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A recent study calculated that in the first year of a baby’s life, parents face 1,750 difficult decisions. These include what to name the baby, whether to breastfeed the baby, how to sleep-train the baby, what pediatrician to take the baby to, and whether to post pictures of the baby on social media. And that is only year one.
How can parents make these decisions, and the thousands to come? They can always turn to Google, but it’s easy to find conflicting answers to just about any question. The New York Times recommends that parents “try timeouts,” while PBS says “you should never use timeouts.” After reading “all” of the books on baby sleep, one frustrated mother, Ava Neyer, posted a rant on her blog:
Swaddle the baby tightly, but not too tightly. Put them on their back to sleep, but don’t let them be on their backs too long or they will be developmentally delayed. Give them a pacifier to reduce SIDS. Be careful about pacifiers because they can cause nursing problems and stop your baby from sleeping soundly. If your baby sleeps too soundly, they’ll die of SIDS.
I’m no parenting expert; I’m merely an uncle. (My decision making largely consists of asking my mom what gift I should get my nephew and her telling me “get him a truck” and me getting him a truck, and then my nephew thanking me for the next four years for once having gotten him a truck.) But I am an economist and a data scientist, and I’ve scoured the scientific literature to try to understand whether data can help people parent better. If you’re a parent who’s terrified of the consequences of choosing wrong, I’m here to tell you to worry less. Almost none of the decisions you make matter nearly as much as you think they do.
Let’s start with a basic question: How much do parents matter? How much can great parents improve a kid’s life, compared with average parents?
A major challenge with learning about parental influence is that correlation doesn’t imply causation. For example, kids whose parents read a lot to them tend to achieve more academically. But parents don’t just give their kids books. They also give them DNA. Are some kids drawn to books because of their parents’ reading habits? Or are both parent and child drawn to books because of their genetics? Is it nature or nurture?
Genes are powerful determinants. Consider the story of the identical twins Jim Lewis and Jim Springer, who were raised separately from the age of four weeks. They reunited at 39 and found that they were each six feet tall and weighed 180 pounds; bit their nails and had tension headaches; owned a dog named Toy when they were kids; went on family vacations at the same beach in Florida; had worked part-time in law enforcement; and liked Miller Lite beer and Salem cigarettes. There was one notable difference: Jim Lewis named his firstborn James Alan, while Jim Springer named his James Allan. Had Lewis and Springer never met each other, they might have assumed that their adoptive parents played big roles in creating their tastes. But it appears that those interests were, to a large degree, coded in their DNA.
The only way to scientifically determine just how much parents affect their kids would be to randomly assign different kids to different parents and study how they turned out. In fact, this has been done.
Since the 1950s, the nonprofit Holt International has helped American families adopt tens of thousands of children from Korea and other countries. Parents would sign up, get approved, and get the next available child who fit their general criteria. The process was essentially random, which gave scientists an opportunity. They could compare genetically unrelated children who were assigned to the same parents: The more the parents influenced the children, the more these adopted brothers and sisters would end up alike.
What the scientists found was that the family a kid was raised in had surprisingly little impact on how that kid ended up. Unrelated children adopted into the same home ended up only a little more similar than unrelated children who were raised separately. The effects of nature on a child’s future income were some 2.5 times larger than the effects of nurture.
Other researchers have done further studies of adoptees and twins, with similar results. As Bryan Caplan notes in his 2011 book, Selfish Reasons to Have More Kids, parents have only small effects on their children’s health, life expectancy, education, and religiosity (though studies have found that they have moderate effects on drug and alcohol use and sexual behavior, particularly during the teenage years, as well as how kids feel about their parents).
There are, of course, examples of parents who have had an enormous impact. Consider Jared Kushner. His father pledged $2.5 million to Harvard, which accepted Jared despite what were reportedly fairly low GPA and SAT scores. Jared then received a stake in his dad’s real-estate business. At the risk of being presumptuous, I think it is clear that his estimated $800 million net worth is many times higher than it would have been had he not inherited a real-estate empire. But the data suggest that the average parent—the one deciding, say, how much to read to their kids, rather than how many millions to give to Harvard—has limited effects on a kid’s education and income.
If the overall effects of parenting are this limited, the effects of individual parenting decisions are likely to be small. And indeed, if you stop reading the headlines from the parenting-industrial complex, and instead look at high-quality studies, you’ll find that’s the case for even the most debated techniques.
Some examples: One of the largest randomized controlled trials on breastfeeding found that it had no significant long-term effect on a variety of outcomes. A careful study of television use among preschoolers found that TV had no long-term effects on child test scores. A randomized trial suggests that teaching kids cognitively demanding games, such as chess, doesn’t make them smarter in the long term. A meta-analysis of bilingualism found that it has only small effects on a child’s cognitive performance, and that even these may be due to a bias in favor of publishing positive study results.
However, there is evidence that one decision may be very important—and it’s a decision that parenting experts and advice books rarely even consider.
In 1996, Hillary Clinton, then the first lady of the United States, published It Takes a Village: And Other Lessons Children Teach Us. Clinton’s book—and the proverb the title referenced—argue that children’s lives are shaped by many people in their neighborhood: firefighters and police officers, garbage collectors, teachers and coaches.
At that year’s Republican convention, Bob Dole, the nominee for president, took on Clinton’s thesis. By emphasizing the role that community members can play in a child’s life, he suggested, the first lady was minimizing parents’ responsibilities—a subtle attack on family values. “With all due respect,” Dole said, “I am here to tell you: It does not take a village to raise a child. It takes a family to raise a child.” The crowd roared.
So who was right, Bob Dole or Hillary Clinton?
For 22 years, no one could say. There wasn’t conclusive research one way or the other. The problem, once again, was the difficulty with establishing causality. Sure, some neighborhoods produce more successful kids: One in every 864 Baby Boomers born in Washtenaw, Michigan, the county that includes the University of Michigan, did something notable enough to warrant an entry in Wikipedia, while just one in 31,167 kids born in Harlan County, Kentucky, achieved that distinction. But how much of this is due to the kids of professors and other upper-middle-class professionals being really smart and ambitious—intelligence and drive they also would have used had they been born in rural Kentucky? The populations born in different neighborhoods are different, making it seemingly impossible to know how much a given neighborhood is causing its kids to succeed.
But several years ago, the economist Raj Chetty (a former professor of mine) and others began looking at this question. They had convinced the IRS to give their team of researchers de-identified and anonymous data on virtually an entire generation of American taxpayers. By linking the tax records of children and their parents, Chetty and his team could see where people had lived as children, and how much they ended up earning as adults. If a kid spent the first five years of her life in Philadelphia and then the rest of her childhood in Chicago, Chetty and his team knew that. They knew it for millions of Americans.
It was an extraordinary data set in the hands of an extraordinary scholar—and it offered a way out of the correlation problem. Chetty and his team focused on siblings who’d moved as kids. Take a hypothetical family of two children, Sarah and Emily Johnson. Suppose that when Sarah was 13 and Emily was 8, the family moved from Los Angeles to Denver. Suppose that Denver is a better place to raise a kid than Los Angeles. If this is the case, we would expect grown-up Emily to do better than Sarah, because she had five more years in Denver’s good-for-children air.
Now, perhaps Sarah was smarter, and outshone her sister despite Denver’s good influence. But if you have enough movers, the differences between specific siblings would cancel out. Also, because we can assume that siblings with the same parents have more or less the same genetic capabilities, we can be confident that the neighborhood is what’s driving any consistent differences in achievement. Multiply those differences over an entire universe of taxpayers and add some clever math, and you have a measure of the value of every neighborhood in the United States.
The results showed that some large metropolitan areas give kids an edge. They get a better education. They earn more money: The best cities can increase a child’s future income by about 12 percent. They found that the five best metropolitan areas are: Seattle; Minneapolis; Salt Lake City; Reading, Pennsylvania; and Madison, Wisconsin.
However, parents don’t merely pick a metropolitan area to live in. They have to pick neighborhoods within these areas, so Chetty and co. drilled down, determining that some were much more advantageous than others. They created a website, The Opportunity Atlas, that allows anyone to find out how beneficial any neighborhood is expected to be for kids of different income levels, genders, and races.
Something interesting happens when we compare the study on adoptions with this work on neighborhoods. We find that one factor about a home—its location—accounts for a significant fraction of the total effect of that home. In fact, putting together the different numbers, I have estimated that some 25 percent—and possibly more—of the overall effects of a parent are driven by where that parent raises their child. In other words, this one parenting decision has much more impact than many thousands of others.
Why is this decision so powerful? Chetty’s team has a possible answer for that. Three of the biggest predictors that a neighborhood will increase a child’s success are the percentage of households in which there are two parents, the percentage of residents who are college graduates, and the percentage of residents who return their census forms. These are neighborhoods, in other words, with many role models: adults who are smart, accomplished, engaged in their community, and committed to stable family lives.
There is more evidence for just how powerful role models can be. A different study that Chetty co-authored found that girls who move to areas with lots of female patent holders in a specific field are far more likely to grow up to earn patents in that same field. And another study found that Black boys who grow up on blocks with many Black fathers around, even if that doesn’t include their own father, end up with much better life outcomes.
Data can be liberating. It can’t make decisions for us, but it can tell us which decisions really matter. When it comes to parenting, the data tells us, moms and dads should put more thought into the neighbors they surround their children with—and lighten up about everything else.
This article has been adapted from Seth Stephens-Davidowitz’s forthcoming book, Don’t Trust Your Gut: Using Data to Get What You Really Want in Life.