3

The Promise Fulfilled?

Taking Stock of Assessments of Fair Housing

NICHOLAS F. KELLY, MAIA S. WOLUCHEM,
REED JORDAN, AND JUSTIN P. STEIL

The Department of Housing and Urban Development (HUD) created the Affirmatively Furthering Fair Housing (AFFH) Rule to undo generations of policies that have left America’s cities deeply segregated and unequal. But as demonstrated by a half century of halting fair housing progress and lack of enforcement of the Fair Housing Act’s provision mandating that HUD and its grantees affirmatively further fair housing, the prospects for real change even after the AFFH’s Rule passage were unclear. After years of effort at crafting the rule, its passage raised several pressing questions. To what extent would municipalities resist efforts to reduce segregation and to increase access to place-based opportunities, or take meaningful steps to advance fair housing? Would HUD staff essentially ignore these fair housing plans, as they had previous ones for decades, or would they thoroughly review and provide municipalities with meaningful feedback? Would the new rule, so delayed, debated, and finally, as the previous chapter demonstrated, pushed through with bureaucratic jiu-jitsu, live up to its promise?

In this chapter, we examine the effectiveness of the AFFH Rule in helping jurisdictions craft policies that provide more equal access to place-based resources and access to housing in areas rich with opportunities. With limited private remedies to advance the AFFH provision in the courts, the success of the rule before its suspension depended in large part on the enforcement system that HUD implemented. From October 2016 through January 2018 (when HUD suspended the rule), 49 sets of HUD grantees, representing 103 municipalities and public housing agencies from across the country, submitted plans to affirmatively further fair housing, called Assessments of Fair Housing (AFHs). In previous research, we have demonstrated that these plans represented a vast improvement on the Analyses of Impediments (AIs) previously required by HUD.¹ The AFFH Rule provided municipalities with relevant, locally tailored data; required municipalities to analyze and reflect upon those data; and asked municipalities to propose clear, realizable goals in response. This specificity stood in stark contrast to previous vague guidance on submitting AIs—plans that HUD rarely ever read and that did not require municipalities to demonstrate progress toward fair housing objectives. In the AFH process, HUD and other partners offered training to municipalities on how to successfully complete their fair housing plans under the new rule; reviewed every AFH to ensure that it fulfilled the standards required by the regulation; and refused to accept some substandard AFHs until municipalities made revisions.²

We collected all forty-nine AFHs that were reviewed by HUD before the Donald Trump administration suspended the AFFH Rule in January 2018—including the thirty-two that HUD accepted and the seventeen that HUD rejected. We then coded and analyzed these plans to identify the types of goals that the municipalities proposed. To examine the robustness of the plans, we determined whether the goals included (a) an objective supported by numerical metrics or milestones that would allow quantifiable evaluation of progress or (b) a new policy or program to accomplish that objective. Finally, we analyzed those data to understand which jurisdictions were more likely to submit fair housing plans with quantifiable objectives and to propose new policies to realize those objectives. We also sought to understand how they implemented the rule’s “balanced approach” to housing mobility and place-based investments. Case studies of fair housing plans in Seattle, Washington; Temecula, California; Hidalgo County, Texas; and the Kansas City Metropolitan Area—including interviews with lead authors of all four of those plans—highlight the nuances of the AFFH Rule and the complexities that municipalities face when creating their fair housing plans.

Who Participated in the Assessment of Fair Housing Process?

The forty-nine municipalities that submitted AFHs varied along a number of metrics relevant to their responsibility to affirmatively furthering fair housing. HUD scheduled the due date for AFH submissions based on the due date for a municipality’s Consolidated Plan. As a result, the municipalities that submitted AFHs were, if not quite randomly selected, then at least arbitrarily designated to submit their proposals before the rule’s suspension. As Table 3.1 shows, these municipalities represented a broad swath of counties, cities, and towns from across the United States, from large counties (Los Angeles County) and big cities (Philadelphia) to small cities (Ithaca, New York) and small counties (Manatee County, Florida); from regional submissions (Kansas City) to smaller cities operating within a large fragmented metropolitan region (Somerville, Massachusetts). Table 3.1 also shows the range of levels of segregation within these communities, as measured by the Black-white dissimilarity and Latinx-white dissimilarity index, which indicates the proportion of a group that would need to move to create a uniform distribution. For this group of municipalities, the median Black-white dissimilarity index is 38, while the median Latinx-white dissimilarity index is 34. These medians among the AFH submitters can be compared to the national median Black-white dissimilarity score of 53 and the median Latinx-white dissimilarity score of 41.³

As discussed in the Introduction, Chapter 2, and Chapter 8 of this volume, the AFFH Rule relies on collaboration between the federal government and state and local governments. HUD’s rule and the Assessment Tool provide data, set out a broad framework for analysis, and ask localities to craft locally tailored goals based on that analysis. Planning scholars conducting research in other contexts have found that characteristics associated with successful future implementation include the factual basis of the plan, the presence of goals based on measurable objectives, and the specification of policies designed to achieve those goals.⁴ To be effective, plan goals must be specific enough to be able to be tied to concrete actions, supported by a written commitment to carry out those actions, and include provisions for measuring progress. These include indicators of advancement, timelines for completing the required actions, and identification of the parties responsible for implementation.⁵ Through the Assessment Tool, HUD provides municipalities with data as a starting point, requires them to analyze those data, and asks them to answer specific questions that HUD poses in the AFH Tool. The factual basis of the plans, therefore, has at least a shared baseline. There is significant variation, however, in the goals that municipalities put forth in their AFHs, the metrics they present to evaluate progress, and the new policies, if any, they plan to create to realize the goals. Accordingly, imperfect but consistently measurable proxies for plan quality or robustness among AFHs are commitments to measurable objectives or to the creation of new policies to implement goal objectives.

The presence of measurable objectives gives local residents and fair housing advocates clear benchmarks by which to hold local governments accountable for their progress on fair housing. A lack of measurable objectives, on the other hand, may indicate a conscious or unconscious effort to avoid accountability to either HUD or the public. Similarly, a new planned policy or program reflects an assessment of the obstacles to fair housing and an analysis of a specific, novel path to overcome that obstacle. Creating a new policy or program can involve the expenditure of political or financial capital by local government officials to secure its approval and allocate staff to execute it; officials are unlikely to provide those resources if they see it as a waste and unlikely to deliver results.⁶ These two measures—whether a particular goal has a measurable objective and whether it represents a new policy—are the criteria by which we evaluate goals in the AFHs we analyze in this chapter.

The AFFH Rule is a form of meta-regulation that requires municipalities to develop a locally-tailored plan. As such, it allows municipalities significant leeway in shaping their plans.⁷ Research on meta-regulation finds these types of regulations tend to be particularly successful when they have commitment from local stakeholders. We measure local commitment—which we expect to be associated with robust AFHs—first through local political ideology, which runs on a scale of –1 for most liberal and 1 for most conservative. Given the partisan divide on the AFFH Rule, we expect more liberal municipalities to express a greater commitment to it.⁸ We also measure commitment through the strength of local nonprofit fair housing organizations funded by HUD’s Fair Housing Initiatives Program (FHIP), given that fair housing is a low-salience issue and historically driven in part by these groups. Additionally, we examine the number of complaints alleging housing discrimination filed with HUD’s Office of Fair Housing and Equal Opportunity (FHEO), given the importance in the past of these suits to force municipalities to act to address fair housing issues.⁹ We also measure commitment by examining local socioeconomic conditions, which may shape fair housing efforts, as well as measures of heterogeneity and segregation that can influence the political context for creating policies to reduce racial disparities and demographic conditions.¹⁰ Existing research has also found that greater capacity is associated with more rigorous compliance with meta-regulation.¹¹ As a result, we operationalize capacity by calculating the overall amount and efficient use of Community Development Block Grant (CDBG) funding as measured through HUD’s “timeliness” measure in 2015 or 2016. We gather these data from the 2013–2017 5-Year American Community Survey, American Ideology project, and HUD.¹² We present summary statistics on these variables in Table 3.2.

Grantees vary widely across these measures of socioeconomic status, demographic composition, likely commitment, and estimated capacity. From large CDBG-funded cities (such as Philadelphia, with a CDBG allocation of more than $38 million) to smaller towns (such as Rogers, Arkansas, with a CDBG allocation of less than $500,000); from very conservative areas (such as Springdale, Arkansas, with a conservatism score of .42) to very liberal ones (such as New Rochelle, New York, with a score of –.53); from regions with low unemployment (such as Lewisville, Texas, at 4.2 percent) to small cities with high unemployment (such as Greenville, North Carolina, at 10.2 percent)—not only do these jurisdictions vary greatly in their level of segregation; they also range significantly in their demographic composition, from 89 percent white in Lake County, Ohio, to 4 percent white in Paramount, California.

What Did the Resulting Assessments of Fair Housing Look Like?

To evaluate the the AFHs, we build on the literature on plan quality by assessing fair housing goals in the AFHs in two ways. First, we code each goal in every assessment of fair housing in the forty-nine plans discussed here to evaluate whether the goal has a measurable objective, with a numerical metric or milestone presented to allow quantifiable evaluation of progress. Second, we examine whether the goal results in a new policy to achieve that objective. We also focus on a number of other substantive measures of the goals put forth in the fair housing plans—in particular, whether the goals advance place-based investments to reinvest in low-income communities or support promoting mobility for protected classes to access areas of greater opportunity. We also examine whether each goal falls into a variety of other categories, as illustrated in Table 3.3. Each goal can fall into multiple substantive categories and have quantifiable metrics or be considered a new policy. For example, the goal in Chester County, Pennsylvania, to encourage mobility among low-income residents living in areas of poverty by decreasing the number of voucher holders living in a high-poverty area from 43.9 percent to 39 percent would be coded as having a measurable objective concerning mobility and voucher holders.

In Table 3.4, we present the types of goals present in each plan and the number and share of those types of goals that contain a measurable objective or include a new policy. Of the 857 goals in 49 AFHs in our sample, 255 of them address affordable housing, by far the most dominant focus area. Fair housing education and disability access are the next most common goals. On the other hand, homeownership and place-based goals are the most likely goal types to have measurable objectives. Zoning and mobility goals are the most likely to be accompanied by new policy efforts.

We next compare those municipalities that put forward goals with a large number of measurable objectives or new policies as compared to those that did not. Table 3.5 presents those municipalities that score in the bottom tercile according to these measures, with two or fewer goals meeting these criteria, compared to those in the top tercile, with six or more goals meeting these criteria. The only statistically significant difference between the two groups is the measure of Black-white dissimilarity, in which municipalities with more measurable objectives or new policies have higher levels of Black-white segregation than those municipalities with fewer measurable objectives or new policies.

To further test this relationship between municipal characteristics and goal characteristics, we estimate the relationship between the number of goals with a measurable objective or a new policy and measures of local context and capacity. In Table 3.6, we run four models to test the association of various municipal characteristics on a municipality’s overall number of goals with a quantifiable metric or a new policy. In Model 1, we start with the one municipal characteristic that is significantly different in Table 3.5 and confirm that more segregated areas—those municipalities with larger Black-white dissimilarity indexes—have more measurable objectives and new policies in their AFHs. This association holds consistently across Model 2, where we control for municipal population. This model also reveals a statistically significant positive association between more populous municipalities and a larger number of quantifiable metrics and new policy goals. Model 3 adds measures of capacity, none of which show statistically significant relationships with measurable objectives or new policies. Model 4 adds other socioeconomic variables and finds a positive relationship between median household income and the continued significance of Black-white segregation with the number of measurable objectives or new policies in the fair housing assessments. The fact that this positive correlation between more segregated municipalities and more quantifiable goals and new policies persists after controlling for other relevant characteristics suggests that, according to at least one metric, the AFFH Rule was working as intended. Grantees with higher levels of segregation propose more concrete steps to reduce segregation and make access to place-based resources more equitable in their communities compared to those grantees with lower levels of segregation.

In Table 3.7, we compare plans that have the most goals focused on place-based investments and support for mobility—what many HUD program participants believed were the core issues of the AFFH Rule—with plans that have the fewest such goals. Municipalities that submitted plans with more of these goals tend to have more CDBG funding (a function, in part, of their being large cities with comparatively high numbers of residents in poverty); be more ideologically liberal; and have a greater number of cases filed by HUD’s FHEO office alleging discrimination in violation of the Fair Housing Act. As above, more segregated municipalities—as measured by not only Black-white dissimilarity but also non-white–white dissimilarity and Asian-white dissimilarity—have more goals focused on placed-based investments and on mobility than other municipalities.

We test this relationship more rigorously by estimating the relationship between the number of goals focused on mobility and on place-based investments and municipal characteristics, as seen in Table 3.8. The results in Models 1 through 4 indicate that a higher Black-white dissimilarity score is initially associated with more goals focused on mobility and place-based investments, but this relationship disappears once we control for the capacity of a municipality, measured by the value of local CDBG funding. The amount of CDBG funding—even when controlling for population—is positively associated with more goals focused on mobility and place-based investments. This connection suggests that the larger federal community development investment—allocated according to measures of population, share of population in poverty, and either share of overcrowded housing units or share of housing units built before 1940—is associated with more fair housing goals focused on increasing access to opportunity either through place-based investments or through support for mobility programs, when compared to those with lower levels of CDBG investment. In addition, the number of cases filed by HUD’s FHEO office (at the county level, per million residents) is also a significant predictor of these place-based and mobility goals.

Case Studies

The forty-nine municipalities that submitted AFHs to HUD took varied approaches. Some, such as Hidalgo County, Texas, and Kansas City, Missouri, submitted regional plans to address fair housing, combining the work of several municipalities and housing authorities. Others, such as Temecula, California, focused on a narrow set of policy solutions and submitted an AFH with only four highly prescriptive goals. In this section, we examine four fair housing plans that vary along a number of relevant dimensions, but especially the capacity of the submitting grantees, in order to examine their varying approaches. We also conduct interviews with key staff working on those fair housing plans to understand the benefits and challenges they encountered with implementation. First, we examine Seattle, Washington, a city with substantial resources, that submitted a bold and creative initial assessment of fair housing. We then examine Temecula, California, a smaller city with less capacity that submitted a plan that was initially rejected and subsequently revised and accepted. We then examine two regional AFHs: one plan conducted by Kansas City, including five communities in total; and one by Hidalgo County, Texas, including eighteen housing authorities and municipalities. By examining variation within fair housing plans and by municipality type, we illuminate the diversity of municipal responses to the AFFH Rule.

Seattle: Building on a History of Racial Equity Work and Pursuing Fair Housing in a High-Cost City

Before embarking on the AFH process, Seattle was already engaged in extensive multi-agency collaborative work focused on racial equity and on affordable and fair housing. The AFH process provided an opportunity to reflect further on this existing work, to clarify how existing projects related to each other and to fair housing, and to cement many of these commitments in a single plan with goals and metrics. Seattle’s extensive AFH also provides an illustration of how complex fair housing can be in high-cost cities where displacement is at the forefront of the minds of many working-class households, especially households of color, not segregation or integration. As Seattle’s AFH emphasizes, in these high-cost contexts, anti-displacement work is a central strategy to advance integration, and the common conflations of mobility with integration and place-based investments with continuing segregation do not hold up.

Seattle’s AFH stands as a robust encapsulation of the city’s multipronged efforts to increase racial equity and includes important critiques of the federal AFFH Rule with suggestions for improvement to more effectively secure fair housing for future generations. The project represents a collaboration between more than a dozen departments, including the Seattle Housing Authority. While a regional collaboration with Seattle’s frequent partner King County and its housing authority was considered, given the level of coordination already involved within the city, the city decided not to pursue a regional collaboration.¹³

In 2009, Seattle set out a series of public commitments through the creation of its Race and Social Justice Initiative. Out of this effort came several reports and smaller initiatives, including the Seattle 2035 Growth Management Plan, Seattle 2035 Growth & Equity: Analyzing Impacts on Displacement & Opportunity Related to Seattle’s Growth Strategy, and the Mayor’s Resolution 31577 committing to racial and social equity.¹⁴ Seattle expands upon these plans in its AFH, using momentum gained over the previous years of work to tackle such issues as education, employment, and economic development. In addition to putting forward a strategy that reaches across multiple city agencies, the plan also effectively builds upon preexisting efforts to advance racial equity to highlight place-based policies as a powerful mechanism to combat inequity in the city. Staff in Seattle thus note that the AFH plays a useful role in helping bring together initiatives already underway:

In contrast to some of the other forty-nine municipalities focusing more intently on mobility-based strategies, Seattle struggled with the tension between place-based investments in existing low-income neighborhoods and the implicit consequence of mobility-based strategies in contributing to ongoing neighborhood change. This tension reflects Seattle’s approach to the AFH as just one aspect of a complex web of overlapping policies and legislative attempts to mitigate the history of white supremacy in the city. Seattle’s staff critique the AFFH Rule, as follows:

Given this position, Seattle’s AFH takes care to focus on a broad conversation about equity. The City of Seattle and the Seattle Housing Authority view the effort as a wide-reaching endeavor, writing that “it was difficult to ensure that the AFH was not limited only to impacts on vulnerable populations. It was necessary to remind agencies, stakeholders, and participants that the AFH is about inequity and potential discrimination regardless of income on a broader scope and scale than in prior planning.”¹⁷

In Seattle, a high-cost city where gentrification and displacement are primary concerns, the struggle to balance place-based and mobility-based initiatives was particularly evident. As Seattle staff note:

The example of Seattle’s AFH illustrates how in high-cost cities, anti-displacement efforts and affordable housing preservation investments are a crucial integration strategy. These place-based investments are increasingly essential to ensuring that residents of color, people who are disabled, and others have the opportunity to live in neighborhoods rich with public amenities and economic opportunities. These place-based investments in Seattle have the potential over the long term to be more effective at achieving the central goals of mobility strategies for access to opportunity than a mobility strategy could be, as central-city housing costs continue to rise. Seattle’s plan also includes goals related to housing mobility, although without clear measurable objectives. For example, an explicit goal of Seattle’s AFH focuses on providing more housing choices for families, for which the policy prescriptions range from funding larger units to offering financial assistance to families looking to live in higher-opportunity areas. These strategies are part of a greater effort to mitigate the dearth of properties available to larger households in Seattle’s existing housing stock but are less structured than in some other jurisdictions’ AFHs.

These mobility-related goals are part of a careful balance in Seattle’s AFH between place-based and mobility goals. On the whole, Seattle makes a case for mobility to high-opportunity neighborhoods as a potential alternative to gentrification-induced displacement to high-poverty neighborhoods, a source of much community disruption in Seattle. Notably, the Seattle Housing Authority is also participating in the national “Creating Moves to Opportunity” project, an evaluation of its mobility interventions, with the Abdul Latif Jameel Poverty Action Lab.¹⁸ These concurrent projects allow the city to fully absorb its work on Creating Moves to Opportunity into an effort that focuses on mobility as a tool for fair housing. Seattle also creates a number of goals focusing on place-based investments, particularly those that can improve housing quality and prevent displacement caused by gentrification. Seattle highlights a number of ways it is working to mitigate displacement by building medium-term affordability into the portfolios of high-displacement neighborhoods and by supporting low-income and marginalized individuals at risk of displacement. The place-based goals address a number of different areas of focus, including equitable access to schools, environmental justice, and affordable housing.

Seattle also uses its AFH to highlight some of the limitations of the process, in scope and in execution. Seattle’s AFH challenges HUD on several of its metrics, including the widely used dissimilarity index, generally implemented to measure segregation but limited to measuring the geographic dispersion of only two groups at a time. In its AFH, Seattle notes that the metric’s comparison of communities of color to white communities limits the city’s ability to truly assess the diversity of its neighborhoods. As an example, its 2017 assessment cites a number of neighborhoods in which a diverse group of people of color are the majority (South Park, High Point, Rainier Valley, Pioneer Square, the International District, First Hill, and the Central Area), noting that just using a white–non-white dissimilarity measure does not reflect the diversity of many of the city’s neighborhoods.¹⁹

Seattle pushes HUD to consider new measures in other parts of its AFH, including measuring Racially and Ethnically Concentrated Areas of Poverty (R/ECAPs). In particular, staff note that “changes in R/ECAP status can happen solely as an artifact of the large margins of error inherent in the American Community Survey (ACS) estimates used to test for R/ECAP status. This suggests a need to consider neighborhood demographic and socioeconomic conditions in a more holistic way that goes beyond ACS estimates.”²⁰ In addition, given Seattle’s articulation of a long-term strategy advancing racial equity, the city already has detailed knowledge of the data representing its communities. As described in its AFH, Seattle’s engagement strategy was held up for four months due to an inconsistent inclusion of data “from the 1990, 2000, and 2010 Census regarding multi-racial individuals. This population represents approximately 5 percent of Seattle’s total population. The lack of this data could potentially skew results for concentrations by race and ethnicity.”²¹ Seattle notes a number of other limitations to the AFH process. Given that Seattle is one of the first municipalities to submit an AFH, staff note that they did not receive the assessment of fair housing mapping and database tool until four months into the process.²²

Despite these drawbacks, Seattle staff note that many parts of the AFH are immensely beneficial—namely, the value of the data and maps provided by HUD, which staff use in community meetings to create a “much richer dialogue” than would exist otherwise. The maps are particularly beneficial to the community process:

Seattle’s staff note that by freezing the rule, HUD is preventing the city from tracking trends over time. This issue is particularly important because, as a result of the AFHs being submitted before HUD’s suspension of the rule, Seattle is actually required to integrate its AFH goals into its Consolidated Plan and report on progress toward those goals. But without the updated data, Seattle’s task becomes much more difficult. Staff in Seattle also note that HUD’s freezing of the rule is creating a large amount of uncertainty about future work on the AFH Rule in terms of losing momentum around these issues and figuring out next steps. Also, in terms of implementation, Seattle notes that the AFH adds particular value around disability issues. As a result of the process, the rule gives departments the ability to raise those issues with more urgency.²⁴

Overall, Seattle’s AFH has a clear focus on racial equity and sets out meaningful goals to advance fair housing. The Seattle strategy addresses a balance between the place-based strategies that support vulnerable communities and the option to move to high-opportunity neighborhoods that individuals who experience poverty may also choose. The AFH illustrates how this balance is complicated in a high-cost city, where the significant need for place-based anti-displacement work could also be considered a strategy to promote integration and preserve neighborhood diversity. The fact that a high-capacity city such as Seattle finds HUD’s data so useful—and argues for the need to bring the datasets back to allow for continued implementation of the AFFH Rule—speaks to the power of data and mapping in the AFH process to help governments have more impact within their communities.

Temecula: A Relationship with HUD Breeds Better Results

Temecula, California, was one of seventeen municipalities to receive a letter of “non-acceptance” from HUD. HUD’s review of the AFH found that Temecula’s initial submission in October 2015 had vague metrics that were occasionally beyond the jurisdiction’s purview, prompting HUD to ask for a revision that Temecula submitted in January 2017.

Temecula’s initial AFH features nine goals that are not clearly tied to the required analysis of the HUD-provided data. Goals in the AFH should be tied to contributing factors that affect the current state of fair housing in the jurisdiction authoring the plan—such issues as lending discrimination, land-use and zoning laws, or lack of regional cooperation. In the original AFH, some goals have contributing factors that are not supported by the analysis the city has conducted in the AFH, and the goals are framed in terms of regional programs that are not within Temecula’s power to control. Temecula staff note that part of the reason for those vague goals is a lack of clarity about exactly what municipalities should include as part of their fair housing goals. As one staff member notes:

This question points toward a difficulty that a number of municipalities encounter in balancing the need for measurable, meaningful goals with actions that they can realistically achieve. Temecula staff also note that since HUD itself was also figuring out how to implement the AFH Rule during the process, writing the AFH led to an increased burden on staff time.²⁶

HUD proposed a range of changes to Temecula’s AFH after the initial submission, adding new and relevant contributing factors and focusing on goals and policies that were actually within the power of the Temecula City Council or city agencies to achieve. For example, Temecula’s second draft removes goals addressing access and usage of the regional public transportation network. These revisions are not a statement about these goals’ importance to fair housing but allow Temecula to focus on those aspects of the AFH that the municipality has the jurisdiction and resources to change. In an interview, Temecula staff note that they included that original goal because they thought the maps showed that transportation issues were an obstacle to achieving fair housing—but once HUD clarified the importance of focusing on actions within the city’s control, they simply removed it.²⁷ This back and forth indicates that in some cases, municipalities trying in good faith to comply with the regulations had difficulty interpreting HUD’s mandate.

HUD also urged Temecula to revise some original goals for more clarity, including such vague pronouncements as “Increase the affordable housing stock in the City.”²⁸ In its revised goal, Temecula provides much more specificity, proposing instead an Affordable Housing Overlay “accommodating 2,007 affordable units for lower income households.”²⁹ This careful look at the goals of the AFH led to a more robust and actionable set of aims in Temecula’s revision, grounded in data, metrics, and realistic hopes of achievement. Each goal in Temecula’s new AFH is followed by a detailed discussion, demonstrating the research behind the goal and the precedents that make pursuing this goal possible. In contrast to some other AFHs with a large number of goals, Temecula’s final version has only four, which could make the plan more comprehensible to a broad audience and therefore more manageable to implement. Although they are targeted in their focus, Temecula staff put forth a number of measurable actions under those four categories.

Beyond the improvements to the AFH, HUD’s technical assistance seemed to foster a positive relationship between HUD and Temecula.³⁰ City officials made great use of the technical assistance available to them through HUD, ultimately completing three rounds of revisions. Temecula staff indicate that the short time frame between revisions and an initial lack of mutual understanding about the requirements of the process led to some strain, but that overall they perceived the AFFH process as positive.

Temecula staff describe a few ways that this process facilitates future implementation. The AFH caused them to examine issues they would not have considered previously, including the strengths and weaknesses of their housing programs. Specifically, as with Seattle, their fair housing analysis revealed issues related to access for people with disabilities. They identified a need for more affordable housing for their special-needs residents. Similarly, the process pushed Temecula to complete an Americans with Disabilities Act transition plan.³¹

Hidalgo: A Wide Lens, a Less Effective Focus?

One innovation of the AFH process is to encourage regional collaborations between local jurisdictions. In the next two case studies, we examine two regional submissions. First, we examine Hidalgo County, Texas, a county on the U.S.-Mexico border with a median household income of $37,000 (one of the lowest among initial AFH submissions). As with Temecula, HUD initially rejected Hidalgo’s submission. However, unlike Temecula, Hidalgo was still in the process of submitting a revision when HUD suspended the AFFH Rule. The first submission completed in October 2017 includes coordination between nineteen program participants, including fourteen housing authorities operating within the county. The community engagement efforts are robust, including about three hundred local stakeholders and organizations throughout the region, in addition to a survey of nearly six hundred community members representing all zip codes in Hidalgo County and several in-person community meetings. However, this incredibly wide net may have also contributed to the lack of specificity in Hidalgo’s AFH that spurred the eventual request from HUD to submit a revised draft.

Although the AFH was submitted using Hidalgo County as the geographic boundary, the submission includes the efforts of the five entitlement communities in the McAllen-Edinburg-Mission Metropolitan Statistical Area (a geography defined by the Census as containing a significant population as well as adjacent communities connected to that population hub), including the Hidalgo County Urban County Program, and Cities of Edinburg, McAllen, Mission, and Pharr. Each of the five entities entered into a Collaborative Interlocal Agreement with the fourteen public housing authorities active within each of their jurisdictions. This regional partnership is not new to Hidalgo County; these particular entitlement communities have collaborated several times for other federal initiatives, including three previous Consolidated Plans. However, this particular effort is the first to include the Public Housing Authorities (PHAs), expanding their capacity to speak to issues of fair housing. Staff in the Hidalgo County Urban County Program explain that the housing authorities signed onto the proposal because of this history of regional collaboration and because it would reduce the regulatory burden, especially for small housing authorities with little staff support.³²

Because the number of participants is so large—by far the largest participant cohort in any of the forty-nine submissions—a governing structure was created to coordinate efforts. Hidalgo County Urban County Program led the effort, with the cities of Edinburg, McAllen, Mission, and Pharr as well as the Housing Authorities of the County of Hidalgo, Edinburg, McAllen, Mission, and Pharr rounding out the executive committee. Each of the remaining nine housing authorities composed a “General Committee.” To complete the work, Hidalgo County initiated a structure intended to meet the needs of each area of the AFH. Each committee member served on a number of subject-matter subcommittees, including education, transportation, poverty, disability and access, and others.

Hidalgo County’s goals include affordable housing, infrastructure improvements, social services, economic development, and public facilities. However, the county fails to fully explain what interventions the collaboration aims to implement and how. For example, Goal #6 reads “To expand economic opportunities in Hidalgo County,” yet the metrics and milestones remain vague, noting that participants would “support goals and projects identified within provider’s long-term strategy,” among other interventions.³³ Ultimately, Hidalgo County’s AFH reflects competing interests: each of its nineteen parties has a particular commitment to the issues affecting that specific jurisdiction, leading to a lack of clarity about overall goals for the entire county.

An interview with staff reveals further reasons for vague metrics, which speak again to the conflicting incentives that municipalities face when developing fair housing goals, especially in a regional context. Staff note:

Within two months of their initial October 2017 submission, the Hidalgo County Collaborating Program Participants received a letter from HUD requesting specific revisions of the AFH “to meet the requirements under the AFFH rule.” Although they were one of several to receive this notice to resubmit, they were one of only a small group of jurisdictions asked to submit a revision in late 2017. This initial letter was sent on December 12, 2017, but by January 5, 2018, it proved a moot point once HUD moved to suspend the AFFH Rule. As a result, the Hidalgo team never had the opportunity to work with HUD, as Temecula did, to improve its AFH.

Although Hidalgo County’s revised AFH was stymied by federal policy changes, the letter still serves as an illustrative window into the aims of the program, particularly for those jurisdictions with such wide-ranging regional aspirations. In Hidalgo County’s case, much of HUD’s feedback focused on issues related to goal setting. Because the range of participants was so broad, they proposed goals that lacked specific and quantifiable metrics and milestones or responsible parties, thus making the goals much more difficult to enforce. HUD’s revision letter to Hidalgo County recommends that the collaborative revise each goal to make it easier to evaluate and to ensure that the participants would actually reinforce fair housing throughout their individual geographies and the entire jurisdiction overall. Hidalgo County’s staff note that, had they been able to proceed with the AFH, they would have required those actors who had been absent from the process to actually implement the goals in their revised fair housing plan.³⁵

Despite the arrested development of Hidalgo County’s plan due to HUD’s freezing of the AFFH Rule, staff there say the process was a vast improvement over the previous AI requirements. They note that they were able to learn a lot about their community through the local data they were required to collect as part of the process and through their community outreach. The rule freeze was therefore disappointing.³⁶

Kansas City: An Ambitious Regional Plan

Like Hidalgo, Kansas City, Missouri, submitted a regional assessment. This regional collaboration included the five cities in the metropolitan area: Kansas City, Missouri; Kansas City, Kansas; Independence, Missouri; Blue Springs, Missouri; and Leavenworth, Kansas. This coalition built upon past engagement with the Mid-America Regional Council (MARC), the area’s regional planning organization; the Regional Equity Network; and others. Notably, creating this plan entailed coordination across state lines. Yet despite such complex challenges of coordination, the partners were able to concentrate their efforts during the summer of 2016 and produce an ambitious and rigorous AFH, as measured by the number of goals with a quantifiable metric or new policy.

Kansas City’s plan builds on a more established and robust regional planning body—MARC—than existed in Hidalgo County; indeed, MARC is the principal author of the plan. MARC staff explain that because of Kansas City’s past regional collaboration, HUD urged it to again collaborate regionally in the AFH process.³⁷ Kansas City’s regional focus enables the area to take a broad look at patterns of concentrated poverty and segregation. With this broad lens, it finds variation in patterns across areas of concentrated poverty in different parts of the region, noting that patterns of high concentrations of poverty are particularly severe in Kansas City, Missouri, and in Kansas City, Kansas. The other four cities within the regional AFH lack the same levels of segregation—a finding that could only have been recognized with a regional lens. Suburban areas in the region have the jobs and educational opportunities these cities lack—but without the public transit and affordable housing necessary to connect people to those opportunities. The fractured nature of school districts in the region and school residency requirements further reinforce racial disparities in opportunity.

Much as in Seattle, staff at MARC take issue with the definitions of R/ECAPs. In this case, staff find that many areas that fall slightly below the thresholds are, in fact, quite disadvantaged.³⁸ However, the staff believe that the AFH process was a vast improvement over the previous AI regime:

Even more than its regional analysis, Kansas City’s fair housing goals are particularly noteworthy for their clarity. First, Kansas City divides its goals into multiple sections that emphasize the importance of fair housing work at the local and regional levels. In its “local goals” section, each of the five participating cities focuses on specific AFFH measures unique to the locality. Then, in the “regional goals” section, the collaborative puts forward specific measures that apply across all the program participants and that try to forge greater regional equity, such as working with local housing authorities to explore a regional approach to using vouchers, including a regional housing locator service; creating model zoning codes that all the smaller city participants could implement to increase their housing stock; developing incentive policies to create more affordable housing in higher-opportunity areas; and better connecting transit with affordable housing and employment centers.

For example, the first regional goal in Kansas City’s plan is to “expand the use of Community Development Financial Institutions and New Market Tax Credits in neighborhoods with concentrations of persons in protected classes and low income residents.” This strategy involves convening the Local Initiatives Support Corporation, AltCap, other sources of capital, MARC, and the participating localities to develop a plan of action. This type of convening across municipalities and sectors is a powerful example of how municipalities can use the AFH as a convening tool to start collaborations. By specifying the jurisdiction responsible for each goal, Kansas City’s AFH makes tracking progress and ensuring accountability much more likely.

Overall, Kansas City has twenty-three goals with quantifiable metrics or new policies—an indication of a potentially rigorous fair housing plan. Even so, staff note that a number of the communities outside Kansas City have very modest goals, even those related to initiatives they are already undertaking. Staff note this circumstance occurs because they were advised not to include goals that they could not begin to implement within five years. This highlights again the conflicting incentives facing municipalities in setting up goals, especially in a regional context. Kansas City, like Hidalgo County, has a regional plan for which some lower-capacity, less-motivated municipalities contributed less-ambitious goals. Unlike Hidalgo County, Kansas City’s carefully designed AFH, with separate regional and local goals, yields ambitious, quantifiable regional objectives even as it exposes some variation in the robustness of local goals.

Kansas City’s goals tend to be placed-based but also include mobility efforts, attempts to create mixed-income communities, goals to combat displacement, and zoning changes. Staff note that the push for place-based initiatives came from the community engagement process:

In the long run, MARC staff view the AFFH as the first step in a long-term process to educate the public and shift the opinions of wealthy households around fair housing issues—to demonstrate “that affordable housing doesn’t lead to a disaster in your community if you accept low-income people.” They also note that, separate from the AFH process, a movement around affordable housing and access to opportunity has been growing in Kansas City that could support further implementation in the future.

In terms of ways to improve the AFFH process, Kanas City staff cite funding to go along with the AFFH mandate as a key improvement that could be made. Funding would have been preferable to technical assistance, in their view. They also recommend allowing communities to use their own data instead of HUD’s where they are more helpful. This perspective varies from that of other municipalities discussed in this chapter, which welcomed HUD’s data even as they supplemented them with local data. Regarding implementation, MARC also pointed toward the importance of how the AFH is incorporated into the Consolidated Plan process. MARC staff note that they are tracking progress on regional goals but not on the local goals of each community.⁴¹ However, staff note that the localities are keeping track of local implementation because the AFFH Rule requires reporting to HUD in their Consolidated Plans.⁴²

Kansas City’s AFH shows that it is possible to develop an ambitious regional fair housing plan. It also reveals how high-capacity cities may interpret the AFH document differently but still develop equally thoughtful assessments of fair housing. Seattle’s document, as noted above, spends far more time than Kansas City’s discussing fair housing in the context of its broader racial equity work. The Kansas City regional AFH has less discussion of racial equity and social inclusion than Seattle’s but is more focused on specific measurable objectives in its fair housing goals. Both plans are carefully thought out and include ambitious, measurable objectives related to furthering fair housing, and both were accepted by HUD. The very different approaches in these AFHs exemplify the latitude that the AFFH Rule gives grantees to shape fair housing plans according to their own local needs. These and the rest of the AFHs suggest that one of the main reasons that the Trump administration cited for rolling back the AFFH Rule—that it limits local flexibility—is not accurate. On the contrary, we observe municipalities setting out goals to fulfill the AFFH Rule in ways that suit their particular municipal needs.

Looking Forward

Overall, we find that the municipalities put forward a range of creative goals to affirmatively further fair housing, including measurable objectives and innovative new policies intended to make access to place-based resources, such as high-performing schools or access to jobs, more equitable. For many municipalities, the AFFH process began by engaging in a lengthy series of community engagements that helped produce these original fair housing goals. Some municipalities initially failed to meet the AFFH Rule’s standards but then worked with HUD to improve their plans. Although this process was not perfect in all cases, overall, the municipalities’ staff members we spoke with reported positive experiences with the rule and disappointment in HUD’s action to freeze it. The oversight from HUD and the technical assistance that this agency and other nonprofit organizations provided speak to the importance of these continuing oversight and technical assistance roles. Certainly, there is room for improvement in the AFFH Rule, as likely would be the case with any new major federal requirement. Our conversations with municipalities’ staff members engaged in the AFH process speak to ways in which the rule could be improved in the future, were it to be reinstated, as do subsequent chapters in this book. Contrary to HUD’s justifications for suspending it, overall, the AFFH Rule in the first forty-nine submissions appears to be an important starting point for creating meaningful action plans that focus on positive, measurable results. Future research is needed to determine how effective these plans are at guiding municipalities to implement these policy changes.

Indeed, despite federal retrenchment, many municipalities have been proceeding voluntarily with their own AFHs. From New York City to Dallas to Denver to Boston, cities are continuing to fulfill the promise of the AFFH Rule. Future research could focus on how cities are responding to this regulatory uncertainty and the variations we see in these self-driven AFH processes. It also raises questions for academics and practitioners about how best to support these efforts and encourage more municipalities to participate.

Our research has made us hopeful for the future of efforts to affirmatively further fair housing. After a half century of virtual inaction at the local level to combat entrenched patterns of segregation and racial inequality, many of the municipalities we studied are making concerted efforts to take steps toward real change for their residents. We find that many municipalities have risen to the occasion to produce innovative goals to increase access to opportunity in their communities. We hope this chapter provides an evidence base for policy makers in the future looking to revive the 2015 AFFH Rule or perhaps adopt some form of the AFH in their own communities.

ENDNOTES

1. Justin P. Steil and Nicholas F. Kelly, “The Fairest of Them All: Analyzing Affirmatively Furthering Fair Housing Compliance,” Housing Policy Debate 29, no. 1 (2019): 85–105, available at https://doi.org/10.1080/10511482.2018.1469527.

2. Justin P. Steil and Nicholas F. Kelly, “Survival of the Fairest: Examining HUD Reviews of Assessments of Fair Housing,” Housing Policy Debate 29, no. 5 (2019): 736–751, available at https://doi.org/10.1080/10511482.2018.1524444.

3. “Residential Segregation Data for U.S. Metro Areas,” available at https://www.governing.com/gov-data/education-data/residential-racial-segregation-metro-areas.html.

4. William C. Baer, “General Plan Evaluation Criteria: An Approach to Making Better Plans,” Journal of the American Planning Association 63, no. 3 (1997): 329–344; Philip R. Berke and Steven P. French, “The Influence of State Planning Mandates on Local Plan Quality,” Journal of Planning Education and Research 13, no. 4 (1994): 237–250; Philip Berke and David Godschalk, “Searching for the Good Plan: A Meta-analysis of Plan Quality Studies,” Journal of Planning Literature 23, no. 3 (2009): 227–240; Philip R. Berke, “Enhancing Plan Quality: Evaluating the Role of State Planning Mandates for Natural Hazard Mitigation,” Journal of Environmental Planning and Management 39, no. 1 (2010): 79–96.

5. Baer, “General Plan Evaluation Criteria,” 1997; Berke and Godschalk, “Searching for the Good Plan,” 2009.

6. Focusing on new policies is not a perfect metric, in that it overlooks municipalities that are already implementing existing, effective fair housing policies (see Chapter 5). We nevertheless believe that new policies created to achieve AFFH goals are still a relevant indication of a more robust AFH, one in which the process of creating it has generated new approaches to furthering fair housing. Another reason why we might believe that new policies are indications of strong plans: given the historic lack of enforcement of fair housing, it would be reasonable to expect many jurisdictions undergoing the AFH to discover fair housing issues for which they do not yet have policy solutions.

7. Cary Coglianese and Evan Mendelson, “Meta-Regulation and Self-Regulation,” in The Oxford Handbook on Regulation, ed. Martin Cave, Robert Baldwin, and Martin Lodge (Oxford: Oxford University Press, 2010), 146–168.

8. Gabe Rubin, “Democrats Laud HUD’s Fair-Housing Rule, Republicans Try to Block Funding,” Morning Consult, July 10, 2015, available at https://morningconsult.com/2015/07/10/democrats-laud-huds-fair-housing-rule-republicans-try-to-block-funding/.

9. Michael H. Schill and Samantha Friedman, “The Fair Housing Amendments Act of 1988: The First Decade,” Cityscape: A Journal of Policy Development and Research 4, no. 3 (1999): 57–78; Robert G. Schwemm, “Overcoming Structural Barriers to Integrated Housing: A Back-to-the-Future Reflection on the Fair Housing Act’s Affirmatively Further Mandate,” Kentucky Law Journal 100 (2011): 125–176; John Yinger, “Sustaining the Fair Housing Act,” Cityscape: A Journal of Policy Development and Research 4, no. 3 (1999): 93–106.

10. Steil and Kelly, “The Fairest of Them All.”

11. Sharon Gilad, “It Runs in the Family: Meta-regulation and Its Siblings,” Regulation and Governance 4, no. 4 (2010): 485–506.

12. Chris Tausanovitch and Christopher Warshaw, American Ideology Project, 2015, available at http://www.americanideologyproject.com.

13. City of Seattle and Seattle Housing Authority.

14. These documents from Seattle’s Race and Social Justice Initiative are available at https://www.seattle.gov/rsji; see also, 2017 City of Seattle and Seattle Housing Authority Joint Assessment of Fair Housing, available at: https://www.seattle.gov/housing/data-and-reports.

15. Debra Rhinehart, strategic adviser, Department of Human Services, interview, November 15, 2019.

16. Ibid.

17. City of Seattle and Seattle Housing Authority.

18. “Creating Moves to Opportunity | The Abdul Latif Jameel Poverty Action Lab,” available at https://www.povertyactionlab.org/na/cmto.

19. City of Seattle and Seattle Housing Authority.

20. Rhinehart interview.

21. City of Seattle and Seattle Housing Authority.

22. Rhinehart interview.

23. Ibid.

24. Ibid.

25. Lynn Lehner, Temecula, interview, November 5, 2019.

26. Ibid.

27. Ibid.

28. U.S. Department of Housing and Urban Development, “Response to Temecula, CA Regarding Revision of AFH,” November 30, 2016.

29. City of Temecula, “City of Temecula: Final Assessment of Fair Housing,” report (City of Temecula, September 2016).

30. Ibid.

31. Lehner interview.

32. Steven de la Garza, Hidalgo County Urban County Program, interview, November 26, 2019.

33. Hidalgo County, “Hidalgo County, Texas Regional Assessment of Fair Housing,” 2017.

34. Garza interview.

35. Ibid.

36. Ibid.

37. Marlene Nagel and Frank Lenk, Mid-America Regional Council, interview, November 25, 2019.

38. Ibid.

39. Ibid.

40. Ibid.

41. Ibid.

42. Ibid.