Aterio Datasets
US Housing Forecast
Explore housing characteristics and forecast housing inventory through 2030 at a zip code level
About
Aterio's Housing Dataset serves as an extensive repository not only furnishing current housing data but also offering crucial insights into future housing requirements, particularly for 2030, informed by population growth patterns. Emphasizing the differentiation between owner-occupied and renter-occupied residences, alongside an evaluation of vacancy rates, it additionally encompasses rental vacancy rates, facilitating a thorough examination of rental market dynamics. This dataset aids researchers, analysts, and decision-makers, serving as an indispensable resource for making informed decisions within the dynamic real estate and housing sectors. Meticulously curated through the amalgamation of data from the U.S. Census Bureau, research by Columbia University and NASA, Department of Housing and Urban Development records, County Clerk Applications, and refined through the application of machine learning algorithms for prediction, this dataset proves invaluable to stakeholders seeking to analyze and proactively anticipate shifts in housing demand and supply trends.
Dataset Components:
- All housing data from the latest U.S. Census Bureau, research by Columbia University and NASA, Department of Housing and Urban Development records, incorporated county register building permits issuance with monthly updates to keep you informed about evolving trends.
- Enhanced data quality by incorporating additional proprietary data, accounting for various factors contributing to population growth using machine learning methods.
- Metadata mapping linking attribute names to table IDs, zip codes to cities and counties, and Core Based Statistical Areas (CBSAs).
Primary Fields Included:
- Zip Codes
- Aterio Unique ID
- County
- City
- CBSAs
- State
- Latitude/Longitude
Business Needs:
- Market Analysis: Identify attractive investment opportunities by leveraging predictive modeling to pinpoint locations and neighborhoods with high housing demand potential. Estimate the number of housing units needed by 2030 to meet projected population growth and changing demographics.
- Real Estate: Real estate developers and investors can make more informed decisions about property investments by assessing housing availability and estimations in specific zip codes. This data enables them to identify areas with potential for higher property values and rental income based on projected housing needs.
- Location Data Enrichment: A dataset emphasizing the inventory of existing housing units and projections for required housing by zip code addresses a fundamental business need for accurate and localized data. It empowers businesses and organizations to make strategic choices, allocate resources effectively, and stay ahead of changing housing market dynamics.
- Housing and Urban Planning: Government agencies, urban planners, and policymakers can utilize this dataset to forecast housing demands, identify underserved areas, and develop targeted strategies for affordable housing initiatives, infrastructure development, and resource allocation based on projected population growth and housing needs at a granular level.
- Rental Property Management: Rental property owners and managers can leverage housing demand insights to better understand population trends and housing needs. By analyzing data on projected household units, geographical mobility, and income status at the zip code level, they can optimize rental pricing, identify high-demand areas, and improve occupancy rates.
- Demographic and Housing Research: Research institutions focusing on demographics, housing studies, and urban planning can utilize this comprehensive dataset to conduct in-depth analysis and projections. With access to historical, current, and forecasted housing data, researchers can study trends, identify patterns, and publish findings that contribute to the broader understanding of housing dynamics and their implications.
Why Choose Aterio ?
- Precise Projections: Dive into the future with confidence, as our dataset provides granular insights into anticipated housing demand, ensuring you make informed investment decisions.
- Monthly Updates: Stay ahead of the curve with regular dataset updates, keeping your strategies aligned with the latest data.
- Estimation: Plan strategically by estimating housing needs focused on the year 2030, enabling long-term investment planning.
- Comprehensive Coverage: Covering 41,000 US zip codes, our dataset offers nationwide coverage, supporting your investment decisions across diverse markets.
Fields
Column Name | Description |
---|---|
ZIP_CODE | US Zip Code |
CITY_NAME | City name |
COUNTY_NAME | County name |
COUNTY_FIPS_CODE | Federal Information Processing Standards (FIPS) code for counties |
STATE_CODE | State code |
TOT_HOME_AVAILABLE_2020 | Total available homes in 2020 |
TOT_HOME_AVAILABLE_2021 | Total available homes in 2021 |
RT_BUILDING_PERMIT_YOY_2022_2021 | Year-over-year building permit rate for 2021-2022 |
AVG_PEOPLE_PER_HOME | Average number of people per home |
EST_TOTAL_HOME_DEMAND_2030 | Estimated demand for homes in 2030 |
TOT_BALANCE_INVENTORY | Total balance of available homes in inventory |
TOT_FX_CONSTRUCTION_5Y | Forecasted construction of homes over the next 5 years |
TOT_HOUSING_UNIT | Total housing units in the latest year |
TOT_OWNER_OCCUPIED_HOUSING_UNIT | Total owner-occupied housing units |
TOT_RENTER_OCCUPIED_HOUSING_UNIT | Total renter-occupied housing units |
RT_VACANCY | Rate of vacant housing units |
RT_VACANCY_RENTAL | Rate of vacant rental housing units |
LBL_LATEST_HOUSING_YEAR_DATA | Latest available housing data |
IDX_DEMAND_SUPPLY | Index evaluating demand and supply factors |