Here are four attributes of a city—three of them do not correlate with poor people’s life expectancy, and one of them does. See if you can guess which one matters.
WHAT MAKES POOR PEOPLE IN A CITY LIVE MUCH LONGER?
The city has a high level of religiosity.
The city has low levels of pollution.
The city has a higher percentage of residents covered by health insurance.
A lot of rich people live in the city.
The first three—religion, environment, and health insurance—do not correlate with longer life spans for the poor. The variable that does matter, according to Chetty and the others who worked on this study? How many rich people live in a city. More rich people in a city means the poor there live longer. Poor people in New York City, for example, live a lot longer than poor people in Detroit.
Why is the presence of rich people such a powerful predictor of poor people’s life expectancy? One hypothesis—and this is speculative—was put forth by David Cutler, one of the authors of the study and one of my advisors. Contagious behavior may be driving some of this.
There is a large amount of research showing that habits are contagious. So poor people living near rich people may pick up a lot of their habits. Some of these habits—say, pretentious vocabulary—aren’t likely to affect one’s health. Others—working out—will definitely have a positive impact. Indeed, poor people living near rich people exercise more, smoke less, and are less likely to suffer from obesity.
My personal favorite study by Raj Chetty’s team, which had access to that massive collection of IRS data, was their inquiry into why some people cheat on their taxes while others do not. Explaining this study is a bit more complicated.
The key is knowing that there is an easy way for self-employed people with one child to maximize the money they receive from the government. If you report that you had taxable income of exactly $9,000 in a given year, the government will write you a check for $1,377—that amount represents the Earned Income Tax Credit, a grant to supplement the earnings of the working poor, minus your payroll taxes. Report any more than that, and your payroll taxes will go up. Report any less than that, and the Earned Income Tax Credit drops. A taxable income of $9,000 is the sweet spot.
And, wouldn’t you know it, $9,000 is the most common taxable income reported by self-employed people with one child.
Did these Americans adjust their work schedules to make sure they earned the perfect income? Nope. When these workers were randomly audited—a very rare occurrence—it was almost always found that they made nowhere near $9,000—they earned either substantially less or substantially more.
In other words, they cheated on their taxes by pretending they made the amount that would give them the fattest check from the government.
So how typical was this type of tax fraud and who among the self-employed with one child was most likely to commit it? It turns out, Chetty and colleagues reported, that there were huge differences across the United States in how common this type of cheating was. In Miami, among people in this category, an astonishing 30 percent reported they made $9,000. In Philadelphia, just 2 percent did.
What predicts who is going to cheat? What is it about places that have the greater number of cheaters and those that have lower numbers? We can correlate rates of cheating with other city-level demographics and it turns out that there are two strong predictors: a high concentration of people in the area qualifying for the Earned Income Tax Credit and a high concentration of tax professionals in the neighborhood.
What do these factors indicate? Chetty and the authors had an explanation. The key motivator for cheating on your taxes in this manner was information.
Most self-employed one-kid taxpayers simply did not know that the magic number for getting a big fat check from the government was $9,000. But living near others who might—either their neighbors or tax assisters—dramatically increased the odds that they would learn about it.
In fact, Chetty’s team found even more evidence that knowledge drove this kind of cheating. When Americans moved from an area where this variety of tax fraud was low to an area where it was high, they learned and adopted the trick. Through time, cheating spread from region to region throughout the United States. Like a virus, cheating on taxes is contagious.
Now stop for a moment and think about how revealing this study is. It demonstrated that, when it comes to figuring out who will cheat on their taxes, the key isn’t determining who is honest and who is dishonest. It is determining who knows how to cheat and who doesn’t.
So when someone tells you they would never cheat on their taxes, there’s a pretty good chance that they are—you guessed it—lying. Chetty’s research suggests that many would if they knew how.
If you want to cheat on your taxes (and I am not recommending this), you should live near tax professionals or live near tax cheaters who can show you the way. If you want to have kids who are world-famous, where should you live? This ability to zoom in on data and get really granular can help answer this question, too.
I was curious where the most successful Americans come from, so one day I decided to download Wikipedia. (You can do that sort of thing nowadays.)
With a little coding, I had a dataset of more than 150,000 Americans deemed by Wikipedia’s editors to be notable enough to warrant an entry. The dataset included county of birth, date of birth, occupation, and gender. I merged it with county-level birth data gathered by the National Center for Health Statistics. For every county in the United States, I calculated the odds of making it into Wikipedia if you were born there.
Is being profiled in Wikipedia a meaningful marker of notable achievement? There are certainly limitations. Wikipedia’s editors skew young and male, which may bias the sample. And some types of notability are not particularly worthy. Ted Bundy, for example, rates a Wikipedia entry because he killed dozens of young women. That said, I was able to remove criminals without affecting the results much.
I limited the study to baby boomers (those born between 1946 and 1964) because they have had nearly a full lifetime to become notable. Roughly one in 2,058 American-born baby boomers were deemed notable enough to warrant a Wikipedia entry. About 30 percent made it through achievements in art or entertainment, 29 percent through sports, 9 percent via politics, and 3 percent in academia or science.
The first striking fact I noticed in the data was the enormous geographic variation in the likelihood of becoming a big success, at least on Wikipedia’s terms. Your chances of achieving notability were highly dependent on where you were born.
Roughly one in 1,209 baby boomers born in California reached Wikipedia. Only one in 4,496 baby boomers born in West Virginia did. Zoom in by county and the results become more telling. Roughly one in 748 baby boomers born in Suffolk County, Massachusetts, where Boston is located, made it to Wikipedia. In some other counties, the success rate was twenty times lower.
Why do some parts of the country appear to be so much better at churning out America’s movers and shakers? I closely examined the top counties. It turns out that nearly all of them fit into one of two categories.
First, and this surprised me, many of these counties contained a sizable college town. Just about every time I saw the name of a county that I had not heard of near the top of the list, like Washtenaw, Michigan, I found out that it was dominated by a classic college town, in this case Ann Arbor. The counties graced by Madison, Wisconsin; Athens, Georgia; Columbia, Missouri; Berkeley, California; Chapel Hill, North Carolina; Gainesville, Florida; Lexington, Kentucky; and Ithaca, New York, are all in the top 3 percent.
Why is this? Some of it is may well be due to the gene pool: sons and daughters of professors and graduate students tend to be smart (a trait that, in the game of big success, can be mighty useful). And, indeed, having more college graduates in an area is a strong predictor of the success of the people born there.
But there is most likely something more going on: early exposure to inn
ovation. One of the fields where college towns are most successful in producing top dogs is music. A kid in a college town will be exposed to unique concerts, unusual radio stations, and even independent record stores. And this isn’t limited to the arts. College towns also incubate more than their expected share of notable businesspeople. Maybe early exposure to cutting-edge art and ideas helps them, too.
The success of college towns does not just cross regions. It crosses race. African-Americans were noticeably underrepresented on Wikipedia in nonathletic fields, especially business and science. This undoubtedly has a lot to do with discrimination. But one small county, where the 1950 population was 84 percent black, produced notable baby boomers at a rate near those of the highest counties.
Of fewer than 13,000 boomers born in Macon County, Alabama, fifteen made it to Wikipedia—or one in 852. Every single one of them is black. Fourteen of them were from the town of Tuskegee, home of Tuskegee University, a historically black college founded by Booker T. Washington. The list included judges, writers, and scientists. In fact, a black child born in Tuskegee had the same probability of becoming a notable in a field outside of sports as a white child born in some of the highest-scoring, majority-white college towns.
The second attribute most likely to make a county’s natives successful was the presence in that county of a big city. Being born in San Francisco County, Los Angeles County, or New York City all offered among the highest probabilities of making it to Wikipedia. (I grouped New York City’s five counties together because many Wikipedia entries did not specify a borough of birth.)
Urban areas tend to be well supplied with models of success. To see the value of being near successful practitioners of a craft when young, compare New York City, Boston, and Los Angeles. Among the three, New York City produces notable journalists at the highest rate; Boston produces notable scientists at the highest rate; and Los Angeles produces notable actors at the highest rate. Remember, we are talking about people who were born there, not people who moved there. And this holds true even after subtracting people with notable parents in that field.
Suburban counties, unless they contained major college towns, performed far worse than their urban counterparts. My parents, like many boomers, moved away from crowded sidewalks to tree-shaded streets—in this case from Manhattan to Bergen County, New Jersey—to raise their three children. This was potentially a mistake, at least from the perspective of having notable children. A child born in New York City is 80 percent more likely to make it into Wikipedia than a kid born in Bergen County. These are just correlations, but they do suggest that growing up near big ideas is better than growing up with a big backyard.
The stark effects identified here might be even stronger if I had better data on places lived throughout childhood, since many people grow up in different counties than the one where they were born.
The success of college towns and big cities is striking when you just look at the data. But I also delved more deeply to undertake a more sophisticated empirical analysis.
Doing so showed that there was another variable that was a strong predictor of a person’s securing an entry in Wikipedia: the proportion of immigrants in your county of birth. The greater the percentage of foreign-born residents in an area, the higher the proportion of children born there who go on to notable success. (Take that, Donald Trump!) If two places have similar urban and college populations, the one with more immigrants will produce more prominent Americans. What explains this?
A lot of it seems to be directly attributable to the children of immigrants. I did an exhaustive search of the biographies of the hundred most famous white baby boomers, according to the Massachusetts Institute of Technology’s Pantheon project, which is also working with Wikipedia data. Most of these were entertainers. At least thirteen had foreign-born mothers, including Oliver Stone, Sandra Bullock, and Julianne Moore. This rate is more than three times higher than the national average during this period. (Many had fathers who were immigrants, including Steve Jobs and John Belushi, but this data was more difficult to compare to national averages, since information on fathers is not always included on birth certificates.)
What about variables that don’t impact success? One that I found more than a little surprising was how much money a state spends on education. In states with similar percentages of its residents living in urban areas, education spending did not correlate with rates of producing notable writers, artists, or business leaders.
It is interesting to compare my Wikipedia study to one of Chetty’s team’s studies discussed earlier. Recall that Chetty’s team was trying to figure out what areas are good at allowing people to reach the upper middle class. My study was trying to figure out what areas are good at allowing people to reach fame. The results are strikingly different.
Spending a lot on education helps kids reach the upper middle class. It does little to help them become a notable writer, artist, or business leader. Many of these huge successes hated school. Some dropped out.
New York City, Chetty’s team found, is not a particularly good place to raise a child if you want to ensure he reaches the upper middle class. It is a great place, my study found, if you want to give him a chance at fame.
When you look at the factors that drive success, the large variation between counties begins to make sense. Many counties combine all the main ingredients for success. Return, again, to Boston. With numerous universities, it is stewing in innovative ideas. It is an urban area with many extremely accomplished people offering youngsters examples of how to make it. And it draws plenty of immigrants, whose children are driven to apply these lessons.
What if an area has none of these qualities? Is it destined to produce fewer superstars? Not necessarily. There is another path: extreme specialization. Roseau County, Minnesota, a small rural county with few foreigners and no major universities, is a good example. Roughly 1 in 740 people born here made it into Wikipedia. Their secret? All nine were professional hockey players, no doubt helped by the county’s world-class youth and high school hockey programs.
So is the point here—assuming you’re not so interested in raising a hockey star—to move to Boston or Tuskegee if you want to give your future children the utmost advantage? It can’t hurt. But there are larger lessons here. Usually, economists and sociologists focus on how to avoid bad outcomes, such as poverty and crime. Yet the goal of a great society is not only to leave fewer people behind; it is to help as many people as possible to really stand out. Perhaps this effort to zoom in on the places where hundreds of thousands of the most famous Americans were born can give us some initial strategies: encouraging immigration, subsidizing universities, and supporting the arts, among them.
Usually, I study the United States. So when I think of zooming in by geography, I think of zooming in on our cities and towns—of looking at places like Macon County, Alabama, and Roseau County, Minnesota. But another huge—and still growing—advantage of data from the internet is that it is easy to collect data from around the world. We can then see how countries differ. And data scientists get an opportunity to tiptoe into anthropology.
One somewhat random topic I recently explored: how does pregnancy play out in different countries around the world? I examined Google searches by pregnant women. The first thing I found was a striking similarity in the physical symptoms about which women complain.
I tested how often various symptoms were searched in combination with the word “pregnant.” For example, how often is “pregnant” searched in conjunction with “nausea,” “back pain,” or “constipation”? Canada’s symptoms were very close to those in the United States. Symptoms in countries like Britain, Australia, and India were all roughly similar, too.
Pregnant women around the world apparently also crave the same things. In the United States, the top Google search in this category is “craving ice during pregnancy.” The next four are salt, sweets, fruit, and spicy food. In Australia, those cravings don’t differ all that much: the
list features salt, sweets, chocolate, ice, and fruit. What about India? A similar story: spicy food, sweets, chocolate, salt, and ice cream. In fact, the top five are very similar in all of the countries I looked at.
Preliminary evidence suggests that no part of the world has stumbled upon a diet or environment that drastically changes the physical experience of pregnancy.
But the thoughts that surround pregnancy most definitely do differ.
Start with questions about what pregnant women can safely do. The top questions in the United States: can pregnant women “eat shrimp,” “drink wine,” “drink coffee,” or “take Tylenol”?
When it comes to such concerns, other countries don’t have much in common with the United States or one another. Whether pregnant women can “drink wine” is not among the top ten questions in Canada, Australia, or Britain. Australia’s concerns are mostly related to eating dairy products while pregnant, particularly cream cheese. In Nigeria, where 30 percent of the population uses the internet, the top question is whether pregnant women can drink cold water.
Are these worries legitimate? It depends. There is strong evidence that pregnant women are at an increased risk of listeria from unpasteurized cheese. Links have been established between drinking too much alcohol and negative outcomes for the child. In some parts of the world, it is believed that drinking cold water can give your baby pneumonia; I don’t know of any medical support for this.
The huge differences in questions posed around the world are most likely caused by the overwhelming flood of information coming from disparate sources in each country: legitimate scientific studies, so-so scientific studies, old wives’ tales, and neighborhood chatter. It is difficult for women to know what to focus on—or what to Google.
We can see another clear difference when we look at the top searches for “how to ___ during pregnancy?” In the United States, Australia, and Canada, the top search is “how to prevent stretch marks during pregnancy.” But in Ghana, India, and Nigeria, preventing stretch marks is not even in the top five. These countries tend to be more concerned with how to have sex or how to sleep.
Everybody Lies Page 15