Owned Away From Home

An analysis by   Regrid   using our  nationwide parcel data  as of 2023 finds that 1 in 4 U.S. homes are owned outside their local area:

• 5% of US housing stock is owned in a state other than the home itself
• 19.5% is owned in a different zip code within the same state

Our analysis, based on property addresses, ownership details, US Postal Service data, and property tax bill mailing information, highlights the significant presence of non-local homeownership in the U.S. The research creates new opportunities and questions for understanding the implications of where housing ownership sits.

One thing I have learned in more than a decade split between working with nationwide parcel data here at  Regrid  and designing housing programs in Detroit is that where ownership of housing sits matters. It is a factor that influences local governance, investment, and economy as well as the social fabric of communities.

Using Regrid data on street addresses, land use classifications, property tax bill mailing addresses, and more, we were able to evaluate where ownership sits for  85% of US housing  -- approximately 95 million residential properties (per situs address) representing ~110M housing units.

There are many ways to approach the topic of ownership of the country's housing supply. What we are particularly interested in are homes for which ownership sits at some distance from the property itself.

The two categories we have defined are:

1. Housing that is owned by an entity out of state
2. Housing owned by an entity in the same state, but in a different zip code

By "entity" we do not mean any particular kind of owner -- these owners could be individuals, local landlords, large scale institutional investors, nonprofits, etc. Though it is an obvious next step for investigation, we are not trying to differentiate ownership by type of owner in this research.

Additionally, this analysis includes a variety of housing types without distinguishing their use, such as multifamily rentals vs. beachfront second homes. Differentiating housing categories by use and owner type is worth exploring in future research.

Our analysis relies on Regrid's property tax bill mailing addresses to identify ownership locations, covering 93% of nationwide parcels. However, this method isn't without its limitations. Out-of-state tax bills suggest non-local ownership, but some owners may use in-state law firms or management offices for their mailing addresses, potentially underrepresenting true out-of-state ownership. Our estimates may lean conservative.

What we aim to do is provide an accessible, nationwide, picture of the extent to which American homes are owned at some distance from homes themselves.

This report will:

• Provide interactive, nationwide, census tract level data as of 2023 showing the share of homes owned out of state, or, in the same state but in a different zip code.

• Discuss the relative scale of out of state ownership vs. in-state, out of zip code ownership of housing, while exploring several examples.

• Present the relationship between census tract level household income and ownership of housing.

• Conclude with some questions for continued research and background on methodology.

On that last point, we very much invite ideas and questions on where people would like to see this research go next. Please feel free to reach out to directly with ideas and questions -- purpose@regrid.com -- and if you are an academic or nonprofit interested in working with this data yourself (or other parcel data from Regrid), we invite you to check out  Regrid's Data With Purpose  program through which we license data to academics and nonprofits on a "propose your own budget" basis.

Explore the housing ownership data nationwide in the map below. We'll zoom in on several examples.

(Note: In the lower left hand corner of each map is an expandable legend. Click the magnifying glass in the upper left to search for an address or place. If you want a fullscreen map, click the expand icon in the upper right corner of the map. You can also click and drag the map to move around, and use the + / - at lower right to zoom in / out.)

Looking at income alongside where an area's housing is owned is also revealing. By combining 2022 ACS data on median household income by census tract with the Regrid data on ownership of housing stock we can look at the rates of out of state and out of zip code ownership by household income level:

The chart above tells us that, on average, 42% of the housing stock in census tracts with the lowest household incomes is owned in a different zip code or state -- a rate 2.5x higher than census tracts in the top 10% of tracts by household income.

The relationship between household income and ownership of housing stock is clear, if not surprising: as income declines, ownership of housing stock moves farther away from home.

In order to see the relationship between ownership of housing and household income nationally, we've developed a simple index that scores each census tract in this analysis on a 0-2 scale:

• A 0-1 score for the combined percentage of housing owned out of state and out of zip code (the percentage equals the index score)
• A 0.1 - 1 score for the decile into which the tract's median household income (per 2022 ACS data) falls. For household income, the top 10% of median household income has a score of 0.1, while the bottom 10% of income has a score of 1.

The Income & Ownership Index scale ranges from 0.1 (highest income, lowest percent of housing owned out of state or in a different zip code) to 2 (lowest income, highest percent of housing owned out of state or in a different zip code). You can explore the data nationwide in the map below.

A substantial portion of U.S. homes are owned beyond their immediate localities. Drawing upon  Regrid's  expansive land parcel data, we've identified that one in every four homes in the country is owned either out-of-state or in a different zip code within the same state. Further, we've demonstrated the -- perhaps not surprising, but certainly dramatic -- relationship between income and local control of housing.

We hope this is a foundation for deeper exploration into the dynamics that shape communities, governance, investment, and the very social fabric of the country.

There are many questions for further study that this work has raised for us. Some of them are outlined below:

• We have looked at where ownership sits, but what is the distribution of different owner typologies behind housing owned at a distance?

• What is the breakdown in the uses of these homes? How many are vacation homes, multifamily rental properties, single family rentals, etc.

• How has the share of housing owned out of state or out of zip code changed over time? Has it accelerated since the pandemic? Or is the phenomenon of ownership slowly returning to local control, as seen in Detroit since 2020, one found more widely as well?

• To what extent are out of state and / or out of zip code ownership manifestations of other issues or factors in a particular state's or area's housing market? (For instance, the apparent relationship between low out of state ownership in California and Prop 13.)

• What can we learn about the distribution of property types to which property tax bills for residential properties are mailed?

• Within the Income and Ownership Index, what does it look like to remove owner occupied homes from the Index -- does it reveal segmentation within high income census tracts as well?

Purpose: To provide an extensive analysis of residential properties owned by individuals living outside the state or outside the zip code of the property using Regrid's nationwide parcel data. Utilizing a comprehensive nationwide dataset from Regrid, properties were evaluated based on tax bill mailing addresses, which serve as proxies for the location of ownership.

Data Vintage: The median parcel data vintage, at the county level nationwide, for the data used in the analysis was September 2023.

Data Coverage & Data Dictionary:  Regrid's nationwide Coverage Report  includes county level parcel data refresh information and percent-coverage of all data fields. Find  Regrid's Data Dictionary here .

• mail_state2: State where the tax bill is mailed, indicative of the owner's address.
• mail_zip: Zip code where the tax bill is mailed, indicative of the owner's address.
• state2: State where the property is located.
• szip: Zip code where the property is located.
• census_tract: Geographic region defined for the purpose of taking a census.
• ll_bldg_count: The number of buildings located on the property.
• ll_address_count: A count of all the addresses we know of existing on a parcel. This includes the primary situs address and all the secondary or unit based addresses in our matched secondary address dataset.
• rdi: Residential Delivery Indicator by the US Postal Service, marking whether the location is residential (Y) or not (N).

• State Abbreviations: Mapped full state names to their respective abbreviations to ensure uniformity.
• Zip Codes: Standardized to the first 5 digits and added leading zeros where necessary for consistency.

• Data Filtering: Included only properties marked as residential (rdi == 'Y') with at least one building on the parcel.
• Ownership Calculation: Grouped data by census tract and calculated rates of out-of-state ownership and out-of-zip code ownership.

• Rates were calculated as a percentage of total homes within each census tract that were owned by individuals either out-of-state or outside the local zip code.

The Income and Ownership Index (IOI) is a composite measure designed to capture and quantify the relationship between median household income levels and the prevalence of out-of-state and out-of-zip-code residential property ownership at the census tract level across the United States. This index integrates 2022 ACS census tract-level median household income data with the combined proportion of residential properties owned by out-of-state or out-of-zip-code entities.

The IOI utilizes two primary data sources:

1. Median Household Income Data: Sourced from the 2022 U.S. Census Bureau's American Community Survey (ACS) at the census tract level.
2. Out-of-State and Out-of-Zip-Code Residential Property Ownership Data: Derived from  Regrid's  parcel data records, the index includes the total percentage of residential properties within each census tract that have out-of-state or out-of-zip-code mailing addresses for their property tax bills, indicating ownership by non-local entities.

The methodology involves several preparatory and normalization steps for each dataset:

• Income Percentile Ranges: Census tract-level median income data were classified into deciles, with each representing a specific income percentile range (e.g., Bottom 10%, 11-20%, up to Top 90-100%). Each range was assigned a numerical score inversely proportional to the income level, ranging from 1 (Bottom 10%) to 0.1 (Top 90-100%).
• Out-of-State Ownership Percentages: The proportion of out-of-state owned residential properties was already in a percentage format (0% to 100%) and was directly used in the index calculation.

• Missing Tax Bill Mailing Address Data: Regrid's coverage of tax bill mailing address data includes 93% of our nationwide parcels. Records for which we do not have tax bill mailing address data were excluded from this analysis.
• International Ownership Not Reflected in Analysis: Although international ownership of US property can be difficult to discern from assessment data, it is sometimes the case that tax bill mailing address data includes addresses outside the US. Only US states and territories were included in this analysis.
• Housing Unit Count: The data used to estimate the nationwide housing unit count represented by the number of residential situs addresses captured in the analysis has certain limitations. The field is a count of the number of addresses associated with a given parcel, but does not differentiate commercial vs. residential use. The primary use of the situs address is residential, but that does not preclude the presence of some commercial addresses as well (such as mixed use commercial / residential property). Additionally, in our experience using the data, 2-4 unit subdivided single family homes are sometimes not captured in the address count.