Cross-Class Friendship Key to Rising Out of Poverty

BIANNA GOLODRYGA: Well, now we turn to the power of friendship. But not in the way you might expect. A new study has found that cross-class connections are key in helping children rise out of poverty. Behind the research is Raj Chetty, professor of economics at Harvard University and Director of Opportunity Insights, an organization studying have to give disadvantaged children a better chance of success. He speaks to Walter Isaacson about his research and how to restore the American dream.

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WALTER ISAACSON, HOST: Thank you, Bianna. And Professor Raj Chetty, welcome to the show.

RAJ CHETTY, WILLIAM A. ACKMAN PROFESSOR OF ECONOMIC, HARVARD UNIVERSITY AND OPPORTUNITY INSIGHTS DIRECTOR: Thank you, Walter. My pleasure.

ISAACSON: You published a while back, a few years ago, the Opportunity Atlas. And now, you have two papers in nature where you expand on that, where you talk about opportunities for kids from different zip codes, different backgrounds. Explain the Opportunity Atlas and how that led to these papers.

CHETTY: Yes, absolutely. So, for the past several years and my research here at Harvard, Opportunity Insights. We’ve been interested in understanding the roots of upward mobility in America. What gives children the best chances of rising up? What determines whether you go on to be successful in life, rising out of poverty if you grew up in an above-income family, and so on. And so, in some work we did several years ago to construct what we call the Opportunity Atlas, we use information from anonymized tax returns covering a centrally all children born in the U.S. in the early 1980s to measure children’s chances of rising up for every zip code in America. So, what we did is map kids back to where they grew up, link them to their parents using information from tax returns, and asked, if you grew up in a low-income family, say, a family making about $30,000 a year, how — where would you end up 30 years later in the income distribution? And what we found is there are really big differences in different parts of America in children’s chances of rising up. There are some parts of the country, like much of rural Iowa, for example, much of the Great Plains, where kids who grew up in a low-income families have great chances of rising into the middle class or beyond. But then there are other parts of the country, much of the southeast, cities like Charlotte and Atlanta. Places like Detroit and Indianapolis where kids’ chances of rising up are much poorer. And so, Walter, the key question that emerged from that earlier work is, what is driving that variation? Why is it that kids in certain cities and some neighborhoods have much better chances of rising up than others? And naturally, we, and many other researchers, have investigated a variety of explanations. Things like the quality of local schools, poverty rates, rates of crime, of issues like family structure, and so forth. And people have found a role for each of these, but there is still a lot that remained to be explained. And that’s what motivated this most recent work on trying to understand the potential importance of social capital in driving economic mobility.

ISAACSON: One of the factors you didn’t mention in that long list was race. To what extent is that correlated?

CHETTY: Yes. So, there are important differences by race in upward mobility in America. And I’m glad you emphasized that. I think race plays an incredibly important role here. And so, in some of our earlier work, we showed that black kids and black boys, in particular, have much lower chances of rising up in the income distribution relative to white boys. Even controlling for parental income. So, if you take a black boy and a white boy starting in a family, earning the same amount, living in the same neighborhood, going to the same school, both raised in a two-parent household, you still see really significant differences in their prospects for rising up. And that is what underlies racial disparities in America, and is an important ongoing factor that, of course, we’re all aware of and something to be addressed going forward.

ISAACSON: In these new studies, you used a Gotcha (ph). I mean, a real Gotcha, a Facebook data. I mean, millions and millions. First of all, how did you get Facebook to allow you to use that data? Was it anonymized? And to what — how do you end up processing that much data?

CHETTY: I, with my collaborators, approached Meta, the owner of Facebook and Mark Zuckerberg to talk about this idea of whether we could use Facebook data in a privacy protected manner to study these important social questions. In particular, whether social capital might be relevant for economic mobility, and how we might be able to increase social capital in America. And I think, like many private sector companies, naturally, there are concerns about protecting privacy, making sure the data are used in ways that can inform policy but don’t compromise any single person’s information. And so, we took a number of steps, Walter, to anonymize the data. To make sure any statistics we’re releasing would not inadvertently reveal information about any one person. Taking all those safeguards, we were then able to take, as you noted, an enormous data set. Data on 70 million Facebook users between the ages of 25 and 44. So, why that age range? We want to focus on an age range for lots of people who are on Facebook. In that age range, 85 percent of Americans are on the Facebook platform. So, you have good data and virtually everybody in the country in that age range. And between them, they have 21 billion friendships, which we then analyzed using the power of modern technology to construct measures for every zip code and every high school and every college in America on different notions of social capital. So, one example is to what extent are low-income and high-income people friends with each other in a given place? Another example is what we call cohesiveness. To what extent is a network of friends fragmented into separate clicks versus everyone being friends with everyone? A more cohesive community. So, we were able to construct a variety of different measures of social capital using these unprecedented new data.

ISAACSON: So, what were the findings? What did you figure out about what allow some kids to rise from the lowest levels of poverty to upper and middle class, and some kids not to be able to?

CHETTY: So, there is a very simple and clear finding from the data, which is, if you look at these different measures of social capital, measures of connections between people in different levels of income, measures of cohesiveness, the fragmentation of networks, or other measures that people have talked about like volunteering rates. How much people trust each other? How strong are — is the community? The data show clearly that that first set of measures of cross-class interaction are strongly predictive of upward mobility. In fact, the strongest predictor we have identified, to date, in numerous studies that researchers have done. So, what I mean by that is, if you grow up in a zip code where low-income folks are interacting more with high-income folks, you see significantly higher rates of upward mobility. You are more likely to rise out of poverty if you move at a young age to a zip code where there’s more interaction across class lines. So, that’s a very clear result that emerges from the data. And what’s more, Walter, and what really, I think, had us excited is that that relationship explains a lot of prior findings that people had established in the literature. So, we talked earlier, for example, about the role of race. It’s been well documented that more racially segregated neighborhoods tend to have lower rates of upward economic mobility. Kids are less likely to stay poverty in areas that are predominantly black neighborhoods, for example. And so, what we show in this study is that pattern is completely explained by this measure of cross-class interaction that we call economic connectedness. Those types of neighborhoods, racially segregated areas, tend to be very disconnected. Low-income kids there tend not to have many interactions with folks from higher income backgrounds who might provide them with job opportunities, with internships, with information about how to apply to college, who might shift their aspirations. And once we account for that, we can fully explain why more racially segregated areas have lower levels of upward mobility. So, a number of previous patterns have been documented that are somewhat puzzling can be explained by this new measure of cross-class interaction.

ISAACSON: So, you looked at Facebook friending, for example, and you found in some zip codes, people made friends from people of different economic classes. And some zip codes, they tended to stick in their own class. And I think you compared Silver Spring, Maryland to Little Rock, right? How do you factor out the other possible things that are different between Little Rock and Silver Spring, Maryland?

CHETTY: Yes, that’s a great question. What we’re able to do, Walter, is two things. First, by looking at kids who move at different ages to these neighborhoods. We’re able to show that it’s something about growing up in a neighborhood that has a lot of cross-class interaction that leads kids to do better in adulthood. So, if you move at an early year age to one of these places, you have a better chance of rising out of poverty than if you move later. So, that shows us there’s kind of a dosage effect and indicates that it’s something about the environment in which you are growing up that is having an influence. It rules out the possibility that it’s just different types of people living in different places, who get different jobs. You know, it can’t be something as simple as that. But then second, you know, let’s take one specific example. We see that places where people have more higher-income friends, they tend to be places with lower poverty rates. That makes intuitive sense, right? You tend to be friends with the people around you. If you live in a very poor community, you’re going to have fewer high-income friends. So, you might wonder, well, places with – that have lower incomes, they also have less resources for their schools, with property tax, financing. They may have higher rates of crime. They may have other lack of resources on various dimensions. And so, how do we know that it’s about the economic connectedness and not the poverty rates directly that are affecting kids’ outcomes? So, what we’re able to do is an analysis where we compare the effects of poverty rates versus cross-class interaction. So, basically, think of an example where we take a bunch of places that have different rates of poverty, but all have the same level of interaction across class lines. What we show is across those places, there’s not much a difference in kids’ chances of rising up, even though some are much richer than others. But now, think about the opposite dimension. Suppose I look at places where the poor interact a lot more with the rich, but they all have the same level of incomes overall. There I find an enormous difference in economic mobility as I move to the places where the poor interacting more with the rich. So, doing comparisons like this across the thousands of zip codes in America, it really looks like the key factor that predicts differences in economic mobility are the degree of cross-class interaction, not poverty rates.

ISAACSON: OK. I get it. And I really loved reading the papers. But what should we do about it? What are the policy implications?

CHETTY: Yes, so I think what this data suggests, like a lot of recent work on these issues, is that first of all this is changeable. We don’t have to look to the Scandinavian system or back to the 1950s to a period where we had much higher economic mobility in order to figure out how to change things. Often, you just need to look two miles down the road and you see kids having much better chances of rising up. So, we should see that as an encouraging sign in an era with a lot of pessimism about many social and economic issues. There are places where things are thriving. And I think we need to focus on those, learn from them, and figure out how we can, A, maybe give kids access to those opportunities by helping them perhaps move those neighborhoods. Desegregating our cities through things like affordable housing programs, housing measures, changing and zoning regulations, and so on. All of which can create that integration and provide greater access to opportunity. But then second, figure out how you bring opportunity to the neighborhoods where it’s currently lacking. And what these latest papers are suggesting is that thinking about social interaction and how, in particular, you bring people together so that they actually interact across class lines may be an important element to focus on. And critically there, Walter, I think there’s a lot of discussion about what we call the exposure dimension. So, bringing people together physically, where we try and integrate schools, where we try to change school district boundaries, or change zoning laws, and so on. And I think while we haven’t been completely successful, there’s a lot of focus on that type of thing, reducing segregation in America. But what we show in this new work is that, even conditional on that, there is a tendency for people not to interact with people from different backgrounds, even when they go to the same school, what we call friending biased, and figuring out how to tackle that dimension, I think, is equally important. Trying to understand why kids are splitting apart within schools. How you might change that through things like changes in tracking policies, the size of classrooms, and so forth.

ISAACSON: Yes, I noticed that when you look at the friending data. If it’s a really big school or a really big institution of any type, it’s harder. People self-segregate a bit. But if you make it into smaller interactions, maybe you can have more socioeconomic mixing. Is that some policy we should be doing in our schools, having smaller schools and —

CHETTY: I think that’s exactly right, Walter. And the intuition is really very simple. I mean, think about going to a dinner party where there are 10 people who are invited. You probably will talk to everybody by the end of the evening. Suppose you go to a party with 500 people, you’re probably going to go look for the folks you know. People who are like you. And not end up interacting with everyone. So, that phenomenon plays out systematically across our institutions.

ISAACSON: And on the flip side, it seems to be an argument against what happens at some schools, universities, whatever, in which you have clubs based on various things. Including ethnic clubs, or racial clubs, or you know, fraternities. Does that work against cross-economic mixing?

CHETTY: That’s exactly right. So, what we see in the data is places — colleges, that have more group life, for example. To take one example that you mentioned, fraternities and sororities, they tend to be the ones that have a lot of friending bias. So, you can have these big public institutions that, in principle, on the surface, look very diverse. They look like they’re bringing people together. But in practice, and it’s very interesting to read things like student newspapers that bring this out, you know, because of simple things like dos or the costs associated with activities that certain kids might be able to participate in and not others. You start to get the segmentation within the student body. It also goes beyond colleges, Walter. So, an example, we’ve given the paper and I think it’s telling is if you look at religious institutions, faith- based organizations, or you look at recreational groups, those are some of the groups where we see the least friending bias, where we see the most interaction across class lines. And my sense of what might be going on there is, at your church or in your synagogue, in your temple, you know, you see people from different backgrounds and you have something in common. And that tends to lead to interactions across class lines that look different than they do in other settings where there’s this kind of stratification. So, certainly, something to think more about. What is it about those places where we might be able to learn some lessons? And think about how we create some of our interactions in other settings as well.

ISAACSON: What you’re writing about goes to the heart of the American dream. This notion that people can — as Benjamin Franklin wrote about in his autobiography, start off poor with a few coins in his pocket, and move up in the world. So, based on all of these studies, what can people like us, what can we do to make sure that America remains a land of opportunity?

CHETTY: So, what I would suggest is the simplest message. You know, when we think of issues like the American dream, inequality, trans and economic mobility, there’s a tendency to think, oh, that’s all in the hands of federal policymakers. And we’ve got to resolve this in Washington before anything is really going to change. And I think, of course, federal policy is extremely important. But what these data are showing, the sharp community level differences are that there’s a lot we can do in our own communities to try to create more integration. In fact, you can look up the data yourself. Go to a website called the Social Capital Atlas at socialcapital.org. Anyone can freely access. Just type in your address, and you can see in your community to what extent are low-income folks interacting with high-income folks. And if it’s low, is that because of a lack of exposure. That people are attending different groups versus, you know, the friending bias phenomenon within schools and so on. And using that kind of information, you know, it could be as simple as, when you’re deciding where to send your kid, to a camp, and if you’re interested in creating more of this cross-class interaction, you know, maybe you make a different decision there or foster a different set of interactions in terms of who you invite over, or where you volunteer, or the kinds of activities you participate in. I honestly think each of us can make a significant difference at the individual level. I also think we need systematic policy changes and things like zoning regulations, and affordable housing, and schools, and so forth. But these are complex problems where each of us can be empowered to really make a difference in reviving the American dream.

ISAACSON: Professor Raj Chetty, thanks so much for joining us.

CHETTY: Thank you, Walter. My pleasure.