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Abstract

Gentrification has been viewed by some as a solution to many of the problems facing older central cities. At the same time, many are wary of the potential for gentrification to displace disadvantaged residents. To date, however, surprisingly little reliable evidence has been produced about the magnitude of this problem that could guide planners, policymakers, or community-based organizations. The study described in this article attempts to fill this void by examining residential mobility among disadvantaged households in New York City during the 1990s. We found that rather than rapid displacement, gentrification was associated with slower residential turnover among these households. In New York City, during the 1990s. at least, normal succession appears to be responsible for changes in gentrifying neighborhoods. The article concludes with a discussion of the implications of these findings for planning.
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Gentrification and Displacement New York City in the
1990s
Lance Freeman & Frank Braconi
Published online: 26 Nov 2007.
To cite this article: Lance Freeman & Frank Braconi (2004) Gentrification and Displacement New York City in the 1990s,
Journal of the American Planning Association, 70:1, 39-52, DOI: 10.1080/01944360408976337
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D
uring the past several decades, neighborhoods in a number of cities
have experienced gentrification—a dramatic shift in their demographic
composition toward better educated and more affluent residents. If it
continues, this reurbanization of the middle and professional classes presents a
historic opportunity to reverse central-city decline and to further other widely
accepted societal goals. Many cities face fiscal problems because higher income
households have migrated to the suburbs and disadvantaged (poor and less
educated) households are concentrated in the urban core. These problems could
be ameliorated if wealthier households increasingly settle within central cities,
raising taxable income and property values and stimulating retail activity and
sales tax proceeds (Miesowski & Mills,
).
If it proceeds without widespread displacement, gentrification also offers
the opportunity to increase socioeconomic, racial, and ethnic integration. An
increasing middle class in central-city neighborhoods, to the degree that it in-
cludes White households, could help desegregate urban areas and, eventually,
their school districts (Lee et al.,
). Moreover, the concentrated poverty that
is
thought to diminish the life chances of the poor might be reduced if middle-
income residents settle in formerly depressed neighborhoods (Wilson,
).
In addition, existing residents of inner-city neighborhoods could benefit
directly from gentrifi
cation if it brings new housing investment and stimulates
additional retail and cultural services. Furthermore, the infusion of residents with
more political influence may help the community to procure better public serv-
ices. The employment prospects of low-income residents could also be enhanced
if gentrification contributes to local job creation or if informal job information
networks are enriched by an infl
ux of working residents.
Despite these potential benefits, local populations and community activists
often oppose the gentrification of urban neighborhoods. Although the rhetoric of
resistance sometimes expresses class and racial resentments, the principal concern
is usually that lower-income households are vulnerable to displacement resulting
from redevelopment projects or rising rents. A common response is for activists
to pressure local government for more affordable housing development, to orga
-
nize community development corporations for that end, or to establish service
programs that provide legal or financial assistance to renters who face eviction. In
Gentrification has been viewed by some
a
s a solution to many of the problems
facing older central cities. At the same
time, many are wary of the potential for
gentrification to displace disadvantaged
residents. To date, however, surprisingly
little reliable evidence has been produced
about the magnitude of this problem
that could guide planners, policymakers,
or community-based organizations. The
study described in this article attempts to
fill this void by examining residential
mobility among disadvantaged house-
holds in New York City during the
s. We found that rather than rapid
displacement, gentrification was associ-
ated with slower residential turnover
among these households. In New York
City, during the
s at least, normal
succession appears to be responsible for
changes in gentrifying neighborhoods.
The article concludes with a discussion
of the implications of these findings for
planning.
Lance Freeman is an assistant professor
in the Urban Planning Department of
the Graduate School of Architecture,
Planning, and Preservation at Columbia
University. His research interests are
housing policy, neighborhood change,
the social consequences of sprawl, and
urban poverty. He is the author of
several articles on these subjects.
Frank
Braconi
is the executive director of New
York City’s Citizen Housing and
Planning Council.
Journal of the American Planning Association,
Vol.
, No. , Winter .
© American Planning Association, Chicago, IL.
Gentrification and
Displacement
New York City in the 1990s
Lance Freeman and Frank Braconi
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some cases, however, opponents have sought to block
community improvement projects through political pres-
sure or legal challenge (Lin,
; Robinson, ).
The degree to which government policies should
actively promote gentrification in order to achieve fiscal
and societal goals is a policy calculation that should con-
sider adverse consequences such as displacement. Conse-
quently, it is imperative that social scientists and policy
analysts provide better quantitative evidence of the extent
and implications of displacement and of the effectiveness
of strategies intended to mitigate it.
Background and Prior Research on
Displacement
Scholars have been drawn to the phenomenon of
gentrification since it first emerged during the
s as a
major force shaping the fate of urban neighborhoods. They
first sought to document whether inner-city revitalization
was actually occurring and if so, to what extent (Baldassare,
; Clay, ; James, ; Lipton, ; National
Urban Coalition,
; Sumka, ). The studies were
consistent in showing that although gentrification was a
small part of the overall scheme of metropolitan shifts, it
was indeed a reality in many older central-city communi
-
ties during the
s. With gentrification’s existence docu-
mented, theorists debated about its origins and its conse-
quences for cities. What emerged from this debate was
recognition of the importance of several factors as precon-
ditions for gentrification, including changing demograph-
ics and lifestyle preferences, professionals clustering in
cities to provide services for the gentrifiers, and a history of
disinvestment that created ripe opportunities for reinvest
-
ment in certain neighborhoods (Beauregard,
; Ham-
nett,
; Ley, ; Rose, ; Smith, ).
Although it did not signal the demise of gentrification,
as some observers claimed, the recession of the late
s
and early
s did reverse or at least slow the process in
many cities (Lees & Bondi,
; Smith & Defi
lippis,
). The economic boom of the s, however, erased
any lingering doubts that gentrification would be a long-
lasting phenomenon. The boom, coupled with shifts in the
housing finance industry that were favorable to low-in-
come neighborhoods and reinvestment in federal low-
income housing through the HOPE VI program, created
conditions that expanded the process of gentrification in
many cities (Wyly & Hammel,
). To be sure, gentrifi-
cation still affected only a small share of all U.S. neighbor-
hoods (Kasarda et al.,
), but this share was prominent
enough to reawaken old fears about displacement. In
response, community-oriented organizations set up Web
sites to dampen its impacts on the poor (PolicyLink,
),
and even popular magazines addressed the displacement
perils of gentrification, referring to it is as “hood snatch-
ing” (Montgomery,
, pp. ). Thus, in spite of all
the promise for central-city rebirth associated with gentrifi-
cation, for many, the assumption that it causes widespread
displacement makes it a dirty word.
Prior Research and Its Limitations
Given the fears of displacement that have long been
associated with gentrification, it is not surprising that
scholars have attempted to define and measure this rela-
tionship. Researchers have generally used two approaches
to assess the degree of displacement resulting from gentri-
fication: (
) studies of succession that examine how the
socioeconomic characteristics of in-movers differ from
those of out-movers and (
) surveys that ask residents why
they moved from their former residence.
Succession Studies. Succession studies examine
whether individuals moving into a housing unit are of
higher socioeconomic status than those moving out, as
would be expected if gentrification were occurring. By
focusing on specifi
c locales, one can get a sense of the
extent to which gentrification is occurring. Using this
approach in a study of nine Midwestern cities, Henig
(
) found that the majority of the neighborhoods lost
professional households, and those that experienced a net
increase did not experience a concomitant decrease in blue-
collar/service workers, households headed by females, or
the elderly. Henig concluded that although displacement
may be a problem in certain neighborhoods, it was proba
-
bly not as widespread as the popular wisdom of the time
perceived it to be.
Spain et al. (
) performed a similar analysis using
American Housing Survey data for
. If gentrifica-
tion is associated with the socioeconomic and demographic
transformation of neighborhoods, then middle-income
households, who are often White, should increasingly
occupy the units vacated by lower-income households,
who are often Black. The results of their analysis were
consistent with an increase in gentrification during the
decade. Because Spain and her colleagues did not stratify
their analysis at a finer geographic level than central city/
suburb, however, it is impossible to know if the White-to-
Black or poor-to-middle-income successions were concen-
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trated in gentrifying neighborhoods. Moreover, succession
studies can only help to define the upper boundary of
displacement; they cannot be used to determine whether
housing or neighborhood transitions occurred through the
induced departure of low-income households or through
normal housing turnover and succession, because they do
not consider other reasons that households might move.
Succession studies can thus verify that the process of gen-
trification is underway, but without additional informa-
tion, they cannot demonstrate how that process occurs.
Resident Surveys. Studies based on asking respon-
dents why they moved generally use some variation of
Grier and Grier’s (
) definition of displacement:
. . . when any household is forced to move from its
residence by conditions which affect the dwelling or its
immediate surroundings, and;
. Are beyond the household’s reasonable ability to
control or prevent;
. Occur despite the household’s having met all previ-
ously imposed conditions of occupancy; and
. Make continued occupancy by that household
impossible, hazardous, or unaffordable. (p.
)
Newman and Owen (
) used this definition,
amended to exclude natural disasters. They estimated a
displacement rate of approximately
% for the entire U.S.,
based on data from the Panel Study of Income Dynamics.
Lee and Hodge (
) used a somewhat more restric-
tive defi
nition, limiting it to those displaced by “private
action including abandonment, demolition, eviction,
condominium conversion, mortgage default and the termi-
nation of a rental contract” (p.
). They estimated a
displacement rate of
.% for the entire U.S., based on
data from the American Housing Survey.
Out-Movers Study. The biggest problem with studies
that focus retrospectively on motives for moving is that
they typically fail to identify the location of the respon-
dent’s former residence. Consequently, it is impossible to
determine how much, if any, of the displacement observed
is due to gentrifi
cation.
Schill and Nathan (
) attempted to solve this prob-
lem by focusing on gentrifying neighborhoods and the
individuals moving out of them with a narrow defi
nition
of displacement that could be directly attributable to
gentrification. They then used local sources and data from
the R.L. Polk Company to track down residents who had
moved from each of nine neighborhoods in five mid-sized
cities in the previous year.
In the sample of out-movers from gentrifying neigh-
borhoods, Schill and Nathan determined that
% were
displaced. The principal drawback to this method was that
no baseline displacement rate could be estimated. Conse-
quently, one cannot compare displacement rates in gentri-
fying and nongentrifying areas. Moreover, there is no
measure of the relative mobility of households in different
types of neighborhoods, so a higher percentage of moves
from gentrifying areas may be displacements while the
aggregate number of displacements from those neighbor-
hoods may be the same or lower.
Comparison Study. In order to determine whether
gentrification causes an increased number of disadvantaged
households to be displaced, there must be a basis of com
-
parison to neighborhoods in which gentrification is not
occurring. In a recent study of the effects of gentrification
on the disadvantaged in Boston, Vigdor (
) attempted
to do just that by evaluating the mobility rates of both the
poor and the less-educated households in gentrifying and
nongentrifying areas. Using the American Housing Survey,
which after  divides the Boston metropolitan area into
 geographic zones, Vigdor evaluated exits from housing
units between
 and . Two classifi
cations of gentri-
fying zones were identified (one narrower than the other)
and probit regressions were estimated. Controls were
included for householder age, income, tenure, whether a
unit had rent regulation, and several other household and
housing characteristics.
Using his narrower classification of gentrifying zones
and defi
ning disadvantaged households as those in which
the head had no post-secondary education, Vigdor found
that gentrification increased the exit rate from housing
units overall but decreased it for less-educated households,
who were significantly more likely to remain in their
housing units in gentrifying areas than those elsewhere in
the metropolitan area. Although Vigdor could not deter-
mine the reasons for exits from housing units, he con
-
cluded that the results provide “compelling evidence of the
importance of considering baseline exit rates in any study
of residential displacement” (p.
).
Summary. Considering the concern that residential
displacement generates in gentrifying or potentially gentri-
fying urban neighborhoods, the research record on dis-
placement is surprisingly inconclusive. Most of it suggests
that a relatively small percentage of housing moves can be
attributed to displacement, and there is little evidence that
implicates neighborhood gentrification in the process. The
research of Schill and Nathan () does indicate that the
proportion of housing exits in gentrifying areas that could
F
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be considered displacement is fairly high, but Vigdor’s
(
) results indicate that overall exits of disadvantaged
households from gentrifying areas are actually below those
elsewhere. Although those results are not inherently con-
tradictory, the disparity in the time and place of the two
studies suggests that more research is necessary before those
countervailing patterns can be considered characteristic of
the gentrification process.
Displacement in New York City,
1991–1999
In this study, we focused on New York City during
the
s. The city provides a prime laboratory to study
the patterns and processes of gentrification, insofar as its
size and economic vitality have produced several distinct
areas of gentrification activity. Following a regional reces-
sion that bottomed out in , the city experienced rapid
economic growth and strong job creation for the remain-
der of the decade. Job creation and income growth were
particularly strong in the creative and information process
-
ing sectors of the economy, including fi
nance, insurance,
and real estate; communications; higher education; and
business services. Growth in those economic sectors is
often considered a prerequisite for gentrification, as their
businesses tend to prefer central business district locations
and employ workers who have educational and other
characteristics that make them predisposed to urban life-
styles and residence. A large renter population and the
presence of rent regulation also permit large-sample statis-
tical analysis of renter mobility and displacement and an
evaluation of the role rent regulation may play in mitigat-
ing it.
It is well known that New York City has had some
form of rent regulation in place continuously since
;
it
is less widely appreciated that the city has transitioned
from the earlier, rigid form of regulation known as rent
control to a more flexible, “second-generation” form known
as rent
stabilization. Currently, there are about ,
controlled rental units and . million stabilized rental
units—representing about
% and % of the rental stock,
respectively (Lee,
). Under rent stabilization, permissi-
ble rent increases on
-year and -year leases are deter
-
mined annually by a nine-member panel composed of
public, tenant, and owner representatives. Permissible rent
increases for occupied units generally correspond to the
rate of inflation in operating costs; vacant units are per-
mitted to rent at higher prices according to a complex
“vacancy allowance” formula. In addition, the rents of
many other units are regulated through a variety of federal
and state housing assistance programs.
Our study of gentrification in New York City was
facilitated by the availability of the New York City Hous-
ing and Vacancy Survey (NYCHVS), a representative
sample of approximately , housing units, of which
about
% are rental units. It is conducted every years by
the Census Bureau for New York City in accordance with
the City’s rent regulation guidelines. For this analysis, we
used the
,
, , and  NYCHVS longitudinal
data files. Although the chief purpose of the survey is
to collect data regarding New York City’s vacancy rate, the
NYCHVS also collects a variety of other housing, socio
-
economic, and demographic data that are useful for study-
ing gentrification.
Methodology
To discern how gentrification is related to displace-
ment, we examined the relationship between residence in a
gentrifying neighborhood and residential mobility among
disadvantaged households. If gentrifi
cation increases dis
-
placement, all other things being equal, we should observe
higher mobility rates among disadvantaged households
residing in gentrifying neighborhoods than among those
residing elsewhere in the city.
The longitudinal feature of the NYCHVS facilitates an
analysis of mobility patterns. The same panel of dwelling
units is generally visited for each triennial survey, with
some alterations to account for additions and losses to
the stock and for reweighting to account for population
changes. Overall, about
% of the observations in the
 survey were linked to observations of the same dwell-
ing in previous surveys. Within that constant frame of
dwelling units, the resident households may have changed,
but their year of initial occupancy is provided. Those
longitudinal features of the survey allowed us to identify
which dwelling units had new occupants as of each survey
and to recover from earlier surveys a significant amount of
information about the previous occupant household. Using
this procedure, we were also able to analyze exits from
housing units on a neighborhood basis.
Selection Criteria
Neighborhoods are defined as the  subborough areas
coded in the NYCHVS data. These subborough areas
correspond closely to New York City’s Community Board
Districts, the smallest unit of municipal government,
which were initially drawn to represent coherent geo-
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graphic, demographic, and political entities. In , they
consisted of approximately
, households each. Al-
though this number is much larger than what is typically
considered a neighborhood in social science research, the
density of New York City is unusually high, and most of
these areas represent well-known sections of the city, such
as the Upper East Side, Brooklyn Heights, or Flushing.
Based on our familiarity with recent trends in neigh-
borhood change, we classified the subboroughs of Chelsea,
Harlem, the Lower East Side, and Morningside Heights in
Manhattan and Fort Greene, Park Slope, and Williams-
burg in Brooklyn as gentrifying neighborhoods. Figure
shows the locations of these neighborhoods. Figure
illustrates how gentrifying neighborhoods changed during
the
s in contrast to other New York neighborhoods:
The proportion of Whites in gentrifying neighborhoods
increased even as the proportion in the rest of the city
declined. Moreover, average monthly rent, educational
attainment, and median income were also rising faster.
These changes are consistent with what would be expected
for gentrifying neighborhoods—relative increases in socio-
economic status—and lend support to our designation of
these neighborhoods as gentrifying.
To determine if a household subsequently moved, we
first identified housing units that had a new occupant in
year t. If so, we considered the occupant of that housing
unit in year t
as having moved.
We then used character-
istics of the occupants of the unit in year t
as predictors
of mobility. Consequently, we observed residential mobil-
ity between
 and ,  and , and  and
.
We used two indicators of disadvantage: the house
-
hold’s income level and the household head’s educational
level. A disadvantaged household had an income below the
federal poverty line in the year prior to the survey or the
head lacked a college degree. While income level is more
F
reeman and Braconi: Gentrification and Displacement
Figure . Gentrifying neighborhoods in New York City, .
Downloaded by [Columbia University] at 07:05 17 September 2014
directly related to rent-paying ability, educational status is
not as subject to fluctuation and thus is a more stable
indicator of socioeconomic status.
Controls
To control for the possibility that disadvantaged
households in gentrifying neighborhoods differ systemati-
cally in a manner that makes them less likely to move, we
developed a multivariate model of residential mobility.
This model is based on the life-cycle model of housing
consumption, which posits that life-cycle events typically
trigger consumption/needs discrepancies that lead to a
decision to move (Rossi, ; Speare, ). For example,
marriage is a major life-cycle event likely to trigger a move
by at least one of the partners. We used this theoretical
framework to guide us in the development of a logistic
regression model
that predicts the likelihood of someone
moving.
Using the life-cycle framework, we controlled for age,
marital status, and the presence of children in our model of
residential mobility. Other demographic control variables
included race, gender, income, employment status, and
J
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Figure . Changes in four key socioeconomic indicators, .
Racial Composition Rent
   
Education    
Income
   
   
Neighborhood Type
Gentrifying
Other
White
(
%)
College
Graduate
(%)
Average
M
onthly
Rent
(%)
Average
Annual
Income
(%)






















,
,
,
,
,
,
Downloaded by [Columbia University] at 07:05 17 September 2014
educational attainment. We also controlled for housing
unit characteristics likely to be associated with mobility,
including monthly rent, length of tenure, overcrowding,
the respondent’s rating of their neighborhood’s physical
conditions, and the number of maintenance deficiencies
in their unit.
As access to both subsidized housing units and rent-
regulated units occurs on a first-come, first-served basis, a
model of residential mobility should also take into consid-
eration how the rent regulation/housing subsidy status of
the dwelling unit might affect a household’s decision to
move. Households residing in regulated or subsidized units
are likely to think twice before moving, cognizant of the
scarcity of other available units with mechanisms for
keeping rent affordable and the high cost of housing in the
unregulated private sector. With this in mind, we excluded
from our analysis both residents of public housing and
residents of units acquired by the City because the owners
did not pay their taxes. We did control for residence in a
rent-regulated unit, including those regulated under the
State of New York Mitchell Llama Program
and under
U.S. Department of Housing and Urban Development
programs.
Our rationale for including these controls is
that gentrification might increase pressure on landlords to
“encourage” residents of rent-regulated units to leave and
that other types of subsidized housing typically expire after
a given period—say  or  years. Table shows a full list
of the variables included in the analysis and their descrip-
tive statistics.
Results of Multivariate Analyses
Gentrification as Independent Variable
Table presents the results of our multivariate analy-
ses. It shows that after controlling for all of the factors
described above, poor households residing in one of the
seven gentrifying neighborhoods were found to be
% less
likely to move than poor households residing elsewhere
(see second and third columns of Table
). When we
controlled for the factors listed above and limited our
sample to respondents who lacked a
-year college degree,
disadvantaged households residing in one of these neigh
-
borhoods were still
% less likely to move than their
counterparts residing elsewhere (see fourth and fifth col-
umns of Table
).
The results pertaining to the rent regulation variables
are also suggestive. The coefficient on rent control indi-
cates that occupants of such units exit at a much higher
rate than occupants of unregulated units. This is probably
because under the City’s rent regulations, only apartments
that have been continuously occupied since
 by the
same tenant (or one with legal rights to succession) are
“controlled.” Consequently, elderly tenants, who are more
apt to exit only when they retire, are institutionalized,
or die, occupy controlled units disproportionately. Rent
stabilization is by far the more common form of rent
regulation in New York City. Our results indicate that
poor tenants in such units are insignificantly less likely to
exit than those in unregulated units. Rent stabilization
does appear, however, to substantially reduce the odds that
a less-educated household will move from their dwelling
unit during any given time period. These results are consis-
tent with conventional wisdom in New York, which holds
that rent regulation is a program that primarily benefits the
lower middle class rather than the very poor. In many of
the city’s poorest neighborhoods, regulated rents are com-
parable to market rents, and hence are superfluous to
keeping rents affordable. We also tested in our regressions
a variable interacting residence in a rent-regulated unit and
in a gentrifying area and found that it was not signifi
cant.
This indicates that while rent regulation tends to decrease
tenant mobility, it does not do so more in gentrifying areas
than in others.
Rent Inflation as Independent Variable
Although most knowledgeable observers would concur
with our designations of the seven gentrifying neighbor
-
hoods, it is possible that we have erred in our categoriza-
tion. An alternative approach is simply to measure the rate
of increase in neighborhood market rents, on the assump-
tion that the market appropriately values the increasing or
decreasing desirability of residential areas. After all, it is the
notion that gentrification leads to increased demand in a
neighborhood, and consequently to rising rents, that is
thought to spur displacement.
Thus, as a further robustness check, we examined
the relationship between the average rate of rent inflation
among unregulated units in a neighborhood and the
likelihood that a disadvantaged household in that neigh-
borhood would move. Because of New York City’s large
rent-regulated housing stock, we use the rate of rent in
-
crease only for unregulated units to proxy for the degree
of gentrification in a neighborhood. To the extent that
gentrification causes rent inflation, and rising rents induce
displacement, we would expect a positive relationship
between rent inflation and the likelihood of moving.
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Non-college-graduate
Poor households head of household
Gentrified Other Gentrified Other
Variable neighborhoods neighborhoods neighborhoods neighborhoods
Moved .%** .% .%*** .%
Monthly rent $
.*** $. $.*** $.
Average rent increase  .%*** .% .%*** .%
Years in current residence
.*** . .*** .
Rent-stabilized unit
a
.%*** .% .%*** .%
Rent-controlled unit
a
.%*** .% .%*** .%
Other regulated unit
a
.%* .% .%*** .%
No. maintenance deficiencies
.*** . .%*** .
Overcrowded unit .%*** .% .%* .%
Seriously overcrowded unit
.%* .% .%*** .%
Native born .%** .% .%*** .%
Black
.% .% .%* .%
Hispanic
.% .% .%* .%
Asian
.%*** .% .%*** .%
Other .
%.%.%.%
Age (years) .** . .*** .
Male .%*** .% .%* .%
Married .%** .% .%*** .%
Has child
.%*** .% .%*** .%
High school graduate .%*** .% .%*** .%
Some college
.% .% .% .%
College graduate
.% .%—
Employed
.% .% .%** .%
Income $
,.* $,. $,.*** $,.
Neighborhood Rating
b
Excellent .%** .% .%*** .%
Good
.%*** .% .%*** .%
Fair
.%*** .% .%*** .%
N  , , ,
a. Reference category: unregulated unit
b. Reference category: poor
*
p < .10 ** p < .05 *** p < .01
Table . Descriptive statistics for variables used in regressions.
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Non-college-graduate
Poor households head of household
Variable Odds ratio p value Odds ratio p value
Monthly rent . .*** . .***
Residence in gentrified neighborhood .
 .** . .***
Years in current residence .
 .*** . .***
Rent-stabilized unit
a
. . . .***
Rent-controlled unit
a
. . . .***
Other regulated unit
a
. . . .***
No. maintenance deficiencies
. . . .
Overcrowded unit . .** . .*
Seriously overcrowded unit
. . . .*
Native born . . . .
Black . . . .
Hispanic . . . .
Asian . . . .
Other race . . . .
Age . .*** . .***
Age squared
. .*** . .***
Male
. . . .***
Married . . . .***
Has child .
 .*** . .**
High school graduate . .* —- —-
Some college .
 . —- —-
College graduate
. .* —- —-
Employed
. . . .
Annual Income . . . .*
Neighborhood Rating
b
Excellent . . . .**
Good .
 . . .***
Fair .
 . . .*
Year =  . .*** . .***
Year =
 . . . .***
Wald
χ
2
. .*** . .***
Summary statistics
% correct predictions % %
N
, ,
a. Reference category: unregulated unit
b. Reference category: poor
*
p < .10 ** p < .05 *** p < .01
Table . Logistic regression model using gentrification as independent variable.
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We found that increases in rent are indeed related to
the probability of a household moving. But as was the case
with the seven gentrifying neighborhoods, these increases
were associated with a
lower probability of moving rather
than a higher one. Table
illustrates the results of our
logistic regression analysis predicting if a household would
move, using the rate of rent inflation as the independent
variable.
The first and third columns show that the probability
of a poor or less-educated household moving from a unit
declines as the rate of rent inflation in the neighborhood
increases. For poor households, a
% increase in rent
inflation is associated with a
% decrease in the odds of
moving. The same is true for households whose head lacks
a college degree. Moreover, this relationship persists even
when other factors associated with residential mobility are
controlled for.
As a final robustness check, we tested whether rent
inflation had a stronger effect on disadvantaged households
in low-rent neighborhoods. These are neighborhoods
where rent inflation might be especially burdensome and
most associated with displacement. To test this possibility,
we classifi
ed neighborhoods with rents below the citywide
median in  as low-rent and neighborhoods with rents
above the citywide median in
 as high-rent, using a
dummy variable. We then interacted this dummy variable
with the rate of rent infl
ation, measured as described
above. If residence in a low-rent neighborhood renders
disadvantaged households especially sensitive to rent infla-
tion, then this interaction term should be statistically
significant and positive. For the sake of brevity, we do not
report the results here; we only note that the interaction
term was not statistically significant. This suggests that
the effect of rent inflation on mobility was invariant with
regard to the average rent levels in the neighborhood at the
beginning of the decade. The relationship between residen-
tial mobility and gentrifi
cation thus appears robust across
different measures of gentrification.
Rethinking the Gentrification Process
Gentrifi
cation has become one of the more controver
-
sial issues for planners and others who work in low-income
communities. For reasons described in the introduction,
gentrifi
cation has both boosters and detractors. The latter
are motivated primarily by fears of displacement. Gentrifi-
cation has typically been depicted as a process of higher
socioeconomic households displacing disadvantaged house-
holds. Indeed, some have defined gentrification as this type
of displacement (Marcuse,
). The assumption behind
this view is that displacement is the principal mechanism
through which gentrification changes the socioeconomic
character of a neighborhood. The results presented here, in
conjunction with Vigdor’s (
) analysis, which produced
similar findings, suggest that a rethinking of the gentrifica-
tion process is in order. Insofar as many of the other rea-
sons people change residence (marriage or divorce, change
of job, want a bigger unit, want to own, etc.) would not be
expected to diminish as their neighborhood gentrifies, the
reduced mobility rates we find in gentrifying neighbor-
hoods are inconsistent with a process dependent on the
massive displacement of disadvantaged residents. Rather,
demographic change appears to occur primarily through
normal housing succession and may even be slowed by a
below-normal rate of exit by existing residents.
It is possible that the lower rates of residential mobility
we observed among poor and less-educated people in
gentrifying neighborhoods are due entirely to a lower rate
of moves
within the neighborhood, because of a lack of
affordable housing alternatives in nearby, familiar loca-
tions. However, in a separate analysis not presented here,
we identifi
ed renters who had been displaced as those who
had moved because () they wanted a less expensive resi
-
dence and/or had difficulty paying their previous rent,
(
) they experienced landlord harassment, or () their units
were converted to condominiums or coops but they did
not have the desire or means to stay.
Those displaced
renters were no less likely to be found residing in gentrify-
ing neighborhoods than in nongentrifying ones. This sug-
gests that for residents who seek to lower their rent bills,
trade-down options exist even within gentrifying neighbor-
hoods. In any event, a claim that intraneighborhood mo-
bility is reduced for low-income residents in gentrifying
neighborhoods is fundamentally different from a claim
that they will be displaced from their existing homes.
An Alternative Interpretation
If the lower mobility rates in gentrifying areas are not a
statistical illusion, what might be causing them? The most
plausible interpretation may also be the simplest: As neigh-
borhoods gentrify, they also improve in many ways that
may be appreciated as much by their disadvantaged resi-
dents as by their more affluent ones. To the extent that
gentrifi
cation is associated not only with an infl
ux of
higher-income households but also with better retail and
public services, safer streets, more job opportunities, and
improvements in the built environment, disadvantaged
households may have less reason to change residences in
search of a better living environment. Indeed, the strong
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F
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Non-college-graduate
Poor households head of household
Variable Odds ratio p value Odds ratio p value
Monthly rent . .*** . .***
Rate of rent inflation in neighborhood .
 .*** . .***
Years in current residence .
 .*** . .***
Rent-stabilized unit
a
. . . .**
Rent-controlled unit
a
. .* . .***
Other regulated unit
a
. . . .***
No. maintenance deficiencies
. . . .
Overcrowded unit . .** . .*
Seriously overcrowded unit
. . . .*
Native born . . . .
Black . . . .
Hispanic . . . .
Asian . . . .
Other race . . . .
Age . .*** . .***
Age squared
. .*** . .***
Male
. . . .***
Married . . . .***
Has child .
 .*** . .***
High school graduate . .* —- —-
Some college .
 . —- —-
College graduate
. .* —- —-
Employed
. . . .
Annual Income . . . .*
Neighborhood Rating
b
Excellent . . . .**
Good .
 . . .***
Fair .
 . . .*
Year- . .*** . .***
Year-
 . . . .***
Wald
χ
2
. .*** . .***
Summary statistics
% correct predictions % %
N
, ,
a. Reference category: unregulated unit
b. Reference category: poor
*
p < .10 ** p < .05 *** p < .01
Table . Logistic regression model using average rate of rent inflation as independent variable.
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association between a resident’s rating of their neighbor-
hood and their propensity to remain in place is demon-
strated by the results of the logistic regressions in Tables
and . Although the NYCHVS questionnaire asks respon-
dents to rate only the
physical condition of their neighbor-
hood, the strong correlation between a neighborhood’s
physical and social conditions permits us to interpret this
rating as a proxy for overall neighborhood quality. Al-
though the coefficients are statistically significant only for
the less-educated sample, mobility appears to decrease as
neighborhood quality increases for both categories of
disadvantaged residents.
A neighborhood can gentrify without direct displace-
ment as long as in-movers are of a higher socioeconomic
status than out-movers. Given the typical pattern of low-
income renter mobility in New York City, a neighborhood
could go from a
% poverty population to % in as few
as
 years without any displacement whatsoever, provid-
ing that all vacated units are rented by non-poor house-
holds. Even if disadvantaged households who reside in
gentrifying neighborhoods are less likely to move, these
neighborhoods can still undergo demographic transforma
-
tions if the households moving into vacated units are of a
higher socioeconomic status than those leaving. Indeed,
that appears to be the case in the gentrifying neighbor-
hoods in New York City from
. Table shows
that households moving into units in gentrifying neighbor
-
hoods had substantially higher incomes, higher levels of
educational attainment, and lower poverty rates than the
previous residents of those units. Because the NYCHVS
does not allow us to determine where in-movers are com-
ing from, we cannot be sure that all of these in-movers are
indeed coming from outside of the neighborhood. While
it appears that disadvantaged households are less likely to
move away if they live in a gentrifying neighborhood, they
are also less likely to move into one if they do not already
live there.
Implications for Planning
We believe our results have implications for how we
understand the process of gentrification, what gentrifica-
tion may mean to disadvantaged households, and how
housing policy should be crafted to address concerns about
gentrification. We discuss each of these below.
If our speculation that many disadvantaged households
would prefer to stay in their neighborhoods as they gen-
trify is correct, this is all the more reason to fashion hous-
ing policy to mitigate some of the pressures of displace-
ment. For although our results imply that the amount of
displacement occurring in gentrifying areas may be no
worse than in other parts of the city, this does not mean
that no one is being displaced. In addition, those disadvan-
taged households staying in gentrifying neighborhoods
may be devoting a substantial portion of their income for
improved neighborhood conditions. Indeed, data from the
NYCHVS shows that the average rent burden for poor
households living in gentrifying neighborhoods was
%
during the study period, in contrast to a lower, although
still problematic,
% for poor households living outside of
gentrifying neighborhoods.
Furthermore, disadvantaged households who wish to
move into these neighborhoods may not be able to find
an affordable unit, as may disadvantaged households in
gentrifying neighborhoods who wish to move within their
neighborhood. Moreover, if gentrification occurs on a
sufficiently wide scale, it could result in a gradual shrinking
of the pool of low-cost housing available in a metropolitan
area. For these reasons, gentrification can still exacerbate
the housing problems of the poor, even if widespread
displacement is not occurring.
Ironically, two of the most maligned housing policies,
rent regulation and public housing, may have a certain
logic in the context of gentrification. We have already
shown that rent regulation reduces housing turnover
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Average income College graduate Poverty rate
In-movers $,* %* %*
Current residents $
, % %
* p < .01
Table . Characteristics of in-movers and current residents.
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among disadvantaged renters, although no more so in
gentrifying areas than elsewhere. It may be equally impor-
tant in moderating the rent burdens of those who do stay
in their apartments, however. Our tabulations, for exam-
ple, show that between  and , rents for unregu-
lated apartments in gentrifying neighborhoods of New
York City increased by an average of
.%. For rent-
stabilized apartments, the corresponding increase was
.%. More research is necessary, however, to determine
how rent regulations affect the rent burdens of poor
families already living in gentrifying areas and how those
rent burdens might change if regulations were not in
place.
Public housing, often criticized for anchoring the poor
to declining neighborhoods, may also have the advantage
of anchoring them to gentrifying neighborhoods. The
households probably least at risk of being displaced in
neighborhoods like Harlem and the Lower East Side of
Manhattan are those in public housing; they are insulated
from rent competition with more affluent households be-
cause of public housing’s income eligibility rules. Tenant-
based housing assistance offers no such assurances if mar
-
ket rents in a neighborhood rise above fair market rent
levels. Likewise, owners of Low Income Housing Tax
Credit (LIHTC) developments and other types of private,
assisted housing may be quicker to opt out of the program
at the end of the obligatory time period if the surrounding
neighborhood is undergoing gentrification. This is an
important consideration that should be kept in mind,
especially if gentrifi
cation becomes a more widespread
phenomenon in urban areas.
Conclusion
Our analysis indicates that rather than speeding up the
departure of low-income residents through displacement,
neighborhood gentrification in New York City was actually
associated with a lower propensity of disadvantaged house-
holds to move. These findings suggest that normal housing
succession is the primary channel through which neighbor
-
hood change occurs. Indeed, housing turnover may actu-
ally be slowed by the reduced mobility rates of lower-
income and less-educated households. The most plausible
explanation for this surprising finding is that gentrification
brings with it neighborhood improvements that are valued
by disadvantaged households, and they consequently make
greater efforts to remain in their dwelling units, even if the
proportion of their income devoted to rent rises.
The results of this study and Vigdor’s analysis suggest
that some degree of gentrification can occur without rapid
and massive displacement of disadvantaged households.
Insofar as gentrification in these studies does not appear to
cause the widespread dislocation of the disadvantaged that
some observers have claimed and it may also help to pro-
mote important fiscal and social goals, municipal govern-
ments may become more inclined to pursue policies explic-
itly geared to promoting it. Before pursuing that course,
however, it would be wise for planners and policymakers to
gain a better understanding of whether the effects we have
identified would be likely to occur under different scenar-
ios and under what circumstances, if any, widespread
displacement could be a problem.
Even though urban gentrification may provide benefits
to disadvantaged populations, it may also create adverse
effects that public policies should seek to mitigate. Our
results indicate that rent regulation can promote residential
stability for disadvantaged households, but those effects do
not seem to be consistent across all subgroups of the disad-
vantaged population. More research is needed to evaluate
the usefulness of rent regulation in reducing displacement
and moderating the rent burdens of disadvantaged house
-
holds in gentrifying neighborhoods. Other traditional
housing assistance programs, such as public housing and
Section
rent subsidies, also need to be re-evaluated in the
context of urban gentrifi
cation, rather than in the context
of urban decline.
Notes
. The NYCHVS was conducted in  instead of  to avoid
overlapping with the decennial census.
. t in the case of the  interval.
. Because each household contributed more than one observation to
the dataset (one for each year observed), it was necessary to correct our
estimates for possible dependence among observations. Although our
models include numerous statistical controls, observations from the
same household are still unlikely to be independent, and consequently
the error terms correlated as well. To address this possibility, we esti-
mated our models using a random effects approach (Conway,
).
. The Mitchell Llama Program provides housing primarily for middle-
income tenants.
. This would include units developed under Section New Construc-
tion, Substantial and Moderate Rehabilitation, and other subsidized
construction and rehabilitation programs.
. We did not use this approach to link gentrification with displacement
because the NYCHVS does not allow us to identify the neighborhood
of origin. Thus, we can categorize some recent movers as displaced, but
we cannot say if it was due to gentrification because we do not know
from which neighborhood they came.
F
reeman and Braconi: Gentrification and Displacement
Downloaded by [Columbia University] at 07:05 17 September 2014
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