Hidden Brain - Who's In Your Inner Circle?

Episode Date: January 10, 2023

If you think about the people in your life, it's likely that they share a lot in common with you. Maybe they like the same kinds of food, or enjoy the same hobbies. But, if you dig a little deeper, you may find that they share much more: they might make the same amount of money as you, or share the same race. This week, we talk with economists Luigi Pistaferri and Matthew Jackson about why we often surround ourselves with people who are just like us — and how we can transform our lives by pushing back against this phenomenon.  Did you catch last week's episode on the science of figuring out what you want? You can find it  here. And if you'd like to make a financial contribution to support our work, you can do so here. Thanks!

This is Hidden Brain, I'm Shankar Vedanta. Look up at the sky in most places in the world and you will see flocks of birds. Look carefully and you'll see these flocks are usually made up of the same kind of birds. Pigeons flap around with other pigeons, crows with crows, starlings congregate with well,

lots and lots of other starlings. Somewhere along the way, someone coined a memorable phrase, birds of a feather flocked together. Sociologists have noticed that this phenomenon is not restricted to birds. Humans tend to do the same thing, Except because we are complex creatures, the things that draw us together are not just physical similarities, but cultural constructions, such as social class, shared interests, and common cuisines. We think nothing of the fact that music lovers hang out with other music lovers, or that book readers congregate in book clubs, and that gardeners form their own societies. The internet has made it possible for people with all manner of niche interests

to discover others who are exactly like them. When we do think about this at all, we usually say it's a wonderful thing. Well, it is and it isn't. This week on Hidden Brain, the unintended consequences of enjoying the company of others who are just like us. The next time you attend a wedding, take a close look at the couples around you. The couple getting married, sure, but all the other couples too. How many couples do you think have both members vote for the same political party, or belong to the same race, or speak the same language?

The answer is obvious. Most people married to each other have similar backgrounds. They are usually of the same race or ethnicity. They might even have attended the same schools or work in similar professions. This hasn't always been the case. The old trope on television was the business executive or law firm partner invariably a man who ran off with the secretary. The new reality is that law firm partners tend to marry other

highly paid lawyers. Doctors get hitched to other medical professionals, especially in well-to-do communities, it's vanishingly rare for people to marry others from starkly different backgrounds. Matches that span significant educational divides, where one person has gone to say graduate school, while the other hasn't finished high school, are extremely rare. At Stanford University, Luigi Pistaferi studies the consequences of such matching. He uses the usual tools of the economist,

models, math, and data. But besides being an economist, Luigi is also a Jane Austen fan. The most important novel of Jane Austen, Pride and Prejudice, is kind of centered around the fact that the Bennett family wants to have all the daughters been married to people from hopefully higher social classes. You might remember the story. It centers around one of the Bennett daughters, Elizabeth, and her unlikely relationship

with Mr. Darcy, a very wealthy bachelor. His name is Darcy, and he has a mighty fortune at a greater state in Derbyshire. Their romance is unlikely, because Elizabeth is supposed to be well beneath Mr. Darcy's social class. When the seemingly mismatched lovers finally overcome many hurdles and get together, we are left with a treetly conclusion that love conquers all. I have been selfish being all my life. As a child I was given good principles, but I was left to follow them in pride and conceit.

Such I might still have been with you. You know, it's lovely, it still is. As a Jane Austen fan, Luigi loved the story, but as an economist, he doesn't buy the plot. You know, it's the kind of the comical aspect of it that is interesting. Together with the fact that it seems in the, you know, from watching the movies that the bandits are actually a lower social class, well, in fact, they were probably themselves in the top 10% of the time, you know, the three or four girls, I remember how many sisters there were, they were illiterate and, you know, they could have

servants in their house, already tells you that, you know, the Bennett family actually is not poor, but given their norms and amount of wealth inequality, there was at that time, it looks as if the kind of lower ranks of the society, while in fact they were pretty high up. Luigi says that if you think about pride and prejudice through the lens of an economist, in fact, if you think of love and marriage through the lens of an economist, you start to see things differently. You start to see lots and lots of what sociologists call homophily. Birds of a feather flocking together.

We economists tend to think in terms of markets, so here I'm referring to what we call the marriage market. So the marriage market homophily means someone marrying someone similar to themselves. So that could be cast in terms of wealth. I can be cast in terms of levels of education. It can be cast in terms of income. People from relatively high social classes try to marry someone from the very top of the distribution of social classes.

That would be Mr. Darcy, for example, in the novel. So the research in economics is a form of homophily we call it a sartini mating. A sort of mating is what you see when doctors pair up with other doctors. Or lawyers marry other lawyers. It goes back to that idea we discussed that most people tend to choose partners who are similar to themselves, in background, in education, in wealth. Several powerful forces drive a sort of mating.

Think about how and where people tend to meet romantic partners. On dating apps, you can filter potential matches based on education, professional background, age, and physical appearance. And the places where people are most likely to meet potential partners in real life, those tend to be school and work, situations where you are overwhelmingly likely to find others with similar interests and educational backgrounds. There are, you know, frictions, what we call frictions, costs of actually exploring the universe of potential mates that you can have. And so, you know, given that you don't have a lot of time to do this, you tend to marry people you encounter or you meet with in places where you spend most of your time. So it could be the workplace, it could be the place where you went to college and

indeed we observe a lot of the matches actually occurring happening through these two channels. There's a lot of people who end up meeting the person they marry, work or in college. This is a very common occurrence. On a recent visit to Chicago, I heard that 50% of University of Chicago undergrads end up marrying someone else from the same school. Now, that number seems improbably high, but the fact remains, homophily is a real thing in the marriage market. What striking Luigi says is how movies and popular culture celebrate a world that is very different than reality. He cites a famous movie from 1990.

The modern scene in the real story is, you know, kind of pretty woman. Add the moi richa gear and the, and junior Roberts. Hey sugar, you looking for a date? No, I want to find Beverly Hills. Can I give you directions? Sure. For five bucks. Ridiculous.

Crashes from up to ten. All right, okay. If all right, you win, I lose. Ah, so the story of a very wealthy man meeting almost randomly, the very poor girl, and then eventually, essentially marrying, I think, that's what the movie suggested. So that is an example that I use to show that the probability of that happening in the data is extremely low, although it's not zero.

But of course, we call it a Cinderella story precisely because it's unusual. Yeah, it's a sort of, you know, underdog stories. We all love underdog stories, but that doesn't make them very real. So they're very, you know, unusual, rare occurrences. So unusual, rare that we made movies about. How did you come to be studying a sort of meeting? Why were you drawn to this topic? What interests you in it? I studied wealth inequality and why wealth inequality and wealth concentration is rising over the last 20 to 30 years. And one thing that is often cited as an element that may have contributed to a rising wealth concentration is the marriage market. So, you know So people with wealth, manning other people with wealth,

kind of excessive date, the extent of wealth inequality or wealth concentration that you see in a society. Some time ago, Luigi spotted some very unusual data that allowed him to quantify the extent of a sort of mating in society. The data came from Norway. Why Norway? Well, in most countries, it's hard to find precise data on the socioeconomic backgrounds of people.

Most of us don't broadcast our bank balances, and the ones who tell us how rich they are are often narcissists who might be lying. But in Norway, banks directly report to the government about how much citizens have in their accounts. And then the other thing that is important is that Norway has a world tax, unlike the US, unlike many other countries. So the tax authority collects very detailed information on the assets you own, and pretty much all the assets you own.

So it could be housing, it could be the value of your stock. Market portfolio, it could be the bonds, it could be the value of private business, etc. So you have a very exhausting information on the assets that people own and also the debt that they have. Luigi and his colleagues collected 11 years worth of tax data? It included the income and assets of over five million people, the rich, the poor, and everyone in between. Next, they looked at marriage records. So what we did, first of all, was to look at the wealth of the assets that people have used before they get married. And in one advantage of this data is that you observe people before they enter their formal marriage relationship. So you know, you know, eventually if you're going to marry X, you know, how much income a wealth that

X person has before the marriage is observed. What did you find first in terms of who was marrying whom in Norway? find first in terms of who was marrying whom in Norway? So we find that, you know, if you rank people according to the wealth they have before marriage, then someone who has a wealth of a hundred will tend to marry with a high probability someone with a wealth of a hundred. And similarly, someone at the bottom will tend to marry someone who's similar to them. That sense we find strong evidence of a self-denimating. I just want to spend a moment talking about how this actually unfolds in real life. I mean, it's possible that people in Norway are actually asking one another,

how much money do you have in your bank balance? And basically saying, okay, you're on my list, you're off my list, but I suspect it doesn't happen at that level where someone's saying, show me your bank balance, and I'm going to decide whether to offer my hand in marriage or ask for your hand in marriage. I don't think it happens at that level. How is this happening with if those conversations are not transparent and on the surface? How is this matching actually taking place, do you think, Luigi? It seems to say you make this comment because actually know what that's happened. We have a lot of information. Because you know, we text records are actually public. Oh, I see. They're not just shared with the government. They're actually public.

Yeah. So if you have an internet, you know, access to the internet, and you have a social security number registered with the Norwegian tax authority, you can go on the web, enter the main or the person kind of looking for, and that would speed out information about assets, the income, the taxes they pay, the year they're born, where they live and so forth. So you have a pretty, if you want. I mean, the interesting thing is that the gum and that some part realize that this was a little bit between true, even by Norwegian standards, and they changed the roles, and you know, the roles is now, yes,

you can still search, but the person you search will know who's searching for them. So this discourage almost immediately a lot of the searches, you know, your neighbor, your colleague, and so on. Of course, what happens in Norway doesn't happen in most places. But Luigi says you don't need to access someone's detailed financial information to glean how wealthy they are. So you can infer how wealthy Simon is by the card that they drive or the kind of causes that they wear or things of that sort. So, or the type of indication they have, or what they can afford, where they go on vacation, etc.

So, there's a lot of signals of display of wealth that comes from the things that you spend your money on. One of the other things that you found in your paper fascinatingly was not just wealthy people pulling their wealth together, but what happens to that wealth afterwards? Can you talk about what you found Luigi? We find that people are really good at generating high return for their assets, tend to marry people very good at making a high return from their assets. There is, but there seems to be a certain

in mating or returns on top of the assault in mating wealth. Can I just ask you to try and speculate on what could be driving that? Because let's say, I show up at a date with a very fancy car, and my date shows up at the date in a driving a very fancy car. We can both infer that the other person is wealthy.

But how in the world would I know that my date actually has a high rate of return on his or her investment? And how would my date figure that out about me? You know, if you date someone, you typically don't marry a person after one day, you know, after going out one night. I mean, yes, there are the shotgun larges from Vegas, but you know, we're not talking about that. We're talking about normal people. So normal people, you know, kind of dates, sometimes go habit for a long time. So they learn a lot about what the other person does with his money before they actually

merge their wealth. And I use the example of, you know, Lady Mary in downtown Habby, you know, Lady Mary at some point has to Mary and because it's a society where, you know, she will marry some other rich guy, certainly made him wealthy as guaranteed. So the question is, you know, she has two potential students. So one is a guy who is really good at managing his, you know, estate and the other one is, you know, really someone who is an aristocrat. He's very wealthy, but he was the money in a few ways.

And so the question that we ask rhetorically is, OK, should she marry the guy who is not very good at managing his wealth? And the answer is, and this is something that we provide evidence for, the answer, which kind of person should she pick, is, well, it depends on who's going to end up managing the resources of the family after the family's four. So, in those families, where, of course, there is a lot of wealth, you have greater incentives to have, you know, efficiency. So, to have the portfolio being managed by someone is really good, now to start with.

really good and to start with. What Luigi is saying is that when wealthy people marry other wealthy people, the shared family wealth is invariably managed by the person with a better head for money. Maybe someone with an entrepreneurial streak or a sophisticated investor. A sort of mating ensures that with each generation, wealth not only merges with wealth, but that wealth accumulation accelerates on top of wealth. And this has profound consequences.

When you emerge your wealth, you have immediately a scale effect. You have accelerating forms of wealth inequality. So this is an explosive form of wealth inequality. So, you know, this is an explosive form of wealth acceleration. And that's exactly what, you know, people have seen if you look at work by economies like Emmanuel Saez and Gabriel Zuchman, that is exactly what are the findings they have for the United States. So in the last 30 years, the degree of concentration

of world distribution has been accelerating at a very fast rate. I'm wondering besides your academic work and your research, do you see the effects of a sort of mating around you, Luigi? Do you notice that in your social circle? I mean, I feel like as I read this paper, I started to think about the people who I know. And it's remarkable how similar so many of the couples are whom

I know. You know, this is whether they're older or younger. People tend to come from the same background. Is that the same for you? Oh, yeah. So, I mean, we have extreme cases like, you know, professors in the part that been married to other professors. So, that's an extreme form of sort in mating on education. And in fact, they have students working on that. I think it's very rare for people, you know, who get to the top of the distribution of education to be married with someone from, you know, high school degree degree or high school dropout.

If you look around you and you find some example, you know that these are very rare exceptions. So yeah, certainly, meetings everywhere. When we talk about wealth inequality, we typically think of systemic causes. The housing market, student debt, the tax system. We rarely think about how our own decisions, decisions that are very personal involving whom we love and whom we marry could accelerate inequality. When we come back, if our personal connections can exacerbate the problem of inequality, surprising new research suggests personal connections might also be the answer to the problem.

You're listening to Hidden Brain. I'm Shankar Vedantam. This is Hidden Brain, I'm Shankar Vedantam. When two people with similar interests, backgrounds and temperaments get together romantically, we're often inclined to say, the couple is made for each other. What is harder to see are the downstream effects of what is known as a sortative mating. Our tendency to connect with others like ourselves can greatly exacerbate inequality over time. This may be one reason why research by the Harvard economist Raj Shetty and his colleagues has found that where you are born can shape your outcomes in life. If you are born in a poor neighborhood and hang out with other people who are poor,

it's a lot harder to climb the socio-economic ladder than if you are a rich person born into a wealthy community. Here is Raj from our episode some years ago called Zipco Destiny. So think about upward mobility in the context of the classic Rags to Rich's kind of notion. Suppose you're a kid growing up in a low income family, say the bottom fifth of the income distribution. What are your odds of reaching the top fifth of the income distribution, making that leap from the bottom to the top?

So it turns out if you look at the US as a whole, that number is seven and a half percent, seven and a half percent of kids who start out in a relatively low income family will end up reaching the top fifth on average. That doesn't paint a very positive picture of economic mobility in the United States. Recently, however, new research suggests a way out of the trap. To understand what it is, I want to take you back to the early 1980s and the story of

a man named Matthew Jackson. So this was actually in late high school and then if the first couple of years in back to the early 1980s and the story of a man named Matthew Jackson. So this was actually in late high school and then if the first couple of years in college I was working in warehouses in Chicago, mostly unloading. Trucks was one of the few jobs that you could get without a connection. I needed the money to help pay for college And so it certainly wasn't a glamorous job. I mean, it was what you would expect. So it was a warehouse that sold catalog stuff

and we would ship televisions, household wears, diapers, food products, all kinds of things would come in these trucks. And our job was to sit there for hours and wait till a truck came and then get the truck unloaded in half an hour and then wait for the next one and it was, you know, hard work physically, but mentally it was just extremely boring. Matthew's managers had, shall we say, a less than trusting attitude toward him and his fellow blue collar workers. We had lie detector tests that we were given every couple of weeks, you know, because I think the main thing

that the company actually worried about was losing, they lost a lot of money to employ ethos. So it's easy for somebody unloading a truck to just unload something to the side and get away with it. It's a privilege of being bag falling off the truck. Exactly. So it was, you know, it was clearly a position that, you know, changed my perspective on work and what I wanted to do with my life. Matthew loved academics and wanted to do work that he found stimulating, but that turned out

to be really hard to find. And so when it came to college, to paying for a private university, there was a lot more money needed than we could afford. And so, you know, I worked during high school. I worked these trucking jobs and actually on weekends, I would work a night watchman shift at a local medical center. That was the best paying job I ever had at that time, which was, you know, I'd go in at midnight and then stay there until 8 a.m. and just walk around the building, making sure nobody was breaking in. You know, so it was jobs like that that were

available without connections. And so, you know, they were jobs that paid and, you know, helped save money for universities. That must have been pretty deadly boring as well, right? Walking around from midnight to 8 o'clock in the morning to make sure no one's breaking into a building. Yeah, the worst was a day where you did a shift of unloading trucks and then went to the medical center overnight. And by the next morning, you just completely went out. It was tough. Like many people without connections, Matthew

didn't have a way of breaking into the kind of job he knew he would be good at. But that changed one day after he got to college. He was having a chat with his undergraduate advisor Hugo Sonnanchine about his summer plans. So I was having a talk with Hugo one day in his office and he said, well, what are you going to do this summer? And I said, well, I'll go back to Chicago and unload trucks. And he said, no, no, no, no, no. You know, we're going to get you a job that you'll actually learn something from. And he literally picked up the phone while I was in his office and called a friend of his in Chicago, Galen Burkehart, who had been a friend of his from his years at University of

Massachusetts Amherst and said, you know, I've got this undergraduate, he needs some work, he lives in Chicago, Gailin was working in Chicago Mercantile Exchange and Gailin said, yeah, we can figure out something. When Matthew returned to Chicago, he started working at the Chicago Mercantile Exchange. All of a sudden, he realized that his math skills could be put to use in the field of economics. The summer job proved to be transformative. You know, that was just an incredible change in terms of the kind of work I was doing. And I was actually doing research for them, which eventually became a paper that I wrote and played into the research I did as a PhD student, so it was really life-changing

in many ways. That chance conversation with his advisor changed the trajectory of Matthew's life. He went on to become a respected economist, eventually finding his way to Stanford University. I think it's easy for us to underestimate how much our trajectory in life is determined by the connections that we have in terms of friends and family and how critical those are, you know, because it's not like every day these matter, but occasionally they matter and then they matter in a very big way. So, you know, without that connection, it's possible that I wouldn't have done that work

in the summers and I wouldn't have, you know, had that experience and it wouldn't have opened my eyes to research possibilities. I wouldn't have done a PhD. You know, it put me on a different road. And without that, I probably would have gone back and worked in the warehouse another summer and then, you know, who knows what would have happened after that.

But those kinds of connections, you know, they're infrequent in terms of the changes that they make, but they can be big changes at those points in time. Whether or not you get your foot in the door or not, is really so vital, and it really depends on our networks. So another element of the story that jumps out at me is that Hugo and Galen went to school together and of course they didn't go to school together in order that one day Hugo would introduce you to Galen. They didn't plan 25 years ahead.

So this was a chance, the fact that they were going to school together was probably driven by chance as much as anything else, but that chance encountered that they had ended up playing a pivotal role in your life. Yes, yeah. And I think, you know, that's one thing that is important to understand about our networks is that, you know, that they're not necessarily optimized in the sense that,

you know, connections that I make give me information that can help my students and can help my colleagues. And when I'm thinking about, oh, should I go to this conference and am I going to learn something new? I'm usually thinking about this for myself. I'm not thinking, oh, maybe I'll learn this thing, which I can actually tell so and so about. And so the full value of these kinds of interactions

and the importance of reaching out, the value of that to the greater society isn't something that's necessarily governing people's choices. When they're deciding, oh, should I go and do this? Or should I go and meet this person? Or is it makes sense to call this person? And do I follow through this friendship and so forth? So there's a lot of things that we do

that aren't optimizing on that. And the serendipitous relationships matter a lot and can have a lot of consequences, but they're not something that's fully accounted for when we form our relationships. And so that means that somehow we're all underforming and under broadening our networks and enriching ourselves. broadening our networks and enriching ourselves. What Matthew was pointing out is that social networks have ripple effects. I may think that my choice of friendship influences only me and my friends,

but in fact, those choices can profoundly shape the lives of other people down the road. the lives of other people down the road. When we come back, if our friendships and romantic attachments can unintentionally be the source of division and inequality, Matthews researchers found that they can also be drivers of connection and opportunity. You're listening to Hidden Brain, I'm Shankar Vedanta. This is Hidden Brain, I'm Shankar Vedanta. Some of the biggest problems in the world today are the result of mismanagement and corruption. But there are also many serious problems that stem from the internal architecture and predispositions of the human mind.

One of those powerful predispositions is that we gravitate toward people who are similar to us in some way. It's a phenomenon known as homophily. At Stanford University, Matthew Jackson says this happens so regularly in daily life that most of us don't even realize we do it. If you walk into a conference or a room or a meeting where there's people that you don't know, one of your natural tendencies is to start trying to find common ground. Oh, you ask people questions, and then once you find something in common, you really zero in on that, right? If you find that you both came from the same state or hometown, or that you both went to the same school at some point,

or that you both know somebody in common, those become points where you feel much more comfortable because now you've got something to talk about and something in common. It helps you understand the other person. It helps you understand their perspective. It reduces uncertainty. Psychologically, it's just much more comfortable to be in a situation where you understand the

other person and you know what their background is and their viewpoint than meeting somebody who you don't really understand at all and might have very different perspectives than you. That's a harder kind of situation to be in. And so we naturally tend to those things, even though that's not necessarily the best thing in our long-term interest. So I want you to talk a little bit about that, which is that these forces are in some way

such natural forces of feeling saying, I want to be comfortable around other people, and someone who basically shares my outlook or likes the same sports team or comes from the same geographic background or has the same racial background or income background. I feel more comfortable around this person and so I'm going to spend time with them. That very natural thing ends up playing this really consequential role when multiplied across an entire society. Can you talk about how this homophily essentially ends up

segregating groups of people and sealing off aspects of society or access to income mobility for people who are especially poor? Yeah, so I think one thing that's pretty amazing in the US is that there's a lot of heterogeneity. Different parts of the country have very different mobility patterns. You're much more likely to advance if you live and say the upper Midwest than if you live in the deep south.

There are places where you see connections across class lines, but there's a lot where you don't. There's a huge amount of homophily by economic class, and that tends to be in areas where you have very low mobility. When you look at it in terms of how predictive our parents' income of children's income, the U.S. doesn't do so well. The chance that you look like your parents is fairly high. And that means that, you know, for some reasons, children, their future is heavily determined

by the conditions that they're born into and the situations that they're born into. And at a fundamental level, there's something about that that rankles, doesn't it, which is that I think many of us imagine that we should not be constrained by the circumstances of our birth, by the accident of birth. We think that that should not determine what happens in terms of the outcomes in life. But really what you're saying is, accidents of birth are playing an enormous role in the likelihood of people's economic and social success in a country like the United States. Yes, definitely.

And in fact, I think, you know, when we think about the philosophy of it and the moral aspects of it, when people object to inequality, a lot of what we're objecting to is unequal opportunities because it's saying, you were just born in a circumstances no matter how hard you worked, you were going to be behind. And that's different than saying, oh, you know, so and so happened to get lucky or so and so is really talented. Obviously Michael Jordan can play basketball at a level that other humans can't, right? And we don't envy him.

Well maybe we envy him, but we don't say, oh, he doesn't deserve that what he earned from that. That's very different from saying somebody who's born in a community and never got a chance because of where they started. As they try to figure out how something works or how to fix a problem, scientists sometimes look for what's called positive deviants. Let's say a virus is spreading. You can study people who fall sick to figure out the nature of the pathogen.

But you can also study people who don't fall sick, the positive deviance, and ask what their secret is. If you can figure it out, the insight can help you keep other people from falling sick. In this case, the word deviant is not being used as a pejorative, but as something often accolade. Matthew and other researchers knew from the data that most kids who are born poor don't break into the ranks of the rich, but a small number do. What was their secret? Matthew's own life had been transformed by a chance

conversation and the fact that his college advisor was friends from his college days with someone who worked at the Chicago Mercantile Exchange. Matthew had a hunch, the same thing, on a massive scale, might be connected to differences he was seeing in income mobility. To test this idea, he turned to Facebook. Facebook was really valuable on several dimensions. So we were actually able to look at 84% of the population of the age group we were looking at.

Secondly, we can see all the friendships of these people and really see who are their high school friends, who are their college friends, who are their work friends, so we can actually classify where their friendships are formed, what their networks look like. We can also begin to see a lot of demographics about the people so we can estimate their income level and get information about exactly where they live and so forth. So just putting all that information together is something that's pretty rare to have.

And it allowed us to see how those social connections actually translate into the economic outcomes. And when you look at this pattern of friendships, what do you find in terms of homophily? Yeah, so the main thing that pops out in terms of the homophily that we were looking at was take somebody who's below median income and ask what fraction of their friends are above median income. If it was a completely well mixed random world, 50% of their friends should be above median income. It's just over 38% on average. If you look at people who are above median income, it's above 70% of their friends or above median income. So there's a huge gap between what fraction of people's

friends or above median income, depending on whether you're above or below yourself. And so that level of homophily is pretty strong. How did you measure people's income using Facebook data? So we inferred it. So we have locations on people people and then we have a lot of information about people, what phone they use, if they go to college, where did they go to college, it's so forth. There's just, you know, we use 22 variables, I think, in the end and a machine learning

algorithm that could basically estimate them. And we could put that together with census data. So census data goes down to a block level. So you have a very fine grade of where somebody is located. And the interesting thing about that is that if you're looking in the US and you look down to a block level, you pretty much can nail somebody's income. So putting that census data together with various variables we could observe with people in the locations, we could build a model that said, look, if you tell us these characteristics about a person, we can tell you pretty much what their income level is.

So at one level, what you're finding in some ways using this very large sample set is essentially a large scale replication of something that we've already known in a small scale, which is that people tend to cluster together. People who are poor tend to spend, have more friends who are poor, and fewer friends who are rich. People who are richer tend to have more friends who are rich. Fewer friends who are poor.

But you didn't just stop there. You actually went somewhere further with the study. Walk me through what you did now with all of these connections that you've established that people have or don't have. Yeah, so the, you know, the base question that we started with was, you know, what is it that predicts whether somebody who's born into the poor half of the distribution could end up in the top half of the income distribution? And in particular, there's lots of different things about a person's network and community

structure that you could imagine would matter. Things that are commonly referred to as social capital, right? We know financial capital matters. If you have wealth that helps you. If human capital, if your parents are educated, that's going to help you. But social capital, what is it about your network that matters? Three possibilities jumped out. One would just be, okay, does the community all know each other?

So we can look at that in a Facebook data, and you can just look at, okay, if my, I have two friends, are they friends with each other? And you can see how tightly knit communities are in terms of that clustering. So that's something we can measure directly. If poor kids from tight knit communities were the ones who made their way into upper-income groups, the solution to improve income ability would be to encourage greater community cohesion. Possibility, too, a higher degree of generosity and altruism in the community. If you come from an especially kind place, maybe there

are people and groups who can be stepping stones to help a poor kid succeed. The nationwide Facebook data contain the answer about people in different communities. You can see on their Facebook page are they part of a volunteer organization, are they part of some NGO or charity. When you look at things like the kinds of trust or volunteering rates and so forth, those are often associated with how well functioning are sort of the local organizations and do we have good institutions in our area. So those are things that we often think would help people out in terms of, you know, economic mobility. There was a third possibility to explain why poor people in some places were better able to

transform their economic station in life. These places had more connections between rich and poor people. They had bridges between groups that counteracted the effects of homophily. In these places, people were more likely to talk to people who came from different backgrounds than themselves. Poor people and rich people counted one another as friends or acquaintances. Matthew called this economic connectedness. You can find communities where you have no connectedness, but you have very strong clustering, or you can find places where people are very civically minded, but people don't cluster. So you can find each of these in different combinations across the country. And in the end, it turns out that the only thing that really was a strong predictor

was this economic connectedness of whether or not there were friendships between the poor people and the wealthier people. Matthew was blown away by the strength of the data. I think one of the surprising things to us, at least to me, was how strongly the economic connectedness ended up predicting somebody's mobility. And that means if you're in a community where you have strong economic connectedness, you're very likely to be in a community where the poor have a chance of growing up to have above median income or sort of rising. And that correlation also was stood all kinds of other things. So you could put in whatever variables you think of how poor is the area, how unequal is

the area, you know, is it urban, rural, what's the percent of white versus black versus Hispanic? You can look at all kinds of different variables. None of those really had nearly the same kind of power that this did. So I think one striking thing was how powerful that is as a predictor. So in other words, correct me if I'm wrong, but if I was a poor person in the United States and I wanted to ask myself, how can I extricate myself from my economic station and move to a better station in life? And I had to choose between living in a community that was very cohesive, where everyone knew

one another, people in some ways bonded together very tightly, or in a community that had very good social service organizations and charities, or I lived in a community that had very good social service organizations and charities or I lived in a community where I could actually be friends with people who were wealthier than I am. What I'm hearing you saying is that my odds would be the highest of actually changing my social station if I wasn't that last community. If I had friends from different economic strata. Yeah, overwhelmingly. So in fact, how well people know each other within your community and whether you have sort of well-functioning civic organizations

and connections to those are actually sometimes even negatively correlated with the outcome in terms of mobility. And I think part of what's actually happening here is that in those poorer communities, then you see more of that cohesiveness because people are helping each other out, and you see more volunteering, or you might see more volunteer organizations appearing because they're needed. And they provide vital help and informal support and services that you don't have otherwise.

vital help and informal support and services that you don't have otherwise. So they're still, you know, useful in some ways, but they're not helping poor kids grow up to be, you know, to have a chance at being not constrained and end up where their parents were. How much of a difference does economic connectedness make in a community? Yeah, so the difference in outcome if you take a typical poor kid and move them and give them the same friendships network that a typical rich kid would have, that predicts a 20% increase in their lifetime income. It's very hard to find any variable that has that kind of magnitude of change in lifetime income.

What do you think is actually happening at a granular level here? When people have these cross-SES, cross-social economic status friendships, what exactly do you think is happening? Are they just getting contacts? Are they getting leads to jobs? What do you think is actually changing their life outcomes? I think it's, you know, as with many things, it's a combination that matters.

There's those vital opportunities that might be rare, but it can matter. You know, it could be 10 years down the line that I have a former high school friend and I'm out of the job and I can call him up and say, oh, you know, I know you work at this bank, could you give me a job there? And they can say yes.

So it could be something like that, but it could also be just the information that we have when we're in high school. And am I seeing other kids go to college? Did I see what it took for them to go to college? Do I see them actually getting jobs afterwards? And what do I see them doing? What do I envision myself doing? A lot of that is formed by that community.

And I think when you put all these things together, you know, especially at an early age, they just amplify themselves, right? So the more you study, the more you can study, the more chance you have of advancing, the more friends you're gonna make who are also taking classes that are, you know, preparatory for going to college and so forth.

So it all plays into itself, and then it continues throughout your lifetime in terms of those friendships then giving you opportunities and everything else. I think just all of us can try to think a little bit about what is it that's limiting our networks, how can we do when are there opportunities for us to step out a little bit from what we normally do and broaden those horizons and bridge across whatever gap it is that might matter.

It's natural to want to spend time with people who I like us. It doesn't make you a bad person to join a book club or a bird watching group and find others who share the same interests, backgrounds and temperaments. But this very human impulse, magnified on the scale of a nation, has the propensity to create sealed economic caste systems, where it becomes very hard for people who are poor to change the trajectory of their lives. When we reach out to form connections with people in different economic stations, it has the potential to transform our lives, their lives, and the lives of strangers in the

far future. Hidden Brain is produced by Hidden Brain Media. Our audio production team includes Bridget McCarthy, Annie Murphy-Paul, Kristen Wong, Laura Correll, Ryan Katz, Autumn Barnes and Andrew Chadwick. Tara Boyle is our executive producer. I'm Hidden Brain's executive editor. For today's Anson Quiro, we're bringing you a story from our sister show, My Anson Quiro. Today's story comes from Senna Karumi. Some years ago Senna was living in France, working on a PhD. One cold winter weekend, she and her friends took a break and spent the day

at Disneyland Paris. This state as long as they could until it was finally time to catch the last tram home. One by one, all of Senna's friends got off at their stops until she was the only one left. And I noticed that the tram was super empty like there was just two people in there, two guys, both of them friends, and I wear the hijabs, I really stand out when I go, I do stand out. One of the men was in the front of the tram. The other set a few rows behind Senna. She didn't feel like either of them were paying her or her headscarf much attention, so

she put on her headphones and looked out the window. Something, maybe the switch, like the time between music or something like this, when you have the small silence, I heard something and it turned and I saw this guy just being very agitated. He was waving his hands and swearing and just pointing in my direction and I wasn't sure if it was me or the other guy because I didn't do anything that may trigger him to do that.

So I assumed that he was probably talking to the guy behind me. I took my head's phone off, and that when I heard all those very harmful words that he was saying, that we took the jobs, that we are making Europe and civilized, that we are everything that is wrong with Europe and France. At that moment I was like, yes, this is about me, this is differently about me. I wasn't scared, I was just numb and shocked, I didn't understand why is this happening. I didn't even cross my mind that I would be in danger, but it was like, why?

Why? Why? What did I do? Why? Just a senna began to stand, the man who had been sitting behind her rushed to the front of the tram and placed himself between her and the angry man. A few seconds he was up front of me and he kept on pushing the door of the tram. He kept on saying, you don't touch her, you don't say those words to her, she's just a student. Everything is wrong with Europe, it's you. At this phrase I remember it very clearly. Everything that is wrong with Europe is people like you, not her.

The man defending Senna kept the angry man from getting close to her. At the beginning he kept pushing him toward the tramway door and at the driver stopped the tram, this guy needs to get off the next station. Once the tram stopped, he pushed the man off the tram and then stood by the doors to make sure he couldn't get back on. He stayed there, didn't talk to me, stayed by the door, just like watching me. This happens a lot when you are veiled and especially in France. When they see you as veiled, they really don't know how to interact with you.

They don't know what are your boundaries. Some assuming that's why he didn't come and talk to me. Although it would have not been a problem at all, I probably would have welcomed it, but I'm pretty sure that that's the reason. So now it was too shocked to say anything either. She and the man stood in silence on the tram until her stop came. When she got out, the man followed and made sure that she got into her building safely. Senna was still in too much shock to turn around and say goodbye. It was the very first time that I encountered something like it in my entire life. I heard stories, of course I did,

I knew that it happens, but I never assumed that it would happen to me. And at the moment, even what the nice guy did, it didn't register, I was still so focused on what the bad guy said. Why was he attacking me? What did I do? And then somehow I was like, oh, but wait,

I wasn't alone in this. There was another guy who kind of knew that I didn't do anything wrong, that I didn't deserve the hatred and the violence. And he actually defended me. And then I said, wait, he had no reason to defend me. He wasn't sharing the same beliefs and the same culture. And yet he was there. He actually put himself

in danger by doing that. He could have gotten hurt. He could have gotten in so much trouble. And he didn't think about that. Every time Sana experienced Islamophobia after that day, she remembered the man who defended her. His kindness and courage gave her the strength to remain in France. I don't remember it as the day where I was attacked by a stranger, I remembered as the day where I was saved by a stranger. And that made all the difference, all the difference. And I'm really, really grateful to that guy for this.

Lysna Senna Karumi. Some years after the incident, Senna finished her PhD and moved back to her home country of Morocco. When we spoke to her, she was working as an international management consultant. If you would like to help us build more stories like this, please act now. Visit support.hiddenbrain.org and join the hundreds of other hidden brain listeners who have signed up to help. Again, that support.hiddenbrain.org.

I'm Shankar Vedantum. See you soon. you