An important and relatively recent type of employment arrangement involves work through online platforms or mobile apps, sometimes known as “gig” work. Platform companies help workers connect to clients. Platforms also handle payments between clients and workers; clients pay the platform for the workers’ services, and the platform, after taking a fee for its service, pays the worker. Some platform companies such as Uber, Lyft, DoorDash, and Rover.com help workers connect to jobs in which they provide ride-share, food delivery, pet, or other in-person services. On other platforms such as Mechanical Turk and Upwork, workers provide services for clients entirely online.
In this new business model, the platform companies typically classify workers as independent contractors, not employees. The distinction is significant. Independent contractors are self-employed and therefore are not covered by employment and labor laws that govern minimum wages, overtime hours, and rights to collective bargaining that protect workers from discrimination on the basis gender, race, ethnicity, and age. Additionally, as independent contractors, these workers do not have access to unemployment insurance and workers’ compensation.
The advent of the “online platform economy” has garnered significant interest from the media, policymakers, and scholars, not only because of the technological advancement these firms represent, but also for what their widespread reliance on nonemployee arrangements might portend for the American workforce. Despite this attention, there is limited reliable evidence about the size of the online platform economy, the nature of these employment arrangements, and their impacts on workers.
The Size and Growth of Platform Work
Evidence on the incidence and growth of this new form of work comes from household surveys, administrative data collected for tax purposes, and private sector administrative data. Each has strengths and weaknesses as a source for measuring platform work.
The Contingent Worker Supplement (CWS) to the Current Population Survey, last conducted in 2017, added several questions to capture platform work performed during the prior week. Other one-time household surveys conducted as modules on the Rand American Life Panel and on the Gallup Education Pulse survey also included CWS-style questions to capture platform work (Abraham, Hershbein, and Houseman 2019; Katz and Krueger 2019). These surveys estimate that a relatively small share of those employed in the prior week worked through a platform.i
An advantage of household surveys is that they provide information on the characteristics of workers holding these jobs. For example, data from the 2017 CWS show that those engaged in platform work are disproportionately minority and college educated, controlling for other factors (Abraham and Houseman, forthcoming). A concern with household surveys has been whether respondents fully understand the questions on platform work, potentially compromising the accuracy of their answers (Abraham, Hershbein, and Houseman 2019; Committee on National Statistics, National Academy of Sciences, Engineering, and Medicine 2020). To address this problem on the 2017 CWS, the Bureau of Labor Statistics reviewed all survey responses pertaining to online platform work, recoding answers where respondents appeared to misinterpret the question. The recoding reduced the estimated share of employed reporting that they had held platform work in the prior week from 3.3 percent to 1.0 percent (Bureau of Labor Statistics 2018).
Although tax return data do not capture undeclared income, and administrative data from financial institutions may not be representative of the general population, studies based on these data avoid the problem of respondent confusion associated with household surveys. Using individual tax returns, supplemental information from 1099-Misc and 1099-K forms,ii and a list of leading platform companies, Collins et al. (2019) observe that about 1 percent of workers received pay from one of the identified online platforms in 2016. They also find that between 2012 (roughly when the online platform economy began) and 2016, 86 percent of the increase in the 1099 workforce was due to individuals working for an online platform. Data on financial transactions in 2.8 million accounts of JPMorgan Chase customers linked to a list of 128 online platform companies show that 1.6 percent of households received payment from one of these online platforms in March 2016—up from about 0.5 percent three years earlier, with nearly all of the growth driven by transportation platforms such as Uber and Lyft (Farrell, Grieg, and Hamoudi 2018). Thus, the increase in the online platform economy has been rapid, although its overall size remains small.
Are These Arrangement Good for Workers?
Whether the growth in online platform work is good or bad news for workers is a contentious question. Additional employment opportunities and increased flexibility may be a welcome development for individuals otherwise struggling to earn additional income. At the same time, there are longstanding concerns that these employment arrangements, by allowing firms to abuse exemptions provided to independent contractors, pose significant risks to systems meant to protect wage earners (Collier, Dubal, and Carter 2017).
We have limited evidence about how workers value and use these types of jobs. Because standard household surveys generally do not capture work for online platforms, researchers instead have relied on proprietary data from financial institutions and from online platform companies themselves to investigate these questions. For example, Chen et al. (2019) use detailed data on earnings and hours worked for Uber drivers and find that flexibility associated with the independent contractor arrangement yields significant benefits for drivers. Koustas (2018, 2019) uses individual-level and transaction-level data from an online financial aggregator to document how households rely on online platform jobs to cushion against a drop in income. He documents how consumption falls and savings deteriorate in the quarter before a worker takes on a gig job, suggesting that the availability and flexibility of this type of work helps workers to better respond to hard times. Garin et al. (2020), using tax data, and Farrell, Grieg, and Hamoudi (2019), using bank data, reach similar conclusions. Although this research indicates that online platform work plays a valuable role in helping households make ends meet during periods of unemployment or other financial distress, some studies suggest an important caveat to this conclusion. In particular, Jackson (2019) finds that while workers who become unemployed in counties with more online platform penetration are more likely to use these platforms for income in the short term, they also are less likely to return to traditional wage and salary jobs over the next few years, with less total earned income as a result.iii
As noted, because most platform workers are treated as independent contractors, they are not covered by minimum wage laws. Several studies have examined hourly earnings for ride-share workers after accounting for expenses such as gas and vehicle depreciation (Henao and Marshall 2019, Parrott and Reich 2020, Hyman et al. 2020). All find evidence that some workers earn below the minimum wage, although data sources, methods, and conclusions about the extent of the problem vary across studies.
Policy concern over the growing number of workers, including platform workers, classified as independent contractors prompted the passage of Assembly Bill 5 (AB5) in California. AB5 was intended to reduce misclassification of employees as independent contractors and, in most cases, required platform companies to reclassify their independent contractors as employees. However, a successful initiative on the ballot in California in November 2020—funded by Uber, Lyft, and DoorDash—exempts app-based drivers from AB5. In an unusual legal arrangement set out in the initiative, these drivers will continue to be classified as independent contractors, but they will be covered by labor and wage policies specific to ride-share drivers. As platform work continues to expand, contentious policy debates over the adequacy of legal protections for these workers are likely to continue.
Abraham, Katherine G., John C. Haltiwanger, Kristin Sandusky, and James R. Spletzer. 2018. “Measuring the Gig Economy: Current Knowledge and Open Issues.” NBER Working Paper No. 24950.
Abraham, Katharine G., and Susan N. Houseman. Forthcoming. “Contingent and Alternative Employment: Lessons from the Contingent Worker Supplement, 1995–2017.” Paper prepared for the U.S. Department of Labor, Chief Evaluation Office, Washington, DC.
Abraham, Katharine G., Brad Hershbein, and Susan N. Houseman. 2019. “Independent Contract, Informal, and Online Intermediary Work: Preliminary Evidence on Developing Better Measures in Household Surveys.” Unpublished working paper.
Bureau of Labor Statistics. 2018. “Electronically Mediated Work: New Questions on the Contingent Worker Supplement.” Monthly Labor Review, September.
Chen, M. Keith, Judith A. Chevalier, Emily Oehlsen, and Peter E. Rossi. 2019. “The Value of Flexible Work: Evidence from Uber Drivers.” Journal of Political Economy 127(6): 2735-2794.
Collier, Ruth Berins, V.B. Dubal, and Christopher Carter. 2017. “Labor Platforms and Gig Work: The Failure to Regulate.” IRLE Working Paper No. 106-17. Berkeley: University of California.
Committee on National Statistics, National Academy of Sciences, Engineering, and Medicine. 2020. Measuring Alternative Work Arrangements for Research and Policy, Consensus Study Report. The National Academies Press.
Farrell, Diana, Fiona Greig, and Amar Hamoudi. 2018. “The Online Platform Economy in 2018: Drivers, Workers, Sellers, and Lessors.” JPMorgan Chase Institute.
———. 2019. “Bridging the Gap: How Families Use the Online Platform Economy to Manage their Cash Flow.” JPMorgan Chase Institute.
Garin, Andrew, Emilie Jackson, Dmitri Koustas, and Carl McPherson. 2020. “Is New Platform Work Different than Other Freelancing?” AEA Papers and Proceedings 110: 157-161.
Henao, Alejandro, and Wesley E. Marshall. 2019. “An Analysis of the Individual Economics of Ride-Hailing Drivers.” Transportation Research Part A: Policy and Practice 130: 440–451.
Hyman, Louis, Erica L. Groshen, Adam Seth Litwin, Martin T. Wells, Kwelina P. Thompson, and Kyrylo Chernyshov. 2020. Platform Driving in Seattle. Ithaca, NY: ILR School, Cornell University.
Jackson, Emilie. 2019. “Availability of the Gig Economy and Long Run Labor Supply Effects for the Unemployed.” Unpublished working paper, Stanford University.
Katz, Lawrence F., and Alan B. Krueger. 2019. “The Rise and Nature of Alternative Work Arrangements in the United States, 1995-2015.” ILR Review 72(2): 382-416.
Koustas, Dmitri. 2018. “Consumption Insurance and Multiple Jobs: Evidence from Rideshare Drivers.” Unpublished working paper, University of Chicago.
———. 2019. “What Do Big Data Tell Us about Why People Take Gig Economy Jobs?” AEA Papers and Proceedings 109: 367-371.
Parrott, James A., and Michael Reich. 2020. A Minimum Compensation Standard for Seattle TNC Drivers. Report for the City of Seattle. New York: Center for New York City Affairs, The New School.
- i. The share of the employed engaged in any platform work during the survey week was 0.5 percent in the American Life Panel conducted in 2015, 1.0 percent in the CWS conducted in 2017, and 3.0 percent in the Gallup survey module conducted in 2018 and 2019. Differences in these estimates likely partially reflect rapid growth in platform work over time, though they also could reflect differences in survey samples and question wording.
- ii. These two tax forms are submitted to the IRS by firms on behalf of their contractors. The former documents compensation paid by firms to all self-employed workers; the latter documents workers’ earnings that are paid via electronic transactions and processed by that firm.
- iii. Jackson (2019) also finds that unemployed workers age 55 or older living in areas with more online platform opportunities are more likely to postpone Social Security benefits and less likely to receive disability benefits.