✪✪✪ Steven D. Levitts Freakonomics

Sunday, May 23, 2021 3:40:21 PM

Steven D. Levitts Freakonomics



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How to Think Like a Freak: Learn How to Make Smarter Decisions with the authors of Freakonomics

What Makes a Perfect Parent? The conversion of parenting from an art to a science. Why parenting experts like to scare parents to death. Which is more dangerous: a gun or a swimming pool? The economics of fear. Obsessive parents and the nature-nurture quagmire. A boy named Winner and his brother, Loser. The blackest names and the whitest names. If you have a really bad name, should you just change it? High-end names and low-end names and how one becomes the other. Britney Spears: a symptom, not a cause. Is Aviva the next Madison? What your parents were telling the world when they gave you your name. It is a sunny day in mid-June. But the car is quiet for now, as are the noontime streets: gas stations, boundless concrete, brick buildings with plywood windows.

An elderly homeless man approaches. It says he is homeless right on his sign, which also asks for money. He wears a torn jacket, too heavy for the warm day, and a grimy red baseball cap. Nor does he go scrounging for spare change. He just watches, as if through one-way glass. After a while, the homeless man moves along. Differently, too, than the average economist. This is either a wonderful trait or a troubling one, depending on how you feel about economists.

Levitt, a heralded young economist at the University of Chicago. He professed little interest in the sort of monetary issues that come to mind when most people think about economics; he practically blustered with selfeffacement. His investigations were a feast for anyone wanting to know how the world really works. His particular gift is the ability to ask such questions. For instance: If drug dealers make so much money, why do they still live with their mothers? Which is more dangerous, a gun or a swimming pool? What really caused crime rates to plunge during the past decade?

Why do black parents give their children names that may hurt their career prospects? Do schoolteachers cheat to meet high-stakes testing standards? Is sumo wrestling corrupt? But he has merely distilled the so-called dismal science to its most primal aim: explaining how people get what they want. Unlike most academics, he is unafraid of using personal observations and curiosities; he is also unafraid of anecdote and storytelling but he is afraid of calculus. He is an intuitionist. A former Tour de France champion called Levitt to ask his help in proving that the current Tour is rife with doping; the Central Intelligence Agency wanted to know how Levitt might use data to catch money launderers and terrorists.

All it takes is a new way of looking. In New York City, the publishers were telling Levitt he should write a book. Nor did he think himself much of a writer. But the two of them—henceforth known as the two of us—decided to talk things over to see if such a book might work. We decided it could. We hope you agree. He would be interviewed over dinner by the senior fellows, a collection of world-renowned philosophers, scientists, and historians. Could you explain it? He had no idea what his unifying theme was, or if he even had one.

Another fellow then offered another theme. And so it went, like dogs tugging at a bone, until the philosopher Robert Nozick interrupted. Why does he need to have a unifying theme? The culprit was crime. So too had carjacking and crack dealing, robbery and rape. Violent crime was a gruesome, constant companion. And things were about to get even worse. Much worse. All the experts were saying so. The cause was the so-called superpredator. For a time, he was everywhere. Glowering from the cover of newsweeklies. Swaggering his way through foot-thick government reports.

He was a scrawny, big-city teenager with a cheap gun in his hand and nothing in his heart but ruthlessness. In the criminologist James Alan Fox wrote a report for the U. Fox proposed optimistic and pessimistic scenarios. In the optimistic scenario, he believed, the rate of teen homicides would rise another 15 percent over the next decade; in the pessimistic scenario, it would more than double.

And then, instead of going up and up and up, crime began to fall. And fall and fall and fall some more. The crime drop was startling in several respects. It was ubiquitous, with every category of crime falling in every part of the country. It was persistent, with incremental decreases year after year. And it was entirely unanticipated—especially by the very experts who had been predicting the opposite. The magnitude of the reversal was astounding. So had the rate of just about every other sort of crime, from assault to car theft. Even though the experts had failed to anticipate the crime drop— which was in fact well under way even as they made their horrifying 4 I n t ro d u c t i o n : Th e H i d d e n S i d e of Eve r y t h i n g predictions—they now hurried to explain it.

Most of their theories sounded perfectly logical. It was the roaring s economy, they said, that helped turn back crime. It was the proliferation of gun control laws, they said. It was the sort of innovative policing strategies put into place in New York City, where murders would fall from 2, in to in If it was gun control and clever police strategies and betterpaying jobs that quelled crime—well then, the power to stop criminals had been within our reach all along. As it would be the next time, God forbid, that crime got so bad. In short course, they became conventional wisdom. There was another factor, meanwhile, that had greatly contributed to the massive crime drop of the s.

It had taken shape more than twenty years earlier and concerned a young woman in Dallas named Norma McCorvey. All she had wanted was an abortion. She was a poor, uneducated, unskilled, alcoholic, drug-using twenty-one-year-old woman who had already given up two children for adoption and now, in , found herself pregnant again. But in Texas, as in all but a few states at that time, abortion was illegal. They made her the lead plaintiff in a class-action lawsuit seeking to legalize abortion. The defendant was Henry Wade, the Dallas County district attorney. On January 22, , the court ruled in favor of Ms. Roe, allowing legalized abortion throughout the country. By this time, of course, it was far too late for Ms.

She had given birth and put the child up for adoption. Years later she would renounce her allegiance to legalized abortion and become a pro-life activist. So how did Roe v. Wade help trigger, a generation later, the greatest crime drop in recorded history? As far as crime is concerned, it turns out that not all children are born equal. Not even close. Decades of studies have shown that a child born into an adverse family environment is far more likely than other children to become a criminal. And the millions of women most likely to have an abortion in the wake of Roe v.

Wade—poor, unmarried, and teenage mothers for whom illegal abortions had been too expensive or too hard to get—were often models of adversity. They were the very women whose children, if born, would have been much more likely than average to become criminals. But because of Roe v. This powerful cause would have a drastic, distant effect: years later, just as these unborn children would have entered their criminal primes, the rate of crime began to plummet. It was, among other factors, the reality that the pool of potential criminals had dramatically shrunk.

Now, as the crime-drop experts the former crime doomsayers spun their theories to the media, how many times did they cite legalized abortion as a cause? She sizes up its charms, snaps some pictures, sets the price, writes a seductive ad, shows the house aggressively, negotiates the offers, and sees the deal through to its end. A real-estate agent is a different breed of expert than a criminologist, but she is every bit the expert. You depend on her for this information. That, in fact, is why you hired an expert. As the world has grown more specialized, countless such experts have made themselves similarly indispensable.

And they use that advantage to help you, the person who hired them, get exactly what you want for the best price. It would be lovely to think so. But experts are human, and humans respond to incentives. Sometimes his incentives may work in your favor. For instance: a study of California auto mechanics found they often passed up a small repair bill by letting failing cars pass emissions inspections—the reason being that 7 F R E A KO N O M I CS lenient mechanics are rewarded with repeat business.

In a medical study, it turned out that obstetricians in areas with declining birth rates are much more likely to perform cesarean-section deliveries than obstetricians in growing areas—suggesting that, when business is tough, doctors try to ring up more expensive procedures. The best way to do so would be to measure how an expert treats you versus how he performs the same service for himself.

Real-estate sales, however, are a matter of public record. And realestate agents often do sell their own homes. A recent set of data covering the sale of nearly , houses in suburban Chicago shows that more than 3, of those houses were owned by the agents themselves. Simple: to make the best deal possible. Presumably this is also your incentive when you are selling your home. Her commission, after all, is based on the sale price. But as incentives go, commissions are tricky. Each agent then kicks back half of her take to the agency. Which means that only 1. Still not bad, you say. Like a stockbroker churning commissions, she wants to make deals and make them fast. Why not? Of all the truisms about politics, one is held to be truer than the rest: money buys elections.

Arnold Schwarzenegger, Michael Bloomberg, Jon Corzine—these are but a few recent, dramatic examples of the truism at work. Indeed, election data show it is true that the candidate who spends more money in a campaign usually wins. But is money the cause of the victory? It might seem logical to think so, much as it might have seemed logical that a booming s economy helped reduce crime. But just because two things are correlated does not mean that one causes the other. Denver and Washington, D. Such wayward thinking, which has a long history, generally provokes a wayward response. Consider the folktale of the czar who learned that the most diseaseridden province in his empire was also the province with the most doctors.

His solution? He promptly ordered all the doctors shot dead. Just ask any presidential hopeful who bombs in Iowa and New Hampshire. So front-runners and incumbents raise a lot more money than long shots. And what about spending that money? Incumbents and frontrunners obviously have more cash, but they only spend a lot of it when they stand a legitimate chance of losing; otherwise, why dip into a war chest that might be more useful later on, when a more formidable opponent appears? Now picture two candidates, one intrinsically appealing and the other not so. The appealing candidate raises much more money and wins easily.

But was it the money that won him the votes, or was it his appeal that won the votes and the money? How can it be measured? The key is to measure a candidate against. That is, Candidate A today is likely to be similar to Candidate A two or four years hence. The same could be said for Candidate B. If only Candidate A ran against Candidate B in two consecutive elections but in each case spent different amounts of money. As it turns out, the same two candidates run against each other in consecutive elections all the time—indeed, in nearly a thousand U. What do the numbers have to say about such cases?

A winning candidate can cut his spending in half and lose only 1 percent of the vote. What really matters for a political candidate is not how much you spend; what matters is who you are. The same could be said—and will be said, in chapter 5—about parents. It is the same amount, for instance, that Americans spend every year on chewing gum. It will certainly address these scenarios and dozens more, from the art of parenting to the mechanics of cheating, from the inner workings of the Ku Klux Klan to racial discrimination on The Weakest Link. What this book is about is stripping a layer or two from the surface of modern life and seeing what is happening underneath.

We will ask a lot of questions, some frivolous and some about life-and-death issues. The answers may often seem odd but, after the fact, also rather obvious. It is well and good to opine or theorize about a subject, as humankind is wont to do, but when moral posturing is replaced by an honest assessment of the data, the result is often a new, surprising insight. Morality, it could be argued, represents the way that people would like the world to work—whereas economics represents how it actually does work. Economics is above all a science of measurement. But the tools of economics can be just as easily applied to subjects that are more—well, more interesting. And understanding them—or, often, ferreting them out—is the key to solving just about any riddle, from violent crime to sports cheating to online dating.

The conventional wisdom is often wrong. Dramatic effects often have distant, even subtle, causes. The answer to a given riddle is not always right in front of you. Norma McCorvey had a far greater impact on crime than did the combined forces of gun control, a strong economy, and innovative police strategies. However, they can be beat at their own game. Knowing what to measure and how to measure it makes a complicated world much less so. If you learn how to look at data in the right way, you can explain riddles that otherwise might have seemed impossible. Because there is nothing like the sheer power of numbers to scrub away layers of confusion and contradiction.

So the aim of this book is to explore the hidden side of. This may occasionally be a frustrating exercise. It may sometimes feel as if we are peering at the world through a straw or even staring into a funhouse mirror; but the idea is to look at many different scenarios and examine them in a way they have rarely been examined. In some regards, this is a strange concept for a book. Most books put forth a single theme, crisply expressed in a sentence or two, and then tell the entire story of that theme: the history of salt; the fragility of democracy; the use and misuse of punctuation.

This book boasts no such unifying theme. We did consider, for about six minutes, writing a book that would revolve around a single theme—the theory and practice of applied microeconomics, anyone? Yes, this approach employs the best analytical tools that economics can offer, but it also allows us to follow whatever freakish curiosities may occur to us. The sort of stories told in this book are not often covered in Econ.

Since the science of economics is primarily a set of tools, as opposed to a subject matter, then no subject, however offbeat, need be beyond its reach. He strove to be a moralist and, in doing so, became an economist. When he published 14 I n t ro d u c t i o n : Th e H i d d e n S i d e of Eve r y t h i n g The Theory of Moral Sentiments in , modern capitalism was just getting under way. It was the human effect, the fact that economic forces were vastly changing the way a person thought and behaved in a given situation.

The gravity and shock of these changes were as overwhelming to the citizens of his time as the gravity and shock of modern life seem to us today. The economic historian Robert Heilbroner, writing in The Worldly Philosophers, wondered how Smith was able to separate the doings of man, a creature of self-interest, from the greater moral plane in which man operated. These explorations generally begin with the asking of a simple unasked question. Such as: what do schoolteachers and sumo wrestlers have in common? But given the right data, I have little doubt that I could figure out the answer. Just as it must have seemed absurd if you were a Chicago schoolteacher, called into an office and told that, ahem, the algorithms designed by that skinny man with thick glasses had determined that you are a cheater.

And that you are being fired. Steven Levitt may not fully believe in himself, but he does believe in this: teachers and criminals and real-estate agents may lie, and politicians, and even CIA analysts. Imagine for a moment that you are the manager of a day-care center. You have a clearly stated policy that children are supposed to be picked up by 4 p. But very often parents are late. What to do? Why, after all, should the day-care center take care of these kids for free? The economists decided to test their solution by conducting a study of ten day-care centers in Haifa, Israel. Before long there were twenty late pickups per week, more than double the original average.

Economics is, at root, the study of incentives: how people get what they want, or need, especially when other people want or need the same thing. Economists love incentives. They love to dream them up and enact them, study them and tinker with them. An incentive is a bullet, a lever, a key: an often tiny object with astonishing power to change a situation. We all learn to respond to incentives, negative and positive, from the outset of life. If you are spotted picking your nose in class, you get ridiculed. But if you make the basketball team, you move up the social ladder. If you break curfew, you get grounded. But if you ace your SATs, you get to go to a good college. But if you perform so well that a rival company comes calling, you become a vice president and no longer have to work for your father.

An incentive is simply a means of urging people to do more of a good thing and less of a bad thing. Someone—an economist or a politician or a parent—has to invent them. Your three-year-old eats all her vegetables for a week? She wins a trip to the toy store. A big steelmaker belches too much smoke into the air? Very often a single incentive scheme will include all three varieties. Think about the anti-smoking campaign of recent years. The banning of cigarettes in restaurants and bars is a powerful social incentive. And when the U. Some of the most compelling incentives yet invented have been put in place to deter crime.

Considering this fact, it might be worthwhile to take a familiar question—why is there so much crime in modern society? After all, every one of us regularly passes up opportunities to maim, steal, and defraud. The chance of going to jail—thereby losing your job, your house, and your freedom, all of which are essentially economic penalties—is certainly a strong incentive. For certain types of misbehavior, social incentives are terribly powerful. So through a complicated, haphazard, and constantly readjusted web of economic, social, and moral incentives, modern society does its best to militate against crime.

But taking the long view, that is clearly not true. So what was wrong with the incentive at the Israeli day-care centers? That would have likely put an end to the late pickups, though it would have also engendered plenty of ill will. Any incentive is inherently a trade-off; the trick is to balance the extremes. For just a few dollars each day, parents could buy off their guilt. Such is the strange and powerful nature of incentives. A slight tweak can produce drastic and often unforeseen results. In this case, they wanted to learn about the motivation behind blood donations.

Their discovery: when people are given a small stipend for donating blood rather than simply being praised for their altruism, they tend to donate less blood. Surely the number of donors would have changed dramatically. But something else would have changed dramatically as well, for every incentive has its dark side. They might literally steal blood at knifepoint. They might pass off pig blood as their own. They might circumvent donation limits by using fake IDs.

Whatever the incentive, whatever the situation, dishonest people will try to gain an advantage by whatever means necessary. Or, as W. Fields once said: a thing worth having is a thing worth cheating for. Who cheats? Well, just about anyone, if the stakes are right. And then you might remember the time you cheated on, say, a board game. Last week. Or the golf ball you nudged out of its bad lie. And then took the bagel anyway. For every clever person who goes to the trouble of creating an in24 Schoolteachers and Sumo Wrestlers centive scheme, there is an army of people, clever and otherwise, who will inevitably spend even more time trying to beat it.

Cheating may or may not be human nature, but it is certainly a prominent feature in just about every human endeavor. Cheating is a primordial economic act: getting more for less. It is the waitress who pockets her tips instead of pooling them. It is the third grader who, worried about not making it to the fourth grade, copies test answers from the kid sitting next to him.

Some cheating leaves barely a shadow of evidence. In other cases, the evidence is massive. Consider what happened one spring evening at midnight in seven million American children suddenly disappeared. The worst kidnapping wave in history? It was the night of April 15, and the Internal Revenue Service had just changed a rule. The incentive for those cheating taxpayers was quite clear. The same for the waitress, the payroll manager, and the third grader. Might she have an incentive to cheat? And if so, how would she do it?

Imagine now that instead of running a day-care center in Haifa, you are running the Chicago Public Schools, a system that educates , students each year. The stakes are considered high because instead of simply testing students to measure their progress, schools are increasingly held accountable for the results. The federal government mandated high-stakes testing as part of the No Child Left Behind law, signed by President Bush in But even before that law, most states gave annual standardized tests to students in elementary and secondary school.

The Chicago Public School system embraced high-stakes testing in Under the new policy, a school with low reading scores would be placed on probation and face the threat of being shut down, its staff to be dismissed or reassigned. The CPS also did away with what is known as social promotion. Now, in order to be promoted, every student in third, sixth, and eighth grade had to manage a minimum score on the standardized, multiple-choice exam known as the Iowa Test of Basic Skills. Advocates of high-stakes testing argue that it raises the standards of learning and gives students more incentive to study.

Schoolchildren, of course, have had incentive to cheat for as long as there have been tests. But high-stakes testing has so radically changed the incentives for teachers that they too now have added reason to cheat. With high-stakes testing, a teacher whose students test 26 Schoolteachers and Sumo Wrestlers poorly can be censured or passed over for a raise or promotion. High-stakes testing also presents teachers with some positive incentives. How might a teacher go about cheating? There are any number of possibilities, from the brazen to the sophisticated. A teacher can simply give students extra time to complete the test.

And you always thought that no. If this kind of teacher cheating is truly going on, how might it be detected? To catch a cheater, it helps to think like one. That would clearly be a tip-off. Nor, in all likelihood, would you have enough time, because the answer sheets are turned in soon after the test is over. You might even think to focus your activity toward the end of the test, where the questions tend to be harder than the earlier questions. If economics is a science primarily concerned with incentives, it is also—fortunately—a science with statistical tools to measure how people respond to those incentives. All you need are some data. In this case, the Chicago Public School system obliged. It made available a database of the test answers for every CPS student from third grade through seventh grade from to This amounts to roughly 30, students per grade per year, more than , sets of test answers, and nearly million individual answers.

The actual paper answer sheets were not included; they were habitually shredded soon 28 Schoolteachers and Sumo Wrestlers after a test. The data also included some information about each teacher and demographic information for every student, as well as his or her past and future test scores—which would prove a key element in detecting the teacher cheating. Now it was time to construct an algorithm that could tease some conclusions from this mass of data. Consider now the answer strings from the students in two sixthgrade Chicago classrooms who took the identical math test. The letter a, b, c, or d indicates a correct answer; a number indicates a wrong answer, with 1 corresponding to a, 2 corresponding to b, and so on. A zero represents an answer that was left blank.

Here again are the answer strings from classroom A, now reordered by a computer that has been asked to apply the cheating algorithm and seek out suspicious patterns. Classroom A With cheating algorithm applied 1. There are at least four reasons this is unlikely. One: those questions, coming near the end of the test, were harder than the earlier questions.

Two: these were mainly subpar students to begin with, few of whom got six consecutive right answers elsewhere on the test, making it all the more unlikely they would get right the same six hard questions. Four: three of the students numbers 1, 9, and 12 left at least one answer blank before the suspicious string and then ended the test with another string of blanks. This suggests that a long, unbroken string of blank answers was broken not by the student but by the teacher.

There is another oddity about the suspicious answer string. Perhaps she is merely being strategic. With standardized tests, the teacher is typically not given an answer key. As sixth graders who were taking the test in the eighth month of the academic year, these students needed to achieve an average score of 6. Fifth graders taking the test in the eighth month of the year needed to score 5. The students in classroom A averaged 5. So plainly these are poor students. A year earlier, however, these students did even worse, averaging just 4. But this miraculous improvement was short-lived. When these sixth-grade students reached seventh grade, they averaged 5.

So an entire roomful of children in classroom A suddenly got very smart one year and very dim the next, or more likely, their sixth-grade teacher worked some magic with a no. There are two noteworthy points to be made about the children in classroom A, tangential to the cheating itself. The second point is that these students would be in for a terrible shock once they reached the seventh grade. All they knew was that they had been successfully promoted due to their test scores.

No child left behind, indeed. This may be the cruelest twist yet in high-stakes testing. A cheating teacher may tell herself that she is helping her students, but the fact is that she would appear far more concerned with helping herself. An analysis of the entire Chicago data reveals evidence of teacher cheating in more than two hundred classrooms per year, roughly 5 percent of the total. What are the characteristics of a cheating teacher? The Chicago data show that male and female teachers are about equally prone to cheating. She is also more likely to cheat after her incentives change. Because the Chicago data ran from to , it bracketed the introduction of high-stakes testing in Sure enough, there was a pronounced spike in cheating in Nor was the cheating random.

It was the teachers in the lowest-scoring classrooms who were most likely to cheat. Not every result of the Chicago cheating analysis was so dour. In addition to detecting cheaters, the algorithm could also identify the best teachers in the school system. Instead of getting random answers correct, her students would show real improvement on the easier types of questions they had previously missed, an indication of actual learning. Most academic analyses of this sort tend to languish, unread, on a dusty library shelf. Duncan was an unlikely candidate to hold such a powerful job. He was only thirty-six when appointed, a onetime academic allAmerican at Harvard who later played pro basketball in Australia.

His father taught psychology at the University of Chicago; his mother ran an afterschool program for forty years, without pay, in a poor neighborhood. When Duncan was a boy, his afterschool playmates were the underprivileged kids his mother cared for. So when he took over the public schools, his allegiance lay more with schoolchildren and their families than with teachers and their union. The best way to get rid of cheating teachers, Duncan had decided, was to readminister the standardized exam.

He only had the resources to retest classrooms, however, so he asked the creators of the cheating algorithm to help choose which classrooms to test. How could those retests be used most effectively? It might have seemed sensible to retest only the classrooms that likely had a cheating teacher. To make the retest results convincing, some non-cheaters were needed as a control group. The best control group? The classrooms shown by the algorithm to have the best teachers, in which big gains were thought to have been legitimately attained. So a blend was settled upon. More than half of the retested classrooms were those suspected of having a cheating teacher. The remainder were divided between the supposedly excellent teachers high scores but no suspicious answer patterns and, as a further control, classrooms with mediocre scores and no suspicious answers.

The retest was given a few weeks after the original exam. The chil36 Schoolteachers and Sumo Wrestlers dren were not told the reason for the retest. Neither were the teachers. The teachers were asked to stay in the classroom with their students, but they would not be allowed to even touch the answer sheets. The results were as compelling as the cheating algorithm had predicted. In the classrooms chosen as controls, where no cheating was suspected, scores stayed about the same or even rose. The evidence was only strong enough to get rid of a dozen of them, but the many other cheaters had been duly warned.

You might think that the sophistication of teachers who cheat would increase along with the level of schooling. But an exam given at the University of Georgia in the fall of disputes that idea. Among the questions: How many halves are in a college basketball game? Eye Exam b. How Do the Grits Taste Exam c. Bug Control Exam d. Ron Jirsa b. John Pelphrey c. Jim Harrick Jr. It might also help to know that his father, Jim Harrick Sr. Every student in the class received an A. Not long afterward, both Harricks were relieved of their coaching duties.

If it strikes you as disgraceful that Chicago schoolteachers and University of Georgia professors will cheat—a teacher, after all, is meant to instill values along with the facts—then the thought of cheating among sumo wrestlers may also be deeply disturbing. Indeed, sumo is said to be less about competition than about honor itself. It is true that sports and cheating go hand in hand. Olympic sprinters and weightlifters, cyclists in the Tour de France, football linemen and baseball sluggers: they have all been shown to swallow whatever pill or powder may give them an edge. It is not only the participants who cheat.

The man accused of orchestrating the vote swap, a reputed Russian mob boss named Alimzhan Tokhtakhounov, was also suspected of rigging beauty pageants in Moscow. An athlete who gets caught cheating is generally condemned, but most fans at least appreciate his motive: he wanted so badly to win that he bent the rules. The Chicago White Sox, who conspired with gamblers to throw the World Series and are therefore known forever as the Black Sox , retain a stench of iniquity among even casual baseball fans. Otherwise, he could have had class; he could have been a contender. Could it? Once again, the data can tell the story. The incentive scheme that rules sumo is intricate and extraordinarily powerful.

Each wrestler maintains a ranking that affects every slice of his life: how much money he makes, how large an entourage he carries, how much he gets to eat, sleep, and otherwise take advantage of his success. The sixty-six highest-ranked wrestlers in Japan, comprising the makuuchi and juryo divisions, make up the sumo elite. A wrestler near the top of this elite pyramid may earn millions and is treated like royalty.

Low-ranked wrestlers must tend to their superiors, preparing their meals and cleaning their quarters and even soaping up their hardestto-reach body parts. So ranking is everything. If he has a losing record, his ranking falls. If it falls far enough, he is booted from the elite rank entirely. The eighth victory in any tournament is therefore critical, the difference between promotion and demotion; it is roughly four times as valuable in the rankings as the typical victory. How might we measure the data to prove it? The right column shows how often the 7—7 wrestler actually did win.

This makes sense; their records in this tournament indicate that the 8—6 wrestler is slightly better. But perhaps there are further clues in the data that prove collusion. Maybe he accepts a bribe which would obviously not be recorded in the data. Or perhaps some other arrangement is made between the two wrestlers. Keep in mind that the pool of elite sumo wrestlers is extraordinarily tight-knit. Furthermore, each wrestler belongs to a stable that is typically managed by a former sumo champion, so even the rival stables have close ties. Wrestlers from the same stable do not wrestle one another. In this case, there is no great pressure on the individual match. So you might expect the wrestlers who won their 7—7 matches in the previous tournament to do about as well as they had in earlier matches against these same opponents—that is, winning roughly 50 percent of the time.

Eighty percent in one match and 40 percent in the next? How do you make sense of that? The collective records of the various sumo stables are similarly aberrational. No formal disciplinary action has ever been taken against a Japanese sumo wrestler for match rigging. People tend to get defensive when the integrity of their national sport is impugned. These occasional media storms offer one more chance to measure possible corruption in sumo.

Media scrutiny, after all, creates a powerful incentive: if two sumo wrestlers or their stables have been rigging matches, they might be leery to continue when a swarm of journalists and TV cameras descend upon them. Several years ago, two former sumo wrestlers came forward with extensive allegations of match rigging—and more. The two men began to receive threatening phone calls; one of them told friends he was afraid he would be killed by the yakuza. But shortly beforehand, the two men died—hours apart, in the same hospital, of a similar respiratory ailment. The police declared there had been no foul play but did not conduct an investigation. In matches between two supposedly corrupt wrestlers, the wrestler who was on the bubble won about 80 percent of the time.

In bubble matches against a supposedly clean opponent, meanwhile, the bubble wrestler was no more likely to win than his record would predict. So if sumo wrestlers, schoolteachers, and day-care parents all cheat, are we to assume that mankind is innately and universally corrupt? And if so, how corrupt? The answer may lie in. Consider the true story of a man named Paul Feldman. Once upon a time, Feldman dreamed big dreams. Trained as an agricultural economist, he wanted to tackle world hunger. Instead, he took a job in Washington, analyzing weapons expenditures for the U.

This was in For the next twenty-odd years, he did more of the same. Then he made it a habit. Every Friday, he would bring in some bagels, a serrated knife, and cream cheese. In order to recoup his costs, he set out a cash basket and a sign with the suggested price. His collection rate was about 95 percent; he attributed the underpayment to oversight, not fraud. In , when his research institute fell under new management, Feldman took a look at his career and grimaced.

He decided to quit his job and sell bagels. It was an honor-system commerce scheme, and it worked. Within a few years, Feldman was delivering 8, bagels a week to companies and earning as much as he had ever made as a research analyst. He had thrown off the shackles of cubicle life and made himself happy. He had also—quite without meaning to—designed a beautiful economic experiment. From the beginning, Feldman kept rigorous data on his business. So by measuring the money collected against the bagels taken, he found it possible to tell, down to the penny, just how honest his customers were.

Did they steal from him? If so, what were the characteristics of a company that stole versus a company that did not? Under what circumstances did people tend to steal more, or less? Yes, shorting the bagel man is white-collar crime, writ however small. It might seem ludicrous to address as large and intractable a problem as white-collar crime through the life of a bagel man. But often a small and simple question can help chisel away at the biggest problems. Despite all the attention paid to rogue companies like Enron, academics know very little about the practicalities of white-collar crime. The reason? There are no good data. A key fact of white-collar crime is that we hear about only the very slim fraction of people who are caught cheating.

Most embezzlers lead quiet and theoretically happy lives; employees who steal company property are rarely detected. With street crime, meanwhile, that is not the case. A mugging or a 46 Schoolteachers and Sumo Wrestlers burglary or a murder is usually tallied whether or not the criminal is caught. A street crime has a victim, who typically reports the crime to the police, who generate data, which in turn generate thousands of academic papers by criminologists, sociologists, and economists.

But white-collar crime presents no obvious victim. From whom, exactly, did the masters of Enron steal? It did present a victim. The victim was Paul Feldman. Not only that, but those bagel eaters knew the provider and had feelings presumably good ones about him. A broad swath of psychological and economic research has shown that people will pay different amounts for the same item depending on who is providing it.

In the real world, Feldman learned to settle for less than 95 percent. In the beginning, Feldman left behind an open basket for the cash, but too often the money vanished. Then he tried a coffee can with a money slot in its plastic lid, which also proved too tempting. In the end, he resorted to making small plywood boxes with a slot cut into the top. The wooden box has worked well. Each year he drops off about seven thousand boxes and loses, on average, just one to theft.

This is an intriguing statistic: the same people who routinely steal more than 10 percent of his bagels almost never stoop to stealing his money box—a tribute to the nuanced social calculus of theft. So what do the bagel data have to say? In recent years, there have been two noteworthy trends in the overall payment rate. By the summer of , the overall rate had slipped to about 87 percent. Or it may have represented a more general surge in empathy. This may seem counterintuitive. There is far less street crime per capita in rural areas than in cities, in large part because a rural criminal is more likely to be known and therefore caught.

Also, a smaller community tends to exert greater social incentives against crime, the main one being shame. Weather, for instance, is a major factor. Unseasonably pleasant weather inspires people to pay at a higher rate. Worst are the holidays. The difference in the two sets of holidays? The low-cheating holidays represent little more than an extra day off from work. The high-cheating holidays are fraught with miscellaneous anxieties and the high expectations of loved ones.

Feldman has also reached some of his own conclusions about honesty, based more on his experience than the data. Feldman wondered if perhaps the executives cheated out of an overdeveloped sense of entitlement. Yes, a lot of people steal from him, but the vast majority, even though no one is watching over them, do not. But it would not have surprised Adam Smith. A student named Glaucon offered the story in response to a lesson by Socrates— who, like Adam Smith, argued that people are generally good even without enforcement. He told of a shepherd named Gyges who stumbled upon a secret cavern with a corpse inside that wore a ring. When Gyges put on the ring, he found that it made him invisible. With no one able to 50 Schoolteachers and Sumo Wrestlers monitor his behavior, Gyges proceeded to do woeful things—seduce the queen, murder the king, and so on.

Glaucon seemed to think the answer was no. But Paul Feldman sides with Socrates and Adam Smith—for he knows that the answer, at least 87 percent of the time, is yes. But he has shown other economists just how well their tools can make sense of the real world. Camerer, an economist at the California Institute of Technology. As institutions go, the Ku Klux Klan has had a markedly up-anddown history. It was founded in the immediate aftermath of the Civil War by six former Confederate soldiers in Pulaski, Tennessee. In the beginning, their activities were said to be harmless midnight pranks—riding horses through the countryside while draped in white sheets and pillowcase hoods.

But soon the Klan evolved into a multistate terrorist organization designed to frighten and kill emancipated slaves. In , President Ulysses S. Within barely a decade, however, the Klan had been extinguished, largely by legal and military interventions out of Washington, D. But if the Klan itself was defeated, its aims had largely been achieved through the establishment of Jim Crow laws. Congress, which during Reconstruction had been quick to enact measures of legal, social, and economic freedom for blacks, just as quickly began to roll them back. The federal government agreed to withdraw its occupation troops from the South, allowing the restoration of white rule.

In Plessy v. Ferguson, the U. Supreme Court gave the go-ahead to full-scale racial segregation. The Ku Klux Klan lay largely dormant until , when D. By the s, a revived Klan claimed eight million members, including President Warren G. Public sentiment turned against the Klan as the unity of a country at war trumped its message of separatism. But within a few years, there were already signs of a massive revival. Stetson, founder of the famed hat company and the man for whom Stetson University was named. He professed little interest in the sort of monetary issues that come to mind when most people think about economics; he practically blustered with self-effacement.

His investigations were a feast for anyone wanting to know how the world really works. His particular gift is the ability to ask such questions. For instance: If drug dealers make so much money, why do they still live with their mothers? Which is more dangerous, a gun or a swimming pool? What really caused crime rates to plunge during the past decade? Why do black parents give their children names that may hurt their career prospects? Do schoolteachers cheat to meet high-stakes testing standards? Is sumo wrestling corrupt? But he has merely distilled the so-called dismal science to its most primal aim: explaining how people get what they want.

Unlike most academics, viii An Explanatory Note he is unafraid of using personal observations and curiosities; he is also unafraid of anecdote and storytelling although he is afraid of calculus. He is an intuitionist. A former Tour de France champion called Levitt to ask his help in proving that the current Tour is rife with doping; the Central Intelligence Agency wanted to know how Levitt might use data to catch money launderers and terrorists.

All it takes is a new way of looking. In New York City, the publishers were telling Levitt he should write a book. Nor did he think himself much of a writer. But the two of them—henceforth known as the two of us—decided to talk things over to see if such a book might work. We decided it could. We hope you agree. But we are very happy, and grateful, to have been wrong. So why bother with a revised edition? There are a few reasons. But because Freakonomics explores all sorts of modern real-world issues, and because the modern world tends to change quite fast, we have gone through the book and made a number of minor updates.

Also, we made some mistakes. It was usually a reader who would bring a mistake to our attention, and we very much appreciate this input. Again, most of these changes are quite minor. As unpleasant as it was to acknowledge this error, and to diminish the reputation of a man beloved in many quarters, we felt it was important to set straight the historical record. We have also futzed a bit with the architecture of the book. There, it can be easily skipped over if one so chooses, or read in isolation. We have included in this edition several of these columns, on subjects ranging from voting behavior to dog poop to the economics of sexual preference.

We have also included a variety of writings from our blog www. We blogged reluctantly, tentatively, infrequently. But as the months went on, and as we discovered an audience of people who had read Freakonomics and xii P re fa ce to t h e Rev i se d a n d E x pa n d e d Ed i t i o n were eager to bat its ideas back and forth, we took to it more enthusiastically. The culprit was crime. So too had carjacking and crack dealing, robbery and rape. Violent crime was a gruesome, constant companion. And things were about to get even worse. Much worse. All the experts were saying so.

The cause was the so-called superpredator. For a time, he was everywhere. Glowering from the cover of newsweeklies. Swaggering his way through foot-thick government reports. He was a scrawny, big-city teenager with a cheap gun in his hand and nothing in his heart but ruthlessness. In the criminologist James Alan Fox wrote a report for the U. Fox proposed optimistic and pessimistic scenarios. In the optimistic scenario, he believed, the rate of teen homicides would rise another 15 percent over the next decade; in the pessimistic scenario, it would more than double. And then, instead of going up and up and up, crime began to fall.

And fall and fall and fall some more. The crime drop was startling in several respects. It was ubiquitous, with every category of crime falling in every part of the country. It was persistent, with incremental decreases year after year. And it was entirely unanticipated—especially by the very experts who had been predicting the opposite. The magnitude of the reversal was astounding. So had the rate of just about every other sort of crime, from assault to car theft. Even though the experts had failed to anticipate the crime drop— which was in fact well under way even as they made their horrifying 2 I n t ro d u c t i o n : Th e H i d d e n S i d e of Eve r y t h i n g predictions—they now hurried to explain it. Most of their theories sounded perfectly logical.

It was the roaring s economy, they said, that helped turn back crime. It was the proliferation of gun control laws, they said. It was the sort of innovative policing strategies put into place in New York City, where murders would fall from 2, in to in If it was gun control and clever police strategies and betterpaying jobs that quelled crime—well then, the power to stop criminals had been within our reach all along. As it would be the next time, God forbid, that crime got so bad. In short course, they became conventional wisdom. There was another factor, meanwhile, that had greatly contributed to the massive crime drop of the s. It had taken shape more than twenty years earlier and concerned a young woman in Dallas named Norma McCorvey. All she had wanted was an abortion.

She was a poor, uneducated, unskilled, alcoholic, drug-using twenty-one-year-old woman who had already given up two children for adoption and now, in , found herself pregnant again. But in Texas, as in all but a few states at that time, abortion was illegal. They made her the lead plaintiff in a class-action lawsuit seeking to legalize abortion. The defendant was Henry Wade, the Dallas County district attorney. On January 22, , the court ruled in favor of Ms. Roe, allowing legalized abortion throughout the United States.

By this time, of course, it was far too late for Ms. She had given birth and put the child up for adoption. Years later she would renounce her allegiance to legalized abortion and become a pro-life activist. So how did Roe v. Wade help trigger, a generation later, the greatest crime drop in recorded history? As far as crime is concerned, it turns out that not all children are born equal. Not even close. Decades of studies have shown that a child born into an adverse family environment is far more likely than other children to become a criminal. And the millions of women most likely to have an abortion in the wake of Roe v. Wade—poor, unmarried, and teenage mothers for whom illegal abortions had been too expensive or too hard to get—were often models of adversity.

They were the very women whose children, if born, would have been much more likely than average to become criminals. But because of Roe v. This powerful cause would have a drastic, distant effect: years later, just as these unborn children would have entered their criminal primes, the rate of crime began to plummet. It was, among other factors, the reality that the pool of potential criminals had dramatically shrunk. Now, as the crime-drop experts the former crime doomsayers spun their theories to the media, how many times did they cite legalized abortion as a cause?

She sizes up its charms, snaps some pictures, sets the price, writes a seductive ad, shows the house aggressively, negotiates the offers, and sees the deal through to its end. A real-estate agent is a different breed of expert than a criminologist, but she is every bit the expert. You depend on her for this information. That, in fact, is why you hired an expert. As the world has grown more specialized, countless such experts have made themselves similarly indispensable. And they use that advantage to help you, the person who hired them, get exactly what you want for the best price. It would be lovely to think so. But experts are human, and humans respond to incentives. Sometimes his incentives may work in your favor. For instance: a study of California auto mechanics found they often passed up a small repair bill by letting failing cars pass emissions inspections—the reason being that 5 F R E A KO N O M I CS lenient mechanics are rewarded with repeat business.

In a medical study, it turned out that obstetricians in areas with declining birth rates are much more likely to perform cesarean-section deliveries than obstetricians in growing areas—suggesting that, when business is tough, doctors try to ring up more expensive procedures. The best way to do so would be to measure how an expert treats you versus how he performs the same service for himself. Real-estate sales, however, are a matter of public record. And realestate agents often do sell their own homes. A recent set of data covering the sale of nearly , houses in suburban Chicago shows that more than 3, of those houses were owned by the agents themselves.

Simple: to make the best deal possible. Presumably this is also your incentive when you are selling your home. Her commission, after all, is based on the sale price. But as incentives go, commissions are tricky. Each agent then kicks back roughly half of her take to the agency. Which means that only 1. Still not bad, you say. Like a stockbroker churning commissions, she wants to make deals and make them fast. Why not? Of all the truisms about politics, one is held to be truer than the rest: money buys elections.

Arnold Schwarzenegger, Michael Bloomberg, Jon Corzine—these are but a few recent, dramatic examples of the truism at work. Indeed, election data show it is true that the candidate who spends more money in a campaign usually wins. But is money the cause of the victory? It might seem logical to think so, much as it might have seemed logical that a booming s economy helped reduce crime. But just because two things are correlated does not mean that one causes the other. Denver and Washington, D. Such wayward thinking, which has a long history, generally provokes a wayward response. Consider the folktale of the czar who learned that the most diseaseridden province in his empire was also the province with the most doctors. His solution?

He promptly ordered all the doctors shot dead. Just ask any presidential hopeful who bombs in Iowa and New Hampshire. So front-runners and incumbents raise a lot more money than long shots. And what about spending that money? Incumbents and frontrunners obviously have more cash, but they only spend a lot of it when they stand a legitimate chance of losing; otherwise, why dip into a war chest that might be more useful later on, when a more formidable opponent appears? Now picture two candidates, one intrinsically appealing and the other not so. The appealing candidate raises much more money and wins easily. But was it the money that won him the votes, or was it his appeal that won the votes and the money?

How can it be measured? The key is to measure a candidate against. That is, Candidate A today is likely to be similar to Candidate A two or four years hence. The same could be said for Candidate B. If only Candidate A ran against Candidate B in two consecutive elections but in each case spent different amounts of money. As it turns out, the same two candidates run against each other in consecutive elections all the time—indeed, in nearly a thousand U.

What do the numbers have to say about such cases? Meanwhile, a losing candidate who doubles his spending can expect to shift the vote in his favor by only that same 1 percent. What really matters for a political candidate is not how much you spend; what matters is who you are. The same could be said—and will be said, in chapter 5—about parents. It is the same amount, for instance, that Americans spend every year on chewing gum. It will certainly address these scenarios and dozens more, from the art of parenting to the mechanics of cheating, from the inner workings of a crack-selling gang to racial discrimination on The Weakest Link. What this book is about is stripping a layer or two from the surface of modern life and seeing what is happening underneath.

We will ask a lot of questions, some frivolous and some about life-and-death issues. The answers may often seem odd but, after the fact, also rather obvious. It is well and good to opine or theorize about a subject, as humankind is wont to do, but when moral posturing is replaced by an honest assessment of the data, the result is often a new, surprising insight. Morality, it could be argued, represents the way that people would like the world to work—whereas economics represents how it actually does work.

Economics is above all a science of measurement. But the tools of economics can be just as easily applied to subjects that are more—well, more interesting. And understanding them—or, often, ferreting them out—is the key to solving just about any riddle, from violent crime to sports cheating to online dating. The conventional wisdom is often wrong. Dramatic effects often have distant, even subtle, causes.

The answer to a given riddle is not always right in front of you. Norma McCorvey had a far greater impact on crime than did the combined forces of gun control, a strong economy, and innovative police strategies. However, they can be beat at their own game. Knowing what to measure and how to measure it makes a complicated world much less so. If you learn to look at data in the right way, you can explain riddles that otherwise might have seemed impossible. Because there is nothing like the sheer power of numbers to scrub away layers of confusion and contradiction.

So the aim of this book is to explore the hidden side of. This may occasionally be a frustrating exercise. It may sometimes feel as if we are peering at the world through a straw or even staring into a funhouse mirror; but the idea is to look at many different scenarios and examine them in a way they have rarely been examined. In some regards, this is a strange concept for a book. Most books put forth a single theme, crisply expressed in a sentence or two, and then tell the entire story of that theme: the history of salt; the fragility of democracy; the use and misuse of punctuation. This book has no such unifying theme. We did consider, for about six minutes, writing a book that would revolve around a single theme—the theory and practice of applied microeconomics, anyone?

Yes, this approach employs the best analytical tools that economics can offer, but it also allows us to follow whatever freakish curiosities may occur to us. The sort of stories told in this book are not often covered in Econ , but that may change. Since the science of economics is primarily a set of tools, as opposed to a subject matter, then no subject, however offbeat, need be beyond its reach. When he published The Theory of Moral Sentiments in , modern capitalism was just getting under way.

It was the human effect, the fact that economic forces were vastly changing the way a person thought and behaved in a given situation. The gravity and shock of these changes were as overwhelming to the citizens of his time as the gravity and shock of modern life may seem to us today. The economic historian Robert Heilbroner, writing in The Worldly Philosophers, wondered how Smith was able to separate the doings of man, a creature of self-interest, from the greater moral plane in which man operated.

These explorations generally begin with the asking of a simple unasked question. Such as: what do schoolteachers and sumo wrestlers have in common? Imagine for a moment that you are the manager of a day-care center. You have a clearly stated policy that children are supposed to be picked up by 4 p. But very often parents are late. What to do? Why, after all, should the day-care center take care of these kids for free?

The economists decided to test their solution by conducting a study of ten day-care centers in Haifa, Israel. Before long there were twenty late pickups per week, more than double the original average. Economics is, at root, the study of incentives: how people get what they want, or need, especially when other people want or need the same thing. Economists love incentives. They love to dream them up and enact them, study them and tinker with them. An incentive is a bullet, a lever, a key: an often tiny object with astonishing power to change a situation. We all learn to respond to incentives, negative and positive, from the outset of life. If you are spotted picking your nose in class, you get ridiculed.

But if you make the basketball team, you move up the social ladder. If you break curfew, you get grounded. But if you ace your SATs, you get to go to a good college. But if you perform so well that a rival company comes calling, you become a vice president and no longer have to work for your father. An incentive is simply a means of urging people to do more of a good thing and less of a bad thing.

Someone—an economist or a politician or a parent—has to invent them. Your three-year-old eats all her vegetables for a week? She wins a trip to the toy store. A big steelmaker belches too much smoke into the air? Very often a single incentive scheme will include all three varieties. Think about the anti-smoking campaign of recent years. The banning of cigarettes in restaurants and bars is a powerful social incentive. And when the U. Some of the most compelling incentives yet invented have been put in place to deter crime. Considering this fact, it might be worthwhile to take a familiar question—why is there so much crime in modern society?

After all, every one of us regularly passes up opportunities to maim, steal, and defraud. The chance of going to jail—thereby losing your job, your house, and your freedom, all of which are essentially economic penalties—is certainly a strong incentive. For certain types of misbehavior, social incentives are terribly powerful. So through a complicated, haphazard, and constantly readjusted web of economic, social, and moral incentives, modern society does its best to militate against crime. But taking the long view, that is clearly not true. So what was wrong with the incentive at the Israeli day-care centers? That would have likely put an end to the late pickups, though it would have also engendered plenty of ill will.

Any incentive is inherently a trade-off; the trick is to balance the extremes. For just a few dollars each day, parents could buy off their guilt. Such is the strange and powerful nature of incentives. A slight tweak can produce drastic and often unforeseen results. In this case, they wanted to learn about the motivation behind blood donations. Their discovery: when people are given a small stipend for donating blood rather than simply being praised for their altruism, they tend to donate less blood. Surely the number of donors would have changed dramatically.

But something else would have changed dramatically as well, for every incentive has its dark side. They might literally steal blood at knifepoint. They might pass off pig blood as their own. They might circumvent donation limits by using fake IDs. Whatever the incentive, whatever the situation, dishonest people will try to gain an advantage by whatever means necessary. Or, as W. Fields once said: a thing worth having is a thing worth cheating for. Who cheats? Well, just about anyone, if the stakes are right. And then you might remember the time you cheated on, say, a board game. Last week.

Or the golf ball you nudged out of its bad lie. And then took the bagel anyway. For every clever person who goes to the trouble of creating an in20 Schoolteachers and Sumo Wrestlers centive scheme, there is an army of people, clever and otherwise, who will inevitably spend even more time trying to beat it. Cheating may or may not be human nature, but it is certainly a prominent feature in just about every human endeavor. Cheating is a primordial economic act: getting more for less. It is the waitress who pockets her tips instead of pooling them. It is the third grader who, worried about not making it to the fourth grade, copies test answers from the kid sitting next to him. Some cheating leaves barely a shadow of evidence.

In other cases, the evidence is massive. Consider what happened one spring evening at midnight in seven million American children suddenly disappeared. The worst kidnapping wave in history? It was the night of April 15, and the Internal Revenue Service had just changed a rule. The incentive for those cheating taxpayers was quite clear. The same for the waitress, the payroll manager, and the third grader. Might she have an incentive to cheat?

And if so, how would she do it? Imagine now that instead of running a day-care center in Haifa, you are running the Chicago Public Schools, a system that educates , students each year. The stakes are considered high because instead of simply testing students to measure their progress, schools are increasingly held accountable for the results. The federal government mandated high-stakes testing as part of the No Child Left Behind law, signed by President Bush in But even before that law, most states gave annual standardized tests to students in elementary and secondary school. The Chicago Public School system embraced high-stakes testing in Under the new policy, a school with low reading scores would be placed on probation and face the threat of being shut down, its staff to be dismissed or reassigned.

The CPS also did away with what is known as social promotion. Now, in order to be promoted, every student in third, sixth, and eighth grade had to manage a minimum score on the standardized, multiple-choice exam known as the Iowa Test of Basic Skills. Advocates of high-stakes testing argue that it raises the standards of learning and gives students more incentive to study. Schoolchildren, of course, have had incentive to cheat for as long as there have been tests. But high-stakes testing has so radically changed the incentives for teachers that they too now have added reason to cheat. With high-stakes testing, a teacher whose students test 22 Schoolteachers and Sumo Wrestlers poorly can be censured or passed over for a raise or promotion.

High-stakes testing also presents teachers with some positive incentives. How might a teacher go about cheating? There are any number of possibilities, from brazen to subtle. A teacher can simply give students extra time to complete the test. And you always thought that no. If this kind of teacher cheating is truly going on, how might it be detected? To catch a cheater, it helps to think like one. That would clearly be a tip-off. Nor, in all likelihood, would you have enough time, because the answer sheets have to be turned in soon after the test is over.

You might even think to focus your activity toward the end of the test, where the questions tend to be harder than the earlier questions. If economics is a science primarily concerned with incentives, it is also—fortunately—a science with statistical tools to measure how people respond to those incentives. All you need are some data. In this case, the Chicago Public School system obliged.

It made available a database of the test answers for every CPS student from third grade through seventh grade from to This amounts to roughly 30, students per grade per year, more than , sets of test answers, and nearly million individual answers. The actual paper answer sheets were not included; they were habitually shredded soon 24 Schoolteachers and Sumo Wrestlers after a test. The data also included some information about each teacher and demographic information for every student, as well as his or her past and future test scores—which would prove a key element in detecting the teacher cheating.

Now it was time to construct an algorithm that could tease some conclusions from this mass of data. Consider now the answer strings from the students in two sixthgrade Chicago classrooms who took the identical math test. The letter a, b, c, or d indicates a correct answer; a number indicates a wrong answer, with 1 corresponding to a, 2 corresponding to b, and so on. A zero represents an answer that was left blank. Here again are the answer strings from classroom A, now reordered by a computer that has been asked to apply the cheating algorithm and seek out suspicious patterns. Classroom A With cheating algorithm applied 1. There are at least four reasons this is unlikely. One: those questions, coming near the end of the test, were harder than the earlier questions.

Two: these were mainly subpar students to begin with, few of whom got six consecutive right answers elsewhere on the test, making it all the more unlikely they would get right the same six hard questions. Four: three of the students numbers 1, 9, and 12 left more than one answer blank before the suspicious string and then ended the test with another string of blanks. This suggests that a long, unbroken string of blank answers was broken not by the student but by the teacher.

There is another oddity about the suspicious answer string. Perhaps she is merely being strategic. With standardized tests, the teacher is typically not given an answer key. As sixth graders who were taking the test in the eighth month of the academic year, these students needed to achieve an average score of 6. Fifth graders taking the test in the eighth month of the year needed to score 5. The students in classroom A averaged 5. So plainly these are poor students. A year earlier, however, these students did even worse, averaging just 4.

But this miraculous improvement was short-lived. When these sixth-grade students reached seventh grade, they averaged 5. So an entire roomful of children in classroom A suddenly got very smart one year and very dim the next, or more likely, their sixth-grade teacher worked some magic with her pencil. There are two noteworthy points to be made about the children in classroom A, tangential to the cheating itself. The second point is that these students and their parents would be in for a terrible shock once they reached the seventh grade. All they knew was that they had been successfully promoted due to their test scores. No child left behind, indeed. This may be the cruelest twist yet in high-stakes testing. A cheating teacher may tell herself that she is helping her students, but the fact is that she would appear far more concerned with helping herself.

An analysis of the entire Chicago data reveals evidence of teacher cheating in more than two hundred classrooms per year, roughly 5 percent of the total. What are the characteristics of a cheating teacher? The Chicago data shows that male and female teachers are equally prone to cheating. She is also more likely to cheat after her incentives change.

Because the Chicago data ran from to , it bracketed the introduction of high-stakes testing in Sure enough, there was a pronounced spike in cheating in Nor was the cheating random. It was the teachers in the lowest-scoring classrooms who were most likely to cheat. Not every result of the Chicago cheating analysis was so dour. In addition to detecting cheaters, the algorithm could also identify the best teachers in the school system. Instead of getting random answers correct, her students would show real improvement on the easier types of questions they had previously missed, an indication of actual learning.

Most academic analyses of this sort tend to languish, unread, on a dusty library shelf. Duncan was an unlikely candidate to hold such a powerful job. He was only thirty-six when appointed, a onetime academic allAmerican at Harvard who later played pro basketball in Australia. He had spent just three years with the CPS—and never in a job important enough to have his own secretary—before becoming its CEO.

His father taught psychology at the University of Chicago; his mother ran an afterschool program for forty years, without pay, in a poor neighborhood. When Duncan was a boy, his afterschool playmates were the underprivileged kids his mother cared for. So when he took over the public schools, his allegiance lay more with schoolchildren and their families than with teachers and their union. The best way to get rid of cheating teachers, Duncan had decided, was to readminister the standardized exam. He only had the resources to retest classrooms, however, so he asked the creators of the cheating algorithm to help choose which classrooms to test. How could those retests be used most effectively?

It might have seemed sensible to retest only the classrooms that likely had a cheating teacher. To make the retest results convincing, some non-cheaters were needed as a control group. The best control group? The classrooms shown by the algorithm to have the best teachers, in which big gains were thought to have been legitimately attained. So a blend was settled upon. More than half of the retested classrooms were those suspected of having a cheating teacher. The remainder were divided between the supposedly excellent teachers high scores but no suspicious answer patterns and, as a further control, classrooms with mediocre scores and no suspicious answers.

The retest was given a few weeks after the original exam. The children were not told the reason for the retest. Neither were the teachers. The teachers were asked to stay in the classroom with their students, but they would not be allowed to even touch the answer sheets. The results were as compelling as the cheating algorithm had predicted. In the classrooms chosen as controls, where no cheating was suspected, scores stayed about the same or even rose. The evidence was only strong enough to get rid of a dozen of them, but the many other cheaters had been duly warned. You might think that the sophistication of teachers who cheat would increase along with the level of schooling. But an exam given at the University of Georgia in the fall of disputes that idea.

Among the questions: How many halves are in a college basketball game? Eye Exam b. How Do the Grits Taste Exam c. Bug Control Exam d. Ron Jirsa b. John Pelphrey c. Jim Harrick Jr. It might also help to know that his father, Jim Harrick Sr. Every student in the class received an A. Not long afterward, both Harricks were relieved of their coaching duties. If it strikes you as disgraceful that Chicago schoolteachers and University of Georgia professors will cheat—a teacher, after all, is meant to instill values along with the facts—then the thought of cheating among sumo wrestlers may also be deeply disturbing.

Indeed, sumo is said to be less about competition than about honor itself. It is true that sports and cheating go hand in hand. Olympic sprinters and weightlifters, cyclists in the Tour de France, football linemen and baseball sluggers: they have all been shown to swallow whatever pill or powder may give them an edge. It is not only the participants who cheat. The man accused of orchestrating the vote swap, a reputed Russian mob boss named Alimzhan Tokhtakhounov, was also suspected of rigging beauty pageants in Moscow. An athlete who gets caught cheating is generally condemned, but most fans at least appreciate his motive: he wanted so badly to win that he bent the rules.

The Chicago White Sox, who conspired with gamblers to throw the World Series and are therefore known forever as the Black Sox , retain a stench of iniquity among even casual baseball fans. Otherwise, he could have had class; he could have been a contender. Could it? Once again, the data can tell the story. The incentive scheme that rules sumo is intricate and extraordinarily powerful. Each wrestler maintains a ranking that affects every slice of his life: how much money he makes, how large an entourage he carries, how much he gets to eat, sleep, and otherwise take advantage of his success. The sixty-six highest-ranked wrestlers in Japan, comprising the makuuchi and juryo divisions, make up the sumo elite. A wrestler near the top of this elite pyramid may earn millions and is treated like royalty.

Low-ranked wrestlers must tend to their superiors, preparing their meals, cleaning their quarters, and even soaping up their hardest-toreach body parts. So ranking is everything. If he has a losing record, his ranking falls. If it falls far enough, he is booted from the elite rank entirely. The eighth victory in any tournament is therefore critical, the difference between promotion and demotion; it is roughly four times as valuable in the rankings as the typical victory.

How might we measure the data to prove it? The right column shows how often the 7—7 wrestler actually did win. This makes sense; their records in this tournament indicate that the 8—6 wrestler is slightly better. But perhaps there are further clues in the data that prove collusion. Maybe he accepts a bribe which would obviously not be recorded in the data. Or perhaps some other arrangement is made between the two wrestlers. Keep in mind that the pool of elite sumo wrestlers is extraordinarily tight-knit.

Furthermore, each wrestler belongs to a stable that is typically managed by a former sumo champion, so even the rival stables have close ties. Wrestlers from the same stable do not wrestle one another. In this case, there is no great pressure on the individual match. So you might expect the wrestlers who won their 7—7 matches in the previous tournament to do about as well as they had in earlier matches against these same opponents—that is, winning roughly 50 percent of the time. Eighty percent in one match and 40 percent in the next? How do you make sense of that?

The collective records of the various sumo stables are similarly aberrational. No formal disciplinary action has ever been taken against a Japanese sumo wrestler for match rigging. People tend to get defensive when the integrity of their national sport is impugned. These occasional media storms offer one more chance to measure possible corruption in sumo. Media scrutiny, after all, creates a powerful incentive: if two sumo wrestlers or their stables have been rigging matches, they might be leery to continue when a swarm of journalists and TV cameras descend upon them.

So what happens in such cases? Several years ago, two former sumo wrestlers came forward with extensive allegations of match rigging—and more. The two men began to receive threatening phone calls; one of them told friends he was afraid he would be killed by the yakuza. But shortly beforehand, the two men died—hours apart, in the same hospital, of a similar respiratory ailment. The police declared there had been no foul play but did not conduct an investigation. In matches between two supposedly corrupt wrestlers, the wrestler who was on the bubble won about 80 percent of the time.

In bubble matches against a supposedly clean opponent, meanwhile, the bubble wrestler was no more likely to win than his record would predict. So if sumo wrestlers, schoolteachers, and day-care parents all cheat, are we to assume that mankind is innately and universally corrupt? And if so, how corrupt? The answer may lie in. Consider this story about a man named Paul Feldman. Once upon a time, Feldman dreamed big dreams. With early training in agricultural economics, he wanted to tackle world hunger. Instead, he took a job in Washington, analyzing weapons expenditures for the U. This was in For the next twenty-odd years, he did further analytic work in Washington. Then he made it a habit. Every Friday, he would bring in some bagels, a serrated knife, and cream cheese.

In order to recoup his costs, he set out a cash basket and a sign with the suggested price. His collection rate was about 95 percent; he attributed the underpayment to oversight, not fraud. In , when his research institute fell under new management, Feldman took a look at his future and grimaced. He decided to quit his job and sell bagels. It was an honor-system commerce scheme, and it worked. Within a few years, Feldman was delivering 8, bagels a week to companies and earning as much as he had ever made as a research analyst.

He had thrown off the shackles of cubicle life and made himself happy. He had also—quite without meaning to—designed a beautiful economic experiment. From the beginning, Feldman kept rigorous data on his bagel business. So by measuring the money collected against the bagels taken, he found it possible to tell, down to the penny, just how honest his customers were. Did they steal from him? If so, what were the characteristics of a company that stole versus a company that did not? Under what circumstances did people tend to steal more, or less?

Yes, shorting the bagel man is white-collar crime, writ however small. It might seem ludicrous to address as large and intractable a problem as white-collar crime through the life of a bagel man. But often a small and simple question can help chisel away at the biggest problems. Despite all the attention paid to rogue companies like Enron, academics know very little about the practicalities of white-collar crime. The reason? There are no good data. A key fact of white-collar crime is that we hear about only the very slim fraction of people who are caught cheating. Most embezzlers lead quiet and theoretically happy lives; employees who steal company property are rarely detected.

With street crime, meanwhile, that is not the case. A mugging or a 42 Schoolteachers and Sumo Wrestlers burglary or a murder is usually tallied whether or not the criminal is caught. A street crime has a victim, who typically reports the crime to the police, who generate data, which in turn generate thousands of academic papers by criminologists, sociologists, and economists. But white-collar crime presents no obvious victim. From whom, exactly, did the masters of Enron steal? It did present a victim. The victim was Paul Feldman. Not only that, but those bagel eaters knew the provider and had feelings presumably good ones about him.

A broad swath of psychological and economic research has shown that people will pay different amounts for the same item depending on who is providing it. In the real world, Feldman learned to settle for less than 95 percent. In the beginning, Feldman left behind an open basket for the cash, but too often the money vanished. Then he tried a coffee can with a money slot in its plastic lid, which also proved too tempting. In the end, he resorted to making small plywood boxes with a slot cut into the top.

The wooden box has worked well. Each year he drops off about seven thousand boxes and loses, on average, just one to theft. This is an intriguing statistic: the same people who routinely steal more than 10 percent of his bagels almost never stoop to stealing his money box—a tribute to the nuanced social calculus of theft. So what do the bagel data have to say? In recent years, there have been two noteworthy trends in the overall payment rate.

By the summer of , the overall rate had slipped to about 87 percent. Or it may have represented a more general surge in empathy. This may seem counterintuitive. There is far less street crime per capita in rural areas than in cities, in large part because a rural criminal is more likely to be known and therefore caught. Also, a smaller community tends to exert greater social incentives against crime, the main one being shame. Weather, for instance, is a major factor. Unseasonably pleasant weather inspires people to pay at a higher rate. Worst are the holidays. The difference in the two sets of holidays? The low-cheating holidays represent little more than an extra day off from work. The high-cheating holidays are fraught with miscellaneous anxieties and the high expectations of loved ones.

Feldman has also reached some of his own conclusions about honesty, based more on his experience than the data. Feldman wondered if perhaps the executives cheated out of an overdeveloped sense of entitlement. Yes, a lot of people steal from him, but the vast majority, even though no one is watching over them, do not. But it would not have surprised Adam Smith. A student named Glaucon offered the story in response to a lesson by Socrates— who, like Adam Smith, argued that people are generally good even without enforcement.

He told of a shepherd named Gyges who stumbled upon a secret cavern with a corpse inside that wore a ring. When Gyges put on the ring, he found that it made him invisible. With no one able to 46 Schoolteachers and Sumo Wrestlers monitor his behavior, Gyges proceeded to do woeful things—seduce the queen, murder the king, and so on. Glaucon seemed to think the answer was no. But Paul Feldman sides with Socrates and Adam Smith—for he knows that the answer, at least 87 percent of the time, is yes. As institutions go, the Ku Klux Klan has had a markedly up-anddown history. It was founded in the immediate aftermath of the Civil War by six former Confederate soldiers in Pulaski, Tennessee.

The six young men, four of whom were budding lawyers, saw themselves as merely a circle of like-minded friends. But soon the Klan evolved into a multistate terrorist organization designed to frighten and kill emancipated slaves. In , President Ulysses S. But within barely a decade, the Klan had been extinguished, largely by legal and military interventions out of Washington, D. If the Klan itself was defeated, however, its aims had largely been achieved through the establishment of Jim Crow laws. Congress, which during Reconstruction had been quick to enact measures of legal, social, and economic freedom for blacks, just as quickly began to roll them back.

The federal government agreed to withdraw its occupation troops from the South, allowing the restoration of white rule. In Plessy v. Ferguson, the U. Supreme Court gave the go-ahead to full-scale racial segregation. The Ku Klux Klan lay largely dormant until , when D. By the s, a revived Klan claimed eight million members. Public sentiment turned against the Klan as the unity of a country at war trumped its message of separatism. But within a few years, there were already signs of a massive revival. Stetson, founder of the famed hat company and the man for whom Stetson University was named. His uncle Brady was a Klansman. What drove Kennedy was a hatred of small-mindedness, ignorance, obstructionism, and intimidation—which, in his view, were displayed by no organization more proudly than the Ku Klux Klan.

Kennedy saw the Klan as the terrorist arm of the white establishment itself. This struck him as an intractable problem, for a variety of reasons. The Klan was in cahoots with political, business, and lawenforcement leaders. The public was frightened and felt powerless to act against the Klan. And the few anti-hate groups that existed at the time had little leverage or even information about the Klan. He would spend years interviewing Klan leaders and sympathizers, sometimes taking advantage of his own background and lineage to pretend that he was on their side of the issues.

Kennedy, a folklorist at heart, apparently wanted to put across 52 The Ku Klux Klan and Real-Estate Agents the most dramatic story possible, and therefore included not only his own anti-Klan activities but those of another man, code-named John Brown. It was Klan custom, for instance, to append a Kl to many words. Thus would two Klansmen hold a Klonversation in the local Klavern. But as it happened, a central tenet of life in the Klan—and of terrorism in general—is that most of the threatened violence never goes beyond the threat stage. The statistics reveal at least three noteworthy facts.

The second is the absence of a correlation between lynchings and Klan membership: there were actually more lynchings of blacks between and , when the Klan was dormant, than during the s, when the Klan had millions of members—which suggests that the Ku Klux Klan carried out far fewer lynchings than is generally thought. Third, relative to the size of the black population, lynchings were exceedingly rare. To be sure, one lynching is one too many. But by the turn of the century, lynchings were hardly the everyday occurrence that they are often considered in the public recollection. Compare the victims of lynchings in the s to the number of black infants who were dying at that time as a result of malnutrition, pneumonia, diarrhea, and the like.

As of , about 13 out of every black children died in infancy, or roughly 20, children each year—compared to 28 people who were lynched in a year. As late as , about 10, black infants died each year. What does it mean that lynchings were relatively rare and that they fell pre- 54 The Ku Klux Klan and Real-Estate Agents cipitously over time, even in the face of a boom in Klan membership?

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