Affordable Rental Housing in Loudoun County Affordable housing communities are eligible to renters based on Area Median Income (AMI) as defined by the U.S. Department of Housing and Urban Development (HUD). AMI is updated annually in April by HUD. Please refer to the most recent AMI levels here to learn if you are eligible.The Unmet Housing Needs Units (UHNU) Program offers a limited number of apartments available to eligible households with a gross income no more than 30% of the Area Median Income. Communities with the UHNU symbol in this guide have UHNU units. The County is currently accepting applications. To request an application for the UHNU Program, send an Email to the Loudoun County Department of Housing and Community Development. The Affordable Dwelling Unit (ADU) Rental Program offers eligible households the opportunity to rent an apartment that is below market rate. The total household gross income must be between 30% – 50% of the Area Median Income. Communities with the ADU symbol in this guide have ADU units. If eligible, applicants will be placed on a waitlist. The waitlist is Open. To review requirements and access the application, please visit Affordable Dwelling Unit page for more information.The Low-Income Housing Tax Credit (LIHTC) Program offers apartments affordable to households earning no more than 60% of the Area Median Income. Communities with the TC symbol in this guide have LIHTC units. The program is administered by Virginia Housing and the Loudoun County Department of Housing and Community Development does not manage LIHTC units. Call each community directly for more information and to apply.Apartment Communities for Older Adults are included in this map. For age restrictions and other requirements, contact each communities directly. For information on retirement communities, assisted living facilities, and nursing home placement, contact Loudoun County Adult and Aging Services at (703) 771-5742, or visit the Aging & Independence page for more information.Apartment Rental Guide

This dataset contains multifamily affordable and market-rate housing sites (typically 5+ units) in the City of Detroit that have been built or rehabbed since 2015, or are currently under construction. Most sites are rental housing, though some are for sale. The data are collected from developers, other government departments and agencies, and proprietary data sources in order to track new multifamily and affordable housing construction and rehabilitation occurring in throughout the city, in service of the City's multifamily affordable housing goals. Data are compiled by various teams within the Housing and Revitalization Department (HRD), led by the Preservation Team. This dataset reflects HRD's current knowledge of multifamily units under construction in the city and will be updated as the department's knowledge changes. For more information about the City's multifamily affordable housing policies and goals, visit here.Affordability level for affordable units are measured by the percentage of the Area Median Income (AMI) that a household could earn for that unit to be considered affordable for them. For example, a unit that rents at a 60% AMI threshold would be affordable to a household earning 60% or less of the median income for the area. Rent affordability is typically defined as housing costs consuming 30% or less of monthly income. Regulated housing programs are designed to serve households based on certain income benchmarks relative to AMI, and these income benchmarks vary based on household size. Detroit city's AMI levels are set by the Department of Housing and Urban Development (HUD) for the Detroit-Warren-Livonia, MI Metro Fair Market Rent (FMR) area. For more information on AMI in Detroit, visit here.

Rental Affordability Analysis Based on Median Income

Trends in Tier-Based Affordability Across the U.S

By Zillow Data [source]

About this dataset

This dataset contains rental affordability data for different regions in the US, giving valuable insights into regional rental markets. Renters can use this information to identify where their budget will go the farthest. The cities are organized by rent tier in order to analyze affordability trends within and between different housing stock types. Within each region, the data includes median household income, Zillow Rent Index (ZRI), and percent of income spent on rent.

The Zillow Home Value Forecast (ZHVF) is used to calculate future combined mortgage pay/rent payments in each region using current median home prices, actual outstanding debt amounts and 30-year fixed mortgage interest rates reported through partnership with TransUnion credit bureau. Zillow also provides a breakdown of cash vs financing purchases for buyers looking for an investment or cash option solution.

This dataset provides an effective tool for consumers who want to better understand how their budget fits into diverse rental markets across the US; from condominiums and co-ops, multifamily residences with five or more units, duplexes and triplexes - every renter can determine how their housing budget should be adjusted as they consider multiple living possibilities throughout the country based on real-time price data!

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How to use the dataset

Introduction

Getting Started

• First, you'll need to download the TieredAffordability_Rental.csv dataset from this Kaggle page onto your computer or device.

• After downloading the data set onto your device, open it with any CSV viewing software of your choice (ex: Excel). It will include columns for RegionName**RegionName** , homes type/housing stock (All Homes or Condo/Co-op) SizeRank , Rent tier tier , Date date , median household income income , Zillow Rent Index zri and PercentIncomeSpentOnRent percentage (what portion of monthly median house-hold goes toward monthly mortgage payment) .

• To begin analyzing rental prices across different regions using this dataset, look first at column four: SizeRank; which ranks each region based on size - smallest regions listed first and largest at last - so that you can compare a similar range of Regions when looking at affordability by home sizes larger than one unit multiplex dwellings.*Duples/Triplex*. Once there is an understanding of how all homes compare overall now it is time to consider home types Multifamily 5+ units according to rent tiers tier .

• Next, choose one or more region(s) for comparison based on their rank in SizeRank column –so that all information gathered about them reflects what portionof households fall into certain categories ; eg; All Homes / Small Home /Large Home / MultiPlex Dwelling and what tier does each size rank falls into eg.: Affordable/Slightly Expensive/ Moderately Expensive etc.. This will enable further abstraction from other elements like date vs inflation rate per month or periodical intervals set herein by Rate segmentation i e dates givenin ‘Date’Columns – making the task easier and more direct while analyzing renatalAffordibility Analysis Based On Median Income zri 00 zwi & PCISOR 00 PCIRO

Research Ideas

• Use the PercentIncomeSpentOnRent column to compare rental affordability between regions within a particular tier and determine optimal rent tiers for relocating families.
• Analyze how market conditions are affecting rental affordability over time by using the income, zri, and PercentageIncomeSpentOnRent columns.
• Identify trends in housing prices for different tiers over the years by comparing SizeRank data with Zillow Home Value Forecast (ZHVF) numbers across different regions in order to identify locations that may be headed up or down in terms of home values (and therefore rent levels)

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: TieredAffordability_Rental.csv | Column name | Description | |:-----------------------------|:-------------------------------------------------------------| | RegionName | The name of the region. (String) ...

Displacement risk indicator classifying census tracts according to apartment rent prices in census tracts. We classify apartment rent along two dimensions: The average rents within the census tract for the specified year, balancing between nominal rental price and rental price per square foot.The change in average rent price (again balanced between nominal rent price and price per square foot) from the previous year.Note: Average rent calculations include market-rate and mixed-income multifamily apartment properties with 5 or more rental units in Seattle, excluding special types like student, senior, corporate or military housing. Source: Data from CoStar Group, www.costar.com, prepared by City of Seattle, Office of Planning and Community Development

This dataset contains existing multifamily rental sites in the City of Detroit with housing units that have been preserved as affordable since 2018 with assistance from the public sector.

Over time, affordable units are at risk of falling off line, either due to obsolescence or conversion to market-rate rents. This dataset contains occupied multifamily rental housing sites (typically 5+ units) in the City of Detroit, including those that have units that have been preserved as affordable since 2015 through public funding, regulatory agreements, and other means of assistance from the public sector. Data are collected from developers, other governmental departments and agencies, and proprietary data sources by various teams within the Housing and Revitalization Department, led by the Preservation Team. Data have been tracked since 2018 in service of citywide housing preservation goals. This reflects HRD's current knowledge of multifamily units in the city and will be updated as the department's knowledge changes. For more information about the City's multifamily affordable housing policies and goals, visit here.

Affordability level for affordable units are measured by the percentage of the Area Median Income (AMI) that a household could earn for that unit to be considered affordable for them. For example, a unit that rents at a 60% AMI threshold would be affordable to a household earning 60% or less of the median income for the area. Rent affordability is typically defined as housing costs consuming 30% or less of monthly income. Regulated housing programs are designed to serve households based on certain income benchmarks relative to AMI, and these income benchmarks vary based on household size. Detroit city's AMI levels are set by the Department of Housing and Urban Development (HUD) for the Detroit-Warren-Livonia, MI Metro Fair Market Rent (FMR) area. For more information on AMI in Detroit, visit here.

The Housing Affordability Data System (HADS) is a set of files derived from the 1985 and later national American Housing Survey (AHS) and the 2002 and later Metro AHS. This system categorizes housing units by affordability and households by income, with respect to the Adjusted Median Income, Fair Market Rent (FMR), and poverty income. It also includes housing cost burden for owner and renter households. These files have been the basis for the worst case needs tables since 2001. The data files are available for public use, since they were derived from AHS public use files and the published income limits and FMRs. These dataset give the community of housing analysts the opportunity to use a consistent set of affordability measures. The most recent year HADS is available as a Public Use File (PUF) is 2013. For 2015 and beyond, HADS is only available as an IUF and can no longer be released on a PUF. Those seeking access to more recent data should reach to the listed point of contact.

This dataset provides insights into the global housing market, covering various economic factors from 2015 to 2024. It includes details about property prices, rental yields, interest rates, and household income across multiple countries. This dataset is ideal for real estate analysis, financial forecasting, and market trend visualization.

📑 Column Descriptions

The median rents within the census tract for the specified year, balancing between nominal rental price and rental price per square foot.The change in median rent price (again balanced between nominal rent price and price per square foot) from the previous year.Note: Median rent calculations include market-rate and mixed-income multifamily apartment properties with 5 or more rental units in Seattle, excluding special types like student, senior, corporate or military housing.

In accordance with 24 CFR Part 92.252, HUD provides maximum HOME rent limits. The maximum HOME rents are the lesser of: The fair market rent for existing housing for comparable units in the area as established by HUD under 24 CFR 888.111 or A rent that does not exceed 30 percent of the adjusted income of a family whose annual income equals 65 percent of the median income for the area, as determined by HUD, with adjustments for number of bedrooms in the unit. The HOME rent limits provided by HUD will include average occupancy per unit and adjusted income assumptions.

Context

The Housing Affordability Data System (HADS) is a set of files used for the American housing survey to analyze housing affordability. This system categorizes housing units by affordability and households by income, with respect to the Adjusted Median Income, Fair Market Rent (FMR), and poverty income. It also includes the housing cost burden for owner and renter households.

Content

There are 99 variables in the original dataset. Most of them are derived. After cleaning and filtering - Dataset contains 27 columns.

The Low-Income Housing Tax Credit (LIHTC) is the most important resource for creating affordable housing in the United States today. The LIHTC database, created by HUD and available to the public since 1997, contains information on 48,672 projects and 3.23 million housing units placed in service since 1987. 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.

A Home for Everyone is the City of Boise’s (city) initiative to address needs in the community by supporting the development and preservation of housing affordable to residents on Boise budgets. A Home for Everyone has three core goals: produce new homes affordable at 60% of area median income, create permanent supportive housing for households experiencing homelessness, and preserve home affordable at 80% of area median income. This dataset includes information about all homes that count toward the city’s Home for Everyone goals.

While the “produce affordable housing” and “create permanent supportive housing” goals are focused on supporting the development of new housing, the preservation goal is focused on maintaining existing housing affordable. As a result, many of the data fields related to new development are not relevant to preservation projects. For example, zoning incentives are only applicable to new construction projects.

Data may be unavailable for some projects and details are subject to change until construction is complete. Addresses are excluded for projects with fewer than five homes for privacy reasons.

The dataset includes details on the number of “homes”. We use the word "home" to refer to any single unit of housing regardless of size, type, or whether it is rented or owned. For example, a building with 40 apartments counts as 40 homes, and a single detached house counts as one home.

The dataset includes details about the phase of each project when a project involves constructing new housing. The process for building a new development is as follows: First, one must receive approval from the city’s Planning Division, which is also known as being “entitled.” Next, one must apply for and receive a permit from the city’s Building Division before beginning construction. Finally, once construction is complete and all city inspections have been passed, the building can be occupied.

To contribute to a city goal, homes must meet affordability requirements based on a standard called area median income. The city considers housing affordable if is targeted to households earning at or below 80% of the area median income. For a three-person household in Boise, that equates to an annual income of $60,650 and monthly housing cost of $1,516. Deeply affordable housing sets the income limit at 60% of area median income, or even 30% of area median income. See Boise Income Guidelines for more details.Project Name – The name of each project. If a row is related to the Home Improvement Loan program, that row aggregates data for all homes that received a loan in that quarter or year. Primary Address – The primary address for the development. Some developments encompass multiple addresses.Project Address(es) – Includes all addresses that are included as part of the development project.Parcel Number(s) – The identification code for all parcels of land included in the development.Acreage – The number of acres for the parcel(s) included in the project.Planning Permit Number – The identification code for all permits the development has received from the Planning Division for the City of Boise. The number and types of permits required vary based on the location and type of development.Date Entitled – The date a development was approved by the City’s Planning Division.Building Permit Number – The identification code for all permits the development has received from the city’s Building Division.Date Building Permit Issued – Building permits are required to begin construction on a development.Date Final Certificate of Occupancy Issued – A certificate of occupancy is the final approval by the city for a development, once construction is complete. Not all developments require a certificate of occupancy.Studio – The number of homes in the development that are classified as a studio. A studio is typically defined as a home in which there is no separate bedroom. A single room serves as both a bedroom and a living room.1-Bedroom – The number of homes in a development that have exactly one bedroom.2-Bedroom – The number of homes in a development that have exactly two bedrooms.3-Bedroom – The number of homes in a development that have exactly three bedrooms.4+ Bedroom – The number of homes in a development that have four or more bedrooms.# of Total Project Units – The total number of homes in the development.# of units toward goals – The number of homes in a development that contribute to either the city’s goal to produce housing affordable at or under 60% of area median income, or the city’s goal to create permanent supportive housing for households experiencing homelessness. Rent at or under 60% AMI - The number of homes in a development that are required to be rented at or below 60% of area median income. See the description of the dataset above for an explanation of area median income or see Boise Income Guidelines for more details. Boise defines a home as “affordable” if it is rented or sold at or below 80% of area median income.Rent 61-80% AMI – The number of homes in a development that are required to be rented at between 61% and 80% of area median income. See the description of the dataset above for an explanation of area median income or see Boise Income Guidelines for more details. Boise defines a home as “affordable” if it is rented or sold at or below 80% of area median income.Rent 81-120% AMI - The number of homes in a development that are required to be rented at between 81% and 120% of area median income. See the description of the dataset above for an explanation of area median income or see Boise Income Guidelines for more details.Own at or under 60% AMI - The number of homes in a development that are required to be sold at or below 60% of area median income. See the description of the dataset above for an explanation of area median income or see Boise Income Guidelines for more details. Boise defines a home as “affordable” if it is rented or sold at or below 80% of area median income.

The Housing Affordability Data System (HADS) is a set of housing unit level datasets that measures the affordability of housing units and the housing cost burdens of households, relative to area median incomes, poverty level incomes, and Fair Market Rents. The purpose of these datasets is to provide housing analysts with consistent measures of affordability and burdens over a long period. The datasets are based on the American Housing Survey (AHS) national files from 1985 through 2005 and the metropolitan files for 2002 and 2004. Users can link records in HADS files to AHS records, allowing access to all of the AHS variables. Housing-level variables include information on the number of rooms in the housing unit, the year the unit was built, whether it was occupied or vacant, whether the unit was rented or owned, whether it was a single family or multiunit structure, the number of units in the building, the current market value of the unit, and measures of relative housing costs. The dataset also includes variables describing the number of people living in the household, household income, and the type of residential area (e.g., urban or suburban).

This layer shows housing costs as a percentage of household income. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Income is based on earnings in past 12 months of survey. This layer is symbolized to show the percent of renter households that spend 30.0% or more of their household income on gross rent (contract rent plus tenant-paid utilities). To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B25070, B25091 Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

Thumbnail image by Tony Moody.This dataset includes all housing developments approved by the City of Boise’s (“city”) Planning Division since 2020 that are known by the city to have received or are expected to receive support or incentives from a government entity. Each row represents one development. Data may be unavailable for some projects and details are subject to change until construction is complete. Addresses are excluded for projects with fewer than five homes for privacy reasons.

The dataset includes details on the number of “homes” in a development. We use the word "home" to refer to any single unit of housing regardless of size, type, or whether it is rented or owned. For example, a building with 40 apartments counts as 40 homes, and a single detached house counts as one home.

The dataset includes details about the phase of each project. The process for build a new development is as follows: First, one must receive approval from the city’s Planning Division, which is also known as being “entitled.” Next, one must apply for and receive a permit from the city’s Building Division before beginning construction. Finally, once construction is complete and all city inspections have been passed, the building can be occupied.

The dataset also includes data on the affordability level of each development. To receive a government incentive, a developer is typically required to rent or sell a specified number of homes to households that have an income below limits set by the government and their housing cost must not exceed 30% of their income. The federal government determines income limits based on a standard called “area median income.” The city considers housing affordable if is targeted to households earning at or below 80% of the area median income. For a three-person household in Boise, that equates to an annual income of $60,650 and monthly rent or mortgage of $1,516. See Boise Income Guidelines for more details.Project Address(es) – Includes all addresses that are included as part of the development project.Address – The primary address for the development.Parcel Number(s) – The identification code for all parcels of land included in the development.Acreage – The number of acres for the parcel(s) included in the project.Planning Permit Number – The identification code for all permits the development has received from the Planning Division for the City of Boise. The number and types of permits required vary based on the location and type of development.Date Entitled – The date a development was approved by the City’s Planning Division.Building Permit Number – The identification code for all permits the development has received from the city’s Building Division.Date Building Permit Issued – Building permits are required to begin construction on a development.Date Final Certificate of Occupancy Issued – A certificate of occupancy is the final approval by the city for a development, once construction is complete. Not all developments require a certificate of occupancy.Studio – The number of homes in the development that are classified as a studio. A studio is typically defined as a home in which there is no separate bedroom. A single room serves as both a bedroom and a living room.1-Bedroom – The number of homes in a development that have exactly one bedroom.2-Bedroom – The number of homes in a development that have exactly two bedrooms.3-Bedroom – The number of homes in a development that have exactly three bedrooms.4+ Bedroom – The number of homes in a development that have four or more bedrooms.# of Total Project Units – The total number of homes in the development.# of units toward goals – The number of homes in a development that contribute to either the city’s goal to produce housing affordable at or under 60% of area median income, or the city’s goal to create permanent supportive housing for households experiencing homelessness.Rent at or under 60% AMI - The number of homes in a development that are required to be rented at or below 60% of area median income. See the description of the dataset above for an explanation of area median income or see Boise Income Guidelines for more details. Boise defines a home as “affordable” if it is rented or sold at or below 80% of area median income.Rent 61-80% AMI – The number of homes in a development that are required to be rented at between 61% and 80% of area median income. See the description of the dataset above for an explanation of area median income or see Boise Income Guidelines for more details. Boise defines a home as “affordable” if it is rented or sold at or below 80% of area median income.Rent 81-120% AMI - The number of homes in a development that are required to be rented at between 81% and 120% of area median income. See the description of the dataset above for an explanation of area median income or see Boise Income Guidelines for more details.Own at or under 60% AMI - The number of homes in a development that are required to be sold at or below 60% of area median income. See the description of the dataset above for an explanation of area median income or see Boise Income Guidelines for more details. Boise defines a home as “affordable” if it is rented or sold at or below 80% of area median income.Own 61-80% AMI – The number of homes in a development that are required to be sold at between 61% and 80% of area median income. See the description of the dataset above for an explanation of area median income or see Boise Income Guidelines for more details. Boise defines a home as “affordable” if it is rented or sold at or below 80% of area median income.Own 81-120% AMI - The number of homes in a development that are required to be sold at between 81% and 120% of area median income. See the description of the dataset above for an explanation of area median income or see Boise Income Guidelines for more details.Housing Land Trust – “Yes” if a development receives or is expected to receive this incentive. The Housing Land Trust is a model in which the city owns land that it leases to a developer to build affordable housing.City Investment – “Yes” if the city invests funding or contributes land to an affordable development.Zoning Incentive - The city's zoning code provides incentives for developers to create affordable housing. Incentives may include the ability to build an extra floor or be subject to reduced parking requirements. “Yes” if a development receives or is expected to receive one of these incentives.Project Management - The city provides a developer and their design team a single point of contact who works across city departments to simplify the permitting process, and assists the applicants in understanding the city’s requirements to avoid possible delays. “Yes” if a development receives or is expected to receive this incentive.Low-Income Housing Tax Credit (LIHTC) - A federal tax credit available to some new affordable housing developments. The Idaho Housing and Finance Association is a quasi-governmental agency that administers these federal tax credits. “Yes” if a development receives or is expected to receive this incentive.CCDC Investment - The Capital City Development Corp (CCDC) is a public agency that financially supports some affordable housing development in Urban Renewal Districts. “Yes” if a development receives or is expected to receive this incentive. If “Yes” the field identifies the Urban Renewal District associated with the development.City Goal – The city has set goals to produce housing affordable to households at or below 60% of area median income, and to create permanent supportive housing for households experiencing homelessness. This field identifies whether a development contributes to one of those goals.Project Phase - The process for build a new development is as follows: First, one must receive approval from the city’s Planning Division, which is also known as being “entitled.” Next, one must apply for and receive a permit from the city’s Building Division before beginning construction. Finally, once construction is complete and all city inspections have been passed, the building can be occupied.

Graph and download economic data for Consumer Price Index for All Urban Consumers: Rent of Primary Residence in U.S. City Average (CUUR0000SEHA) from Dec 1914 to Sep 2025 about primary, rent, urban, consumer, CPI, inflation, price index, indexes, price, and USA.

Real Estate Breakeven Analysis for U.S. Home Types

Buy vs Rent Comparison Across Markets

By Zillow Data [source]

About this dataset

This dataset provides a comprehensive analysis of the current real estate situation in the United States. It includes breakeven analysis charts that compare buying vs renting across major U.S. markets. This dataset contains various metrics such as home types, housing stock, price-to-income ratio, cash buyers, mortgage affordability and rental affordability to name a few. This data has been compiled using Zillow's own data along with TransUnion financing survey data and the Freddie Mac Primary Mortgage Market Survey to provide an accurate understanding of each metro area’s market health and purchasing power for buyers and renters alike. By downloading this information you can compare different regions based on size rank and other factors to get full insights regarding their potential fit for your needs or investments strategies as well as any potential risks associated with each region's housing market health

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How to use the dataset

This dataset is for real estate professionals, owner-occupants, potential buyers and renters who are interested in understanding which U.S. markets offer the most favorable home buying or rental opportunities from a financial perspective over the long term.

The “Real Estate Breakeven Analysis for U.S Home Types” dataset contains data pulled from Zillow's current and forecasted housing market metrics across many different real estate regions in the United States including cities, counties, states, metro areas and combined statistical areas (CSAs). The data includes several measures of affordability such as median price-to-rent ratio (MedPR), median breakeven horizon (MedBE) - which refers to how long it takes to make up purchase costs when compared with renting; cash purchaser share; mortgage rate; mortgage affordability indices; rental affordability rates etc.

In order to analyze and compare buying vs renting decisions across various regions in the US this dataset provides breakeven analysis at various levels of geographies i.e., state names, region types (city/metro area/county) and show how long it will take homeowners to break even on their purchase costs when compared with renting in that region over a longer period of time using discounted cash flow methodology. This information helps people understand what type of transaction is a better fit for them by weighing short term vs long term goals accordingly by evaluating these different factors related to housing metrics carefully before making financial decisions about purchasing or renting properties in desired location(s).

To use this dataset one can use either basic filters like RegionType or RegionName or more detailed filter criteria like CountyName, City name , Metro area name , State Name etc . For example if someone wanted to look at properties available for rent only then they can apply filters based on Province Type =‘Rental’ Also one can further refine searches based on filtering them with defined SampleRate , Median Price – To – Rent Ratio …..etc . This could be useful if seekers would want only specific type of property like Condominium/Coop /Multifamily 5+ Units /Duplex Triplex listing etc …and then apply other parameters like Cash Buyers percent , Mortgage Affordability Rate….etc ..in order narrow down search results while looking at Breakeven scores /horizons in their target locations . One should take advantages of all relevant parameters while searching through data before making any decision related with owning rental properties so that they can make sure best possible investment decision given

Research Ideas

• Visualizing changes in real estate trends across regions by comparing price to rent ratios, mortgage affordability indices and cash buyers over time.
• Market segmentation analysis based on region-level market characteristics such as negative equity data, rental affordability, median house values and population size.
• Predicting housing demand within a particular region based on its breakeven horizon or price to rent ratio

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: BreakEven_2017-03.csv | Column name | Description | |:----------------|:----------------------------------------------------...

This dataset presents the Rental Affordability Index (RAI) for all dwellings. The data uses a single median income value for all of Australia (enabling comparisons across regions), and spans the quarters Q1 2011 to Q2 2021. The RAI covers all states with available data, the Northern Territory does not form part of this dataset. National Shelter, Bendigo Bank, The Brotherhood of St Laurence, and SGS Economics and Planning have released the RentalAffordability Index (RAI) on a biannual basis since 2015. Since 2019, the RAI has been released annually. It is generally accepted that if housing costs exceed 30% of a low-income household's gross income, the household is experiencing housing stress (30/40 rule). That is, housing is unaffordable and housing costs consume a disproportionately high amount of household income. The RAI uses the 30 per cent of income rule. Rental affordability is calculated using the following equation, where 'qualifying income' refers to the household income required to pay rent where rent is equal to 30% of income: RAI = (Median income ∕ Qualifying Income) x 100 In the RAI, households who are paying 30% of income on rent have a score of 100, indicating that these households are at the critical threshold for housing stress. A score of 100 or less indicates that households would pay more than 30% of income to access a rental dwelling, meaning they are at risk of experiencing housing stress. For more information on the Rental Affordability Index please refer to SGS Economics and Planning. The RAI is a price index for housing rental markets. It is a clear and concise indicator of rental affordability relative to household incomes, applied to geographic areas across Australia. AURIN has spatially enabled the original data using geometries provided by SGS Economics and Planning. Values of 'NA' in the original data have been set to NULL.

The Location Affordability Index (LAI) estimates the percentage of a family’s income dedicated to the combined cost of housing and transportation in a given location. Because what is “affordable” is different for everyone, users can choose among a diverse set of family profiles—which vary by household income, size, and number of commuters—and see the affordability landscape for each in a given neighborhood, city, or region. The Location Affordability Index (LAI) estimates three dependent variables of transportation behavior (auto ownership, auto use, and transit use) as functions of 14 independent variables (median income, per capita income, average household size, average commuters per household, residential density, gross density, block density, intersection density, transit connectivity, transit frequency of service, transit access shed, employment access, job diversity, and average commute distance). To hone in on the built environment’s influence on transportation costs, the independent household variables (income, household size, and commuters per household) are set at fixed values to control for any variation they might cause. The LAI also estimates two dependent variables of housing costs (Selected Monthly Owner Costs and Gross Rent) as functions of 16 independent variables: regional median selected monthly owner costs and regional median gross rent in addition to the 14 variables used in the transportation model.

To learn more about the Location Affordability Index (v.1.0) visit: https://www.locationaffordability.info/LAPMethods.pdf, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Data Dictionary: DD_Location Affordability Indev v.1.0. Date of Coverage: 2005-2009 https://www.locationaffordability.info/LAPMethodsV2.pdf