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June 22 - July 13, 2025
In a typical audit study, a researcher would send two identical (and fake) résumés, one with a traditionally white name and the other with an immigrant or minority-sounding name, to potential employers. The “white” résumés have always gleaned more job interviews.
Such studies are tantalizing but severely limited, for they can’t explain why DeShawn didn’t get the call. Was he rejected because the employer is a racist and is convinced that DeShawn Williams is black? Or did he reject him because “DeShawn” sounds like someone from a low-income, low-education family?
“DeShawn” may simply signal a disadvantaged background to an employer who believes that workers from such backgrounds are undependable.
Along those same lines, perhaps a black person with a white name pays an economic penalty in the black community;
The California data included not only each baby’s vital statistics but information about the mother’s level of education, income, and, most significantly, her own date of birth. This last fact made it possible to identify the hundreds of thousands of California mothers who had themselves been born in California and then to link them to their own birth records. Now a new and extremely potent story emerged from the data: it was possible to track the life outcome of any individual woman.
Using regression analysis to control for other factors that might influence life trajectories, it was then possible to measure the impact of a single factor—in this case, a woman’s first name—on her educational, income, and health outcomes. So does a name matter? The data show that, on average, a person with a distinctively black name—whether it is a woman named Imani or a man named DeShawn—does have a worse life outcome than a woman named Molly or a man named Jake. But it isn’t the fault of their names. If two black boys, Jake Williams and DeShawn Williams, are born in the same neighborhood
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A DeShawn is more likely to have been handicapped by a low-income, low-education, single-parent background. His name is an indicator—not a cause—of his outcome.
Broadly speaking, the data tell us how parents see themselves—and, more significantly, what kind of expectations they have for their children.
There is a clear pattern at play: once a name catches on among high-income, highly educated parents, it starts working its way down the socioeconomic ladder. Amber and Heather started out as high-end names, as did Stephanie and Brittany. For every high-end baby named Stephanie or Brittany, another five lower-income girls received those names within ten years.
So it isn’t famous people who drive the name game. It is the family just a few blocks over, the one with the bigger house and newer car. The kind of families that were the first to call their daughters Amber or Heather and are now calling them Lauren or Madison. The kind of families that used to name their sons Justin or Brandon and are now calling them Alexander or Benjamin.
But as a high-end name is adopted en masse, high-end parents begin to abandon it. Eventually, it is considered so common that even lower-end parents may not want it, whereby it falls out of the rotation entirely. The lower-end parents, meanwhile, go looking for the next name that the upper-end parents have broken in.
What the California names data suggest is that an overwhelming number of parents use a name to signal their own expectations of how successful their children will be. The name isn’t likely to make a shard of difference. But the parents can at least feel better knowing that, from the very outset, they tried their best.
To claim that legalized abortion resulted in a massive drop in crime will inevitably lead to explosive moral reactions. But the fact of the matter is that Freakonomics-style thinking simply doesn’t traffic in morality. As we suggested near the beginning of this book, if morality represents an ideal world, then economics represents the actual world.
The data have by now made it clear that parents matter a great deal in some regards (most of which have been long determined by the time a child is born) and not at all in others (the ones we obsess about).
In Switzerland, as in the U.S., “there exists a fairly strong social norm that a good citizen should go to the polls,” Funk writes. “As long as poll-voting was the only option, there was an incentive (or pressure) to go to the polls only to be seen handing in the vote.
Since in small communities, people know each other better and gossip about who fulfills civic duties and who doesn’t, the benefits of norm adherence were particularly high in this type of community.”
For all the talk of how people “vote their pocketbooks,” the Swiss study suggests that we may be driven to vote less by a financial incentive than a social one. It may be that the most valuable payoff of voting is simply being seen at the polling place by your friends or co-workers.
Those 185,000 deaths, though, came over the course of nearly 15 trillion miles driven. This translates into one fatality for every 81 million miles driven. Although traffic accidents are the leading cause of death for Americans from ages 3 to 33, this would seem to be a pretty low death rate (especially since it includes motorcycles, which are far more dangerous than cars or trucks).
In other words, a lot of people die on U.S. roads each year not because driving is so dangerous, but because an awful lot of people are driving an awful lot of miles.
people who buy an annual membership to a health club overestimate by more than 70 percent how much they’ll actually use it. Many people, therefore, would be better off buying monthly or daily passes.
a report about patients who fail to take their medicine. “People who are prescribed self-administered medications,” it began, “typically take less than half the prescribed doses.”
when asked what influences their decision to report and pay taxes honestly, 62 percent answered “fear of an audit,” while 68 percent said it was the fact that their income was already being reported to the I.R.S. by third parties. For all the civic duty floating around, it would seem that most compliance is determined by good old-fashioned incentives.
In the “wages, salaries, tips” category, for instance, Americans are underreporting only 1 percent of their actual income. Meanwhile, in the “nonfarm proprietor income” category—think of self-employed workers like a restaurateur or the boss of a small construction crew—57 percent of the income goes unreported. That’s $68 billion in unpaid taxes right there. Why such a huge difference between the wage earner and a restaurateur? Simple: The only person reporting the restaurateur’s income to the I.R.S. is the restaurateur himself;
Does this mean that the average self-employed worker is less honest than the average wage earner? Not necessarily. It’s just that he has much more incentive to cheat. He knows that the only chance the I.R.S. has of learning his true income and expenditures is to audit him. And all he has to do is look at the I.R.S.’s infinitesimal audit rate—last year, the agency conducted face-to-face audits on just 0.19 percent of all individual taxpayers—to feel pretty confident to go ahead and cheat.
Does this mean that the average self-employed worker is less honest than the average wage earner? Not necessarily. It’s just that he has much more incentive to cheat. He knows that the only chance the I.R.S. has of learning his true income and expenditures is to audit him. And all he has to do is look at the I.R.S.’s infinitesimal audit rate—last year, the agency conducted face-to-face audits on just .19 percent of all individual taxpayers—to feel pretty confident to cheat.
Levitt: I think there’s a good lesson there, which is that data-based statistical accusations never convince anyone who doesn’t want to be convinced.
Levitt: I think there’s a good lesson there, which is that data-based statistical accusations never convince anyone who doesn’t want to be convinced.
I think really what we do is take things that are completely obvious, but for some reason hard for people to see because of conventional wisdom or because no one really asked.
I think really what we do is take things that are completely obvious, but for some reason hard for people to see because of conventional wisdom or because no one really asked.
Dubner: There are a lot of reasons why most scientists don’t write well. Perhaps the biggest one is that they’ve been incentivized for their entire careers to write in a style that is directly opposite the sort of clear and compelling language that most people want to read. And that’s because they’re not writing for “most people”—they’re writing primarily for each other, in their journals.
Dubner: There are a lot of reasons why most scientists don’t write well. Perhaps the biggest one is that they’ve been incentivized for their entire careers to write in a style that is directly opposite the sort of clear and compelling language that most people want to read. And that’s because they’re not writing for “ most people—they’re writing primarily for each other, in their journals.
Economics gives us a way into almost any topic, which is “How would people respond to the incentives that are present in a given situation? And what happens if those incentives change?”
Economics gives us a way into almost any topic, which is “How would people respond to the incentives that are present in a given situation? And what happened when those incentives change?
Still, even after factoring in the deaths of those innocents, walking drunk leads to five times as many deaths per mile as driving drunk.
Still, even after factoring in the deaths of those innocents, walking drunk leads to five times as many deaths per mile as driving drunk.
Girls are so undervalued in India that there are roughly 35 million fewer females than males in the population. Most of these “missing women,” as the economist Amartya Sen calls them, are presumed dead, either by indirect means (the girl’s parents withheld nutrition or medical care, perhaps to the benefit of a brother), direct harm (the baby girl was killed after birth, whether by a midwife or a parent), or, increasingly, a pre-birth decision.
Girls are so undervalued in India that there are roughly 35 million fewer females than males in the population. Most of these “missing women,” as the economist Amartya Sen calls them, are presumed dead, either by indirect means (the girl’s parents withheld nutrition or medical care, perhaps to the benefit of a brother), direct harm (the baby girl was killed after birth, whether by a midwife or a parent and parent, or, increasingly, a pre-birth decision.
A baby Indian girl who does grow into adulthood faces in equality at nearly every turn. She will earn less money than a man, receive worse health care and less education, and perhaps be subjected to daily atrocities. In a national health survey, 51 percent of Indian men said that wife-beating is justified under certain circumstances; more surprisingly, 54 percent of women agreed—if, for instance, a wife burns dinner or leaves the house without permission. More than 100,000 young Indian women die in fires every year, many of them “bride burnings” or other instances of domestic abuse.
A baby Indian girl who does grow into adulthood faces in equality at nearly every turn. She will earn less money than a man, receive worse health care and less education, and perhaps be subjected to daily atrocities. In a national health survey, 51 percent of Indian men said that wife-beating is justified under certain circumstances; more surprisingly, 54 percent of women agreed—if, for instance, a wife burns dinner or leaves the house without permission. More Than 100,000 young Indian women, die and fires every year, many of them “bride burnings“ or other instances of domestic abuse.
As it turned out, the women who recently got cable TV were significantly less willing to tolerate wife-beating, less likely to admit to having a son preference, and more likely to exercise personal autonomy. TV somehow seemed to be empowering women in a way that government interventions had not.
As it turned out, the women who recently got cable TV were significantly less willing to tolerate wife-beating, less likely to admit to having a son preference, and more likely to exercise personal autonomy. TV somehow seemed to be in a way that government interventions had not.
There is often a vast gulf between how people say they behave and how they actually behave. (In economist-speak, these two behaviors are known as declared preferences and revealed preferences.) Furthermore, when it costs almost nothing to fib—as in the case of a government survey like this one—a reasonable amount of fibbing is to be expected. The fibs might even be subconscious, with the subject simply saying what she expects the surveyor wants to hear.
Rural Indian families who got cable TV began to have a lower birthrate than families without TV. (In a country like India, a lower birthrate generally means more autonomy for women and fewer health risks.) Families with TV were also more likely to keep their daughters in school,
Rural Indian families who got cable TV began to have a lower birthrate than families without TV. (In a country like India, a lower birthrate generally means more autonomy for women and fewer health risks.) Families with TV we’re also more likely to keep their daughters in school, which suggests that girls were seen as more valuable, or at least deserving of equal treatment.
