About This Dataset
Discover the number of owner occupied housing units in the United States compared to the number of renter occupied housing units over time.Â
This data ranges from 1975 through 2022 and displays the number of rented homes, owned homes, and the percentage of rented and owned homes. FourFront’s analytics team collected and blended this data using the US Department of Housing and Urban Development’s data via Statista’s Number of Owner Occupied Housing Units and Number of Renter Occupied Housing Units data.Â
See also:
Sample Data 
Scroll table horizontally to view more
| # | Year | Rented (In millions) | Owned (In millions) | Total | % of rented | %of owned |
|---|---|---|---|---|---|---|
| 1 | 2017 | 43.28 | 77.66 | 120.94 | 36% | 64% |
| 2 | 2018 | 43.11 | 79.36 | 122.47 | 35% | 65% |
| 3 | 2019 | 43.28 | 80.68 | 123.96 | 35% | 65% |
| 4 | 2020 | 43 | 82.81 | 125.81 | 34% | 66% |
| 5 | 2021 | 44.02 | 83.58 | 127.60 | 34% | 66% |
| 6 | 2022 | 44.17 | 85.22 | 129.39 | 34% | 66% |
Date Created: October 2023
Date Modified: October 2023
Price: Free
File Format: XLS
(CSV or JSON available upon request)
Who Is This Data For?
This dataset may be useful to anyone interested in evaluating housing trends overtime, such as those working in housing policy, the building industry, or finance. The trends could also be helpful to audiences interested in planning for home ownership for themselves or their loved ones.Â
The suggested use cases for this dataset include:
- Urban planners can use this dataset to analyze trends and properly allocate resources
- Banks and mortgage companies can analyze the market and tailor their products and services based off the preference of renting or buying
- Educators can use this data as an academic tool exploring historical trends of the housing market
Enrichment Options
We utilize state-of-the-art AI and machine learning to enrich datasets further and provide predictive analytics for your important KPIs. Get in touch to learn more.
Enrichment opportunities for this dataset include:
- Apply predictive analytics to forecast future trends, identify patterns and potential shifts in the housing market.
- Blend data with other data sources for additional insights
- Subscribe to a regularly updated data feed / Create a custom API
- Request related data unique to your needs
Data Enrichment
We can provide additional services such as blending this data with your internal data, applying predictive analytics, and more. Get in touch to learn more.
Additional Questions?
If you have additional questions, or have a specific request for this dataset, contact our team at FourFront.
Date Created: October 2023
Date Modified: October 2023
Available Formats: CSV, XLS, JSON
Price: Free
Sample Data
Scroll table horizontally to view more
| # | Year | Rented (In millions) | Owned (In millions) | Total | % of rented | %of owned |
|---|---|---|---|---|---|---|
| 1 | 2017 | 43.28 | 77.66 | 120.94 | 36% | 64% |
| 2 | 2018 | 43.11 | 79.36 | 122.47 | 35% | 65% |
| 3 | 2019 | 43.28 | 80.68 | 123.96 | 35% | 65% |
| 4 | 2020 | 43 | 82.81 | 125.81 | 34% | 66% |
| 5 | 2021 | 44.02 | 83.58 | 127.60 | 34% | 66% |
| 6 | 2022 | 44.17 | 85.22 | 129.39 | 34% | 66% |
Who Is This Data For?
This dataset may be useful to anyone interested in evaluating housing trends overtime, such as those working in housing policy, the building industry, or finance. The trends could also be helpful to audiences interested in planning for home ownership for themselves or their loved ones.Â
The suggested use cases for this dataset include:
- Urban planners can use this dataset to analyze trends and properly allocate resources
- Banks and mortgage companies can analyze the market and tailor their products and services based off the preference of renting or buying
- Educators can use this data as an academic tool exploring historical trends of the housing market
Enrichment Options
We utilize state-of-the-are AI and machine learning to enrich the datasets further and provide predictive analytics for your important KPIs. Get in touch to learn more.
Enrichment opportunities for this dataset include:
- Apply predictive analytics to forecast future trends, identify patterns and potential shifts in the housing market.
- Blend data with other data sources for additional insights
- Subscribe to a regularly updated data feed / Create a custom API
- Request related data unique to your needs
Data Enrichment
We can provide additional services such as blending this data with your internal data, applying predictive analytics, and more. Get in touch to learn more.
Additional Questions?
If you have additional questions, or have a specific request for this dataset, contact our team at FourFront.