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Issue 4 | 2016

Introducing, understanding, and using
the ICI 300 Peer Cities Identification Tool
ALSO IN THIS ISSUE

Maintaining housing affordability:
The role of university partnerships
in Iowa City and other communities

Published by the Community Development and Policy Studies Division of the Federal Reserve Bank of Chicago

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Advisor
Alicia Williams
Managing Editor
Michael V. Berry
Assistant Editor
Mary Jo Cannistra

Contributing Editors
Jeremiah Boyle
Emily Engel
Steven W. Kuehl
Susan Longworth
Robin Newberger

Senior Designer
Brian Walker
Web Content Specialist
Britt Oliver

Issue 4 | 2016
In the final edition of 2016, Susan Longworth, Taz George, and Mark O’Dell
introduce the Peer Cities Identification Tool, or PCIT. The PCIT, once live in the
first quarter of 2017, will allow city leaders, researchers, policymakers, and others
to compare cities regionally or nationally along various criteria, including housing
affordability, income inequality, and some indicators of future prospects. We provide
a brief case study of housing conditions in Iowa City with the PCIT article. Marva
Williams and Taz George provide a more in-depth look at the housing situation in
Iowa City from a practitioner’s standpoint, in “Measuring housing affordability: The
role of university partnerships in Iowa City and other communities.”

The Federal Reserve Bank of Chicago
The Federal Reserve Bank of Chicagoand its branch in
Detroit serve the Seventh Federal Reserve District, which
IOWA
encompasses southern W
 isconsin, Iowa, northern Illinois,
northern Indiana, and southern Michigan. As a part of
the FederalReserve System, the Bank participates in setting national
monetary policy, supervising banks and bank holding companies, and
providing check processing and other services to depository institutions.

WISCONSIN
MICHIGAN

ILLINOIS
INDIANA

Introducing, understanding,
and using the ICI 300 Peer Cities
Identification Tool
by Taz George, Susan Longworth, and Mark O’Dell
Municipalities, especially those that are mid-sized or
smaller, often face significant challenges in providing
services and amenities to meet the needs of their diverse
and changing populations. Solutions are usually contextspecific and must factor in larger demographic and
economic trends, in order to be effective. And, yet, in spite
of contextual differences, cities frequently have meaningful
similarities. However, identifying peer cities is often
informed more by conversation than by data or evidence.
The Peer Cities Identification Tool (PCIT) developed
by the Community Development and Policy Studies
(CDPS) Division of the Federal Reserve Bank of Chicago
is a data comparison and visualization instrument that
can help policymakers and practitioners understand
a municipality in the context of peer cities. The tool
stems from the Industrial Cities Initiative (ICI), a
study that originally profiled ten midwestern cities with
manufacturing legacies, at least 50,000 population and at
least 25 percent employed in manufacturing in 1960, and
how they have fared in socioeconomic terms over time.1
The original study generated a great deal of attention
among leaders of cities with comparable histories. The
PCIT is in part a response to inquiries from these leaders
as to how they “compare” to similar cities both within the
region and in other regions of the country, as well as in
response to a stated need/desire to share and learn from
best practices to address entrenched municipal challenges.
The PCIT is different from other “city-data” tools in that
it is not a ranking, but a comparison tool that provides the
user with a baseline of data from which to ask questions
and interpret and apply the answers. This approach is
based on a fundamental belief that every city is different,
possessing its own assets and liabilities. Usually no one

is more aware of the “municipal balance sheet” than the
people who live in and lead a city.
The PCIT allows city leaders concerned with community
and economic development issues to identify groups
of cities experiencing similar trends, challenges, and
opportunities along economic, demographic, social, and
housing dimensions. Using data on 300 cities from the
2010-2014 American Community Survey, as well as
longitudinal historical census data, the PCIT performs a
cluster analysis to identify similar cities. The 300 cities
located nationwide have a common baseline: a population
of at least 50,000 in 1960. Today, the 300 cities have a
median population of just over 100,000.

Understanding the themes
Peer cities are grouped along four key themes (others may
be added at a later time), which are essentially ‘portals’ to
the data. These themes are designed in response to key
areas of concern voiced by city leaders following more than
200 interviews across almost a dozen cities as part of the
ICI and other place-based research.
• Equity addresses questions regarding inclusion,
access, and diversity using wage-based Gini
coefficient, race and ethnicity-based dissimilarity
indices, changes in poverty levels, and educational
attainment. City leaders cited challenges of creating
and implementing inclusive growth strategies that
attract new businesses and jobs to their cities, while
creating policies that allow marginalized populations
to benefit from these new opportunities. The PCIT
uses the wage-based Gini coefficient (as opposed to
the income-based coefficient more frequently used)

ProfitWise News and Views Issue 4 | 2016
— 4—

How it works
From the PCIT website, users enter a city and select one of four
themes off which to base their analysis: ‘Equity, Affordability,
Resilience, and Outlook.’ Users first see a map of the United
States highlighting the identified peer cities – usually between
five and 15 cities. While often peers are geographically
proximate (i.e., within the same general region of the country),
sometimes a peer search can yield surprising results. The PCIT
will also present the user with data from the peer cities and
a table of key variables that were used to identify the group.
In addition, the tool generates peer median, minimum, and
maximum for each variable, as well as the ICI 300 median for
the selected variable enabling comparison across and within
the cities, in addition to the (full) dataset. This perspective can
provide further context, especially in identifying areas in which
the subject city might deviate from its peers, which can serve
to highlight particular challenges or opportunities. Users can
also select variables to graph or chart, providing a useful visual.
All data and images can be exported.

Peer City Identification Tool

Equity

Equity

Resilience

NextGen

Housing Affordability

Cedar Rapids

Peer City Results

Housing Affordability

NextGen

Resilience

Peer City Identification Tool

Percent of jobs in
manufacturing

Total
population

Labor force
participation

Change in labor force
participation, 1970-2010

Aurora, IL

Change in manufacturing
jobs, 1970-2010

16.1%

199,878

Change in real household
income, 2000-2010

Berwyn, IL
Cedar Rapids, IA

73.1%

14.5%

8.0%

56,762

68.9%

-63.0%

10.6%

-15.7%

16.2%

128,009

-59.6%

15.6%

6.9%

-9.7%

Royal Oak, MI

70.9%

58,382

74.7%

-53.8%

12.1%

-9.4%

-50.6%

-9.7%

Wauwatosa, WI

12.9%

46,838

Peer average

71.4%

15.1%

12.4%

97,974

71.8%

-51.1%

10.3%

10.0%

-7.3%

ICI 300 average

222,117

64.1%

-55.6%

4.5%

-10.4%

-57.0%

-10.1%

GINI

Cedar Rapids

Education

Household Income

Gini coefficient of wage inequality
0.5
0.4
0.3
0.2
0.1
0
Aurora
Illiniois

Change in labor force
participation, 1970-2010

Change in manufacturing
jobs, 1970-2010

Change in real household
income, 2000-2010

73.1%

8.0%

-63.0%

-15.7%

68.9%

10.6%

-59.6%

-9.7%

6.9%

-53.8%

-9.4%

74.7%

12.1%

-50.6%

-9.7%

71.4%

-51.1%

-7.3%

46,838

12.4%
10.0%

-55.6%

-10.4%

4.5%

-57.0%

-10.1%

Labor force
participation

Percent of jobs in
manufacturing

Total
population

Aurora, IL

16.1%

199,878

Berwyn, IL
Cedar Rapids, IA

14.5%

56,762

16.2%

128,009

70.9%

15.6%

58,382

12.9%

Peer City Results

Royal Oak, MI
Wauwatosa, WI
Peer average

15.1%

97,974

71.8%

ICI 300 average

10.3%

222,117

64.1%

Education

GINI

Berwyn
Illiniois

Cedar Rapids
Iowa

Royal Oak
Michigan

Wauwatosa
Wisconsin

Household Income

Gini coefficient of wage inequality

The images presented here are
samples of PCIT maps and charts.

0.5
0.4
0.3
0.2
0.1
0

Aurora
Illiniois

Berwyn
Illiniois

Cedar Rapids
Iowa

Royal Oak
Michigan

Wauwatosa
Wisconsin

Peer Average

ICI 300 Average

ProfitWise News and Views Issue 4 | 2016
— 5—

Peer Average

ICI 300 Average

to focus in on wage-earning workers who have been
employed for the full year.
• Housing speaks to issues of affordability by
incorporating data relating to homeownership
(income-to-home value ratio) and renting (rent
burden), the quality and competitiveness of housing
stock by using the age of housing as a proxy, and
monthly living costs. Providing competitive housing
affordable and attractive to both renters and buyers
was a primary discussion point among leaders.
• Resilience speaks to issues related to economic
diversification in terms of changes in manufacturing
employment, existing levels of manufacturing
employment, labor force participation, and
unemployment. Many cities experienced economic
shocks during the Great Recession, but had
experienced decline along these measures during the
preceding decades. Economic diversification and
labor force conditions provide broad insights into
areas of vulnerability and strength.
• The Outlook theme explores signs of a city’s
demographic and economic future by incorporating
changes in the working age population, family
composition, and mobility (over time). Changes in
the age distribution of a population, net migration,
and household size and composition, can all provide
clues about a city’s future. Cities experiencing unusual
demographic shifts may look to peers undergoing
similar shifts, and to (non-demographic) factors, such
as employment and educational opportunities, that
may be drivers.

Methodology
The tool works by performing a hierarchical cluster
analysis on all 300 cities, using the variables included
in the selected theme. A cluster analysis is a way of
grouping data based on the similarity of responses to
several variables. A cluster analysis treats the subject city
data as a “case” and will find “similar” or “peer” cases
based on several variables. The clustering method used is
Ward’s method, which minimizes the variance across all
variables in a given group.2 If a cluster produces only a
small number of results, the program has the option of
using the ranked values instead of the normalized values,
which tends to produce more evenly distributed groups,

but does not allow for easy distinction between extreme
outliers and more typical cities. The cluster containing
the focus city is squared off for ease of explanation and
verification, by looking at the maximum and minimum
values for each variable within the cluster and including all
cities within the given range for each variable as peer cities
for the focus city. Finally, the program produces a table of
all the included variables for all peer cities in the cluster.
As mentioned above, the PCIT has several potential
uses. For many municipal planners, comparison cities
are often, for practical reasons, limited to those that are
geographically proximate, subject to similar regional
trends, and to the planner’s personal knowledge and
familiarity. Sometimes, this is satisfactory, for example,
when planners may want to understand cities subject to
similar statewide policies or conditions. However, at other
times this purview is limiting and frustrating to planners
and other practitioners who wish to go outside of their
‘familiarity zone’ to interact with other places that may be
experiencing similar challenges or changes. In particular,
cities that have experienced changes in their economy,
with respect to manufacturing employment, for example,
may find it useful to learn about cities outside of their
specific region.
To this end, the PCIT will return cities that may not
initially appear to be peers – the most evident difference
is often that the peers are in very different regions of the
country – but that upon closer look are experiencing
similar conditions, at least along one of the variable
clusters. Different variable clusters will return different
sets of peers – occasionally there will be common cities
across the theme-based peer groups – and additional
data exploration can often shed light on similarities and
differences. Usually, however, the PCIT peer group will
include regionally proximate cities, as the methodology
used specifically seeks to minimize variance across clusters.
While the PCIT can be a useful comparison tool
from which to initiate planning discussions, it is not a
planning tool per se. Users are cautioned against taking
high level, longitudinal data as a directive or prescription
in any way: each of these cities is unique, with its own
distinct characteristics. However, as the case study
(see page 7) illustrates, it can be helpful in answering a
specific question (about housing, for example). It can
be especially useful in informing, without judgment or
qualification, broader discussions.

Note: We expect to bring the PCIT online in the first quarter of 2017,
and will provide an update in the next edition of ProfitWise News and Views.

ProfitWise News and Views Issue 4 | 2016
— 6—

The Peer City Identification Tool sheds light on Iowa City’s housing affordability challenges
by Taz George
Iowa City, Iowa, is home to the University of Iowa main
campus and is the principal city of a metropolitan area
with a population of 166,498,3 located in eastern Iowa
about 30 miles south of Cedar Rapids. Iowa City faces
acute affordable housing challenges, with a majority of
rental households spending over 30 percent of income on
rent. Adding to the challenge, the quantity of universityowned (and developed) student housing has not kept
pace with the growth of the student population, leading
students to seek housing in the private market and
pressuring the supply of affordable housing for the
general population, roughly 14 percent of whom (metro
area-wide) are employed by the university. For more indepth information about Iowa City's housing issues, see
article on page 9.
In June 2016, the Housing Trust Fund of Johnson County in
Iowa City hosted a local housing affordability conference,
with CDPS as an organizing partner. The Fund asked CDPS
to quantify the severity of Johnson County’s affordability
challenges relative to otherwise comparable areas, to
explore potential factors impacting these challenges, and
to present those findings at the conference. Using the Peer
City Identification Tool (PCIT), we were able to provide
context to Iowa City’s (the city represents roughly 52
percent of the county population) affordability challenges
and identify possible factors underlying the area’s rising
cost of rent relative to income.
The PCIT allows users to select a set of variables (relating to
housing, equity, resilience, and others) from the ICI dataset,
which are used to identify peers from among roughly
300 cities. For this analysis, a mix of general economic
and demographic variables, including employment rate,
labor force participation rate, total population size and
growth, educational attainment, race and ethnicity, and
geographic region, were used. Housing-related variables
were omitted from the peer selection process, in order to
identify otherwise similar cities, as a comparison for Iowa
City’s affordability issues. While Iowa City is not among
the cities included in the PCIT (its population in 1960 was
too low to meet the 50,000 threshold), it was added to
a custom dataset for the purposes of this analysis, and
supplemented with about 20 additional data points
gathered from the American Community Survey.

The PCIT identified five peer cities to Iowa City: Topeka,
Kansas; Duluth, Minnesota; Springfield, Missouri; Asheville,
North Carolina; and San Angelo, Texas. These cities were
included in a comparison sample along with Ames and
Cedar Rapids (Iowa) due to the local audience’s familiarity
with these places. We then collected and visualized a
variety of housing data on the sample group at the county
level,4 including the cost of rent from 1980 to 2014, the
rate of high and severe rental cost burden, the rental and
overall vacancy rate, the share of the population enrolled
in a university, housing tenure and structure composition,
and the homeownership rate. Among other findings, the
data showed that Johnson County’s cost of rent grew more
rapidly than its peers, that its level of rental cost burden is
comparatively high, and that its students account for a
much larger share of its population than all but one of its
peers. Johnson County’s housing stock also stood out for
being dominated by small multifamily rental structures.
An overall takeaway was that Johnson County’s housing
challenges shared some common ground with Story
County, where Iowa State University is located, in Ames.
The conference organizers hoped to use this data as a
basis for greater collaboration and information sharing
between the two areas.
Conference attendees were intrigued by the comparison
across peers, and several expressed desire to see different
comparison samples. For example, it was suggested to
compare only to other cities where a large university is
located, as that proved to be a key distinguishing factor
for Iowa City among its peers. By identifying cities that
were not ‘natural’ peers, for example Asheville, North
Carolina, participants were able to broaden their frame
of reference. The PCIT was useful in identifying baseline
areas of commonality between places, which laid the
foundation for further data collection, analysis, and
collaboration.
The PCIT empowers policymakers, researchers, and
practitioners from cities large and small to conduct
customizable analyses for their own purposes. CDPS’
experience in Iowa City demonstrates the ability of this
tool to better inform community development practices
by facilitating access to data across geographies to
address timely policy questions.

ProfitWise News and Views Issue 4 | 2016
— 7—

Notes

Biographies

1. For more information on the Industrial Cities Initiative, please visit https://
www.chicagofed.org/region/community-development/community-economicdevelopment/ici/index.
2. For more information regarding Ward’s Method, the original article detailing
the method is publicly available at http://homes.mpimf-heidelberg.mpg.
de/~mhelmsta/pdf/1963%20Ward%20JASA.pdf.
3. According to American Community Survey 2015 1-Year Estimates.
4. PCIT matches based on city-level data. For the presentation, county data was used
as conference attendees were interested in affordability challenges throughout
Johnson County, not just in Iowa City.

Susan Longworth is a senior business economist in the
Community Development and Policy Studies Division of
the Federal Reserve Bank of Chicago.
Taz George is a research analyst in the Community
Development and Policy Studies Division of the Federal
Reserve Bank of Chicago.
Mark O’Dell is a research analyst in the Community
Development and Policy Studies Division of the Federal
Reserve Bank of Chicago.

Tenth Biennial Federal Reserve
System Community Development
Research Conference

Registration is open! To register, please visit the conference website at www.minneapolisfed.org/2017CDResearchConference.
Registration for the conference will remain open until February 24, 2017, or until capacity is reached.
The Federal Reserve System Community Development Research Conference is a unique event that convenes researchers,
policymakers, and practitioners across sectors to consider important issues that low- to moderate-income people and
communities face.
The 2017 conference will explore the interplay between the development of kids and their communities, with an understanding
that “development” factors into key economic and social aspects of kids’ lives. High-quality and emerging research from multiple
disciplines will be presented in a dialogue with policymakers and community practitioners who can utilize the lessons gleaned
from the research. This event will spotlight research that can inform questions about key drivers to success, differences across
subpopulations, scalable intervention strategies, and policy considerations. The conference will also feature remarks by Federal
Reserve leaders, including Federal Reserve Chair Janet Yellen.
This conference is open to the public. Attendance by academic, government, nonprofit, and foundation employees is strongly
encouraged. If you have questions about the conference or registration, please email CDConference@mpls.frb.org.

ProfitWise News and Views Issue 4 | 2016
— 8—

Maintaining housing affordability:
The role of university partnerships
in Iowa City and other communities
by Taz George and Marva Williams
The Community Development and Policy Studies
(CDPS) Division of the Federal Reserve Bank of Chicago
works across the Seventh District1 to improve the
socioeconomic prospects of low- and moderate-income
people, in addition to working with community leaders
to bring development and reinvestment opportunities to
underserved communities. Our district comprises urban
centers, suburban, exurban, and large rural areas, and the
issues facing these areas vary widely. This article explores
the significant rental housing shortage in Iowa City
(Iowa’s fifth largest city and the county seat of Johnson
County) stemming mostly from the large University
of Iowa (UI) student population, of which the school
houses less than 20 percent. Accordingly, local residents
must contend with a large population of students vying
for the same, limited supply of rental units. The student
population has contributed to increasing rents and a
deeper deficit of affordable housing.
CDPS began working this year with the Place-Based
Inclusion Working Group, a group of university
professionals and affordable housing advocates that
organized to formulate strategies and encourage UI
administrators to work in partnership with community
groups to address the city’s housing shortage. In early May
2016, CDPS facilitated a meeting with UI administrators,
local government leaders, and housing advocates with
university professionals who have entered partnerships to
improve local communities. A separate, public meeting
with (other) affordable housing advocates, residents, and
students provided a means to share best practices and
findings from the first meeting more broadly.
This article comprises two main elements; the first is a
review of this process and those meetings. It begins with
an overview of how UI policies have impacted affordable

housing markets in Johnson County, the county home
of Iowa City. The second section describes university
partnerships that involve institutional engagement to
address local housing issues and other local needs, shared
by three university professionals from Drexel University,
the University of Minnesota, and the University of Illinois
at Chicago. The conclusion is a short description of next
steps.

Affordable rental housing in Iowa City
and Johnson County
Iowa City is the home of the University of Iowa.
Demographic data from Decennial Census and American
Community Survey estimates show that the population
of Johnson County, where Iowa City is located, is
undergoing significant changes. The county is growing
rapidly, with a population of 144,251 in 2015, an increase
of almost 30 percent from 2000. Johnson County is the
third largest county in Iowa, after Polk (Des Moines) and
Linn (Cedar Rapids) counties. The diversity of Johnson
County has also grown. Blacks were 2.9 percent and
Latinos were 2.5 percent of the population in 2000. By
2015, the percent of blacks and Latinos doubled and the
percent of whites decreased from 90 percent to 85 percent.
Further, the percent of foreign-born residents increased
from 6.4 percent in 2000 to almost 10 percent in 2015.
The percent of people living in poverty decreased slightly
from 15.9 percent in 2000 to 15 percent in 2015.
With an enrollment of over 32,000 students, UI is the
largest university in the region,2 offering wide-ranging
undergraduate and graduate courses of study. Enrollment
at UI has increased significantly over time, from less than

ProfitWise News and Views Issue 4 | 2016
— 9—

20,000 students in the late 1960s (see chart 1) to over
30,000 students in 2006.3 Students comprise 23 percent
of the county’s population; in contrast, the statewide (and
national) proportion is about 8 percent of the population.4
Like most large universities, UI is an economic anchor
of Iowa City. It employs almost 23,000 people,5 and its
hospital system has over 12,000 health care practitioners
and support staff.6 In fact, UI is aware of the challenges it
presents in terms of the local housing supply. The staff is
so large that, to ease the strain in Iowa City and disperse
employees, UI has moved some of its operations to
Coralville and North Liberty, two suburbs of Iowa City.
Chart 2 shows the ratio of UI dorm capacity to students.
The rate has declined from over .20, or one dorm space
per five students, in the early 1990s to .17 in 2016 because
UI did not add new dormitories for its growing student
population. From 1968 to 2014, no new dorms were
constructed, although the student population grew by
60 percent. Further, although one new dorm was
established in 2015, and another is projected to open
2017, the ratio of dorm capacity to students is expected to
still be roughly .20 in 2017.7

There are few studies of UI student satisfaction that
inquire about student views on housing at UI. However,
there are a few examples of dissatisfaction with the status
quo. Graduate students expressed concerns about an
increase in rent at a private student development, which
rose by 10-12 percent from 2014 to 2016. In the spring of
2016, students from a communications class documented
the views of 200 students living in off-campus housing
through small group discussions. Although the results
may not be generalizable to the entire student body,
several trends emerged. First, security is a major concern.
Students provided examples of apartment buildings with
no locks on exterior doors, broken door handles, and
broken windows that made their residences vulnerable
to burglars. Second, students complained about the high
cost of their housing. Many spoke about having to take
jobs to pay for housing and the stress they felt due to high
rent. Third, students felt that large leasing companies
that manage student off-campus housing are difficult
to reach and unresponsive to complaints from renters.
Last, students complained about living conditions. They
described broken appliances that were not repaired or
replaced for several months.8
UI students seeking housing have a deleterious impact
on the cost of housing in several respects. First, income-

Chart 1. UI fall student enrollment, 1968-2015
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
1970

1975

1980

1985

1990

1995

Source: Hawkinson and Garza (ND).

ProfitWise News and Views Issue 4 | 2016
— 10 —

2000

2005

2010

2015

as chart 3 illustrates. Since 1980, median gross rent
in Johnson County has increased by 35 percent after
inflation, while median household income has increased
by 29 percent after inflation. Among renter households,
however, the income picture is more concerning; real
income in 2014 dollars has actually declined by 13 percent
over this period, from $30,186 in 1980 to $26,262 in
2014. Not surprisingly, rental households with annual
income of less than $20,000 experienced the highest cost
burden of all income groups, with almost 100 percent,
spending 30 percent or more of income on rent. Yet even
among rental households with more typical income of
$20,000 to $35,000 (the county’s median renter income
is $26,262), 82 percent experience cost burden. Rental
cost burden is also elevated across multiple age groups.
Almost 80 percent of very young households (age 15 to
24) are cost burdened. Many of these households are
likely UI students and are unable to work full time or are
out of the labor force all together, leaving their income
low enough to necessitate spending over 30 percent of it
on rent. But even among working age households, the rate
of cost burden is over 40 percent, and for senior renter
households age 65 and older, the rate of cost burden is an
even higher 59 percent.

constrained students compete with lower-income
(non-student) households. According to Iowa City and
affordable housing advocates, multiple students living in
remodeled single family homes often pay in total more
than a single family would pay for the entire structure.
The demand inelasticity resulting from such a large
student body and relatively little campus housing has
contributed to a very low average vacancy rate of 2.1
percent among rental housing units in Johnson County
from 2010 to 2014; across the state, the rental vacancy
rate over the same period was about three times higher at
6.2 percent.9 Second, as reflected in the focus groups of
students, disinvestment in student leased units has led to
decay and problematic property management.
The result is of these factors is high rent cost burdens,
according to American Community Survey estimates.10
As of 2014, 57 percent of Johnson County renters
experienced high housing cost burden, meaning they
spend 30 percent or more of income on rent. Rental
households facing high housing cost burden have less
resources for cost of living expenses like food and
transportation, and may find it more difficult to save for
future investments such as a mortgage down payment or
retirement fund. The problem has worsened over time
as rental costs have outpaced renter household income,

Chart 2. Ratio of UI dorm rooms to students, 1963-2017
.25

.20

Projections 2016 & 2017

.15
1965

1970

1975

1980

1985

1990

1995

Source: Hawkinson and Garza (ND).

ProfitWise News and Views Issue 4 | 2016
— 11 —

2000

2005

2010

2015

of limited credit access, especially for lower-cost homes.
For example, while roughly 16 percent of owner-occupied
homes in the county are worth less than $100,000,
according to American Community Survey estimates,
only 12 percent of new purchase mortgages had an
origination balance of under $100,000 in 2014, based on
an analysis of Home Mortgage Disclosure Act records.
In other words, a disproportionately small number of
mortgages were made for purchasing low-cost homes,
which could be driven by weak buyer demand for these
properties, as well as tightened credit standards.

Chart 3. Johnson County rent and income
comparisons, 1980-2014
$35,000

Annual median renter household income
$30,000
$25,000
$20,000
$15,000

Profiles of university anchor
participants

$10,000

Annual median gross rent
$5,000
0
1980

1990

2000

2010

2014

Source: American Community Survey data and census data.

Anchor institutions are organizations that cannot easily
move to another location. They are ‘anchored’ to the
community. Generally nonprofit organizations, they
include museums, hospitals, libraries, churches, and
universities. Due in part to the decline in manufacturing
employment, anchor institutions are sometimes the
largest employer in a community or region.

Moreover, notwithstanding significant demand, there
has been limited growth in the rental housing stock in
Johnson County after the 2007 recession. Despite low
vacancy rates, growth in multifamily housing, which
accounts for 61 percent of Johnson County’s rental
housing stock,11 has only recently begun to recover from
the Great Recession. From 2007 through 2010, permits
were issued for the construction of fewer than 200 units of
multifamily housing in each year, compared to over 500
units per year from 2000 through 2003, according to the
US Census Building Permits Survey reports. More recent
data indicate an increased rate of construction; permits
issued from 2011 to 2014 allowed for the construction
of an average of 358 multifamily units per year. In 2015,
permits were issued for 675 multifamily units. Expanding
the supply of housing may help bring vacancy rates up
and prevent gains in rents from significantly outpacing
income.

Some anchor institutions do a better job of community
engagement and partnership than others. Increasingly,
they are vested to their community and invested in their
development and growth. Examples include purchasing
services and goods from local small businesses, training
and hiring local residents, providing technical assistance
and low interest rate loans to nonprofit organizations, and
investing in affordable housing loan funds or community
development financial institutions (CDFIs).

Though Johnson County’s homeownership rate is
low relative to Iowa as a whole, homeownership is an
important part of the county’s affordability challenges.
Renters facing high housing cost burden may struggle to
save for a down payment and to build up a strong credit
score. In addition, Johnson County exhibits some signs

• Craig Taylor, the director of the Community Planning
& Economic Development (CPED) Department at
the city of Minneapolis, and the former executive
director of the Office for Business & Community
Economic Development and the Business and
Technology Center at the University of Minnesota

The meeting organized by the Place-Based Inclusion
Working Group with administrators at UI and led
by CDPS staff focused on university-community
partnerships in urban communities. Three representatives
from universities participated in the meeting:
• Lucy Kerman, vice provost for University and
Community Partnerships at Drexel University

ProfitWise News and Views Issue 4 | 2016
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• David C. Perry, professor of urban planning and
policy in the College of Urban Planning and Public
Affairs at the University of Illinois at Chicago
Kerman and Taylor presented information on their
experiences with anchor activities. Perry presented his
research on university partnerships across the country.

Drexel University
Drexel University (DU) is located in West Philadelphia, a
community with a population of 243,459 in 2014, which
decreased by over 5 percent from 2000. The community
is majority white with 15 percent Asian, 20 percent
black, and 3 percent Latino residents. Poverty rates in the
community are very high, ranging from 24 percent to 53
percent in the community’s zip codes.12
DU is a private university founded in 1891. The school has
26,000 students, 2,168 faculty, over 200 degree programs,
and 15 colleges and schools. As one of Philadelphia’s
top 10 private employers, DU has significant economic
impacts on the community.13
Kerman began her talk by describing how all universities
are ‘agents of gentrification’ due to the number of people
they attract to their communities, including students,
university staff, and faculty. These groups raise demand
for housing and offer a ready market for retail stores and
restaurants. Kerman further characterized universities
as placed-based institutions that have made a long-term
investment in a community – moving large academic
institutions is usually beyond practical consideration –
and therefore the university’s future hinges in part on
the success of the surrounding community. Kerman also
talked about the benefits of anchor partnerships for local
communities. Universities have tremendous academic and
professional expertise, student energy, and local economic
(development) potential.
Kerman stated that DU administrators are well aware of
the pressure that its student body has on the local real
estate market. Because the university is predominantly a
commuter institution, it has little experience in developing
dormitories. The result has been a proliferation of
apartments developed by speculators near the campus, as
well as quasi-legal or illegal rooming house arrangements.
As an alternative, in 2012, DU leased a portion of its
property to American Campus Communities, a developer
and manager of dormitories, to create a mixed use project.
The result is an increase of 2,000 student beds.14 This

partnership allowed for increased housing for DU students
without a financial commitment from the university.
The upshot is that DU can now house all freshmen and
sophomores, and requires them to live on campus.
DU is considering other ways to preserve and develop
affordable housing. Kerman is working with two
community development corporations to promote
efforts to preserve homeownership and rental housing
for lower-income households near the campus. Further,
she works with a local intermediary, the Philadelphia
office of the Local Initiatives Support Corporation
(LISC Philadelphia), which advocated a designation of
the community as a Federal Promise Zone. The Federal
Promise Zone Program, which does not provide direct
funding, will make West Philadelphia more competitive
for an array of grant opportunities from federal agencies,
including the U.S. Department of Housing and Urban
Development, U.S. Department of Agriculture, U.S.
Department of Justice, and U.S. Department of
Education. The goals of the Promise Zone are to create
jobs, improve educational opportunities, and reduce
crime. Further, the city has collected about $575 million
in financial commitments projects in the Zone.
Kerman’s view is that universities can partner with
neighborhood groups who address different areas of need,
depending on the challenges of the community. Much of
this work is accomplished at DU’s Lindy Center for Civic
Engagement and the Dornsife Center for Neighborhood
Partnerships, both overseen by Kerman’s office. The Lindy
Center coordinates community service opportunities for
students and provides mathematics, writing, and literacy
enhancement programs for neighborhood youth. It also
provides volunteers opportunities in community projects.
The Dornsife Center for Neighborhood Partnerships
provides resources and information for community
residents, including adult education and workforce
development, health and wellness services, and tutoring
and homework support for youth. The Center is also a
hub for nonprofit agencies that provide services to local
individuals and families.
DU strives to hire local residents and support local
businesses. Over 10 percent of DU staff are local residents.
Many of them were hired through Philadelphia job
training programs. DU has also established Economic
Opportunity Plans that maximize contracts with local
businesses. This includes a construction partnership as
well as economic inclusion language in all requests for

ProfitWise News and Views Issue 4 | 2016
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proposals. Last, Kerman’s office works to sustain local
small businesses by building a bloc of local vendors that
provide services and products to the university community.
Much of the leadership for community engagement
originates with the president of DU, Dr. John A. Fry. In his
convocation address in 2010, Fry stated that he wants the
DU to become the most civically engaged university in the
country. In addition, the provost hired by Fry is committed
to developing community engagement and foster a culture
of local engagement throughout the administrative and
academic departments of the university.
Kerman identified several benefits to DU of community
engagement. It helps to substantiate the school’s nonprofit
status and meets the expectations of the city government
by, in short, providing community development services
in lieu of paying taxes. Community engagement has also
created a safer environment for students and staff. Last,
these strategies are also supported by alumni, who want
the school to be relevant and progressive.

University of Minnesota
The University of Minnesota (UM), the state’s largest
university, has its main campus in Minneapolis.
This campus, located in the University Community
neighborhood, has almost 50,000 students and nearly
20,000 employees at the Twin Cities campuses in
Minneapolis and St. Paul. The University Community
had a population of 39,400 in 2014, an increase of
18 percent from 2010. The community is 65 percent white,
15 percent black, 13 percent Asian, and 3 percent Latino.
The University Community reflects the demographics of
UM. Almost 80 percent of the housing is renter occupied,
nearly 20 percent of the residents are foreign-born, and
over half of the population are between ages 18 and 24.
The University Community is very disadvantaged –
approximately half of the households have incomes below
the poverty line and only 60 percent of adults between
18 and 64 are employed. Further, the median income is
about $30,000, compared to a median income of nearly
$55,000 in the city of Minneapolis.15
Most of the anchor activities at UM occur through
the Office for Business and Community Economic
Development (BCED), which was formed in 1999 to
support the economic growth of local communities.
BCED, which is a part of the University’s outreach
mission, provides technical assistance to small businesses,
computer classes for community residents, financial

and organizational capacity conferences for nonprofit
organizations, and a supplier diversity program.
In addition, BCED oversees student internships in
community development organizations.
Craig Taylor was the executive director of BCED from
2002 to 2014. He described how UM created economic
and community development strategies through
collaborations with nonprofit, corporate, and public
sector partners that focus on enhancing the quality
of life of underserved communities. This activity was
catalyzed at a community meeting where residents and
owners of local firms criticized UM for turning its back
on the community. In direct response, BCED formed the
Business and Technology Center (BTC), which provides
technical services for small businesses. BTC has evolved
into an information clearinghouse, trainer and locus for
networking, and a resource for innovation, technology,
and research.
The Community Health Initiative (CHI), a project
of BCED, provides supervised services by students at
UM Schools of Medicine, Public Health, and Social
Work programs to participants of community-based
organizations in the interest of improving public
health, social services, or medical technology. CHI
also administers community internships and student
consultations for public and community health agencies,
and provides funding for public health challenges.
Another program begun by BCED is the Robert J. Jones
Urban Research and Outreach-Engagement Center
(UROC), which partners with urban communities in
the region. Examples of its projects include the African
American Leadership Forum, which was formed to reduce
disparities in black communities; the Hmong Mothers
and Daughters Club that develops leaders and serves as a
showcase for cultural food and dance; and the Expanded
Food and Nutrition Education Program, which delivers
health and nutrition information to low-income families.
UROC has made $10 million in investments since its
founding in 2006.

Case studies of university partnerships
Perry maintains that universities have significant impacts
on local communities due to their economic influence and
ability to attract tens of thousands of students, staff, and
visitors. He asserts that no one organization or institution
can revitalize a community. It is essential to reduce risks
created by the high costs of land and the construction

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and challenges of housing and commercial projects. Each
university has a unique ability to influence neighborhoods
depending on their size, the local environment, and
leadership at the institution.
Perry’s research on university partnerships has led to these
classifications:
Universities as anchor collaborators: These universities
engage in partnerships with other urban partners,
including local government and private firms to develop
mixed use projects. Two examples occurred in downtown
Chicago, which faced severe disinvestment in the 1990s
and early 2000s. One, DePaul University, purchased a
disused building, moved its offices to the upper floors,
and allowed for a book store and other retailers on the
first floor. Second, the University Center of Chicago is a
student housing complex that serves as a home to 6,000
students from three universities and has restaurants and
other retail uses of its first floor. These developments are
creating a 24/7 atmosphere in downtown Chicago.
University as a neighbor: These institutions work with
other partners to rehabilitate the community as well as
the campus. They include Morehouse College (MC)
in Atlanta. Located in a deteriorated city community,
MC participated with a neighborhood community
development corporation (CDC) to develop new
affordable housing. It also participated in a land swap that
provided property for a mixed use university/community
development. Another example is Ohio State University
in Columbus, which redeveloped over 1,300 distressed
housing units. Many of these units are subsidized by the
U.S. Department of Housing and Urban Development
(HUD), thus offering affordable housing for lowerincome households.
Universities as community-based institutions: These
schools provide housing, public safety, and education
services for their local community. Due to lack of
affordable housing for university staff, Case Western
Reserve in Cleveland connects staff to community
organizations and city home buying programs to
enable them to purchase local homes. The University
of California institutions provide loans with flexible
underwriting and a salary differential housing allowance
for staff to purchase homes near campuses. Perry also
noted the higher level of engagement of universities that
have community-based police forces, and education for
early childhood classes to high school for local residents.

Perry concluded that committed leadership at the
university is essential for these partnerships. He posits that
in order for this work to be taken seriously by employees,
a commitment of the university administrators is crucial.
This means that the university must recognize that there is
an enlightened self-interest in improving the community
surrounding the institution, such as enhancing public
safety and providing affordable decent housing for
students and staff; reassuring parents their children
are living in well managed housing, and developing
community-based learning and research opportunities
for university faculty and students.

Conclusion
The members of the Place-Based Inclusion Working Group
hope to work with university administrators to develop a
strategy to improve opportunities for affordable housing
in Johnson County. They have several arguments in their
favor. Providing additional dorms for undergraduate and
graduate students can improve the ‘brand’ of IU. Dorms
are viewed by students, and importantly, by their parents,
as safer than off-campus housing. Dorms are monitored
by resident assistants and many campuses have security
phones and security staff. Living in dormitories is often
more affordable, and eliminates worries such as collecting
rent from roommates, and dealing with landlords. Dorms
are also convenient – they provide food services, are close to
classrooms, and include services such as cleaning and trash
removal. Dorm life can lead to better academic performance,
and provide a network of friends and acquaintances that
could not otherwise occur. Relations with alumnae may
also improve due to their interest in public perception of
the university as a thought leader. In addition, community
partnerships and relations with private developers are a
way to reduce the risk and cost of dorm development, as
exemplified by Drexel and other universities.
However, there are additional options to developing
dormitories. UI may choose to also enter the affordable
housing field by providing incentives to staff, donating
properties, or developing relationships with agencies like
HUD that can provide housing subsidies.
Last, there are many alternatives for UI in the economic
development field. It is a local powerhouse, and its
contracts with local businesses and unemployed can
improve the lives of countless lower-income households.

ProfitWise News and Views Issue 4 | 2016
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Notes

Biographies

1. The Seventh District comprises Iowa, roughly the northern two-thirds of Illinois and
Indiana and southern two thirds of Wisconsin, and the lower peninsula of Michigan.
2. University of Iowa, 2016, About the University, retrieved October 14 from https://
uiowa.edu/homepage/about-university.

Marva Williams is the community development and Iowa
state director in the Community Development and Policy
Studies Division of the Federal Reserve Bank of Chicago.

3. Hawkinson, Eric, and Kevin Garza (ND), Housing and Equity in Iowa City: Investigating
Trends of Housing Inequality in the Iowa City Metropolitan Area, Iowa City: The
University of Iowa School of Urban and Regional Planning, available at https://
www.urban.uiowa.edu/system/files/Iowa_City_Housing_Final%20Report.pdf.

Taz George is a research analyst in the Community
Development and Policy Studies Division of the Federal
Reserve Bank of Chicago.

4. US Census Bureau American Community Survey, 2015; Demographic and Housing
Estimates; Washington, DC: American Community Survey.
5. University of Iowa, 2016, Employment, retrieved October 14 from https://uiowa.edu/
homepage/about-university/employment.
6. University of Iowa Hospitals & Clinics (ND), 2016, Basic Facts, retrieved October 14
from https://uihc.org/basic-facts.
7. Hawkinson, Eric, and Kevin Garza (ND), Housing and Equity in Iowa City: Investigating
Trends of Housing Inequality in the Iowa City Metropolitan Area, Iowa City: The
University of Iowa School of Urban and Regional Planning, available at https://
www.urban.uiowa.edu/system/files/Iowa_City_Housing_Final%20Report.pdf.
8. Students of Communications, 2016, Discussion Report: Student Off-Campus Housing
Concerns, Iowa City: Iowa Program for Public Life.
9. US Census Bureau American Community Survey, 2015; Demographic and Housing
Estimates; Washington, DC: American Community Survey.
10. Ibid.
11. Ibid.
12. Ibid.
13. College Factual (ND), 2016, Drexel University, retrieved October 13 from http://
www.collegefactual.com/colleges/drexel-university/academic-life/facultycomposition/#; Drexel University (ND), 2016, Drexel University at a Glance, retrieved
October 13 from http://drexel.edu/about/glance.
14. Kerman, Lucy, 2016, interview with vice provost, Drexel University, by Marva
Williams, August 5.
15. Minnesota Compass, 2016, University Community, retrieved October 17 from http://
www.mncompass.org/profiles/communities/minneapolis/university.

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