How Poverty in the U.S. is Driven By ‘The Injustice of Place’
For many Americans facing low-incomes and a lack of economic opportunity, geography is fate. That’s the thesis of the new book, The Injustice of Place, written by three of country’s most noted poverty researchers: Timothy J. Nelson, director of undergraduate studies at Princeton; Kathryn Edin, a professor of public affairs and sociology at Princeton; and H. Luke Shaefer, director of Poverty Solutions at the University of Michigan. The three created an Index of Deep Disadvantage to layer on additional environmental and social-economic filters to the usual categorizations of poverty and subsequently spent time on the ground in areas that have seen generations of deep poverty. Shaefer spoke to Spotlight recently about the book; the transcript of that conversation has been lightly edited for length and clarity
Congratulations on the new book!
It’s been a really exciting project with lots of surprises along the way.
Tell me how it got started.
Actually, it wasn’t long after we published $2.00 a Day that we started talking about the idea of studying place instead of people. Originally, we had thought about traveling to see how extreme poverty gets in the U.S., but then out of the blue, two program officers at the Robert Woods Johnson Foundation came to us and said we’d love to support a project that does exactly that and tries to use data to zero in on some of the nation’s poorest places and then take readers there and think about how place really matters.
Coming out of $2.00 a Day, we really wanted to try to take a holistic approach to determining where we would go. So, we use both poverty data, but also health metrics, life expectancy and low-income birth weight, and then Raj (Chetty) and Nathaniel’s (Hendren) social mobility metrics. We wanted to try to just think more holistically about what we’re talking about when we’re talking about poverty policy. We’re trying to respond to some of the critiques of poverty data and concerns about measurement error and we liked the fact that these different measures came from very different sources, and they would all have their own strengths and weaknesses. We thought we could paint a richer picture and actually put the data in conversation with each other.
We use principal component analysis that sort of weights them, and we were able to use that to create this continuum of counties and cities. I think that’s something that we’ve done that no other study has done where we were able to do a apples-to-apples comparison of counties and the 500 largest cities— about 3,600 places in the United States—and created this continuum of disadvantage based on these factors.
The first thing that really stood out to us was how very rural the places at the very bottom were and how they were sort of in these clusters that you wouldn’t normally get with just poverty data. There were also some really interesting places where we found very, very high poverty rates, but they had really good life expectancy and really strong social mobility and other places where the poverty rate actually wasn’t that high, but these other factors was really bad. So, I think it painted a richer picture than we had before.
Many of the assumptions about rural America that we had come into the project with started to fall by the wayside. One assumption is that rural America is predominantly White. Well, that’s true nationally, but there are lots of rural communities of color. And when we look at the very most disadvantaged places, there’s a lot of communities that are majority African American and majority Latino as well as White. We were able to pick field sites that were represented of all of those demographics.
Another thing that really interested me was, as we started to talk to people about the rural places that are really showing very high on the index, they would say, “Oh, well, that’s because those places are all poor. There’s no inequality.” Whereas in large cities, you see deep poverty and wealth and our markers of inequality in these places were quite unequal as well. And when we got into the history, that’s where we were able to see that divide goes back for generations.
Were there other common denominators that surprised you?
I was surprised that a place like Chicago didn’t even make it into the 600 most disadvantaged places in the country—both Chicago and New York, places where a huge amount of our research on poverty has taken place. To see them not represented at the very bottom made me wonder how representative has our picture been of these places.
The West is also very interesting as you do see these very, very disadvantaged places. They tend to be places with tribal or reservation land—there are just very few deeply disadvantaged places west of the Mississippi that aren’t tribal lands or reservations.
Give us examples of some of the places where you spent time?
In the book, we were in Clay County, Ky., in the country seat of Manchester. We were in Marion County, S.C., which is one of those places where the poverty rate is actually not too high, but the other indicators suggest serious, serious problems. LeFlore County, Ms. in the Mississippi Delta is another, with Greenwood being sort of the main city and then Zavala County in south Texas, with Crystal City being the community that we’re in.
As I mentioned at the start, this book was really a book of surprises for me. A lot of what we ended up writing about in the book was not anywhere on my radar when we started. One thing that could be interesting for readers of the book is to think about, what are the 10 most pressing issues that face Americans in very poor places in the United States? And then see how many of those come up in our research. Government corruption, for example, is one that I didn’t expect to write about.
That’s fascinating:
We saw in every single case, in every single community that we were in, cases of either current or not-distant past cases of significant government corruption, some of the time directly taking advantage of resources that should go to the poor. We write about the Mississippi welfare scandal, for example, and we found other instances where local officials were focused on their own interests and not doing the things they need to do to really help communities thrive. In Crystal City in 2016, a number of city officials, including the mayor, were indicted for bribery schemes. In Manchester and Clay County, there’s decades of examples of local officials being charged with corruption. So, you can really see the extent to which corruption really stifles the ability of communities to thrive. It can be a real barrier to success and I think one that’s not anywhere on the poverty community’s radar.
It would also be interesting to know how that tracks with the gutting of local journalism, you know?
Absolutely. Local journalism and our enforcement mechanisms.
I was also going to mention violence as a factor we didn’t necessarily expect as a common attribute. I had the misconception that violence was really an urban challenge but a lot of the places that we were in—especially in the Mississippi Delta and Appalachia—the rates of violence per capita are similar or in some cases higher than what you would see in Chicago or other violent hotspots.
What about healthcare deficiencies? I’m sure you expected that, but I would guess that was particularly stark in places like the Delta and in rural Kentucky.
Yes, and I think that one in particular helps clarify some of what I think is a deficiency in the way that we measure poverty right now. A lot of our discussion on measuring poverty is focused on different geographic cost of living questions. You hear a lot about how it costs so much more to live in San Francisco or L.A. than it does in a rural community in Mississippi, but I think we haven’t factored in that part of the extra cost is related to the services that are there. A functioning healthcare system, functioning schools, public transportation, available food resources. We’re really good at thinking about the challenges of living in an urban place that has a high cost of living and not good, I think, at accounting for the fact that those amenities don’t even exist in many of these communities.
Will the index continue to be updated?
We see the index as the start of a conversation rather than the final word. We hope that it’ll get people thinking differently about how we measure poverty and how we measure disadvantage in this country, and it will help them see things that I think we as poverty scholars weren’t paying attention to, like how deeply poor a lot of our rural communities are.
So, we’ll be updating it. We are often adding new data sources. We’re working on a lot of empirical tests for many of the arguments that we make in the book, based on our qualitative research. And we’d love to hear from people, especially when they have data that can be merged onto counties as well as cities. This is all publicly available information. We have a website up where people can download the full dataset.
Finally, did this make you think differently about potential solutions. We’ve talked before about the impact of the expanded Child Tax Credit and this work would only seem to underscore that.
It did underscore that because you can see how difficult it is to get money and resources into places and how differential access could be. Places that have a great number of grant writers and social service agencies tend to be urban and tend to be better off. People like to give to their own communities. And then you have places like the ones that we’ve worked in where there are incredible hometown heroes who are working really hard, but they are serving as the executive director and the maintenance director and everything else. The CTC gets money directly to families and can be equally distributed across the country, so there’s a lot of appeal there. But I do think that when we’re thinking about investing in places, this project made me realize how important that work is too, and we need to do it. But we need to think about the context, about who we’re giving the money to and not assume that communities are like homogenous.