The Ups and Downs of the Gig Economy, 2015–2017
The term “gig economy” refers to many forms of nonstandard work arrangements—typically nonpayroll-based and of short duration—including driving for Uber or Lyft as well as babysitting or house sitting and numerous other jobs. While work in the gig economy offers flexible hours and independence, such employment typically lacks the benefits that accompany payroll-based work such as subsidized health insurance, paid vacation, and employer-matched contributions to a 401(k) retirement account. Several economic studies using survey and/or administrative data have found that alternative work arrangements have increased in prevalence in recent decades or at least since the onset of the Great Recession. In contrast, a recent Bureau of Labor Statistics (BLS 2018) report finds no significant increase in the prevalence of alternative work arrangements between 2005 and 2017. In addition to the debate over long-term trends in alternative work arrangements, it is not yet clear how recent improvements in the formal labor market affected participation in the gig economy. Using the Survey of Informal Work Participation that is conducted each December as part of the Survey of Consumer Expectations, this paper assesses changes in informal work activity across 2015, 2016, and 2017 to investigate whether participation in the gig economy increased or decreased as the unemployment rate fell and other labor market indicators also improved. Fluctuations in the prevalence of informal “gig” work may hold implications for worker well-being, for the conduct of monetary policy, and for the measurement of employment.
- Broadly speaking, we find that the participation rate in informal work was roughly flat between 2015 and 2017. However, among participants the average hours per month spent engaging in informal work declined over the same time period. Also, the aggregate amount of informal work performed in the economy, measured in terms of full-time equivalents or FTEs, also declined between 2015 and 2017.
- Within our baseline survey sample, which includes both non-retirees and retirees, the estimated share of household heads who performed any type of paid informal work was 31.5 percent in 2015 and 28.4 percent in 2017, although the apparent decline was not statistically significant.
- Among informal work participants in the baseline sample, the average number of hours per month spent engaging in informal work declined by a statistically significant margin, from 22.1 hours in 2015 to 16.4 hours in 2017. This latter decline is also reflected in the aggregate amount of informal work in the economy, calculated as the number of full-time job equivalents (FTEs) of informal work as a percent of household heads. In both the baseline sample and the non-retiree sample our FTE estimates declined by economically significant margins between 2015 and 2017, but we cannot readily determine the statistical significance of those declines.
- Considering average monthly income from informal work among participants in the baseline sample, the estimated income declined from $475 in 2015 to $368 in 2017, but the margins of error are too large to clearly distinguish those estimates from each other.
- On net between 2015 and 2017, only three activities, all for selected technology-enabled tasks, showed an increase in average monthly hours among participants: renting and selling, online activities, and ridesharing, the latter quadrupling from 7.3 hours in 2015 to 34.6 hours in 2017.
- Regression analysis reveals that, at the level of the census division, informal work hours and participation are each positively related to the unemployment rate. This result is consistent with the hypothesis that gig economy activity, especially in terms of average hours, will decline when conditions improve in the formal labor market.
- Focusing on the non-retiree household heads and the broad U-6 measure of unemployment, a 1 percentage point decline in the unemployment rate is associated with a decline of 11.6 hours spent in informal work activity per month. This means that the decline in the national U-6 unemployment rate between 2015 and 2016 can explain about 65 percent of the observed decline in average informal work hours among non-retired gig workers during that time period.
- In each survey year, among those who engaged in labor-intensive gig work, at least 39 percent or more of the respondents indicated that the decision was motivated by experiencing adverse circumstances such as job loss or stagnant wages. At least 40 percent answered that gig economy work helped offset economic hardships either “somewhat” or “very much.” At least 60 percent said that earning extra income was a reason why they chose to undertake informal work activity.
The analysis suggests that informal work activity—particularly in terms of hours per month—behaves countercyclically in the sense that such activity declines as labor market indicators (such as the unemployment rate) improve. While additional survey responses suggest that this relationship may be causal—for example people may reduce their informal hours because they gain preferred employment opportunities in the formal sector—we cannot definitively prove such a causal link. Fluctuations in the prevalence of informal work have potential implications for the measurement of employment, a consideration that informs US monetary policy. Gaining a better understanding of how the gig economy functions in the United States has potentially important welfare implications for individuals, as workers in such arrangements may be more vulnerable when economic conditions deteriorate.
A variety of researchers and public entities have estimated the prevalence of nontraditional work arrangements—using diverse definitions—in recent decades, and the topic has received increasing attention in the past five years. Despite numerous media reports that the prevalence of nonstandard work has increased since the Great Recession, not all sources agree on this point, and very little evidence exists relating to hours or earnings from such arrangements and their changes over time. Using unique data from the Survey of Informal Work Participation (SIWP), we describe changes in informal work activity across 2015, 2016, and 2017 along multiple dimensions and for a variety of specific jobs. Considering the net changes observed between 2015 and 2017, we find that participation rates and earnings were mostly flat across the period, while average hours for gig workers declined by economically and statistically significant margins. The aggregate number of full-time equivalent jobs embodied in informal work—a measure combining participation rates and hours—also declined by an economically significant margin between 2015 and 2017. A major exception to these trends is that average ridesharing hours more than quadrupled between 2015 and 2017. We find some evidence that the recent declines in informal work hours represented a response to declining unemployment rates, but during this time period there also appears to have been upward structural pressure on gig work that provided a particular boost to platform-based work.