind conformity from intelligent imitation? Often, we cannot easily tell the difference.

Our everyday lives provide some examples. Imagine that you are in a meeting and you are asked to vote on an issue about which you do not feel particularly passionate or well informed. You decide to raise your hand in favour because you see a few of your colleagues doing the same. Are you being lazy? Responding to peer pressure? Perhaps. Or perhaps you are using your colleagues’ actions as an alternative source of information. You interpret their hand-raising as a signal that they know something you do not. If you knew what they know, then perhaps you would vote in favour too. In cases like this, following others is clearly not stupid, even when it involves minimal brainwork.

At times, all of us find it easier just to follow what others are doing because we assume they know more than we do. When we are lost, it is reasonable to follow a crowd to find our way. By observing and following the actions of others, we can gather signals, information and guidance – all of which can help us to do better for ourselves. This is the phenomenon of self-interested herding. We herd because we get some benefit as selfish individuals.

Rational choice theory, developed in the 1970s by the Nobel Prize-winning American economist Gary Becker, provides deeper exploration of what motivates individuals to follow a crowd or join a group.¹ Becker maintained that individuals are the best at choosing for themselves. No other person or organisation is better able to prioritise the individual’s interests in a rationally analytical way. Becker and his colleagues argued that this assumption helps to explain a wide range of human decisions and problems – everything from marriage and divorce to addiction and discrimination. Becker’s rational choice approach is most commonly embraced by economists, with many economic models describing rational individuals making choices to help themselves, as if guided by sophisticated mathematical rules. Even so, Becker does allow that social interactions are important to us. He argues that our social environment has monetary value, helping us to generate what he calls ‘social income’ via our relationships with others around us.² Our professional relationships illustrate Becker’s point: the opinions of our colleagues and bosses may have monetary value for us if they increase our chances of a pay rise.

To explain self-interested herding, economists start with the concrete advantages each person might enjoy from following others. A self-interested person is not concerned with promoting group interests. From an economist’s perspective, we do not herd to help the group; we herd to help ourselves. We can learn from others. Sometimes, we can improve our reputations by following others. We can gain more when we act as a group than as an individual. All these advantages can be understood relatively easily in terms of economic motivations and incentives. Copying and collaborating is a means to an end – the end being something to do with helping ourselves.

Homo economicus in the crowd

How do economists link their assumptions about our capacity for rational choice with human social behaviour? Some insights have their roots in the ideas of Vilfredo Pareto, an Italian polymath who trained as an engineer and went on to make a range of enduring contributions to economics, sociology and political science. Often lauded as one of the forefathers of modern neoclassical economics, Pareto was one of many characters contributing to an impressive Italian tradition in economic analysis which has included inspirational thinkers from both left and right.³ Pareto’s name is well known to students of economics, associated as it is with one of the fundamental concepts in the subject – Pareto optimality. This is achieved when welfare improvements from voluntary exchange are exhausted, at the point where no-one can be made better off without making someone else worse off.

To ensure this simple (some would say simplistic) result, Pareto assumed rational choice by a peculiar, hypothetical species: Homo economicus.⁴ Characterised by its clever, self-interested and individualistic nature, the choices Homo economicus makes are driven by rigorous, analytical decision-making processes as it searches for ways to maximise its own welfare. Homo economicus is not, however, infallible. It makes mistakes, but these are quickly corrected to ensure that they are not repeated. Homo economicus does not care what happens to others, but it does have a restricted social awareness. It realises that the information others convey in their choices and decisions is potentially useful, and it uses this social information to guide its choices, without necessarily worrying too much about how its actions may impinge on others’ well-being.

What are the impacts on the economy as a whole? They are beneficial, according to neoclassical economists – who often cite Adam Smith, grandfather of modern economics. In his 1776 book, An Inquiry into the Nature and Causes of the Wealth of Nations, Smith observed:

It is not from the benevolence of the butcher, the brewer, or the baker that we expect our dinner, but from their regard to their own self-interest. We address ourselves not to their humanity but to their self-love, and never talk to them of our own necessities, but of their advantages . . . Nor is it always the worse for the society that it was not part of it. By pursuing his own interest [a person] frequently promotes that of the society more effectually than when he really intends to promote it. I have never known much good done by those who affected to trade for the public good. It is an affectation, indeed, not very common amongst merchants, and very few words need be employed in dissuading them from it . . .⁵

Adam Smith’s insight about how we help others by helping ourselves is backed up in modern economics using a collection of assumptions and relatively simple mathematical proofs. How? Smith uses his famous metaphor of the Invisible Hand to capture how, across a marketplace, everyone’s selfish choices are coordinated, via shifting prices, to achieve what is best for everyone in the market as a whole. The price mechanism is neither tangible nor concrete. We cannot see lots of other people wanting to buy and sell stuff, but prices rise and fall to reflect the shifting balance of those who want to buy versus those who want to sell. In these anonymous marketplaces, we will gain nothing from attempting to second-guess others’ choices. Our best strategy is selfishly to focus on ourselves and let the Invisible Hand of the price mechanism coordinate all our choices so that the prices paid reflect each person’s willingness to buy or sell.

Of course, there are all sorts of problems with this account of price movements. Economists are often accused of promulgating a perspective on human behaviour that is excessively stark and unrealistic. And Adam Smith’s views on our social lives were much more complex and nuanced than some might imagine just from reading selective quotations. More generally, economists make unrealistic assumptions to abstract from the complexity of the real world. Some economists argue that such assumptions help us to simplify and so capture the essence of human behaviour. The complexity is particularly significant when people are interacting by copying and herding. So, economists bring Homo economicus into their models, not because they believe real people operate in such a logical and mathematical way, but because it simplifies the analysis, especially when economists are investigating numerous, complex interactions between large numbers of people.

We can see this most clearly in a macroeconomy – essentially a crowd of crowds. Capturing group and herding behaviour within a small group is hard enough, but macroeconomists face an even greater challenge. To capture myriad interactions between people across an economy, macroeconomists have conventionally categorised different breeds of Homo economicus using assumptions about representative agents. These representative agents capture the stereotypical behaviour of key decision-makers in the economy, and they include representative worker-consumers and representative producer-employers. In a conventional macroeconomist’s account, the representative worker-consumer makes a decision about how much they want to work, balancing the wages they can spend on consuming the things they enjoy against the discomfort and inconvenience of working. Workers have a symbiotic relationship with the representative employer-producers, who maximise their profits by employing workers at the lowest feasible cost so as to produce all the things that the worker-consumers want to consume. If these different groups of representative agents are identical and behaving in the same way, then economists can more easily analyse macroeconomic phenomena. They can add together the representative agents’ choices via relatively easy arithmetic calculations.

What has this got to do with herding? Economic models of herding bring the same types of representative agents into their technical, mathematical analysis of how and why people copy others around them. In the case of self-interested herding, each member of the herd is rationally and individualistically pursuing their own self-interest – asking themselves ‘What do I gain if I join?’ Benefits may be immediate if we are able to make better choices for ourselves by following other people’s good ideas and choices. Other benefits may be indirect and delayed. Sometimes we join a group because we believe that cooperating with others will deliver us long-term rewards. Many long-term collaborations and relationships involve patiently incurring costs in the beginning to ensure larger rewards in the end. Whether leading to short- or long-term gains, these choices are conscious and cognitively driven, inspired by a spirit of cooperation and collaboration but in ways that are consistent with self-interest and rational choice.

Social learning

Another feature of economists’ representative agents is that they are super-rational and clever with information, using complex mathematical rules to process information efficiently. Herding is one manifestation of this clever information-gathering strategy. Rational herders identify strategies to minimise the costs to them of searching for information to guide their choices. They do this by balancing their private information against their social information. Our private information includes all the things we know that others cannot know we know. It is the information we have that other people cannot see because it is inherently unobservable and we cannot read each other’s minds. Social information is the information we gather from observing other people’s actions, and we use it to infer what caused others to act as they did. Just as other people cannot know what we know just by looking at what we do, so we cannot know for sure what they know just by watching them. But, by observing the choices they make, we can infer something about their incentives, motivations and intent. In the context of herding, we may conclude – though not always correctly – that the choices of others reflect underlying knowledge or expertise that we don’t have. Often, we will not know, and may never find out, whether their knowledge is truly superior to ours. Consider the example of the vote at the meeting discussed at the start of this chapter. Voting in favour of a motion because others are doing so is consistent with rational choice if our vote is based on a rational calculation that the colleagues we are copying are better informed than us, and so we would do well to emulate them. Social information enables social learning: by observing other people’s choices, and the rewards or costs those choices confer, we can learn about what is best for ourselves.⁶ It is particularly important in situations where information is scarce and uncertainty is endemic. Why? Because, when we know very little, what we observe in others’ behaviour and choices might be the best information we have.

Information cascades

In the early 1990s, economists started to develop a keen interest in the phenomenon of herding. They developed a range of theories and experiments to explore models of rational herding based around principles of social learning. They focused on explaining how we rationally balance social and private information, and how self-interested herding unfolds as a consequence. Pioneering studies of herding were developed by a team of economists including Sushil Bikhchandani, David Hirshleifer and Ivo Welch, based at the University of California.⁷ They described self-interested herding as a sequential social learning process, with each person balancing what they already know against what they see others doing. The herd grows when each individual discounts what they privately know themselves and instead decides to follow the person in front of them. Bikhchandani, Hirshleifer and Welch use the powerful metaphor of what they call an information cascade to describe this herding process. One person makes a choice, the next person observes them and decides to do the same. Then the next person observes them and does the same too, with more conviction because they have had a chance to watch two people decide, not just one. As more and more people copy more and more people ahead of them, the power of the herd’s signal increases. Social information about other people’s actions flows through a group, building momentum as the herd grows. In other words, social information cascades through the herd. Information cascades help us understand a wide range of fragile and unstable phenomena in our economy and society, including booms, crashes, fads and fashions.⁸

Independently, the MIT economist Abhijit Banerjee developed a similar model of herding, illustrated with the everyday example of choosing between two restaurants.⁹ Imagine that Restaurant A is crowded while next door Restaurant B is empty. Why don’t the customers move from one to the other? Banerjee explains this apparent anomaly as evidence of rational herding.¹⁰ People have a private signal favouring Restaurant A – say, a restaurant review they have read, or a recommendation from a friend. They can also collect some social information – they can observe which restaurant the other people ahead of them have chosen. Sometimes this social information conflicts with the private signal: someone has a recommendation favouring Restaurant A but sees a long queue waiting for a table at Restaurant B. The queue may encourage them to disregard their private signal and choose the crowded restaurant instead.

Banerjee’s restaurant problem can also illustrate how information cascades work in practice. Imagine you face a similar conundrum to that posed by Banerjee. You are choosing between two adjoining Mexican street-food restaurants, Amigo’s and Benito’s. Assume that you know that Amigo’s has in the past been favoured by most people, and Benito’s by not so many. So, at the start, the balance of probabilities is in favour of Amigo’s. However, you have read a restaurant review praising Benito’s for its delicious tacos, tostadas and enchiladas. The private information you have suggests that Benito’s is better.

Let’s imagine that you join a crowd of restaurant-goers outside the two restaurants, and each of you decides, one by one, which restaurant to eat in. Your choice is complicated by the fact that the people waiting alongside you also have valuable private information. They are strangers, and so you don’t know what they know or what might motivate them to choose one restaurant over the other. They may have read the same review that you read, praising Benito’s. They may have read other reviews also raving about it. They may have heard from friends and family that Benito’s is a great restaurant. So, even though Amigo’s has been preferred in the past by most people, the unobservable private information suggests that the past preferences of the majority are unreliable. But no-one knows this because each person is ...