Concentrated poverty

The Perils of Conflating Gentrification and Displacement: A Longer and Wonkier Critique of Governing’s Gentrification Issue

Posted on by Joe Cortright

It’s telling that Governing calls gentrification the “g-word”—it’s become almost impossible to talk about neighborhood revitalization without objections being raised almost any change amounts to gentrification. While we applaud the attempt to inject some rigor and precision into a debate that has been too often fueled by emotion and anecdote, Governing’s analysis serves only to muddy the waters of this contentious issue.

The Governing team explains that there is no agreed-upon definition for gentrification, and then go on to choose a definition and use it to measure number of neighborhoods that have, and haven’t, gentrified. The report notes that gentrification is not the same thing as displacement; but then repeatedly describes the harm of gentrification as being the displacement of the existing population.

Is Gentrification About Displacement? Or isn’t it?

The underlying problem confronting Governing’s analysis is the confusion of the terms “gentrification” and “displacement”. The Governing team begins by explaining that their definition of gentrification has nothing to do with displacement, but they then go on to detail how “gentrification signifies displacement of the poor, mostly people of color.”

The reason policy analysts and public officials are concerned about gentrification, to the extent it happens, is because it holds the potential to displace the poor from their longtime neighborhoods. As Governing acknowledges, the original definition by British sociologist Ruth Glass was that the middle class “invade” a neighborhood “until all or most of the working class occupiers are displaced,” and the social character of the neighborhood is changed.

Our own work has shown that over four decades, relatively few high-poverty neighborhoods have seen their poverty rates decline to below the national average. It’s also the case that far more of the long-suffering poor move out of high-poverty neighborhoods that stay poor than move away from high-poverty neighborhoods that see a significant reduction in poverty.

A striking omission from the Governing article is any more than a passing mention of the robust academic literature on the extent of displacement in gentrifying neighborhoods. Columbia University’s Lance Freeman reports that outmigration rates for low-skilled black residents of gentrifying neighborhoods are lower than in otherwise similar, non-gentrifying neighborhoods. The University of Colorado’s Terra McKinnish and Kirk White conclude the demographic flows associated with the gentrification of urban neighborhoods are not consistent with displacement or harm to minority households. New York University’s Ingrid Gould Ellen and Katherine O’Reagan write “. . . original residents are much less harmed than is typically assumed. They do not appear to be displaced in the course of change, they experience modest gains in income during the process, and they are more satisfied with their neighborhoods in the wake of the change.”

It’s also discouraging that this entire discussion of poor neighborhoods isn’t placed in a broader context of income segregation of the U.S. population. Income inequality has achieved a new level of visibility in public discussions in the past few years, thanks to the work of Thomas Piketty and others. A number of scholars—Brown University’s John Logan, Rutger’s Paul Jargosky, the University of Missouri’s Todd Swanstrom, and others—have carefully traced out how income inequality has played out in the form of greater spatial separation by income in the nation’s metropolitan areas. The latest research from Stanford’s Sean Reardon and his colleagues shows that income segregation is increasing, driven by the increasing secession of the rich from neighborhoods of lower- and middle-income households. The focus on gentrification—the very limited and small-scale movement of some higher-income and better-educated households into lower-income communities–completely misses the fact that income segregation is being driven by the decisions of higher-income families to increasingly isolate themselves in higher-income enclaves, often in exclusive suburbs and established high-income areas.

One of the ironies of the fear of gentrification is that is often used as excuse to steer limited dollars for assisted housing predominantly or exclusively into low-income neighborhoods, a practice the University of Minnesota’s Myron Orfield has shown to reinforce historical patterns of racial and economic segregation.

Levels vs. Change

In quantitative analysis, we can measure the level of something (whether incomes are high or low, for example). We can also measure the “change” in something—whether incomes are increasing or decreasing.

The limitation of the Governing definition of gentrification is that it is all about change, and it largely ignores levels. Even if education levels or incomes increase in a poor neighborhood, it still may be much less well-educated and lower-income than the average neighborhood in the metropolitan area of which it is a part. This absence of clearly defined thresholds is a perennial omission of gentrification discussions: if one wealthier, whiter, better-educated person moves into a neighborhood, does that constitute gentrification?

As the University of Pennsylvania’s Mark Stern and Susan Seifert note:

Clearly, there is no objective measure of when neighborhood improvement—or, in Jane Jacobs’ striking phrase, ‘unslumming’—becomes gentrification. But if we see neighborhood revitalization as desirable, we cannot afford to label all population change as gentrification. (2007)

There’s something odd about a measurement that purports to examine the extent of “gentrification,” but excludes from its analysis all city neighborhoods with income levels over 40 percent of the metropolitan average. In San Francisco, a city with 196 census tracts, Governing concluded that only 16 were “eligible” to gentrify, and that only 3 tracts did gentrify. Superficially, this creates the impression that gentrification affects only 3 neighborhoods in San Francisco, as opposed to say, 84 neighborhoods in Philadelphia, and 39 neighborhoods in Baltimore. But is it meaningful to conclude that gentrification, income disparities, and displacement are a tenth as widespread in San Francisco as these other cities, simply because San Francisco already had most of its neighborhoods dominated by “the gentry?” Should we put any stock in a measure that says gentrification is more prevalent in Detroit (7 neighborhoods), Cleveland (10) and Fresno (5), than it is in San Francisco (3 neighborhoods)?

The levels of income and education are still very low, and the levels of poverty still very high, in many of the neighborhoods that Governing says have “gentrified.” Can it be said that a neighborhood has gentrified if it has, by comparison to the rest of its metropolitan area, a higher fraction of low-income households than the rest of the metropolitan area? Is this really a helpful way to describe what’s happening in metropolitan areas?

No Apparent Displacement in “Gentrifying” Tracts

The identifiable harm of gentrification is displacement: if Governing has identified tracts that are gentrifying, and if gentrification is a problem, then we should be able to find evidence of displacement. Or, put another way, if neighborhoods are gentrifying and displacement isn’t happening, is it a serious problem?

Let’s compare what happened to gentrifying and non-gentrifying tracts, according to Governing’s definition. Of a total of 4,750 central city census tracts “eligible” to gentrify, 948 gentrified, but 3,802 did not. The tracts that did not gentrify lost 2.4 percent of their population in aggregate. The tracts that did gentrify actually saw their population increase by 6.7%. (This is consistent with the “up or out” pattern we identified in high-poverty tracts nationally: either poverty rates decline and population increases, or high poverty rates persist and population declines).

One recurring theme in overly simplistic gentrification analyses is housing as a zero sum game. If one whiter, wealthier, or better-educated person moves into a neighborhood, that must necessarily mean that one poorer, less-educated person of color must move out. Both Governing’s report and our analysis of high poverty neighborhoods shows that gentrifying or rebounding neighborhoods are actually seeing population increases.

It’s also the case that more poor people live in the Governing’s “gentrified” tracts today than in 2000: the poverty rate in gentrified tracts declined by 0.7%, while the total population increased by 6.5%. Assuming the poverty rate in these tracts exceeded 13 percent in 2000, the population living below the poverty line in these tracts had to have actually increased between 2000 and 2013; hardly evidence, on its face, of widespread displacement.

Another recurring theme in this kind of analysis is the implication that if a neighborhood doesn’t gentrify, that it somehow stays the same. But our analysis of poor neighborhoods showed that places of high poverty aren’t stable; if these neighborhoods don’t see a reduction in poverty, people leave: on average high-poverty neighborhoods that didn’t rebound lost 40 percent of their population over four decades. The same pattern holds for Governing’s “non-gentrifying” neighborhoods—they lost 2.4 percent of their population. This contrasts with the gentrifying places, which were adding population.

Understanding the Nuance of Neighborhood Change

Rather than just a binary classification of neighborhoods as either “gentrified” and “not gentrified,” it’s worth looking at the actual numbers of people involved, poor and non-poor, to get a sense of what’s really happening and what it means.

At City Observatory, we frequently work with tract-level data, and closely follow developments in Portland, where we’re based. We took a close look at Governing’s data for Portland, in part because they concluded that 58% of “eligible” census tracts gentrified in the past decade.

Here are their headline findings for Portland: According to Governing, 62 of 143 census tracts in the City of Portland were “eligible” to gentrify. Of these, 36 gentrified, and 26 did not, according to their calculations.

We gathered the data on population and poverty for all the City of Portland census tracts for 2000 and 2009-13, and categorized them according to the Governing methodology (we noted the classifications as coded on Governing’s map of Portland tracts). We have one more census tract in the City of Portland (in the not eligible category). We ignore this minor difference for the purpose of our analysis. Here’s what the data show about the gentrifying neighborhoods in Portland in the aggregate:

The total population in “gentrifying” neighborhoods actually increased from about 152,000 to about 165,000. This is consistent with our observation that neighborhood change is not a zero sum game. Neighborhoods can gain new residents without necessarily losing existing ones.

The number of poor persons living in “gentrifying” neighborhoods increased. In 2000, there were 25,037 persons in poverty in these neighborhoods; in 2013 there were 34,499 persons living in poverty, about 9,500 more. Even allowing for the increase in poverty rates in the nation and the region over the decade, it’s hard to argue that there was widespread displacement of the poor from these “gentrifying” neighborhoods if they now have 9,500 more poor residents.

As a result, the poverty rate in “gentrifying” neighborhoods in Portland increased between 2000 and 2013 in the aggregate. In 2000 the poverty rate was 16 percent; in 2013, the poverty rate had risen to 20 percent. Even after “gentrifying,” these neighborhoods had a poverty rate that was higher than the regional average of about 13.5 percent.

Meanwhile, the number of non-poor residents also increased by a net of 3,800, from about 127,000 to about 130,000. The “gentrifying” neighborhoods gained about two-and-a half times more net additional poor residents than net additional non-poor residents. Spread over 36 Census Tracts and about 11 years, (2000 through 2011, the mid-point of the 2009-13 five year census pattern) this works out to a net increase of about 10 non-poor persons per “gentrifying” census tract per year—hardly a sweeping change in typical neighborhood demographics.

Poverty, Population, City of Portland, 2000 and 2009-13

Organized by Governing Magazine Gentrification Typology
Governing Category “Gentrified” “Not Gentrified” “Not Eligible” City Total
Tracts 36 26 81 143
Population 2013 165,436 120,742 317,422 603,600
Calculated Persons in Poverty 2013 34,499 27,948 44,845 107,292
Average Tract Poverty Rate 2013 20.0% 22.7% 13.8% 17.0%
Population 2000 152,168 105,583 280,454 538,205
Calculated Persons in Poverty 2000 25,037 15,000 30,242 70,279
Average Tract Poverty Rate 2000 16.8% 14.0% 10.9% 12.9%
Growth in Poverty, 2000-2013 37.8% 86.3% 48.3% 52.7%
NonPoor 2000 127,131 90,583 250,212 467,926
NonPoor 2013 130,937 92,794 272,577 496,308
Percent Change 3.0% 2.4% 8.9% 6.1%
Change in Non_Poor 3,806 2,211 22,365 28,382
Growth in Population 13,268 15,159 36,968 65,395
Poor 9,462 12,948 14,603 37,013
NonPoor 3,806 2,211 22,365 28,382

This is not to say that all of these neighborhoods experienced this same pattern. By our count, 22 of Governing’s 36 gentrifying Portland census tracts experienced increased numbers of persons living in poverty, and 14 saw decreases in their poverty population. Of these 14, nine had decreases of less than five percent since 2000, four had decreases of between five to ten percent, and only one census tract saw a decrease of more than ten percent in its population living in poverty. Arguably, these tracts may be experiencing a measure of displacement. But for reference, it’s worth noting that the between 1970 and 2010, the typical urban high-poverty tract that stayed high-poverty lost about 40 percent of its population. 31 of the 36 “gentrifying” tracts still had poverty rates above the regional average “post-gentrification.”

Defining the Undefinable

After musing about whether gentrification is synonymous with displacement, Governing concludes that we should treat them as two different things, and cites the Centers of Disease Control as agreeing with this view. The authors quote the CDC as saying: “gentrification is merely the transformation of neighborhoods from low value to high value.” The CDC definition, says Governing, has nothing to do with displacement.

It’s worth looking at the CDC’s work here. It turns out that the Centers for Disease Control hasn’t actually done its own research on gentrification. What you’ll find at the CDC website is one wiki-like page of secondary citations, compiled by an unidentified author: http://www.cdc.gov/healthyplaces/healthtopics/gentrification.htm. The CDC is hardly regarded as an expert or arbiter on the subject: Google Scholar reports a total of four citations to this CDC webpage.

It’s important to note that the CDC website—like the rest of the literature on gentrification—clearly flags the harm of gentrification as displacement of the existing population. They use the term “transformation” in their definition. If you read on in the sentences immediately following the definition cited by Governing, this is clear: “This change has the potential to cause displacement of long-time residents and businesses. Displacement happens when long-time or original neighborhood residents move from a gentrified area because of higher rents, mortgages, and property taxes.”

There’s one more wrinkle here. Notice that the CDC definition refers to the transformation of neighborhoods from “low value to high value.” The CDC definition, unlike Governing’s, is about levels, and not just changes. Governing’s definition is not that formerly poor neighborhoods become “high value” neighborhoods, but that they become “higher” value neighborhoods—that their property values increase faster than for the region as a whole. It is entirely possible for a low-value neighborhood to have a higher percentage increase in prices, and still be a low-value neighborhood.

Is there some reason we might want to be cautious about leaning on housing price data from the past decade or so?

A linchpin of the Governing analysis is its reliance on a decade’s worth of housing price data as reported by homeowners to the Census Bureau. They compare the reported value of owner-occupied housing in the 2000 Census, with data from the 2009-13 editions of the American Community Survey, and use this to identify lower income neighborhoods that have experienced higher than average rates of home price appreciation.

As we all recall, that decade represented the period of the biggest volatility in home prices and housing markets in at least eight decades. Home prices were inflated by a giant bubble through the mid-part of the decade, and collapsed in a downturn that wiped out trillions of dollars of household equity, produced millions of foreclosures, and resulted in 17 million more households renting their homes.

Another important development during the past decade was the big increase in gas prices in 2007-08, which persisted until just the past few months. Arguably, higher gas prices had a big impact on the housing market, depressing the price of suburban and exurban homes that were sold to what the real estate community called the “drive-til-you-qualify” crowd.

It’s obvious that this was a decade where a range of market forces were buffeting housing prices. It’s a stretch to assume that gentrification was the sole cause of higher prices in some previously poor neighborhoods.

There’s another deeper technical issue here: Governing’s estimates are based on median home values data that are subject to bias from composition effects. (For a discussion of the volatility and noise that median measures create for housing price inflation estimates, see Jordan Rappaport, “A guide to aggregate house price measures” Kansas City Federal Reserve Bank, 2007.)  The Census Bureau asks for estimates of home values only for owner-occupied homes—not rentals. As long as the number and mix of these homes doesn’t change from one census to another, this isn’t a problem for using the census data to estimate average prices. But the “median” home value is subject to composition effects: if a different number and mix of homes is in the sample in the base year and the final year, the quality of the estimate is compromised. If many formerly owner-occupied low-value homes are foreclosed upon, and converted to rentals, they are no longer included in the median. Because foreclosure was more common among low-value houses this effect drives up the reported median for the remaining higher-value houses. Foreclosure problems are far more common in lower-income neighborhoods than middle- and upper-income neighborhoods. It’s also the case that if new market rate housing gets built in a neighborhood, it is usually at a higher price point than existing housing; this too tends to cause measured median prices to rise, especially in neighborhoods with lots of older, smaller, lower-value homes.

What do we do?

As the Governing team well understands, the metropolitan U.S. is dramatically segregated by income—and income segregation is increasing. An abundance of social science literature shows that concentrated poverty magnifies all of the negative effects of growing up poor (Patrick Sharkey, Jargowsky & Swanstrom). Newly released research on intergenerational mobility shows the devastating effects of concentrated poverty, and that even poor kids that grow up in integrated places have much greater opportunities than their counterparts in neighborhoods of more concentrated poverty (Chetty, Massey and Rothwell).

We live in a nation increasingly segregated by income. Even as racial segregation has waned, income segregation has increased. If we’re serious in our rhetoric about equality of opportunity, we have to do something to tackle the growing spatial class segregation we see in cities.

As Daniel Kay Hertz has observed, critics of gentrification need to say how they expect to achieve a more integrated nation and more integrated cities if they are somehow opposed to some higher-income people moving into what have become lower-income neighborhoods. “The kind of cognitive dissonance that allows someone to decry segregation while they wish to “reverse” the process of integration makes it impossible to articulate a real vision for what a just city might look like. Those who would declare themselves firmly anti-gentrification need to grapple with whether they’re comfortable defending a racial geography born of discrimination and violence.”

Those who raise “gentrification” as an impending threat to American cities owe us a coherent vision of how we can create more just and equitable neighborhoods. Lamenting—and exaggerating—gentrification generates plenty of heat, but precious little light on how cities ought to respond to the twin challenges of income segregation and neighborhood change.

How Governing got it wrong: The problem with confusing gentrification and displacement

Posted on by Joe Cortright

Here’s a quick quiz:  Which of the following statements is true?

a) Gentrification can be harmful because it causes displacement

b) Gentrification is the same thing as displacement

c) Gentrification is a totally different thing than displacement

d) All of the above

If the only studying you did was a reading of the latest series on gentrification from Governing Magazine, you’d have answered “d.” And of course, you’d have a tough time defending your answer.

In attempting to assemble a strong, data-driven definition of this controversial buzzword, a set of feature articles in its February 2015 issue entitled “The ‘G’ word—a special report on gentrification,” Governing succeeds only in making the tortured debate over gentrification even more contentious and unclear.

The most basic flaw of its analysis is coming down squarely on all sides of whether “gentrification” is the same thing as “displacement.”  While the authors claim that these two terms are different things, all of the harms from gentrification that they point to involve displacement: the problem of previous, generally poor residents being forced out of a neighborhood as it changes.

Governing has impressive maps and data—but maps and data are only as sound as the assumptions they are built on. The assumptions here—that gentrification can be accurately measured solely by looking at changes in house prices and education levels in relatively poor city neighborhoods—are flat out wrong, if we are concerned, as Governing tells us we should be, about the displacement of the poor.

There’s precious little evidence that there has been, in the aggregate, any displacement of the poor from the neighborhoods Governing flags as “gentrifying.”  If there were displacement, you’d expect the number of poor people in these neighborhoods to be declining.  In fact, nationally, there are more poor people living in the neighborhoods that they identify as “gentrifying” in 2013 than there were in 2000. Here’s the math*. Governing’s gentrifying neighborhoods have gained poor AND nonpoor residents according to Census data. And even after “gentrifying,” these neighborhoods still have higher poverty rates, on average, than the national average.

Careful academic studies of gentrifying neighborhoods, by Columbia’s Lance Freeman and the University of Colorado’s Terra McKinnish, show that improving neighborhoods actually do a better job of hanging on to previous poor and minority residents than poor neighborhoods that don’t improve. The University of Washington’s Jacob Vigdor has estimated that even when rents go up, existing residents generally attach a value to neighborhood improvements that more than compensates for the higher costs.

This confirms our own analysis of 1,100 urban high-poverty neighborhoods over the past four decades. Only about one in twenty of the census tracts we analyzed saw their poverty rate drop below the national average, and three-quarters stayed very high poverty, but didn’t improve or stay the same: they continued to deteriorate, losing on average 40 percent of their population over 40 years.

In contrast to gentrification, which is rare and seems to be seldom associated with actual displacement, concentrated poverty is real—a growing and devastating challenge that is damaging the futures of millions of Americans, especially children of color. In the past forty years, the number of high-poverty urban neighborhoods has tripled and their population has doubled, to 4 million. Growing up poor is difficult; growing up in neighborhoods where a large fraction of your neighbors are also poor is worse, exposing kids to higher crime and lower quality schools, results in increased mental health issues, fewer job and educational opportunities, and— according to new research by Patrick Sharkey, Raj Chetty and Jonathan Rothwell & Doug Massey— permanently lowers life prospects relative to otherwise similar kids who grow up in mixed income neighborhoods.

Raising a false alarm about gentrification is the policy equivalent of shouting “fire” in a crowded theatre: it promotes mindless panic and does nothing to help us understand and tackle our real urban problems. A magazine that calls itself “Governing” should know the difference between sensationalism and thoughtful analysis.

 

*:  Here’s the math:

Mathematically it’s clear that more poor people live in the Governing’s “gentrified” tracts today than in 2000: according to Governing between 2000 and 2009-13, the poverty rate in gentrified tracts declined by 0.7%, while the total population of these tracts increased by 6.5%.  Assuming the poverty rate in these tracts exceeded 13 percent in 2000, the population living below the poverty line in these tracts had to have actually increased between 2000 and 2013:  hardly evidence, on its face, of widespread displacement.

 

How segregation limits opportunity

Posted on by Joe Cortright

The more segregated an metro area is, the worse the economic prospects of the poor and people of color

Our City Observatory report, Lost in Place, closely tracks the growth of concentrated poverty in the nation’s cities; this is particularly important because of the widespread evidence of the permanent damage high-poverty neighborhoods do to children of poor families.

Two recent studies shed additional light on the importance of economic and racial integration to the life chances of students from low income families and children of color.

Writing in the journal Social Problems, Lincoln Quillan explores the question “Does Segregation Create Winners and Losers?” Quillian uses data from the Panel Study of Income Dynamics, a federal survey program that gathers longitudinal data on a representative group of Americans over several decades.

Quillian shows that increases in segregation at the metropolitan level are associated with lower rates of high school completion for poor and black students. Poor and black students that live in more segregated metropolitan areas are less likely to graduate from high school after controlling for other observable factors that influence individual success, such as the level of their parents’ education. Significantly, higher rates of segregation do not appear to have any statistically significant effects on the high school completion rates of whites or the non-poor. Taken together, these findings suggest that increasing racial and economic integration improves the educational outcomes for black and poor students without any negative effect on the educational outcomes of white and non-poor students.

This is important. If increased economic integration does not affect educational prospects for higher-income students, then the myth that having more integrated neighborhoods will “drag down” the potential success for the current residents is just that: a false myth. The implication of this research for housing policy is particularly salient.

In another article, published in the Annals of the American Academy of Political and Social Science, Sean Reardon, Lindsay Fox, and Joseph Townsend look at the trends in income segregation. Using data from the American Community Survey, they look at the trends behind the growing overall levels of income segregation in most metropolitan areas.

Their analysis finds that aggregate household income segregation has increased mostly because of the increasing isolation of the highest income households from low- and moderate-income households. This is what Robert Reich famously labeled “the secession of the successful.” Higher-income households are more likely to live in neighborhoods with other high-income households than was true two three decades ago. The authors also estimate changes in income segregation for each of the 50 largest metropolitan areas in the nation. They point out wide variations across the country.

Differences in income levels and residential segregation patterns among metropolitan areas produce very different experiences for the urban poor in different metros. In some higher income metro areas with less segregation, the poorest residents live in neighborhoods with noticeably higher incomes than the poorest residents of poorer, more segregated metros. For example, those in the tenth percentile of household income in Washington D.C. and Minneapolis live in neighborhoods that have average household incomes equal to the levels experienced by the median-income households in Atlanta and Los Angeles. You can see these differences in the figure below, excerpted from the paper:

Reardon Figure 4

This plots household income against neighborhood income. Most metros are similar, with the typical low-income family living in a neighborhood with a median income of $45K. Washington and Minneapolis have higher average incomes and are more economically integrated than other large metropolitan areas. Families in the lowest 25th percentile in these cities live in neighborhoods with median incomes of $60,000 (Minneapolis) and $70,000 (Washington). In the typical large metro area, you have to have an income of $75,000 (or more) to have such well-to-do neighbors.

Finally, this paper also presents major findings on racial integration and associated effects on economic integration. Black and Hispanic households tend to be highly concentrated into black and Hispanic neighborhoods, which has implications for poverty and economic mobility that we outline in our report here and blog post here. Most importantly, households with the same yearly income live in very different neighborhoods depending on their race:

“Black middle-class households (with incomes of roughly $55-$60,000), for example, typically live in neighborhoods with median incomes similar to those of very poor white households (those with incomes of roughly $12,000). For Hispanic households the disparity is only slightly smaller. Moreover, even high-income black and Hispanic households do not achieve neighborhood income parity with similar-income white households.”

While the growing gap between rich and poor is capturing greater policy attention, these two studies remind us that the spatial patterns of integration within metropolitan areas have a big impact on the quality of life and life prospects, especially of low-income households. It also indicates that how we build and inhabit our cities influences educational attainment and economic success, have an important role in ameliorating the effects of income inequality, which can have long-lasting impacts on city-wide educational attainment and economic success.

A hat tip to City Observatory’s friend Bridget Marquis for flagging these articles.

New Findings on Economic Opportunity (that you should know)

Posted on by Joe Cortright

Our recent report, Lost in Place, closely tracks the growth of concentrated poverty in the nation’s cities; this is particularly important because of the widespread evidence of the permanent damage high-poverty neighborhoods do to children of poor families.

Two new studies shed additional light on the importance of economic and racial integration to the life chances of poor students and children of color.

Writing in the journal Social Problems, Lincoln Quillan explores the question “Does Segregation Create Winners and Losers?”

Quillian uses data from the Panel Study of Income Dynamics, a federal survey program that gathers longitudinal data on a representative group of Americans over several decades.

Quillian shows that increases in segregation at the metropolitan level are associated with lower rates of high school completion for poor and black students. Poor and black students that live in more segregated metropolitan areas are less likely to graduate from high school after controlling for other observable factors that influence individual success, such as the level of their parents’ education. Significantly, higher rates of segregation do not appear to have any statistically significant effects on the high school completion rates of whites or the non-poor. Taken together, these findings suggest that increasing racial and economic integration improves the educational outcomes for black and poor students without any negative effect on the educational outcomes of white and non-poor students.

This is important. If increased economic integration does not affect educational prospects for higher-income students, then the myth that having more integrated neighborhoods will “drag down” the potential success for the current residents is just that: a false myth. The implication of this research for housing policy is particularly salient.

In another article, due for publication in a forthcoming issue of the Annals of the American Academy of Political and Social Science, Sean Reardon, Lindsay Fox, and Joseph Townsend look at the trends in income segregation. Using data from the American Community Survey, they look at the trends behind the growing overall levels of income segregation in most metropolitan areas.

Their analysis finds that aggregate household income segregation has increased mostly because of the increasing isolation of the highest income households from low- and moderate-income households. Higher-income households are more likely to live in neighborhoods with other high-income households than was true two three decades ago. The authors also estimate changes in income segregation for each of the 50 largest metropolitan areas in the nation. They point out wide variations across the country.

Differences in income levels and residential segregation patterns among metropolitan areas produce very different experiences for the urban poor in different metros. In some higher income metro areas with less segregation, the poorest residents live in neighborhoods with noticeably higher incomes than the poorest residents of poorer, more segregated metros. For example, those in the tenth percentile of household income in Washington D.C. and Minneapolis live in neighborhoods that have average household incomes equal to the levels experienced by the median-income households in Atlanta and Los Angeles. You can see these differences in the figure below, excerpted from the paper:

Reardon Figure 4

This plots household income against neighborhood income. Most metros are similar, with the typical low-income family living in a neighborhood with a median income of $45K. Washington and Minneapolis have higher average incomes and are more economically integrated than other large metropolitan areas. Families in the lowest 25th percentile in these cities live in neighborhoods with median incomes of $60,000 (Minneapolis) and $70,000 (Washington). In the typical large metro area, you have to have an income of $75,000 (or more) to have such well-to-do neighbors.

Finally, this paper also presents major findings on racial integration and associated effects on economic integration. Black and Hispanic households tend to be highly concentrated into black and hispanic neighborhoods, which has implications for poverty and economic mobility that we outline in our report here and blog post here. Most importantly, households with the same yearly income live in very different neighborhoods depending on their race: “Black middle-class households (with incomes of roughly $55-$60,000), for example, typically live in neighborhoods with median incomes similar to those of very poor white households (those with incomes of roughly $12,000). For Hispanic households the disparity is only slightly smaller. Moreover, even high-income black and Hispanic households do not achieve neighborhood income parity with similar-income white households.”

While the growing gap between rich and poor is capturing greater policy attention, these two studies remind us that the spatial patterns of integration within metropolitan areas have a big impact on the quality of life and life prospects, especially of low-income households. It also indicates that how we build and inhabit our cities influences educational attainment and economic success, have an important role in ameliorating the effects of income inequality, which can have long-lasting impacts on city-wide educational attainment and economic success.

A hat tip to City Observatory’s friend Bridget Marquis for flagging these articles.

Why integration matters

Posted on by Joe Cortright

Socioeconomic mixing, in neighborhoods that are diverse in race, ethnicity and income, benefits everyone

To some extent, we take for granted that integration and equal opportunity should be valued for their own sake. But its worth noting that achieving greater integration along both racial/ethnic and income dimensions is important to achieving more widespread prosperity and combatting poverty.

A growing body of sociological and economic research have demonstrated the high costs associated with racial and income segregation. While a comprehensive review of this literature is beyond the scope of this paper, we highlight here some of the key research findings that bear on the economic consequences of neighborhood diversity. Neighborhoods of concentrated disadvantage are not simply places where many households suffer from their own individual problems. The segregation of poverty (or a marginalized racial group) creates its own additional, collective burden on residents of these communities.

Galster and Sharkey undertake an extensive literature review of data on neighborhood effects of poverty. They find that segregation is associated with lower cognitive development and weaker academic performance, greater likelihood of teen pregnancy and risky behaviors, reduced physical and mental health, lower incomes and lower probability of employment, greater likelihood of being affected by or engaged in crime. Looking at more than 100 studies which they regard as quantitatively rigorous they conclude:

. . . the findings on the number of (methodologically rigorous) studies that have found substantial, statistically significant effects of spatial context (for at least some set of individuals) and those that have not, by outcome domain. The tally makes it clear that the preponderance of evidence in every outcome domain is that multiple aspects of spatial context exert important causal influences over a wide range of outcomes related to socioeconomic opportunity, though which aspects are most powerful depends on the outcome and the gender and ethnicity of the individuals in question.
(Galster & Sharkey, 2017)

Part of this burden is evident in day-to-day quality of life issues, such as greater exposure to crime. Studies of the “Moving to Opportunity” program, in which families were given assistance to move from low-income to middle-income neighborhoods, showed a marked improvement in self-reported well-being. Moving to a neighborhood whose poverty rate was 13 percentage points lower was associated with an increase in self-reported quality of life equivalent to an increase of $13,000 in household income (Ludwig et al., 2012). But perhaps the most serious effects of concentrated disadvantage are the ways in which it acts to reproduce inequality and quash economic opportunity and mobility—the very promise of the American dream.

High-poverty neighborhoods put their residents at a significant and immediate economic disadvantage. They typically have fewer local jobs than other neighborhoods, and often are distant from, or poorly connected to, other major job centers. These communities also often lack social networks that allow residents to find job openings (Bayer, Ross, & Topa, 2004).

For these and other reasons, people who grow up in high-poverty neighborhoods, on average, have worse economic outcomes than people who grow up in other kinds of neighborhoods, even if their family backgrounds are identical. The Equality of Opportunity Project has shown that inter-generational income mobility is significantly higher in metropolitan areas with lower levels of income segregation(Chetty, Hendren, Kline, & Saez, 2014)). The effect is so strong that, for children whose families move from high-segregation to low-segregation metropolitan areas, each additional year spent in the high-segregation region before the move is associated with less income as an adult.

Chetty and Hendren find that across metropolitan areas both income and racial ethnic segregation have a negative effect on children’s income as adults (Chetty & Hendren, 2016) (Chetty & Hendren, 2016)

“. . . our analysis strongly supports the hypothesis that growing up in a more segregated area – that is, in a neighborhood with concentrated poverty – is detrimental for disadvantaged youth. “

But they go on to say that it’s not because of their parents access to jobs, but because of the children’s exposure to a different set of peers.

“Areas with less concentrated poverty, less income inequality, better schools, a larger share of two-parent families, and lower crime rates tend to produce better outcomes for children in poor families. Boys’ outcomes vary more across areas than girls’ outcomes, and boys have especially negative outcomes in highly segregated areas. One-fifth of the black-white income gap can be explained by differences in the counties in which black and white children grow up.”

Other studies have found similar effects. For example, black children who grow up in high-poverty neighborhoods that transition to low levels of poverty have incomes that are 30 to 40 percent higher than black children with similar backgrounds who grow up in neighborhoods that remain at high levels of poverty (Sharkey, 2013) Observing the results of a natural experiment that relocated families from public housing in Chicago, Eric Chyn found that children who moved even relatively short distances to neighborhoods with somewhat lower poverty rates also experienced noticeable gains in earnings (Chyn, 2016)

Another analysis suggests that the educational level of ones neighbors has an effect on a child’s economic future nearly as large as that of the educational level of a child’s own parents. The effect of neighborhood educational level on children’s future earnings have been estimated to be two-thirds as powerful as the influence of the children’s own parental educaton (Rothwell & Massey, 2014).

The effects that are observed at the neighborhood level appear to compound to produce the variations in economic results we observe across metropolitan areas. Quillian shows that increases in segregation at the metropolitan level are associated with lower rates of high school completion for poor and black students. (Quillian, 2014) Quillian uses data from the Panel Study of Income Dynamics, a federal survey program that gathers longitudinal data on a representative group of Americans over several decades. Poor and black students that live in more segregated metropolitan areas are less likely to graduate from high school after controlling for other observable factors that influence individual success, such as the level of their parents’ education. Significantly, higher rates of segregation do not appear to have any statistically significant effects on the high school completion rates of whites or the non-poor. Taken together, these findings suggest that increasing racial and economic integration improves the educational outcomes for black and poor students without any negative effect on the educational outcomes of white and non-poor students.

A recent study prepared by the Urban Institute and the Metropolitan Policy Center estimated the cumulative economic and social costs associated with segregation in that metropolitan area. They found that the annual estimated cost of segregation in Chicago was more than $4 billion annually in lost income, and meant that fewer residents achieved a college education, while more were victims of crime, including homicide. (Acs, Pendall, Treskon, & Khare, 2017)

Taken together, the weight of social science evidence shows that racial/ethnic and economic segregation have profound consequences for individuals, for neighborhoods and entire cities. Much of the persistence and severity of poverty is due to the continued segregation. More integrated neighborhoods and more integrated cities enjoy better economic results, and produce better lifetime opportunities for their children. These findings point up the critical importance of the role of the nation’s racially and ethnically diverse, mixed income neighborhoods.

References

Acs, G., Pendall, R., Treskon, M., & Khare, A. (2017). The Cost of Segregation: National Trends and the Case of Chicago, 1990–2010. Washington, DC: Urban Institute. Retrieved from http://www. urban. org/research/publication/cost-segregation.

Bayer, P., Ross, S. L., & Topa, G. (2004). Place of Work and Place of Residence: Informal Hiring Networks and Labor Market Outcomes (Working paper No. 2004–07). University of Connecticut, Department of Economics. Retrieved from https://ideas.repec.org/p/uct/uconnp/2004-07.html

Chetty, R., & Hendren, N. (2016). The impacts of neighborhoods on intergenerational mobility ii: County-level estimates. National Bureau of Economic Research. Retrieved from http://www.nber.org/papers/w23002

Chetty, R., Hendren, N., Kline, P., & Saez, E. (2014). Where is the Land of Opportunity? The Geography of Intergenerational Mobility in the United States. National Bureau of Economic Research. Retrieved from http://www.nber.org/papers/w19843

Chyn, E. (2016). Moved to opportunity: The long-run effect of public housing demolition on labor market outcomes of children. Unpublished Paper. University of Michigan, Ann Arbor.

Galster, G., & Sharkey, P. (2017). Spatial Foundations of Inequality: A Conceptual Model and Empirical Overview. RSF, 3(2), 1–33. https://doi.org/10.7758/RSF.2017.3.2.01

Ludwig, J., Duncan, G. J., Gennetian, L. A., Katz, L. F., Kessler, R. C., Kling, J. R., & Sanbonmatsu, L. (2012). Neighborhood effects on the long-term well-being of low-income adults. Science, 337(6101), 1505–1510.

Quillian, L. (2014). Does Segregation Create Winners and Losers? Residential Segregation and Inequality in Educational Attainment. Social Problems, 61(3), 402–426.

Rothwell, J. T., & Massey, D. S. (2014). Geographic Effects on Intergenerational Income Mobility. Economic Geography, n/a-n/a. https://doi.org/10.1111/ecge.12072

Sharkey, P. (2013). Stuck in place: Urban neighborhoods and the end of progress toward racial equality. University of Chicago Press. Retrieved from http://books.google.com/books?hl=en&lr=&id=R-b_NlPJeuUC&oi=fnd&pg=PR5&dq=patrick+sharkey+stuck+in+place&ots=xJkeq39Kje&sig=0lmKDBM6OxHGMNk0jBga4EtDFqM

 

Where are the food deserts?

Posted on by Joe Cortright

One of the nation’s biggest health problems is the challenge of obesity:  since the early 1960s the number of American’s who are obese has increased from about 13 percent to 35 percent.

The problem is a complex, deep-seated one, and everything from our diet, to our inactive life-styles, to the built environment have been implicated as contributing factors.

Over the past five years, a new term has crept into our common lexicon of cities:  food desert.  (Google Trends reports almost no use of the term prior to 2009, and mentions have grown steadily since then).

The image of a food desert conveys a strong, specific image:  people who live so far from a grocery store with healthy food that they have little alternative but to subsist on the unhealthy alternatives close at hand.  But what exactly is a food desert?  And how many Americans have poor diets because of the distance they have to travel to reach a grocery store?

Judged by proximity to grocery stores nearly all of rural America is a food desert.  Nathan Yau at FlowingData uses Google maps data to construct a compelling map of how far it is to the nearest grocery store across the entire nation. The bleakest food deserts are the actual deserts of the American West, in Nevada and Wyoming.

City dwellers, particularly those in the biggest, most dense cities tend to live closest to supermarkets and have the best food access.  At City Observatory, we’re big fans of WalkScore, the app that computes a walkability index for any residential address in the U.S. based on its proximity to common destinations like stores, parks and schools.  Earlier this year, WalkScore used their data and modeling prowess to develop some clear, objective images of who does (and doesn’t) have a good grocery store nearby.  They estimate that 72 percent of New York City residents live within a five-minute walk of a grocery store.  At the other end of the spectrum, only about five percent of residents of Indianapolis and Oklahoma City are so close.  If you want to walk to the store, this data shows the real food deserts are in the suburbs.

There are other ways of measuring food access and mapping food deserts.  The U.S. Department of Agriculture and PolicyMap have both worked to generate their own maps of the nation’s food deserts.  They use a combination of physical proximity (how far it is to the nearest grocery store) and measurements of neighborhood income levels.

While it’s clear that income plays a big role in food access, it’s far from clear how to combine income and proximity to define food deserts.  The USDA uses an overlay which identifies low-income neighborhoods with limited food access.  PolicyMap has a complicated multi-step process that compares how far low-income residents have to travel to stores compared to higher income residents living in similarly dense neighborhoods.

In practice, combining neighborhood income and physical proximity actually muddles the definition of food access.  First, and most important, it acknowledges that income, not physical distance is the big factor in nutrition.  Both of these methods imply that having wealthy neighbors or living in the country-side means than physical access to food is not a barrier.  Second, it is your household’s income, not your neighbor’s income, that determines whether you can buy food.  Third, these methods implicitly treat low income families differently depending on where they live.  For example, PolicyMap excludes middle income and higher income neighborhoods from its definition of “limited supermarket access” areas—and therefore doesn’t count lower income families living in these areas as having poor food access.

The fact that both of these systems use a different yardstick for measuring accessibility in rural areas suggests that proximity isn’t really the issue. Rural residents are considered by USDA to have adequate food access if they live within ten miles of a grocery story whereas otherwise identical urban residents are considered to have adequate access only if they live within a mile or half-mile of a store.

If we’re concerned about food access, we probably ought to focus our attention on poverty and a lack of income, not grocery store location.  The argument here parallels that of Nobel Prize winning economist Amartya Sen, who pointed out that the cause starvation and death in famines is seldom the physical lack of sufficient food, but is instead the collapse of the incomes of the poor.  Sen’s conclusion was that governments should focus on raising incomes if they wanted to stave off hunger, rather than stockpiling or distributing foodstuffs

It’s tempting to blame poor nutrition and obesity on a lack of convenient access to healthier choices, but the problem is more difficult and complex than that.  Poverty and poor education are strong correlates of poor nutrition and obesity.

Finally, it’s reasonable to question whether the physical proximity to healthier eating choices is the big driver of our hunger and nutrition problems.

Millions of Americans, rich and poor, walk right past the fresh vegetables and buy chips, soda, and other calorie-rich processed foods.  The “food desert” narrative is a convenient way of making it sound like personal choice doesn’t enter into the problem.  But studies show that there is no apparent relationship between a store’s mix of products and its customer’s body/mass index (BMI) (Lear, Gasevic, and Schuurman, 2013). Limited experimental evidence suggest that improving the supply of fresh foods seems to have limited impacts on food consumption patterns.  Preliminary results of a study of consumers in a Philadelphia neighborhood that got better supermarket access showed no improvement in fruit and vegetable consumption or body mass index even for those who patronized the new store.

Of course, we have good reasons to believe that the built environment does play an important role in obesity—but that may have more to do with how easy it is to walk to all our daily destinations, and not just the distance to the fresh food aisle.

Tracking Neighborhood Change: How we made “Lost In Place”

Posted on by Dillon Mahmoudi

In this post, we’ll go over the data and mapping steps that were used to create our Lost In Place report on the concentration of poverty and the interactive web map. This post is one of several commentary posts that accompany the report, including an examination of how poverty has deepened.

Data for our report is provided at the Census Tract geography for US Metropolitan Statistical Areas (MSAs) with a 2010 population of over 1 million people — 51 in total. Our online map and report are based off two reported data points across five Census years: population and poverty levels in 1970, 1980, 1990, 2000 and 2010. Unfortunately for data analysis, Census Tract boundaries changed each census year between 1970 and 2010 as the geography of people changed. Fortunately, John Logan of Brown University and his colleagues released the Longitudinal Tract Database (LTDB) and have estimated tract-level Census counts from historical Census data from 1970 through 2010 using Census 2010 tract boundaries.

Two additional steps were necessary: we needed to determine which Census Tracts were part of our MSAs of interest, and in order to create maps and determine which tracts are within 10 miles of each MSAs central business district (CBD), we need to merge the Census tract data with their corresponding Census tract polygons. First, each 2010 Census Tract number is composed of a 2-digit identifier for the state, a 3-digit county identifier, followed by a 6-digit tract identifier. For example, Census Tract number 41051010600 can be decomposed State 41 (Oregon), County 051 (Multnomah) and Tract 010600. Using the Census Metropolitan Statistical Area Definition Files, we see that any Census Tract that starts with 41051 (often referred to as the FIPS State-County) is within the MSA 38900 (Portland-Vancouver-Hillsboro, OR-WA). Using this information, we filtered the our tracts list to only those within our MSAs of interest.

Second, using only this filtered set of Census Tracts, we matched the Census Tract numbers to the Census Tract numbers of Census 2010 tract shapefiles. Using a list of CBDs for each of the metro areas, we calculated the distance from the CBD to the nearest point of each MSAs Census Tract polygon. Once this spatial relationship is calculated, we could calculate totals for core MSA and the MSA as a total.

Using the existing literature, we developed the typology of tracts in poverty featured in the report. We used QGIS to create GEOJSON-based shapefiles with the geographic data in them. This allows us to host the files on github, making them available for download. But first, we needed to shrink the size of the shapefiles in order to serve an entire metro areas tract files quickly. We did this by simplifying the geography using rgeos in R. Additionally, by having a shapefile for each metropolitan area, we can quickly and dynamically load shapefiles for each metro area. To create the interactive maps for each metro, we used a combination of Mapbox.js and the Stamen Design basemaps.

We hope that both the data and the analysis that we develop at City Observatory help advance the understanding of cities.  Please feel free to contact us with your questions and comments.

Our dataset can be downloaded here.

How Poverty Has Deepened (part 2)

Posted on by CityObservatory Guest

Recently, we discussed the growth in the number of urban high-poverty neighborhoods, which we illustrated by examining the distribution of poverty rates among census tracts. This analysis showed that high poverty neighborhoods are becoming more common in urban areas. Today we will use this distribution to discuss what few of us have directly experienced: extremely concentrated poverty. There is a small but growing segment of the population that lives in significantly differently conditions than the rest of the population; this group is one that sees extreme hardship and the highest rates of poverty nationally.

As you can see, while next to no one lived in urban census tracts had an 80% or higher poverty rate in 1970, over 72,000 people lived in neighborhoods with an 80% or higher poverty rate 40 years later. 20,000 lived in tracts with a 90% or higher poverty rate. It is extremely difficult for many to imagine living in a neighborhood where 1 in 2 people live in poverty (notice that this number tripled 1970 to 2010), but to live in a place where almost no one lives on more than $22,050 a year- for a family of 4- has profound implications for those residents.

While 72,000 is not a lot in the scope of the millions of residents of urban neighborhoods nationwide, it is still deeply concerning to have that many live in pockets of such highly concentrated poverty. To understand more about what 80% poverty means, I examined a census tract in Cleveland with an 83% poverty rate. It is census tract # 39035109801, and it is part of the Central neighborhood in Cleveland. In 1970, it had over a 50% poverty rate. Google Earth shows this picture of it:

cleveland google maps

It is a mix of empty land, industrial warehouses, and low-income housing units. The 2010 Census data provides the following demographic breakdown:

These are extremely atypical demographics. For example, the national median household income was $50,046 in 2010, compared to $7,654 in this neighborhood. Even with pictures, numbers, and demographic profiles, it is very difficult for most people to understand how difficult it can be to live in a place with this level of poverty.

We know that high poverty rates– even at the levels of 30% instead of 50% or higher- can have long-lasting implications for residents. Specifically,

“Concentrated poverty is associated with negative social effects (higher crime, worse mental and physical health), and lower economic prospects (both for current residents now and their children over their lifetimes). Concentrated poverty tends to be self-reinforcing: low-income communities have fewer fiscal resources (despite greater needs), producing low-quality public services. A lack of strong social networks undercuts the political efficacy of these citizens. There are a number of studies that review the extensive literature on the negative effects of concentrated poverty (Jargowsky & Swanstrom, 2009; Sard & Rice, 2014; Kneebone, Nadeau, & Berube, 2011).” –Lost in Place: Why the persistence and spread of concentrated poverty—not gentrification—is our biggest urban challenge.

Most troubling is the direct impact on children in poverty. 26% of children are living in poverty, almost double the national rate (14.5%). In the neighborhood I just highlighted, 897 children 14 and younger—or 45% of the population according to the census—grew up in a place where if they were not impoverished, almost all of their neighbors were. The effects of a poor neighborhood, including sub-standard public services, worse schools, a lack of social ties necessary to get better jobs, and the many other well-noted direct social and economic impacts of living in concentrated poverty all mean that a growing number young children are growing up with less of a chance than they would have had 40 years ago.

More unfortunately, this also means that demographically, the growing concentration of poverty and income segregation has resulted in lower opportunities for people of color. Poverty and lowered income mobility disproportionately affects children of color; 71% of black infants and toddlers are low income, as are 67% of Hispanic infants and toddlers. (The Central neighborhood above is an even more extreme example of this disproportionality.) New evidence by Reardon, Fox and Townsend (2014) examines economic integration and racial segregation, noting that:

“The racial disparities in neighborhood income distributions are particularly troubling because these are differences that are present even among households with the same incomes. If long-term exposure to neighborhood poverty negatively affects child development, educational success, mental health, and adult earnings (and a growing body of research suggests it does, as noted above), then these large racial disparities in exposure to poverty may have long-term consequences. They mean that black and Hispanic children and families are doubly disadvantaged—both economically and contextually—relative to white and Asian families.”

Given the self-reinforcing nature of poverty and its effects, this is a very concerning trend for black and Hispanic communities. The more common experience of urban poverty, and its concentration and deepening, doesn’t add up to a promising future- for any of us.

(At CityObservatory, we will continue to explore themes of poverty, economic integration, and policy solutions aimed at alleviating these issues. We also hope to illuminate growing evidence that increasing the welfare of low-income citizens has positive implications for middle and higher-income citizens. To read more about income segregation and economic opportunity, go here. For some links to articles we find particularly relevant go here and here.)

How Poverty Has Deepened (part 1)

Posted on by CityObservatory Guest

Many talk about poverty—its causes, its effects, and its possible remedies. There is literature on this issue from almost every social science, and no one can summarize it all in one blog post. However, there’s one aspect of our most recent report that I wanted to highlight: the deepening of poverty. Not only are we seeing much more highly concentrated poverty than we used to–but this has the most profound effect on children.

As a quick background if you haven’t read it: the report looks at concentrated poverty in urban neighborhoods (census tracts within 10 miles of the central business district), and concludes that a full three-quarters of neighborhoods that were high-poverty neighborhoods 40 years ago are still mired in poverty today. Additionally, the number of new high poverty neighborhoods has tripled, and the number of poor people in them has doubled, a figure that amounts to 3.2 million people.

smaller infographic

Another way to look at this change is to examine the distribution of poverty rates across both neighborhoods (or census tracts), and population within those neighborhoods. (For those of you that aren’t stats-oriented: a distribution– generally graphically shown as a histogram—gives you an idea of what ‘normal’ looks like, and what kind of variation you would see. The highest point on the histogram is the most common  outcome of any given variable.) The following histograms chart out the poverty rate both in terms of population and census tracts. (So, there were 15 million people in neighborhoods with a 0-5% poverty rate in 1970, 5,000 neighborhoods with a 5-10% poverty rate in 1970, and so on.)

 

As you can see, the general shape is the same across both time periods, and both peak at the 5-10% poverty rate range. However, there seems to be a spreading of both distributions in 2010. That is, while the majority of urban census tracts were in the 5-10% poverty range, the height of this norm was smaller, and there were more people and neighborhoods in the 10% and over bins. This is an indicator that not only are more people in poverty—and economically segregated into high-poverty neighborhoods—but that the experience of high poverty had become more common. The Equality of Opportunity Project has found that intergenerational income mobility is much lower in places with high levels of income segregation; the growing income segregation that we see over this time period means that millions of Americans will not be able to achieve the American dream.

To see the extent of this shift, we examined the tail end of the distribution—basically, the most impoverished neighborhoods. We will discuss this—and its implications—in a post later this week.

Is your city or neighborhood poorer than 40 years ago?

Posted on by CityObservatory Guest

We recently released our latest report, Lost in Place: Why the persistence and spread of concentrated poverty–not gentrification–is our biggest urban challenge. It speaks to a national trend that’s been largely ignored– that urban poor are being concentrated into poorer neighborhoods, and that those neighborhoods are increasing in number. We speak here about some of those implications, and here and here we provide references to what others are saying about gentrification and poverty; here we address economic segregation.

Neighborhood change is by definition a highly local process, and everyone wants to know how their city is performing:  What about their city? Their neighborhood?  Nationally, the number of high-poverty neighborhoods tripled, and the number of people in poverty in those neighborhoods have doubled, but this is not the pattern in every city. In Detroit, the numbers are even more staggering–the population living in poverty is more than 228,000, from less than 40,000 40 years previous.  A few places like Virginia Beach saw an actual decline in concentrated poverty.  Rebounding neighborhoods have been more common in some metros like New York and Chicago.

If you want to see the data for individual metros, we’ve created a city-specific dashboard. Just select the city of interest, and you’ll see a comprehensive set of indicators showing how your metro performed between 1970 and 2010.

As you look at individual cities, keep these overall trends in mind:

  • Most cities only had 1 or 2 “rebounding” neighborhoods, or neighborhoods that were previously high poverty, and by 2010 were below the national average rate of poverty (15%).
  • Nationally, the number of high-poverty tracts tripled.
  • Overall, the number of poor people in those high-poverty tracts doubled.
  • High-poverty neighborhoods that didn’t rebound weren’t stable: they lost, on average, 40 percent of their population over 40 years (both of poor and non-poor persons). This means most “chronic high poverty” neighborhoods saw a dramatic reduction in population by 2010.
  • The majority of the increase in those living in high poverty were in newly poor or “fallen star” neighborhoods. (Fallen stars are neighborhoods that had poverty rates below the national average in 1970, but have poverty rates of 30 percent or higher today).  The number of fallen stars exceeded the number of rebounding neighborhoods 12 to 1.

The process of neighborhood change is often difficult and disruptive, and poverty and gentrification are sensitive topics. Each city is different and has unique challenges; however, most cities follow the national trend of increasing concentrated poverty.  If we are serious about bettering the lives of the poor (and we should be), we need to carefully examine the data about change and look for solutions that are fully grounded in the facts of neighborhood change.

If you want to look at each city’s specific tract-level data, go to the report here and scroll to the maps. We will also be sharing an informational post about how these were made soon- check back in a couple days!