THE DEVALUATION OF ASSETS IN BLACK NEIGHBORHOODS

THE DEVALUATION OF ASSETS

IN BLACK NEIGHBORHOODS

The case of residential property

Andre Perry

Jonathan Rothwell

David Harshbarger

November 2018

BROOKINGS METROPOLITAN POLICY PROGRAM | GALLUP2

Using census and real estate market data, a study of property values in U.S.

metropolitan areas of owner-occupied homes located in neighborhoods at least

50 percent Black nds that:

EXECUTIVE SUMMARY

In U.S. metropolitan areas, 10 percent

of neighborhoods are majority Black,

and they are home to 41 percent of the

Black population living in metropolitan

areas and 37 percent of the U.S. Black

population. These neighborhoods hold

$609 billion in owner-occupied housing

assets and are home to approximately

10,000 public schools and over 3 million

businesses. Though most residents are

Black (14.4 million non-Hispanic Black) by

denition, approximately 5 million non-

Black Americans from every other racial

and ethnic background live in majority Black

neighborhoods.

In the average U.S. metropolitan area,

homes in neighborhoods where the share

of the population is 50 percent Black

are valued at roughly half the price as

homes in neighborhoods with no Black

residents. There is a strong and powerful

statistical relationship between the share

of the population that is Black and the

market value of owner-occupied homes.

Location in a Black neighborhood predicts

a large nancial penalty for 117 out of the

119 metropolitan areas with majority Black

neighborhoods, though the valuation gap

varies widely between them.

THE DEVALUATION OF ASSETS IN BLACK NEIGHBORHOODS 3

The undervaluation of housing in Black neighborhoods has important social implications. Black homeowners

realize lower wealth accumulation, which makes it more difcult to start and invest in businesses and afford

college tuition. We believe anti-Black bias is the reason this undervaluation happens, and we hope to better

understand the precise beliefs and behaviors that drive this process in future research.

Differences in home and neighborhood

quality do not fully explain the

devaluation of homes in Black

neighborhoods. Homes of similar quality

in neighborhoods with similar amenities

are worth 23 percent less in majority Black

neighborhoods, compared to those with

very few or no Black residents. Majority

Black neighborhoods do exhibit features

associated with lower property values,

including higher crime rates, longer

commute times, and less access to high-

scoring schools and well-rated restaurants.

Yet, these factors only explain roughly half

of the undervaluation of homes in Black

neighborhoods. Across all majority Black

neighborhoods, owner-occupied homes

are undervalued by $48,000 per home

on average, amounting to $156 billion in

cumulative losses.

Metropolitan areas with greater

devaluation of Black neighborhoods

are more segregated and produce less

upward mobility for the Black children

who grow up in those communities. Using

combined tax and census data from the

Equality of Opportunity Project, this analysis

nds a positive and statistically signicant

correlation between the devaluation of

homes in Black neighborhoods and upward

mobility of Black children in metropolitan

areas with majority Black neighborhoods.

Segregation is negatively correlated with

Black home valuations.

BROOKINGS METROPOLITAN POLICY PROGRAM | GALLUP4

Notwithstanding the underlying assumption of

Meek’s perceived problem at Oxford, the presence

of a negative bias toward Blacks prevents even the

most noble of efforts to improve neighborhoods from

building upon the strengths of Black residents. That

sentiment can be heard in a common refrain in Black

communities that “reform is done to us, not with us.”

The value of assets is inuenced by implicit societal

cues. Researchers at the Kirwan Institute for the

Study of Race and Ethnicity at Ohio State University

dene implicit bias as the “attitudes or stereotypes

that affect our understanding, actions, and decisions

in an unconscious manner.”

They nd that “implicit

associations we harbor in our subconscious cause

us to have feelings and attitudes about other people

based on characteristics such as race, ethnicity, age,

and appearance.” Through direct and indirect cues,

people develop these associations over the course of

a lifetime, beginning at a very early age.

Researchers have demonstrated the presence of

unconscious bias in education, the criminal justice

system and health care.

And since the murder of

Trayvon Martin by George Zimmerman in 2012,

activists have raised public consciousness around

the biases involved in the killing of Black men at the

hands of police, captured so many times on cell phone

video.

n September 19, 2018 University of Mississippi

alumnus, former faculty member and

administrator, Ed Meek, posted on Facebook two

separate pictures of African American women along

with the caption, “Enough, Oxford and Ole Miss

leaders, get on top of this before it is too late.” For

Meek, namesake of the Meek School of Journalism

and New Media, the women’s presence apparently

signaled the decline of the town of Oxford, home of

the University of Mississippi. “A 3 percent decline in

enrollment is nothing compared to what we will see if

this continues…and real estate values will plummet as

will tax revenue,” Meek wrote.

To be clear, the sheer presence of Black women

doesn’t devalue homes. However, signaling they do

can negatively impact housing markets. Meek served

as the university’s assistant vice chancellor for

public relations and marketing for 37 years.

Meeks’

Facebook post suggests in word and deed that the

values we place on people are strongly associated

with proximate assets. Black people according to

Meek lowers real estate values.

After community-wide condemnation, Meek

halfheartedly backed in to an apology. “I have done as

you requested, Chancellor,” Meek wrote. “I am sorry I

posted those pictures but there was no intent to imply

a racial issue. My intent was to highlight we do have a

problem in The Grove and on the Oxford Square.”

INTRODUCTION

THE DEVALUATION OF ASSETS IN BLACK NEIGHBORHOODS 5

Much of the research on implicit bias focuses on

individuals’ perception of individual members of an

oppressed class. However, we should expect some of

these biases to carry over into places where there

are high concentrations of Black people. The value of

assets—buildings, schools, leadership, and land itself—

are inextricably linked to the perceptions of Black

people.

There is strong evidence that bias has tangible effects

on real estate markets, both historically and today.

During the 20th century, both explicit government

institutions and decentralized political actions created

and sustained racially segregated housing conditions

in the United States.

This has created what has

been dubbed a “segregation tax,” resulting in lower

property valuations for Blacks compared to whites per

dollar of income.

Contemporary work from social scientists has

aimed to sort out whether these lower valuations

are caused by differences in socio-economic status,

neighborhood qualities, or discrimination.

The results

tend to show compelling evidence for discrimination.

In one study, Valerie Lewis, Michael Emerson, and

Stephen Klineberg collected detailed survey data on

neighborhood racial preferences in Houston, Texas.

They asked people to imagine that they were looking

for a new house, found one within their price range

and close to their job; they then say to respondents,

“checking the neighborhood . . .” and then present

difference scenarios based on racial composition,

school quality, crime, and property value changes

for the hypothetical neighborhood.” Consistent with

previous research, they nd that these neighborhood

features strongly predict whether someone says they

would buy the house. Racial composition strongly

predicted the preferences of whites in neighborhoods

that were otherwise identical.

Researchers Jacob Fabera and Ingrid Gould Ellen

examined the variation of rising housing prices among

people of different racial categories who purchased

their homes before the boom from 2000 to 2007 and

kept them through the bust of 2008.

They found that

Blacks and Hispanics gained less equity than whites

during that period and were more likely to owe more

than their home was worth. The researchers found

that “[b]lack–white gaps were driven in part by racial

disparities in income and education and differences

in types of homes purchased.” They hypothesized

that racial segregation and the corollary economic

and education stratication between neighborhoods

exacerbated existing equity disparities within

neighborhoods with high concentrations of poverty.

Consequently, the recession hit those neighborhoods

disproportionately harder, creating intense volatility

in those particular markets. Declining incomes

reduced people’s ability to purchase homes, thus

deating prices in those neighborhoods. The ndings

around education and income may result from the

disparities in wealth as it is “a powerful predictor

of individual educational and economic outcomes,

and despite their signicantly lower homeownership

… the long-run consequences of these gaps are

substantively important and difcult to overcome.”

But how does the concentration of Blackness

impact demand among all buyers—whether from the

community or not? Income and education certainly

matter, but how much of the demand that impacts

housing price is affected by how people around it are

perceived? In other words, what is the cost of racial

bias?

Real estate agents have been shown to direct

Black and white home buyers differently based on

racial stereotypes, reinforcing patterns of racial

segregation. Researcher Sun Jung Oh and John

Yinger reviewed four different national studies on

the topic in a 2015 article and found a common

thread: There is “evidence of statistically signicant

discrimination against home seekers who belong to a

historically disadvantaged racial or ethnic group.”

Some of this research is not about devaluation, per

se, but about steering and price discrimination. It

indicates that Blacks actually pay more than whites

for equivalent housing. The focus of this paper is on

how lower prices in majority-Black neighborhoods

convey lower value. Nevertheless, prior research

forces us to assume that bias is baked into home

prices. This study seeks to understand how much

money majority Black communities have to lose from

the devaluation of housing assets stemming from

racial bias throughout the market.

BROOKINGS METROPOLITAN POLICY PROGRAM | GALLUP6

MAIN CONCEPTS

We dene the devaluation of housing in Black

communities as the property value penalty that

characterizes an owner-occupied home in a

neighborhood that is 50 percent Black.

We provide three estimates for this penalty at

the national and metropolitan levels. Our national

analysis is restricted to only metropolitan areas, since

estimates would likely have large margins of errors in

rural counties with few census tracts or small Black

populations.

Actual devaluation: We start with a simple

description of the mean difference in home value

(shown in percentage point terms) between properties

in neighborhoods with zero African-Americans and

neighborhoods that are 50 percent African-American.

Devaluation adjusted for structural characteristics

of the home: This adjusts the predicted effect of

Black neighborhood population by the physical

characteristics of the home—such as when it was built,

the number of bedrooms—and the distance between

the home and centers of work and the type of homes

in the neighborhood.

Devaluation adjusted for structural characteristics

of the home and neighborhood amenities: This

adjusts for all the above characteristics, as well as

the number of people living in the neighborhood,

the family structure of neighbors, their age, and,

importantly, the quality of local schools and access to

retail establishments.

METHODS

Structural Characteristics

• Median bedrooms

• Median year built

• Single family detached share of owner-occupied

units

• Single family attached share of owner-occupied

units

• Mobile homes share of owner-occupied units

• Share of homes with no vehicle availability

• Share of homes with gas or electric heating

• Share of homes with kitchen

Neighborhood Amenities

• Mean commute of working adults

• Percent of working adults who carpool to work

• Percent of working adults who use public

transportation

• Percent of units that are owner-occupied

• Population (natural log)

• Share of households with children under 18

• Share of households headed by single moms

• Median age of population

• EPA Walkability Index

• Number of professional service businesses

• Number of libraries

• Number of museums and historical sites

• Number of food and drinking places

• Number of gas stations

• Prociency rate of 4th-8th grade public school

students

THE DEVALUATION OF ASSETS IN BLACK NEIGHBORHOODS 7

Community Survey, we averaged Zillow’s ZIP code-

level data from 2012 to 2016.

In practice, the census and Zillow measures are highly

correlated. The correlational coefcient between

census tract median owner-occupied home values and

the Zillow median listing price is 0.84. The census-

based correlation with Zillow’s median price per

square foot is 0.78.

Access to schools

To measure school quality, we consider that

public school attendance areas roughly align with

neighborhoods, and housing prices are higher in

areas near high-scoring public schools, as previous

Brookings research has discussed.

To account for

school quality in our analysis, we obtained prociency

rates on state exams for all public schools covering

grades 4-8 for both mathematics and reading.

These data are available from the Department of

Education.

We matched schools to census tracts based on

the latitude and longitude coordinates, which are

available via the Department of Education. Our

approach was to take a 5-mile radius around each

census tract and consider every school in that radius

as a potential school for that neighborhood. The

nearest schools to the tract—including all those in the

tract—were assigned to the tract until the cumulative

school population in grades 4 to 8 equaled the

population of 10-to-14-year-olds in the tract.

DATA SOURCES

Home values

Home values, neighborhood demographics, and

structural characteristics are from the 2016 American

Community Survey 5-Year Estimates (ACS).

Our dependent variable from the ACS—median home

values at the census tract level—comes from an item

on the questionnaire that asks homeowners: “About

how much do you think this house and lot, apartment,

or mobile home (and lot, if owned) would sell for if it

were for sale?”

These data are limited by the fact that they are

self-reported and not all homes are actually for sale.

Our primary measure of housing value overcomes

these limitations. It consists of ZIP code data from

Zillow, a housing market research company. Zillow

provides median price listing overall and per square

foot at the ZIP-code level.

There is some error in

moving between ZIP codes and census tracts, which is

needed to characterize ZIP-code racial demographics,

but the property-level accuracy of the Zillow data

is likely to be superior, since it is based on actual

listing prices rather than self-reported valuations.

Another advantage of Zillow data is that it includes

estimates for price per square foot, a quality-adjusted

price. We matched ZIP codes to census tracts

using a correspondence engine from the Missouri

Census Data Center (MABLE).

To make Zillow data

as comparable as possible to the 5-year American

WHY STUDY OWNER-OCCUPIED HOUSING

We focus on owner-occupied homes for two

reasons. Home appreciation results in higher home

values, and this brings wealth to owners. There

is a large and well-known wealth gap between

Blacks and other racial groups in the United States,

much of which can be attributed to differences in

homeownership rates and the value of housing.

Second, the devaluation of rental properties is

advantageous to renters, insofar as it results in a

lower rental payment for similar quality housing.

The devaluation of owner-occupied housing makes

it easier to acquire the home, but once purchased,

it is unambiguously disadvantageous to the owner

and occupier, who would otherwise benet from

being able to renance, borrow, or sell at a higher

valuation.

BROOKINGS METROPOLITAN POLICY PROGRAM | GALLUP8

Our nal measure of school quality is the mean

prociency rate of all 4th-8th grade students in the

census tract. We take the mean of high and low-end

estimates, since data for many schools are reported

as ranges.

Access to businesses

To measure access to stores, restaurants, and other

goods and service providers, we obtained data on the

number of business establishments by industry by ZIP

code from the 2016 Census Bureau’s County Business

Patterns database. We matched ZIP codes to census

ZIP code tabulation areas (ZCTAs), using a crosswalk

developed by GeoMapper, and then ZCTAs to tracts

using a correspondence engine from the Missouri

Census Data Center (MABLE).

We examined all two-digit sectors and found

professional business establishments best

explained variation in home prices. It is unlikely

that homeowners give much value to proximity to

engineering and law rms. Instead, the signicance of

this variable likely comes from the fact professional

establishments tend to cluster near neighborhoods

with professional workers for commuting reasons.

We also examined three-digit industries in retail,

restaurants, and other services. We found that the

number of food and drinking places (e.g. restaurants

and bars), museums, and gas stations were all

signicant predictors of home value (gas stations

have a negative relationship) and reasonably

independent of one another. Surprisingly, grocery

stores and other retail had no consistent relationship

with home value. Finally, we also tested libraries

as another possible amenity, and that proved to be

robust, so it was included in the nal model.

Walkability

Another aspect of access to businesses and

a desirable urban lifestyle is the concept of

“walkability.” For this, we rely on the Environmental

Protection Agency’s (EPA) National Walkability Index.

It gives higher scores to neighborhoods with diverse

businesses, a large number of housing units, and

intersecting streets. These features predict more walk

trips. We convert block measures to tracts.

Crime

Exposure to crime is an important neighborhood

characteristic that likely affects home values.

Unfortunately, comprehensive data on crime is only

available at the county-level, and our analysis did

not nd that neighborhoods located in counties with

higher crime rates had lower property values. We do,

however, control for the median age of residents in

the neighborhood and the percent of families that

are single-mothers with children under 18 living in

the home. Both are correlated with crime rates (-.28

and .47 respectively), suggesting that we are likely

capturing crime effects in our analysis.

To further investigate this, we obtained data from

10 large cities from U.S. City Open Data Census

where crimes were coded using geo-coordinates.

The analysis is described in more detail in the

Appendix. Adding crime to our model did not affect

our estimates of the association between Black

population and home values, providing further

reassurance that explicitly measuring crime at the

neighborhood level would not change the conclusions

of this research.

Income mobility and other metrics

Using data from Chetty, Hendren, Jones, and Porter,

we measure income mobility of Black children by

showing the average income rank by metropolitan

area for Black adults aged 31 to 37 who grew up in

low-income families, dened as those at the 25th

percentile of the national income distribution.

Chetty

and his coauthors made these data available at the

level of commuting zones, which are like metropolitan

areas but dened to include non-metropolitan

counties and use a slightly different algorithm to

assign counties to areas. We assign commuting zones

to metropolitan areas by assigning the largest county

(by 2010 population) in each commuting zone to its

metropolitan area.

We follow Chetty, Hendren, Jones, and Porter in

supplementing our analysis with data from Stephens-

Davidowitz on the prevalence of anti-Black Google

searches in the metropolitan area.

In the absence of

representative survey data at the metropolitan scale

on racist beliefs, this metric is one of the few potential

THE DEVALUATION OF ASSETS IN BLACK NEIGHBORHOODS 9

indicators of racist or anti-Black sentiment available.

If racism is a factor in the devaluation of Black

homes, and Google searches that use anti-Black slang

indicate racism, then this metric may explain some of

the variation in devaluation.

We further supplement the analysis with a standard

measure of segregation, the dissimilarity index, which

measures the unevenness of racial group residency

across census tracts. We construct this measure using

the same 2012-2016 American Community Survey

data used in the rest of the analysis.

Household income and educational

attainment

We did not include household income or education

directly in our model to estimate devaluation. Income

and education reect the buying power of individuals,

and naturally, both tend to rise along with home

values. Including them in the model would essentially

test whether homes in Black neighborhoods are over

or under-valued relative to the purchasing power of

residents; in other words, it would be estimating the

affordability of housing. That is a different question

than the one we ask here, which is whether homes are

over or under-valued in Black neighborhoods based

on the qualities of the home and neighborhood in a

given metropolitan housing market. People who live

outside of the neighborhood are potential buyers and

so should be considered part of the market. Since

we control for metropolitan area xed effects, this is

captured in our analysis.

To understand the consequences of omitting income

and education in our model, we ran our preferred

specication—a regression of the list price per square

foot on our full model—while including median

household income and the share of residents with a

bachelor’s degree or higher. Both are signicant and

positively related to home values, as expected, but

their inclusion has no effect on our main variable of

interest—the Black population share. Our devaluation

estimate excluding income and education in this

model is -22.7 percent, whereas it is -21.7 percent

if we include them. We infer from this that home

affordability patterns are similar for homeowners

in majority Black neighborhoods and those outside

them, controlling for everything else we see about

the home and neighborhood. This result reinforces

our nding that homes are devalued in Black

neighborhoods in large part because they are in Black

neighborhoods, and not only because the homes or

neighborhoods have less desirable features or the

residents have lowering purchasing power.

BROOKINGS METROPOLITAN POLICY PROGRAM | GALLUP10

1. In U.S. metropolitan areas, 10 percent of

neighborhoods are majority Black, and they are

home to 41 percent of the Black population living

in metropolitan areas and 37 percent of the U.S.

Black population.

Black Americans are highly urbanized. 90 percent

live in metropolitan areas, compared to 86 percent of

all U.S. residents. And decades after the Civil Rights

movement, Blacks remain highly segregated. Though

Blacks comprise just 12 percent of the U.S. population,

70 percent live in neighborhoods that are over 20

percent Black, and 41 percent live in majority Black

neighborhoods.

These majority Black neighborhoods may be

overlooked as sites for economic development, but

they contain important assets, in terms of people,

public infrastructure, and wealth.

Majority Black neighborhoods in metropolitan areas

are also home to 14.4 million non-Hispanic Black

residents and 5 million residents from other racial

and ethnic groups. They also house a large portion

of the nation’s human capital, in that 2.3 million

adults 25 and older call majority Black neighborhoods

their home, representing 5 percent of the nation’s

metropolitan population with a bachelor’s degree, and

10 percent of its public schools and 6 percent of its

libraries.

There is also wealth in these neighborhoods. In

metropolitan America, there are 3.2 million owner-

occupied homes in majority Black neighborhoods,

5 percent of the total, and they are collectively

worth $609 billion.

Likewise, over 3 million

business establishments are located in majority

Black metropolitan neighborhoods, 7 percent of all

metropolitan businesses.

FINDINGS

The distribution of neighborhoods and Black population by exposure to Black neighbors

U.S. metropolitan areas, 2012-2016

Source: Authors’ analysis of 2016 American Community Survey 5-year estimates

TABLE 1

Share of Black

metropolitan population

Share of metropolitan

neighborhoods

Blacks 0% to less than 1% 1% 22%

Blacks 1% to less than 5% 6% 28%

Blacks 5% to less than 10% 9% 14%

Blacks 10% to less than 20% 15% 13%

Blacks 20% to less than 50% 29% 12%

Blacks 50% or higher 41% 10%

THE DEVALUATION OF ASSETS IN BLACK NEIGHBORHOODS 11

2. In the average U.S. metropolitan area, homes in

neighborhoods where the share of the population

is 50 percent Black are valued at roughly half the

price as homes in neighborhoods with no Black

residents.

Across metropolitan America, housing prices are

systematically lower where neighborhood Black

population share is higher. In neighborhoods where

less than 1 percent of the population is Black

(which

we refer to as “non-Black neighborhoods”), median

listing prices on Zillow are $341,000 compared to

$184,000 in majority Black neighborhoods. Using

Census Bureau estimates from homeowners yield

similar discrepancies. Comparing only homes within

the same metropolitan area, both data sources

suggest that home values are just over 50 percent

lower in neighborhoods where the Black population is

50 percent compared to neighborhoods with no Black

residents.

The devaluation of Black neighborhoods is widespread

across the country. There are 119 metropolitan areas

with at least one majority Black census tract and

one census tract that is less than 1 percent Black.

In 117 of these 119 metro areas, homes in majority

Black neighborhoods are valued lower than homes in

neighborhoods where Blacks are less than 1 percent of

the population. Gainesville, Fla. and Sebring, Fla. are

the only exceptions.

Neighborhood median home value by Black population share

U.S. metropolitan areas, 2012-2016

Source: Authors’ analysis of Zillow and 2016 American Community Survey 5-year estimates

FIGURE 1

$341,155

$337,654

$278,056

$239,669

$211,383

$184,440

$306,511

$308,441

$250,356

$208,474

$181,281

$149,217

Blacks 0%-1% 1%-5% 5%-10% 10%-20% 20%-50% 50% or higher

Median list price (Zillow) Median value (Census Bureau)

BROOKINGS METROPOLITAN POLICY PROGRAM | GALLUP12

The valuation gaps are extreme in a number of

areas. The largest gap is in the Bridgeport-Stamford-

Norwalk, Conn. metropolitan area. In neighborhoods

where Blacks are less than 1 percent of the population,

the median home value is $784,000, compared to

just $131,000 in majority Black neighborhoods, a

six-fold difference. Home values in majority Black

neighborhoods are just 17 percent of those in non-

Black neighborhoods. Likewise, very large differences

are found throughout the South and Midwest—in

Charleston, S.C., Cape Coral, Fla., Youngtown, Ohio,

and Ann Arbor, Mich.

The 10 metropolitan areas with the largest and smallest differences in the value of homes

Black neighborhoods in U.S. metropolitan areas, 2012-2016

Note: Sample limited to metropolitan areas with at least one census tract that is majority Black and at least one census tract

that is less than one percent Black.

Source: Authors’ analysis of 2016 American Community Survey 5-year estimates

TABLE 2

Median value

of homes in

majority Black

neighborhoods

Median value

of homes in

neighborhoods with

less than 1% Black

population

Relative

valuation of Black

neighborhoods in

percentage points

Areas with the largest difference in home value

Bridgeport-Stamford-Norwalk, CT $131,011 $783,887 17%

Charleston-North Charleston, SC $130,854 $717,711 18%

Savannah, GA $112,539 $562,500 20%

Hilton Head Island-Bluffton-Beaufort, SC $93,262 $460,712 20%

Youngstown-Warren-Boardman, OH-PA $33,045 $131,484 25%

Port St. Lucie, FL $65,880 $259,926 25%

Palm Bay-Melbourne-Titusville, FL $61,662 $241,853 25%

Lexington-Fayette, KY $7 7, 270 $301,526 26%

Cape Coral-Fort Myers, FL $67,192 $259,118 26%

Ann Arbor, MI $68,320 $259,985 26%

Mean of group $84,104 $397,870 21%

Areas with the smallest difference in home value

Greenville-Anderson-Mauldin, SC $82,680 $114,743 72%

New York-Newark-Jersey City, NY-NJ-PA $403,314 $559,706 72%

Baton Rouge, LA $109,951 $152,543 72%

Boston-Cambridge-Newton, MA-NH $313,353 $430,997 73%

Naples-Immokalee-Marco Island, FL $390,200 $459,728 85%

Asheville, NC $178,200 $195,882 91%

Lakeland-Winter Haven, FL $82,559 $89,334 92%

Anniston-Oxford-Jacksonville, AL $59,371 $61,200 97%

Gainesville, FL $95,591 $95,237 100%

Sebring, FL $134,600 $69,644 193%

Mean of group $184,982 $222,901 83%

THE DEVALUATION OF ASSETS IN BLACK NEIGHBORHOODS 13

There is nonetheless an extremely wide range of

estimates across metropolitan areas for the housing

market penalty for homes in Black neighborhoods. In

the New York City metropolitan area, median home

values in majority Black neighborhoods are over

$400,000, reecting the extraordinarily high overall

cost of living and value of real estate. That is much

less than the value for neighborhoods with fewer than

1 percent Black population shares ($560,000), but the

percentage point gap is much lower than other parts

of the country. Greenville, S.C., Boston, Mass., and

Baton Rouge, La. are other examples of metro areas

with relatively narrow gaps in valuations between

majority Black neighborhoods and those with few

Black residents.

3. Neighborhood quality is only part of the

explanation for the devaluation of homes in Black

neighborhoods.

During the 20th century, segregation and Jim

Crow forcibly lowered the quality of neighborhood

conditions for Blacks and impeded their nancial

ability to move to better opportunities. This occurred

through deed restrictions, redlining, and zoning, as

well as other mechanisms. As a result of that dynamic

and the continuation of housing policies that exclude

working-class housing from non-Black neighborhoods,

majority Black neighborhoods suffer from lower

quality housing and limited access to good schools

and neighborhood amenities.

The quality of housing in majority Black

neighborhoods differs from less Black neighborhoods

in terms of age, size, and structure. The median home

in majority Black neighborhoods is 12 years older than

homes in neighborhoods where Blacks are less than

1 percent of the population. These older homes are

also smaller, by nearly half a room, and are much less

likely to be detached single-family homes. Majority

Black neighborhoods are much more likely to have

denser housing structures, such as attached single-

family units, which also reects the concentration of

Blacks in America’s cities.

Not only is the housing stock of lower quality, so is

the surrounding neighborhood in several important

dimensions. School performance is weaker, commute

times are longer, and access to business amenities

is more limited. There is also evidence that exposure

to environmental pollution is greater, through, for

example, proximity to a greater number of gas

stations.

Physical characteristics of housing units by Black neighborhood population share

U.S. metropolitan areas, 2012-2016

Source: Authors’ analysis of 2016 American Community Survey 5-year estimates

TABLE 3

Median year

structure built

Median number of

rooms per unit

Single-family

detached, % of

units

Single-family

attached, % of

units

Blacks 0%-1% 1975 6.5 83.1 5.0

Blacks 1%-5% 1974 6.4 79.7 6.7

Blacks 5%-10% 1976 6.4 79.1 7.4

Blacks 10%-20% 1975 6.2 7 7.4 8.5

Blacks 20%-50% 1973 6.2 75.2 9.5

Blacks 50% or higher 1963 6.1 73.2 12.7

BROOKINGS METROPOLITAN POLICY PROGRAM | GALLUP14

The school test score gaps between neighborhoods

are particularly extreme. The gap in test scores

between majority Black neighborhoods and those

that have Black population shares that are 5 percent

or lower is approximately 1.1 standard deviations.

More concretely, the prociency rate on state exams

in majority Black neighborhoods is only 15 percent,

compared to 60 percent in neighborhoods with less

than 1 percent Black population shares.

Likewise, residents of majority Black neighborhoods

confront longer commute times by several minutes

compared to those in other neighborhoods,

suggesting constrained access to jobs. Yet this

interpretation requires caution because residents

of majority Black neighborhoods are far more likely

to commute via public transportation, which can be

slower, especially via bus.

Still, the apparent weaknesses of Black neighborhoods

can also be strengths. With homes more densely

situated, residents of Black neighborhoods live in

more “walkable” communities, with a greater diversity

of business types and more frequent intersections.

These qualities are associated with higher home

values.

There is a striking difference on this

score between majority Black neighborhoods and

neighborhoods that are less than 1 percent Black; they

differ by over half a standard deviation.

Given the above discussion of housing and

neighborhood attributes, the central question of this

study remains: Do the differences in housing and

neighborhood quality fully account for the differences

in housing values?

The analysis here suggests not. We use regression

analysis to predict home values as a function of the

Black population share, the qualities of homes in the

neighborhood, and the qualities of the neighborhoods

within each metropolitan area.

First, there is clear evidence that adjusting for the

size of the home lowers the devaluation estimate for

Black neighborhoods by a meaningful fraction—from

-51 percent to -35 percent when we use the two Zillow-

based measures for median list price overall and by

square foot. Since Black homes are smaller, they have

less market value, but that still leaves a very large gap

unexplained.

Neighborhood characteristics by Black population share

U.S. metropolitan areas, 2012-2016

Source: Authors’ analysis data from 2016 American Community Survey 5-year estimates, Department of Education,

Environmental Protection Agency, and County Business Patterns

TABLE 4

Black

population

School

test scores

(Standardized)

EPA

Walkability

Index

Number of

restaurants

Number of

gas stations

Percent who

use public

transpor-

tation

Average

commute

time

(minutes)

0%-1% 0.29 -0.31 53.2 6.9 3.6 26.7

1%-5% 0.28 -0.03 69.3 8.1 5.1 26.5

5%-10% 0.17 -0.01 69.7 9.2 4.7 26.6

10%-20% -0.01 -0.01 67. 5 10.0 5.4 26.5

20%-50% -0.27 0.01 61.9 10.6 7.7 27.1

50% or higher -0.85 0.23 50.0 10.8 15.0 29.2

THE DEVALUATION OF ASSETS IN BLACK NEIGHBORHOODS 15

The value metrics that do not include square footage

are sensitive to the structural features of homes in

the neighborhood—such as age, number of rooms,

percentage detached, but adjusting these things did

not greatly reduce the devaluation estimate. The

Zillow median list price estimates for devaluation

in neighborhoods that are 50 percent Black range

from -40 percent to -44 percent, with census-based

estimates from owner self-appraisals in the middle at

-41 percent.

The next set of regression estimates includes

neighborhood control variables, and these variables

go further in explaining the devaluation of majority

Black neighborhoods. The devaluation estimates are

-22 percent for median list price and -23 percent for

the list price per square foot and self-appraisals of all

owner-occupied properties.

In the model that predicts value per square foot, three

variables measured at the neighborhood level stand

out as strong predictors: school quality—measured

by state test scores (strongly positive); the number

of gas stations (strongly negative) and access to

public transportation (strongly positive). Majority

Black neighborhoods are at a disadvantage on

school quality and exposure to gas stations but have

greater access to public transportation. Walkability

predicts modestly higher home values, and Black

neighborhoods have an advantage on that score as

well.

While this analysis explains roughly half of the

devaluation effect, we are left with the fact that

a square foot of residential real-estate is worth

23 percent less in neighborhoods where half the

population is Black compared to neighborhood with

few or no Black residents, even after adjusting for

housing quality and neighborhood quality.

To put this devaluation value in perspective, we

estimate that home values in majority Black

neighborhoods should be worth an additional

$48,000 per home, which amounts to a cumulative

sum of $156 billion in aggregate value.

It is certainly possible that our analysis has omitted

variables that are correlated with both the Black-

population share and the value of housing and that

could go further in explaining the gaps we observe

in value. Yet, we believe it is unlikely that any such

factors would explain the gap entirely. We have

included important variables in both formal property

appraisals and variables that consumers can use as

search criteria on popular real estate websites.

For example, on Zillow, buyers can lter homes by

the number of rooms, square footage, and year

Average devaluation of homes due to location in a neighborhood that is 50% Black compared to 0% Black

Owner-occupied units in U.S. metropolitan areas, 2012-2016

Source: Authors’ analysis of 2016 American Community Survey 5-year estimates and median values from Zillow averaged

from 2012-2016. See text for list of structural characteristics and neighborhood amenities

TABLE 5

Actual price

comparison

Adjustments

for structural

characteristics

of home

Adjustments

for structural

characteristics

of home and

neighborhood

amenities

Census median home value -55% -42% -23%

Zillow median list price of houses per square foot -35% -40% -23%

Zillow median list price of houses -51% -44% -22%

BROOKINGS METROPOLITAN POLICY PROGRAM | GALLUP16

built. These are included in our model. As explained

in the appendix, the main results are also robust

when including crime, at least in a subset of large

cities where crime data are readily available at the

neighborhood scale.

With more effort or with local knowledge,

sophisticated shoppers can also nd out information

about school quality, using the same data included

in our models, test prociency rates. There are no

publicly available metrics on school quality available

to consumers beyond what we have included in

our model. With further effort or by exploring the

neighborhood, potential buyers can also get a sense

of access to restaurants, libraries, and other business

amenities. Our model uses measures for these

amenities that best explain variation in housing,

without regard to how inclusion of these variables

affected the estimate for devaluation associated with

Black population shares. We also adjust for the length

of commute and the mode of commute and several

variables that capture neighborhood household age

and family relationships.

4. Metropolitan areas with greater devaluation

of Black neighborhoods are more segregated and

produce less upward mobility for the Black children

who grow up in those communities.

Black males earn lower incomes as adults than

white males, even when born to parents with

similar incomes. In this sense, Blacks have lower

intergenerational mobility than whites—as well as

Hispanics and Asians. Intriguingly, this is not true for

Black females, who have similar incomes as white

females born to parents at the same income scale.

These nding comes from recent research by Harvard

economists Raj Chetty and Nathaniel Hendren—along

with Census Bureau economists—which linked records

from the Internal Revenue Service to the Census

Bureau to understand intergenerational income

mobility for people aged 31 to 37 who were born

between 1978 and 1983.

We use these data to investigate whether or not Black

children raised in areas with greater devaluation

of Black assets experience less mobility. There are

several reasons why this might be so. There are

large gaps in wealth between races and residential

real estate wealth is a major reason for this gap.

If properties in Black neighborhoods were priced

equally as those in white neighborhoods, Black

children coming of age in the 1990s and 2000s would

have had much more wealth to draw upon to pay for

things like private schooling, tutoring, travel, and

educational experiences, as well as higher education

and greater access to higher scoring schools in the

suburbs. Greater property wealth may have also

facilitated higher rates of entrepreneurship among

Black parents, which may have positively affected

children.

In fact, there is a positive correlation between the

valuation of properties in Black neighborhoods and

upward mobility of Black children whose parents

had incomes at the 25th percent of the national

income distribution. In other words, Black children

born to low-income families had higher income as

adults if they grew up in a metro area that valued

Black property closer to its observable market

characteristics. We restrict this analysis to the

113 metropolitan areas with at least one majority

Black neighborhood. We also give extra weight

in the analysis to metro areas with larger Black

populations to reduce the inuence of measurement

error; as such, the estimates should be thought of

as characterizing the experience of the average

Black person living in different types of metropolitan

areas.

As shown in Figure 2, metropolitan areas in the lowest

quintile of valuation for majority Black neighborhoods

compared to white neighborhoods generate very

low upward mobility for Black children born near

1980. The average Black child born in these areas to

families at the 25th percentile of the national income

distribution advances only to the 31st percentile. In

areas with greater valuation for Black neighborhoods,

in the fourth quintile in particular, children end up in

the 35th percentile. The positive relationship is more

muted for the areas with the highest valuations of

Black neighborhoods.

We also nd that segregation is correlated with

devaluation. Areas that undervalue homes in Black

neighborhoods are much more likely to be highly

segregated, using a standard Black-white segregation

index.

THE DEVALUATION OF ASSETS IN BLACK NEIGHBORHOODS 17

A regression analysis that predicts the quality-

adjusted valuation of Black neighborhoods based

on Black economic mobility, segregation, and racist

internet searches nds all three are signicant

and help explain variation in the valuation of Black

properties. The anti-Black internet search term

variable, however, is less robust and only signicant

when controlling for the other variables.

Turning to specic metro areas, Rochester, N.Y. gives

the lowest relative value to homes in neighborhoods

that are 50 percent Black, after adjusting for housing

and neighborhood quality. These properties are listed

with 65 percent less value per square foot. Rochester

also exhibits high levels of Black-white segregation

and anti-Black internet searches are common. Black

children growing up in Rochester, New York in low-

income families (at the 25th percentile) do relatively

poorly as adults (the 31st percentile).

Tulsa, Okla., Omaha, Neb., and Jacksonville, Fla. are

also among the 10 areas with the lowest valuations

for Black neighborhoods, at -40 percent or lower.

Economic mobility is low there as well, though better

Effect of housing valuation on upward income mobility of Black children

Majority-Black neighborhoods in U.S. metro areas, 2012-2016

Note: Income rank calculated for Black children born to parents at 25th percentile of national income. Devaluation

measure is based on median list price per square foot after adjusting for home and neighborhood quality. Analysis is of 113

metropolitan areas with at least one majority Black census tract and one tract with Black population shares under 1 percent.

Means are weighted by the number of Black residents in metro area.

Source: Authors’ analysis of data from Zillow, the 5-year 2016 American Community Survey and Equality of Opportunity

Project. Devaluation measure is based on median list price per square foot after adjusting for home and neighborhood

quality. Analysis is of 113 metropolitan areas with at least one majority Black census tract and one tract with Black population

shares under 1 percent. Means are weighted by the number of Black residents in metro area

FIGURE 2

31.5

32.5

33.8

35.0

33.0

Lowest valuation of

Black neighborhoods

2 3 4

Average income rank

Valuation quintile

Highest valuation of

Black neighborhoods

BROOKINGS METROPOLITAN POLICY PROGRAM | GALLUP18

in Tulsa, where segregation is relatively low and

Google searches with anti-Black slurs are relatively

rare.

Upward mobility tends to be somewhat higher

where homes are more highly valued in Black

neighborhoods. In Boston, Mass., for example, Black

children reach the 39th percentile, on average,

when growing up at the 25th percentile. Boston is

also characterized by infrequent anti-Black internet

searches but high levels of segregation. Black children

born in the Hartford metropolitan area and Oklahoma

City also did relatively well.

Segregation and the value of housing in Black neighborhoods

Majority-Black neighborhoods in U.S. metro areas, 2012-2016

Note: Segregation is measured by the dissimilarity index at the census tract level. Devaluation measure is based on median

list price per square foot after adjusting for home and neighborhood quality. Analysis is of 113 metropolitan areas with at

least one majority Black census tract and one tract with Black population shares under 1 percent. Means are weighted by the

number of Black residents in metro area.

Source: Authors’ Analysis of 2012-2016 ACS estimates

FIGURE 3

60.3

58.6

52.6

56.3

51.7

2 3 4

Segregation

Valuation quintile

Lowest valuation of

Black neighborhoods

Highest valuation of

Black neighborhoods

This evidence presented here is not meant to prove

that devaluation causes lower mobility or vice versa.

That cannot be answered with these data, but the

evidence does suggest there may be underlying links

between the two phenomena that warrant further

exploration. Likewise, we intend to collect more

relevant and targeted data on anti-Black sentiment

in the future. The results linking anti-Black internet

searches to the devaluation of Black neighborhoods

are intriguing, but we believe the question requires

new data sources.

THE DEVALUATION OF ASSETS IN BLACK NEIGHBORHOODS 19

The devaluation of majority-Black neighborhoods

is penalizing homeowners in Black neighborhoods

by an average of $48,000 per home, amounting to

$156 billion in cumulative losses. Over the years,

segregation has negatively affected neighborhood

conditions—fewer quality schools, in particular—and

reduced the quality of homes by limiting access

to nance. However, differences in home and

neighborhood quality do not fully explain the lower

prices. In addition, there are positive but overlooked

assets in Black communities like walkability of Black

neighborhoods and access to public transportation.

The nding that Black children born into low-income

families achieve higher incomes as adults if they grew

up in metro areas where homes were less devalued

is noteworthy and could be strengthened with

further work that more directly links discrimination

to barriers to mobility and explores the potential for

neighborhood devaluation to serve as an active agent

that worsens outcomes for Blacks and their children.

The undervaluation of Black assets in housing

markets has other important social implications.

Black homeowners realize lower wealth accumulation,

which, among other effects, makes it more difcult

to start and invest in business enterprises and afford

college tuition for their children.

CONCLUSION

We hope to better identify some of the causes for

this devaluation—including potential psychological

mechanisms—in subsequent research. Some of the

most enduring and pernicious effects of the more

than 350 years of slavery, Jim Crow racism, as well

as de jure and de facto segregation in the U.S., have

been the internalization of stereotypes, insults,

and dehumanizing innuendos about Black people,

stemming from the malevolent use of such tropes by

the (white) people in power to justify discrimination—

what researchers describe as unconscious bias. Our

ndings are generally consistent with the widespread

presence of anti-Black bias—whether unconscious or

not, ingrained stereotypes and automatic associations

of a particular group, and even outright discrimination

and racism.

By controlling for commonly held causes of price

differences including education, lower home quality,

and crime, this paper suggests that bias is likely to

be a large part of the unexplained devaluation of

Black neighborhoods and some perspective on how

anti-Black beliefs distort the value of assets. In the

absence of representative survey data on racist

beliefs at the metropolitan scale, we can’t see the

degree and nature of devaluation in the context

of cities. Our future work will aim to collect and

analyze subjective survey data to see how people

from different races view each other and their

neighborhoods.

BROOKINGS METROPOLITAN POLICY PROGRAM | GALLUP20

The 10 metropolitan areas with the most and least devaluation of homes

Black neighborhoods in U.S. metropolitan areas, 2012-2016

Notes: Devaluation measure estimates median list price per sq foot after adjusting for home and neighborhood quality. The number shown

in the rst column is the average price difference in percentage point terms for homes in neighborhoods that are 50% Black compared to

those that in neighborhoods with no Black residents after making these adjustments. Metropolitan area sample is limited to those with at

least one majority Black neighborhood and one neighborhood with a less than 1% Black population share. Segregation is measured by the

dissimilarity index at the census tract level. Anti-Black sentiment is measured using Google search terms from data created and analyzed

Stephens-Davidowitz.

Source: Authors’ analysis of data from Zillow, 2016 American Community Survey 5-year estimates, and the Equality of Opportunity Project

TABLE 6

Valuation of

homes by sq

foot in Black

neighbor-

hoods (full

model)

Income rank

for Black

children born

to parents

at 25th

percentile

of national

income

Anti-Black

sentiment

index from

Google

searches

Segregation

index

Areas with the most devaluation of homes in Black neighborhoods

Rochester, NY -65% 31.2 71.1 60.9

Jacksonville, FL -47% 31.3 59.1 51.1

Omaha-Council Bluffs, NE-IA -44% 31.9 48.4 58.4

Tulsa, OK -40% 32.7 40.6 50.7

Birmingham-Hoover, AL -39% 32.0 65.3 63.1

Cape Coral-Fort Myers, FL -38% 32.9 59.3 55.8

Detroit-Warren-Dearborn, MI -37% 31.2 68.4 72.2

Milwaukee-Waukesha-West Allis, WI -34% 30.8 70.5 76.7

Chattanooga, TN-GA -33% 30.8 70.6 61.4

Buffalo-Cheektowaga-Niagara Falls, NY -32% 31.2 76.0 68.3

Mean of group (weighted by Black

population)

-40% 31.4 66.0 66.1

Areas with the least devaluation of homes in Black neighborhoods

Winston-Salem, NC -4% 30.9 67.9 52.1

Albany-Schenectady-Troy, NY -4% 33.2 78.6 58.0

Hartford-West Hartford-East Hartford, CT -3% 35.2 63.8 5 7.4

Oklahoma City, OK 0% 33.6 58.9 50.1

Tampa-St. Petersburg-Clearwater, FL 1% 30.4 68.7 50.1

Syracuse, NY 1% 30.8 69.6 63.8

Greenville-Anderson-Mauldin, SC 1% 32.0 71.7 40.1

Wichita, KS 4% 31.8 38.3 56.1

Nashville-Davidson-Murfreesboro-Franklin,

10% 31.9 63.4 50.8

Boston-Cambridge-Newton, MA-NH 23% 39.1 51.0 59.9

Mean of group (weighted by Black

population)

7% 33.5 62.5 53.2

THE DEVALUATION OF ASSETS IN BLACK NEIGHBORHOODS 21

We did not include census tract measures of crime

in our analysis because we are not aware of any

comprehensive publicly available data source at the

ZIP code or census tract level for crime incidence.

Using data from U.S. City Open Data Census,

we collected crime data reported by city police

departments for 10 large cities covering each region

of the country: Washington D.C., Baton Rouge, New

Orleans, Boston, Chicago, Durham, Philadelphia, San

Francisco, Las Vegas, and Los Angeles. We classied

assault, rape, murder, and robbery as violent crimes

and thefts, burglaries, and carjacking as property

crimes. The data from these cities were organized at

the incident level and included longitude and latitude

coordinates, which we assigned to Census tracts. This

gave us 3,917 tracts with crime data.

The rst step was to analyze the correlation between

property values and crime measures. We nd that

violent crime predicts signicantly lower property

values and is highly correlated with the Black share of

the population. This makes violent crime a potentially

confounding variable for our analysis, but it is

noteworthy that the correlation with property values

is rather low. Property crimes, by contrast, occur in

census tracts with relatively high home prices, though

the correlation is weak and has almost no correlation

with Black population shares.

To more formally test how including crime would

affect our estimates of devaluation, we include violent

crime in our main models and re-estimate the effect

of Black population shares. Again, the estimates

are calculated within metropolitan areas—that is

controlling for metropolitan xed effects. Though the

results use a much smaller number of census tracts

than the national estimates, we again nd evidence

for signicant devaluation. The magnitude of the

results is very similar to what we nd in the main

models. With the full set of controls, we nd that

Black homes are devalued by 19 percent to 22 percent,

depending on whether we use the Zillow square foot

adjusted price or the census home value estimate.

Moreover, in the census models, violent crime is never

signicantly predictive of property values, and even in

the Zillow models, the relationship is relatively weak.

An increase in 100 violent crimes predicts a decrease

of only 4.9% in property values per square foot, while

controlling for the other factors in our model.

APPENDIX

Correlation between the number of violent and property crimes in a census tract and home value

and Black population shares

Selected U.S. cities, 2016-2017

Source: Authors’ analysis of data from Zillow, 2016 American Community Survey 5-year estimates, and 2017 US City Open

Data Census records

TABLE 1A

Median list

price per sq

foot

Median list

price

Median home

value

Percent

Black in

neighborhood

Violent -0.10 -0.19 -0.21 0.38

Property 0.15 0.10 0.08 0.09

Number of tracts 3,201 3,106 3,740 3,883

BROOKINGS METROPOLITAN POLICY PROGRAM | GALLUP22

Estimates for the devaluation of owner-occupied homes in Black neighborhoods, controlling for

violent crime

Selected U.S. cities, 2016-2017

Source: Authors’ analysis of data from Zillow, 2016 American Community Survey 5-year estimates, and 2017 US City Open

Data Census records

TABLE 2A

Absolute price

comparison

Adjustments

for structural

characteristics of

home

Adjustments

for structural

characteristics

of home and

neighborhood

amenities

Estimated penalty of location in a neighborhood that is 50% Black compared to 0% Black

Census median home value, 2012-2016 -42% -40% -22%

Zillow median list price of houses per square

foot, 2012-2016

-43% -37% -19%

Estimated penalty for every 100 violent crimes per year (values in red are not statistically signifcant)

Census median home value, 2012-2016 -10.6% -4.8% -0.8%

Zillow median list price of houses per square

foot, 2012-2016

-2.9% -7. 3% -4.9%

THE DEVALUATION OF ASSETS IN BLACK NEIGHBORHOODS 23

1 “UPDATE: Chancellor, Campus Leaders Condemn

Post Made by Ole Miss Alumnus, Donor Ed Meek -

The Daily Mississippian | The Daily Mississippian,”

accessed September 28, 2018, http://thedmonline.

com/update-chancellor-campus-leaders-condemn-

post-made-by-ole-miss-alumnus-donor-ed-meek/.

2 “Perceptions: Done to Us, Not With Us:

African American Parent Perceptions of K-12

Education|UNCF,” United Negro College Fund,

accessed September 20, 2018, https://www.uncf.org/

pages/perceptions-done-to-us-not-with-us-african-

american-parent-perceptions-of-k.

3 “Understanding Implicit Bias,” accessed April

5, 2018, http://kirwaninstitute.osu.edu/research/

understanding-implicit-bias/.

4 “Science-of-Equality-111214_web. Pdf,” accessed

September 20, 2018, http://perception.org/wp-

content/uploads/2014/11/Science-of-Equality-111214_

web.pdf.

5 Richard Rothstein, The color of law: A forgotten

history of how our government segregated America.

Live right Publishing, 2017; Douglas S. Massey, and

Nancy A. Denton, American apartheid: Segregation

and the making of the underclass. Harvard University

Press, 1993.

6 David Rusk, “The “Segregation Tax”: The Cost of

Racial Segregation to Black Homeowners (2001).

7 David R. Harris, “’Property values drop when

Blacks move in because…’: Racial and socioeconomic

determinants of neighborhood desirability.” American

Sociological Review 64(3)(1999): 461-79.

8 Caitlin Knowles Myers, “Discrimination and

neighborhood effects: Understanding racial

differentials in US housing prices.” Journal of Urban

Economics 56.2 (2004): 279-302.

9 “Faber_Ellen_2016_Race_and_the_Housing_Cycle.

Pdf,” accessed October 3, 2018, https://wagner.nyu.

edu/les/faculty/publications/Faber_Ellen_2016_

Race_and_the_Housing_Cycle.pdf.

10 “Faber_Ellen_2016_Race_and_the_Housing_Cycle.

Pdf,” accessed October 3, 2018, https://wagner.nyu.

edu/les/faculty/publications/Faber_Ellen_2016_

Race_and_the_Housing_Cycle.pdf.

11 Sun Jung Oh and John Yinger, “What Have We

Learned From Paired Testing in Housing Markets?,”

Cityscape 17, no. 3 (2015): 15–60.

12 “Zillow Research Data.” Zillow. Available at

https://www.zillow.com/research/data/.

13 https://www.udsmapper.org/zcta-crosswalk.cfm;

Missouri Census Data Center, MABLE/Geocorr14,

Version 1.0: Geographic Correspondence Engine.

Web application accessed July 2018 at http://mcdc.

missouri.edu/websas/geocorr14.html.

14 This is based on 22,020 census tracts in U.S.

metropolitan areas.

15 Jonathan Rothwell. “Housing Costs, Zoning,

and Access to High-Scoring Schools.” Brookings

Institution (Washington D.C.: 2012).

16 “EDFacts Data Files.” U.S. Department of

Education. Available at https://www2.ed.gov/about/

inits/ed/edfacts/data-les/index.html.

17 https://www.udsmapper.org/zcta-crosswalk.cfm;

Missouri Census Data Center, MABLE/Geocorr14,

Version 1.0: Geographic Correspondence Engine.

Web application accessed July 2018 at: http://mcdc.

missouri.edu/websas/geocorr14.html.

18 “Smart Location Mapping.” EPA. Available at

https://www.epa.gov/smartgrowth/smart-location-

mapping.

19 Raj Chetty, Nathaniel Hendren, Maggie R. Jones,

and Sonya R. Porter. Race and economic opportunity

in the United States: An intergenerational perspective.

ENDNOTES

BROOKINGS METROPOLITAN POLICY PROGRAM | GALLUP24

No. w24441. National Bureau of Economic Research,

2018. Data are available at http://www.equality-of-

opportunity.org/data/index.html#race.

20 Seth Stephens-Davidowitz, “The cost of racial

animus on a Black candidate: Evidence using Google

search data.” Journal of Public Economics 118 (2014):

26-40.

21 This gure multiplies the median value of homes

listed in Black neighborhoods by the number of units.

It likely understates the true aggregated value since

the median excludes outliers.

22 Jean D. Brender, Juliana A. Maantay, and Jayajit

Chakraborty, “Residential proximity to environmental

hazards and adverse health outcomes.” American

Journal of Public Health 101.S1 (2011): S37-S52.

23 Joe Cortright, “How Walkability Raises Home

Values in U.S. Cities,” CEOs for Cities (2009).

24 These gures rely on the Zillow listing price

estimates. For Census-based estimates, we calculate

a loss of $39,000 per home and $126 billion in

aggregate. The calculation is done as follows: We

take the log of median list price in majority Black

neighborhoods (the ln of $184,000 is .123) and add .23

(the devaluation estimate) and apply the exponential

function, making make the value $232,000. The

difference is our estimate of loss per home. We then

multiply that by the number of homes in majority

Black metropolitan neighborhoods.

25 Raj Chetty, Nathaniel Hendren, Maggie R. Jones,

and Sonya R. Porter. Race and economic opportunity

in the United States: An intergenerational perspective.

No. w24441. National Bureau of Economic Research,

2018.

26 Thomas Shapiro Tatjana Meschede Sam Osoro,

“The Roots of the Widening Racial Wealth Gap:

Explaining the Black-White Economic Divide” (Institute

on Assets and Social Policy, 2013), available at http://

iasp.brandeis.edu/pdfs/2013/Roots_of_Widening_

RWG.pdf.

27 A regression of our home and neighborhood

quality adjusted devaluation measure (using Zillow

list price per square foot) on upward mobility shows a

coefcient of 0.02 and a t-statistic of 3.9, explaining

.12 percent of the variation in a sample of the 113

metro areas with at least one majority Black census

tract and at least one non-Black census tract (<1%

Black population). Limiting the analysis further to the

65 metro areas that are also among the 100 largest

metropolitan areas by 2012–2016 ACS population,

results in a t-stat of 4.1 and a r-squared of .20. Results

are similar using the Census-based devaluation

metric—again adjusted by quality.

THE DEVALUATION OF ASSETS IN BLACK NEIGHBORHOODS 25

BROOKINGS METROPOLITAN POLICY PROGRAM | GALLUP26

Acknowledgements

The Metropolitan Policy Program at Brookings would like to thank the Heinz Endowments and Brookings Mountain

West for their generous support, which contributed to this analysis, and the Metropolitan Council, a network of

business, civic, and philanthropic leaders that provides both nancial and intellectual support for the Program.

The authors would like to thank the following colleagues for providing valuable insights and critiques on early

versions of the analysis and report: Jenny Schuetz; Alan Berube; and Dany Bahar. Thanks to Luisa Zottis for layout

and design.

The Brookings Institution is a nonprot organization devoted to independent research and policy solutions. Its

mission is to conduct high-quality independent research and, based on that research, to provide innovative practical

recommendations for policymakers and the public. The conclusions and recommendations of any Brookings

publication are solely those of its author(s), and do not reect the views of the Institution, its management, or its

other scholars. Brookings is committed to quality, independence, and impact in all of its work. Activities supported

by its donors reect this commitment.

Image credits

Photos via Shutterstock. Icons via Flaticon.com.

THE DEVALUATION OF ASSETS IN BLACK NEIGHBORHOODS 27

About the Metropolitan Policy at Brookings

The Metropolitan Policy Program at Brookings delivers research and solutions to help metropolitan leaders build

an advanced economy that works for all. To learn more, visit brookings.edu/metro.

About Gallup

Gallup delivers analytics and advice to help leaders and organizations solve their most pressing problems.

Combining more than 80 years of experience with its global reach, Gallup knows more about the attitudes and

behaviors of employees, customers, students and citizens than any other organization in the world.

For more information

Andre Perry

David M. Rubenstein Fellow

Metropolitan Policy Program at Brookings

aperry@brookings.edu

Jonathan Rothwell

Senior Economist

Gallup

jonathan_rothw[email protected]om

BROOKINGS METROPOLITAN POLICY PROGRAM | GALLUP28