Freakonomics Revised and Expanded Edition

by Steven D. Levitt

  Levitt speaks with a boyish lisp. His appearance is High Nerd: a plaid button-down shirt, nondescript khakis and a braided belt, sensible shoes. His pocket calendar is branded with the National Bureau of Economic Research logo. “I wish he would get more than three haircuts a year,” his wife, Jeannette, says, “and that he wasn’t still wearing the same glasses he got fifteen years ago, which weren’t even in fashion then.” He was a good golfer in high school but has so physically atrophied that he calls himself “the weakest human being alive” and asks Jeannette to open jars around the house. There is nothing in his appearance or manner, in other words, that suggests a flamethrower. He will tell you that all he does is sit at his desk, day and night, wrestling with some strange mountain of data. He will tell you that he would do it for free (his salary is reportedly more than $200,000), and you tend to believe him. He may be an accidental provocateur, but he is a provocateur nonetheless.

  He takes particular delight in catching wrongdoers. In one paper, he devised a set of algorithms that could identify teachers in the Chicago public-school system who were cheating. “Cheating classrooms will systematically differ from other classrooms along a number of dimensions,” he and his co-author, Brian Jacob of the Kennedy School of Government, wrote in “Catching Cheating Teachers.” “For instance, students in cheating classrooms are likely to experience unusually large test-score gains in the year of the cheating, followed by unusually small gains or even declines in the following year when the boost attributable to cheating disappears.”

  Levitt used test-score data from the Chicago schools that had long been available to other researchers. There were a number of ways, he realized, that a teacher could cheat. If she were particularly brazen (and stupid), she might give students the correct answers. Or, after the test, she might actually erase students’ wrong answers and fill in correct ones. A sophisticated cheater would be careful to avoid conspicuous blocks of identical answers. But Levitt was more sophisticated. “The first step in analyzing suspicious strings is to estimate the probability each child would give a particular answer on each question,” he wrote. “This estimation is done using a multinomial logit framework with past test scores, demographics and socioeconomic characteristics as explanatory variables.”

  So by measuring any number of factors—the difficulty of a particular question, the frequency with which students got hard questions right and easy ones wrong, the degree to which certain answers were highly correlated in one classroom—Levitt identified which teachers he thought were cheating. (Perhaps just as valuable, he was also able to identify the good teachers.) The Chicago school system, rather than disputing Levitt’s findings, invited him into the schools for retesting. As a result, the cheaters were fired.

  Then there is his forthcoming “Understanding Why Crime Fell in the 1990’s: Four Factors That Explain the Decline and Seven That Do Not.” The entire drop in crime, Levitt says, was due to more police officers, more prisoners, the waning crack epidemic and Roe v. Wade.

  One factor that probably didn’t make a difference, he argues, was the innovative policing strategy trumpeted in New York by Rudolph Giuliani and William Bratton. “I think,” Levitt says, “I’m pretty much alone in saying that.”

  He comes from a Minneapolis family of high, if unusual, achievers. His father, a medical researcher, is considered a leading authority on intestinal gas. (He bills himself as “The Man Who Gave Status to Flatus and Class to Gas.”) One of Levitt’s great-uncles, Robert May, wrote Rudolph the Red-Nosed Reindeer—the book, that is; another great-uncle, Johnny Marks, later wrote the song.

  At Harvard, Levitt wrote his senior thesis on thoroughbred breeding and graduated summa cum laude. (He is still obsessed with horse racing. He says he believes it is corrupt and has designed a betting system—the details of which he will not share—to take advantage of the corruption.) He worked for two years as a management consultant before enrolling at M.I.T. for a doctorate in economics. The M.I.T. program was famous for its mathematical intensity. Levitt had taken exactly one math course as an undergraduate and had forgotten even that. During his first graduate class, he asked the student next to him about a formula on the board: Is there any difference between the derivative sign that’s straight up-and-down and the curly one? “You are in so much trouble,” he was told.

  “People wrote him off,” recalls Austan Goolsbee, the Chicago economist who was then a classmate. “They’d say, ‘That guy has no future.’”

  Levitt set his own course. Other grad students stayed up all night working on problem sets, trying to make good grades. He stayed up researching and writing. “My view was that the way you succeed in this profession is you write great papers,” he says. “So I just started.”

  Sometimes he would begin with a question. Sometimes it was a set of data that caught his eye. He spent one entire summer typing into his computer the results of years’ worth of Congressional elections. (Today, with so much information so easily available on the Internet, Levitt complains that he can’t get his students to input data at all.) All he had was a vague curiosity about why incumbents were so often re-elected.

  Then he happened upon a political-science book whose authors claimed that money wins elections, period. “They were trying to explain election outcomes as a function of campaign expenditures,” he recalls, “completely ignoring the fact that contributors will only give money to challengers when they have a realistic chance of winning, and incumbents only spend a lot when they have a chance of losing. They convinced themselves this was the causal story even though it’s so obvious in retrospect that it’s a spurious effect.”

  Obvious, at least, to Levitt. Within five minutes, he had a vision of the paper he would write. “It came to me,” he says, “in full bloom.”

  The problem was that his data couldn’t tell him who was a good candidate and who wasn’t. It was therefore impossible to tease out the effect of the money. As with the police/crime rate puzzle, he had to trick the data.

  Because he himself had typed in the data, he had noticed something: often, the same two candidates faced each other multiple times. By analyzing the data from only those elections, Levitt was able to find a true result. His conclusion: campaign money has about one-tenth the impact as was commonly accepted.

  An unknown graduate student, he sent his paper to the Journal of Political Economy—one professor told him he was crazy for even trying—where it was published. He completed his Ph.D. in three years, but because of his priorities, he says, he was “invisible” to the faculty, “a real zero.” Then he stumbled upon what he now calls the turning point in his career.

  He had an interview for the Society of Fellows, the venerable intellectual Harvard clubhouse that pays young scholars to do their own work, for three years, with no commitments. Levitt felt he didn’t stand a chance. For starters, he didn’t consider himself an intellectual. He would be interviewed over dinner by the senior fellows, a collection of world-renowned philosophers, scientists and historians. He worried he wouldn’t have enough conversation for even the first course.

  Instead, he was on fire. Whatever subject came up—the brain, ants, philosophy—he just happened to remember something pithy he’d read. His wit crackled as it had never crackled before. When he told them about the two summers he spent betting the horses back in Minnesota, they ate it up!

  Finally—disquietingly—one of them said: “I’m having a hard time seeing the unifying theme of your work. Could you explain it?”

  Levitt was stymied. He had no idea what his unifying theme was, or if he even had one.

  Amartya Sen, the future Nobel-winning economist, jumped in and neatly summarized what he saw as Levitt’s theme.

  Yes, Levitt said eagerly, that’s my theme.

  Another fellow then offered another theme.

  You’re right, Levitt said, that’s my theme.

  And so it went, like dogs tugging at a bone, until the philosopher Robert Nozick interrupted. If Levitt could have be
en said to have an intellectual hero, it would be Nozick.

  “How old are you, Steve?” he asked.

  “Twenty-six.”

  Nozick turned to the other fellows: “He’s twenty-six years old. Why does he need to have a unifying theme? Maybe he’s going to be one of those people who’s so talented he doesn’t need one. He’ll take a question and he’ll just answer it, and it’ll be fine.”

  The University of Chicago’s economics department had a famous unifying theme—the Gospel of Free Markets, with a conservative twist—and would therefore not have seemed the most likely fit for Levitt. As he sees it, Chicago is about theory, deep thinking and big ideas, while he is about empiricism, clever thinking and “cute but ultimately insubstantial ideas.”

  But Chicago also had Gary Becker. To Levitt, Becker is the most influential economist of the past fifty years. Long before it was fashionable, Becker brought microeconomic theory to offbeat topics, the family and crime in particular. For years, Becker was demonized—a single phrase like “the price of children” would set off untold alarms. “I took a lot of heat over my career from people who thought my work was silly or irrelevant or not economics,” Becker says. But Chicago supported him; he persevered, winning the Nobel Prize in 1992; and he became Steven Levitt’s role model.

  Becker told Levitt that Chicago would be a great environment for him. “Not everybody agrees with all your results,” he said, “but we agree what you’re doing is very interesting work, and we’ll support you in that.”

  Levitt soon found that the support at Chicago went beyond the scholarly. The year after he was hired, his wife gave birth to their first child, Andrew. One day, just after Andrew turned a year old, he came down with a slight fever. The doctor diagnosed an ear infection. When he started vomiting the next morning, his parents took him to the hospital. A few days later he was dead of pneumococcal meningitis.

  Amid the shock and grief, Levitt had an undergraduate class that needed teaching. It was Gary Becker—a Nobel laureate nearing his seventieth birthday—who sat in for him. Another colleague, D. Gale Johnson, sent a condolence card that Levitt still quotes from memory.

  Levitt and Johnson, an agricultural economist in his eighties, began speaking regularly. Levitt learned that Johnson’s daughter was one of the first Americans to adopt a daughter from China. Soon the Levitts adopted a daughter of their own, whom they named Amanda. In addition to Amanda, they have since had a daughter, now almost three, and a son. But Andrew’s death has played on, in various ways. They have become close friends with the family of the little girl to whom they donated Andrew’s liver. (They also donated his heart, but that baby died.) And, not surprisingly for a scholar who pursues real-life subjects, the death also informed Levitt’s work.

  He and Jeannette joined a support group for grieving parents. Levitt was struck by how many children had drowned in swimming pools. They were the kinds of deaths that don’t make the newspaper—unlike, for instance, a child who dies while playing with a gun.

  Levitt was curious and went looking for numbers that would tell the story. He wrote up the results as an op-ed article for the Chicago Sun-Times. It featured the sort of plangent counterintuition for which he has become famous: “If you own a gun and have a swimming pool in the yard, the swimming pool is almost 100 times more likely to kill a child than the gun is.”

  Trying to get his mind off death, Levitt took up a hobby: rehabbing and selling old houses in Oak Park, where he lives. This experience has led to yet another paper, about the real-estate market. It is his most Chicago-style paper yet, a romp in price theory, a sign that the university’s influence on him is perhaps as strong as his influence on it. But Levitt being Levitt, it also deals with corruption.

  While negotiating to buy old houses, he found that the seller’s agent often encouraged him, albeit cagily, to underbid. This seemed odd: didn’t the agent represent the seller’s best interest? Then he thought more about the agent’s role. Like many other “experts” (auto mechanics and stockbrokers come to mind), a real-estate agent is thought to know his field far better than a lay person. A homeowner is encouraged to trust the agent’s information. So if the agent brings in a low offer and says it might just be the best the homeowner can expect, the homeowner tends to believe him. But the key, Levitt determined, lay in the fact that agents “receive only a small share of the incremental profit when a house sells for a higher value.” Like a stockbroker churning commissions or a bookie grabbing his vig, an agent was simply looking to make a deal, any deal. So he would push homeowners to sell too fast and too cheap.

  Now if Levitt could only measure this effect. Once again, he found a clever mechanism. Using data from more than 50,000 home sales in Cook County, Ill., he compared the figures for homes owned by real-estate agents with those for homes for which they acted only as agents. The agents’ homes stayed on the market about 10 days longer and sold for 2 percent more.

  Late on a summer afternoon, Levitt is in his office, deep inside one of the university’s Gothic behemoths. The ceiling is stained, the plaster around the window crumbling. He is just back from sabbatical at Stanford, and his desk is a holy mess: stacks of books and journals, a green sippy cup and a little orange squeeze hippo.

  This is his afternoon to meet with students. Levitt drinks a Mountain Dew and talks softly. Some students come for research assignments, some for advice. One has just written her undergraduate thesis: “The Labor Market Consequence of Graduating College in a Bad Economy.” For a thesis, Levitt tells her, it’s very good. But now she wants to have it published.

  “You write like a college student, and that’s a problem,” he says. “The thing is, you’re telling a story. There’s foreshadowing going on, all those tricks. You want the reader going down a particular path so when they get the results, they understand them and believe them. But you also want to be honest about your weaknesses. People are much less harsh on weaknesses that are clear than weaknesses that are hidden—as they should be.”

  Be honest about your weaknesses. Has there ever been a prizewinning scholar as honest about his weaknesses as Steven Levitt? He doesn’t understand economics, he claims, or math. He’s a little thinker in a world of big thinkers. He can’t even open a jar of spaghetti sauce at home, poor guy.

  Friends say that Levitt’s self-deprecation is as calculated as it is genuine. Within academia, economists take pride in being the most cutthroat of a cutthroat breed. Anyone who writes papers on Weakest Link (contestants discriminate against Latino and elderly peers, Levitt concluded, but not blacks or women) and sumo (to best manage their tournament rankings, wrestlers often conspire to throw matches) had better not also be arrogant.

  Or maybe it is not self-deprecation at all. Maybe it is self-flagellation. Maybe what Steven Levitt really wants is to graduate from his “silly” and “trivial” and “shallow” topics.

  He thinks he’s onto something with a new paper about black names. He wanted to know if someone with a distinctly black name suffers an economic penalty. His answer—contrary to other recent research—is no. But now he has a bigger question: Is black culture a cause of racial inequality or is it a consequence? For an economist, even for Levitt, this is new turf—“quantifying culture,” he calls it. As a task, he finds it thorny, messy, perhaps impossible and deeply tantalizing.

  Driving home to Oak Park that evening, his Cavalier glumly thrumming along the Eisenhower Expressway, he dutifully addresses his future. Leaving academia for a hedge fund or a government job does not interest him (though he might, on the side, start a company to catch cheating teachers). He is said to be at the top of every economics department’s poaching list. But the tree he and Jeannette planted when Andrew died is getting too big to move. You get the feeling he may stay at Chicago awhile.

  There are important problems, he says, that he feels ready to address. For instance? “Tax evasion. Money-laundering. I’d like to put together a set of tools that lets us catch terrorists. I mean, that’s the g
oal. I don’t necessarily know yet how I’d go about it. But given the right data, I have little doubt that I could figure out the answer.”

  It might seem absurd for an economist to dream of catching terrorists. 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 C.I.A. analysts. But numbers don’t.

  “Freakonomics” Columns from the New York Times Magazine

  UP IN SMOKE

  Whatever happened to crack cocaine?

  August 7, 2005

  If you rely on the news media for your information, you probably think that crack cocaine is a thing of the past. If you rely on data, however, you reach a different conclusion.

  Measuring the use and impact of a drug like crack isn’t easy. There is no government Web site to provide crack data, and surveying dealers is bound to be pretty unreliable. So how can you get to the truth of crack use? One way is to look at a variety of imperfect but plausible proxies, including cocaine arrests, emergency-room visits and deaths. Unlike the volume of news coverage, the rates for all of these remain shockingly high. Cocaine arrests, for instance, have fallen only about 15 percent since the crack boom of the late 1980s. Cocaine-related deaths are actually higher now; so are the number of emergency-room visits due to cocaine. When combined in a sensible way, these proxies can be used to construct a useful index of crack.

  And what does this index reveal? That crack use was nonexistent until the early 1980s and spiked like mad in 1985, peaking in 1989. That it arrived early on the West Coast, but became most prevalent in the cities of the Northeast and Middle Atlantic States. And that it produced a remarkable level of gun violence, particularly among young black men, who made up the bulk of street-level crack dealers. During the crack boom, the homicide rate among thirteen-to seventeen-year-old blacks more than quadrupled. But perhaps the biggest surprise in the crack index is the fact that, as of 2000—the most recent year for which the index data are available—Americans were still smoking about 70 percent as much crack as they smoked when consumption was at its peak.