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New Interactive Data Tools Added to Gig Economy Data Hub

This week, the Gig Economy Data Hub is releasing new interactive data tools that help readers learn more about non-traditional workers in the U.S. These interactive visual elements are based on data from the Bureau of Labor Statistics’ (BLS) 2017 Contingent Worker Supplement, and were created in collaboration with graduate students at Carnegie Mellon University’s Heinz College. These interactive tools add another lens to the analysis of available data sources on independent and gig work in the U.S. on the Data Hub, which was launched in 2018 in partnership with Cornell University’s ILR School.

Visitors to the site now can see the demographic composition of contingent workers in comparison to the total U.S. labor force, and can explore a map showing how the proportion of contingent workers varies by state. Contingent workers are those who do not expect their current job to last, and are one category of workers counted by the Contingent Worker Supplement. The BLS measure of contingent work is one of the best state-level estimates of non-traditional work, but it is important to note that samples from many states are still relatively small, and comparisons between states are imprecise estimates. For more on different definitions of non-traditional and gig workers, see the Data Hub’s discussion of “What is a Gig Worker?”

In addition to the demographic compositions and state-by-state comparisons of contingent work, additional new visualizations allow readers to see the makeup of alternative workersincluding temp-agency, on-call, subcontracted, and independent workersby industry, and to see differences in rates of access to employer-provided health insurance and retirement plans between alternative and traditional workers.

The new data visualization tools reveal that:

  • The gender and racial composition of the contingent workforce reflects that of the overall U.S. workforce. Contingent work is spread across age and education levels, reflecting that a wide range of jobs can be insecure.
  • The greatest share of workers in alternative arrangements are in the construction industry and business services, a diverse category that includes accountants, janitors, and administrative support workers.
  • Workers in alternative arrangements are less likely than traditional workers to receive health insurance and access to retirement plans through an employer.

The accuracy of interactive data tools, like those introduced this week, relies on the quality of the data available. Unfortunately, the data available on non-traditional workers at the state level is limited. More and better data collection promises to further our understanding of today’s workforce, and in turn, enable policymakers to craft more effective policy solutions for the challenges facing non-traditional workers.

We are grateful to the CMU Heinz College students and their faculty advisors for their work on this project. The team was comprised of graduate students Akash Kakkaragolla Manjunath, Xuehan Qiao, Sisi Rao, and Jinyi Yang.

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