AIs



Assessments of Fair Housing
On This Page:

FAQs: Analyses of Impediments (AIs)
District of Columbia 2012
Billings, Montana 2012
Houston, Texas 2015

Clark County, Boulder City, Mesquite, North Las Vegas, Nevada AI 2011
Lakewood, Ohio AI 2011

Murfreesboro, Tennessee AI 2010
Naperville, Illinois AI 2007


Fairfax County, Virginia Analysis of Impediments 2016–2020

This analysis of impediments examines one of the wealthiest and most diverse counties in the nation. It contains the most thorough and detailed explanation yet of the Free Market Analysis™ that identifies what the racial and Hispanic of any race composition would be in a jurisdiction and its census tracts in a genuinely free housing market that is not distorted by housing discrimination. The recommendations to resolve impediments provide a pathway toward establishing a unitary housing market in which all races and ethnicities participate. Ending the phenomena that contribute to the relatively low proportions of African American households in 83 percent of the county’s census tracts would expand the housing choices of African American households that can afford to live in Fairfax County to include the county in their housing search. And it would enable the county’s efforts to get affordable housing built to be racially integrated. This AI also finds that the Commonwealth of Virginia, a Dillon state, poses impediments to fair housing choice.
Fairfax County 2016-202) AI Cover

Free Market Analysis™ Taken to a Higher Level (Houston, TX)

After HUD rejected its analysis of impediments, the City of Houston retained our services to conduct some of the portions of the AI to which HUD objected. The city produced much of the new Analysis of Impediments [this link is to the complete AI] in–house, but needed assistance from a consulting firm with the unique skills essential to conduct  three key elements [this link is to only the portions Planning/Communications produced]:

(1) We conducted our focused Free Market Analysis™ to identify racial, ethnic, and economic concentrations more accurately and fairly than the Dissimilarity Index does. Be sure to read the explanation of our methodology. The analysis identifies those census tracts, organized by Super Neighborhood, where the actual proportions of each racial group and Hispanics of any race differed significantly from the proportions that would be expected in a genuine free housing market that is not distorted by discrimination, a market in which household income and current housing costs are the prime determinants of where one lives. Based on these data, the city can prioritize where to conduct real estate testing and where households need assistance to expand their choices of where to look for housing that would give them access to greater opportunities and reduce concentrations.

(2) Although Houston does not have a zoning code, we examined its other land–use controls to identify provisions that could exclude housing affordable to households with modest incomes.

(3) We analyzed the city’s treatment of community residences for people with disabilities to identify any practices or laws that may fail to make the “reasonable accommodations” that the nation’s Fair Housing Act requires.

The city included these three reports as appendices to the AI and incorporated recommendations into the AI’s table of recommendations to overcome impediments to fair housing choice.

Houston 2015 AI Cover
The full AI is available from the City of Houston by clicking here.
The Gold Standard of AIs.

See the thorough and innovative AI we conducted for Naperville, Illinois, in 2007.
Click
here to view or download the AI.

Testimonials


Best Practices Award 2009

from the Illinois Chapter of the
American Planning Association

Each of our subsequent AIs has improved upon the “gold standard” set by the 2007 Naperville AI.
Cover Naperville AI 2007Innovation in the AI Analysis

The government of the District of Columbia has been doing more to affirmatively
further fair housing than any jurisdiction we have heard of. The challenge the District faces is that its demographics require it to do much more. This new AI goes where no AI has gone before to incorporate affirmatively furthering fair housing into the city’s routine planning and zoning practices and to bring stable racial and economic integration to gentrifying neighborhoods.
Click here to view or  download the AI.
DC AI Cover
Addressing Issues Rarely Faced

The Lakewood, Ohio Analysis of Impediments to Fair Housing Choice 2011 addresses how a city can achieve stable racial integration in the midst of a very segregated metropolitan area. The substance of the Lakewood AI is very different than any other AI we have conducted due to Lakewood’s challenging situation in which the city is beginning to integrate racially while all around it is heavily segregated.
Click here to view or download the AI.
Clark County NV AI 2011 Cover
Billings, Montana AI 2012: When Fair and Affordable Housing Meet


Known for favoring diversity over separation and isolation, the City of Billings is in a rare position where it can prevent excessive levels of racial and economic concentrations from expanding and intensifying. This AI offers guidance for collaborating with the public schools and housing authority to achieve greater socio–economic diversity throughout the city.
Cover of Billings MT 2012 AI

Further Advancing AI Innovation and Analysis:Murfreesboro, Tennessee AI 2010

Murfreesboro is a “college town,” complete with the unique characteristics and issues that brings. For decades, the city’s comprehensive plan has sought to foster racial and economic integration. This AI provides a path to achieve both.
Click here to view or download.

Murfreesboro, TN AI 2010Taking the Regional AI to a New Level

The Clark County, Nevada Analysis of Impediments to Fair Housing Choice 2011  goes beyond our previous AIs to add a new layer of in–depth analysis applied to a county AI covering three cities (North Las Vegas, Boulder City, and Mesquite) plus unincorporated Clark County. The substance of the AI is very different than the other AIs due to the very different circumstances in Clark County, Nevada.
Click here to to view or download the AI.
Clark County NV AI 2011 Cover

AI FAQs
All cities and counties that receive Community Development Block Grant (CDBG) funds from the U.S. Department of Housing and Urban Development are required to certify that they will affirmatively further fair housing. The tool used to establish that they are affirmatively furthering fair housing is the “analysis of impediments to fair housing choice.”

HUD officials have determined that “Local communities will meet this obligation by performing an analysis of the impediments to fair housing choice within their communities and developing (and implementing) strategies and actions to overcome these barriers based on their history, circumstances, and experiences.”

In all too many ways, it appears to be a conflict of interest for a CDBG recipient community to conduct an analysis of impediments itself. Try to imagine the impossible position city staff would face if asked to evaluate whether their own work — and the work of their superiors — posed an impediment to fair housing choice. In addition, few local government staff have the in–depth level of expertise on the fair housing issues needed to conduct an AI. To avoid this conflict of interest, prudent communities retain the services of an outside consultant to conduct their AIs.

We have worked with some jurisdictions that decided to conduct their analysis of impediments or assessment of fair housing in–house. We’ve tackled the parts of the AI in which their staff did not have the training to conduct themselves: Free Market Analysis™, analysis of land–use controls for possible exclusionary provisions, and analysis of zoning treatment of community residences for people with disabilities.

Planning/Communications can conduct a genuinely fair and balanced analysis of impediments that complies with the Westchester County Doctrine for your town, village, city, county, or state. While the demographics of every community are unique to that community, each of the AIs we have produced provides a good idea of the depth of research, readability, and extent of documentation we put into an AI. We do not produce a cut–and–paste AI. Although the physical structures of our AIs are similar and some explanatory information is similar (why reinvent the wheel?), the content of each AI we produce is singular for each jurisdiction studied. Each new AI we produce adds something new to the analysis as we constantly refine our techniques. For more information, please call Dan at 708/366–5200 (9 a.m. to 6 p.m. central time) or send us an email.

 A bit more about Analyses of Impediments

While the extent of the obligation to affirmatively advance fair housing is not defined statutorily, HUD defines it as requiring a fund recipient to:

  1. Conduct an analysis to identify impediments to fair housing choice within the jurisdiction
  2. Take appropriate actions to overcome the effects of any impediments identified through the analysis, and
  3. Maintain records reflecting the analysis and actions in this regard.”

Throughout the nation, HUD interprets these broad objectives to mean:

The “Westchester County Doctrine” emerges from the federal district court  decisions and August 10, 2009 settlement in the False Claims Act lawsuit against Westchester County, NY, in which the county falsely certified that it used $30 million in Community Development Block Grant funds to “affirmatively further fair housing”  — which every CDBG recipient is obligated to do when it accepts CDBG monies. The county has agreed to pay $62.5 million, develop at least 750 housing units in the most residentially segregated white municipalities in the county, and institute meaningful housing desegregation policies. The settlement has had an major impact on the way federal housing and community development funds are used throughout the country. We urge you to visit http://antibiaslaw.com to get the full details of the settlement, download the settlement agreement and the important court decisions (especially judge Denise Cote’s seminal February 24, 2009 decision).

The AIs we conduct anticipated and comply with the standards established by Judge Cote’s decision and the settlement. This reflects our in–depth understanding of the issues that AIs are supposed to address.

Learn more about what AIs are supposed to cover in chapter 2 of the District of Columbia AI.

 

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