Scituate: Ground zero for the full implementation of RhodeMapRI throughout Rhode Island – multiple buildings with 113 units of low-income housing
Scituate, RI: Huge corporate developers imposing their will on a small town's character.
The Facts:
1. Clearly, huge out-of-state corporate construction companies are looking to supersede the town of Scituate’s local zoning laws through the coercive power of Rhode Island's court system to build a multi-building, 193 unit complex, with 113 units slated to be low-income housing.
2. RhodeMapRI states unequivocally that, "Another important aspect of local regulation that needs to be addressed in Rhode Island deals directly with what can and cannot be built. This issue is certainly not unique to Rhode Island municipalities, but there are far too many local ordinances that do not meet the needs of residents and business owners. Higher density housing, particularly in suburban and rural areas, should be allowed at different scales in every Rhode Island community." (pg. 148) (Emphasis added)
3. The Hope Mill housing project is ground zero for the full implementation of RhodeMapRI/RI Rising and the first, necessary step to take local zoning power from the citizens and place it in the hands of the courts and politicians. Due to the obvious absurdity of the project when contrasted with the self-evident desires of the people who live in the town, it is evident that the final implementation of this project will set the precedent for every other town in Rhode Island.
4. PRARI [Property Rights Alliance of Rhode Island], the statewide collation to keep local zoning a local citizen-based decision believes strongly that the state planners’ strategy is to first force high density housing throughout every census tract of Rhode Island and then follow through with the manipulation of local property tax policies into a mandated statewide property tax regimen that forces local taxpayers to subsidize affordable housing via their own local property taxes.
IMPORTANT NOTE: The term “neighborhood” will be used by state planners. It is important to note that this is the state planners’ term for census tract; cite from RhodeMapRI’s “Equity Profile of Rhode Island” pg. 86: The term “neighborhood” is used at various points throughout the equity profile. While in the introductory portion of the profile this term is meant to be interpreted in the colloquial sense, in relation to any data analysis it refers to census tracts.) (Emphasis added)
According to RhodeMapRI, pg. 168 of the final document with edits, “The State should consider the creation of a permanent commission on property taxation to establish a system of universal, understandable and fair standards for the municipal taxation of property throughout the state."
Presently, all affordable housing units built in Rhode Island do not pay property taxes based upon the needs of the town budget for schools, police, fire, etc.. The Hope Mill developers will, without question, cause taxes in Scituate to spike because local taxpayers are now forced to subsidize these out-of-town developers. According to PRARI, it has been proposed that this so-called “fair” standard of property taxation will include not just rehabbed rental properties, but also, new construction of rental properties:
A big-corporate construction company windfall and the true, final goal of the planners.
This scheme will make Rhode Island property taxation weighted so that single family homeowners will be subsidizing nearly 70% of the developers' property tax costs. And the developers can later flip these properties without paying back local taxpayers for years of subsidization. This in fact happened in East Providence with the Kent Farms affordable housing development where, after years of local subsidizing, the developer flipped the entire 250 unit property to a wealth management company for a huge profit.
The planners understand that they first must place local zoning decisions in the hands of the courts and politicians through legal precedent (happening now at Hope Mill), next use this to force high density housing everywhere possible, and then finally implement a property tax system that places nearly all the financial burden on single family homes.
5. According to Rhode Island’s land use policy, Land Use 2025 page 85, “If we are successful, this Plan’s recommendations are followed, 63 percent or more of the State’s landscape would remain as open, undeveloped land in 2025. One of our greatest challenges will be to permanently preserve as much greenspace as possible in both the rural areas and within the built environment.” (Emphasis added)
6. According to RhodeMapRI, pg. 116; "The economic pressures on landowners, combined with the limited opportunities of traditional zoning, contribute to a haphazard, sprawling pattern of development. Interestingly, when reading many local Comprehensive Plans, this pattern of development is at odds with a town’s goals to protect rural character and quality of life while encouraging appropriate economic development. It also works against elements of the State Guide Plan, including Land Use 2025, and the desire for more concentrated growth center development." (Emphasis added)
7. Therefore, it is the view of PRARI that in order to achieved Rhode Island planners’ stated goal in Land Use 2025 of nearly two-thirds of the state being “undeveloped land,” and the stated strategy of the planners to end the “a haphazard, sprawling pattern of development” of single family homes, the events in our state are unfolding as follows:
First: Take the power of local zoning away from one town in order to set legal precedent throughout the state, which is what is happening right now in Scituate.
Second: Once the State Guide Plan (RhodeMapRI/RI Rising) is successfully implemented through the courts and local zoning rights are removed, expand the statewide property tax formula to encourage affordable housing construction as much as possible; empowering powerful out of state construction companies to impose their will on Rhode Island towns.
Third: Finally achieve the land use and housing goals of RhodeMapRI/RI Rising: Make single family home ownership unaffordable to the middle class through taxation, destroy any and all equity single family homeowners have worked their lives to build, and finally forcing those families into high density housing.
Scituate is ground zero for the next critical step in the implementation of RhodeMapRI/RI Rising. If we lose this fight, the legal precedent will be set that towns are not the keepers of their zoning laws, but the politicians and courts. Once this precedent is set, outside interests will have full reign to shape our small towns in any way they deem most profitable.
The ONLY way to solve this problem is to remove from office those politicians allowing this to happen. DONATE TODAY TO PRARI and The Gaspee Project:
PRARI, the Property Rights Alliance of Rhode Island, is not in any way a legal entity and we are not lawyers. This document is in no way legal advice. This is simply our perception of the events surrounding the Hope Mill Project in Scituate and how that squares with the goals of the state’s “economic development plan” RhodeMapRI.
Tell President Trump to End HUD's AFFH Destruction of Private Property Rights

PRARI has not given up the fight against the federal law that removes local zoning authority. The liberals and the state planning department in RI continue to move RhodeMapRI forward by providing tax credits to their cronies and forcing you to pay for your neighbor’s property taxes.
However, there is some hope with U.S. Senator Mike Lee. Lee is going to work with a Republican majority in the House and Senate, a Republican Executive branch, and with any luck, Dr. Ben Carson as HUD secretary, to attack the outrageous power HUD has given to local elected officials and administrators who accept federal money - the power to ignore your local zoning laws and the power to force you to subsidize others in your neighborhood.
Included here is a link to sign a petition supporting his efforts to stop the social engineering of our neighborhoods by halting both the implementation and funding of the Affirmatively Furthering Fair Housing (AFFH) rule. Please pass it along to your family and friends to sign!
In the past we explained how AFFH would impact our RI neighborhoods, how it would come to fruition in RI through RhodeMapRI. Speaker Mattiello told you RhodeMapRI would be ‘shelved’. Take a look at the projects and giveaways below. Speaker Mattiello knows full well that RhodeMapRI and its destructive forces were not shelved.
NeighborWorks Blackstone River Valley RI: Mixed-Use Developments
Heritage Place, Woonsocket
Clocktower Apartments, Burrillville
ArTech Hub, Woonsocket
Greenridge, Burrillville
3 projects seeking Rebuild R.I. tax credits
Prospect Heights, 560 Prospect St., Pawtucket
Union Trust Company Building, 170 Westminster St., Providence
78 Fountain St., Providence
Rhode Island Housing Awards LIHTCs to 3 Projects
"Rhode Island Housing has awarded more than $2.5 million in low-income housing tax credits (LIHTCs) to three developments as part of its 2015 round: Greenridge Apartments development by NeighborWorks Blackstone River Valley in Burrillville, the Revitalize SouthSide development by SWAP, Inc., in Providence, and Amherst Gardens by Olneyville Housing Corp. in Olneyville."
Raimondo Announces New Construction Projects
"Governor Gina M. Raimondo and the Rhode Island Commerce Corporation Board of Directors last evening approved incentive agreements for over $9 million in tax credits and grant funding [YOUR MONEY] to spur new construction and support research and development."
Why would a developer want to build mixed-use, high density affordable housing? If it is affordable, how can they profit??
ANSWER:
MILLIONS OF DOLLARS IN TAX CREDITS that can be used to offset ANY tax bill.
Millions of YOUR TAX DOLLARS given to developers to subsidized housing you have NO RIGHT to question.
And not only will developers profit from this scheme, they will be able to determine where they might profit the most, without concern for local zoning.
Page 123 of the RhodeMap "Economic Development Plan"
"Adopt mixed-use development zoning which incorporates village-like amenities, services, and housing options for a mixed-age, mixed-income residential population, and includes by-right multi-family or other denser housing models for rural and suburban centers."
The phrase "by-right development" not only implies statewide "on-demand" approvals in favor of developers, but such developments may soon contain forced local property tax breaks subsidized by local residents, not the State of RI. Such property tax breaks paid for by local residents was already attempted in 2015 under House Bill H6107A, and is expected to be pushed again in the future.
In other words, without ANY say from you and your neighbors, Gina Raimondo and the rest of the Establishment in Rhode Island want construction development companies to build and expand mixed-use, high density housing anywhere they want without your approval.
Do you think you'll have a choice?
From RI Planning, April 28 2015:
"The decision to make a local inclusionary housing ordinance mandatory or voluntary is an important one. Based on discussions with planners and developers, it seems clear that voluntary programs are FAR LESS LIKELY TO BE USED. Therefore, the policy recommendation is for mandatory provisions that are triggered by a certain threshold."
October Radio Ads
We are in the home stretch of our last opportunity to finally change Rhode Island for the better. Below are videos of radio ads that will be broadcast throughout the airways in Rhode Island over the next month. These ads strike at the heart of why Rhode Island has been for decades and continues to be the worst state for businesses to grow and prosper.
The Rhode Island government seems to be immersed in:
- Corruption
- Waste
- Apathy to the will of the people
- Tolling vehicles
- The destruction of property rights
- Higher and higher taxes
- Destroying people's means of retiring comfortably
- . . . and so much more
The Gaspee Project and our partners are making the most of every penny given to us to help save our state for our children and grandchildren.
Please listen to these ads and share them with your friends and family all throughout social media and email:
Also, share this information as a webpage on social media and to your email contacts.
Alert: Farm owners under attack this Wednesday – Politicians work to advance the RhodeMapRI Agenda
This Wednesday at 5:30PM the RI DEM is conducting a “Farmland Acquisition Rules and Regulations” workshop intended to take a huge step toward bringing under state control the small business farms in Rhode Island and to divert this money to future efforts to advance the RhodeMapRI/Land Use 2025 agenda. Instead of helping small family farms advance their efforts to grow and prosper, the state wants to destroy their right to live and operate as they have for generations.
The stated goal of Rhode Island’s Land Use 2025 plan is that “63 percent or more of the State’s landscape would remain as open, undeveloped land in 2025,” and this new initiative is the first big step forward. Farms are being targeted because those that are left have been regulated into stagnation and represent one of the largest single percentages of the land throughout the state.
This assault on our family farms is insidiously scheduled for a public hearing on the same day the Washington County Fair is to open. It is evident that this was intentionally done so that those who have prepared for the event all year have to choose between standing up for their rights or participating in the start of their most important event of the year.
Consider the audacity the state of Rhode Island enlists its power in regard to this property grab. As stated in the document announcing the meeting and their intent to acquire family farms:
“The terms and provisions of these rules and regulations shall be liberally construed to permit the Department to effectuate the purposes of state law, goals and policies.”
In other words, as long as the rules are not specified, the unelected bureaucrats in the RI DEM will grant themselves the power to interpret these new rules and regulations in any way they see fit.
PRARI members are strongly advised to attend this meeting and show their support for the family farms that will be at the meeting and standing up for their rights. This is the start of the slippery slope intended to destroy the property rights of every Rhode Islander.
Please share this information everywhere and join us on Wednesday. Details:
235 Promenade Street
Room 300
Providence, Rhode Island 02908
Cordially,
The volunteers of PRARI
Gaspee Project Information Center for Rhode Island
Portsmouth RI Town Council Moves To Seize Resident Voting Rights On ALL Tax Stabilization Initiatives
Posted by John Niewiecki · January 27, 2016 1:42 PM
Gaspee Project Information Center for Rhode Island
Posted by John Niewiecki · January 27, 2016 1:07 PM
How HUD is deceiving Rhode Islanders Regarding New AFFH Mandate "Clarifications"
This US Department of Housing and Urban Development Letter proves HUD is intentionally attempting to decisive Rhode Island Citizens
How??
Read this letter from HUD to the Foster RI Town Planner who made inquiries about the new AFFH "clarification" and then read this analysis and proof the agency is telling half-truths about what will happen if the Property Rights Alliance of Rhode Island fails and HUD achieves its goals:
The major flaws of the attached HUD letter to Foster are as follows:
1) The letter leaves out the most critical piece being that there is not only a requirement to have an "Analysis of Impediments (AI)" document completed, but there is also a required second document being the local plan created on how to overcome the identified impediments contained in the AI. Failure to have a comprehensive working plan to address the impediments was the primary basis for the Westchester lawsuit. This second requirement is spelled out in HUD's Fair Housing Planning Guide (see e.g. page 1-2), and Federal Reg 24 CFR 570.487(b)). See, respectively:
http://www.hud.gov/offices/fheo/images/fhpg.pdf
https://www.law.cornell.edu/cfr/text/24/570.487
The letter leaves out this critical requirement of any "grantee" who accepts CDBG funds.
2) The letter makes a big deal about HUD not forcing changes on a community. HUD is not the problem. The central issue is whether an advocacy group, or a developer, can bring a lawsuit in federal court based on AFFH compliance (i.e. those who take CDBG). Westchester County originally tried to claim in court that advocacy groups did not have standing to bring a claim into federal court. But Judge Denise Cote held that they did have standing (see attached OPINION and ORDER).
The letter fails to make this point, instead making it appear that there are zero risks to a local community when taking CDBG (try telling that to Westchester residents who are getting their local zoning deconstructed because of HUD).
HUD's Final Rule on Affirmatively Furthering Fair Housing (AFFH) and reaffirms housing mandate on the census tract level
Download and see for yourself what the Property Rights Alliance of Rhode Island has known for over a year: HUD demands affordable housing in every census tract in Rhode Island.
Why does this information about HUD's AFFH new rule interpretation regarding affordable housing matter to you?
Newport, RI meets Rhode Island state standards for affordable housing (i.e. meets the overall 10% goal), BUT Newport does not meet the federal AFFH mandates (e.g. Senator Whitehouse's exclusive Newport neighborhood being census tract 409, is not AFFH compliant).
See here:
Read the Data documentation here, straight from HUD's website; the AFFH housing enforcement based upon people's identity and NOT local zoning laws.
The document reads as follows:
Affirmatively Furthering Fair Housing (AFFH)
Data Documentation
July 7, 2015
U.S. Department of Housing and Urban Development*
Table of ContentsI. Overview...................................................................................................... 2
II. Data Sources ............................................................................................... 2
III. Geographic Notes ........................................................................................ 5
IV. Race/Ethnicity ................................................................................................ 5
V. National Origin and Limited English Proficiency (LEP) .................................... 6
VI. Disability Type ................................................................................................ 6
VII. Sex and Age ................................................................................................... 7
VIII. Families with Children....................................................................................... 7
IX. Housing Types.................................................................................................. 7
X. R/ECAP............................................................................................................. 7
XI. Housing Problems and Disproportionate Housing Need.................................... 8
XII. Indices ...............................................................................................................9
List of Tables
Table 1: Data Sources Table ........................................................................................... 3
I. Overview
HUD has asked its program participants to evaluate fair housing issues in their jurisdictions and regions. The agency is taking a more active role in assisting program participants to prepare the required analysis by providing data and analytical tools to help grantees quantify and interpret particular fair housing issues. HUD provides a dynamic online mapping and data-generating tool (Data Tool) for communities to use in their completion of the Fair Housing Assessment Tool (AFH Tool). HUD accompanies these tools with guidance tailored to accommodate program participants of all capacity levels.
This document outlines the data, methods, and sources behind the tool that HUD provides. It describes demographic, socioeconomic, and housing characteristics, as well as access to community assets through a series of opportunity indices.
This data package is not exhaustive and should not supplant local data or local knowledge that is more robust, timely, or accurate. It represents a baseline effort to assemble consistent, nationally available data from a variety of sources compiled into one location.
II. Data Sources
Table 1 lists data sources, years, and the spatial scale used to populate the tables and maps in the Data Tool.
Table 1: Data Sources
Data Category |
Variables |
Geographic level or Primary Sampling Unit |
Tables |
Maps |
Sources and years |
Demographics |
Race/Ethnicity population in 2010 |
Block-group |
1, 2, 6 |
1, 5-7, 9-14 |
Decennial Census, 2010 |
Demographics |
Race/Ethnicity population in 2000 & 1990 |
Tract |
2 |
2 |
Brown Longitudinal Tract Database (LTDB) based on decennial census data, 2000 & 1990 |
Demographics |
Percent of race/ethnicity census tract |
Tract |
10 |
na |
Decennial Census, 2010 |
Demographics |
Limited English Proficiency (LEP) population; LEP languages; Foreign-born population; Foreign-born population place of birth (national origin) |
Tract |
1, 2, 5, 6 |
3, 4, 8, 9-14 |
American Community Survey (ACS), 2006-2010; Brown Longitudinal Tract Database (LTDB) based on decennial census data, 2000 & 1990 |
Demographics |
Disability Type population; Disabled population by Age |
Tract |
1, 15, 16 |
15, 16 |
American Community Survey (ACS), 2008-2012 |
Demographics |
Population by Age, Sex, Family Type |
Tract |
1, 2, 6 |
9-14 |
Decennial Census, 2010; Brown Longitudinal Tract Database (LTDB) based on decennial census data, 2000 & 1990 |
Socioeconomic |
Racially/Ethnically-Concentrated Areas of Poverty (R/ECAP) |
Tract |
6, 9 |
1-16 |
Decennial census (2010); American Community Survey (ACS), 2006-2010; Brown Longitudinal Tract Database (LTDB) based on decennial census data, 2000 & 1990 |
Housing |
Population, housing units, occupied housing units, race/ethnicity, age, disability status, household type, and household size by Housing Type |
Development; |
7-9, 13, 17 |
na |
Inventory Management System (IMS)/ PIH Information Center (PIC), 2013; Tenant Rental Assistance Certification System (TRACS), 2013 |
Housing |
Low-Income Housing Tax Credit developments |
Development |
10 |
na |
National Low-Income Housing Tax Credit (LIHTC) Database, 2013 |
Housing |
Households with Housing Problems; Households with Severe Housing Problems; Households with Income Less than 31% of Area Median Income (AMI); Households with Housing Problems by Race, Household Type, Household Size |
Tract |
11, 12 |
7, 8 |
Comprehensive Housing Affordability Strategy (CHAS), 2007-2011 |
Demographics |
Dissimilarity Index |
Community Development Block Grant (CDBG); Core Based Statistical Area (CBSA) |
3, 4 |
na |
Decennial Census, 2010; Brown Longitudinal Tract Database (LTDB) based on decennial census data, 2000 & 1990 |
Opportunity |
Low Poverty Index, Labor Market Index |
Tract |
14 |
11, 13 |
American Community Survey (ACS), 2006-2010 |
Opportunity |
School Proficiency Index |
Block-group |
14 |
9 |
Great Schools, 2012; Common Core of Data (4th grade enrollment and school addresses), 2012; School Attendance Boundary Information System (SABINS), 2012 |
Opportunity |
Low Transportation Cost Index; Transit Trips Index |
Tract |
14 |
12 |
Location Affordability Index (LAI) data, 2008-2012 |
Opportunity |
Jobs Proximity Index |
Block-group |
14 |
10 |
Longitudinal Employer-Household Dynamics (LEHD), 2010 |
Opportunity |
Environmental Health Index |
Tract |
14 |
14 |
National Air Toxics Assessment (NATA) data, 2005 |
III. Levels of Geography and Weights
The Data Tool includes data for all U.S. states, the District of Columbia, and Puerto Rico. Users may access data through the Data Tool at various spatial scales, including geo-boundaries of Census tracts, the Community Development Block Grant (CDBG) and the Core-based Statistical Area (CBSA). As shown in Table 1, most data in the Data Tool are at the Census tract or block-group levels. The selection of a spatial scale to use as the initial basis for each data element is primarily based on the lowest level in which HUD has faith in its accuracy. For example, data elements constructed from the American Community Survey (ACS) data are based on Census tract estimates rather than block-group estimates due to concerns about sampling errors.
Data displayed in the Data Tool map views are at the Census tract level. Data displayed in the report tables are aggregated from smaller geographic units (i.e. either the Census tract or block-group level) to the CDBG[1] and CBSA levels. As shown in Table 1, the AFFH data are from multiple sources in various years. In order to compile them into one mapping tool database, data issued or released at different years need to be adjusted to the same year. The Census tract and block-group boundaries in the Data Tool are based on those released by Census in 2010. The Data Tool incorporates minor changes indicated in the ACS “Geography Release Notes” for 2011 and 2012 on the Census Bureau website,[2] resulting in boundaries and corresponding data adjusted to calendar year 2012. The CDBG boundaries are based on political jurisdiction boundaries for calendar year 2011. The CBSA boundaries are based on OMB 2013 definitions.
The CDBG level reflects the geographic boundaries for grantees that receive direct allocations of CDBG funds from HUD. CDBG jurisdictions are not census-designated areas, which means that CDBG jurisdictional boundaries do not fall consistently along Census tracts or block-groups. A series of technical procedures were necessary to construct a crosswalk between census-designated areas and CDBG jurisdictions. Census geographic identifiers at the summary level 070 (state-county-county subdivision-place/remainder) and summary level 080 (state-county-county subdivision-place/remainder-census tract) were matched to HUD CDGB jurisdiction geographic identifiers.
Weights
At the boundaries of CDBG jurisdictions, some Census tracts fell partially within the jurisdiction and partially outside of the jurisdiction. Data from these tracts were weighted by the share of the population within the CDBG boundary to approximate including only the portion of those tracts within the CDBG jurisdiction in aggregate figures reported at the CDBG level. In contrast, block groups were simply assigned to the CDBG jurisdiction that contained its centroid (i.e., central point).
IV. Race/Ethnicity
Among other protected characteristics, the Fair Housing Act prohibits housing discrimination based on race. HUD offers data on both race and ethnicity. Because the Fair Housing Assessment focuses on discrimination, HUD provides data for non-Hispanic whites, considering Hispanics of any race as a separate race/ethnic category that can experience housing discrimination differently than other groups. Similarly, the data provided for the other race groups – Black, Asian and Pacific Islander, Native American, and other – also exclude information for people who identify their ethnicity as Hispanic. Other race/ethnicity data are discussed in sections IX and XI.
Data Source: American Community Survey (ACS) 2006-2010; Decennial Census, 2010; Brown Longitudinal Tract Database (LTDB) based on decennial census data, 2000 & 1990
Related Tables/Maps: Table 1, 2, 5, 6; Map 1, 2, 5-7, 9-14
V. National Origin and Limited English Proficiency (LEP)
The Fair Housing Act prohibits housing discrimination based on national origin. The Data Tool provides data for four indicators of national origin. The first two are the ten most common places of birth of the foreign-born population by jurisdiction and region and the number and percentage of the population that is foreign-born. The second two indicators are the most common ten languages spoken at home (for the population age 5 years and over) for those who speak English “less than ‘very well,’” and the number and percentage of the population who speak English “less than very well.”
Data on national origin and LEP originate from the 2006-2010 American Community Survey and Brown Longitudinal Tract Database (LTDB) based on decennial census data, 2000 and 1990. Counts of each place of birth by tract were aggregated to the jurisdiction and regional level separately. Within these geographies, the counts for places of birth were ranked and the ten most populous groups were determined and are presented.
The full most common ten places of birth and LEP languages are displayed in the Tables, while the most common five are displayed in the Maps. HUD limits the number of categories for the maps to enable users to better visualize the most populous groups. National origin and LEP data were missing for Puerto Rico.
Data Source: American Community Survey (ACS) 2006-2010; Brown Longitudinal Tract Database (LTDB) based on decennial census data, 2000 & 1990.
Related Tables/Maps: Table 1, 2, 5, 6; Map 3, 4, 8, 9-14
VI. Disability Status and Type
The Fair Housing Act prohibits housing discrimination against any person based on disability. The Data Tool provides information on disability type, disability status by age group, and disability status by housing type. The disability type and disability status by age group measures are from the ACS, while the measure of persons with disabilities by housing type is from the PIC/TRACS data (see section IX). The definition of “disability” used by the Census Bureau may not be comparable to reporting requirements under certain HUD programs, which sometimes use different definitions of disability for purposes of determining eligibility.
The disability type categories are: hearing difficulty, vision difficulty, cognitive difficulty, ambulatory difficulty, self-care difficulty, and independent living difficulty. These categories are based on a new set of disability questions introduced into the ACS in 2008 and are not comparable to disability type figures in prior years.
Data Source: American Community Survey (ACS), 2008-2012; Inventory Management System (IMS)/ PIH Information Center (PIC), 2013; Tenant Rental Assistance Certification System (TRACS), 2013
Related Tables/Maps: Table 1, 15, 16; Map 15, 16
VII. Sex
The Fair Housing Act prohibits housing discrimination against any person based on sex. The Data Tool provides information on male/female status.
Data Source: Decennial Census, 2010; Brown Longitudinal Tract Database (LTDB) based on decennial census data, 2000 & 1990
Related Tables/Maps: Table 1, 2
VIII. Families with Children and Age
The Fair Housing Act prohibits housing discrimination against any person based on familial status. For purposes of the Fair Housing Act, familial status includes one or more individuals under the age of 18 being domiciled with a parent or other person with legal custody of such individuals. The Data Tool provides information on families with children. Specifically, familial status is measured as the number and percentage of all families (with two or more related people in the household) that are families with children under age 18. The Data Tool also provides data on age group (under 18, 18-64, and 65+).
Data Source: Decennial Census, 2010; Brown Longitudinal Tract Database (LTDB) based on decennial census data, 2000 & 1990
Related Tables/Maps: Table 1, 2, 6; Map 9-14
IX. Households in Assisted Housing
The Data Tool provides data on households within the following housing categories: Public Housing, Section 8 Project-based Rental Assistance (PBRA), other assisted housing multifamily properties, Section 8 Housing Choice Voucher (HCV) Program, and Low-Income Housing Tax Credit (LIHTC). The “other assisted housing multifamily” properties include properties funded through the Supportive Housing for the Elderly (Section 202), Supportive Housing for Persons with Disabilities (Section 811), Rental Housing Assistance (Section 236), Rent Supplement (Rent Supp.), Rental Assistance Payment (RAP), and Below Market Interest Rates (BMIR) programs.
The sources for data on households in these housing types are:
- HCV: census tract-level data extract from the Family Report Form HUD-50058 (PIC)
- Public Housing: development-level data extract from the Family Report Form HUD-50058 (PIC)
- PBRA and other multifamily properties: development-level data extract from HUD-50059 (TRACS)
- LIHTC: National Low-Income Housing Tax Credit (LIHTC) Database
The Tool reports data by housing category differently depending on the report table. These details are outlined below:
Tables 7, 8, 13, and 17 present data on households in Public Housing, PBRA, other assisted housing multifamily properties, and HCV. Data on developments with fewer than 11 households reported or with fewer than 50 percent of occupied units reported at the CDBG and CBSA aggregations were omitted to ensure confidentiality.
Table 7 presents the total number of units in housing assistance programs and their share of the total number of housing units within CDBG jurisdictions. The denominator used in Table 7 is the total number of housing units in the 2010 census block-group aggregated at the CDBG level.
Table 8 presents data on the race and ethnicity of households in housing assistance programs. The race/ethnicity categories are non-Hispanic white, non-Hispanic black, Hispanic, and non-Hispanic Asian or Pacific Islander. Information on the race and ethnicity of households with incomes at or below 30 percent of the area median income (AMI) is from the Comprehensive Housing Affordability Strategy (CHAS) database.
Table 9 reports the following data on households in housing assistance programs within the CDBG jurisdiction: race/ethnicity (percent white, black, Hispanic, and Asian or Pacific Islander), percent of households with at least one member with a disability, and percent of households where the head or spouse is age 62 or older. The data in this table are presented separately for properties/households located within and outside of racially/ethnically-concentrated areas of poverty (detailed below in section X) within the CDBG jurisdiction.
Table 10 presents data on the composition of households assisted through Public Housing, PBRA, and other assisted housing multifamily properties. Population characteristics – race/ethnicity (white, black, Hispanic, Asian), households with children, and poverty rate – of the census tracts that contain assisted housing are also presented. Although information on households in LIHTC properties is not displayed in Table 10, the data on geographic coordinates for properties were used to identify the list of census tracts presented. Data on properties with fewer than 11 households reported or with fewer than 50 percent of occupied units reported at the development and at the Census tract aggregation were omitted to ensure confidentiality.
Tables 9 and 10 include only developments with spatial information that is precise enough to accurately determine their location within a Census tract, such as a rooftop location or the ZIP+4 centroid associated with the address. Developments with less precise spatial information are omitted because they cannot reliably be located to the correct street block or the correct side of the street block.
In conjunction with Tables 9 and 10, Maps 5 and 6 also include only developments with spatial information that is precise enough to be accurately mapped. Over 96 percent of Public Housing, PBRA, and other assisted housing multifamily properties and 84 percent of LIHTC properties have sufficient geographic information to be included in the tables and maps.
Tables 13 and 17 present data on unit size (households in 0-1 bedroom units, 2 bedroom units, and 3 or more bedroom units), households with children, and households where at least one member has a disability.
Data Source: Inventory Management System (IMS)/PIH Information Center (PIC), 2013; Tenant Rental Assistance Certification System (TRACS), 2013; National Low-Income Housing Tax Credit (LIHTC) Database, 2013; Decennial Census, 2010; Comprehensive Housing Affordability Strategy (CHAS), 2007-2011
Related Tables/Maps: Table 7-10, 13, 17; Map 5, 6
X. R/ECAP
To assist communities in identifying racially/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, Wilson (1980) defines neighborhoods of “extreme poverty” 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. This translates into the following equation:
Where i represents census tracts, () is the metropolitan/micropolitan (CBSA) mean tract poverty rate, PovRate is the ith tract poverty rate, () is the non-Hispanic white population in tract i, and Pop is the population in tract i.
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.
Data Source: Decennial census (2010); American Community Survey (ACS), 2006-2010; Brown Longitudinal Tract Database (LTDB) based on decennial census data, 2000 & 1990
Related Tables/Maps: Table 6, 9; Map 1-16
References:
Wilson, William J. (1980). The Declining Significance of Race: Blacks and Changing American Institutions. Chicago: University of Chicago Press.
XI. Housing Problems and Disproportionate Housing Need
To assist communities in describing disproportionate housing need in their jurisdiction and region, the Data Tool provides data identifying instances where housing problems or severe housing problems exist. The Tool presents housing problems overall, as well as variations by race/ethnicity, household type and household size. The race/ethnicity categories presented are non-Hispanic white, non-Hispanic black, Hispanic, non-Hispanic Asian or Pacific Islander, non-Hispanic Native American, and non-Hispanic other. The household type and size categories presented are family households of less than five people, family households of five or more people, and non-family households of any size.
Information on housing problems is drawn from CHAS, which demonstrates the extent of housing problems and housing needs, particularly for low-income households. The CHAS data are produced via custom tabulations of ACS data by the U.S. Census Bureau.
The Data Tool provides data on the number and share of households with one of the following four housing problems:
- Lacks complete kitchen facilities
- Lacks complete plumbing facilities
- More than one person per room
- Cost Burden - monthly housing costs (including utilities) exceed 30% of monthly income
Additionally, the Data Tool provides data on the number and share of households with one or more of the following “severe” housing problems, defined as:
- Lacks complete kitchen facilities
- Lacks complete plumbing facilities
- More than one person per room
- Severe Cost Burden - monthly housing costs (including utilities) exceed 50% of monthly income
Grantees should review these data to determine where disproportionate housing need may be found. For example, a sub-group, such as households of a particular racial/ethnic group or household size, may experience housing problems more frequently than the overall population as a whole or than another sub-group.
Data Source: Comprehensive Housing Affordability Strategy (CHAS), 2007-2011
Related Tables/Maps: Table 11, 12; Map 7, 8
XII. Indices
HUD has developed a series of indices to help inform communities about segregation in their jurisdiction and region, as well as about disparities in access to opportunity. A description of the methodology for each of the following indices may be found below:
- Dissimilarity Index
- Low Poverty Index
- School Proficiency Index
- Jobs Proximity Index
- Labor Market Index
- Low Transportation Cost Index
- Transit Trips Index
- Jobs Proximity Index
- Environmental Health Index
Tables 3 and 4 of the AFFH data tables provide values for the dissimilarity index. Table 14 of the AFFH data tables provides values for all the remaining indices.
To generate Table 14, index values were calculated for each census tract. These tract values were averaged and then weighted based on the distribution of people of different races and ethnicities within the CDBG jurisdiction or CBSA to generate composite index values for each race and ethnicity. A similar process was applied to weight the data based on the distribution of people of different races and ethnicities who are living in poverty within the CDBG jurisdiction and CBSA. The population estimates are based on the 2010 Decennial Census at the census tract or block-group level, depending on the geographic level at which the index was originally calculated.
The indices from Table 14 are also used to populate maps generated by the Data Tool, showing the overall index values of census tracts juxtaposed against data on race/ethnicity, national origin, and family type.
The following details each of the eight indices used in the Data Tool.
- A. Analyzing Segregation
- 1. Dissimilarity Index
Summary
The dissimilarity index (or the index of dissimilarity) is a commonly used measure of community-level segregation. The dissimilarity index represents the extent to which the distribution of any two groups (frequently racial or ethnic groups) differs across census tracts or block-groups. It is calculated as:
Where i indexes census block-groups or tracts, j is the jth jurisdiction, W is group one and B is group two, and N is the number of block-groups or tracts i in jurisdiction j.
Interpretation
The values of the dissimilarity index range from 0 to 100, with a value of zero representing perfect integration between the racial groups in question, and a value of 100 representing perfect segregation between the racial groups. The following is one way to understand these values:
Measure |
Values |
Description |
Dissimilarity Index |
<40 |
Low Segregation |
[range 0-100] |
40-54 |
Moderate Segregation |
|
>55 |
High Segregation |
Data Source: Decennial Census, 2010, 2000, 1990. Block-group level data were used for 2010, and census tracts were used for 2000 and 1990.
Related Tables/Maps: Table 3, 4
References:
Massey, Douglas S. and Nancy A. Denton. 1988. The Dimensions of Residential Segregation. Social Forces, 67(2): 281-315.
- B. Analyzing Indicators of Access to Opportunity
HUD has developed a two-stage process for analyzing disparities in access to opportunity and has selected five opportunity indicators upon which to focus: poverty, education, employment, transportation, and health. These indicators were selected because existing research suggests they have a bearing on a range of outcomes.
The first stage involves quantifying the degree to which a neighborhood offers features commonly viewed as important opportunity indicators such as education, employment, and transportation.. In the second stage, HUD compares these opportunity indicators across individuals in particular racial and economic subgroups to characterize disparities in access to opportunities. To focus the analysis, HUD developed methods to quantify a selected number of the important “opportunities” in every neighborhood. Invariably, these opportunity indicators do not capture all that is encompassed in an individual’s or a family’s access to opportunity.
While these important dimensions are identified by research as important to quality of life, the measures are not without limitations. HUD constrained the scope of HUD-provided items to those that are closely linked to neighborhood geographies and could be measured consistently at small area levels across the country. For example, HUD's measure of school performance only reflects elementary school proficiency. It does not capture academic achievement for higher grades of schooling, which are important to a community's well-being, but may not be as geographically tied to individual neighborhoods as elementary schools. Similarly, the health hazard measure only captures outdoor toxins, missing indoor exposures. The national-availability restriction is a necessity given that all HUD program participants must complete an Assessment of Fair Housing. HUD realizes that there are other opportunity indicators that are relevant, such as housing unit lead and radon levels. However, these lack consistent neighborhood-level data across all program participant geographies. As a consequence, HUD encourages program participants to supplement the data it provides with local data and local knowledge on these other opportunity indicators so that the analysis is as thorough as possible. The five opportunity indicators are operationalized by seven indices, described below.
- 2. Low Poverty Index
Summary
The low poverty index captures the intensity of poverty in a given neighborhood. The index uses both family poverty rates and public assistance receipt, in the form of cash-welfare, such as Temporary Assistance for Needy Families (TANF). The index is a linear combination of two vectors: the family poverty rate (pv) and the percentage of households receiving public assistance (pa).
Where means (, ) and standard errors () are estimated over the national distribution.
The poverty rate and public assistance for neighborhoods are determined at the census tract level.
Interpretation
Values are inverted and percentile ranked nationally. The resulting values range from 0 to 100. The higher the score, the less exposure to poverty in a neighborhood.
Data Source: American Community Survey, 2006-2010
Related Tables/Maps: Table 14; Map 13
- 3. School Proficiency Index
Summary
The school proficiency index uses school-level data on the performance of 4th grade students on state exams to describe which neighborhoods have high-performing elementary schools nearby and which are near lower performing elementary schools. The school proficiency index is a function of the percent of 4th grade students proficient in reading (r) and math (m) on state test scores for up to three schools (i=1,2,3) within 1.5 miles of the block-group centroid. S denotes 4th grade school enrollment:
Elementary schools are linked with block-groups based on a geographic mapping of attendance area zones from School Attendance Boundary Information System (SABINS), where available, or within-district proximity matches of up to the three-closest schools within 1.5 miles. In cases with multiple school matches, an enrollment-weighted score is calculated following the equation above.
Interpretation
Values are percentile ranked and range from 0 to 100. The higher the score, the higher the quality of the school system in a neighborhood.
Data Source: Great Schools (proficiency data, 2011-12 or more recent); Common Core of Data (school addresses and enrollment, 2011-12); SABINS (attendance boundaries, 2011-12).
Related Tables/Maps: Table 14; Map 9
- 1. Jobs Proximity Index
Summary
The jobs proximity index quantifies the accessibility of a given residential neighborhood as a function of its distance to all job locations within a CBSA, with distance to larger employment centers weighted more heavily. Specifically, a gravity model is used, where the accessibility (Ai) of a given residential block-group is a summary description of the distance to all job locations, with the distance from any single job location positively weighted by the size of employment (job opportunities) at that location and inversely weighted by the labor supply (competition) to that location. More formally, the model has the following specification:
Where i indexes residential locations and j indexes job locations within a CBSA, and distance, d, is measured as “as the crow flies” between block-groups i and j. E represents the number of jobs in block-group j and L is the number of workers.
The Longitudinal Employer-Household Dynamics (LEHD) has missing jobs data in all of Puerto Rico and a concentration of missing records in Massachusetts.
Interpretation
Values are percentile ranked with values ranging from 0 to 100. The higher the index value, the better the access to employment opportunities for residents in a neighborhood.
Data Source: Longitudinal Employer-Household Dynamics (LEHD) data, 2010
Related Template Tables/Maps: Table 14; Map 10
- 2. Labor Market Index
Summary
The labor market index provides a summary description of the relative intensity of labor market engagement and human capital in a neighborhood. This is based upon the level of employment, labor force participation, and educational attainment in a census tract (i). Formally, the labor market index is a linear combination of three standardized vectors: unemployment rate (u), labor-force participation rate (l), and percent with a bachelor’s degree or higher (b), using the following formula:
Where the means (, , ) and standard errors (, , ) are estimated over the national distribution. Also, the value for unemployment rate is inverted.
Interpretation
Values are percentile ranked nationally and range from 0 to 100. The higher the score, the higher the labor force participation and human capital in a neighborhood.
Data Source: American Community Survey, 2006-2010
Related Tables/Maps: Table 14; Map 11
- 3. Low Transportation Cost Index
Summary
This index is based on estimates of transportation costs for a family that meets the following description: a 3-person single-parent family with income at 50% of the median income for renters for the region (i.e. CBSA). The estimates come from the Location Affordability Index (LAI). The data used in the AFFH Tool correspond to those for household type 6 (hh_type6_) as noted in the LAI data dictionary. More specifically, among this household type, we model transportation costs as a percent of income for renters (t_rent). Neighborhoods are defined as census tracts. The LAI data do not contain transportation cost information for Puerto Rico.
Interpretation
Values are inverted and percentile ranked nationally, with values ranging from 0 to 100. The higher the score, the lower the cost of transportation in that neighborhood. Transportation costs may be low for a variety of reasons, including greater access to public transportation and the density of homes, services, and jobs in the neighborhood and surrounding community.
Data Source: Location Affordability Index (LAI) data, 2008-2012
Related Tables/Maps: Table 14; Map 12
References:
www.locationaffordability.info
http://lai.locationaffordability.info//lai_data_dictionary.pdf
- 4. Transit Trips Index
Summary
This index is based on estimates of transit trips taken by a family that meets the following description: a 3-person single-parent family with income at 50% of the median income for renters for the region (i.e. the Core-Based Statistical Area (CBSA)). The estimates come from the Location Affordability Index (LAI). The data used in the AFFH tool correspond to those for household type 6 (hh_type6_) as noted in the LAI data dictionary. More specifically, among this household type, we model annual transit trips for renters (transit_trips_rent). Neighborhoods are defined as census tracts. The LAI has missing transit trip information for Puerto Rico.
Interpretation
Values are percentile ranked nationally, with values ranging from 0 to 100. The higher the score, the more likely residents in that neighborhood utilize public transit. The index controls for income such that a higher index value will often reflect better access to public transit.
Data Source: Location Affordability Index (LAI) data, 2008-2012
Related Tables/Maps: Table 14; Map 12
References:
www.locationaffordability.info
http://lai.locationaffordability.info//lai_data_dictionary.pdf
- 5. Environmental Health Index
Summary
The environmental health index summarizes potential exposure to harmful toxins at a neighborhood level. The index is a linear combination of standardized EPA estimates of air quality carcinogenic (c), respiratory (r) and neurological (n) hazards with i indexing census tracts.
Where means (, , ) and standard errors (, , ) are estimated over the national distribution.
Interpretation
Values are inverted and then percentile ranked nationally. Values range from 0 to 100. The higher the index value, the less exposure to toxins harmful to human health. Therefore, the higher the value, the better the environmental quality of a neighborhood, where a neighborhood is a census block-group.
Data Source: National Air Toxics Assessment (NATA) data, 2005
Related Tables/Maps: Table 14; Map 14
References:
http://www.epa.gov/ttn/atw/natamain/
- C. Computing Indices by Protected Class
The Data Tool provides index values documenting the extent to which members of different racial or ethnic groups have access to particular opportunity indicators. The Data Tool provides a weighted average for a given racial or ethnic group. The generic access for racial or ethnic group M to asset dimension R in jurisdiction j is calculated as:
Where indicates Census tracts in jurisdiction j for subgroup M to dimension R. N is the total number of Census tracts in jurisdiction j.
It is useful to provide an example of this in practice (Table 2). Consider Jurisdiction X with a total of three neighborhoods (A, B, and C). Each neighborhood has an index score representing the prevalence of poverty within that neighborhood (Column (1), with higher values representing lower levels of poverty. To compute the index value for a particular racial or ethnic group, the values are weighted based on the distribution of that racial or ethnic group across the three neighborhoods. For example, 40% of the jurisdiction’s white population lives in neighborhood A, so the index value for neighborhood A represents 40% of the composite index value for the white population in the jurisdiction. The values for neighborhoods B and C are weighted at 40% and 20% respectively, based on the share of white individuals living in those neighborhoods, leading to a final weighted low poverty index for whites in the jurisdiction of 56.
Table 2. Example of Weighting of Low Poverty Index by Race in a Hypothetical Jurisdiction
|
Dimension |
White |
Black |
||||
Neighborhood |
Low Poverty Index |
white pop |
%white of total pop |
Index for whites |
black pop |
%black of total pop |
Index for blacks |
(1) |
(2) |
(3) |
(4) |
(5) |
(6) |
(7) |
|
A |
80 |
400 |
40% |
32 |
100 |
20% |
16 |
B |
50 |
400 |
40% |
20 |
150 |
30% |
15 |
C |
20 |
200 |
20% |
4 |
250 |
50% |
10 |
Total |
|
1000 |
100% |
56 |
500 |
100% |
41 |
This exercise can be repeated for each racial or ethnic group. For example, the low poverty index among blacks in Jurisdiction X is 41. Using these indices, it is possible to identify disparities in access to c opportunity across protected classes.
To account for differences in household income across groups, the Data Tool also provides separate index values for persons with incomes below the Federal poverty line, again breaking out values by racial or ethnic group. This will aid jurisdictions in understanding whether there are meaningful disparities in access to opportunity across protected classes that cannot be explained by differences in poverty status. These index values for racial/ethnic groups and for racial/ethnic groups below the Federal poverty line are available in Table 14.
[1] CDBG jurisdictions in the Data Tool exclude non-entitlement jurisdictions.
[2] Tract changes between 2010 and 2011 are here: http://www.census.gov/acs/www/data_documentation/2011_geography_release_notes/; Tract changes between 2011 and 2012 are here: http://www.census.gov/acs/www/data_documentation/2012_geography_release_notes/
H6107A: Rhode Island's Plan to Make Single Family Homes Subsidize High-Density Housing
RhodeMap RI / RI Rising depends upon an important State initiative: Getting you to subsidize your neighbors property taxes, even when your neighbor is financially better off than you!
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