Aterio Datasets
US Population Forecast
Granular demographic insights and forecasts for every Zip Code until 2030.
About
Aterio’s Population Dataset is a robust resource that furnishes data regarding the present population, its historical evolution, and forecasts concerning its future dynamics. This dataset is meticulously crafted by merging information from the U.S. Census Bureau and research conducted by Columbia University, NASA, and enhanced through the application of machine learning models to predict population changes while factoring in zip code-specific demographics. This information proves highly valuable to researchers, analysts, and decision-makers seeking to analyze and proactively anticipate shifts in population trends. It offers a dependable and precise means to glean insights into demographic patterns, enabling informed decision-making.
Dataset Components:
- All demographic data from the latest U.S. Census Bureau, NASA and Columbia University research, enhanced with META ( Facebook audience insights) 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 population growth potential.
- Real Estate: Real estate developers and investors can make more informed decisions about property investments by assessing population growth and migration trends in specific zip codes, enabling them to identify areas with potential for higher property values and rental income.
- Location Data Enrichment: A dataset focusing on population forecasts and migration patterns by zip code addresses a fundamental business need for accurate and localized data, empowering businesses and organizations to make strategic choices, allocate resources effectively, and stay ahead of changing market dynamics.
- Healthcare Analytics: Healthcare providers and analysts can utilize our detailed demographic data to enhance service line forecasting and resource allocation. By understanding population dynamics and future trends at a hyper-local level, healthcare organizations can optimize their operations, improve patient outcomes, and strategically plan for future demands.
- Rental Property Management: Rental property owners and managers can leverage our demographic insights to better understand population trends and housing demands. By analyzing data on household units availability, 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 Population Research: Research institutions focusing on demographics and population studies can utilize our comprehensive dataset to conduct in-depth analysis and projections. With access to historical, current, and forecasted population data, researchers can study trends, identify patterns, and publish findings that contribute to the broader understanding of population dynamics and their implications.
Why Choose Aterio?
- Hyper-Local Precision: Dive deep into population trends at the zip code level.
- Monthly Data Refresh: Stay consistently ahead with monthly dataset updates, ensuring you're equipped with the freshest information to guide your decisions.
- Projection: Forecast values until 2030
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_CENSUS_POP_2010 | Population count for Census year 2010 |
TOT_CENSUS_POP_2011 | Population count for Census year 2011 |
TOT_CENSUS_POP_2012 | Population count for Census year 2012 |
TOT_CENSUS_POP_2013 | Population count for Census year 2013 |
TOT_CENSUS_POP_2014 | Population count for Census year 2014 |
TOT_CENSUS_POP_2015 | Population count for Census year 2015 |
TOT_CENSUS_POP_2016 | Population count for Census year 2016 |
TOT_CENSUS_POP_2017 | Population count for Census year 2017 |
TOT_CENSUS_POP_2018 | Population count for Census year 2018 |
TOT_CENSUS_POP_2019 | Population count for Census year 2019 |
TOT_CENSUS_POP_2020 | Population count for Census year 2020 |
TOT_CENSUS_POP_2021 | Population count for Census year 2021 |
TOT_CENSUS_POP_2022 | Population count for Census year 2022 |
TOT_FX_POP_2023 | Forecasted population for the year 2023 |
TOT_FX_POP_2024 | Forecasted population for the year 2024 |
TOT_FX_POP_2025 | Forecasted population for the year 2025 |
TOT_FX_POP_2026 | Forecasted population for the year 2026 |
TOT_FX_POP_2027 | Forecasted population for the year 2027 |
TOT_FX_POP_2028 | Forecasted population for the year 2028 |
TOT_FX_POP_2029 | Forecasted population for the year 2029 |
TOT_FX_POP_2030 | Forecasted population for the year 2030 |
PCT_CHANGE_PRECOVID | Population variation before Covid |
PCT_CHANGE_COVID | Population variation during Covid |
PCT_CHANGE_POSTCOVID | Population variation after Covid |