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Geography in IRS 990 Data

Knowing how mySidewalk assigns nonprofit organizations to geographies can help you know how best to use the IRS 990 data.

In mySidewalk, IRS 990 nonprofit tax data is summarized by geography. This makes it easy for users to compare nonprofit activities in their communities, and to see how it relates to data from other sources.

Geographies Available

Nonprofit data are available at the

  • Tract,
  • Zip,
  • Unified School District,
  • State Senate District,
  • State House District,
  • Place,
  • County Subdivision,
  • County,
  • MPO,
  • Congressional District,
  • CBSA
  • State, and
  • Nation geographies.

How mySidewalk builds IRS 990 data

There are some peculiarities in how this works that benefit from explanation.

When mySidewalk retrieves data from the IRS, the EO BMF data table contains address data for every nonprofit organization in the nation.

How We Clean Address Information

Address data is self-reported by the nonprofits themselves, and is not always machine readable or easily translatable to a point location. To the extent possible, mySidewalk cleans the address data so that each address is formatted similarly (e.g. 123 Main Street, Townsville, MO 63038).

This cleaned address data is geocoded, which involves assigning each address an XY-coordinate, which can then be mapped.

There are limitations to the capabilities of geocoding software:

  • PO Boxes, RR Boxes, and other similar non-address data cannot be geocoded.
    • Organizations whose listed address is a PO Box or RR Box are still captured at the place, zip code, state, and nation geographic levels.
    • Sometimes, PO Boxes belong to Zip Codes which represent a single post office location.
      • Zip Codes are merely postal delivery routes, while their “shape” equivalents – Zip Code Tabulation Areas (ZCTAs) – may or may not correspond to these routes 1:1.
      • Single-location Zip Codes do not typically correspond to a ZCTA. Learn more about this here.
      • To accurately locate nonprofits with Zip Codes that don't correspond to a ZCTA, we use a crosswalk table from the Health Resources and Services Administration (HRSA).
  • Some addresses can only be geocoded to the accuracy of their home city. This data is only counted for the place, state, and nation geographies in mySidewalk.
  • Nonprofits with invalid addresses are only counted for the nation geography.

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Given these limitations, counts between different geographies may not match.

  • For example, adding the number of nonprofits in all counties in a state will likely produce a different total than the number reported at the state level.

Once nonprofit addresses have been geocoded, they are summarized for each geography by counting, summing, or averaging the data values that fall within each shape.

  • For example, to get values for the city of Alpharetta, Georgia, all nonprofit organizations whose geocoded XY-coordinates fall within the boundaries of that city are summarized.

What geographic data means

mySidewalk’s 990 data summarizes nonprofit financial activity data by geography. It is important for users to understand that this data only summarizes data provided by organizations within each geography.

This can be especially tricky when referencing revenue and expense data.

Revenue and expense data refers to the revenue and expenses of nonprofit organizations within a given geographic area. It explicitly doesn't refer to the origin or destination of those revenues and expenses.

If we know that Nonprofit A raised $100 and spent $50 last tax year, that data is reported in the geography of Nonprofit A’s listed address. It isn't known – and not reported or implied by mySidewalk’s data – where the $100 came from, or where the $50 was spent, geographically speaking.

Many nonprofit organizations work directly and exclusively in their communities. These communities vary in size. Nonprofits may operate fully within their own neighborhoods, or they may be statewide or regional in nature. Some nonprofits have national scopes.

How and how not to describe this data

Yes: “nonprofit organizations in my community had $x revenue and $y expenses.”

No: “nonprofit organizations in my community raised $x revenue from local sources"

No: “nonprofits in my community spent $y in my community.”