This Toolkit does not reflect any decisions made in connection with HUD's February 9, 2023 notice of proposed rulemaking and only relates to voluntary fair housing planning conducted pursuant to HUD's June 10, 2021 Interim Final Rule and may be used to support a program participant's certification that they will affirmatively further fair housing.

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Module 2

Preparing for Fair Housing Planning and Data Analysis

Fair Housing Planning Toolkit

Module 2 Objectives:

  • Icon of check mark Learn WHAT to do to prepare for Fair Housing Planning
  • Icon of check mark Learn WHAT topics should be reviewed at a minimum consistent with the definition of AFFH
  • Icon of check mark Learn WHAT data should be leveraged in Fair Housing Planning

Module 2 Content:

Key Players

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Since Program Participants vary in size, capacity, and have different types and amounts of resources available to them, the key players may differ from entity to entity. However, that does not mean smaller Program Participants are at a disadvantage. The work that goes into Fair Housing Planning is scalable across Program Participants of various sizes, including the data analysis, Community Participation, goalsetting, and other components of a Fair Housing Plan. While it can seem complex, creating a Fair Housing Plan should be a manageable task for Program Participants of all sizes and capacities.

This stage is about preparing for the details of Fair Housing Planning, including who will be organizing and conducting Fair Housing Planning, as well as analyzing data.

Key players may include:

  • Fair Housing Plan Coordinator, who acts as the primary point of contact for Fair Housing Planning, including data analysis, Community Participation, the actual Fair Housing Planning document, fair housing goal setting, etc.
  • Data Analyst(s), including a geographer, statistician, or other data professional, if available
    • Program Participants that do not have these professionals on staff may also accomplish their data analysis with HUD-provided data tools, which were created to simplify data analysis for Fair Housing Planning, or by collaborating with data professionals at local universities, regional planning organizations, FHIPs/FHAPs, or others
  • Local Universities/Research Organizations

Key Definitions

HUD currently provides AFFH-related data through the AFFH-T Data and Mapping Tool, available at: https://egis.hud.gov/affht/.

A review of impediments to fair housing choice in the public and private sector. The AI involves:

  • A comprehensive review of a state or entitlement jurisdiction’s laws, regulations, and administrative policies, procedures, and practices
  • An assessment of how those laws, etc. affect the location, availability, and accessibility of housing
  • An assessment of conditions, both public and private, affecting fair housing choice for all protected classes
  • An assessment of the availability of affordable, accessible housing in a range of unit sizes

The analysis undertaken pursuant to the 2015 AFFH Rule that includes an analysis of fair housing data, an assessment of fair housing issues and contributing factors, and an identification of fair housing priorities and goals, and is conducted and submitted to HUD using the Assessment Tool. The AFH may be conducted and submitted by an individual Program Participant (individual AFH), or may be a single AFH conducted and submitted by two or more Program Participants (joint AFH), where at least two of which are Consolidated Plan Program Participants (regional AFH).

The term “data” collectively refers to: (1) HUD-provided data and (2) Local data. The term “HUD-provided data” refers to metrics, statistics, and other quantified information that may be used when conducting fair housing planning. HUD-provided data will not only be provided to program participants but will be posted on HUD’s website for availability to all of the public. The term “local data” refers to metrics, statistics, and other quantified information, relevant to the program participant's geographic areas of analysis, that can be found through a reasonable amount of search, are readily available at little or no cost, and may be used to conduct fair housing planning. See also 24 CFR § 5.152

Fair Housing enforcement capacity by state and local agencies or non-profits, such as Fair Housing Initiatives Program (FHIP) or Fair Housing Assistance Program (FHAP) grantees, as well as other organizations involved in fair housing, civil rights, or disability rights work. Relevant data includes fair housing laws, results of fair housing testing, charges/lawsuits, settlements, and fair housing audits.

A fair housing goal is a goal identified through the analysis in the Fair Housing Plan, to overcome fair housing issues. Program Participants are responsible for taking meaningful actions to achieve each of the fair housing goals identified in their Fair Housing Plan. Meaningful actions are significant actions that are designed and can be reasonably expected to achieve a material positive change that affirmatively furthers fair housing by, for example, increasing fair housing choice or decreasing disparities in access to opportunity.

A fair housing issue is a condition in a Program Participant’s geographic area of analysis that restricts fair housing choice or access to opportunity and community assets. Examples of such conditions include but are not limited to: ongoing local or regional segregation or lack of integration, racially or ethnically concentrated areas of poverty, significant disparities in access to opportunity, inequitable access to affordable housing opportunities and homeownership opportunities, laws, ordinances, policies, practices, and procedures that impede the provision of affordable housing in well-resourced neighborhoods of opportunity, inequitable distribution of local resources, which may include municipal services, emergency services, community-based supportive services, and investments in infrastructure, and discrimination or violations of civil rights law or regulations related to housing or access to community assets.

A document that details a review and analysis of fair housing issues in a Program Participant’s jurisdiction or region, in the public and private sectors, resulting in goals that the Program Participant sets forth to achieve over the Program Participant’s coming planning cycle. Currently, under the IFR, a Fair Housing Plan can be an Analysis of Impediments to Fair Housing Choice (AI), an Assessment of Fair Housing (AFH), or another form of Fair Housing Planning that incorporates elements from both.

The primary point of contact for Fair Housing Planning, including data analysis, Community Participation, the actual Fair Housing Planning document, fair housing goal setting, etc.

Fair Housing Planning is community planning consistent with the duty to affirmatively further fair housing, in which Program Participants analyze historic barriers to equal opportunity (the fair housing landscape) in their jurisdiction or service area and set goals to overcome those barriers and ensure fair housing choice for individuals with protected characteristics, including race, color, national origin, religion, sex (including sexual orientation and gender identity), familial status, and disability, within a community.

A condition, within the Program Participant’s geographic areas of analysis in which there is not a high concentration of persons of a particular race, color, national origin, religion, sex (including sexual orientation and gender identity), familial status, or having a disability in a particular geographic area when compared to a broader geographic area. See also 24 CFR § 5.151

Protected characteristics are race, color, religion, sex (including sexual orientation and gender identity), familial status, national origin, having a disability, and having a type of disability. See also 24 CFR § 5.152

A R/ECAP is a geographic area with significant concentrations of poverty and concentrations of people of color (e.g., Black, Hispanic, Asian/Pacific Islander, Native American/Alaska Native individuals, or other designations). To assist communities in identifying racially or ethnically concentrated areas of poverty (R/ECAPs), HUD has developed a census tract-based definition of R/ECAPs. The definition involves a racial/ethnic group concentration threshold and a poverty test. The racial/ethnic group concentration threshold is straightforward: R/ECAPs must have a non-White population of 50 percent or more. Regarding the poverty threshold, neighborhoods of “extreme poverty” are defined as census tracts with 40 percent or more of individuals living at or below the poverty line. Because overall poverty levels are substantially lower in many parts of the country, HUD supplements this with an alternate criterion. Thus, a neighborhood can be a R/ECAP if it has a poverty rate that exceeds 40% or is three or more times the average tract poverty rate for the metropolitan/micropolitan area, whichever threshold is lower. Census tracts with this extreme poverty that satisfy the racial/ethnic concentration threshold are deemed R/ECAPs. HUD’s data documentation notes, “While this definition of R/ECAP works well for tracts in CBSAs, places outside of these geographies are unlikely to have racial or ethnic group concentrations as high as 50 percent. In these areas, the racial/ethnic group concentration threshold is set at 20 percent.” See also 24 CFR § 5.151

Segregation is a condition within the Program Participant’s geographic area of analysis in which there is a high concentration of persons of a particular race, color, national origin, religion, sex (including sexual orientation and gender identity), familial status, or having a disability or a type of disability in a particular geographic area when compared to a broader geographic area. See also 24 CFR § 5.151

Significant disparities in access to opportunity are substantial and measurable differences in access to educational, transportation, economic, healthcare, and other important opportunities in a community based on protected class in housing. See also 24 CFR § 5.151

Timeframes

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We estimate that this Fair Housing Planning task of Preparing for Fair Housing Planning should take approximately 10 business days.

The length of time Fair Housing Planning takes may vary based on the size of the Program Participant, the different types and amounts of resources available to them, or the number of barriers to fair housing choice that must be analyzed. The timeline provides information on how long an estimated planning task might take. The work that goes into Fair Housing Planning is scalable across Program Participants of various sizes, so while it can seem like a complex task, creating a Fair Housing Plan is a manageable task for Program Participants of all sizes and capacities.

As you are beginning to prepare for Fair Housing Planning, consider the following:

  • Before Fair Housing Planning commences, identify a key data analyst(s) and needed data resources
  • Before Fair Housing Planning commences, decide on the format for the Fair Housing Planning document
  • Before Fair Housing Planning commences, understand the topics that should be reviewed from a fair housing perspective consistent with the definition of AFFH

Module 2.1: What to do to Prepare for Fair Housing Planning?

HUD’s AFFH IFR reinstated a process for Program Participants to conduct Fair Housing Planning and take meaningful actions based on that Fair Housing Planning. The IFR does not require Program Participants to undertake any specific type of Fair Housing Planning to support their certifications, however Program Participants may wish to choose a format they are familiar with, such as utilizing the Assessments of Fair Housing (AFH) format, Analyses of Impediments to Fair Housing Choice (AI) format, or other forms of Fair Housing Planning.

You’ll want to assemble your Fair Housing Planning team as you prepare for Fair Housing Planning. HUD recommends that Program Participants designate a Fair Housing Plan Coordinator to act as the main point of contact, as well as a Data Analyst(s) such as a geographer, statistician, or other data professional, if available. Please note that this is not necessary for Fair Housing Planning depending on the size and capacity of the Program Participant and also may be accomplished by using the AFFH-T or collaborating with local universities, regional planning organizations, or FHIPs and FHAPs. Your Fair Housing Planning team will help prepare the Fair Housing Plan by conducting the necessary data collection and analysis, which will ultimately inform setting fair housing goals.

Deciding what data and topics will be included in a Fair Housing Plan is a necessary initial step. In Module 1 of this Toolkit, you took time to orient yourself with AFFH.

A Fair Housing Plan should assess:

  • Patterns of segregation and/or integration on the basis of the Fair Housing Act’s protected characteristics, including racially or ethnically concentrated areas of poverty
  • The relationship of those residential patterns of segregation to access to opportunity on the basis of protected characteristics
  • Fair housing issues related to publicly supported housing
  • Fair housing enforcement infrastructure

The assessment conducted in the Fair Housing Plan will inform setting meaningful fair housing goals, which ultimately should lead to meaningful actions to meet the AFFH obligation.

Module 2.2: Utilizing Data Resources for Fair Housing Planning

To assess patterns of segregation, access to opportunity, and many other fair housing issues, Program Participants often use data and local knowledge. This module will help Program Participants understand what to do to prepare and utilize data resources for Fair Housing Planning.

Both HUD-provided data and local data should be used to assess a Program Participant’s fair housing issues and to set corresponding fair housing goals. Data must be assessed across the Program Participant’s geographic areas—locally and regionally—and provide benchmarks to measure trends and changes over time. Analyzing jurisdictional and regional data together may help Program Participants examine whether adjacent communities influence housing demand or housing patterns within the relevant jurisdiction or service area, for example, through zoning codes, occupancy standards, and other laws relating to housing and community development. It may also be important to analyze differences in the availability, quality, and accessibility of other amenities across a region, such as public transportation, schools, grocery stores, jobs, sidewalks, water, sewer, and sanitation services, which can limit housing choice on a protected class basis.

Key Considerations for Data Collection outside AFFH-T

Know the limitations of HUD-provided data.

  • Explore how to define R/ECAPs within the context of your community and area if the HUD definition is not useful.
  • Census tracts may be less useful in areas where those tracts span hundreds of square miles, such as in rural areas. Generally, poverty is more dispersed in rural areas, and segregation patterns often include fewer people of color. Due to these demographic differences, some rural areas may want to explore how to define R/ECAPs in their areas.
  • Due to the concentration of minority groups in predominantly Black, Asian, Hispanic, and/or Native American areas, some majority minority areas should pay special attention to assessing patterns of integration among the various populations. It is important to note that segregation in the form of ethnic enclaves is often viewed in a more nuanced manner than other types of segregation. For example, the concentration of tribal communities on reservations is often seen as an asset to supporting tribal culture and economy.
  • Utilize input from the Community Participation process, administrative records, and other local data and local knowledge sources. Community Participation may be challenging in rural areas where, in contrast to larger urban regions, there may be fewer groups (or less of an organizational infrastructure) to represent protected class populations.
  • Highlight regional analysis and comparisons. Regional data, such as data on disparities in access to opportunity, may be useful in determining whether areas are disconnected or excluded from areas of opportunity.

Leverage local data and local knowledge. Utilizing input from the Community Participation process, administrative records, and other local data and local knowledge sources can be instrumental in Fair Housing Planning. Examples of local knowledge that may be relevant to Fair Housing Planning include, but are not limited to:

  • Local history on fair housing issues and the capacity of fair housing outreach and enforcement efforts in the jurisdiction and region;
  • Historical trends in types of fair housing complaints filed in the region. Local Fair Housing Initiative Programs (FHIPs) have this data;
  • Major redevelopment plans, including community-based revitalization efforts, transit-oriented development initiatives, and information about the neighborhoods in the jurisdiction and region that are most in need of revitalization;
  • State and local laws, regulations, and processes, such as occupancy, land use, and zoning codes, ordinances, regulations, and procedures;
  • Changes to public housing, including demolition or disposition applications and Rental Assistance Demonstration (RAD) conversion applications;
  • Plans to build, renovate, or demolish schools, libraries, parks, community gardens, recreation centers, transportation assets, etc.;
  • Changing community living patterns in the jurisdiction or region, such as neighborhoods subject to gentrification where affordable housing may be at risk, neighborhoods impacted by large numbers of foreclosures, and increased demands on public transportation or schools.

Data Resources

Checklist

  • Icon of check mark Decide on format for voluntary Fair Housing Planning document (AI, AFH, or another format)
  • Icon of check mark Decide on Needed Data Resources utilizing HUD List and Local Data and Knowledge
  • Icon of check mark Decide on Key Data Analyst(s), including how a Program Participant may leverage a local University or FHIP/FHAP, or the AFFH-T
  • Icon of check mark Decide how to engage the community with data

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