Freakonomics: A Rogue Economist Explores the Hidden Side of Everything

by Steven D. Levitt

As Levitt sees it, economics is a science with excellent tools for gaining answers but a serious shortage of interesting questions. 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? Do real-estate agents have their clients’ best interests at heart? 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?

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.

By 2000 the overall murder rate in the United States had dropped to its lowest level in thirty-five years. So had the rate of just about every other sort of crime, from assault to car theft.

Most of their theories sounded perfectly logical. It was the roaring 1990s 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 2,262 in 1990 to 540 in 2005.

Like the proverbial butterfly that flaps its wings on one continent and eventually causes a hurricane on another, Norma McCorvey dramatically altered the course of events without intending to. All she had wanted was an abortion.

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. Wade, these children weren’t being born. 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.

the pool of potential criminals had dramatically shrunk.

Doctors, lawyers, contractors, stockbrokers, auto mechanics, mortgage brokers, financial planners: they all enjoy a gigantic informational advantage.

But experts are human, and humans respond to incentives. How any given expert treats you, therefore, will depend on how that expert’s incentives are set up.

Before plunging into the data, it helps to ask a question: what is the real-estate agent’s incentive when she is selling her own home? Simple: to make the best deal possible. Presumably this is also your incentive when you are selling your home.

But as incentives go, commissions are tricky. First of all, a 6 percent real-estate commission is typically split between the seller’s agent and the buyer’s. Each agent then kicks back roughly half of her take to the agency. Which means that only 1.5 percent of the purchase price goes directly into your agent’s pocket. So on the sale of your $300,000 house, her personal take of the $18,000 commission is $4,500.

she could have sold it for $310,000? After the commission, that puts an additional $9,400 in your pocket. But the agent’s additional share—her personal 1.5 percent of the extra $10,000—is a mere $150. If you earn $9,400 while she earns only $150,

it turns out that a real-estate agent keeps her own home on the market an average of ten days longer and sells it for an extra 3-plus percent, or $10,000 on a $300,000 house. When she sells her own house, an agent holds out for the best offer; when she sells yours, she encourages you to take the first decent offer that comes along.

Her share of a better offer—$150—is too puny an incentive to encourage her to do otherwise.

It’s possible that X causes Y; it’s also possible that Y causes X; and it may be that X and Y are both being caused by some other factor, Z.

Consider the folktale of the czar who learned that the most disease-ridden province in his empire was also the province with the most doctors. His solution? He promptly ordered all the doctors shot dead.

Here’s the surprise: the amount of money spent by the candidates hardly matters at all. A winning candidate can cut his spending in half and lose only 1 percent of the vote. 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.

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.

Incentives are the cornerstone of modern life. 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.

Conventional wisdom is often shoddily formed and devilishly difficult to see through, but it can be done.

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.

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.

what do schoolteachers and sumo wrestlers have in common?

The typical economist believes the world has not yet invented a problem that he cannot fix if given a free hand to design the proper incentive scheme.

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.

An incentive is simply a means of urging people to do more of a good thing and less of a bad thing. But most incentives don’t come about organically. Someone—an economist or a politician or a parent—has to invent them.

There are three basic flavors of incentive: economic, social, and moral. Very often a single incentive scheme will include all three varieties. Think about the anti-smoking campaign of recent years.

economic penalties—is certainly a strong incentive. But when it comes to crime, people also respond to moral incentives (they don’t want to do something they consider wrong) and social incentives (they don’t want to be seen by others as doing something wrong).

Which is a more horrifying deterrent: a $500 fine for soliciting a prostitute or the thought of your friends and family ogling you on www.HookersAndJohns.com?

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. The stipend turned a noble act of charity into a painful way to make a few dollars, and it wasn’t worth it.

Whatever the incentive, whatever the situation, dishonest people will try to gain an advantage by whatever means necessary.

For every clever person who goes to the trouble of creating an incentive scheme, there is an army of people, clever and otherwise, who will inevitably spend even more time trying to beat it.

The incentive for those cheating taxpayers was quite clear. The same for the waitress, the payroll manager, and the third grader. But what about that third grader’s teacher? Might she have an incentive to cheat? And if so, how would she do it?

The federal government mandated high-stakes testing as part of the No Child Left Behind law, signed by President Bush in 2002. But even before that law, most states gave annual standardized tests to students in elementary and secondary school. Twenty states rewarded individual schools for good test scores or dramatic improvement; thirty-two states sanctioned the schools that didn’t do well. The Chicago Public School system embraced high-stakes testing in 1996.

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 poorly can be censured or passed over for a raise or promotion. If the entire school does poorly, federal funding can be withheld; if the school is put on probation, the teacher stands to be fired. High-stakes testing also presents teachers with some positive incentives.

And if a teacher were to survey this newly incentivized landscape and consider somehow inflating her students’ scores, she just might be persuaded by one final incentive: teacher cheating is rarely looked for, hardly ever detected, and just about never punished.

But if a teacher really wanted to cheat—and make it worth her while—she might collect her students’ answer sheets and, in the hour or so before turning them in to be read by an electronic scanner, erase the wrong answers and fill in correct ones.

So what you might do is select a string of eight or ten consecutive questions and fill in the correct answers for, say, one-half or two-thirds of your students. You could easily memorize a short pattern of correct answers,

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 1993 to 2000.

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

The first thing to search for would be unusual answer patterns in a given classroom: blocks of identical answers, for instance, especially among the harder questions.

Another red flag would be a strange pattern within any one student’s exam—such as getting the hard questions right while missing the easy ones—especially

A dramatic one-year spike in test scores might initially be attributed to a good teacher; but with a dramatic fall to follow, there’s a strong likelihood that the spike was brought about by artificial means.

Did fifteen out of twenty-two students somehow manage to reel off the same six consecutive correct answers (the d-a-d-b-c-b string) all by themselves? 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. Three: up to this point in the test, the fifteen students’ answers were virtually uncorrelated. 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.

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.

they probably expected to do great in the seventh grade—and then they failed miserably. 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.

In a recent study among North Carolina schoolteachers, some 35 percent of the respondents said they had witnessed their colleagues cheating in some fashion, whether by giving students extra time, suggesting answers, or manually changing students’ answers.

Nor was the cheating random. It was the teachers in the lowest-scoring classrooms who were most likely to cheat.