This is a map to assist Department of Housing & Community Development staff determine if properties qualify for ARPA and repair funds.Targeted Rehab Boundaries Boundaries for the West Dallas Targeted Rehab Program (Census Tracts 106.01, 160.02, 105, 205, 101.01, 101.02, 43) and Tenth Street Rehab Program (Historic Tenth Street). Home repair programs available in these areas: Housing & Neighborhood Revitalization Targeted Rehabilitation Program (TRP) (dallascityhall.com) Unserved Areas Dallas Water Utilities (DWU) 's Unserved Areas Report identified geographical areas that need water and/or wastewater services throughout the City. DWU is in the process of building out service in these areas. (2020 update) Home repair programs available in these areas: Housing & Neighborhood Revitalization ARPA Septic Tank (dallascityhall.com) QCTs This service contains a list of census tracts that qualify for the American Rescue Plan Act (ARPA).  The list was provided to EGIS by BMS.  The data used to produce this service can be found at Qualified Census Tracts and Difficult Development Areas | HUD USER. Low-Income Housing Tax Credit Qualified Census Tracts must have 50 percent of households with incomes below 60 percent of the Area Median Gross Income (AMGI) or have a poverty rate of 25 percent or more. Difficult Development Areas (DDA) are areas with high land, construction and utility costs relative to the area median income and are based on Fair Market Rents, income limits, the 2010 census counts, and 5-year American Community Survey (ACS) data. Maps of Qualified Census Tracts and Difficult Development Areas are available at: 2022 and 2023 Small DDAs and QCTs | HUD USER. Qualified Census Tracts - Generate QCT Tables for Individual Areas (Also Includes DDA Information) This data was created by the Department of Housing and Urban Development in 2023.  This data is updated on a yearly basis.  Updated ARPA boundaries ARPA Home Repair Program boundaries for qualified neighborhoods. Home repair programs available in these areas: American Rescue Plan Act Neighborhood Revitalization Program (dallascityhall.com) (Limited availability, applications accepted based on funding available) Equity Strategy Target AreasThe Department of Housing & Neighborhood Revitalization (Housing) with the assistance of TDA Consultants selected three Equity Strategy Target Areas (ESTAs) for the implementation of the Dallas Housing Policy 2033 (DHP33). This layer contains boundaries as of January 2024. Housing will be collaborating with other City of Dallas departments and development and preservation partners to target housing and neighborhood revitalization projects in these areas. The Equity Strategy Target Areas (ESTAs) were selected using an Equity Index created by TDA consultants and the Housing Department. The Equity Index is based upon the 2023 Market Value Analysis, the City of Dallas OEI Equity Impact Assessment Tool (EIA), and the potential investment from the Dallas Water Utility Unserved Areas Program.Housing Opportunity Fund TIF District AreasThis is the Housing Opportunity Fund TIF District map for Housing & Community Development and Economic Development in the City of Dallas. The three TIF districts in this map are areas within the City of Dallas with select TIF funds for homeowner stabilization programs that may include Home Improvement and Preservation Programs (HIPP) and the Dallas Homebuyer Assistance Program (DHAP). The three Housing Opportunity Fund TIF districts are: the Oak Cliff Housing TIF, the Fort Worth Avenue Housing TIF, and the Deep Ellum Housing TIF. Housing & Community Development is starting to implement these areas in 2025.

Income limits used to determine the income eligibility of applicants for assistance under three programs authorized by the National Housing Act. These programs are the Section 221(d)(3) Below Market Interest Rate (BMIR) rental program, the Section 235 program, and the Section 236 program. These income limits are listed by dollar amount and family size, and they are effective on the date issued. Due to the Housing and Economic Recovery Act of 2008 (Public Law 110-289), Income Limits used to determine qualification levels as well as set maximum rental rates for projects funded with tax credits authorized under section 42 of the Internal Revenue Code (the Code) and projects financed with tax exempt housing bonds issued to provide qualified residential rental development under section 142 of the Code (hereafter referred to as Multifamily Tax Subsidy Projects (MTSPs)) are now calculated and presented separately from the Section 8 income limits.

The Housing Affordability Index value in the United States plummeted in 2022, surpassing the historical record of 107.1 index points in 2006. In 2024, the housing affordability index measured 98.1 index points, making it the second-worst year for homebuyers since the start of the observation period. What does the Housing Affordability Index mean? The Housing Affordability Index uses data provided by the National Association of Realtors (NAR). It measures whether a family earning the national median income can afford the monthly mortgage payments on a median-priced existing single-family home. An index value of 100 means that a family has exactly enough income to qualify for a mortgage on a home. The higher the index value, the more affordable a house is to a family. Key factors that drive the real estate market Income, house prices, and mortgage rates are some of the most important factors influencing homebuyer sentiment. When incomes increase, consumer power also increases. The median household income in the United States declined in 2022, affecting affordability. Additionally, mortgage interest rates have soared, adding to the financial burden of homebuyers. The sales price of existing single-family homes in the U.S. has increased year-on-year since 2011 and reached 389,000 U.S. dollars in 2023.

Analysis of ‘Residential Existing Homes (One-to-Four Units) Energy Efficiency Projects for Households with Income up to 60% State Median Income: Beginning January 2018’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/361fed56-140f-4b31-8092-22e8d4c807a5 on 12 February 2022.

--- Dataset description provided by original source is as follows ---

IMPORTANT! PLEASE READ DISCLAIMER BEFORE USING DATA. To reduce the energy burden on income-qualified households within New York State, NYSERDA offers the EmPower New York (EmPower) program, a retrofit program that provides cost-effective electric reduction measures (i.e., primarily lighting and refrigerator replacements), and cost-effective home performance measures (i.e., insulation air sealing, heating system repair and replacments, and health and safety measures) to income qualified homeowners and renters. Home assessments and implementation services are provided by Building Performance Institute (BPI) Goldstar contractors to reduce energy use for low income households. This data set includes energy efficiency projects completed since January 2018 for households with income up to 60% area (county) median income.

D I S C L A I M E R: Estimated Annual kWh Savings, Estimated Annual MMBtu Savings, and First Year Energy Savings $ Estimate represent contractor reported savings derived from energy modeling software calculations and not actual realized energy savings. The accuracy of the Estimated Annual kWh Savings and Estimated Annual MMBtu Savings for projects has been evaluated by an independent third party. The results of the impact analysis indicate that, on average, actual savings amount to 54 percent of the Estimated Annual kWh Savings and 70 percent of the Estimated Annual MMBtu Savings. The analysis did not evaluate every single project, but rather a sample of projects from 2007 and 2008, so the results are applicable to the population on average but not necessarily to any individual project which could have over or under achieved in comparison to the evaluated savings. The results from the impact analysis will be updated when more recent information is available. Some reasons individual households may realize savings different from those projected include, but are not limited to, changes in the number or needs of household members, changes in occupancy schedules, changes in energy usage behaviors, changes to appliances and electronics installed in the home, and beginning or ending a home business. For more information, please refer to the Evaluation Report published on NYSERDA’s website at: https://www.nyserda.ny.gov/-/media/Files/Publications/PPSER/Program-Evaluation/2012ContractorReports/2012-EmPower-New-York-Impact-Report.pdf.

This dataset includes the following data points for projects completed after January 1, 2018: Reporting Period, Project ID, Project County, Project City, Project ZIP, Gas Utility, Electric Utility, Project Completion Date, Total Project Cost (USD), Pre-Retrofit Home Heating Fuel Type, Year Home Built, Size of Home, Number of Units, Job Type, Type of Dwelling, Measure Type, Estimated Annual kWh Savings, Estimated Annual MMBtu Savings, First Year Modeled Energy Savings $ Estimate (USD).

How does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov.

--- Original source retains full ownership of the source dataset ---

IMPORTANT! PLEASE READ DISCLAIMER BEFORE USING DATA. To reduce the energy burden on income-qualified households within New York State, NYSERDA offers the EmPower New York (EmPower) program, a retrofit program that provides cost-effective electric reduction measures (i.e., primarily lighting and refrigerator replacements), and cost-effective home performance measures (i.e., insulation air sealing, heating system repair and replacments, and health and safety measures) to income qualified homeowners and renters. Home assessments and implementation services are provided by Building Performance Institute (BPI) Goldstar contractors to reduce energy use for low income households. This data set includes energy efficiency projects completed since January 2018 for households with income up to 60% area (county) median income.

D I S C L A I M E R: Estimated Annual kWh Savings, Estimated Annual MMBtu Savings, and First Year Energy Savings $ Estimate represent contractor reported savings derived from energy modeling software calculations and not actual realized energy savings. The accuracy of the Estimated Annual kWh Savings and Estimated Annual MMBtu Savings for projects has been evaluated by an independent third party. The results of the impact analysis indicate that, on average, actual savings amount to 54 percent of the Estimated Annual kWh Savings and 70 percent of the Estimated Annual MMBtu Savings. The analysis did not evaluate every single project, but rather a sample of projects from 2007 and 2008, so the results are applicable to the population on average but not necessarily to any individual project which could have over or under achieved in comparison to the evaluated savings. The results from the impact analysis will be updated when more recent information is available. Some reasons individual households may realize savings different from those projected include, but are not limited to, changes in the number or needs of household members, changes in occupancy schedules, changes in energy usage behaviors, changes to appliances and electronics installed in the home, and beginning or ending a home business. For more information, please refer to the Evaluation Report published on NYSERDA’s website at: https://www.nyserda.ny.gov/-/media/Files/Publications/PPSER/Program-Evaluation/2012ContractorReports/2012-EmPower-New-York-Impact-Report.pdf.

This dataset includes the following data points for projects completed after January 1, 2018: Reporting Period, Project ID, Project County, Project City, Project ZIP, Gas Utility, Electric Utility, Project Completion Date, Total Project Cost (USD), Pre-Retrofit Home Heating Fuel Type, Year Home Built, Size of Home, Number of Units, Job Type, Type of Dwelling, Measure Type, Estimated Annual kWh Savings, Estimated Annual MMBtu Savings, First Year Modeled Energy Savings $ Estimate (USD).

The U.S. Department of Housing and Urban Development (HUD) periodically receives "custom tabulations" of Census data from the U.S. Census Bureau that are largely not available through standard Census products. These datasets, known as "CHAS" (Comprehensive Housing Affordability Strategy) data, demonstrate the extent of housing problems and housing needs, particularly for low income households. The primary purpose of CHAS data is to demonstrate the number of households in need of housing assistance. This is estimated by the number of households that have certain housing problems and have income low enough to qualify for HUD’s programs (primarily 30, 50, and 80 percent of median income). CHAS data provides counts of the numbers of households that fit these HUD-specified characteristics in a variety of geographic areas. In addition to estimating low-income housing needs, CHAS data contributes to a more comprehensive market analysis by documenting issues like lead paint risks, "affordability mismatch," and the interaction of affordability with variables like age of homes, number of bedrooms, and type of building.This dataset is a special tabulation of the 2016-2020 American Community Survey (ACS) and reflects conditions over that time period. The dataset uses custom HUD Area Median Family Income (HAMFI) figures calculated by HUD PDR staff based on 2016-2020 ACS income data. CHAS datasets are used by Federal, State, and Local governments to plan how to spend, and distribute HUD program funds. To learn more about the Comprehensive Housing Affordability Strategy (CHAS), visit: https://www.huduser.gov/portal/datasets/cp.html, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. To learn more about the American Community Survey (ACS), and associated datasets visit: https://www.census.gov/programs-surveys/acs Data Dictionary: DD_ACS 5-Year CHAS Estimate Data by County Date of Coverage: 2016-2020

In many metros in the United States, the median household income was insufficient to qualify for the median-priced home. Among the 50 largest metros in the U.S., San Jose-Sunnyvale-Santa Clara, CA was the least affordable one in 2022, with the housing affordability index at 41.5 index points. This means that the median household income, when accounting for monthly housing expenses, was less than 42 percent of the necessary income to qualify for a mortgage. An index value over 100, on the other hand, shows that the median income is sufficient for a mortgage. Metros, such as Cleveland-Elyria, OH, and St. Louis, MO-IL had a median household income much higher than the income needed to buy the median-priced home.

This map shows households that spend more than 30 percent of their income on housing, a threshold widely used by many affordable housing advocates and official government sources including Housing and Urban Development. Census asks about income and housing costs to understand whether housing is affordable in local communities. When housing is not sufficient or not affordable, income data helps communities:

• Enroll eligible households in programs designed to assist them.
• Qualify for grants from the Community Development Block Grant (CDBG), HOME Investment Partnership Program, Emergency Solutions Grants (ESG), Housing Opportunities for Persons with AIDS (HOPWA), and other programs.

Map opens in Atlanta. Use the bookmarks or search bar to view other cities. Data is symbolized to show the relationship between burdensome housing costs for owner households with a mortgage and renter households:

This map uses these hosted feature layers containing the most recent American Community Survey data. These layers are part of the ArcGIS Living Atlas, and are updated every year when the American Community Survey releases new estimates, so values in the map always reflect the newest data available.

This map shows households that spend 30 percent or more of their income on housing, a threshold widely used by many affordable housing advocates and official government sources including Housing and Urban Development. Census asks about income and housing costs to understand whether housing is affordable in local communities. When housing is not sufficient or not affordable, income data helps communities: Enroll eligible households in programs designed to assist them.Qualify for grants from the Community Development Block Grant (CDBG), HOME Investment Partnership Program, Emergency Solutions Grants (ESG), Housing Opportunities for Persons with AIDS (HOPWA), and other programs.When rental housing is not affordable, the Department of Housing and Urban Development (HUD) uses rent data to determine the amount of tenant subsidies in housing assistance programs.Map opens in Atlanta. Use the bookmarks or search bar to view other cities. Data is symbolized to show the relationship between burdensome housing costs for owner households with a mortgage and renter households:This map uses these hosted feature layers containing the most recent American Community Survey data. These layers are part of the ArcGIS Living Atlas, and are updated every year when the American Community Survey releases new estimates, so values in the map always reflect the newest data available.

The Housing Affordability Index, calculated by the Runstad Center for Real Estate Studies, measures the ability of a middle-income family to carry the mortgage payments on a median-price home. When the index is 100 there is a balance between the family’s ability to pay and the cost. Higher indexes indicate housing is more affordable.

For example, an index of 126 means that a median-income family has 26 percent more income than the bare minimum required to qualify for a mortgage on a median-price home. An index of 80 means that a median-income family has less income than the minimum required.

This dataset and map service provides information on the U.S. Housing and Urban Development's (HUD) low to moderate income areas. The term Low to Moderate Income, often referred to as low-mod, has a specific programmatic context within the Community Development Block Grant (CDBG) program. Over a 1, 2, or 3-year period, as selected by the grantee, not less than 70 percent of CDBG funds must be used for activities that benefit low- and moderate-income persons. HUD uses special tabulations of Census data to determine areas where at least 51% of households have incomes at or below 80% of the area median income (AMI). This dataset and map service contains the following layer.

This map uses a two-color thematic shading to emphasize where areas experience the least to the most affordable housing across the US. This web map is part of the How Affordable is the American Dream story map.

Esri’s Housing Affordability Index (HAI) is a powerful tool to analyze local real estate markets. Esri’s housing affordability index measures the financial ability of a typical household to purchase an existing home in an area. A HAI of 100 represents an area that on average has sufficient household income to qualify for a loan on a home valued at the median home price. An index greater than 100 suggests homes are easily afforded by the average area resident. A HAI less than 100 suggests that homes are less affordable. The housing affordability index is not applicable in areas with no households or in predominantly rental markets . Esri’s home value estimates cover owner-occupied homes only. For a full demographic analysis of US growth refer to Esri's Trending in 2017: The Selectivity of Growth.

The pop-up is configured to show the following 2017 demographics for each County and ZIP Code:

Total Households 2010-17 Annual Pop Change Median Age Percent Owner-Occupied Housing Units Median Household Income Median Home Value Housing Affordability Index Share of Income to Mortgage

Text source: https://www.huduser.gov/portal/publications/hsgfin/addi.html In recognition of the fact that a lack of savings is the most significant barrier to homeownership for most low-income families1, Congress passed the American Dream Downpayment Act of 2003, which established the American Dream Downpayment Initiative (ADDI). The ADDI program was designed to provide assistance with downpayments, closing costs, and, if necessary, rehabilitation work done in conjunction with a home purchase. This formula-based program disburses assistance through a network of Participating Jurisdictions (PJs) in all 50 states and affords them significant flexibility in designing homebuyer programs to meet the needs of their communities. Established as part of the HOME program,2 ADDI is a prime example of direct federal assistance to promote low-income homeownership. In recent years there have been growing concerns that many new low-income homeowners have had difficulty maintaining homeownership.3 To address these concerns in the context of the ADDI program, the Fiscal Year 2006 U.S. Senate Report on the Transportation, Treasury and HUD Appropriations Bill directed the U.S. Department of Housing and Urban Development (HUD) to report on the foreclosure and delinquency rate of households who received downpayment assistance through ADDI.4 This report has been developed in response to this congressional mandate. Due to the limited program history of ADDI, and since HOME-assisted homebuyers are quite similar to those assisted by the ADDI, this study jointly estimates annual foreclosure and delinquency rates for both HOME- and ADDI-assisted borrowers who purchased homes during the period from 2001 through 2005.5 While all HOME/ADDI-assisted borrowers were included in the analysis, in order to have the results be representative of the ADDI program, the sample of PJs was limited to those that were eligible for an allocation of ADDI funds in 2004, the year in which the largest number of PJs were eligible. The primary objective of the study, which addresses the congressional inquiry, is to provide an estimate of the foreclosure and delinquency rates among HOME/ADDI-assisted homebuyers. HUD was also interested in an analysis of the reasons behind these outcomes. Thus, a secondary objective of this study is to analyze the factors associated with variations in delinquency and default rates. 1 See, for example, U. S. Department of Housing and Urban Development, Barriers to Minority Homeownership, July 17, 2002, and Herbert et al., Homeownership Gaps Among Low-Income and Minority Borrowers and Neighborhoods, U.S. Department of Housing and Urban Development, March 2005. 2 Created under Title II of the National Affordable Housing Act of 1990, the HOME program is designed to provide affordable housing to low-income households, expand the capacity of nonprofit housing providers, and strengthen the ability of state and local governments to develop and implement affordable housing strate-gies tailored to local needs and priorities. 3 See, for example, Dean Baker, "Who's Dreaming?: Homeownership Among Low-Income Families," Center for Eco-nomic and Policy Research, Washington, DC, January 2005. 4 Throughout our discussion the terms "default" and "foreclosure" are used to refer to the same outcome where homeowners lose their home in foreclosure. 5 Foreclosure and delinquency rates for 2000 are not included here as the data was not consistent enough to produce valid estimations. This report is based in part on surveys of participating jurisdictions.

State-reported annual data collected on the presence of elderly, disabled, and young children in eligible households receiving Low Income Home Energy Assistance Program (LIHEAP) heating assistance, cooling assistance, crisis assistance or weatherization assistance.

The data set provides information about households served by the California Department of Community Services and Development (CSD) Low-Income Home Energy Assistance Program (LIHEAP). LIHEAP is a federal program that helps eligible low-income households manage and meet their immediate home heating and/or cooling needs. Additional information and a detailed description of program services is available at the CSD LIHEAP webpage: http://www.csd.ca.gov/Services/HelpPayingUtilityBills.aspx

Following a period of stagnation over most of the 2010s, the number of owner occupied housing units in the United States started to grow in 2017. In 2023, there were over 86 million owner-occupied homes. Owner-occupied housing is where the person who owns a property – either outright or through a mortgage – also resides in the property. Excluded are therefore rental properties, employer-provided housing and social housing. Homeownership sentiment in the U.S. Though homeownership is still a cornerstone of the American dream, an increasing share of people see themselves as lifelong renters. Millennials have been notoriously late to enter the housing market, with one in four reporting that they would probably continue to always rent in the future, a 2022 survey found. In 2017, just five years before that, this share stood at about 13 percent. How many renter households are there? Renter households are roughly half as few as owner-occupied households in the U.S. In 2023, the number of renter occupied housing units amounted to almost 45 million. Climbing on the property ladder for renters is not always easy, as it requires prospective homebuyers to save up for a down payment and qualify for a mortgage. In many metros, the median household income is insufficient to qualify for the median-priced home.

In 2024, there were approximately **** million housing units occupied by renters in the United States. This number has been gradually increasing since 2010 as part of a long-term upward swing since 1975. Meanwhile, the number of unoccupied rental housing units has followed a downward trend, suggesting a growing demand and supply failing to catch up. Why are rental homes in such high demand? This high demand for rental homes is related to the shortage of affordable housing. Climbing the property ladder for renters is not always easy, as it requires prospective homebuyers to save up for a down payment and qualify for a mortgage. In many metros, the median household income is insufficient to qualify for the median-priced home. How many owner occupied homes are there in the U.S.? In 2023, there were over ** million owner occupied homes. Owner occupied housing is when the person who owns a property – either outright or through a mortgage – also resides in the property. Excluded are therefore rental properties, employer-provided housing and social housing.

This data, maintained by the Mayor’s Office of Housing (MOH), is an inventory of all income-restricted units in the city. This data includes public housing owned by the Boston Housing Authority (BHA), privately- owned housing built with funding from DND and/or on land that was formerly City-owned, and privately-owned housing built without any City subsidy, e.g., created using Low-Income Housing Tax Credits (LIHTC) or as part of the Inclusionary Development Policy (IDP). Information is gathered from a variety of sources, including the City's IDP list, permitting and completion data from the Inspectional Services Department (ISD), newspaper advertisements for affordable units, Community Economic Development Assistance Corporation’s (CEDAC) Expiring Use list, and project lists from the BHA, the Massachusetts Department of Housing and Community Development (DHCD), MassHousing, and the U.S. Department of Housing and Urban Development (HUD), among others. The data is meant to be as exhaustive and up-to-date as possible, but since many units are not required to report data to the City of Boston, MOH is constantly working to verify and update it. See the data dictionary for more information on the structure of the data and important notes. The database only includes units that have a deed-restriction. It does not include tenant-based (also known as mobile) vouchers, which subsidize rent, but move with the tenant and are not attached to a particular unit. There are over 22,000 tenant-based vouchers in the city of Boston which provide additional affordability to low- and moderate-income households not accounted for here. The Income-Restricted Housing report can be directly accessed here:
https://www.boston.gov/sites/default/files/file/2023/04/Income%20Restricted%20Housing%202022_0.pdf

Learn more about income-restricted housing (as well as other types of affordable housing) here: https://www.boston.gov/affordable-housing-boston#income-restricted

Quarterly median housing prices and Housing Affordability Index from Snohomish County and the state of Washington, per the University of Washington Runstad Department of Real Estate. Data available at: https://wcrer.be.uw.edu/archived-reports/.

The Housing Affordability Index measures whether or not a typical family earns enough income to qualify for a mortgage loan on a typical home. A value of 100 means that a family with the median income has exactly enough income to qualify for a mortgage on a median-priced home. For example, a composite HAI of 120.0 means a family earning the median family income has 120% of the income necessary to qualify for a conventional loan covering 80 percent of a median-priced existing single-family home.

Graph and download economic data for Housing Affordability Index (Fixed) (FIXHAI) from Mar 2024 to Mar 2025 about fixed, housing, indexes, and USA.