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Freakonomics: A rogue economist explores the hidden side of everything

Book cover

by Steven D. Levitt and Stephen J. Dubner, Allen Lane, 2005.

Abstract

One of today’s most original thinkers turns conventional economics on its head and asks provocative questions about human motivation and contemporary living. It’s sometimes hard to make sense of the world but lateral thinking and refusal to accept conventional wisdom can help to answer complex issues. It requires a novel way of looking, discerning and measuring.

(Summarised by Kevin Barham in November 2006)

(These book reviews offer a commentary on some aspects of the contribution the authors are making to management thinking. Neither Ashridge nor the reviewers necessarily agree with the authors’ views and the authors of the books are not responsible for any errors that may have crept in.

We aim to give enough information to enable readers to decide whether a book fits their particular concerns and, if so, to buy it. There is no substitute for reading the whole book and our reviews are no replacement for this. They can give only a broad indication of the value of a book and inevitably miss much of its richness and depth of argument. Nevertheless, we aim to open a window on to some of the benefits awaiting readers of management literature.)

America’s most brilliant economist

What do schoolteachers (American teachers, anyway) and sumo wrestlers have in common? How do experts use the power of information? What do sales of bagels tell us about white collar crime? How honest do you think the people in your firm are? What really caused crime rates to fall in the US? And do parents really matter? These are some of the questions addressed in this book by Stephen Levitt.

Levitt, who teaches economics at the University of Chicago, has been voted the most brilliant young economist in America. As a measure of the attention his ideas have attracted, he was selected by Time magazine in November 2006 as “One of the 100 People Who Shape Our World”. His co-author, Stephen Dubner, is a journalist who wrote a profile of Levitt in the New York Times magazine in 2003. The extraordinary response to the article led to this book.

Malcolm Gladwell, himself a bestselling author (The Tipping Point) says that Levitt has the most interesting mind in America. He turns everything you once thought to be true on its head. And that is certainly what he does in this book whose aim is to explore the “hidden side of everything”.

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The hidden side of everything

Levitt claims that he doesn’t know much about conventional economics. He is interested in the stuff and riddles of every day life. He believes that the essence of economics is explaining how people get what they want and what makes them do it. He sifts through data to dig up stories that nobody else has discovered and finds ways to measure effects that traditional economists have found unmeasurable. His greatest interests are in the motivation behind cheating, corruption and crime. He believes that the modern world, despite all the obfuscation, complication, and deceit that hide the truth, can be understood and, if the right questions are asked, can be found to be even more intriguing than we think. It just takes a new way of looking.

Ostensibly the book has no single unifying theme, although it is based on a few fundamental ideas. While it is not specifically addressed at business and draws most of its examples from other walks of life, those underlying messages are highly relevant to business:

  1. Incentives (positive or negative) are the cornerstone of modern life. Understanding them – and ferreting them out – is the key to solving any riddle.
  2. Conventional wisdom is often wrong. It can be very difficult to see through, but it can be done if you look at data that others don’t investigate and ask questions that other people don’t ask.
  3. Dramatic effects often have distant, subtle causes. The answer to a riddle is not always in front of you.
  4. Experts use their informational advantage to serve their own agenda. (The Internet, however, is shrinking their advantage.)
  5. Complex issues can be understood if we find the right perspective. Knowing what to measure and how to measure it is key.

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Wrestlers and teachers

So what is it then that schoolteachers and sumo wrestlers share? The answer (allegedly) is a propensity to cheat. But then anyone will cheat, says Levitt, if the stakes are right. In his view, economics is essentially the study of incentives, how people get what they want or need, especially when other people want or need the same thing. Economists believe that every problem can be solved if the right incentive (negative or positive) can be designed. An incentive is simply a means of encouraging people to do more of a “good” thing and less of a “bad” thing.

For every incentive scheme devised, there are always people who will try to beat it. Cheating is a prominent feature in almost very field of human activity. As just one example cited by Levitt, in 1987 the Internal Revenue Service in the US changed the tax rules so that, instead of merely listing each dependent child, tax returns had to provide a social security number for each child. Overnight, 7 million, children, who had only existed as phantom exemptions on the previous year’s tax returns and who represented 1 in 10 of all dependent children in the US, vanished from the population figures.

Levitt found that cheating by teachers happens in (US) schools where “high stakes” testing holds schools accountable for pupils’ test results. Incentives and penalties encourage teachers to fiddle the test scores. But how do you find this out?

It’s possible, says Levitt, to catch cheaters if you think like one and identify tell-tale patterns in the test results. It’s far more common than might be supposed. A study in Chicago found evidence of teacher cheating in 200 classrooms per year, 5% of the total. (That was a conservative estimate. In another study among teachers in another state, 35% of respondents said they had seen their colleagues cheating on test results.) When Chicago fired a dozen offending teachers, cheating by teachers fell by 30% the following year – further testimony to the power of incentives.

We might think that cheating by teachers is disgraceful but in Japan, where sumo is sacrosanct, the notion of sumo wrestlers cheating to lose is likewise unthinkable. The stakes, economically and status-wise, are very high in sumo, especially if you are among the elite group of wrestlers, so ranking is all important. Levitt followed up allegations that wrestlers were cheating by testing the data.

His reasoning was as follows. Sumo tournaments consist of 15 bouts; if a wrestler finishes with a winning record (8 victories or better), his ranking will rise. If he has a losing record, his ranking will fall. The 8th victory is therefore critical. A wrestler in the final bout with a 7-7 record has far more to gain from a victory than an opponent with a record of 8-6 has to lose. Is it conceivable, Levitt asked, that an 8-6 wrestler might, if offered the right incentive, allow a 7-7 wrestler to beat him? Again, when he looked at the data on the results of sumo tournaments he found evidence that the unthinkable – extensive match rigging – does take place.

So is mankind innately corrupt, Levitt asks? And if so, how far? Can we measure it? The incidence of white collar crime is one way to look at the question There isn’t much available data here but, again, Levitt finds an unusual way to tackle the question. His window on workplace crime is the story of Paul, the former research analyst who started a very successful business selling bagels to Washington office workers.

Paul works on the honour system, delivering baskets of bagels to office snack rooms and leaving a money box in which he trusts people to put their payment. True to his former calling, he keeps meticulous records of his sales which allow him to measure the honesty of his customers. Paul’s bagel data is very revealing. It shows, for example, that smaller offices are more honest than big ones, that bad weather makes people cheat, that an office is more honest when the employees like their boss and their work, and that senior managers are more likely to cheat than junior employees. The encouraging thing, however, is that the vast majority of people – 87% – do not steal bagels. Levitt takes this as a measure of how honest people in general are. (The bagel honesty rate, incidentally, shot up 2% immediately after September 11.)

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The Klu Klux Klan, and real estate agents

Levitt moves on to another area of interest: the role of experts and the power of information. He starts with the Klu Klux Klan. The influence of the Klan was virtually destroyed, he tell us, by a brave anti-bigot who went undercover to infiltrate the organisation and make public its passwords and rituals. In so doing, he converted the secret knowledge into ammunition for mockery and turned the Klan’s secrecy against itself.

It’s a story (told in some detail by Levitt) which demonstrates the raw power of information. The KKK was a group – like politicians, estate agents or stockbrokers – whose power derives from the fact they hoard information. Once that information gets into other people’s hands, much of the group’s advantage disappears.

The Internet in particular has undermined such advantage. It caused the price of life insurance to fall dramatically in the late 1990s by making it possible for people to shop around for the cheapest policies and forcing expensive life insurance companies to lower their prices. The Internet is brilliant at shifting information from those who have it to those who do not. It’s been especially useful for situations in which a face-to-face encounter might exacerbate the problem of asymmetrical information where the expert can make somebody feel stupid or where you are under emotional duress. (Car salesmen and funeral directors have been particularly affected by online competition.)

But the Internet, though powerful, has not completely solved the problem of information asymmetry. Enron, WorldCom and the other corporate scandals of the early 2000s were crimes of information. Most of them involved “experts” promoting false information or hiding true information, trying to keep information as asymmetric as possible.

Many experts use information to our detriment. They can exert a gigantic, unspoken leverage through fear. Doctors, lawyers, car mechanics, stockbrokers – we depend on numerous such “experts” because they have an informational advantage. How they treat you depends on how their incentives are set up. One way to measure how an expert treats you is to measure how he performs the same service for himself. This is difficult information to find for many professions but it is possible to do it for real estate agents as house sales are on public record (in the US at least).

People may think that they and the real estate agent (whose commission is based on the sales price) share a common aim – to get the best possible deal on their house sale. It turns out, however, that the returns to the estate agent for putting extra effort into a client’s house sale are not worth the effort to them. The data show that estate agents keep their own houses on the market for longer and sell them for a higher price. When they sell their own houses, they hold out for the best offer; but when they sell yours they take the first decent offer that comes along. A big part of the agent’s job is to persuade the homeowner to sell for less than he would like while at the same time letting potential buyers know that a house can be bought for less than its asking price.

The Internet has shrunk the advantage of estate agents too, according to Levitt. Recent sales data shows that while estate agents still get a higher price for their own houses than comparable homes owned by their clients, since the proliferation of real estate websites, the gap between the two prices has shrunk by a third.

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The weakest link

According to Levitt, it isn’t only when people are acting as agents or experts that they are likely to abuse information. We are all likely to do so when it suits us – in job interviews or on a first date, for example. Since the days of the KKK, public displays of bigotry have been greatly curtailed. You wouldn’t now want to be perceived as bigoted while appearing in public. Levitt wanted to find out whether we could still find bigotry at play in public.

But how to test for discrimination in a public setting? Levitt found a way into the puzzle via the TV game show The Weakest Link (imported to the US from the UK) which he says provides a unique laboratory. After each round of trivia questions, the eight contestants vote to eliminate one other contestant. By measuring a contestant’s actual votes against the votes that would best serve their self-interest, it is possible to see if discrimination is at play.

In theory, self-interest should make players vote to eliminate the worse players in the early rounds of the game when the jackpot only grows if correct answers are given. In the later rounds, when the value of the jackpot is outweighed by each contestant’s desire to win the jackpot, they should eliminate the better players. So, for example, if a black man answers a lot of questions but is voted off early in the game, discrimination would seem to be at play. In fact, analysis of the results shows that there is no discrimination against blacks and women (the civil rights and feminist campaigns have demonised discrimination against these groups). But the results do show consistent discrimination against the elderly and Hispanics.

There is often a vast gulf between the information we publicly proclaim and the information we know to be true. Another example is Internet dating sites which offer massive amounts of information to be mined, particularly in response to the questions: how honest are people when sharing their personal information and what kind of personal information in personal ads is considered the most (and least) desirable?

We are used to politicians being economical with the truth but voters lie too. In the US, comparison of pre-election polls and actual election results shows they often tell pollsters beforehand they will vote for the black candidate but then vote for the white candidate on voting day.

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Drug dealers and their moms

“Conventional wisdom” is something that is simple, convenient, comfortable and comforting, but not necessarily true. Once created, it can be hard to budge.

Public perceptions of drug dealers, as Levitt shows, are one example. In the 1990s, the sudden appearance of crack cocaine had police departments across the US competing for resources. They claimed that it was not a fair fight; that the drug dealers had state-of-the-art weapons and limitless supplies of illicit cash. The millionaire drug dealer was a widely-accepted image. But, if drug dealers made so much money, asked Levitt, why were most of them still living at home? The answer, as in all the other stories, is to find the right data and very often the secret to that is to find the right person.

The right person in this story was a Chicago University PhD student who, despite the personal risks, spent six years living with and studying a gang of drug dealers. He discovered that, apart from a few big earners running the gangs, most dealers were earning less than the minimum wage so they had to live with their mothers. Given that it was also a highly dangerous occupation, why would anyone want to do it? Like aspiring film and sports stars, they want to succeed in an extremely competitive field where, if you get to the top, you are paid a fortune. Criminals, like everyone else, respond to incentives, says Levitt. If the prize is big enough, they will queue up for a chance to take part.

Levitt makes the point that drug gangs have a structure just like big corporations such as McDonald’s where the top bosses make great money and thousands of minions barely make the minimum wage. When there a lot of people willing and able to do a job, that job doesn’t generally pay well. In all glamour professions such as films, sports, publishing, or media (and drug dealing is seen as glamorous in poor neighbourhoods) there is a particular dynamic at play. Swarms of bright young people take on jobs that are poorly-paid and demand unstinting devotion. The rules of this “tournament” demand you start at the bottom to have a chance of getting to the top. To progress, you must show yourself to be not just above average but spectacular. Once you realise you won’t make it, you quit the tournament. (Not that the authors are suggesting that drug dealing is glamorous. As they recount, crack cocaine was generally a disaster for the black community in the US and put back its social progress by ten years.)

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Crime and abortion

Here we come to one of Levitt’s most notorious pieces of research and one that has snared him in controversy. In the 1990s, crime rates fell dramatically in the US, confounding previous predictions that crime was escalating out of control. Various explanations were put forward such as a booming economy, more gun control, and innovative policing strategies. Other proposed explanations included the increased use of capital punishment and the aging of the population.

None of these theories can explain the fall in crime, says Levitt. According to his analyses, the factor that most contributed to the massive crime drop was the legalisation of abortion throughout the states following a Supreme Court ruling 20 years earlier in 1973. An entire generation came of age minus the children whose mothers had not wanted to bring a child into the world. Unwanted children are more likely to become criminals later in life due to the neglect and abuse they suffer; legalised abortion led to less unwantedness. By preventing the birth of large numbers of children into adverse circumstances, it shrank the pool of potential criminals.

Levitt’s original paper in which these findings were first presented inevitably sparked a lot of controversy, especially amongst anti-abortionists. Levitt argued that he was not taking a moral stance on abortion, he was analysing in a detached way its impact on society. As he said, “When a scientist presents evidence that global warming is occurring, it doesn’t mean that he or she favours global warming.”

Levitt has also faced criticism from other economists who claim to have found flaws in his statistical test and who say he has stretched the data too far. In response, Levitt has said his thesis is based on a “collage of evidence” of which the test is just one piece

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Do parents matter?

Levitt is on scarcely less controversial ground when he turns to the question of parenting. We are assailed, he says, by advice on how to bring up children. Parenting experts contradict each other and sometimes themselves. They are very sure of their pet theories which often turn into conventional wisdom. They play on our fear that we will do the wrong thing in bringing up our kids. Separating facts from rumour is very hard.

For example, parents will forbid their children to play at the home of a friend whose parents keep a gun in the house but will happily let them play with a friend who has a swimming pool in the backyard. In fact, as Levitt shows, the statistics indicate that a child is 100 times more likely to die in a swimming pool accident than be shot by a gun.

The biggest shift in the conventional thinking on parenting concerns the question: how much do parents really matter? Bad parenting certainly matters – as the link between abortion and crime shows, unwanted children who are subject to neglect and abuse have worse outcomes than children who were wanted by their parents. But how much can the eager parents actually do for their children?

As Levitt says, it’s a very complicated issue. In determining a parent’s influence, for example, what dimensions should we measure – personality, school grades, his moral behaviour, his salary as an adult? Personality is not easily measured by data but school performance is. Levitt draws on a big project by the US Department of Education that has measured the academic progress of 20,000 children from kindergarten through the fifth grade and which includes data on whether the parents spanked their children, whether they took them to libraries or museums, how much TV they watched, etc. This data – if the right questions are asked of it – confirms some accepted ideas on parenting but provides some surprises as well. For instance:

  • Children whose parents are highly educated typically do well at school. But it doesn’t matter whether the family is intact or not – family structure does not affect academic abilities, which is encouraging for single parent families.
  • Children whose parents have a high socioeconomic status have higher test scores but moving to a better neighbourhood won’t improve a child’s chances in school.
  • A woman who doesn’t have her first child until she is at least 30 is likely to see that child do well at school, perhaps because she has progressed her education or career and has put herself and her children in a more advantageous position. But staying at home until the child goes to kindergarten does not provide any advantage.
  • Despite conventional wisdom, the amount of time watching TV has no impact on school performance. But neither does using a computer at home.
  • Children with many books in the home do well on school tests. But regularly reading to a child does not affect test scores.

Levitt concludes that parents who are well educated and successful tend to have children who test well in school, but it doesn’t seem to matter much whether a child is taken to museums or read to or put in front of the television. As Levitt says, this is sobering news for parents who are obsessed with parenting technique. It is not that parents don’t matter. They matter a great deal in some regards, most of which have been determined by the time the child was born. It matters not at all in others, the ones we obsess about. It’s not what you do as a parent; it’s who you are.

Levitt finishes with a chapter investigating whether the names that parents give their children affect their lives. Does someone with a distinctively black name suffer an economic penalty, for instance? (The black comedian Bill Cosby once gave a speech in which he criticised lower-income black people for various self-destructive behaviours, including giving their children “ghetto” names.) Levitt’s trawl through the data showed that on average someone with a distinctively “black” name in the US does have a worse life outcome than a person with a “white” name.

But it is not the fault of their names. If two black boys, one with a distinctively white name (e.g. Jake) and one with a distinctively black name (the most popular is DeShawn) grow up in the same neighbourhood and into the same family and economic circumstances, they will probably have similar life outcomes. But the kind of parents who call their son Jake don’t live in the same neighbourhoods or share economic circumstances with the kind of parents who call their son DeShawn. That is why on average a Jake will get more education and earn more money than a DeShawn. His name is an indicator, not a cause of his outcome.

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How to apply Freakonomics

So what’s the point of all these different stories and their associated statistical analyses (and the many others not mentioned here)? The authors say that, if the book has no unifying theme, there is a common thread running through it and the everyday application of Freakonomics. This is about thinking sensibly about how people behave in the real world. It requires a novel way of looking, discerning and measuring. The result, hopefully, will be to make you more sceptical of the conventional wisdom, to make you look at your collection of data from a new perspective, and to ask a lot of questions. Some of those questions won’t lead anywhere but others may well produce interesting, even surprising, answers.

Most of the authors’ stories, sumo wrestlers apart, draw on US experience, of course. We might wonder what surprises they would come up with if they turned their spotlight on UK data. On the other hand, their assertion that the answers are all to be found in the data does call to mind Darrel Huff’s classic little book of 1954 How to Lie with Statistics. Huff warned that we should always allow ourselves some degree of scepticism about the results of any statistical analysis as long as there is a possibility of bias somewhere. There always is, he said.

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