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The Independent Contractor Workforce: New Evidence On Its Size and Composition and Ways to Improve Its Measurement in Household Surveys

Author

Listed:
  • Katharine G. Abraham
  • Brad Hershbein
  • Susan N. Houseman
  • Beth Truesdale

Abstract

Good data on the size and composition of the independent contractor workforce are elusive, with household survey and administrative tax data often disagreeing on levels and trends. We carried out a series of focus groups to learn how self-employed independent contractors speak about their work. Based on these findings, we designed and fielded a large-scale telephone survey to elicit more accurate and complete information on independent contractors, including those who may be coded incorrectly as employees in conventional household survey data and those who are independent contractors in a secondary work activity. We find that, upon probing, roughly one in 10 workers who initially reports working for an employer on one or more jobs (and thus is coded as an employee) is in fact an independent contractor on at least one of those jobs. Incorporating these miscoded workers into estimates of work arrangement on the main job nearly doubles the share who are independent contractors, to about 15 percent of all workers. Young workers, less-educated workers, workers of color, multiple-job holders, and those with low hours are more likely to be miscoded. Taking these workers into account substantively changes the demographic profile of the independent contractor workforce. Our research indicates that probing in household surveys to clarify a worker’s employment arrangement and identify all low-hours work is critical for accurately measuring independent contractor work.

Suggested Citation

  • Katharine G. Abraham & Brad Hershbein & Susan N. Houseman & Beth Truesdale, 2023. "The Independent Contractor Workforce: New Evidence On Its Size and Composition and Ways to Improve Its Measurement in Household Surveys," NBER Working Papers 30997, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:30997
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    Cited by:

    1. Christopher J. O’Leary & Kenneth J. Kline & Thomas A. Stengle & Stephen A. Wandner, 2024. "Why Are Unemployment Insurance Claims So Low?," Economic Development Quarterly, , vol. 38(3), pages 164-182, August.
    2. Rachel Marie Brooks Atkins & Quentin Brummet & Katie Johnson, 2025. "Understanding the Online Platform Based “Gig” Workforce in the US: Evidence from the Entrepreneurship in the Population Survey," NBER Chapters, in: The Changing Nature of Work, National Bureau of Economic Research, Inc.
    3. Jason B. Cook & Chloe N. East, 2023. "The Effect of Means-Tested Transfers on Work: Evidence from Quasi-Randomly Assigned SNAP Caseworkers," NBER Working Papers 31307, National Bureau of Economic Research, Inc.

    More about this item

    JEL classification:

    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • J41 - Labor and Demographic Economics - - Particular Labor Markets - - - Labor Contracts
    • J46 - Labor and Demographic Economics - - Particular Labor Markets - - - Informal Labor Market
    • L24 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Contracting Out; Joint Ventures
    • M55 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - Labor Contracting Devices

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