Commencement Nadarajan “Raj” Chetty

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MAY 28, 2022

Nadarajan “Raj” Chetty is the William A. Ackman Professor of Economics at Harvard University and the director of Opportunity Insights, which studies the science of economic opportunity. His research combines empirical evidence and economic theory to help design more effective government policies.

Chetty was awarded a Doctor of Humane Letters honorary degree by Amherst College. See the honorary degree citation read by President Biddy Martin at the Commencement 2022 ceremony.

At his talk, Chetty was introduced by Josh Hyman, Assistant Professor of Economics.

Hear Raj Chetty’s talk:

Transcript

Josh Hyman:
Welcome, everyone, and thank you for being here today. Thanks for coming out in this not-so-great weather. I really appreciate it. And congratulations to those of you who are members of the Class of 2022 and friends and family of the graduates. Great, great to see you all here. I'm Josh Hyman. I'm an assistant professor of economics at the college, and I'm a labor and public finance economist studying primarily economics of education, school finance, and inequality. So it's a real special pleasure for me to be able to introduce today's speaker. And so just to set some context here, at each Amherst Commencement, the college awards honorary doctoral degrees to special invitees and recognition of the outstanding contributions in their field.

Josh Hyman:
The individuals chosen for this recognition are not only selected because of their sort of extraordinary contributions to their field, but also because we believe that the arc of their career and their vision and their commitment to excellence really is sort of inspirational for our own students in thinking about them trying to make contributions to society after they graduate Amherst. We're really grateful to our honored guests for generously giving these public talks so that we could have a little more of an intimate experience with them and hear directly from them about their work. So your questions are welcomed following today's talk, and please just remain in your seat, and when the sort of talk is done, I'll have a little handheld mic and I'll go around and I'll give you the microphone. We can all hear questions also because this is being recorded, and then the recording sort of your question will be on that recording there. So please don't ask your question until I get to you with the microphone.

Josh Hyman:
All right, now to the important part. So Raj Chetty is the William A. Ackman Professor of Economics at Harvard University. He's also affiliated with the Department of Sociology there, and he's the founding director of Opportunity Insights, which is a team of researchers and policy analysts who employ a data-driven approach to answering important policy questions with a particular focus on the question of economic opportunity. So Professor Chetty and his collaborators at Opportunity Insights is using empirical evidence and economic theory to shed light and the impact of various factors, being born to a lower income or minority family, for instance, or attending underperforming schools in the success failure and general economic mobility of individuals.

Josh Hyman:
During the pandemic, the team at Opportunity Insights has also been tracking the economic impacts of COVID-19 on individuals, businesses, and communities across the United States. On topics ranging from tax policy to unemployment insurance, education, affordable housing, Professor Chetty's research has been really widely cited in Academia, media outlets, and congressional testimony. Professor Chetty received his BA and PhD, both in economics, from Harvard, where he is one of the youngest tenured professors in institution's history. Before joining Harvard, he was a professor at the University of California, Berkeley, and Stanford University. He's the recipient of many awards and recognitions, including a MacArthur Genius Grant, and the John Bates Clark Medal given to the economist under 40 whose work is judged to have made the most significant contributions to the field of economics. Most recently in 2020, he was awarded with the Infosys Prize in Social Sciences and the Carnegie Foundation, Great Immigrants Award. So please help me in welcoming for his talk and title, Improving Equality of Opportunity in America, New Insights for Big Data, Professor Raj Chetty.

Raj Chetty:
Well, thanks so much, Josh, for that warm introduction. It's really a pleasure to be here with all of you. It's an honor to receive this degree from Amherst, and I appreciate your braving the weather to be here today. So I'm going to talk about how we can improve equality of opportunity in America, even in our own institutions, in our own local communities at a very microscopic level. But I want to start at a much bigger picture level by talking about the American dream, which is of course, a complex multifaceted concept that can mean different things to different people. But I want to distill it to a statistic that we can measure systematically in the data, which I think is a key cornerstone aspect of what America's all about, the type of thing that drew my own parents to come to this country, which is the idea that this is a country where at least we aspire to be a place where through hard work, any child can go on to have a higher standard of living than their parents did.

Raj Chetty:
And so in a paper, my colleagues and I wrote a few years ago, we set about to assess the extent to which America actually lives up to that aspiration. What fraction of children go on to earn more than their parents did, measuring both kids' and parents' incomes in their mid-30s and adjusting for inflation? And we're looking at that data by the year in which the child was born. Starting on the far left here with kids born back in the 1940s, and then looking at what happens over time, going all the way up to the kids born in the middle of the 1980s, we're turning 30 around now when we're measuring their incomes as adults. So what you can see is that if you were born back in the middle of the last century, it was a virtual guarantee that you were going to achieve the American dream of moving up. 92% of children born in 1940, went on to earn more than their parents did.

Raj Chetty:
If you look at what's happened over time, you see a dramatic fading of the American dream, such that for children born in the middle of the 1980s, entering the labor market in recent years, it's essentially become a coin flip as to whether you're going to achieve the American dream, a 50, 50 shot of doing better than your parents. So this dramatic trend is of course of great interest to economists like Josh and myself and many others, because it reflects a fundamental change in the U.S. economy that we'd like to understand the drivers of. But I would argue it's also of great social and political interest because I think it's this very trend that underlies a lot of the frustration that people around the U.S. are expressing that this is no longer a country where it's easy to get ahead, even through hard work.

Raj Chetty:
And so motivated by this trend in our research group at Harvard Opportunity Insights, we're focused at some level on that very big picture question of what is causing the fading of the American dream. And how can we restore the American dream going forward? How can we increase rates of upward economic mobility going forward? So we are, of course, not the only people to be thinking about these issues, social scientists have studied these questions for decades and made quite a bit of progress in understanding the determinants of things like inequality and economic opportunity. Our angle on it is to bring the tools of modern big data to bear on studying this question. So you all hear a lot about the use of big data in the private sector, companies like Amazon and Google using large data sets to improve the products they offer. Analogously increasingly in the social sciences, we're seeing tremendous potential for these types of data to improve our understanding of key economic and social policy questions.

Raj Chetty:
And so in this case, what I'm going to talk about in the next half hour or so is how such data can improve our understanding of the determinants of that trend that I started out with. Now, anytime you're looking at a large set of data like that, you have to have some way you're going to enter the data and structure your analysis. One common approach is to focus on one domain, one set of interventions. So for instance, you might think that education plays a big role in determining inequality and opportunity, and as I will show you, that certainly seems to be the case, but there are also many other factors that seem to matter, things like affordable housing, segregation, social capital, and so forth. And so rather than focusing on one particular topical domain, we're going to analyze a broad range of interventions organized from a life course perspective, looking from childhood to adulthood interventions in different points in time.

Raj Chetty:
The starting point for a lot of our work is that there are very sharp, local differences in rates of upward mobility. And so to show you that, I'm going to turn to this map here, which shows you the geography of upward mobility in the United States. So let me first describe how we construct this map, and then I'll tell you what I think we learn from it. So what we do is take data on 20 million kids in the United States, essentially all kids born in the U.S. in the early 1980s, we obtain information on them from anonymized tax returns, link to their parents' tax returns, so we can basically pinpoint where everybody grew up, follow them over time, and look at their incomes when they're 35 years old. And that allows us to construct a very simple measure of upward mobility for 740 different metro and rural areas in the United States.

Raj Chetty:
We say, suppose you take the kids who grew up in families earning $27,000 a year, grew up in low-income families at the 25th percentile of the national income distribution, how much are they earning as adults when we look at their tax returns when they're 35 years old, no matter where they live? So we map everybody back to where they grew up. You might have grown up in Iowa, but you ended up moving to Chicago, you're going to be mapped back to Iowa for these purposes. And then in each of those different areas, we compute how well our kids who grew up in low-income families doing there. So start by just looking at the scale in the lower right-hand side here. You can see that there's an enormous amount of variation in kids' chances of rising up in America, even in the current generation.

Raj Chetty:
So there are some places that even today look like great places in terms of rates of upward mobility. So in the center of the country, for instance, much of the rural Midwest, you can see that kids growing up, for instance, in a place like Dubuque, Iowa, if growing up in a family that has an income of $27,000 a year, on average, one generation later are making $45,000 a year. So on average, that's quite a bit of upward mobility for kids growing up there. In contrast, you can look at a place like Charlotte, North Carolina, where kids starting out in families at the exact same income level, $27,000 a year, one generation later are actually earning less than their parents did on average, which is pretty remarkable given the tremendous amount of economic growth that's happened in the U.S. over the past 30 years and in Charlotte, in particular. So those kids are basically being left out of the progress that's being made more broadly.

Raj Chetty:
So you can see the broad spatial patterns for yourself, higher levels of economic mobility in America, and much of the center of the country, parts of the coast, lower in the Southeast, many cities in the industrial Midwest, like Cincinnati and Cleveland, and so forth. And so the way I'm going to structure this talk and the way we've been structuring our research agenda in our group is basically to understand this map. What is driving the variation in this map? I think that's a useful question to understand both from a scientific perspective, because it gives us a lens to understand the science of economic opportunity. What is it that makes some places produce better outcomes for kids than others? Is it about the schools? Is it about the labor market? Is it about other things?

Raj Chetty:
But it's more than just an academic question, because if we figure out the answer to that scientific question, then the hope is, of course, that we might be able to figure out how we replicate, whatever good things are happening in the blue, green colored places, in the red, orange colored places, and potentially increased rates of upward mobility throughout America. So essentially the way I'm going to structure the conversation for the next few minutes here is to explore a series of hypotheses. You might already have some in your mind of what is driving the difference that you're seeing in this map and systematically evaluate is it about jobs. Is it about racial differences? Is it about other things that's driving the variation upward mobility that we're seeing?

Raj Chetty:
So the first explanation that economists often think of is maybe this is about differences in the labor markets in different areas. So take, for example, San Francisco Bay Area, we all know the tech sector has been booming over the last 20, 30 years. Maybe we see relatively high rates of upward mobility in places like that because there are lots of high-paying jobs coming into those places. So to assess that more systematically, let's turn to this plot here, where I'm going to plot rates of upward mobility, so the data exactly from the map that I just showed you for the 30 largest cities in America, against rates of job growth from 1990 to 2010. So a simple measure of how rapidly is the city growing. So take, for example, the example I gave you before of Charlotte or Atlanta. Those are two cities where if you look at any conventional measure of job growth or income growth, you would see Charlotte and Atlanta as being real positive outliers. They're kind of the engine of jobs in the Southeast.

Raj Chetty:
You don't really need data to see that. If you drove around the city today, as opposed to in the 1990s, you would see that Charlotte and Atlanta are totally different places now relative to what they were 30 years ago. What is remarkable though is despite that fact, Charlotte ranks 50th out of the 50 largest cities in America in terms of rates of upward mobility for kids who grow up in low and middle-income families in Charlotte. So the first thing you might wonder is just like arithmetically, how is that possible? How can you both be one of the most rapidly growing cities in terms of income and for the kids growing up there have some of the lowest rates of growth of income for those kids?

Raj Chetty:
So the way it adds up basically is Charlotte and Atlanta import talent. Lots of people move to Charlotte and Atlanta to get those high-paying jobs at firms like Bank of America, which is headquartered in Charlotte, but apparently what you can see from this longitudinal data that our team has been constructing and analyzing over the past several years, if you are a kid growing up in a relatively poor family in Charlotte, you don't necessarily benefit from that growth. You don't get that job at Bank of America. There's no guarantee of that. And in fact, you tend not to have very good prospects in general. And so one very simple lesson from this analysis, where you can see there's basically no connection between these two variables, is simply having higher rates of job growth in your city. Trying to get the Amazon headquarters to move to your city is not a recipe directly for having higher rates of upward mobility for your residents. Okay? So that's simple point number one, it's just, it's not just about jobs.

Raj Chetty:
Okay. So let's come back to the map having rejected that explanation. A second potential explanation, anyone familiar with the demography of the United States would recognize that there's a potential connection to race here, in particular, the places that are in the orange and red colors, cities like Cincinnati, Detroit, and so forth, the much of the Southeast are places with larger African American populations. Now, we're all well aware of the long history of discrimination and racial disparities in the United States, and so it might not surprise you to expect that there are significant differences by race and economic mobility. And maybe what we're seeing in this map is not so much about place, but rather about race, given the amount of racial segregation we have in America.

Raj Chetty:
So to evaluate that, what we did next is construct this pair of maps here by linking the census data to the tax data. So the maps that I showed you initially, there's a technical issue here that's quite important. When you just analyze tax records, you don't have information on people's race and ethnicity. What we were able to do next is take everyone's tax returns and link them internally at the Census Bureau to information from the census on race and ethnicity for everyone. And just before I proceed in describing the analysis here, I just want to point out this analysis was done by an Amherst graduate named Jamie Gracie, who's a terrific member of our team and is now a PhD student at Harvard. So she really played a central role in doing what I'm showing you here. So it's cool to be here talking about this.

Raj Chetty:
So what we're doing here is constructing the same pair of maps that I showed you before, but separately for black men on the left and white men on the right. Okay? So same exact measures, take kids growing up in low income families, ask where they end up in the income distribution. So if you start by just looking at these maps, you might think, oh, they put these maps on two different color scales, kind of like a red orange color scale on the left and a blue, green color scale on the right, but in fact, if you look at the bottom of the slide, you can see that we have not done that, they're on the same color scale. It's just that there is such a drastic difference in rates of upward mobility for black men versus white men in America, that it's almost like you're living in two different countries.

Raj Chetty:
To put it a little bit more precisely from a statistical point of view, the very best places in terms of upward mobility for black men growing up in Boston, for example, a black man growing up in a low-income family can expect to earn about $25,000 a year on average, they have lower levels of upward mobility there than the very worst places in terms of upward mobility for white men. So it's like you have two basically non-overlapping distributions, that's why the colors look so disjoined, right? So what we learned from that is there's no mistaking the importance of race in America, even today, even conditional on class. That's I think a crucial point. A lot of people, when you think about racial disparities, they have the view, well, maybe that's related to growing up in families with different levels of income or different neighborhoods with different levels of poverty. But no, here we have very precise data on income from tax returns over many, many years, look at two kids, black and white, identical family income situation, and you see totally different trajectories for black men versus white men. So undoubtedly race is incredibly important.

Raj Chetty:
Now, you'll notice that I specifically showed you the data here for men, and I did that for a very deliberate reason. Breaking up this analysis by gender turns out to be quite important because if I now replicate that pair of maps for black women versus white women, you see a totally different picture. The spectrum of colors and the map on the left is basically the same as the spectrum of colors and the map on the right. More broadly, if we look at outcomes for black women versus white women controlling for parental income, things like college attendance, or various measures of economic success in adulthood, you see very similar outcomes for black women and white women, you see extremely different outcomes as we saw before for black men versus white men. So that's useful in understanding the dynamics of racial disparities in America across generations, because it suggests there's some intersectionality with gender, that really matters. And it might make you think about certain types of issues like mass incarceration that affects men in particular or discrimination that affects black men in particular and impedes their labor market opportunities.

Raj Chetty:
Okay. So what we've seen so far is that race seems to matter quite a bit, but I also want to point out that even conditional on race, if we look among white women, for example, there's still quite a bit of variation in the map in terms of outcomes for white women across different areas. So race matters but so does place. Race is clearly part of the picture, but place matters as well. Now, in most of this talk, I'm going to focus on upward mobility, helping kids rise up in the income distribution, because I think that's what most people are focused on in this kind of context. But I want to make one final point on race, which I think is really important in understanding the persistence of racial disparities in America, which is to think about the converse, think about downward mobility, think about kids starting out in high income families and ask where they end up in the income distribution.

Raj Chetty:
And so to show you that, I'm going to turn to this visual, which the New York Times put together using our data, which I think captures the idea very clearly. Suppose you take a set of kids who grew up in high income families and you ask, where did they end up themselves one generation later in the income distribution? So they start out in the top fifth, do they end up in the bottom fifth, second fifth, or do they stay in the top fifth? Okay? So each dot represents a different kid, green dots are for white men, purple dots are for black men. So what you see here, I think, is really a tragic fact about the U.S, which is the purple dots, as you can see, kind of cascade toward the bottom, whereas the green dots, you can see if you were born to a high income family as a white man, you generally float at the top of the distribution.

Raj Chetty:
So to put it differently, if you're born to a high income family, as a white man, odds are you're going to remain in the upper middle class. It's pretty unlikely you're going to fall to the bottom. Whereas, as a black man, if you're born to a comparably high income family, you're actually almost equally as likely to fall to the very bottom of the income distribution as you are to stay at the top. So this is, I think, extremely important in understanding the persistence of racial disparities over many generations in America. The way I think about it visually is that for white Americans achieving the American dream is like climbing a ladder where you kind of go up from where you were in the previous generation for the most part and go from there. For black Americans, if you look at this picture, it's more like being on a treadmill. Even after you've made it up in one generation, there are tremendous structural forces that are pushing you back down in the next generation only to have to make the climb again.

Raj Chetty:
And so why is that important in understanding how to address racial disparities? If you don't fix that treadmill phenomenon, and even if you manage to create more upward mobility, let's say you try to improve schools in neighborhoods that currently enroll many low income black students, if you've still got this going on, that's never going to stick, and in the next generation, the disparities are going to emerge again. And so I think it's equally important that we focus our attention on figuring out why we see such big differences in outcomes for black and white kids in upper middle class families, as we do in low income families. And so that, I think, is another important area of policy focus.

Raj Chetty:
Okay. So to go further now, and to understand what it is we might actually need to change to narrow racial disparities, to improve outcomes for low income white kids, and so forth, what I'm going to do next is zoom into the data at a finer level. And in order to do that, I'm going to switch over to this website. Let me see if I can get that to work here. So we're looking at this website opportunityatlas.org, which is a freely available website that anyone can access. And the way that this works, so we're starting out by looking at the same national map that I was showing you before, but this works very much like a Google Map where you can basically type in any address you want. And so here, I'm just going to literally zoom into New York City for the purpose of illustration. And what we can do now is look at the same kind of statistics that I've been showing you, but look at them census tract by census tract in New York City.

Raj Chetty:
So for every neighborhood in New York and every neighborhood across the entire country, we construct the same measures of upward mobility. If you grow up in a particular part of Manhattan or in the Bronx or in Queens, what are your chances of rising up? So first very simple point I want to make here is if you look at the spectrum of colors on this map, you see the same range of colors that I started out with on the national map, right? You can go from the deepest reds to the darkest blues, driving a couple miles down the road in New York, as you can in going to different parts of the country. So to put differently, driving two miles down the road in New York, you can go in terms of rates of upward mobility from what you would see in Alabama to what you were seeing in Iowa in terms of children's chances of rising up.

Raj Chetty:
So that observation is useful to understand what the sources are of these differences in economic opportunity, because it shows you that it's not just about regional differences or differences in state-level policies or even differences across cities, no, it's often about differences across nearby neighborhoods on different sides of the same street in a given place. And so that, I think, makes you think about what the factors are that might be important very differently. It's not about just about broad-scale federal policies and so forth, it could be about things like schools that kids in different neighborhoods in New York have access to, or the types of groups that are interacting with what networks look like. It's a different set of factors that would drive those very local differences in economic opportunity.

Raj Chetty:
Okay. So you can explore these data further. If you're interested, lots of people use these data to try to understand now why is it that I'm seeing very different opportunities in one part of my city versus another part of my city? What I'm going to do is come back to the slides here and make two points before pressing ahead. So first, this variation that we're looking at in New York, which is representative of what you see in many other cities, is driven not just by different types of people living in different places, what economists would call selection effects, but actually seem to be due to the causal effect of growing up in one of these neighborhoods versus another. So there've been a series of studies that our team and others have done, where we look at people who move across neighborhoods, sometimes through as part of a randomized experiment, where some people get a housing voucher to move to one of these blue, green colored areas, as opposed to a red area, and then we're able to follow these kids over time.

Raj Chetty:
And we see that there are dramatic improvements in kids' outcomes if they get the chance to grow up in these blue, green-colored areas, particularly if they move there at young ages. So there's kind of a dosage effect. The more years you spend growing up in these high-opportunity places, the better your outcomes are in the long run. So this shows us that place and environment, childhood environment, in particular, really matters for economic opportunity. And so the next question then becomes what is it that's actually leading some of these places, some of these neighborhoods like Queens, for example, to produce better outcomes than parts of Brooklyn that are very nearby? And so just skipping ahead here a bit, and just to kind of cut to the chase on that, this is an ongoing area of research, which basically brings us to the frontier of what social scientists are thinking about in this area, where we are trying to understand what are the characteristics of these high mobility neighborhoods.

Raj Chetty:
Ideally, what we'd be able to say is these are the three things you need to do in order to improve outcomes in this particular neighborhood. We're not quite there yet. What I can share with you is what some of the strongest predictors are of these differences in economic mobility across areas. So we and other social scientists have looked at many different factors over the years, and we basically struck upon a few quite strong, robust patterns. So first, places that are more mixed-income, that have less concentrated poverty tend to have higher levels of economic mobility. So more integrated neighborhoods tend to have higher levels of economic mobility. Second, you see a very strong pattern in the data that places with more stable family structures. So for instance, more two-parent families tend to have higher levels of economic mobility.

Raj Chetty:
Third is you might expect intuitively places with better schools measured in various ways, smaller class sizes, more expenditures per student tend to have higher levels of mobility. And then finally, and this actually is turning out to be a real area of focus for us and seems quite important, places with greater social capital have higher levels of mobility. So what do I mean by social capital? I think of the old adage that it takes a village to raise a child as capturing what social capital is about. Traditionally, it's been a very hard thing to really measure and pinpoint empirically. We have now been doing some work recently, which is not yet public, but gives you a flavor of the types of things that are feasible using social network data to look at who's interacting with whom in a given neighborhood. And we see that in places where there's a lot of social interaction across class lines, where low income and high-income people tend to be friends with each other, you see much higher levels of economic mobility, and this turns out to be an incredibly powerful predictor in various contexts.

Raj Chetty:
Okay. So in the last few minutes here, I want to show how this kind of research that we and many others are doing in our field can be useful, not just as an academic exercise to understand what's going on, but is actually having an impact on the ground in changing policy to improve people's lives. And so I'm going to structure that last discussion here by talking about three different areas for policy intervention that I see as coming directly from the set of research findings I just gave you a quick overview of. So to summarize in a nutshell, what I think you learn from this recent body of research on economic opportunity is that the roots of opportunity are hyper local. It's the particular neighborhood in which you grow up that seems to matter, and in particular, childhood environment from birth to something like your 22 or 23, really shapes people's life trajectories.

Raj Chetty:
So if you have that view of the world, I think you would naturally think about three different types of interventions. So first. You might think about trying to reduce segregation in our cities. So if we see in New York or Los Angeles, here's a neighborhood that seems relatively low opportunity, here's a place where kids do much better, well, maybe we can just give more low income families access to those high opportunity neighborhoods. And so that's one kind of moving to opportunity integration approach that you might think about. Now, of course not everybody wants to move and it's not going to be a scalable policy to have everyone move to a different neighborhood, so the second approach we have to think about to compliment that is what I think of as a place-based investment approach, how do you bring opportunity to people rather than bringing people to opportunity? How do you revitalize the neighborhoods that currently offer very poor prospects for kids from low income families? And I'll say a little bit about the types of efforts that could make sense there.

Raj Chetty:
And then finally, especially given the context we're in today, I think there's a very important role for institutions of higher education, like Amherst and others, to play in increasing economic mobility. And I'll say a little bit about how I think these types of data can inform efforts in that space as well. So let me spend a few minutes on each of these before opening it up for questions. So let's start with the reducing segregation approach. So to discuss this, I'm going to turn to a snapshot from the Opportunity Atlas for Seattle, similar to the map that I was showing you for New York, where you see a very similar checkered pattern, right? Where there are parts of Seattle where kids have good chances of rising up, there are other parts of Seattle where kids don't have very good chances of rising up.

Raj Chetty:
Now, what we've done here is overlaid on that map the most common places where people receiving housing vouchers from the federal government live in Seattle. So just as a bit of institutional context, in the U.S, we spend about $45 billion per year on affordable housing programs, the largest component of which are housing choice vouchers, which a few million families get each year, which you can think of as basically rental assistance to rent housing wherever you would like. And the idea of this program is to try to break the cycle of poverty and give families access to more stable housing and better neighborhoods where their kids might do better in the next generation.

Raj Chetty:
So when we put out these data, a number of housing authorities contacted us and they had noticed a very puzzling pattern, which is if you look at where the green dots are concentrated, so these families are receiving about $1,500 a month of rental assistance in Seattle, a substantial amount of money, despite that notice that the green dots are completely clustered in the red and orange colored parts of the map, as opposed to the blue, green colored parts of the map. So despite the fact that we are spending billions of dollars on this program, we know from our prior work that we're not actually going to break the cycle of poverty through this program because kids are growing up in exactly the same neighborhoods where we are seeing challenging outcomes in subsequent generations.

Raj Chetty:
So motivated by that, we teamed up with the local housing authorities in Seattle and King County to run a pilot study that we called Creating Moves to Opportunity in Seattle, where we basically took 1,000 families that came to apply for housing vouchers through the standard process, divided them randomly into two groups, 500 of them just got the standard, here's your voucher, you get four months to use it to find housing or wherever you want. And then the other 500 got additional assistance, which we thought of as basically trying to scrape away any of the barriers that families might face in moving to high opportunity neighborhoods if they wanted to do so. So in particular, we gave them customized search assistance. Think of this as like a broker who helps you find housing wherever you want, locates units, contacts landlords, things like that.

Raj Chetty:
We had a part of this where we directly reached out to landlords and tried to get them to connect with the housing voucher holders, simplified the inspection process, simplified some of the red tape, things like that. And then we provided a little bit of short term financial assistance to pay things like security deposits, fees, application fees, and so forth. On net, this program cost about $2,500 per family, which is not a small sum in and of itself, but when you benchmark it against the amount we spent per housing voucher for each family, which is $1,500 every month, often over 10 years, when a family has a housing voucher, it's something like a 2% incremental cost relative to what the federal governments are already spending.

Raj Chetty:
So the question basically in the study was if you help families out a little bit in using these vouchers, does that change where they want to move? Or is it that they really don't want to move to these high opportunity areas for other good reasons? Maybe they want to stay close to their jobs, maybe they want to stay close to their family. It's not a guarantee that everybody wants to move to the other side of the lake in Seattle, for instance. And so here's the result. This is the fraction of families that end up moving to high upward mobility places in the control group that did not receive that assistance and in the treatment group that did. And you can see that this has a dramatic effect, this little bit of assistance, you end up changing the families of the fraction of families who move to high upward mobility places from 14% of the control group to over 50% in the treatment group.

Raj Chetty:
Just to give you a concrete sense of potential impact and magnitudes here, we estimate from our prior work that over the course of their lifetimes, the kids who basically got lucky and ended up in the treatment group and ended up moving to these high opportunity areas, on average are going to go on to earn about $200,000 more over their lifetimes, relative to the kids who were in the control group neighborhood. So this is really quite meaningful. Just to show you visually how this plays out, so these blue shaded areas are what we selected as the high opportunity areas in Seattle, based on the data that I was showing you earlier, the green pins show you where the families and the treatment group chose to move, and the red pins show you where the families in the control group chose to move. And you could see that we're basically, through this intervention, starting to desegregate Seattle. You have more low income families moving into these neighborhoods that are providing better opportunities for kids, and that, I think, could have a really meaningful impact in the next generation.

Raj Chetty:
So this type of analysis is important to notice. Especially I think in this polarized climate, many people often ask me, "Well, all this research is great, you guys are compiling this evidence, but in an incredibly politically polarized climate in the United States, does this actually have any impact on policies? Is this going to change things at a broader level?" And I just want to give you one what I see as a hard nay example of that. So after we did this study in Seattle, there was a bill passed in Congress with bipartisan support authorizing about 70 million to do what we did in Seattle in nine other cities across the U.S. That is currently happening at the moment, this demonstration in nine other cities. But I think even more importantly than that, there's now a bill working its way through Congress, again with bipartisan sponsorship...