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Types of Data

Studies included in the Data Hub use two types of quantitative data to measure gig work: self-reported and administrative data. Self-reported data consists of survey or interview responses from workers. Administrative data consists of records originally recorded for non-research purposes, like tax, payroll, or bank account information. Either type of data may be collected by public agencies, such as the Bureau of Labor Statistics, non-profit organizations, academic researchers, or private companies. In addition, there are some qualitative examinations of non-traditional work, drawing on interviews and observations.

Each type of data has pros and cons, and is suited to particular types of questions. Administrative data tends to be thorough in its sampling, but limited in the scope of information it can provide. Self-reported data tends to be more targeted in the information it provides, but requires careful sampling to ensure that it is generalizable, and relies on respondents’ interpretation of questions, which may or may not match researchers’ interpretations.

  Self-reported Administrative
Public
  • Tax forms issued (1099s versus W2s issued)
  • Taxes filed (Schedules C and SE)
  • Nonemployer statistics
Private
  • Bank account records (JPMorgan Chase Institute)
  • Private administrative data (like records of Uber drivers analyzed by Hall and Krueger)

The Data Hub brings together all of these types of data to establish as comprehensive an understanding of the gig economy as possible. Some studies contain original data collected by the authors, while others analyze publicly available data sets. For more information on what research is included and prioritized in the Data Hub, see our Criteria for Study Inclusion.