Data in action: a breakthrough in estimating nonprofit employment
Earlier this year, the federal Office of Management and Budget released a memorandum calling upon agencies to use existing, non-public administrative data sources more effectively for statistical purposes.
The Bureau of Labor Statistics (BLS) got the message.
BLS recently announced the release of a new research dataset that will allow for more precise estimates of nonprofit employment and wages than had previously been possible.
What do the data tell us? Here are a few summary results:
- In the United States, there are 11,426,870 nonprofit employees earning $532 billion in wages—around 10 percent of the total private workforce.
- There are 267,855 workplaces across 152,585 organizations.
- Healthcare and social assistance organizations employ 68 percent of nonprofit workers.
- Nonprofit employment grew steadily through the Great Recession, even while overall employment dropped and has still not fully recovered to pre-recession levels.
- The share of jobs in the nonprofit sector is highest in Washington, DC (26.6 percent) and the Northeast, while it is singularly low in Nevada (2.7 percent).
Where do the data come from?
The data build upon groundbreaking work by Lester Salamon and Wojciech Sokolowski. More specifically, the data use the Quarterly Census of Employment and Wages, a robust compendium of unemployment insurance filings collected from each state’s workforce agency. Those filings are a key part of the unemployment insurance system and are submitted by nearly every employer operating in the United States. Cinthia Schuman Ottinger with the Aspen Institute’s Nonprofit Data Project played a vital role in bringing together stakeholders, including the Urban Institute, to work with BLS on developing and testing the best ways to use QCEW data.
Ultimately, BLS worked with these data to isolate the nonprofit filers through a two-step process, matching entities to the Exempt Organization Business Master File and supplementing it by counting “reimbursable” establishments that usually constitute charitable 501(c)(3) organizations. The result: for the first time, something close to a full census of 501(c)(3) universe activity, broken down by industry and geographically.
Why do these data matter?
As nonprofit researchers, my colleagues and I could not be more thrilled. Perhaps the greatest challenge to nonprofit sector analysis is the lack of available, empirical data. We will be able to incorporate these data into our employment estimates in The Nonprofit Almanac, and they should help those estimates become more detailed, timely and granular than were previously possible. Not to mention, the possibilities for data visualizations and interactive maps are intriguing.
Of course, the data are not just useful to those of us who study the nonprofit sector and get excited about interactive maps. Policymakers and administrators responsible for crafting regulations and tax changes affecting nonprofits have a responsibility to understand how policy changes will impact an industry employing nearly as many people as the manufacturing sector, and roughly twice as many as the construction and finance sectors.
While this resource represents an enormous step forward in our ability to understand the full scope of the nonprofit sector, it remains only a one-time release of BLS—for the time being. Development of a regularly-updated data series is possible, but only if interest is sufficient to justify the use of scarce agency resources. BLS has requested feedback on the methodology and the data themselves, and those interested can submit a comment on the BLS website by December 31.
But even in its current form, BLS has provided a great example of why it is so important not just to collect more and better data, but to use the data collected in innovative and collaborative ways.
Photo: An animal rescue nonprofit in New York City. By a katz/Shutterstock.