Updated Apr 27, 2019

The gig economy is distorting U.S. economic data

Illustration: Aïda Amer/Axios

Online shopping and the gig economy haven't just disrupted traditional brick-and-mortar business, they're disrupting the way U.S. job growth, wage data and inflation are tracked, asserts a new paper from the Dallas Federal Reserve.

What it means: There has been an increase in the number of workers in the gig economy who are either working as contractors or are self-employed, but report themselves as employed. These workers often have less bargaining power and lower wages than full-time employees.

Details: "Essentially, firms are able to hire contract or self-employed workers, who are not on their payrolls and not counted among the unemployed when not on the job," John V. Duca, a vice president in the research department at the Dallas Fed, says in the report. "As a result, the headline measure of unemployment may understate labor slack."

  • In essence, unemployment should be higher than it is because most gig economy workers should be counted as unemployed or underemployed, according to traditional metrics, but aren't. They also make less money, pushing down wage numbers. That is leading to unusually low readings in the data.

The big picture: Economists have long argued about just how much impact the gig economy has had on the persistently low wages in the U.S. and the change in the relationship between unemployment and inflation. Typically as unemployment falls, inflation rises, but that trend has been undermined in recent years, leading many to question the long-held economic principle of the Phillips Curve.

  • Last year, Anat Bracha and Mary A. Burke, senior research economists at the Boston Fed, found recent year-over-year wage growth had fallen short of predicted values by 0.5–1 percentage point.
  • They concluded that the gig economy had "an economically significant" impact on those lower wages.

Yes, but: "These shopping and employment behavior changes are still new enough that the data are insufficient for full statistical analysis," Duca says in the Dallas Fed report.

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