Taking Note: Measuring the Gig Economy through a New Data Source

By Sunil Iyengar and Bonnie Nichols, NEA Office of Research & Analysis
Computer code that says "Freelance is the new employed"

Freelance by flickr user Marco Raaphorst

There may be no higher tribute to the role of working artists in the public imagination than a term that has awakened the interest of labor analysts over the last few years: gig economy. The description is no longer limited to itinerant entertainers; it includes a reportedly growing segment of the labor force employed through temporary, freelance arrangements. Uber-driving, no less than jazz musicianship, has become a popular example.

Inadequate data about gig workers have not prevented journalists from scrutinizing the phenomenon. Just last month, a Wall Street Journal article maintained that the gig economy is slowing, while an earlier piece in the Christian Science Monitor critiqued some commonplaces about gig workers—the perception, for instance, that they are predominantly young adults, or that their totals are rising.

Together, these articles draw from various statistical sources: a McKinsey Global Institute survey of 8,000 workers across the U.S. and Europe; a JPMorgan Chase & Co. Institute report on online platforms for labor and capital; and The Rise and Nature of Alternative Work Arrangements in the United States: 1995-2015, a report by economists Lawrence Katz and Alan Krueger for the National Bureau of Economic Research (NBER).

The JPMorgan Chase & Co. Institute used data from a survey of 240,000 people who earned income through online platforms over a roughly four-year period. The NBER report relied on the RAND Institute’s American Life Panel, targeting over 6,000 U.S. workers. But to generate long-term trend data, Katz and Krueger needed to make their questionnaire comparable to the U.S. Bureau of Labor Statistics’ (BLS) Contingent Worker Supplement to the Census Bureau’s Current Population Survey. The BLS supplement has not been conducted since 2005.

Therein lies the problem—and the solution. The BLS survey is the most reliable and representative source of data about contingent (or “gig”) workers, and yet since 2005 it has not been fielded with regularity. But that may change. BLS plans to conduct the survey in 2017, with the questionnaire largely to mirror the 2005 version, though there will be additional questions about these workers’ participation in the digital marketplace.

By virtue of being tied to the Census Bureau’s Current Population Survey, the BLS supplement will permit more reliable trend analysis of the size of the contingent workforce than can be enabled by other data sources. In addition, it will “measure workers’ satisfaction with their current arrangement; and measure earnings, health insurance coverage, and eligibility for employer-provided retirement plans,” according to BLS Commissioner Erica Groshen. After 2017, BLS proposes to begin conducting the Contingent Worker Supplement on a biennial basis.

In the absence of interim data from BLS, the Government Accountability Office (GAO) synthesized information from diverse sources to produce a 2015 report titled Contingent Workforce: Size, Characteristics, Earnings, and Benefits. The findings are far from uniform: depending on one’s definition, GAO estimates contingent workers make up anywhere from 5 percent to more than one-third of the U.S. workforce.

One attempt to characterize the gig economy via frequently recurring data sources is to use the American Community Survey (ACS). Data from the 2010-2014 ACS show that one-third of all artists are self-employed. Moreover, of the 11 specific artist occupations identified by the NEA, five report self-employment rates of at least 40 percent. For example, more than half of all visual artists (e.g., fine artists, art directors, and animators) and photographers are self-employed, as are 40 percent of writers and authors.

To appreciate the sheer number of self-employed workers among U.S. artists, consider that only 9 percent of the nation’s workers are self-employed.

The GAO reports that contingent work leads to lower earnings and fewer benefits. Is this true of self-employed artists? ACS data say yes. From 2010-2014, self-employed artists (working full-year/full-time) earned an annual median income of just under $42,000, about $14,000 less on average than earned by full-year/full-time artists on payroll.

Similarly, while 87 percent of artists on payrolls have health insurance coverage, the share of self-employed artists with coverage is 79 percent. (A recent report titled Creativity Connects: Trends and Conditions Affecting U.S. Artists finds insufficient protections for artists in general—citing a lack of healthcare insurance and other benefits less commonly available to contingent workers. The report was produced by the Center for Cultural Innovation in partnership with the NEA.)

And what about artists who are not necessarily self-employed, but who nonetheless flit from job to job? The 2005 data from the BLS’ Contingent Worker Supplement (CWS) showed that dancers and actors are the main gig-working artists. At that time, 64 percent of dancers said they expected their job to last a year or less; nearly 23 percent of actors reported that kind of temporary work.

Perhaps a bigger question is whether artists purposely choose contingent work arrangements over payroll jobs. Among self-employed artists, for example, the 2005 CWS showed that 66 percent of self-employed artists enjoyed the independence and flexibility that self-employment provides. Even so, roughly 20 percent of producers and directors, musicians, and writers and authors said they were self-employed because of the nature of their work.

Once the new CWS data are available (in early 2018), the NEA’s Office of Research & Analysis intends to use it to profile the artist share of the contingent workforce. The CWS thus will contribute to the NEA research office’s ongoing efforts to improve and validate federal statistics about artists. In 2017, the office will produce an omnibus research report on artists, which will use several different data sources, including the ACS and, for the first time, the U.S. Census Bureau’s Longitudinal Employer-Household Dynamics dataset. Even if this report will not be able to speak for gig economy trends in general, it will provide detailed characteristics about a critical component of that economy—U.S. artists.