Current Urban Studies
2013. Vol.1, No.3, 28-35
Published Online September 2013 in SciRes (
Copyright © 2013 SciRes.
Chasing a Paper Tiger: Evaluating Buffalo’s Analysis of
Impediments to Fair Housing Choice
Robert Mark Silverman1, Kelly L. Patterson2, Jade Lewis1
1Department of Urban and Regional Planning, University at Buffal o , Buffalo, USA
2School of Social Work, University at Buffalo, Buffalo, USA
Email: rms35@ buf fal
Received June 3rd, 2013; revised July 3rd, 2013 ; a cc ep t ed J ul y 1 0th, 2013
Copyright © 2013 Robert Mark Silverman et al. This is an open access article distributed under the Creative
Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium,
provided the origina l w o rk is properly cited.
This article focuses on a specific component of the US Department of Housing and Urban Development’s
(HUD’s) strategy to implement fair housing policy, its requirement for local jurisdictions that receive
community development block grant (CDBG) dollars to prepare an analysis of impediments to fair hous-
ing choice (AI) report. The article’s analysis is based on an evaluation of the City of Buffalo’s 2004 AI
report. The evaluation was conducted by a local fair housing organization in collaboration with univer-
sity-based researchers. The findings from the evaluation revealed that the City had made little progress in
implementing the action plan from its AI report over an eight year period. This was an outgrowth of local
funding constraints, limited staff capacity, ambiguous HUD rules for AI reporting, and a lack of political
will to pursue fair housing in Buffalo. In light of these findings, we recommend that HUD: mandate time-
frames for AI implementation, require AI updates at regular intervals, and more clearly specify the format
and content of AI reports. We also recommend that HUD require jurisdictions to include evaluation plans
in their AI reports and measure outcomes from the implementation of AI action plans. These reforms will
enhance the ability of AI reports to serve as effective planning tools for the affirmative furthering of fair
housing policy.
Keywords: Fair Housing; Discrimination; Evaluation; Applied Research
Fair Housing and the Analysis of Impediments
Discrimination in the sale and rental of housing has been an
ignominy in the US for most of its history. The first significant
step to stamp out discrimination in US housing markets oc-
curred with the passage of the Fair Housing Act of 1968. The
Act prohibited discrimination at any point in the sale or rental
of housing on the basis of race, color, religion, sex, and national
origin. Under the Act, the US Department of Housing and Ur-
ban Development (HUD) was designated as the federal agency
to administer programs related to fair housing. HUD was au-
thorized to affirmatively further fair housing in all of its pro-
grams and funded activities. Since that point in time, the Act
has been amended and HUD has muddled through the process
of promulgating rules and implementing fair housing policy
(Yinger, 1999; Connerly, 2006; Schill, 2007; Squires, 2008;
Silverman & Patterson, 2012). For the most part, government’s
commitment to eradicate discrimination in housing markets at
the federal, state, and local levels has waxed and waned since
the adoption of the Act (Tisdale, 1999; Sidney, 2004; Lamb &
Wilk, 2009; Patterson & Silverman, 2011; Seabrook et al., 2011;
Wilk et al., 2011). Inconsistent enforcement of the Act has been
compounded by the imprecise definition of its goal to affirma-
tively further fair housing.
This article focuses on a specific component of HUD’s stra-
tegy to implement fair housing policy, its requirement for local
jurisdictions that receive community development block grant
(CDBG) dollars to prepare an analysis of impediments to fair
housing choice (AI) report. HUD recommends that jurisdictions
prepare a new AI every three to five years (US Department of
Housing and Urban Development, 1996). The purpose of AI
reports is to identify impediments to fair housing and develop
strategies to reduce them. In principle, AI reports should be
proactive and guided by the Fair Housing Act’s goal of affir-
matively furthering fair housing.
We focused our analysis on the AI reporting process because
it involves two critical steps in the fair housing enforcement
process. First, the AI report sets the parameters for local fair
housing enforcement. Local jurisdictions identify impediments
to fair housing in their AI reports and develop action plans to
reduce them. Second, AI reports are part of HUD’s annual cer-
tification process for CDBG grantees. Each year, jurisdictions
receiving CDBG funds must certify that they are meeting
HUD’s requirements for affirmatively forwarding fair housing,
which include preparing an AI report and having it on file. Lo-
cal jurisdictions are not required to submit their AI reports to
HUD as part of the certification process. HUD generally ac-
cepts grantees’ annual certifications of affirmatively furthering
fair housing, and does not initiate further review unless third
party complaints produce evidence that suggest otherwise. Al-
though these two steps in the fair housing enforcement process
are important, they have been criticized for lacking specificity
and mandating that local jurisdictions submit AI reports to
HUD for review and approval (US Government Accountability
Office, 2010).
There have also been shortcomings in other aspects of the
implementation of fair housing policy. One of the most notable
shortcomings of the AI reporting process is that there has been
insufficient monitoring and evaluation of local jurisdictions’
implementation of action plans to reduce impediments to fair
housing. Historically, following the preparation of an AI report
by a local jurisdiction, HUD conducts no review of perform-
ance. The local jurisdiction simply certifies that the AI exists on
an annual basis. The lack of monitoring and evaluation has
hampered HUD’s ability to enforce fair housing policy, and this
has been compounded by the dearth of clearly articulated ben-
chmarks and timetables for the implementation of local juris-
dictions’ action plans. In essence, AI reports identify impedi-
ments to fair housing and develop action plans to address them,
but there is no formal process in place to ensure they will be
implemented. Literally and figu ratively, they are paper tigers.
The lack of provisions for monitoring and evaluating local
jurisdictions’ implementation of action plans from their AI re-
ports had not gone unnoticed by HUD. One recent attempt to
address this problem has entailed stepped up efforts by non-
profit fair housing organizations to evaluate the performance of
local jurisdictions on their AI action plans. In the case we ex-
amined for this article, a local nonprofit fair housing organiza-
tion received funding from HUD to perform such an evaluation
and make recommendations to improve the AI reporting proc-
ess. We received a small grant from the American Sociological
Association’s Sydney S. Spivack Program in Applied Social
Research and Social Policy to augment this evaluation. In this
article, we discuss the rationale for this project, its design, our
findings, and the role of university-community collaborations
in continuing this research.
Talking the Fair Housing Act’s Talk
Symbolically, the Fair Housing Act of 1968 represented a
monumental shift in US housing policy. Before the Act, indi-
viduals facing discrimination in housing markets had practical-
ly no legal recourse. After the Act’s passage, individuals could
file complaints with HUD and had standing to sue when they
believed they were discriminated against in their search for
housing. However, this statutory milestone was narrowly con-
structed and focused wholly on providing remedies to individu-
als who experienced discrimination. The Act did not provide re-
medies for structural forms of discrimination faced by ascribed
groups or classes in society. Instead, the burden of demonstrat-
ing that acts of discrimination had occurred was firmly placed
on those who had been victimized.
The Act was narrowly constructed in a number of other ways
(Landis & McClure, 2010; Yinger, 1999). The Act did not ap-
ply to a large proportion of properties available for rent or pur-
chase. The law did not apply to rental properties with four or
fewer units, and it did not apply to home sales unless real estate
agents were used. As a result, many renters and homebuyers re-
mained unprotected from housing discrimination. When the Act
did apply, mechanisms for fair housing enforcement were ex-
tremely weak. HUD had no enforcement powers when fair hous-
ing violations were identified. Instead, HUD filled a concilia-
tion role where it could notify the US Department of Justice
(DOJ) about suspected violations of law in extreme cases of
discrimination. In response, the DOJ would take action on a
small number of highly egregious cases. Fair housing enforce-
ment was further hampered since individuals only had 180 days
to file a lawsuit, they were responsible for all court costs and
attorneys’ fees (unless a court waived them due to economic
hardship), and punitive damages were ca pp ed at $1000.
The Fair Housing Act of 1968 remained untouched for twen-
ty years. After decades of advocacy for strengthening the Act, a
small number of key amendments were finally adopted. The
1988 amendments to the Act expanded protections to those
facing housing discrimination based on disability and family
status. The amendments also gave HUD greater latitude in the
fair housing enforcement process. HUD was granted power to
hold administrative hearings and impose fines and damages for
fair housing violations. The time limit for individuals to file
civil suits was extended from 180 days to 2 years, and caps on
damages that could be awarded to complainants were signifi-
cantly increased1.
Although the 1988 amendments to the Fair Housing Act rep-
resented progress, it was hardly a watershed moment. Since
1988, there have been few advances in federal fair housing po-
licy. It has been over 25 years since fair housing protections
were extended to additional groups or classes. There is still no
federal fair housing protection based on marital status, sources
of income, sexual orientation, gender identification, political
affiliation, Housing Choice Voucher (HCV) status, or other
characteristics. The Act remains focused on individual com-
plaints and lacks remedies for structural forms of discrimination.
In addition, rental properties with four or fewer units and home
sales where real estate agents are not used remain exempt from
the Act.
Not Quite Walking the Fair Housing Walk
The evolution of local fair housing policy implementation
has followed a parallel path to the development of federal fair
housing law. The 1988 amendments to the Fair Housing Act
included language requiring HUD to establish fair housing
review criteria for jurisdictions receiving CDBG funds. Juris-
dictions that met these criteria would receive certification from
HUD that they were affirmatively furthering fair housing. In
order to establish that these criteria had been met, HUD prom-
ulgated rules requiring jurisdictions to: produce AI reports, take
action to eliminate any identified impediments to fair housing,
and maintain records of their efforts to affirmatively further fair
housing. Initially, the policies surrounding the AI process were
somewhat vague and inconsistently enforced.
In order to create more consistency in the AI process, HUD
produced its Fair Housing Planning Guide in 1996, which pro-
vided jurisdictions with instructions for developing their AI
reports and implementing their action plans (US Department of
Housing and Urban Development, 1996). This guide recom-
mends that jurisdictions complete a new AI report every three
to five years (consistent with their CDBG consolidated plann-
ing cycle). However, timing for preparing new AI reports is left
to the discretion of local jurisdictions. The guide also suggested
that jurisdictions identify milestones, timetables and measure-
1The 1988 Amendment to the Fair Housing Act removed the $1000 cap on
punitive damages, allowed for complainants to recover court costs and at-
torneys’ fees, and placed no limits on compensatory awards from the courts.
Under the amendments to the Act, cases heard by administrative law judges
could receive a civil penalty of up to $10,000 for the first discriminatory
practice, up to $25,000 if the respondent has committed another violation
within the prior five years, or up to $50,000 if the respondent committed
two or more v io lations within the prior seven years.
Copyright © 2013 SciRes. 29
able results to be achieved in their action plans. Yet, the identi-
fication of these metrics is not mandatory. Since the promulga-
tion of rules related to AI reports, HUD has continued to hold
the position that jurisdictions maintain records of actions taken
to affirmatively further fair housing and report on their imple-
mentation of AI action plans (US Department of Housing and
Urban Development, 2004; US Department of Housing and Ur-
ban Development, 2007). However, no clear enforcement me-
chanism exists to prompt jurisdictions to do so.
Compliance with HUD’s AI reporting rules have been a
source of concern since their inception. In 2009, HUD complet-
ed and internal Analysis of Impediments Study which found that
many AIs were outdated, lacking detail and subject to limited
oversight by the agency (US General Accountability Office,
2010). In its own independent study, the US Government Ac-
countability Office (GAO) (2010) reached similar conclusions.
The GAO conducted a study using a national sample of 411 ju-
risdictions and concluded that: 29% of all AIs were outdated,
there were broad discrepancies in the content and completeness
of reports, AI authorship and the types of impediments identi-
fied varied widely, and most reports lacked timeframes for im-
plementing recommendations. The GAO study also found that
the large proportion of outdated and inconstantly prepared AI
reports could be partly attributed to HUDs limited regulatory
requirements, oversight and enforcement. According to the
GAO, HUD did not have well defined standards in place for the
formatting of AI reports and timely AI reporting, and jurisdic-
tions were not required to submit the full text of AI reports to
HUD. The GAO concluded that HUD lacked the capacity to
provide jurisdictions with technical support and other assistance
necessary to as sure that AIs serve as an e ffective planning tool.
Following the issuance of the GAO’s findings in 2010, HUD
began to take steps to increase the level of scrutiny given to AI
reports and increase efforts to provide local jurisdictions with
training and assistance in the AI process. However, core con-
cerns identified in the GAO report related to timeliness of AI
reporting, the content of AI reports, and HUD’s capacity re-
mained unaddressed.
The Evaluation
Our analysis adds an additional perspective to earlier criti-
ques of the AI reporting process. We focus specifically on eva-
luating the implementation of the AI action plans generated
through this process. This focus was adopted in response to
concerns raised about the consistency of monitoring and re-
porting related to AI implementation. These concerns were rais-
ed in the GAO’s (2010) study of AIs and echoed in our interac-
tions with local fair housing advocacy organizations and hous-
ing officials.
Our focus on evaluating the implementation of AI action
plans also grew out of a unique collaboration on an applied re-
search project. In 2011, Housing Opportunities Made Equal of
Buffalo (HOME)2 was awarded a Fair Housing Initiatives Pro-
gram (FHIP)3 grant from HUD. One activity HOME received
funding to engage in under the grant was an evaluation of local
jurisdictions’ performance on AI action plans. HOME planned
to evaluate AI performance for four jurisdictions in the Buf-
falo-Niagara Falls metropolitan area over a three year period.
The largest municipality that HOME planned to evaluate was
the City of Buffalo, NY. Buffalo is the second largest city in
the State of New York. Its 2010 population was 261,310
( The city’s population was 38.6% black and
10.5% Latino ( According to the US2010
progject at Brown University (http://www.,
in 2010 Buffalo had a white-black dissimilarity index of 65.84.
This indicated that there was a high degree of segregation be-
tween whites and blacks in the city, where 65.8% of blacks
would have to move in order for the city to be racially inte-
grated. In 2010, the city had a white-Latino dissimilarity index
of 43.4. This indicated that a moderate degree of segregation
existed between whites and Latinos, where 43.4% of Latinos
would have to move in order for the city to be ethnically inte-
We were invited to collaborate with HOME on the evalua-
tion of the City of Buffalo’s 2004 AI report. We received a
small grant from the American Sociological Association’s Syd-
ney S. Spivack Program in Applied Social Research and Social
Policy to augment HOME’s evaluation and to develop this ar-
ticle as a companion piece to this work. During the spring and
summer of 2012 we collaborated with HOME to analyze the
City’s 2004 AI report, collect data on the implementation of its
action plan, and draft a memorandum to HUD summarizing the
findings from the evaluation.
The evaluation was based on an examination of the AI action
plan. Data were collected related to each item in the action plan
and efforts were made to determine if the City had taken proac-
tive steps to reduce identified impediments to fair housing. Data
were collected from municipal documents, HOME records, HUD,
and other sources. These included the City’s past and current
CDBG consolidated plans, city ordinances and land-use poli-
cies, and related records from Erie County, NY5. In addition to
public records and archival materials, data were collected through
meetings held with officials from the City’s Office of Strategic
Planning, the City’s Fair Housing Officer, and the Director of
the City’s Rental Registration program. During these meetings,
the action items from the 2004 AI were reviewed and the indi-
viduals who we met with provided written and verbal responses
to questions concerning steps the City had taken to reduce iden-
tified impediments.
The data were analyzed by quantifying the number of action
items that the City had taken steps to address and through a
qualitative assessment of how effective the City’s efforts were
at reducing impediments to fair housing. For each action item,
3The Fair Housing Initiatives Program (FHIP) was established as a compo-
nent of the Housing and Community Developmen t Act of 1987 (amended in
1992). Under the program, grants are awarded to nonprofit housing organi-
zations on a competitive basis. FHIP organizations undertake activities to
enhance compliance with fair housing law. These activities include educa-
tion, monitoring, routing complaints to other agencies for investigation, and
fair housing compliance programs.
4The dissimilarity index measures whether one particular group is distrib-
uted across census tracts in a geographic area in the same way as another
group. A high value indicates that the two groups tend to live in different
tracts. Dissimilarity indexes range from 0 to 100. A value of 60 (or above)
is consid ered v er y hig h. It means t hat 60% ( or mor e) of the me mber s o f on e
group would need to move to a different tract in order for the two groups to
e equally distributed. Values of 40 or 50 are usually considered to reflect a
moderate level of segregation, and values of 30 or below are considered to
be fairly low.
5Erie County, NY is the county w here the city of Buffalo is loc ated.
2HOME is a not-for-
rofit, membership based, civil rights organization in
western New York. It was founded in 1963. Its mission is to promote the
value of diversity and to ensure the people of western New York an equal
opportunity to live in the housing and communities of their choice through
education, advocacy, enforcement of fair housing laws, and the creation o
housing opportunities.
Copyright © 2013 SciRes.
Copyright © 2013 SciRes. 31
we also identified the degree to which tools for reducing an
impediment fell within the City’s locus of control. The results
from this analysis are summarized in the next section of this
hampered by reductions in staffing, and they speculated that
there were fewer complaints received than in the past due to
this predicament. Consequently, discrimination complaints were
pursued when available staff became aware of them and were
able to document them, and when victims of discrimination
were persistent in reporting. A smaller subset of complaints
received by HOME were well enough documented and sub-
stantial enough to forward to HUD or FHAP agencies for ac-
Fair Housing Complaints
It is estimated that over 4 million instances of housing dis-
crimination occur annually in the US, but less than 1 percent of
them are reported to HUD or FHAP6 agencies (Silverman &
Patterson, 2012). This discrepancy is attributed to a number of
factors. Victims of housing discrimination lack information
about how to report instances, and they perceive the complaint
process as cumbersome and ineffective. These perceptions are
aggravated by the limited capacity of local housing agencies
and advocacy groups to pursue complaints and lax enforcement
of fair housing laws. Also, records of fair housing complaints
are often incomplete and kept in an inconsistent manner over
time. Many of these shortcomings can be observed at the local
HOME, the City of Buffalo, and other local agencies were
unable to provide complaint intake records for the years fol-
lowing Buffalo’s 2004 AI report. When these records were re-
quested for this analysis, respective agencies indicated that they
were not maintained, could not be located, or were unavailable
for some other reason. However, HUD and FHAP discrimina-
tion case records for Buffalo were available from 2004 to 2012.
These records came from HUD’s Title VIII Automated Paper-
less Office Tracking System (TEAPOTS) database. These data
are summarized in Tables 1 and 2. They include annual counts
of HUD and FHAP housing discrimination cases processed,
and the basis for discrimination in those cases. These data also
report the outcomes of housing discrimination cases. Although
these data only reflect instances of housing discrimination that
were included in HUD and FHAP case files, they provide in-
sights into the scope of discrimination occurring in Buffalo
during the implementation of the action plan from the 2004 AI
For example, Buffalo’s 2004 AI report indicated that HOME
received 884 housing discrimination complaints between 1999
and 2003 (City of Buffalo, 2004). Those complaints were based
on: race/color (35%), familial status (30%), disability (19%),
and source of income (13%). The 2004 AI report also indicated
that HUD pursued 57 housing discrimination cases in Buffalo
between 1999 and 2003. Those cases were based on: race/color
(40%), familial status (28%), and disability (23%). At the time
of this study, HOME no longer maintained complete internal
records of discrimination complaints. This was due to staff
turnover and reduced funds for fair housing enforcement.
HOME staff also indicated that the intake of complaints was
Table 1 summarizes TEAPOTS data for Buffalo between
2004 and 2012. The volume of cases processed by HUD and
FHAP agencies during this period was comparable to the vol-
ume identified in the City’s 2004 AI report. Moreover, the basis
for discrimination in cases processed between 2004 and 2012
were similar to the instances of discrimination discussed in the
Table 1.
2004-2012 HUD and FHAP Processed Housing Discrimination Cases for B uff al o, N Y1.
Year Percent
Race Percent
Color Percent
National Origin Percent Nati o n al
Religion Percent SexPercent
Disability Percent
Familial Status Percent
Retaliation Total Cases
2004 38.1 9.5 4.8 4.8 4.8 28.6 28.6 42.9 9.5 21
2005 50.0 - 11.5 3.8 3.8 7.7 26.9 26.9 3.8 26
2006 50.0 11.1 - - - 27.8 27.8 33.3 5.6 18
2007 58.8 - 17.6 - 5.9 11.8 47.1 5.9 11.8 17
2008 33.3 6.7 6.7 - - 26.7 40.0 40.0 - 15
2009 50.0 23.1 15.4 7.7 - 7.7 34.6 30.8 - 26
2010 56.0 8.0 12.0 - 8.0 8.0 40.0 24.0 8.0 25
2011 36.4 9.1 9.1 - - 54.5 9.1 45.5 9.1 11
2012 23.1 7.7 23.1 23.1 - 30.8 38.5 53.8 15.4 13
2004-12 45.9 8.7 11.0 4.1 2.9 19.2 33.1 32.0 6.4 172
Note: Source: US Department of Housing and Urban Development (HUD). Fair Housing and Equal Oppo rtunity Office, Title VIII Automated Paperless Office Tracking
System (TEAPOTS) 1Cases may have more than one basis for discrimination so the total percent across cases for a given year may be greater than 100% 2National Ori-
gin-Hispa nic is a subset of Nat ion al Or ig in.
6The Fair Hous ing Assistance Program (FHAP) was established i n 1979. Under the program, grants are awarded ann ually on a n on competitive basis to s t ate and
local fair housing agenci es. FHAP agencies are referred co mplaints fro m HUD and other organization s and charged with the task of investigating instances o
housing discrimination in their jurisdictions. Based on those investigations, complaints can be dismissed, conciliated/settled, or referred to the US Department
of Justice (DOJ) or courts for l i tigation.
Table 2.
2004-2013 HUD and FHAP Processed Housing Discrimination Case Outcomes for Buffalo, NY.
Year Percent
Administrati ve Closure1 Percent
Cause (FHAP)2 Percent
Charged (HUD)3Percent
Conciliated/Settled4 Percent
No Cause5 Percent
Open6 Total Cases
2004 - 9.5 4.8 38.1 47.6 - 21.0
2005 7.7 3.8 - 50.0 38.5 - 26.0
2006 5.6 11.1 - 16.7 66.7 - 18.0
2007 - 17.6 - 11.8 70.6 - 17.0
2008 13.3 - - 26.7 60.0 - 15.0
2009 3.8 19.2 3.8 15.4 57.7 - 26.0
2010 12.0 8.0 - 20.0 60.0 - 25.0
2011 9.1 27.3 - 18.2 45.5 - 11.0
2012 - 7.7 - 7.7 46.2 38.5 13.0
2004-12 5.8 11.0 1.2 24.4 54.7 2.9 172.0
Note: Source: US Department of Housing and Urban Development (HUD), Fair Housing and Equal Oppo rtunity Office, Title VIII Automated Paperless Office Tracking
System (TEAPOTS). 1HUD and FHAP agencies administ ratively close complaints when the complainant wit hdraws the complaint, fails to cooperate, or can no longer be
located. Agen cies also clos e complaints when , after acceptin g the complain t, it is det ermined that they lack ju risdictio n. 2A reasonable cause determination is issued when
an FHAP agency has complet ed a full investig ation and found that there is reasonable cause to believe that a discriminatory housing practice has occurred. 3HUD issues a
charge of d iscrimin ation when i t has completed a full investig ation and foun d that there is reasonable cause to b elieve th at a discriminatory housing practice has occurred.
4A complainant and respon dent have en tered into a con ciliation agreement or private se ttlement. 5HUD and/or FHAP ag encies found no reasonable caus e to believe that a
discrim inatory housin g practice has occurred. 6Cases open and still under investigation.
2004 AI report. The three most prevalent forms of housing
discrimination in Buffalo between 2004 and 2012 were based
on race (45.9%), disability (33.1%), and familial status (32%).
Despite constraints that local government and fair housing or-
ganizations faced related to the intake of discrimination com-
plaints, patterns of discrimination remained relatively stable in
the city during the implementation of the action plan for the
2004 AI report.
Table 2 adds to our understanding of fair housing imple-
mentation in Buffalo. This table summarizes outcomes of dis-
crimination cases originating in the city between 2004 and 2012.
These data are important because they provide insights into the
effectiveness of the intake and referral process for fair housing
complaints. In over half (54.7%) of the cases processed by
HUD and FHAP agencies, it was determined that there was no
reasonable cause that a discriminatory housing practice had
occurred. This suggests that little vetting took place at the in-
take level when complaints were received by local government
and fair housing organizations. Instead, complaints were simply
forwarded to HUD and FHAP agencies. After cases determined
to have no cause for discrimination complaints were removed,
the vast majority of the remaining cases processed by HUD and
FHAP agencies resulted in a conciliation, settlement, or crimi-
nal charges being filed. Despite the relatively low volume of
cases processed in Buffalo, about one-third (36.6%) resulted in
a favorable outcome for victims of housing discrimination.
Given the obstacles that victims face in filing a complaint and
receiving assistance from local agencies and organizations, the
case outcomes suggest that housing discrimination remained a
salient issue in Buffalo during the implementation of the City’s
2004 AI report.
Implementation of the AI Action Plan
The City of Buffalo identified 32 distinct impediments to fair
housing in its 2004 AI report. The report included action items
to address those impediments. Table 3 summarizes the impe-
diments that were identified in the report. They are subdivided
into four broad categories following the methodology used by
the GAO (2010) in its analysis of AI reports. In addition to
providing counts of the types of impediments identified in the
City’s 2004 AI report, we further subdivided impediments
along two dimensions: the City’s locus of control to take action
on identified impediments to fair housing, and the City’s per-
formance in reducing impediments to fair housing since the
report was adopted. Adding these two dimensions to the analy-
sis enhances our understanding of the AI implementation proc-
ess. Considering the City’s locus of control allows us to assess
the degree to which the City had autonomy when taking action
on identified impediments to fair housing. We hypothesized
that impediments that were within the City’s locus of control
would be more likely to be reduced. Table 3 provides some
support for this hypothesis. Yet, the City’s performance on re-
ducing impediments to fair housing remained low for the pre-
ponderance of the action items examined.
The low levels of performance on reducing impediments to
fair housing are attributed to a number of factors. Many are
linked to issues identified by the GAO (2010) in its analysis of
AIs. These factors include the limited capacity and technical
expertise of local government, overly broad definitions of iden-
tified impediments, ambiguity in action plans, poorly commu-
nicated parameters for monitoring progress on reducing im-
pediments, and limited technical support from HUD in the AI
process. The City of Buffalo wasfurther hampered in its efforts
Copyright © 2013 SciRes.
Table 3.
Type of Impediments Identified in the 2004 Buffalo AI Report with Summar y Evaluation of City’s Locus o f Control & Performance.
City’s Locus of Control City’s Perfo r mance
Impediments Number IdentifiedHigh Medium Low High MediumLow
Zoning, Code Enforceme nt, Local Ordina nces and Policies 7 100% - - 14% - 86%
Neighborhoo d Revitalization & Affordable/Accessible
Housing Deve lopment 7 100% - - - 14% 86%
Lending & Real Estate 12 8% 50% 42% 8% - 92%
Informational & Educational programs 6 67% 33% - 17% - 83%
Total 32 38% 47% 15% 9% 3% 88%
to implement its AI action plan due to fiscal constraints, de-
clining CDBG allocations, and turnover in key staff positions.
Since the adoption of it AI report in 2004, the City had replaced
key staff in its Office of Strategic Planning (OSP) and restruc-
tured several positions. This led to a loss of institutional mem-
ory concerning the implementation of the AI report. This prob-
lem became apparent in our discussions with OSP staff during
our data collection. For example, at an initial meeting a senior
staff member indicated that he was unaware of the City’s AI
report before we contacted him about our evaluation. This staff
person was the third to occupy his position since the 2004 AI
report was adopted. Turnover in staff had negative implications
for continuity in the implementation of the City’s fair housing
action plan.
Buffalo’s Fair Housing Ordinance
Problems with staffing and capacity were ma nifeste d in a va -
riety of other ways that negatively impacted the implementation
of the City’s fair housing action plan. One of the more illustra-
tive examples of how these constraints affected the City’s abili-
ty to reduce impediments to fair housing involved its fair hous-
ing ordinance. In response to the 2004 AI report, the City of
Buffalo adopted a fair housing ordinance. It was adopted in
2006 and extended fair housing protection in the city to classes
of individuals unprotected by federal law, such as individuals
experiencing housing discrimination based on their source of
income. The ordinance included a framework for filing com-
plaints, asse ssing fines fo r local fa ir housing violations, and other
enforcement mechanisms. The ordinance identified a Fair
Housing Officer as the individual responsible for the imple-
mentation of the new law. This was a new position to be ap-
pointed by the Mayor. One key provision in the ordinance was
the establishment of fines and other civil penalties for violating
local fair housing laws. Another key provision of the ordinance
was the requirement for the City to prepare an annual fair
housing report. This requirement included the following:
The Fair Housing Officer shall prepare an annual report
detailing the work performed including a statistical analy-
sis of the caseload, a summary of dispositions of com-
plaints filed and/or referred to housing agencies, and re-
commendations regarding fair housing practices. This re-
port shall be submitted to the Mayor and filed with the
City Clerk no later than March 1st of each year. Copies
shall also be sent to the Commissioner of the New York
State Division of Human Rights, the Attorney General of
the State of New York, and the Secretary of the United
States Department of Housing and Urban Development
(§154 - 21, Code of the City of Buffalo).
The City’s fair housing ordinance contained strong language
and provisions for expanded fair housing protections. This gave
it a high degree of symbolic value. Still, it has been a failure on
substantive grounds due to the lack of implementation. For
example, the Fair Housing Officer’s position that is identified
in the ordinance has been understaffed or vacant since the law
was adopted. The lack of consistent staffing has led to a lapse
in enforcement of the ordinance. No records of fines, civil pen-
alties, or other enforcement actions have been maintained since
the adoption of the ordinance. Moreover, the City of Buffalo
has never prepared an annual report on the work performed
under the law. This is particularly indicting, since this indicates
that the City has been out of compliance with its own fair
housing ordinance since its adoption in 2006.
Lax implementation of the City of Buffalo’s fair housing or-
dinance can be viewed as a microcosm of fair housing policy
implementation nationally (US General Accountability Office,
2010; Silverman & Patterson, 2012). Chronic underfunding of
fair housing programs, limited staff capacity and technical sup-
port, and inconsistent monitoring by state and federal fair hous-
ing agencies have contributed to scant implementation of fair
housing laws at the local, state and federal levels. Many of the
issues that affect fair housing enforcement are outside of local
governments’ locus of control. Nevertheless, these constraints
frame the scope of local enforcement activities. This is clearly
reflected in our findings from the evaluation of the implementa-
tion of Buffalo’s 2004 AI report.
The Memorandum to HUD
In August 2012, HOME submitted a memorandum to HUD
summarizing the findings from its evaluation of the implemen-
tation of the City of Buffalo’s 2004 AI report. The memoran-
dum discussed the impediments identified in the City’s AI re-
port and progress made in reducing them. Overall, the memo-
randum indicated that the City made little progress in reducing
impediments to fair housing between 2004 and 2012. Largely,
this was an outgrowth of lax implementation and a dearth of
municipal resources allocated to affirmatively further fair hous-
ing. These conditions were reflected in the following statement
from the memorandum:
The rate of progress in implementing the City’s action
items appears to have been slowed by inconsistent staffing
of key positions related to fair housing and limited civil
Copyright © 2013 SciRes. 33
service protection for individuals assigned to implement
and enforce fair housing policies… There has also been
limited financial support for fair housing activities and lit-
tle evidence of systematic code enforcement, demolition,
and development of other targeted programs that would
improve housing choices, particularly in areas with con-
centrated minority populations.
The memorandum went on to discuss how implementation of
action items from the 2004 AI report was varied based on the
degree to which remedies to impediments were within the
City’s locus of control. The following excerpt from the memo-
randum highlights this distinction:
The City appeared to make the most progress on action
items within its locus of control. This was reflected in the
adoption of a local fair housing ordinance in 2006 and
other areas. However, there was less progress in the im-
plementation of this new policy and other areas related to
zoning, accommodations for the disabled, and reforming
restrictive use permit policies for nonprofit service pro-
Ironically, the City’s fair housing ordinance was identified as
an example of noticeable progress in reducing impediments to
fair housing in the memorandum. However, as noted above,
resource constraints have hampered the implementation of the
fair housing ordinance since its adoption. In contrast to the
modest progress achieved with the adoption of the fair housing
ordinance, the memorandum went on to conclude that the city
had less success in reducing impediments outside of its imme-
diate locus of control. For example, the memorandum conclud-
ed that, “the City made no progress in addressing impediments
associated with the [Buffalo Niagara Association of Realtors]
BNAR, and there was little evidence of outreach to the [Niag-
ara Frontier Transportation Authority] NFTA.” The memoran-
dum went on to conclude that although the City has less influ-
ence over external entities, “City officials have a bully pulpit to
advocate for positive change and there is little evidence that
they have done so.” Even when opportunities to take action
merely involved initiating dialogue with an external organiza-
tion, the City failed to take steps to affirmatively further fair
housing. In part, this can be attributed to resource constraints,
but it also seems to reflect a lack of political will to take action
on fair housing.
The memorandum partially attributed the lack of perform-
ance in reducing impediments to fair housing to the lackluster
oversight of the AI process by HUD. Specifically, the lack of
requirements for the City to identify outcome measures and
benchmarks in its 2004 AI was cited as problematic. The me-
morandum suggested that HUD promulgate more specific rules
and guidelines for monitoring and reporting outcomes in order
to address this problem. In the absence of outcome measures
and benchmarks, the City essentially deferred from taking ac-
tion on fair housing and routinely kicked the can down the road.
One manifestation of the tendency to defer from taking action
was the City’s repeated claim that plans were in the works for
future activities that tied into fair housing. Throughout the eva-
luation city officials were asked about performance on past ac-
tion items identified in the AI report. They routinely responded
that action items would be addressed by initiatives that were
being planned for the future. For example, on several occasions
city officials suggested that a lack of action to remove impedi-
ments would be addressed when the City’s new land use ordi-
nances, referred to as the “Green Code”, were adopted. Con-
cerns were raised about this in the memorandum:
There is cause for concern about the extent to which the
Green Code will serve as a vehicle to affirmatively further
fair housing, since there is little detail available about it
and specific recommendations related to fair housing were
not identified. For example, there has been no discussion
of an inclusionary zoning ordinance, set asides for af-
fordable housing, or other mechanisms to affirmatively
further fair housing in the current dialogue surrounding
the Green Code.
At the time of this writing a draft version of the Green Code
has not been made available to the public for discussion. A
draft version was originally planned for release by the City in
September of 2012, but it was delayed for undisclosed reasons.
After HOME submitted its memorandum to HUD, the City
of Buffalo provided no official response to the issues identified
in the evaluation. Instead, the City indicated that it planned to
prepare a new AI report with its 2013-2018 CDBG Consoli-
dated Plan. In October of 2012, a private consultant was hired
by the City to conduct a new AI report. This came on the heels
of HOME’s evaluation which indicated that the City’s past
performance on its 2004 AI was relatively poor. It is possible
that HOME’s evaluation of the City’s performance on the ac-
tion plan sped up the initiation of a new AI study. The City may
have also been prompted to revisit its AI due to growing pres-
sure from HUD and other agencies, like the GAO, to improve
fair housing monitoring and reporting efforts.
Recommendations for Action
This analysis helps to refine recommendations to improve the
AI reporting process and augment efforts of local jurisdictions
to affirmatively further fair housing. In 2010, the GAO (2010)
offered specific recommendations to improve the AI reporting
process. One GAO recommendation was for HUD to require ju-
risdictions to include timeframes for the implementation of
their fair housing action plans in their AI reports. These time-
frames would serve as foundations for establishing benchmarks
and measuring jurisdictions’ performance on reducing identi-
fied impediments to fair housing. Another GAO recommenda-
tion was to mandate that jurisdictions update their AIs at regu-
lar intervals, rather than simply leave the timing of AI updates
to each jurisdiction’s discretion. The GAO further recommen-
ded that HUD establish a specific format and identify required
content for jurisdictions to include in their AI reports. Finally,
the GAO recommended that HUD require all jurisdictions to
submit their AI reports to the agency for review and approval.
These recommendations were made with the goal of ensuring
that AIs serve as an effective planning tool for the affirmative
furthering of fair housing policy.
Our experience with the evaluation of Buffalo’s 2004 AI
suggests that additional engagement with local jurisdictions
would augment to benefits of adopting recommendations like
the ones the GAO made in 2010. In particular, we believe that
HUD should put even greater emphasis on the evaluation of
outcomes in the AI process. The focus on evaluation should be
tied to measurable outcomes, and mandates for local jurisdic-
tions to document them throughout the AI implementation pro-
cess. In order to implement ongoing evaluation, HUD should
Copyright © 2013 SciRes.
Copyright © 2013 SciRes. 35
require local jurisdictions to include an evaluation plan in their
AI reports. In addition to the development of measurable out-
comes and evaluation plans, we believe that HUD should re-
quire AI reports to focus on identifying impediments that are
within a local jurisdiction’s locus of control. This would allow
for local fair housing action plans to be more closely aligned
with the deployment of CDBG and other funds available to lo-
cal jurisdictions.
Finally, our experience with the evaluation of Buffalo’s 2004
AI highlights the value of conducting an independent assess-
ment of a jurisdiction’s performance. HUD included funding
for HOME’s evaluation of the City’s AI in the organization’s
2011 FHIP grant. HUD’s support of the evaluation of AI out-
comes in Buffalo made fair housing enforcement a more salient
issue to the City. The presence of an independent evaluation
team was further enhanced by the university-community colla-
boration that was forged between HOME and researchers from
the University at Buffalo. In part, HUD’s support of outside
evaluation and the university-community partnership may have
created a sense of urgency in the City and prompted it to be
more attentive to fair housing planning. The presence of inde-
pendent evaluators appeared to have an effect similar to what
Paul Light (1998) described as watchful eye policies adopted to
improve program performance in government. We believe that
HUD should institutionalize the role of independent evaluators
into the AI process in order to make local fair housing planning
and implementation more transparent.
Ongoing evaluation of fair housing performance will in-
crease the relevance of AI reports as planning tools. An increas-
ed emphasis on evaluation will also create incentives for local
government to identify impediments to fair housing that are
measurable and within their locus of control. There are several
potential benefits of generating data that can be used for evi-
dence-based decisions about fair housing policy. These data can
be used by those within government and outside organizations
to educate the public and advocate for fair housing reforms.
Evaluation data can also be used to identify best practices in
fair housing policy. Moreover, local jurisdictions that can cite
evaluation results in order to demonstrate progress in reducing
impediments to fair housing can increase their chances of re-
ceiving federal and state funding in the future.
This research was funded by a Sydney S. Spivack Program in
Applied Social Research and Social Policy, Community Action
Research Initiative (CARI) grant, from the American Sociolo-
gical Association. Additional funding for this research came
from a Baldy Center Small Research Grant, from the Baldy Cen-
ter for Law & Social Policy at the University at Buffalo. We
thank Scott Gehl, Jennifer Metzger Kimura, and Laurene Sch-
renk who collaborated on the evaluation of Buffalo’s 2004 AI
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