Understanding Housing Abandonment and Owner Decision-Making
in Flint, Michigan: An Exploratory Analysis
Ellen M. Bassett, John Schweitzer and Sarah Panken
© 2006
Lincoln Institute of Land Policy
Working Paper
The findings and conclusions of this paper are not subject to detailed review and
do not necessarily reflect the official views and policies of the Lincoln Institute of Land Policy.
Please do not photocopy without permission of the authors.
Contact the author directly with all questions or requests for permission.
Lincoln Institute Product Code: WP06EB1
Abstract
Housing abandonment is widespread in the City of Flint. The purpose of this study was
to examine the underlying factors that drive abandonment. To accomplish this, archival
research, personal interviews and multivariate techniques were used. From the archival
work, four main themes arose as potentially impacting abandonment: race, school
closures, processes of neighborhood change, and greater indebtedness due to predatory
lending. Personal interviews with residents suggested that absentee landlords,
community disinvestment, poor political leadership, and the economy influenced
abandonment. Correlation and stepwise regression analyses were run to model the
relationship between abandonment and various socio-economic and housing factors.
Two end state measures of abandonment were used as dependent variables in the
modeling: “other vacant” and “state foreclosure.” Results from these analyses showed
that socio-economic factors and the change in the number of housing units influence
abandonment. Based on this study, it appears that the factors driving abandonment are
symptomatic of the poor economy in Flint.
Research Findings and Highlights
•
There is no single best easily available measure of housing abandonment for the
City of Flint.
•
Housing abandonment is significantly related to a range of economic,
demographic and spatial variables.
•
The “other vacancy” measure of housing abandonment is generally best predicted
by economic variables.
•
The “state foreclosure” measure of abandonment is best predicted by
demographic variables.
•
Significant neighborhood change took place in Flint in the 1970s and housing
abandonment became a significant issue in the 1980s.
•
Predatory lending may be currently exacerbating the problem of abandonment in
Flint.
About the Authors
Ellen M. Bassett is an Assistant Professor of Urban and Regional Planning at Michigan
State University. She holds a doctorate in Urban and Regional Planning from the
University of Wisconsin-Madison. Her domestic research interests include urban
redevelopment and the impacts of land use on human health; internationally her research
is focused on urbanization, informal settlements and land tenure in Sub-Saharan Africa.
John Schweitzer, Ph.D., is a Professor of Urban and Regional Planning at MSU. He has
over 30 years of experience in research and teaching related to urban neighborhoods. His
current research involves studying how “sense of community” among urban residents is
related to civic involvement and quality of life. His areas of expertise include research
design, measurement, and data analysis.
Sarah Panken is currently a Master’s Student in the Urban & Regional Planning
Department at Michigan State University. She has Master’s Degree from Michigan State
University in Wildlife Biology and has a background in wildlife conservation and
ecology. Her interests include exploring methods to increase information flow and
communication between biologists and land use planners.
Contact Information:
By mail (all authors): Urban and Regional Planning Program, School of Planning
Michigan State University, 101 UPLA Building, East Lansing, MI 48854.
Email: Ellen Bassett, [email protected]
Sarah Panken, [email protected]
John Schweitzer, [email protected].
TABLE OF CONTENTS
INTRODUCTION......................................................................................................................... 1
FLINT AND THE GENESEE COUNTY LAND BANK .......................................................... 2
VACANT AND ABANDONED HOUSING IN THE CITY OF FLINT............................................... 2
THE GENESEE COUNTY LAND BANK ................................................................................... 8
THE RESEARCH PROJECT ................................................................................................... 10
RESEARCH OBJECTIVES AND QUESTIONS .......................................................................... 10
RESEARCH METHODS: ....................................................................................................... 12
RESEARCH FINDINGS............................................................................................................ 14
ARCHIVAL RESEARCH AND INFORMANT INTERVIEWS ....................................................... 14
MAPPING VACANCY AND NEIGHBORHOOD CHANGE ......................................................... 16
MODEL DEVELOPMENT AND REGRESSION ANALYSIS ........................................................ 17
RESIDENT INTERVIEWS ...................................................................................................... 26
CONCLUSIONS AND DIRECTIONS FOR FUTURE RESEARCH ................................... 30
CONCLUSIONS ................................................................................................................... 30
FUTURE RESEARCH ........................................................................................................... 30
BIBLIOGRAPHY ....................................................................................................................... 32
APPENDIX A: INTERVIEWS CONDUCTED...................................................................... 36
APPENDIX B: MAPS OF DEMOGRAPHIC INFORMATION, VACANCY AND
TAX FORECLOSED PROPERTIES .......................................................................... 38
APPENDIX C: MODELING PROPERTY ABANDONMENT............................................ 46
APPENDIX D: QUESTIONS FOR SEMI-STRUCTURED INTERVIEWS....................... 54
APPENDIX E: FUTURE RESEARCH ON LAND BANKING AND OWNER
DECISION-MAKING.................................................................................................... 56
Understanding Housing Abandonment and Owner Decision-Making
in Flint, Michigan: An Exploratory Analysis
It’s a city that boasts the highest wage scale in the nation: the average factory worker here receives a
weekly paycheck of $185.26. Unemployment is generally low, yet in the city – particularly the Negro
areas – there are many decrepit frame shacks and everyone admits that housing is a major problem.
(New York Times, Oct. 20, 1968)
The depressed automobile manufacturing town of Flint, Michigan led the nation in unemployment in
August … Flint recorded 20.7% unemployment … Bad as Flint’s problem was, its jobless rate was
down slightly from 22.2 percent in July. (New York Times, Oct. 15, 1980)
I was watching TV one day and they showed, like, some of the buildings and areas that had been hit by
bombs and things like that, and while watching I got to thinking — there's parts of Flint that look like
that and we ain't been in a war. (Flint Resident speaking of Baghdad, Fahrenheit 911, film release
2004)
Introduction
Flint, Michigan is a city of changed fortunes: once a center of industrial wealth and power, the
city is now a place of chronic unemployment and poverty; once an education pioneer proud to
have founded the community school movement, the city now has numerous shuttered school
buildings. There are, however, two constants in the history of Flint: race and housing. Even in
its heyday Flint was characterized by poor housing stock and racial segregation. Today these
issues are arguably worse: Flint ranks as Michigan’s most racially segregated city and many of
its neighborhoods are characterized by severe blight and abandoned housing.1
Flint’s problems of housing abandonment, racial segregation and concentrated poverty – while
severe -- are not unique. Such problems affect many of the older industrial cities of the United
States such as Philadelphia, Newark, Baltimore and Milwaukee. The problem of housing
abandonment, the subject of this research project, is particularly commonplace in the cities of the
State of Michigan, most significantly in the state’s Lower Peninsula. From Muskegon in the
west to Lansing and Jackson in the middle of state to smaller cities such as Saginaw and Pontiac
in the east, many of Michigan’s traditional manufacturing centers are grappling with urban
abandonment and the challenge of reutilizing apparently unwanted land. The most dramatic
example of urban abandonment is the city of Detroit which alone has an estimated forty to fifty
thousand parcels of vacant tax-reverted land (Buss, 2003).
Widespread abandonment of property presents severe challenges to the affected municipalities.
Abandoned, tax-reverted houses are a drain on the municipal fiscus as they yield no property
taxes but require maintenance by municipal work crews. These properties are vulnerable to fire
and provide amenable loci for crime, which results in increased expenditures for police patrols
1
Based on data from the Census 2000, the City of Flint has a White/Black Racial Dissimilarity index of 76.8; the
city of Detroit, in contrast, has an index of 63.3. The Dissimilarity Index is a measure of spatial segregation of racial
groups, which ranges from 0 – a perfectly integrated community – to 100 – complete segregation. (Source:
www.censuscope.org) Looking at their respective Metropolitan Statistical Areas, however, yields a different
picture. The Flint MSA score is 76.7, the Detroit MSA, in contrast, is 84.8 making it the most segregated MSA in
the nation(McConville, Ong et al. 2001)
1
and fire protection. Derelict properties also present a threat to human health and safety; cities
thus spend thousands of dollars demolishing or boarding up such structures. Abandoned
properties have notable off-site impacts including effecting the lowering of property values in
nearby homes and businesses. If unaddressed, abandoned properties can become a driver of
further decline and abandonment as current and would-be owners or potential urban dwellers
perceive the affected neighborhood as a risky place in which to live or invest (National Vacant
Properties Campaign, 2005).
Despite the severity of the problems presented by abandonment and the widespread nature of the
phenomenon across US cities, research to understand the processes of housing abandonment and
formulation of policies to tackle the problem have not been at the forefront of urban research or
policy-making in recent years. This is now changing. Issues of housing abandonment, vacant
properties, blight and redevelopment have reemerged as areas of concern. Notably, the Lincoln
Institute of Land Policy, the funder of this research, highlighted research questions associated
with abandoned and vacant properties in its 2004-2005 Planning and Development Fellowship
announcement. This renewed interest is also visibly manifested in the launching of the National
Vacant Properties Campaign by a coalition of groups associated with Smart Growth, city
management, community redevelopment, and historic preservation. An express goal of this
campaign is to find policy solutions for the abandoned and vacant property problem and to
promote these solutions as best practices to other affected cities.
The research reported in this paper has arisen from one such best practice, namely the actions of
the Genesee County Land Bank (herein Land Bank). While the Land Bank is a countywide
institution, the primary impetus for its formation was to address abandoned housing and stabilize
troubled neighborhoods in the City of Flint. Including this introduction, the paper is split into
four sections. In section two, we more fully depict the abandoned and vacant housing situation
in Flint and briefly introduce the objectives and operation of the Genesee County Land Bank. As
this project has been generated in conjunction with the Land Bank, it is useful for the reader to
understand the context from which the research project arose. In the third section, we outline our
research objectives, main questions, and methodology as contained in the original proposal. The
fourth section presents our research results. We present the findings of resident interviews, the
model used for our multiple regression analysis (which have been drawn from both the academic
literature and the informant interviews), and the results of our multivariate analysis. We also
present via maps changing neighborhood conditions in the city using data from the State of
Michigan, the US Census and the records of Genesee County. Finally we discuss the findings
and indicate future direction for our research on abandonment, tax foreclosure and land banking.
Flint and the Genesee County Land Bank
Vacant and Abandoned Properties in the City of Flint
Like many Michigan cities, Flint is associated with the automobile industry – it is the birthplace
of General Motors Corporation. And like many Michigan cities, as the industry restructured
moving toward leaner workforces, oversea production and robotics, the city suffered substantial
job and population losses. Employment by GM went from 82,000 workers in 1970 to 15,000 in
2002. At its peak the city hosted 15 GM factories, today five remain. Table 1, next page,
provides an overview of demographic factors and housing characteristics of the city over time.
2
1960
People
Total Population
% African American
% Non-Hispanic Caucasian
% Under 15
% Over 65
Educational Achievement
% High School Diploma
% College Degree
Households
Total Households
Average HH Size
% Female Headed HH
Employment
Total in Workforce
% Unemployed
% Manufacturing
% Service
Income
Median Family Income ($)
Median HH Income ($)
Housing Stock
Total Units
Median Age Built
% Owner-Occupied
% Rental
Total Vacant (TV)
TV as % of Total Units
Other Vacant (OV)
OV as % of Total Units
Boarded
Table 1: City of Flint, Michigan Over Time
(Data from: US Census Bureau)
1970
% Change
1980
% Change
1990
% Change
2000
% Change
196940
17.53
82.47
32.85
7.27
193317
28.06
71.42
31.6
8.67
-1.84
60.07
-13.40
-3.81
19.26
159611
41.43
58.57
26.33
10.04
-17.44
47.65
-17.99
-16.68
15.80
142876
47.05
50.1
25.7
10.57
-10.48
13.57
-14.46
-2.39
5.28
124954
53.00
43.98
26.49
9.27
-12.54
12.65
-12.22
3.07
-12.30
14.7
3.18
16.12
3.59
9.66
12.89
19.14
4.89
18.73
36.21
18.2
5.91
-4.91
20.86
18.9
6.67
3.85
12.86
58623
3.32
N/A
61082
3.13
N/A
4.19
-5.72
N/A
57883
2.74
N/A
-5.24
-12.46
N/A
54837
2.56
17.16
-5.26
-6.57
N/A
48750
2.51
18.49
-11.10
-1.95
7.75
53505
5.38
69.26
26.62
47001
4.27
69.29
34.11
-12.16
-20.63
0.04
28.14
66261
18.12
34.56
12.73
40.98
324.36
-50.12
-62.68
58749
18.16
23.96
26.51
-11.34
0.22
-30.67
108.25
52717
12.93
20.22
39.33
-10.27
-28.80
-15.61
48.36
5595
6340
8565
9456
53.08
49.15
20080
17181
134.44
81.69
25083
20176
24.92
17.43
31424
28015
25.28
38.85
62275
1939
68.81
25.28
3683
5.91
1031
1.66
1519
64245
1942
65.62
29.22
3261
5.08
947
1.47
N/A
3.16
N/A
-4.64
15.59
-11.46
60976
1948
63.00
31.48
3328
5.46
709
1.16
186
-5.09
0.31
-3.99
7.73
2.05
58724
1953
53.87
37.95
4881
8.31
1463
2.49
1007
-3.69
0.26
-14.49
20.55
46.66
55464
1953
51.70
36.17
6720
12.12
2069
3.73
NA
-5.55
0.00
-4.03
-4.69
37.68
-8.15
N/A
3
-25.13
N/A
106.35
441.40
41.42
N/A
Consequently, the city’s population has fallen from a peak of 196,940 people in 1960 to roughly
125,000 people in 2000. This change has taken its toll on the city in the form of increased
poverty, rising crime and widespread abandonment of property (Kildee, 2004).
As is the case for other cities such as Detroit and Philadelphia, it is difficult to get an accurate
measure of just how much abandoned housing there is in the city (Research for Democracy,
2001). There are a few reasons for this. Part of the problem is that there has been no official
tracking of abandoned housing in the city of Flint. While city government does levy fines and
track code violations, the City of Flint has never conducted an abandoned property survey. A
second reason for this is the complexity of Michigan’s property management system and the
range of potential holders of abandoned housing. Under old legislation, housing became labeled
abandoned only after taxes had ceased being paid on it, the property failed to sell at a tax lien
sale, the land/property was deeded to the State of Michigan or the City of Flint and a site
inspection to determine occupancy took place. This was a very long process — a property could
be functionally abandoned by a private owner for years before it moved into the administrative
channels through which it was officially tallied as abandoned.
The difficulty of quantifying abandonment also reflects a deeper conceptual challenge that
affects research in this area, namely the lack of a shared definition of what is meant by
abandonment. Some studies, for instance, do not explicitly define abandonment and instead
lump together categories of problematic property, often referring to vacant, abandoned, derelict,
and substandard properties (e.g., Sternlieb et al 1974, Leavitt 1988, O’Flaherty 1993, Doyle
2001). Alternatively, abandonment is seen as a residual category identified in contrast to other
land classifications. In their survey on the “vacant and abandoned property problem”, for
instance, Accordino and Johnson (2000) distinguish vacant from abandoned property without
clearly defining abandoned. Some studies treat abandonment as a recognizable legal and
physical end state. Bender (1979) defines abandonment as the forfeiture of title to property.
More recently, Hillier et al. (2003) defines abandonment as an end state in which a property is
declared to be imminently dangerous and thus in need of demolition. In contrast, other studies
view abandonment as a process of withdrawal or disinvestment in a property (Barelt and Lawson
1982; Arnott and Braid 1997). Baldassare (1981), for instance, looks at abandonment as a
process of deterioration arising from physical, social and perceptual factors. Keenan et al.
(1999) see abandonment as a process in which both the public and private sector allow properties
to fall into disuse and ultimately become detached from the housing market. Hybrid definitions,
however, exist. Cohen’s 2001 study of abandoned housing in Baltimore defined abandoned
property as chronically vacant units (end state) whose owners are taking no active steps to bring
the property back to the market (process).
From the perspective of a researcher, defining abandonment as an end state and gathering data to
illustrate a static picture is appealing. Data such as vacant, tax-reverted properties or demolished
housing enable the researcher to draw a tangible picture of distress and neighborhood change.
End state data also has the advantages of finality: few will contest that a deteriorated, long
vacant, tax reverted property qualifies as abandoned. From the perspective of public policy,
however, understanding abandonment as a process is fundamental to formulating proactive
interventions to prevent it. Researching the abandonment process presents severe data
challenges – most communities lack the resources to track housing stock quality over time and
4
quantitative data used to gage owner disinterest or disinvestment (like the tax delinquency data
used herein) are an imperfect proxy since housing can enter into and quickly exit a state such as
tax delinquency. An owner, for instance, may just be playing a financial game – paying taxes at
the last possible moment – which has nothing to do with the state of the property or commitment
to ownership. A final challenge to understanding abandonment as a process is that it can be both
voluntary and involuntary; to understand the process we need to understand the motivation
behind abandonment behaviors. Owners may intentionally refrain from investment, maintenance
and tax payments; they may “walk away” from their property. Owners may also find themselves
unintentionally doing the same actions due to financial distress. These different abandonment
processes necessitate different public policy interventions.
In this paper, we have not solved this conceptual problem decisively. Rather we have opted to
look at abandonment as both an end state and a process. Our overarching research objective is to
understand the process; however, end state data is utilized to present the abandonment problem
for the city of Flint and to model abandonment econometrically. To draw a picture of
abandonment in the city over time, we have relied on data from four sources: the US Census, the
University of Michigan-Flint’s Environmental Block Assessment, the Genesee County
Treasurer’s Department, and the Michigan Department of Natural Resources. The data obtained
from the first three sources are best considered measures of abandonment as a process, whereas
the final set of data is a measure of abandonment as an end state, in this case real estate located
in the City of Flint that was tax forfeited to the State of Michigan. Graphs 1 and 2 on pages 7
and 8 present contrasting measures of abandonment derived from two of these sources.
US Census: The US Census has several categories of vacant housing; these categories,
unfortunately, have changed over time with useful categories such as dilapidated and boarded up
only appearing in a few enumerations. Through all periods, however, the US Census has
measured vacant housing (as a contrast to occupied housing). The tally given in vacant housing
includes all housing that is not occupied at the time of the enumeration, including properties for
sale or rent or seasonal/vacation homes. The category “Other Vacant” is a more restrictive
category defined as vacant year round-housing units that are not for rent or sale or vacant
awaiting occupancy. Because it is the most restrictive category, other analysts (e.g., Shlay and
Whitman, 2004) have used the “other vacant” category as their measure of abandonment.
Environmental Block Assessment: A second measure of abandoned housing available to us
comes from the EBA, which was conducted in 2000. In this survey, University of MichiganFlint students physically assessed and mapped housing quality throughout the entire city. Their
assessment contains five categories of house quality ranging from not salvageable to wellmaintained. The evaluation also indicates whether the structure was boarded up or if it had
sustained fire damage.2 To gain an estimate of abandonment, we queried the database counting
properties as potentially abandoned if they were categorized as not salvageable or in major or
moderate disrepair. By this measure 4314 units in 2000 could be considered abandoned.
Genesee County Treasurer’s Department: A third measure for abandonment was derived from
data obtained from the Genesee County Treasurer’s Department. This data covers only the years
2
The City of Flint ranks nationally as second per capita in number of fires and first in fires per firefighter. (Flint
Fire Department, www.umflint.edu/today/firestudy.php, accessed July 09, 2005.)
5
1997 to 2004. Before the passage of Public Act 123, which enabled counties to foreclose on tax
delinquent property owners, the process of foreclosure in the state of Michigan was private. That
is, taxes owed to the county were sold at tax lien sales; purchasers of tax liens could foreclose on
property owners if taxes remained unpaid. County records, thus, do not indicate foreclosure;
they do indicate tax delinquency.
For our purposes, we created a proxy for abandonment in process that we have called “persistent
delinquency.” To be considered persistently delinquent, a property would have to have tax
arrears for more than three consecutive years and the three-year average taxes owed would have
to constitute 25% of total assessed value. Our rationale is that repeat tax delinquency can be
interpreted as a sign of disinterest and/or economic distress that is a precursor to abandonment.
Additionally, we hypothesize that tax delinquency that amounts to a significant amount of
property value might indicate propensity to abandon the property. For owner-occupiers such
severe indebtedness would be difficult to address through property sale given Flint’s extremely
weak market; for landlords severe indebtedness might represent a strategy to maximize shortterm financial flows from rents on obsolete, unsaleable property. Delinquency data (as is
discussed below in data limitations) was very difficult to obtain for the periods desired. We
obtained data only for the years 1999 to 2003; out of that data only 311 properties qualified as
persistently delinquent.
State Foreclosure from Michigan Dept. of Natural Resources: The final data source on
abandoned property in the city of Flint was obtained from the State of Michigan. As noted
previously, under the old system of tax foreclosure, the state of Michigan received tax reverted
properties. Properties tax reverted to the state only if they failed to sell at auction. As expected
state-owned properties were generally the least desirable properties, eschewed even by rentseeking tax lien buyers. Through a Freedom of Information Act request, we obtained records for
tax reverted properties within the boundaries of the city of Flint for the years 1965 to 2005. Of a
total of 895 records, 752 records (84% of total) were complete; 145 (16% of total) were missing
crucial data points, such as parcel number.
Discussion: Using these figures to look at vacant housing in the city over time yields an
interesting picture. According to the US Census, Flint has had fairly steady levels of total
vacancy over the last decades. For the first three census periods listed in Table 1, total vacancy
hovered around 5-6% of all housing stock. Total vacant housing as a percentage of housing
stock rose in the 1990 census; the 12% recorded in 2000 is the highest level yet. The level of
Other Vacancy as a percent of housing stock actually declined slightly in the first three census
periods. The most significant jump in the Other Vacancy category occurred in 1990 census
when this count doubled from the level recorded in 1980. In 2000, other vacancy continued to
grow as a category, although not by the same percentage as the previous census tally.
The Census data also indicates an interesting trend, namely the continual decrease of housing
stock in the city over time. Flint housing stock only increased between the 1960 and 1970
Census with the addition of 1970 units. For all the remaining years, housing stock decreased
although the rate of housing stock decrease slowed in the 1980s. There appear to be two major
explanations for Flint’s shrinking housing stock. The first is that early losses, namely in the
6
1970s, were at least partially the effect of new highway construction and the clearing of
neighborhoods to built the road. The second is that this shrinkage in the housing unit tally is the
result of housing deterioration or fire followed by demolition. According to interviews, the city
of Flint had a strong “slum clearance” mentality throughout the 1980s; houses were demolished
both to prevent fire and to control the city’s drug trade and the proliferation of crack houses.
According to one informant, the area of the City known as Carriage Town was
disproportionately affected. It had approximately 800 housing units in the early 1980s when
residents there sought a historic district designation; today it has approximately 280 (I07.09.051).
Given the declining level of housing stock over these 10-year periods, Census-based vacancy
calculations, thus, may actually understate the level of housing abandonment in the city. In
2000, for instance, the Census counted 6720 vacant units (12% of total units) and 2069 other
vacant units (4%). Combining the change in the other vacant figure (from 1990 to 2000, 603
units) with the housing units lost in the period (3260) yields an estimated 3863 housing units (or
6.6% percent of the Year 1990 housing stock) that one could argue really represents the toll of
abandonment in the 10 years from 1990 to 2000.
The data provided by the State of Michigan shows that a total of 895 properties tax reverted to
the state from the years 1965 to 2005. Of these, the majority of properties tax reverted in the last
15 years. (Please see below.) Potentially the increase in tax reversions in this period reflects a
time lag between economic contraction, landowner non-payment and completion of foreclosure
processes prior to the enactment of P.A. 123. Likewise, our measure of persistent delinquency
shows that more property owners became significantly indebted in since 2001, but it is very
difficult to tell much from this data given the very few years for which we were able to obtain
data. Details are provided in Table 2 below.
7
Graph 1: Flint Population and Housing Stock Losses: 1960-2000
Graph 2: Vacant, Other Vacant and State Foreclosed Properties, 1960-2-000
8
The Genesee County Land Bank
In the last several years, the Michigan legislature passed a
Status of GCLB
series of bills that significantly altered the state’s property
(as of January 2006)
foreclosure system and led to the establishment of the
Genesee County Land Bank (GCLB). First, in 1999, the
Properties currently held: 2392
legislature passed Public Act 123 (1999), the Delinquent
Houses rehabbed: 11
Property Tax Foreclosure Act.3 Among its features, this
Rehabs in progress: 5
act sped up the process of foreclosure and created
Demolitions: 483
marketable title for the properties that revert to a
Demo in progress: 121
municipality. It also changed the administrative
Side lot transfers: 248
arrangements for dealing with foreclosed properties by
giving counties the right to become foreclosing
government units. Specifically, under P.A. 123, counties in the State of Michigan were given the
choice of “opting out”, that is, leaving the foreclosed properties the State’s responsibility, or
“opting in”, meaning that County government agreed to take control of the foreclosed parcels.
The legislation also gave the county access to financial resources for managing tax foreclosed
properties by directing the proceeds of successful sales to a “land reutilization fund” which can
be used for managing the county’s inventory of foreclosed properties (Kildee, 2004; CRC, 1999).
Genesee County chose to “opt in” under the 1999 law and became the foreclosing unit for the
county that includes the City of Flint. At this time the precursor to the Genesee County Land
Bank, the Genesee County Land Reutilization Council was established.
In 2003, the State of Michigan passed another piece of legislation critical to the establishment of
the Land Bank. Under what is known as Public Act 258, or the “Land Bank Fast Track Act”,
counties that have “opted in” under PA 123 can enter into an agreement with the Michigan Land
Bank Fast Track Authority to create a county-level land bank (Kildee 2005). As with PA 123,
the Land Bank Fast Track Legislation is actually a package of legislation that outlines the rights
and responsibilities of County Land Banks. P.A. 258 authorizes the creation of state and local
Land Bank authorities and establishes an expedited quiet title and foreclosure process for
property held by an authority. Significantly, the legislation gives the land bank the right to take
all its property and list it as part of a brownfield plan (thus enabling the use of tax-increment
financing), as well establishing a five-year period of tax exempt status for the land or property
that it sells.
As of January 2006 the Genesee County Land Bank has completed 4400 foreclosures
(correspondence, Kildee January 2006). The spatial distribution of the Land Bank’s holdings as
of 2004 is displayed on Map 1 next page. The Land Bank has formulated a coherent strategy for
dealing with its holdings: severely blighted houses are being demolished, vacant “side lots” are
pages. The Land Bank has formulated a coherent strategy for being sold to next-door neighbors,
housing non-profits are receiving foreclosed properties to rehabilitate and manage, parcels are
being assembled for development projects, and neighborhood and regional planning efforts are
underway. In conducting its activities the Land Bank has established good working relationships
with community residents and various city council members; relations with the mayor of the City
3
Although it is commonly known as PA 123, changes to the property tax delinquency and reversion process also
include Public Acts 132, 133, and 134 (CRC 2000).
9
of Flint are rather more strained. Notably, the Land Bank is emphasizing community
participation in decision-making. This is reflected in its planning processes and in the
establishment of a Citizens’ Advisory Council to the GCLB.
The Research Project
While the progress underway for addressing existing abandonment in Flint is encouraging, a
concern of Land Bank officials is that ultimately they are treating only one visible symptom of
the city’s problem: the abandoned land and housing left behind by departing residents. To really
effect change, county and city officials need an understanding of what has caused and what is
continuing to drive tax foreclosure and abandonment in the city. Of particular interest is to
understand why Flint is experiencing such sustained high rates of foreclosure and abandonment
so many years after the city contracted economically. Likewise, while we are certain that
economic change, particularly the loss of manufacturing jobs and the restructuring of the
economy is a very important variable in the city’s abandoned housing problem, it is presumably
not the entire story. Other factors have been identified – such as age of housing stock, shifting
housing preferences amongst consumers, preferences for racially homogeneous neighborhoods,
crime, school closures and busing, the rise of predatory lending institutions in minority
neighborhoods, etc. – which might more fully explain housing abandonment and foreclosure in
the city.
Research Objectives and Questions
The primary objective of this research has been was to understand the processes of neighborhood
change, disinvestment and abandonment of property in Flint. Specifically, the research was
organized around three questions.
First, how has abandonment moved spatially throughout the city over the last decades? We
know that at present some neighborhoods are more characterized by abandoned housing than
others. We do not know, however, at what point in time abandonment emerged as problem in
the city. Nor do we know how abandonment, once it emerged, moved across the city and why it
affected certain areas and not others.
Second, what factors are driving abandonment in the city? We also are seeking to identify and
quantitatively evaluate a wide range of factors that might play a causal role in housing
abandonment and foreclosure over time. Judging from the academic literature on abandonment
(as well as from common sense and informant interviews) one can hypothesize that certain social
and economic forces and public policies have played a role in the decline of the city of Flint.
Deindustrialization, racism, and federal housing and highway programs instituted after the
Second World War, for instance, are all recognized as having favored the growth of the suburbs
over the city (e.g., Squires, 2004; Powell, 2004). Accordingly, one can identify a complex mix
of factors that might influence decision-making by landowners and drive abandonment.
Potential factors include societal and economic factors (e.g., economic contraction, demographic
change, crime), physical attributes (e.g., pollution, crowding, poor quality housing stock) and
institutional influences (e.g., redlining, tightened rules for payment of back taxes).
10
11
Finally, why do different landowners act differently in their decision-making about land and
property in Flint? We are interested in learning more about the decision-making process of Flint
property owners. Specifically, why have some owners continued to stay in the city and even
invest, while others have others fled? What factors do landowners cite as being important to
their decision? Theoretically, we have approached the research from the perspective of
economic sociology, which stresses that economic decision-making takes place in a culturally
embedded context. As such, we are particularly interested in identifying the terms owners use or
the factors owners cite when describing their decision-making (e.g., relative importance of
economic considerations versus social or environmental factors.) Our schematic of potential
factors in decision-making and possible outcomes/decisions is contained in Table 2 next page.
Research Methods
To answer the previous questions, quantitative, qualitative and spatial/GIS methods were
utilized. Quantitatively, the research used multivariate techniques to model the relationship
between abandonment and various factors such as economic contraction, demographic change,
fiscal policies, etc. as independent variables over time. Two end state measures of abandonment
were used as dependent variables in the modeling: “other vacant” properties from the US
Census and tax reverted/foreclosed properties from the state of Michigan. These two measures
were selected as they provide the most complete set of longitudinal data related to neighborhood
change and abandonment.
In general, data availability and quality proved a significant problem in this research project. In
the original research proposal we anticipated that the county’s annual records on tax delinquency
and tax lien sales would serve as a major data source for quantifying neighborhood change and
abandonment over time. Unfortunately, accessing this data and moving it into a useable format
for the period under review has not been viable. There are two reasons for this. First, electronic
data accessibility has been problematic. While data are stored on the county’s mainframe
computer, the mainframe is decidedly outmoded and “unfriendly” technology. (We’ve dubbed
the mainframe “Hal.”) After months of pursuit of data, information systems managers for the
county were only able to harvest data in October 2005 covering the years 1997 to 2004. We did
try alternative paths of assembling data on property being offered in tax lien sales through
newspaper advertising and from hard copy records at the County. Unfortunately tax lien sales
are organized by plat, which made assembling the data into our parcel-based GIS impossible.
Second, assembling a complete set of tax delinquency from paper records was not viable given
time and labor constraints. The tax delinquency data from 1997 to 2002, for instance, yielded
10,287 records of delinquency.
12
Table 3: Schematic for Understanding Owners’ Decision-Making
Assume and agree with fundamental perspective of economic theory that economic decisions do take place in a cost-benefit framework.
Determination of costs and benefits, however, socially/institutionally defined.
Typical Factors Affecting Land, Land Value and Decision-Making
Economic /
Institutional
Factors
Social /
Cultural
Factors
Leave city: maintain
ownership (become absentee
landlord), put on rental
market (assumes market
exists; could produce undermaintained or blighted
property)
Environmental
/ Physical
Factors
Economic change
(employment, structure of
economy)
Demographic change
(racism)
Tax rates and other fiscal
policies
Social linkages /
“belongingness” (social
capital measures)
Location
Parcel Size
Attitudes toward urban
living
Accessibility
Leave city: sell property
(assumes market exists)
Factors determine
“value” of
property (both
market value and
owner’s valuation)
Quality of Schools
Land use and local
government legal
institutions (e.g., zoning,
annexation,
incorporation)
Range of Potential Decisions
Leave city: abandon / tax
revert (assumes no market
exists)(voluntary or
involuntary)
Stay in city: willingly remain
(assumes benefits outweigh
costs)
Local plans /
redevelopment actions
Crime / safety
Contamination /
pollution
Subsidies / government
incentives/services
Personal circumstances:
illiteracy, lack of
financial savvy
Housing quality and
amenities
13
Stay in city: unwillingly
remain (costs of leaving
untenable)
Two qualitative methods were also used in the project: archival research and personal
interviews. Archival research has been used to gather data on Flint’s history, identify public
policy changes or initiatives affecting the city, and isolate potential local factors for the
multivariate analysis. Personal interviews were (and are) being used to understand the decisionmaking processes of individual landowners; our primary focus is residential landowners. We
have conducted interviews with long-term owner-occupiers still within the city; additional
interviews are scheduled for former Flint residents. These interviews are gathering data on
neighborhood change, individual circumstances, and key factors in decision-making toward
property. To date, we have not conducted interviews with individuals who have faced
foreclosure (that is, individuals in the foreclosure prevention program) or who have been
foreclosed upon. (Please see the directions for future research section of this paper regarding a
revised methodological approach to researching tax foreclosure.)
Finally, property and ownership data has been assembled in an Access database suitable for a
geographic information system. GIS has been used to present the spatial spread and geographic
extent of key indicators namely, vacant property, state tax foreclosed properties, and persistent
delinquency.
Research Findings
Archival Research and Informant Interviews
To collect background/historic information on Flint, we searched newspaper archives for
accounts associated with Flint, housing, employment, and race. Microfilm archives for the local
newspaper, The Flint Journal, were examined for news stories associated with neighborhood
change for three specific periods, that of 1967-1968 (Open Housing Act), 1982-1992 (period of
major plant closings) and 1997-2002 (closure of Buick City and initiation of the Land Bank).
Three newspaper indices, Infotrac Custom Newspapers, Factiva, and Lexis Nexus Academic,
were used; additionally to understand the type of national coverage the city received over time
we searched The New York Times digital news service (1851 to 2005). Concurrently, nine
informant interviews were conducted beginning in December 2004. Interviewees represented
local Flint leadership, current long-term residents, and university-affiliated individuals with Flint
ties. A list of all interviewees by category is contained in Appendix A.
Discussion
Four themes arose from archival research and informant interviews:
Race and the Open Housing Ordinance of 1968:
Both the archival work and interviews indicated that race is a major factor in neighborhood
change and abandonment of housing. Newspaper accounts of Flint indicate that the city had
acute housing issues throughout the post-World War II period; African American residents had
the poorest housing in the city and lived in segregated neighborhoods. Significantly, in 1968
Flint became the first city in the nation to pass an Open Housing Ordinance (NYT, 1968).4 The
4
The Flint City Council had passed the ordinance by a 4-3 vote in the fall of 1967. A signature campaign to place
the ordinance on the ballot for citizen approval was quickly launched by a local man associated with the John Birch
14
passage of this ordinance through citywide referendum came after a sustained campaign by
housing advocates/civil rights workers; it passed by a mere 38 votes (The Flint Journal, 23 Feb.
1968). According to several informant interviews, the passage of the ordinance was followed by
an immediate and successful campaign by realtors to induce whites to sell, an action now known
as “block busting.” (Also see Land Bank Conference Keynote by Johnson 2005,
www.cityofrochester.org)
Community Schools and School Closures:
Another theme that arose in the informant interviews and archival research was the excellence of
the Flint school system and the centrality of schools to the home purchasing decisions by Flint
residents. Notably, the Community Schools Movement – the idea that schools should serve as
places of lifelong education and recreation for all members of the community – was born in the
city of Flint in 1935 through a creative partnership between Frank J. Manley, a Flint physical
education teacher, and Charles Stuart Mott, industrial titan and philanthropist (Decker, undated,
~2000). At its height, the Flint school system operated 36 community schools and served as a
national example of “how schools and communities could work together to solve community
problems” (Source: National Center for Community Education, www.nccenet.org, accessed July
5, 2005). According to informants, the closure of Flint schools is a potential factor for
explaining differences in abandonment across Flint neighborhoods.
Processes of Neighborhood Change (Interrelationship of Racial Change, Housing Sales,
Abandonment, Foreclosure):
Another theme that arose in the interviews with key informants was the process of neighborhood
change across the city. Most informants described a similar pattern of neighborhood change in
the 1970s: racial integration/in-migration of Africa Americans into historically white
neighborhoods (generally following the Open Housing Ordinance) followed by a spike in
housing sales associated with white flight/block busting or a shift of housing stock out of owneroccupancy into rental. Just when disinvestment and abandonment first occurred is not clear in
the informant interviews. Some indicated that abandonment began just after the ordinance and
was associated with racial change in the neighborhoods. Two types of homeowners were seen as
affected: (1) people unable to sell homes who find renting unprofitable begin to disinvest and (2)
people, generally incoming African American families, who purchased homes at an inflated price
running into financial difficulty. Others indicated that abandonment was not a phenomenon until
the 1980s, emerging once GM’s contraction was permanent and unemployment was widespread
and chronic rather than cyclical. Then the fragility of Flint’s housing market became evident,
with owner-occupiers discovering the potential sales price of their primary residence to be low,
sometimes lower than their remaining mortgage obligation.
Society. Labor and churches launched a sustained campaign to support the ordinance; local opposition was couched
in terms of property rights and onerous regulation on landowners. The election was a cliffhanger. Initial results
indicated defeat of the ordinance, while a recount spurred by conflicting tally at the Flint Journal office showed
passage by a mere 43 votes. The final count from the Flint Board of Canvassers showed a 38-vote victory in the
end. (The Flint Journal, 1967-Feb. 1968).
15
Predatory Lending:
The final theme that arose in both the literature and in informant interviews is the expansion of
sub-prime lending and the potential role played by predatory lenders in exacerbating
indebtedness which may in turn affect ability to pay taxes. While sub-prime lenders are lenders
who offer much needed financial services to often underserved minority communities, Lopez
(1999) characterizes predatory lenders as financial institutions that make loans with exorbitant
rates and excessive closing costs to low-income borrowers. He notes that predatory lenders have
been particularly adept at providing home equity lending in areas of the county where the
residents have little disposable income but substantial home equity due to the fact that their
mortgages are paid down or their property values have appreciated. According to one informant,
such lenders are very aggressive in the city. She reported weekly telephone calls and constant
mail solicitations urging the refinancing of her house and/or the sale of a land contract to which
she is a party (I08.15.05-1). Predatory lending, moreover, is perceived as a problem by Flint
community development corporations and is a regular part of their homeownership counseling
(I03.18.05-1). Analysis of mortgage lending data available through Dataplace service of
Knowledgeplex shows that since 1997 sub-prime lenders have come to capture a significant
portion of the Flint market for both conventional mortgage loans and refinancing. (See graphs 3
and 4 below; data and graphs accessed from www.dataplace.org on January 15, 2006).
Graph 3: % Conventional Mortgages from Sub-Prime Lenders
7-year period: 1997-2003
Graph 3: % Conventional Refinancing Mortgages from Sub-Prime Lenders
7-year period: 1997-2003
16
Mapping Vacancy and Neighborhood Change
In keeping with the research proposal, the data obtained through our research have been mapped
to provide insights into the spatial progress/movement of vacancy and abandonment across the
city of Flint. The two visual pictures of Flint that result are contained in Appendix B of this
document. The first set of maps is derived from US Census data for the last two census periods.
These maps underline trends of neighborhood change that are in keeping with the academic
literature and informant interviews. First, the city is racially segregated with African American
populations concentrated in the northwest part of the city and white populations concentrated in
the southwest and eastern neighborhoods. Even with racially homogeneous neighborhoods,
whites are continuing to leave the city as seen in dropping percentage concentrations in their
traditional neighborhoods. (NB: Tract number 41 is an airport; Tract 21 contains a large
manufacturing facility and few homes.) Household income in the city has a greater range in
2000 than in 1990, ranging from approximately $8,000 to $88,000 in 2000 as compared with
$8,000 to $41,000 in the previous census period. The city’s lowest incomes and highest poverty
are recorded in the north end, which is the predominately African American part of the city. The
maps of Other Vacant property illustrates that vacant property affects all parts of the city, but
that vacancy is concentrated in the north and in the neighborhoods closest to the city’s
downtown, which is located in Tract 28.
The second set of maps is derived from the other data sources used to assess abandonment,
namely state data on tax-reverted properties and county data used to create our measure of
“persistent delinquency.” These maps reveal the same basic spatial trend. Properties that passed
into the hands of the State of Michigan are clustered around downtown Flint, with a sprinkling of
additional properties in the north end. Likewise, persistently delinquent/highly indebted property
owners are located in the same sections of the city. Not surprisingly, these two sets of maps
have great similarity with the properties that have ended up in the possession of the Land Bank
(shown in Maps 1 and 2 previously.)
Model Development and Regression Analysis
To identify the range of factors that could be utilized in our multivariate analysis a systematic
review of the literature on abandonment was undertaken. Specifically, we electronically
searched for articles and books using the search terms “abandonment”, “foreclosure,” “blight,”
and “housing vacancy.” Major indices were used for this search, including LexisNexis, JSTOR,
Wilson Select and ProQuest; the library holdings at Michigan State University, the University of
Michigan and the Michigan Library were also queried. At this point in time, we have identified
80 articles or books relevant to our research.
From this literature, we formulated a conceptual model to explain abandonment and tax
foreclosure. In our model, four broad factors are hypothesized as playing a causal role in
neighborhood change. They are (1) spatial factors, that is factors associated with location,
neighborhood quality, and urban form; (2) socio-economic factors, that is measures of social
characteristics (such as poverty, educational levels, crime, etc.) that influence whether a location
is seen as a desirable place to live; (3) physical factors associated with the quality of housing
stock; and (4) policy variables, such as taxation. To give an example, various research reports
have indicated that housing preferences have changed over time and that the predominant
17
preference in the post WWII period in the United States has been for low density, detached
single-family dwelling units in suburban locations (see, for instance, Ahluwalia, 1999). We
would expect then that higher densities in Flint neighborhoods (due to smaller land parcels)
might have a relationship with neighborhood change. Likewise, we know that locational
decisions for families are strongly influenced by the quality of the local school system, thus,
measures of educational quality may help explain disinvestment as well. In Appendix C, we list
the full set of potential variables for this analysis, outline their hypothesized relationship to the
dependent variable, give the rationale for including each variable in the analysis, and explain
issues of data availability.
Methodology
During the course of this research, two different models were developed to examine potential
influences on housing abandonment. One model included only cross-sectional variables (e.g., %
Owner Occupied Housing) for 1980, 1990, and 2000. This model was used to explore
“snapshots” of how socio-economic and housing variables influenced housing abandonment in
each of the three time periods. The second model included not only all of the cross-sectional
variables, but also the percent change over time of those same variables.5,6 The purpose of using
percent change over time variables was to gain insight into the spatial aspect of the data, mainly
how different variables (e.g., income or unemployment) moved across census tracts over time.
Unfortunately, using percent change over time variables confounded the results. For example,
when examining the percent of the population that had attained at least a high school diploma in
census tract 1, in 1990 it was 68.7% and in 2000 it was 70.6%. Calculating the percent change
over time of the same variable yielded a result of -4.4%. The percent of the population with that
specific education level increased, but between 1990 and 2000 the change was negative. This
indicated that there was a decrease in the number of people who had attained at least a high
school diploma. Because of this type of anomaly, it was decided to drop the second model and
only present results from the first, simpler model. Problems with the second model also
suggested that other methodology should be used to track spatial movements of variables over
time. One such method may be to employ spatial statistics to gain a more detailed insight in how
spatial changes in these variables affect housing abandonment.
Units of Analysis
In order to get the best understanding of housing abandonment and owner decision-making, the
ideal level for the analysis would be at the parcel level. However, we were unable to obtain most
of the data we were interested in at that level. The primary source of data for our statistical
analyses came from the US Census for the years 1980, 1990, and 2000. These data were only
available for census tracts, not at the level of block group or census block. Therefore, the level
of analysis for our research was the census tract level. For the time periods under study, the city
of Flint had varying numbers of census tracts. These were normalized to 41 census tracts in the
Geolytics software that we used. Two of the tracts (21 and 41) were primarily industrial with
very few residential units so they were excluded from the analyses, leaving 39 tracts for analysis.
5
6
There were exceptions when data were not available. Please see Data Limitations Section.
The method for calculating the percent change over time variables is discussed below in the Methodology Section.
18
Variables
Of the full set of possible independent variables listed in Appendix C, we were able to obtain
measures of 15 of them at the census tract level for use in our analyses. Each of the independent
variables was collected for every census tract (n=41) in the City of Flint. Because the census
tracts varied in size, aggregate counts of relevant variables within tracts were transformed into
percents using the total population7 as the denominator (e.g., total population or total housing
units). For example, the number of African Americans in each tract was converted into a
percentage by dividing by the total number of residents within the tract. This served to control
for variations in the size of census tracts.
Demographic Variables
As indicated above, some of the demographic variables were calculated as a percentages of the
total population within a given census tract. Variables that were calculated this way included: %
African American and % Population over 50 Years. Other variables were calculated as percents,
but not calculated using the standard total population. Instead, there was a specific population
from which the variable was calculated. The % High School Diploma variable was calculated
using a total population that consisted of all people within a given census tract that were 25 years
of age or older. So, to determine the percent of the population that had attained at least a high
school degree, the number of residents that earned a high school diploma or higher was divided
by the number of residents in a given census tract that were 25 years of age or older. A similar
calculation was used to determine the % Unemployment variable and the % Manufacturing
variable, except that the total population in this case was considered to be residents in a given
census tract that were 16 years of age or older and who were in the labor force. When
determining the % Female Head of Households variable, the total population was considered to
be the number of households within a given census tract. Furthermore, the % Below Poverty
variable was calculated using a total population that consisted of a sample of residents for which
poverty status was determined. Finally, one of the demographic variables, Household Income,
was calculated as a median so as to not skew the data.
Housing Variables
Housing variables, such as % Owner Occupancy and % Other Vacant variables were calculated
the same as the demographic variables, except that the total population in this case was the total
number of housing units within any given census tract. For example, to determine the % Owner
Occupancy, the number of owner occupied housing units in census tract 25 was divided by the
total number of housing units in census tract 25. Other housing variables were calculated as
medians so that the data would not be skewed by extreme values. Housing variables that were
calculated as medians included: Median Housing Unit Value and Median Tenure.
Percent Change Over Time
To examine how some of the variables changed from one time period to the next, the percent
7
The total population of interest depended on the particular variable. All of the “total populations” are discussed
subsequently.
19
change over time was determined. This was calculated by computing the change from time
period one to time period two and dividing by the number at time period one. For example, to
obtain the percent change in population in census tract 15 from 1990 to 2000, the total
population in census tract 15 in 1900 was subtracted from the total population in census tract 15
in 2000; this was then divided by the total population in census tract 15 in 1990. If the outcome
was positive, that indicated upward growth; on the other hand, if the outcome was negative, that
indicated downward growth.
Dependent Variables for Data Analysis
As discussed earlier, there is no perfect measure of abandoned housing. Thus, analyses were run
using two of the best approximations of housing abandonment. One of the measures was
obtained from the US Census data. It included the number of housing units identified in the US
Census as being vacant not due to seasonal factors or sale purposes. These houses were
identified as “Other Vacant” in the Census. The second measure of abandonment consisted of
properties that were foreclosed upon and the titles reverted to the State of Michigan. These data
were collected on a yearly basis, but to run analyses against the independent variables, the
number of foreclosures had to be grouped by decade. For each of these dependent variable
measures, the actual number of “Other Vacant” or “State Foreclosure” housing units in each
census tract was divided by the total number of housing units in the same tract. This resulted in
dependent variables which were the percent of houses by census tract that were considered
abandoned using each measure.
These two measures of abandonment were not directly comparable because they represented
different periods of time. The “Other Vacant” dependent variable only represented the houses
considered abandoned at the time census data were collected. The “State Foreclosure”
dependent variable was obtained by adding the number of state foreclosures for each year of the
decade; it represented the number of houses considered abandoned during a ten year period. The
1990 “Other Vacant” measure, for example, reflected the current housing conditions in 1990,
while the 1990 “State Foreclosure” measure represented the percent of the houses abandoned in
the decade of the 1990s. When “Other Vacant” was the dependent variable, concurrent census
data were used to predict current vacancies. When “State Foreclosures” was the dependent
variable, census data were used to predict the housing abandonment in the upcoming decade.
Results
Dependent Variable Inter-Correlations
The inter-correlations of the dependent variables are presented in Table 3. This table shows that
the different measures of the dependent variables were positively correlated. A significant
correlation between dependent variables was found for 1980 and 1990; however, the 2000
“Other Vacant” variable was not significantly correlated with the “State Foreclosure” dependent
variable. For the most part, the size of the correlations was not great, with the exception of the
correlation of 1990 and 2000 “State Foreclosure.” The relatively small correlations between
time periods for the same measure indicate that there is much variation in the percent of
abandoned houses in census tracts across the years of the study.
20
Table 4.
Inter-Correlations of Abandonment as Measured by “Other Vacant”(OV) and “State
Foreclosure”(SF) for the Years 1980, 1990, 2000.
OV 80
OV 90
OV 00
SF 80
SF 90
SF 00
OV 80
OV 90 .784**
OV 00 .637**
SF 80 .622**
SF 90 .441**
SF 00 .408*
.784**
.637**
.566**
.622**
.465**
.279
.441**
.592**
.287
.439**
.408*
.558**
.256
.382*
.845**
.566**
.465**
.592**
.558**
.279
.287
.256
.439**
.382*
.845**
**Correlation is significant at the 0.01 level (2-tailed)
*Correlation is significant at the 0.05 level (2-tailed)
Analyzing Abandonment Using “Other Vacant” Data
Correlations between the independent variables and “Other Vacant” for each of the three time
periods were computed as a first step in modeling housing abandonment in Flint. These
correlations are shown in Table 4. The best predictors of housing abandonment are economic
variables. These variables include: % Unemployment, % Below Poverty, and Median
Household Income. All three variables consistently have the highest correlations in the expected
direction with abandonment. Other strong predictors are education as measured by % H.S.
Diploma, as well as Median Housing Value, and % Female Head of Households.
Table 5. Census Variables Significantly Correlated with “Other Vacant” for 1980, 1990 and
2000.
Year
Variable
1980
1990
2000
Spatial
Change in Housing Unit
-.686**
-.405*
-.446**
Median Housing Unit Value -.615**
-.541**
-.372*
% Owner Occupancy
-.524**
-.451**
-.462**
Socioeconomic
% African American
.422**
.280
.346*
% HS Diploma
-.707**
-.569**
-.485**
% Population >50 years
-.231
-.248
-.415**
Median Tenure
N/A
-.269
-.335*
Median HH Income
-.636**
-.518**
-.487**
% Below Poverty
.759**
.544**
.496**
% Female Head HH
.594**
.095
.348*
% Unemployment
.576**
.688**
.659**
Physical
Median Year HU Built
N/A
-.429**
-.241
** Correlation is significant at the 0.01 level; * Correlation is significant at the 0.05 level
21
The next step in the modeling process was to identify the best subset of independent variables
that predict housing abandonment in Flint. Using the stepwise selection procedure in the SPSS
version of multiple linear regression, a model for predicting housing abandonment was
developed for each year. As shown in Table 5, the model for 1980 includes % Below Poverty,
Change in Housing Units, and % Owner Occupancy as independent variables in the model. The
% Below Poverty accounted for 57.6 percent of the variance in abandonment as measured by
“Other Vacant.” The addition of the other two variables in the model accounts for an additional
14.9 percent of the variance in “Other Vacant.” In this model, greater poverty and greater
reduction in housing units predicts greater vacancy, as expected. Controlling for these variables,
however, resulted in % Owner Occupied being positively related to vacancy, as indicated by the
positive beta weight in the model, even though the bivariate relationship between ownership and
vacancy is negative. This anomalous finding may be explained by the multicollinearity of the
predictor variables.
In 1990, there were two variables in the model, % Unemployment and age of the housing stock.
The % Unemployment was entered first in the model and accounted for 47.3 percent of the
variance. On the second step, housing age was added, accounting for an additional 12.9 percent
of the variance. None of the other independent variables added a statistically significant increase
in variance accounted for.
In 2000, the model included three independent variables as shown in Table 5. The first variable
entered was unemployment which accounted for 43.5 percent of the variance in abandonment.
On subsequent steps, significant variance was accounted for by the addition of total population,
and percent owner occupied. The relationship of these three independent variables to “Other
Vacant” was in the expected direction and they accounted for a total of 57.2 percent of the
variance in abandonment.
Table 6. Stepwise Multiple Regression Analysis Using “Other Vacant” as a Measure of
Abandonment in 1980, 1990, and 2000.
Beta
t
1980
% Poverty
Change in Housing Unit
% Owner Occupied
.810
-.461
.394
5.44
-4.10
2.58
.000
.000
.014
.576
.096
.053
1990
% Unemployment
Age of Housing
.650
.362
6.16
3.43
.000
.002
.473
.129
2000
% Unemployment
Total Population
% Owner Occupied
.520
.421
-.386
3.82
3.21
-2.46
.001
.003
.019
.435
.063
.074
22
Significance
R2 Change
Year Variable
Analyzing Abandonment Using “State Foreclosure” Data
In this iteration, abandonment was measured by “State Foreclosure,” and the same sets of
independent variables were used as in the previous analyses. Table 6 displays the statistically
significant bivariate correlations of the independent variables and abandonment as measured by
“State Foreclosure.” In this table, independent variables from the 1980 census are correlated
with the state foreclosures that took place in the 1980s, the independent variables from the 1900
census are correlated with the foreclosures that occurred in the 1990s, and the independent
variables from the 2000 census are correlated with the state foreclosures from the 2000s. There
are a number of interesting results in the table. Significant relationships are found primarily for
the 1980s foreclosures, with fewer significant correlations with the 1990s foreclosures, and only
one significant correlation with the 2000s foreclosures. Most of the significant relationships
relate to socioeconomic conditions and are in the expected direction. The only anomaly is the
negative correlation found between Change in Housing Units and the percent of “State
Foreclosure” housing in the 1990s. This indicates that census tracts that lost housing units in the
1980s had a smaller percentage of foreclosures in the 1990s. It would be expected that more
abandonment would be related to loss of housing, as was found in the 1980s and the 2000s.
Table 7. Census Variables Significantly Correlated with “State Foreclosure” for 1980, 1990,
and 2000.
1980∆
Year
1990◊
2000±
Spatial
Change in Housing Unit
-.644**
Median Housing Unit Value -.460**
% Owner Occupancy
-.425**
.340*
-.251
-.381*
-.437**
-.219
-.171
Socioeconomic
% African American
% HS Diploma
Median HH Income
% Below Poverty
% Female Head HH
% Unemployment
% Manufacturing Employ
.148
-.362*
-.322*
.383*
.107
.313
-.010
.199
-.211
-.163
.239
.098
.213
-.078
Variable
.554**
-.589**
-.399*
.628**
.534**
.512**
.339*
Physical
None
** Correlation is significant at the 0.01 level
* Correlation is significant at the 0.05 level
∆
This variable consists of the number of state foreclosed upon properties from 1981-1989
◊
This variable consists of the number of state foreclosed upon properties from 1991-1999
±
This variable consists of the number of state foreclosed upon properties from 2000-2004
23
This unexpected finding for the 1990s could be the result of a highway that was built in Flint in
the 1980s that resulted in a loss of housing in census tracts with poorer, African American
residents. In these tracts, areas with a large percent of foreclosed houses were removed for
highway construction, possibly resulting in the positive correlation. More spatial analyses are
needed to confirm this speculation. For the following decade the only significant correlation was
with change in housing stock, and this time the correlation was in the expected direction. In
tracts where there was an increase in housing, there were fewer foreclosures and where there was
a reduction in housing there were more foreclosures.
Results of the regression analyses using the foreclosure data from the state are shown in Table 7.
As shown in the Table 7, the best predictors for the state foreclosures in the 1980s were Change
in Housing Units and % African American. For predicting foreclosures in the 1990s, the only
significant predictor in the model was % Below Poverty, and in 2000 Change in Housing Units
was the only significant predictor of foreclosures in the 2000s. Tracts with greater increases in
numbers of houses tended to have a smaller percentage of foreclosures.
Table 8. Stepwise Multiple Regression Analysis Using 1980, 1990, and 2000 Census Data to
Predict Abandonment as Measured by “State Foreclosures” in the 1980s, 1990s, and
2000s.
Year Variable
1980
Beta
t
Significance
R2 Change
Change in Housing
Unit
% African
American
-.644
-5.12
.000
.414
.441
4.1
.000
.186
1990
% Below Poverty
.383
2.52
.016
.146
2000
Change in HU
-.437
-2.95
.005
.191
Data Limitations
Although many of our results reinforced the pervasive idea that economic and social conditions
can have a big impact on housing abandonment, there were limitations to the data we used to run
the statistical analyses. The following sections details shortcomings with the data and how those
shortcomings were resolved.
Census Data: One of the issues with collecting census data was that tract boundaries shifted
over time. Census tract boundaries were consistent between 1990 and 2000; however, the 1980
census tract boundaries were different from later year boundaries. This made it difficult to
compare 1980 census data with the 1990 and 2000 data. This problem was partially solved by
24
purchasing Geolytics, a software program, which transformed the 1980 census tract boundaries
to the 2000 census tract boundaries. There were, however, certain variables that were available
for 1990 and 2000, but were not available for 1980 at the appropriate spatial scale. These
include: median year the housing unit was built and median length of residence for both owner
occupied and rental housing units. In addition, most of the percent change over time variables
that were calculated for 1990 and 2000 could not be calculated for 1980 because there was no
efficient method available to match 1970 census tract boundaries with 1980 census tract
boundaries.
Another limitation of using census data was that it only provided “snapshots” at 10-year
intervals. Because census data were used as independent variables, any other data collected had
to be grouped to conform to the 10-year intervals. While census data were useful in determining
changes in socio-economic and housing conditions, the temporal and spatial scales were so broad
that it was difficult to realistically track the nuances of change in variables and how these more
detailed changes may relate to housing abandonment.
State Foreclosure Data: The major problem with the state foreclosure data was that some of the
property records were missing vital information. There were 145 records missing parcel
identification numbers and 7 records missing the date of acquisition. Of the property records
missing parcel identification numbers, most were acquired during the 1960s, 1970s, and early
1980s. This made it impossible to use the complete data set to run statistical analyses or to
produce a map showing all of the foreclosed upon properties.
To serve as a dependent variable, the state foreclosure data collected had to be grouped to run
statistical analyses with the census data. As noted above, working with census data requires that
statistical analyses be run in 10-year intervals. This temporal scale is broad and, therefore, any
insight into the relationship between these data and housing abandonment that might have been
gained by using the longitudinal state foreclosure data was lost. Aggregating data to a broader
scale glosses over details that may play an important role in influencing housing abandonment.
Genesee County Data (Persistent Delinquency): To calculate which properties were in persistent
delinquency, the average of the taxes owed was calculated and then compared to 25% of the
assessed value for the last year of delinquency. For example, the property with parcel
identification #4731378033 had delinquent taxes owed in 1998, 1999, 2000, 2001, and 2002; the
amount of taxes owed was summed for the 5 years and then divided by 5 to figure out the
“average taxes owed.” The “average taxes owed” was then compared to 25% of the assessed
value of the property in 2002. If the “average taxes owed” was greater than 25% of the
property’s assessed value in 2002, then the property was considered to be in persistent
delinquency. The assessed value from the last year a property was listed as tax delinquent was
used because property taxes do not tend to fluctuate greatly from year to year in Michigan. This
is due to Michigan’s tax system, in particular the impacts of Proposition A which essentially
freezes taxable value at the point of purchase of the property and only allows revaluation at the
time of another transfer or sale (Audia and Buckley, 2005).
In addition, tax delinquency data from Genesee County were only available from 1997 through
2004. This was an issue because these data did not temporally match up the independent
25
variables collected from the census. Thus, these data could not be used as a dependent variable
for statistical analyses.
Data Collection at the Census Tract-Level: Although there were many socio-economic and
housing variables collected from the census, there were other variables that had to be collected
from other sources. The problem arose, however, when variables from other sources were not
available at the appropriate spatial scale (i.e., census tract). Unfortunately, there were several
variables that were either simply unavailable at the census tract-level or would have required
more time to collect than was allotted for this project. These included: building code violations,
crime statistics, voter participation, school quality, business applications, and predatory lending.
Thus, these variables were not used in the regression model. They could, however, still be
important components that affect housing abandonment. To ensure that these variables are
examined, additional resources would need to be mobilized.
Resident Interviews
Face-to-face interviews were conducted with current long-term residents during the months of
July-September 2005. Initial contact with long-term residents was made with the assistance of
the Land Bank; a few additional interviews were conducted as the result of referrals from those
individuals. A total of twelve long-term residents were interviewed; interviews ranged in length
from one to two hours; five of the interviewees were female; seven were male. While they
represented long-term residents, five of the twelve were also owners of residential rental property
in the city. Individuals were interviewed in the place of their choice; this included both their
homes and public locations like the Land Bank’s office and the Public Library. To conduct the
interviews we used a semi-structured interview technique; for all interviews notes were taken;
only four interviews were taped. An outline of core interview questions with prompts is included
in Appendix D. One additional “ad hoc” discussion was conducted with five individuals as part
of a neighborhood visit led by a long term resident. The findings from these interviews are
discussed below.
Before doing so, however, in our original research proposal additional interviews were proposed
for former Flint residents and individuals who have faced or gone through tax foreclosure. These
interviews have only been done on a very limited scale (i.e., two former residents using semistructured approach; one former resident as an informant) for two reasons: the first being a lack
of data and the second reflecting a mid-stream rethinking of our research approach to
foreclosure. In regards to data, in our original research proposal we indicated we would attempt
to trace residents who went through foreclosure through property and tax delinquency records.
Unfortunately, the data we finally obtained on foreclosure from the State of Michigan lacked
names, while data used for persistent delinquency have names but only cover the years 1997 to
2005. Delinquency data, which we have used to estimate a propensity to disinvest, are not a
reliable measure for actual foreclosure. Accessing former residents through current residents has
also born limited fruit. To access former residents we have adopted a third strategy which is
tapping the membership of “The Flint Club.” This strategy is discussed below in the section on
future research.
26
Discussion
As can be seen in the interview outline, residents were asked to “tell their story,” that is, provide
a largely personal, historical perspective on their experience living in Flint, including explaining
why they came to the city, how their neighborhoods have changed, why they continue to stay in
the city, what their perspective was on the city’s future and the prospects for success by the Land
Bank. Accordingly, the following themes regarding neighborhood change, abandonment, and
foreclosure arose in interviews with long-term residents.
Landlordism: Absentee Landlords and Difficult Tenants
Every long-term resident interviewee spoke of the issue of absentee landlords and the impact of
high levels of tenancy on their respective neighborhoods. As expected, absentee landlords were
seen as exacerbating neighborhood decline. One respondent, who estimated that 70% of the
properties on his block were rental, said his neighborhood was “owned by out-of-staters who just
remortgage, pull rent and get maximum value out of it” (R07.12.05-1). While long-term
residents did not like the investment-oriented decision-making of landlords, they clearly
understood it. Five long-term residents were also owners of rental property. Most commonly,
they purchased property in Flint via government sources (e.g., Veteran’s Administration, Federal
Housing Administration or HUD). Varying reasons were cited for becoming landlords,
including seeing economic opportunity, diversifying income sources, and ensuring their own
neighborhood quality by purchasing up surrounding properties.
According to these individuals, even the most well-intentioned landlord faces some very difficult
investment decisions. Incomes in the city are so low that rents cannot be high, but to be viable
they must at least cover the cost of the investment. One landlord indicated that his strategy for
investment and maintenance was determined by taxation policies. He indicated that local
politicians don’t like to raise property taxes on owner-occupiers, but since it was less politically
damaging they could raise taxes on rental properties. As a result of landlords are discouraged
from making any investment -- particularly cosmetic changes. He invested and maintained the
interior of the house, but didn’t make changes or improvements that improved the exterior of the
house. He indicated that while he wanted to put new siding on one of his properties, he wasn’t
doing so because it would attract the attention of the city assessor and increase his taxes
(R07.19.05-3).
A second observation here is the generally negative opinion of tenants held by both owneroccupiers and landlords. Renters were commonly depicted as a problem. Every interviewee had
a pet horror story of the rental property next door or the tenant “from hell” – that is the house
used for drug sales, the neighbor who burnt down their rental house and almost destroyed yours,
or the tenant who never paid and was unevictable.8 For owner-occupiers, a common complaint
was that renters did not respect other people’s property. A block club leader, for instance,
indicated that her club used to distribute pamphlets to new residents urging them to respect their
neighbors and their property. A second perceived problem with renters was transience.
8
We learned about a phenomenon called the “Eastside Eviction” whereby a landlord and a group of friends
essentially moves a problematic tenant and his/her belongings to the curb and forcefully emphasize that he/she is to
move out of the neighborhood.
27
Interviewees indicated that renters moved in and out so fast that it was difficult to get to know
them or develop ways to control who belonged or didn’t belong on their streets.9
Role of Children: Changing Housing Preferences and the Flint School System
As anticipated in our decision-making schematic, children and residential selection preferences
based upon the needs of children were cited numerous times as a reason for leaving Flint.
Residents indicated that while Flint had nice neighborhoods, the lots were small and older houses
lacked features (like multiple bathrooms) that many consumers want today. Additionally,
respondents indicated that the quality of the schools and school closings were important. Many
people perceived local schools as unsafe and impacted by drugs, which also contributed to
decisions to leave the city.
Role of Ownership Transition: Retirees, Inheritance, and Disinvestment
A third “common story” arising in the interview related to problems arising when an owneroccupier died and the house was passed onto survivors. Two interviewees, both of whom were
retired autoworkers, indicated that some people are still living in Flint because they can’t get the
value out of their homes. The death of such stable property owners was identified as ushering in
problems of disinvestment and blight. Specifically, several interviewees noted that following
deaths properties enter into a period of transition in which heirs must decide what to do with the
property. Several stories were given about heirs, particularly children, being uninterested in the
property and when they can’t sell or rent it easily they allow the property to fall into disrepair.
Periods of transition are particularly problematic if the house stands vacant. According to two
interviewees, vacant houses are particularly vulnerable to scavenging for valuable materials. On
the way to one interview, we observed that a nearby home was missing part of its vinyl siding.
According to the interviewee, she had stopped people from stripping off the siding by calling the
police. She said it was a pattern in her neighborhood that the house is stripped of siding and
windows, then used as a dumping ground, and finally suffers from a fire set by squatters or
adolescents (R07.14.05-4). Another interviewee identified one of the worst houses in his
neighborhood as a case involving probate. While heirs bickered over the property, it was
scavenged, vandalized and used as a dump (R07.12.05-1).
Role of Politics and Poor Leadership
Many long-term residents shared the perspective that local leadership has faltered in dealing with
the city’s problems. Three observations were offered. First, city leaders were depicted as not
taking the closure of factories and contraction of General Motors seriously. As the automotive
industry was historically cyclical in its employment base and profitability, leaders particularly in
the 1980s did not recognize the permanent nature of the change and thus were slow to act.
9
The Prevention Research Center of the School of Public Health at the University of Michigan conducts a
community survey in Flint and Genesee County every two years. Based on data from the 2003 and 2005 surveys
residency in the city is relatively stable and comparable to the county. For 2003, the average (mean) number of
years in a neighborhood was 14.70; for 2005 it was 14.05. Residency does vary significantly by age, the 2003
survey showed older residents (65+) residing in the city an average of 31.53 years. (No disaggregated data is
provided for the year 2005.) The survey did not present length of residency results by ownership or rental status.
(See http://www.sph.umich.edu/prc/products/survey_info.html for further data; accessed January 13, 2005).
28
Second, city leaders were characterized as consumed by in-fighting. One interviewee noted “the
City Council has fought every mayor” (R07.12.06-2). Third, city leaders were characterized as
having a reactive “slum clearance” mentality evidenced in demolition campaigns. Many
interviewees averred that the city had done little proactive to deal with the problem; in
particularly the city was accused of little or no code enforcement that might have prevented
severe blight.
Transience in the City: Moving Home
In reflecting on the city and their neighborhoods, interviewees emphasized that Flint in its
heyday was a city of immigrants. People were drawn to the city of Flint because of the well-paid
employment to be had at the factories. Immigrants came mainly from four states: Arkansas,
Mississippi, Louisiana and Tennessee. While no respondents agreed with a hypothesis that Flint
lost residents due to the assembly line workers winterizing cabins and moving “up north”,
several indicated that many workers had actually moved back down south to rejoin their families
in their states of origin. One African American interviewee noted that “it’s a lot easier to live
down south than it used to be” (R07.12.05-1).
Why Stay? Social Capital and Belonging
Overwhelmingly when asked why they stayed in Flint, long-term resident respondents indicated
that this was the place where they had friends and family. The proximity of children and lifelong
friendships kept these people in the city. When we asked one respondent who had come from
another state why he didn’t move home to his state of origin, he asserted that his home was
definitely Flint and that after so many years away he had little to return to. Additionally, the
importance of connections through and support activities provided by churches was also
highlighted specifically by three respondents. A few respondents did indicate that living in Flint
was also a smart economic decision for them. Property values are very low, but in the right
neighborhood or for a particular house with historic features, they could own a quality home that
he/she could not afford elsewhere. Finally, all respondents indicated a level of commitment to
the city and a desire to stay in the city to improve life there. This is not surprising given that the
majority of our contacts in this phase of the research were individuals known to or involved with
the Land Bank.
Recent Foreclosures: It’s the Economy Stupid!
Long-term residents were also asked to reflect on current levels of foreclosure in Flint and
determine whether the situation today varied with previous periods of neighborhood change in
the city. In general, respondents agreed that one basic economic reality was relatively constant
since the 1980s: economic opportunity and decent jobs are scarce in Flint. And since residents
own aging housing stock that requires significant maintenance in a weak property market
continuing to pay taxes on the house is often not economically sensible or even viable.
Interviewees pointed out that many people also had different priorities for their money.
Specifically, two interviewees spoke of the importance for younger residents of buying luxury or
more conspicuous consumer goods; others indicated that other expenditures on basic needs, like
an automobile due to the poor public transportation system, was displacing spending on housing
29
and/or taxes. The role of sub-prime lending only came up obliquely when one interviewee noted
that people were getting “those new types of mortgages” that only require payment of interest
and no down-payment, which she speculated was enabling people to buy houses that they
couldn’t afford (R07.19.05-2). One interviewee summarized the economic situation by simply
saying: “utilities are too high; income is too low and you’ve got to have a vehicle and insurance.
There just isn’t enough money for it all.” (R07.12.05-1).
Conclusions And Directions For Future Research
Conclusions
This research project, to close, underlines the importance of recognized economic and social
factors in neighborhood change and abandonment. In both the modeling and the resident
interviews, economic factors such as poverty and unemployment and social factors such as
owner-occupancy, race and educational levels were identified as related to abandonment in Flint.
Notably, physical factors such as the age of housing did not emerge as significant in the
modeling, although consumer preferences were discussed by interviewees.
Given that factors such as poverty, unemployment and educational attainment are structural in
nature, the probability that an intervention like the Genesee County Land Bank can successfully
address abandonment and “reinvent” the city of Flint is low. The Land Bank is doing good work
that is valued by the city’s residents – it is cleaning up neighborhoods, removing blighted
housing and increasing parcel sizes for remaining residents. The city, however, fundamentally
needs economic opportunities for its residents and this requires statewide leadership and
commitment of public monies to the city’s future. Given that the state’s economy is also
experiencing great difficulties and the inability of the state’s legislature and governor to agree on
an economic recovery strategy, the prospect of such opportunities appearing in Flint, at least in
the short term, is slim.
Future Research
At this point in time, the immediate direction for our research is to complete the interview
processes underway and investigate the potential use of spatial statistics to better understand
abandonment as a geographically situated and mobile phenomenon. Our research to date has not
delved into the drivers of current foreclosure activity in a way that more viable prevention
polices can be crafted. A new research approach has been formulated and is briefly discussed
below.
Interviews with former residents via Flint Club: As noted earlier, we have had only limited
success in contacting former Flint residents. A number of factors come into play here, including
aforementioned data problems and the passage of time. In the last several years, however, a
group of expatriate Flint residents have coalesced and formed a group called “The Flint Club.”
The mission of the Flint Club, as explained on the club’s website (www.flintclub.org), is “to
connect people to the life of the city regardless of where they live.” The organization is
organized as a non-profit and has approximately 500 members who are dispersed around the
country, with some still resident in the city and in Genesee County. The group hosts a number of
30
events in and about the city each year; in addition, they provide scholarships for Flint and Flintarea schools. We have made initial contact with the group and have scheduled a series of
interviews with members.
Researching foreclosure across Michigan cities with land banks: Due to the various factors
noted above, we have not been able to answer our overarching question regarding what is driving
foreclosure in the contemporary period in Flint. A change in methodology is clearly needed.
What has been suggested is to determine which property owners in Flint are “at risk” of losing
their properties through foreclosure and follow those property owners over time to see how they
make decisions regarding their property and identify what factors or life circumstances affect
those decisions.10
We have taken this core idea and expanded it in light of the continuing experimentation with
land banking that is taking place in various locations across the state. Currently, an additional
eight county governments in Michigan are in the process of establishing land banks. With
technical assistance provided by the Genesee Institute, these counties are drafting rules for their
corporate governance, electing or appointing members of their governing boards, and
establishing procedures for the disposition, sale, and rehabilitation of properties, among many
activities needed for establishing this type of authority (Alexander 2005.) Interestingly the
counties that have chosen to establish land bank authorities range from places with little problem
with abandonment (i.e., Grand Traverse County) to localities with an urban abandonment
problem comparable to Genesee County (e.g., Saginaw County). Our revamped research
approach is to identify “at risk property owners” in matched pairs of Michigan communities (one
community with a land bank paired with a “like” community without a land bank) to understand
decision-making and the impact the presence of a land bank has (or does not have) on decisionmaking and propensity to become tax delinquent. For further methodological and conceptual
details, please see Appendix D.
10
This very helpful suggestion came from Dr. Yu-Hung Hong, a fellow at the Lincoln Institute of Land Policy
during a meeting held in July 2005. Thank you again for your comments on the research and assistance with
rethinking our methodology.
31
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Maric, I., R. Quercia, and R. Simons. 1998. “The Value Impact of New Residential
Construction and Neighborhood Disinvestment on Residential Sales Price” Journal of
Real Estate Research 15, 1 and 2: 147-161.
McConville, S., P. Ong, et al. (2001). Examining Residential Segregation. Los Angeles,
University of California Los Angeles, Ralph and Goldy Lewis Center for Regional Policy
Studies: 15.
McCoy, P. 2005. Elder Law: A Behavioral Analysis of Predatory Lending, 38 Akron L. Rev.
725.
Powell, J. 2002. “Sprawl, Fragmentation, and the Persistence of Racial Inequality: Limiting
Civil Rights by Fragmenting Space.” In Urban Sprawl: Causes, Consequences, and
Policy Responses, G. Squires, ed., Washington, DC: Urban Institute Press, pp. 73-118.
Putnam, R.D. 2000. “Bowling Alone.” New York, New York: Simon & Schuster.
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Research for Democracy, 2001. “Blight Free Philadelphia.” Philadelphia: Eastern Pennsylvania
Organizing Project and Temple University Center for Public Policy.
Rossell, C.H. 1975. “School Desegregation and White Flight.” Political Science Quarterly 90:
675-695.
Roy, J. 2004. “Effect of School Finance Reform on Housing Stock and Residential Segregation:
Evidence from Proposal A in Michigan.” Princeton University.
Schwirian, K.P. 1983. “Models of Neighborhood Change.” Annual Review of Sociology 9: 83102.
Shlay, A.B. and G. Whitman. 2004. “Research for Democracy: Linking Community Organizing
and Research to Leverage Blight Policy.” Retrieved June 21, 2005, from University of
Toledo Web site: http://comm-org.utoledo.edu/papers2004/shlay/.
Spivack, R.N. 1987. “The Determinants of Housing Abandonment: A Case Study of
Providence, Rhode Island.” Northeast Journal of Business & Economics 13, 2: 15-32.
Squires, G. 2002. “Urban Sprawl and Uneven Development of Metropolitan America.” In
Urban Sprawl: Causes, Consequences, and Policy Responses, G. Squires, ed.,
Washington, DC: Urban Institute Press, pp. 1-22.
Sternleib, G., R.W. Burchell, J.W. Hughes and F.J. James. 1974. “Housing Abandonment in the
Urban Core.” Journal of the American Planning Association 40, 5: 321-332.
Taylor, R.B, B.A. Koons, E.M. Kurtz, J.R. Greene and D.D. Perkins. 1995. “Street Blocks with
More Nonresidential Land Use Have More Physical Deterioration: Evidence from
Baltimore and Philadelphia.” Urban Affairs Review 31, 1: 120-136.
White, M.J. 1986. “Property Taxes and Urban Housing Abandonment.” Journal of Urban
Economics 20, 3: 312-330.
Wilson, D., H. Margulis and J. Ketchum. 1994. “Spatial Aspects of Housing Abandonment in
the 1990s: The Cleveland Experience.” Housing Studies 9, 4: 493-510.
35
Appendix A: Interviews Conducted
Interview ID
Type of Respondent
1. I12.08.05-1
2. I03.18.05-1
3. I03.28.05-1
Informant
Informant
Informant
Date of
Interview
12/08/2004
03/18/2005
03/28/2005
4.
5.
6.
7.
8.
9.
Informant
Informant
Informant
Informant
Informant
Informant
03/18/2005
03/18/2005
03/18/2005
04/15/2005
07/09/2005
08/15/2005
10. R07.12.05-1 Long Term Resident- Owner
Occupier and Rental Property
Owner
11. R07.12.05-2 Long Term Resident- Owner
Occupier and Rental Property
Owner
12. R07.12.05-3 Long Term Resident
13. R07.12.05-4 Long Term Resident
14. R07.14.05-1 Long Term Resident- Owner
Occupier and Rental Property
Owner
15. R07.14.05-2 Long Term Resident- Owner
Occupier and Rental Property
Owner
16. R07.14.05-3 Long Term Resident
17. R07.14.05-4 Long Term Resident
18. R07.19.05-1 Long Term Resident-Owner
Occupier
19. R07.19.05-2 Long Term Resident- Owner
Occupier and Rental Property
Owner
20. R07.19.05-3 Long Term Resident- Owner
Occupier and Rental Property
Owner
21. R07.19.05-4 Long Term Resident
22. R12.13.05-1 Resident (recent arrival, ~5
years)
07/12/2005
I03.18.05-1
I03.18.051
I03.18.05-2
I04.15.05-1
I07.09.05-1
I08.15.05-1
36
Place/Method
Flint, face to face interview
Flint, face to face interview
East Lansing, face to face
interview
Flint, face to face interview
Flint, face to face interview
Flint, face to face interview
Lansing, face to face interview
Telephone interview
East Lansing, face to face
interview
Flint, face to face interview
07/12/2005 Flint, face to face interview
07/12/2005 Flint, face to face interview
07/12/2005 Flint, face to face interview
07/14/2005 Flint, face to face interview;
neighborhood tour
07/14/2005 Flint, face to face interview;
neighborhood tour
07/14/2005 Flint, face to face interview
07/14/2005 Flint, face to face interview
07/19/2005 Flint, face to face interview
07/19/2005 Flint, face to face interview
07/19/2005 Flint, face to face interview
07/19/2005 Flint, face to face interview
12/13/2005 Flint, face to face interview
Interview ID
Type of Respondent
23. R12.13.05-1
Resident (recent arrival,
~5 years)
Former Resident
Former Resident
24. R10.06.05-1
25. R12.02.05-1
Date of
Interview
12/13/2005
Flint, face to face interview
10/06/2005
12/02/2005
Telephone interview
Telephone interview
37
Place/Method
Appendix B: Maps Of Demographic Information, Vacancy And Tax Foreclosed Properties
38
39
40
41
42
43
44
45
Appendix C: Modeling Property Abandonment
Model 1: Dependent variable = Foreclosed properties (Locally available proxy for abandonment)
Model 2: Dependent variable = Other Vacant measures (US Census proxy for abandonment)
Operationalized: % houses and/or parcels in said state, geo unit x, time y
Variable
Hypothesized Measurement
Relationship
Unit
Spatial Variables (Measuring Neighborhood
Quality/Urban Form)
Code
↑ violations ↑ % (# code
Violations
violations/total
abandon
housing units in
geographic area)
Source of
Data
Data obtained
(Y/N); Explain
Rationale
City of
Flint
Vacant Housing ↑ vacancy ↑
abandon
% (# vacant
units/total units
in geo area)
US Census
N: Code violation
data were not
available for the
temporal and spatial
scales needed.
Y: Data were
collected from the
U.S. Census for both
total vacant housing
units and “other”
vacant housing
units.
Demolished
property
# of units
demolished in
geo unit in time
period y
City of
Flint
GCLB
Lack of maintenance means house is
being neglected; indicator of
disinvestment (Hillier et al., 2003;
Culhane and Hillier, 2001; Arsen,
1992)
(Only for foreclosure analysis)
Vacant housing indicator of an
undesirable neighborhood; poor
neighborhood conditions raise house
moving behavior (Hillier et al., 2003;
Accordino and Johnson, 2000;
Greenberg et al., 1994; Kearns and
Parkes, 2003)
Demolition could improve
neighborhood (e.g., remove crack
house), could also be indicator of
advanced decay/neglect (Bender,
1979)
Unsure
Y: Reduction in
housing units from
one time period was
a proxy for
demolished housing.
46
Variable
Hypothesized Measurement
Relationship
Unit
Spatial Variables (Measuring Neighborhood
Quality/Urban Form)
Delinquent
% (# units in
↑ arrears ↑
Property
arrears/total
abandon
units in geo
area)
Source of
Data
Data obtained
(Y/N); Explain
Rationale
GC
Treasurer
GCLB
Y: Properties in
which 25% or more
of the assessed value
was owed in taxes
for X year was
assumed to be
persistently
delinquent
Y: U.S. Census
No taxes being paid means house is
being neglected (Maric, Quercia and
Simons, 1998; White, 1986;
Baldassare, 1981)
Housing Value
↓ value ↑
abandon
Avg. assessed
value for geo
unit
Owner
occupancy
↑ occupancy ↓
abandon
Y: U.S. Census
Dis-amenities
↑ disamenities ↑
abandon
% owneroccupied
houses/#
housing units in
geo area
# of toxic release DEQ
sites per geo unit EPA
(permits)
Amenities
↑ amenities ↓
abandon
# of amenities in
geo unit
(schools, parks,
hospitals)
N:
Treasurer
City of
Flint
Assessor
Census
Treasurer
N:
Treasurer
47
Lower assessed values indicate less
desirable neighborhoods (Accordino
and Johnson, 2000; White, 1986)
Owner occupancy encourages
investment for housing maintenance,
which can translate into neighborhood
stability (Spivack, 1987; Sternleib et
al., 1974)
Pollution decreases property value;
lowered value equates with weaker
property market/greater potential
abandonment (Hite, 2002; Greenberg
et al., 2000; Leigh and Gradeck, 1996;
Greenberg et al., 1994)
Proximity to amenities positively
related to housing value (Li and
Brown, 1980; Bender, 1979)
Variable
Hypothesized Measurement
Source of
Relationship
Unit
Data
Socioeconomic Variables: (Measuring social characteristics;
economic performance)
Race
% African
Census/
↑ minority ↑
American
in
Tract level
abandon
census tract
Data obtained
(Y/N); Explain
Rationale
Y: U.S. Census
Increased level of minorities and
renters give lower housing values
(Maric, Quercia and Simons, 1998;
Sternleib et al., 1974)
Less disposable income for
maintenance (Cohen, 2001; Maric,
Quercia and Simons, 1998; Arsen,
1992)
Female headed-households correlate
with lower income levels (Leavitt and
Saegert, 1988; Sternleib et al., 1974)
Higher level of education correlates
with higher lifetime earnings;
Increased ability of people to navigate
the process of buying and maintaining
a house, as well as negotiate rental
agreements (Taylor et al., 1995)
Higher level of unemployment leads
to a decrease in financial resources,
which reduces money available for
upkeep; may influence out migration
(Bowman and Pagano, 2000; Wilson
et al., 1994)
Housing consumers not indifferent to
cost and quality of public services;
school quality major factor in
neighborhood selection (Li and
Brown, 1980)
Poverty
↑ poverty ↑
abandon
% HH at or
below poverty
Census/
Tract level
Y: U.S. Census
Female head of
household
↑ FHH ↑
abandon
Census /
Tract
Y: U.S. Census
Educational
Achievement
↑ years
schooling ↓
abandon
% HH Female
Headed per geo
unit
% population
with high school
diploma per geo
unit
Census /
Tract
Y: U.S. Census
Unemployment
↑
unemployment
↑ abandon
Census
BEA /
BLS
Y: U.S. Census
School Quality
↑ graduation
rates ↓
abandon
% workforce
unemployed in
Flint/%
workforce
unemployed
nationally
Graduation rate
(look into
MEAP scores)
Departmen
t of
Education;
MI DoEd
N:
48
Variable
Hypothesized Measurement
Source of
Relationship
Unit
Data
Socioeconomic Variables: (Measuring social characteristics;
economic performance)
School
% Flint student
Flint
↑ busing ↑
desegregation
body bused
School
abandon
System
Data obtained
(Y/N); Explain
Rationale
N:
Busing for racial integration of
schools causal factor in white flight
from American core cities (Clotfelter,
1999, 1979, 1976, 1975; Rossell,
1975)
Neighborhood elementary schools
encourage neighborhood stability and
provide incentive for families to stay
and invest in houses/neighborhood;
schools major factor in residential
purchase decisions; neighborhood
schools enhance property values
(Bogart and Cromwell, 2000, 1997)
Increased length of residence
correlates with long-term investment
in the community (Leavitt and
Saegert, 1988; Sternleib et al., 1974)
A decrease in manufacturing
employment correlates with housing
abandonment, particularly in areas
that are dependent on it as an
employment anchor; may influence
out migration (Cohen, 2001)
Safety priority for housing purchaser;
negative relationship between crime
and housing value/desirability of
neighborhood (Accordino and
Johnson, 2000; Greenberg et al.,
1999; Greenberg et al., 1994)
Elementary
schools
↓ # of schools
↑ abandon
# of elementary
Flint
schools in city of School
Flint (need
System
location in space
of close schools)
Length of
residence
↑ residence ↓
abandon
Median length of Registrar
Y: U.S. Census
residence in
of Deeds
census tract
(?); Census
Structural
composition of
employment
↓
manufacturing
employment ↑
abandon
% change in
manufacturing
employment for
geo unit
US Census
Y: U.S. Census
Crime
↑ violent
crime ↑
abandon
% change over
time in per
capita rate (per
category of
violent crime for
geo unit)
City of
Flint
Police
Dept.
UM Crime
Data
N: Crime data were
unavailable for the
temporal and spatial
scales needed.
Y: Current Flint
school addresses
were obtained from
the yellow pages.
49
Variable
Hypothesized Measurement
Source of
Relationship
Unit
Data
Socioeconomic Variables: (Measuring social characteristics;
economic performance)
Voter turnout
County
↑ voter turnout # voters per
precinct for city Clerk
↓ abandon
council elections
Economic
# new business
City or
↑ new
activity
applications/per
state
business
mits for geo unit licensing
licenses ↓
abandon
Predatory
lending
↑ predatory
lending ↑
abandon
% of new
mortgages per
geo unit
HMDA
data
Age of city
residents
Unsure
Avg. age of
residents in each
census tract OR
% of residents
>65 by census
tracts
Census
Data obtained
(Y/N); Explain
N: Turnout date
over time
unavailable.
N: Used
employment as
proxy for economic
activity.
Rationale
Higher voting participation correlates
with higher social capital (Putnam,
2000)
Businesses moving into an area
suggests a level of economic growth
and a potential for in migration of
people and financial resources;
occupation, repair, and maintenance
of housing units is likely to increase
(Bowman and Pagano, 2000)
N: Data were only
Lending practices that encourage
available from 1997- people to take on mortgages with
2003. Charts and
extraordinarily high interest rates
Maps were obtained increases the likelihood that
for those years.
borrowers will have to forfeit the loan
and foreclose on the property, thus,
facilitating abandonment (Shlay and
Whitman, 2004; Lopez, 1999; Engel
and McCoy, 2002; Lauria et al., 2004)
Y: U.S. Census
Area dominated by middle-aged
residents may indicate neighborhood
stability, whereas an area dominated
by elderly residents may indicate
either neighborhood stability or an
increased likelihood of abandonment
because there are not younger
residents to move into housing stock
(Leavitt and Saegert, 1988)
50
Variable
Hypothesized Measurement
Source of
Relationship
Unit
Data
Socioeconomic Variables: (Measuring social characteristics;
economic performance)
Income
Median HH
Census
↑ income ↓
income
for
Flint
abandon
City/Median HH
income for Flint
MSA
Change in
aggregate
population
↑ Change in
population ↑
abandon
% change in
populationaggregate
decrease by
census tract
Physical Variables (Measuring Quality of Housing
Stock)
Age of housing ↑ age ↑
Avg. age of
housing stock in
abandon
census tract
Census
Data obtained
(Y/N); Explain
Rationale
Y: U.S. Census
A higher level of income suggests a
higher education level; Indicates that
there is more disposable income for
maintenance (Cohen, 2001; Taylor et
al., 1995; Baldassare, 1981; Bender,
1979)
Increase in out migration of residents
correlates with housing abandonment
because the supply of housing stock
eventually becomes greater than the
demand, causing houses to be left
vacant (Bowman and Pagano, 2000)
Y: U.S. Census
Treasurer’s Y: U.S. Census
office/ per
unit;
Assessor
51
Building life cycle theories suggest
older housing stock is usually
occupied by residents that either do
not have the financial resources or
skills to ensure upkeep, or they are
unable to influence a landlord to
perform necessary maintenance
increasing the likelihood of
abandonment (O’Flaherty, 1993;
Arsen, 1992; White, 1986; Schwirian,
1983; Bender, 1979; Anas, 1978)
Variable
Hypothesized Measurement
Relationship
Unit
Physical Variables (Measuring Quality of Housing
Stock)
Parcel size
↓ parcel size ↑ Avg. parcel size
for geo unit in
abandon
square feet
Structure size
Ratio between
the above
variables
Policy
Variables:
Open Housing
Ordinance,
1968
(Fair housing)
Proposal A,
1994 (School
finance)
↓ house size ↑
abandon
Source of
Data
Data obtained
(Y/N); Explain
Rationale
City of
Flint
Assessor
GCLB
N: Used age of
housing stock as
proxy.
Avg. house size
for geo unit in
square feet
City of
Flint
Assessor
N: Same.
Small- or irregular-sized parcels less
desirable; houses on these lots more
likely to become and remain vacant
(Bowman and Pagano, 2000; Adams
et al., 1988)
Residential preferences in post-War
period have shifted toward larger
homes on larger lots; smaller-sized
houses are less desirable (many
authors; conventional wisdom)
Treasurer’s
office/ per unit;
Assessor’s Data
See above
N: Same
↑ Open
Housing ↑
abandon
Whites’ strong aversion to racially
mixed neighborhoods major factor in
US residential segregation (Ihlanfeldt
and Scafidi, 2004)
Proposal A aims to equalize school
quality; Flint currently receives a high
level of state funding for schools and
it is unclear whether this policy has
any influence on the migration of
people to find better funded schools in
the area (Roy, 2004; Arsen et al,
2005)
Unsure
52
Variable
Policy
Variables:
Proposal A
P.A. 123, 1999
(Michigan
Property Tax
Foreclosure
Law)
Hypothesized
Relationship
Measurement
Unit
Source of
Data
Data obtained
(Y/N); Explain
Unsure
Rationale
Proposal A also freezes taxable value;
reassessment takes place at time of
sale. Holding property taxes steady
could assist struggling property
owners; decreased levels of municipal
finance, however, create greater
difficulty for cash strapped central
cities and impede provision of
services (like code enforcement).
(Audia and Buckley, 2005).
Reduced time to foreclosure has taken
property owners by surprise and
resulted in accelerated rates of
foreclosure. (e.g., Detroit News
accounts of Wayne County)
↑ Tax
Foreclosure
Law ↑
abandon
53
Appendix D: Questions For Semi-Structured Interviews
Four types of interviewees:
1) Informant interviews (e.g., MSU contacts, Genesee CED)
2) Current, long-term residents of Flint (owner occupiers)
3) Residents who have gone through foreclosure (recent foreclosure, identified by Genesee
County Treasurer’s Dept. or Land Bank staff)
4) Residents who left Flint and moved elsewhere (smallest sample)
Potential questions/interview sequence
1)
Gather basic demographic data
1. Sex, age, occupation, education level, family size
2)
Residency:
1. Length of residency in Flint
2. Length in current home
3)
Neighborhood description:
1. Define “your” neighborhood (using map, indicate what they consider boundaries
of their neighborhood).
2. Are most of these homes owner-occupied? Tenants? Who owns the rental units?
4)
Neighborhood change:
1. How has your neighborhood changed in the period in which you lived here?
(Look for timeline, events)
2. What do you feel are the main causes of change within your neighborhood?
(Listen for factors identified in the theoretical model; e.g., race, open housing law,
layoffs, housing quality, crack, school closings, etc.)
3. Satisfaction with neighborhood:
i. Former residents: Were you satisfied with your living conditions in Flint
before you sold/left your property?
ii. Current residents: Are you satisfied with your current living conditions in
Flint? What do you like most about your neighborhood? What do you
like least?
5)
Neighborhood response/social capital:
1. How have you and your neighbors responded to the changes you have seen in
your neighborhood?
2. Do you know your neighbors?
3. (Literature indicates the importance of being able to cope with stress)
i. Do the conditions of your neighborhood bother you?
6)
Decision-making and Ownership:
• Current Residents
1. Do you ever think about leaving Flint? (Or: why have you remained in the
city?). Would you leave Flint if you had the opportunity?
2. Why have you remained a property owner when so many others have left?
(Listen for factors. Is it one primary factor or a combination of factors?)
3. Have you had close friends or neighbors move out of the city? Why did they
decide to move? (Or “why do you think they decided to move?”) Where did they
go? Do you know people who have abandoned their property and left Flint?
54
Why do you think they made that decision? (Potential prompt: Were their
circumstances different than yours?)
•
7)
Former Residents
• What were the reasons that led you to leave Flint? (Listen, potential prompts:
What factors led to this decision? Was it primarily one factor or was it a gradual
accumulation of factors? Did you make a conscious decision or was it forced on
you?)
• Were you able to sell your house? To whom did you sell it? (E.g., owneroccupier; landlord)
• Do you know people who have remained in Flint? How were their circumstances
different than yours?
Foreclosure:
• Current and Former Residents (not foreclosed upon)
1. Have you had any neighbors or friends who have lost their homes to foreclosure?
Did the bank foreclose on them or the county?
2. What happened to cause them to go into foreclosure? (Listen for factors associated
with theoretical model, including predatory lending, literacy, layoffs, etc.)
• Foreclosed upon Residents
1. When did your property first start to collect tax arrears? Why did your property start
to collect tax arrears? (Alt: What circumstances led to non-payment of taxes and
foreclosure?)
2. Did you work with the Land Bank to prevent foreclosure? (Yes/No). If yes, what
was your experience with the Foreclosure Prevention Program?
3. Did you have a mortgage on the foreclosed property? Did you have difficulty paying
your mortgage prior to tax foreclosure? From whom did you get the mortgage? (If
possible, what was the interest rate on your mortgage?)
55
Appendix E: Future Research On Land Banking And Owner Decision-Making
Title:
Land Banking and its Effects: Examining “At Risk Property Owners” in
Michigan
Investigators: Ellen M. Bassett and John Schweitzer, Michigan State University;
Robert Beckley, Genesee Institute
Introduction
The state of Michigan has the unfortunate distinction of being home to some of the most troubled
cities in the United States. Older industrial cities such as Detroit, Flint, Saginaw and Pontiac are
characterized by widespread blight, disinvestment and abandonment of housing. They are also
distinguished by concentrated poverty, severe racial segregation, and high rates of violent crime.
While there are myriad reasons for the sorry state of Michigan’s central cities, one factor
identified as exacerbating urban blight and housing abandonment was the state’s former system
of tax lien sales (CRC, 2000). Under this system, county governments sold liens on tax
delinquent properties at auction to private individuals.11 The interest of most private lien
purchasers generally was not property itself, but redeeming the taxes owed by the owners and
even exacerbating their indebtedness through interest and fees. However, if the property taxes
on the property were not paid, the tax lien holder had the opportunity to take title of the property
and displace residents. If the subject property was an owner occupied unit, the foreclosed upon
house might become rental; alternatively the new owner -- having little interest in the house itself
-- might simply let it stand vacant and in turn fail to pay taxes on it. The tax lien sales system,
thus, did not bring properties back into productive use -- rather it contributed to the downward
spiral of older urban neighborhoods.
A significant reform of state’s property tax foreclosure system began in 1999 with the passage of
Public Act 123 and a package of complementary legislation. Taken together this legislation has
significantly reduced the time necessary for moving a property from delinquency to foreclosure;
foreclosure now can occur in 24 months or less, while under the previous system it often took up
to five years (Kildee, 2005). PA 123 also streamlined administrative procedures around
foreclosure by giving the county the right to become tax-foreclosing units of government
responsible for foreclosed properties. Tax lien sales have been eliminated and speculators are no
longer able to purchase liens or add their owner interest and fees to their claim. Finally, the
legislation included a title clearance provision that enables the removal of liens from properties
en masse through an administrative procedure. This last provision is significant as under the
previous system title clearance could only be effected on a parcel-by-parcel basis in the circuit
courts.
These reforms have been augmented other legislation, most significantly by Public Act 258 of
2003, known as the Michigan Land Bank Fast Track Authority, and alterations to Michigan’s
11
Properties with unsold liens and unredeemed property taxes reverted to state government, specifically the
Department of Natural Resources or local government for management (CRC, 2000). Notably, the market for liens
on tax delinquent properties was weaker in urban areas with only 43% of parcels in urban counties selling at auction
in comparison with 62% of parcels located in rural counties.
56
Brownfield Redevelopment Act. PA 258 allowed counties that opted to become tax-foreclosing
units of government to establish Land Bank authorities. Land Bank authorities have been given
the right to acquire, assemble and dispose of property. The legislation also established expedited
quiet title and foreclosure processes for property held by an authority. Significantly, property
held by the authority is exempted from property taxes for five years. The properties held by an
authority are also considered brownfields, a categorization that enables land banks to access
significant financing for redevelopment.
Changing the state’s rules for foreclosure has introduced new opportunities for Michigan local
governments to deal with disinvestment and abandonment. By speeding up the process of
foreclosure and eliminating tax lien sales to private individuals, the cycle of abandonment
perpetuated by absentee, rent-seeking private lien holders who failed to invest in property
maintenance or rehabilitation has effectively been broken.
Problem Statement
Although the new system for tax-reverted properties is encouraging for its ability to deal with
property after tax-reversion, the system provides only limited means for dealing with the
problem of tax delinquency itself. County treasurers have the ability to postpone foreclosure due
to a family’s financial hardship. This measure was adopted to insure that the decrease in time
given for payment of taxes did not adversely affect struggling families who are striving in good
faith to pay their bills. In Genesee County, the county that pioneered land banking in the state, a
tax-foreclosure prevention program has been established. Through this program, owners facing
foreclosure can obtain an extension for paying their tax obligation and develop a plan for dealing
with future tax bills, approximately 300 households have been assisted in each tax year since
1999 when the county opted to become a tax foreclosing unit of government.
While encouraging, the tax foreclosure prevention program is essentially reactive in nature.
Individuals are often deeply indebted by the time they contact the program; the county treasurer
while sympathetic to their plight also has an obligation to taxpayers of the county to ensure that
taxes are paid and sufficient revenues raised for county services. Foreclosure prevention in the
form of deferring or rescheduling payments cannot go on indefinitely.
The Research Project
The purpose of this research is to help the Genesee Institute and the Genesee County Land Bank
(and hence the nascent land banks across the state of Michigan) to formulate more effective
programs by obtaining a greater understanding of how owners make decisions about their urban
property, including identifying the key factors that influence their decisions to meet or avoid/not
meet the key ownership obligation of property tax payment.
Research Questions
In this research project, we proposed to conduct a systematic study to understand:
1) How do owners make decisions in relation to investment in their property and payment of
taxes? Why do some owners meet their ownership obligations (i.e., maintenance, tax
payments) while other similarly situated owners fail to invest in their properties and/or
fall into tax delinquent status? Further, do owners of investment properties differ from
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owner-occupiers in the range of factors they consider when making investment and tax
payment decisions?
2) What is the relative influence of land bank activity on the investment/tax payment
decisions of property owners? Do landowners in cities with active land banks act
differently from owners in cities with less attention being paid to blight and
abandonment? In particular, do the activities of the land bank have appreciable impacts
on owners’ perception of the viability of their local land market and the future
value/salability of their property? For example, does the presence of a land bank and its
activity affect an owner’s impulse to “cut one’s losses” by disinvestment, tax avoidance,
or early departure from the property market?
Theoretical Perspective
Theoretically this research departs from and wishes to test key tenets of economic sociology.
Briefly put, economic sociologists reject the central principle of neoclassical economics, that is,
they reject the completely rational, utility maximizing idea of “the economic man” (Beckert
2003). Human decision-making never fits this ideal: economic actors do not have perfect
information, their preferences change over time and space, and decisions take place in
environments defined by institutional parameters such as law and culture. To really understand
economic decision-making, economic sociologists stress the need to understand the sociallystructured economic context in which the economic actor is locally situated or “embedded” (e.g.,
Granovetter, 1992).
Two key assumptions are derived from this theoretical perspective.
1) Decisions are made in a cost-benefit framework. However, the factors that different
decision-makers balance in their internal calculus/decision-making are not universal,
rather decision-making is situation specific and embedded. There are expected
differences in behavior and decision-making between investment owners and owneroccupiers because they are embedded in different contexts.
For owners of investment properties, economic theory and previous research suggests that the
chief motivation for owning rental property is profit; property taxes are an important factor
affecting the profitability of the investment (Arsen 1992, White 1986, Bartelt and Lawson 1982).
In a system of constrained rents (due to lower income tenant populations), owners seeking to
maximize their profits will put off payment until the last possible date, particularly if the penalty
for late payment is lower than the potential income earned off of that money elsewhere. When
the costs associated with the house (e.g., mortgage, maintenance, insurance, taxes) become
greater than income flows, investment owners can be expected to begin disinvesting in the house
(leading to blight) and holding off on payment of obligations, like their mortgage and/or taxes.
In the case of property markets where the cost of entry is very low (e.g., the cost of some housing
in Flint, for instance, being just the price of the tax lien), tax default by owners may occur
without defaulting on mortgage obligations.
For owner-occupiers, reasons for failing to maintain property or pay property tax are expected to
be more complex. Like investment owners, owner occupiers are expected to balance benefits
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and costs and can be expected to withhold investment in their house (in the form of maintenance)
or withhold tax payments if the costs associated with the house outweigh the benefits. In the
case of owner-occupiers, however, the benefits and costs included in their calculus are expected
to be broader than those of non-resident, profit-driven investment owners. Owner-occupiers, for
instance, may value social benefits (i.e., the sentimental value of the home as a place of family
heritage or the benefit of their established social network) higher than investment-oriented
owners. Owner-occupiers calculus may differ from investment-oriented owners in that they also
bear first hand the negative externalities in their physical environment, like crime and poor
schools, which will not have the same weight as they have with an investment-oriented owner.
(Investment-oriented owners will bear a cost in lower rents, whereas an owner-occupier bears it
in term of actual poor education or potential physical violence.)
2) Non-payment of taxes can be voluntary or involuntary for either class of owner.
Voluntary non-payment might arise out of decisions regarding the relative costs and benefits of
maintaining ownership with non-payment being a rational act in order to maximize profits, like
income flows, in the short term. Involuntary non-payment might arise out of personal
circumstances such as job loss or ill health, that consume the resources that might be used for tax
payment; alternatively it may arise out of a lack of understanding of the obligations of homeownership or the impact of predatory lending practice in lower income communities.
Research Propositions
From the preceding, the research will test the following propositions/hypotheses:
P1: The range of factors considered by investment owners will be narrower than for owneroccupiers. Specifically investment owners base their decisions on narrow fiscal factors, whereas
owner-occupiers weigh social or personal factors such emotional ties to a particular property or
maintenance of social networks in their neighborhood.
P2: The propensity of investment owners to become tax delinquent is indeterminate. Because
investment owners lack social or emotional connections to place, one can hypothesize they have
a higher probability of defaulting on property taxes than owner-occupiers. Alternatively, because
investment owners have greater financial resources; they, therefore, are less likely to default on
property taxes than owner-occupiers.
P3: Both types of owners living in communities with active land banks will be less likely to
default on property taxes than owners living in communities lacking a land bank.
Methodology:
We propose to study over time the decision-making and investment/tax payment behavior of
property owners in four Michigan central cities. Specifically we would like to identify and track
owners for a two-year period starting in June 2006 and ending in May 2008.
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Study Population: “At risk property owners” (ARPOs), that is, property owners who are 1 year
behind in paying their property tax obligation and who can expect to be foreclosed upon in the
following year.
Study Sample: Out of identified population of “at risk property owners” we will select a
stratified random sample of owners for each city. The sample will vary by ownership status.
ARPOs will represent both investment owners and owner-occupiers; because owner-occupiers
are considered integral to revitalization efforts in the affected cities they will be oversampled.
Study Locations: The study will select four locations employing “with/without” criteria
associated with the presence of a land bank. We will draw one sample from residents living in
cities with substantial levels of abandonment and foreclosure AND an active or nascent county
land bank. At this time, the communities identified for the study are Flint (Genesee County) and
Saginaw (Saginaw County). A second sample of owners will be drawn from cities with
substantial levels of abandonment and foreclosure that do not have an active land bank in their
county. At this point in time, the target cities are Pontiac (Oakland County) and Benton Harbor
(Berrien County). (Berrien, however, may be establishing an authority as of Dec. 2005).
Analytical Techniques
Our proposed research will be conducted through a mix of quantitative and qualitative methods.
1) Informant Interviews: Prior to drafting the panel survey (see point 3), a series of
interviews will be conducted with individuals who are currently enrolled in the Genesee
County Treasurer’s Office foreclosure prevention program. These interviews are
intended to identify the range of factors that have led to tax delinquency in the city of
Flint. Additionally, other knowledgeable individuals (e.g., County Treasurers for all
target counties, the Foreclosure Prevention Officer from Genesee County) will be
interviewed.
2) Historical and Spatial Analysis of Tax Delinquency in Sample Cities. In order to have a
fuller description of the tax delinquency/foreclosure problem in Michigan cities, we will
collect and scrutinize existing public data on vacant and foreclosed properties. Data for
this will come from the US Census as well as from the State of Michigan, namely
properties that reverted to the Michigan Department of Natural Resources prior to the
change in tax foreclosure brought about by PA 123. Data will be mapped to assess the
phenomenon spatially. In addition newspapers and public archives will be examined to
gather background information on processes of neighborhood change and urban
redevelopment planning in the target cities. Longitudinal data will be collected for the
16-year period beginning in 1990.
3) Panel Survey of Owners of Tax Delinquent Properties: The third research method will be
to conduct an annual panel survey of owners of tax delinquent properties. Panel survey
designs, briefly, survey a given sample of individuals and/or households and follow them
over time with a sequence of rounds of data collection (Trivellato, 1999). The focus of
these annualized surveys would be on the economic circumstances of the household,
attitudes/objectives regarding their neighborhood, property, and property ownership, and
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the identification and ranking of factors affecting their decision-making, particularly
decisions relating to ownership obligations such as maintenance and tax payment.
Because of the potential for attrition or non-response over time is relatively high in this
design, sample sizes will need to be carefully planned to ensure adequate power and
statistical significance for the analysis. Likewise, because of the relative sensitivity of
the topic, procedures will need to be adopted to build trust and an understanding of the
research objectives in the target population.
4) Detailed Case Studies for Individual Owners: To augment the findings of the panel
survey, the research will prepare 8 detailed case studies (2 per target city) presenting the
individual stories and decision-making context for specific owners reflective of their
experience over the two-year time span of the research project. Preparing case studies
will allow us to provide more depth to our analysis than is normally availed through
standard survey research. Qualitative techniques, such as semi-structured interviews and
archival analysis (e.g., looking at press accounts of property markets in the case study
communities) will be used to gather data for the case studies.
Significance of the Research
The problems created by large swaths of vacant and abandoned properties in American central
cities are numerous (National Vacant Properties Campaign, 2005). While many of the new
strategies to ameliorate abandonment are exciting and laudable, we must also craft public
policies that prevent properties from entering into tax delinquency and/or deteriorated status in
the first place in order to break the abandoned properties cycle. To develop such policies we
need greater understanding of what is driving owners into foreclosure, which is the objective of
this research.
The research also fills a significant gap in the research on neighborhood change and
abandonment. Although there is a fairly rich literature on drivers of disinvestment in urban
housing stock (e.g., property taxes, racial change), none of the literature on the subject has
utilized a comparative, longitudinal survey of at-risk property owners to understand their
individual situations and decision-making processes.
Bibliography
Arsen, David. 1992. “Property Tax Assessment Rates and Residential Abandonment: Policies
for New York City” American Journal of Economics and Sociology 51 (3):361-377.
Bartelt, David and Ronald Lawson. 1982. “Rent Control and Abandonment: A Second Look at
the Evidence.” Journal of Urban Affairs 4 (1): 49-64.
Beckert, J. 2003. “Economic Sociology and Embeddedness: How Shall We Conceptualize
Economic Action?” Journal of Economic Issues 37, 3:769-787.
Citizens Research Council of Michigan (CRC). 1999. “Delinquent Property Taxes as An
Impediment to Development in Michigan.” Report No. 325. Farmington Hills, MI:
CRC. Accessed at www.crcmich.org.
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Granovetter, M. 1992. "Economic Action and Social Structure: The Problem of Embeddedness"
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Kildee, D.T. 2004. “Reusing Forgotten Urban Land: The Genesee County Urban Land
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National Vacant Properties Campaign, 2005. "Vacant Properties: The True Costs to
Communities" Accessed at www.vacantproperties.org, June 15, 2005.
Trivellato, Ugo. 1999. “Issues in the Design and Analysis of Panel Studies: A Cursory
Review” Quality and Quantity 33:339-352.
White, Michelle, 1986. “Property Taxes and Urban Property Abandonment” Journal of Urban
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