While the concept of nontraditional, short-term, and contract work has been around since well before the digital age, it wasn’t until the 2010s that digital platform companies like Uber, DoorDash, Instacart, and TaskRabbit began to rise to prominence and shape the way we define gig work today.
A survey of gig workers in the spring of 2020 revealed that their jobs provided poor working conditions, even relative to other service-sector workers, who themselves typically receive low pay.
- About 1 in 7 gig workers (14%) earned less than the federal minimum wage on an hourly basis. More than a quarter (29%) earned less than the state minimum wage that would be applicable if they were a W-2 service-sector worker.
- Three out of every 5 gig workers (62%) lost earnings because of “technical difficulties clocking in or out,” compared with 19% of W-2 service-sector workers.
- One in 5 gig workers (19%) went hungry because they could not afford enough to eat. Thirty percent used the Supplementary Nutrition Assistance Program (SNAP) within a month of the survey, twice the rate of W-2 service-sector workers (15%).
- Nearly one-third (31%) of gig workers did not pay the full amount of their utility bills in the month prior to the survey.
In the most basic terms, gig work can be defined as work done by individuals who are classified as self-employed, freelancers, or independent contractors. However, in recent years the term “gig work” has become synonymous with working for digital platform companies, including driving for ride-share apps, making deliveries for restaurants, shopping or delivering groceries, and performing errands or household tasks. In this use, “gig work” is a misnomer that helps companies propagate the myth that these workers have more independence and control over their work than they actually do.
Digital platform companies have constructed a business model on the premise that they do not employ their workforce. These companies treat workers who perform the services they offer not as employees but as independent contractors. By classifying their workforce in this way, they deprive workers of fundamental rights under federal and state labor and employment laws, including wage and hour protections, anti-discrimination protection, workers’ compensation, unemployment benefits, and the right to organize and collectively bargain.
Digital platform companies claim that their workforce benefits from this classification, enjoying the benefits of entrepreneurship with good pay and more flexibility than workers classified as traditional W-2 employees. However, a survey of gig workers reveals that these workers often are paid low wages, in some instances less than the minimum wage; they face economic insecurity at high rates; and they routinely report losing earnings because of technical difficulties with digital platforms.
The impact of gig worker misclassification
The determination of whether an individual providing services to an employer is an employee or an independent contractor carries significant consequences for both the individual and the employer in terms of job protections, tax obligations, and eligibility for employment-based benefits and protections.
As Table 1 shows, individuals who are classified as independent contractors are not covered by federal or state wage and hour, anti-discrimination, health and safety, collective bargaining, or other worker protection laws. They do not receive employment-based health insurance or retirement benefits, and they do not qualify for paid sick or family leave in places where those benefits are statutorily prescribed. Nor are independent contractors eligible for unemployment insurance when temporarily unemployed, or workers’ compensation when injured on the job. This leaves independent contractors in a far more vulnerable status, as compared with employees, when it comes to basic rights and protections on the job.
Uber: A business model of misclassification
Digital platform company Uber advertises that driving for the company is flexible, with the driver in control operating as an entrepreneur, according to the company’s website. Interested drivers just download the driving app and complete a “sign-up” process that requires only that drivers have a valid driver’s license and insurance and “complete a background screening.” The company states that drivers set their own hours and may “cash out” after each trip (up to five times per day on the app). Uber brands itself as merely a technology platform that allows drivers to find earning opportunities for their own entrepreneurial endeavors (Mishel and McNicholas 2019).
However, the reality of working for Uber is very different. Drivers have no say on setting fares, on what they are paid, or on the commissions the company takes. Drivers are not shown the passenger’s destination or how much they could earn on a fare before being asked to accept a ride request, and they have limited say on whom they choose to have as customers (Rosenblat 2018). Further, drivers do not select their own routes.
Comparison of workplace legal protections for employees and for independent contractors in the United States
|Labor standard||Employee||Independent contractor|
|Paid sick days||√||X|
|Paid family leave||√||X|
|Health and safety protections||√||X|
|Right to a union||√||X|
|Discrimination and sexual harassment protections||√||X|
Source: Authors’ analysis of current (as of May 2022) federal and state laws. Employees have these protections in places where they are statutorily prescribed. Independent contractors do not have these protections in any jurisdiction.
Much is still unknown about workers’ experience of gig work and its prevalence in the economy because there are few nationally representative surveys on this segment of the workforce compared with W-2 employees.
The Bureau of Labor Statistics (BLS) tries to capture the gig workforce through the Contingent Worker Supplement to the Current Population Survey (CWS), which measures workers in alternative work arrangements such as independent contracting, on-call arrangements, and employment arrangements through temporary agencies or contracted firms. However, the survey reflects only the type of work individuals do as their main or sole job and does not capture any supplemental work. The latest CWS data in 2017 showed that alternative work arrangements make up 10% of all employment (BLS 2018).
Other studies estimate that 16% (Anderson et al. 2021) to 36% (Upwork 2020) of the workforce participate in the gig economy. Even with the limited, albeit growing, research on the gig workforce, the rise of digital platform companies and their use of independent contractor classification have serious ramifications for workers.
In order to understand how workers were faring during the pandemic, in May 2020 the Shift Project collected survey data from two groups of workers: gig workers and service-sector employees.1 Both groups of workers responded to surveys elicited from Facebook and Instagram advertisements. The surveys included modules on demographics, job characteristics, and economic security issues and resulted in a sample of 288 gig worker respondents, which we call the gig worker sample, and 4,201 service-sector employees, which we call the W-2 service-sector sample.2
In contrast to much of the previous research on gig workers, the survey results we present here provide a comprehensive, national portrait of gig workers and their job characteristics. Other studies and surveys have provided extremely useful profiles of gig workers, but most of these have been limited to gig workers in a single city such as Chicago, New York City, San Francisco, or Seattle. Due to data limitations, the small set of nationally representative studies has focused on ride-hail drivers, such as Uber drivers.3
Taken in isolation, the levels of hardship reported by gig workers in our survey sample mostly illustrate the extreme difficulties faced by workers at the beginning of the pandemic, when employment opportunities and earnings dropped precipitously. But by comparing two groups of workers that both faced significant increases in hardships during the pandemic—gig workers compared with restaurant and other service-sector workers—we can reasonably assess the relative ability of gig work or W-2 service-sector work to provide decent working conditions during a time of economic hardship.
Employment fields in Facebook data determined whether respondents worked as gig workers or as service-sector employees.4 Gig workers were listed as working at firms such as Uber, DoorDash, Lyft, Instacart, and Uber Eats. W-2 service-sector workers were listed as working at one of 58 large retail and food service companies, such as Target, Walmart, Publix, Kroger/QFC, Arby’s, McDonald’s, Chick-Fil-A, Walgreens, Starbucks, and Home Depot.
Many gig workers have lower hourly earnings than W-2 service-sector workers. Table 2 shows that 14% of surveyed gig workers earned less than the federal minimum wage of $7.25 per hour. In contrast, 0% of W-2 service-sector workers reported earning less than the federal minimum wage. More than twice as many gig workers (26%) as those in the W-2 sample (11%) earned less than $10.00 per hour.
Hourly wage distribution of gig workers and W-2 service-sector workers, May 2020
|Gig workers||W-2 service-sector workers|
|Less than $7.25||14%||0%|
|$7.25 to $9.99||12%||11%|
|$10 to $14.99||38%||53%|
|$15 to $20.99||24%||27%|
|$21 or more||13%||9%|
Notes: Hourly wages are inclusive of tips. W-2 service-sector workers report hourly wages, and gig worker hourly wages are calculated by dividing their previous week’s earnings by their usual weekly hours.
The prevalence of low wages is especially severe when comparing the hourly wages of gig workers against applicable state minimum wage laws. Table 3 shows that more than a quarter of gig workers (29%) earned less than the state minimum wage that would likely be applicable were they a W-2-based employee. In comparison, only 1% of W-2 employees in the service-sector sample reported hourly wages below state minimum wage thresholds.
Share of workers earning below the applicable state minimum wage, May 2020
|Gig workers||W-2 service-sector workers|
Notes: Hourly wages are inclusive of tips and are compared against the state minimum wage in the worker’s state as of January 2020. W-2 service-sector workers report hourly wages, and gig worker hourly wages are calculated by dividing their previous week’s earnings by their usual hours.
The median degree of underpayment for gig workers was $2.17 per hour (not shown). On an annual basis, this underpayment amount is the equivalent of roughly $3,400, assuming year-round work with the median-reported 30-hour workweek.
For W-2 service-sector workers, the data in Tables 2 and 3 are from current hourly earnings reported by these workers; for gig workers, it is their previous week’s earnings divided by their “usual hours worked” on a weekly basis over the past year. One potential concern, given that the survey was conducted just two months into the pandemic, is that we may overestimate the share of gig workers earning subminimum wages if they are reporting their “usual hours” based on their pre-pandemic hours and if their hours in May 2020 are lower than their usual hours due to pandemic conditions.
While it is impossible to verify whether the hours reported (“usual weekly hours”) were the same as actual hours worked in the prior week, the survey data do provide three additional reasons to think that the prevalence of subminimum wage work is higher among gig workers.
First, the large magnitude of underpayment, relative to effective minimum wages, suggests measurement error in reported hours is unlikely to explain the entire gap between estimated hourly wages and applicable minimum wage levels. Given that the median degree of underpayment is $2.17 per hour, as noted above, even if we artificially increased hourly wages by more than $2, half of gig workers earning less than their state’s minimum wage would still have been paid less than that statutory threshold.
Second, as we explain below, gig workers are significantly more likely than W-2 service-sector workers to face material hardships, consistent with the idea that the wages of gig workers are even lower than those of typically low-paid W-2 employees.
Third, one reason for the high share of subminimum wage work among gig workers is that gig workers are not being paid for some work hours. Many gig workers reported losing earnings because of “technical difficulties clocking in or out” of work. Table 4 shows that more than 3 out of every 5 gig workers (62%) had not been paid for their work on the job at least once. In contrast, less than 1 in 5 W-2 service-sector workers (19%) failed to receive pay due to difficulties clocking in or out of work. More than one-third (36%) of gig workers surveyed had lost pay three or more times.
At low-wage jobs, the failure to be paid for certain hours of work can easily push a given worker’s wages below the effective minimum wage. In both instances, the loss of pay due to technical difficulties can be considered a form of wage theft. However, unlike employees, gig workers have no legal recourse to recover their lost wages due to their independent contractor classification.
Share of workers who have lost pay because of technical difficulties clocking in or out
|Gig workers||W-2 service-sector workers|
|At least once||62%||19%|
|Three or more times||36%||8%|
Source: Authors’ analysis of Shift Project survey data on gig workers collected in May 2020 and Shift Project survey data on W-2 service-sector workers collected in March and April 2020.
Subminimum wages and difficulties obtaining pay have led to significant hardships for gig workers, even in comparison with generally low-paid service-sector workers. Table 5 shows that, relative to W-2 service-sector workers (13%), gig workers were more likely (18%) to live in a household in which someone did not see a doctor or go to the hospital in the last month because of the cost. About 1 in 5 gig workers (19%) went hungry in the last month because they could not afford enough to eat. Thirty percent of gig workers used SNAP within a month of the survey, twice the rate of W-2 service-sector workers (15%).
Economic insecurity of gig workers and W-2 service-sector workers
|In the last month…||Gig workers||W-2 service-sector workers|
|Went hungry because could not afford enough to eat||19%||14%|
|Did not have enough money to pay full amount of gas, oil, or electric bill||31%||17%|
|Household member did not see a doctor or go to the hospital because of the cost||18%||13%|
|Used Supplemental Nutrition Assistance Program (SNAP)||30%||15%|
Low pay for gig workers also made it very difficult to pay utility bills. Table 5 shows that nearly one-third of gig workers (31%) did not pay the full amount of gas, oil, or electric utility bills in the last month; the corresponding percentage for W-2 service-sector workers is 17%. Table 6 shows that, relative to W-2 service-sector workers, gig workers were significantly more likely to report it was “very difficult” to cover expenses and pay bills.
Share of workers reporting it is somewhat or very difficult to cover expenses and pay bills
|Gig workers||W-2 service-sector workers|
Consistent with the higher levels of material hardship and low levels of pay, many gig workers expected to leave gig work for another job soon. Table 7 shows that gig workers intended to leave their current job at a higher rate than W-2 service-sector workers, who already normally have high rates of employee turnover (BLS 2022). More than half (55%) of gig workers intended to find a new job in the next three months, compared with 36% of W-2 service-sector workers.
Share of workers reporting they intend to find a new job within the next three months
|Gig workers||W-2 service-sector workers|
The race and age composition of the gig workforce and the W-2 service-sector workforce tend to be relatively similar. The first two “unweighted” columns of Table 8 show the demographic composition of the raw gig and W-2 service-sector sample data for those observations for which there is complete demographic information. The majority of gig and W-2 service-sector workers in the sample are white and non-Hispanic, and the mean and median age of each sample ranges from 39 to 41 years old. Women make up the majority of each sample, but gig workers are more likely to be men (45%) than W-2 service-sector workers are (31%). Gig workers in the sample are more likely to have some college education (73%) than W-2 service-sector workers (59%).
Demographic profiles of gig workers and W-2 service-sector workers
|Gig workers||W-2 service-sector workers||Gig workers||W-2 service-sector workers|
|Other race/ethnicity, non-Hispanic||6%||7%||8%||10%|
|No degree or diploma earned||4%||4%||7%||5%|
|High school diploma/GED||21%||37%||27%||35%|
|English as a second language||14%||10%||26%||17%|
|Married, living with spouse||27%||31%||24%||25%|
|Living with a partner||21%||18%||21%||19%|
|Not living with a spouse or partner||49%||50%||52%||56%|
|Survey sample size||288||4,201||288||4,201|
We confirmed that the raw survey results provide a reasonable basis for inference about the national population of the gig and service-sector workforces by reweighting the samples to match what is known about service-sector demographics in the U.S. and then observing that the results that follow on economic hardship and pay are not sensitive to this reweighting.
For transparency, we show in columns 3 and 4 of Table 8 the demographic profiles of the surveys if the data are reweighted to match the race, age, and gender distributions of the American Community Survey.5 The gig worker and W-2 service-sector samples tend to be more white and more female than a nationally representative sample of service-sector workers. While reweighting mechanically changes some of the demographic shares in Table 8, reassuringly the reweighting does little to change any of the results; therefore, we report the raw, unweighted results in Tables 2–7.6
Much is still unknown about digital platform workers. As noted above, the Bureau of Labor Statistics has sought to gain a better understanding of this workforce through the Contingent Worker Supplement. However, as discussed, the CWS data reflect only the type of work individuals do as their main or sole job and does not capture any supplemental work. Further, the CWS data are not routinely collected, with the last update in 2017 and the prior in 2005. Resources should be directed to BLS to allow for a more comprehensive and annual report of this workforce.
While more comprehensive data is required to develop appropriate policy solutions to ensure that gig workers have access to fundamental worker protections, some things are clear: Gig workers often are paid low wages, in some instances less than the minimum wage; they face economic insecurity at high rates; and they routinely report losing earnings because of technical difficulties with digital platforms.
One key to improving conditions for these workers is enforcement of existing federal wage and hour laws. DOL must hold companies accountable for misclassification and ensure that workers have access to fundamental workplace protections guaranteed them under federal law. This includes the right to a union. It is well documented that unions are an essential tool for workers to improve their pay, benefits, and working conditions (McNicholas et al. 2020). However, under current federal labor law, independent contractors are not covered under the National Labor Relations Act (NLRA) and are thereby restricted from forming a union.
The Protecting the Right to Organize (PRO) Act, which passed the House last year but has not advanced in the Senate, would require employers to follow the “ABC” test, which is a strong, protective test for determining employee status.7 This would better protect workers’ fundamental right to organize and collectively bargain.
Digital platform companies have established a business model based on denying workers fundamental protections. While the technology these companies utilize may be innovative, a business model that creates profit by denying workers basic wage and hour protections is far from inventive. Corporations have long looked for ways to exempt themselves from worker protections, and they spend hundreds of millions of dollars each year to deny their workforce union representation (McNicholas et al. 2019).
Contrary to the narrative they have set forth, gig companies have not created entrepreneurial opportunities with family-sustaining pay. Instead, more than a quarter of gig workers earn less than the state minimum wage. These workers and their families experience high levels of economic insecurity. Most telling, more than half of these workers intend to find a new job in the next three months. These data demonstrate that the reality of working for these digital platform companies is far from the great “gig” they advertise. Policymakers must address the reality of gig work and prevent these companies from denying their workers basic protections through misclassifying their workforce.
1. The Shift Project, a joint project at Harvard Kennedy School and UCSF, examines the nature and consequences of precarious employment in the service sector, with a focus on how policymakers and firms can improve job quality. Since 2016, Shift has surveyed over 160,000 workers using an innovative recruitment method to target employees at the largest chain retail and food service firms. The survey asks workers across the United States about their working conditions, economic security, health, and family life.
2. In the results presented in this report, most of gig worker and W-2 service-sector responses are from samples and surveys collected in May 2020. The only exception is the set of survey responses on losing pay because of technical difficulties: The gig worker sample for this question is from May 2020, but the W-2 service-sector sample is a different set of workers, from March and April 2020.
3. See NELP 2021 for a comprehensive list of studies and surveys focusing on app-based workers.
4. See Schneider and Harknett 2022 for details about the survey design and collection.
5. See the appendix of Schneider and Harknett 2019 for details on reweighting the survey respondents.
6. For example, reweighting does little to change the estimated shares of workers earning less than the effective state minimum wage. That share for gig workers is 29% using the unweighted data or 34% using the weighted data. For W-2 service-sector employees, the share is 1% in both the unweighted and weighted samples.
7. The ABC test establishes a presumption that an individual performing services for an employer is an employee, not an independent contractor, unless the employer can establish three factors: (1) The work is done without the direction and control of the employer. (2) The work is performed outside the usual course of the employer’s business. (3) The work is done by someone who has their own, independent business or trade doing that kind of work.
Anderson, Monica, Colleen McClain, Michelle Faverio, and Risa Gelles-Watnick. 2021. The State of Gig Work in 2021. Pew Research Center, December 2021.
Bureau of Labor Statistics (BLS). 2018. “Contingent and Alternative Employment Arrangements—May 2017” (news release). June 7, 2018.
Bureau of Labor Statistics (BLS). 2022. “Table 16. Annual Total Separations Rates by Industry and Region, Not Seasonally Adjusted” (economic news release). Last modified March 10, 2022.
McNicholas, Celine, Margaret Poydock, Julia Wolfe, Ben Zipperer, Gordon Lafer, and Lola Loustaunau. 2019. Unlawful: U.S. Employers Are Charged with Violating Federal Law in 41.5% of All Union Election Campaigns. Economic Policy Institute, December 2019.
McNicholas, Celine, Lynn Rhinehart, Margaret Poydock, Heidi Shierholz, and Daniel Perez. 2020. Why Unions Are Good for Workers—Especially in a Crisis Like COVID-19: 12 Policies That Would Boost Worker Rights, Safety, and Wages. Economic Policy Institute, August 2020.
Mishel, Lawrence, and Celine McNicholas. 2019. Uber Drivers Are Not Entrepreneurs: NLRB General Counsel Ignores the Realities of Driving for Uber. Economic Policy Institute, September 2019.
National Employment Law Project (NELP). 2021. App-Based Workers Speak: Studies Reveal Anxiety, Frustration, and a Desire for Good Jobs. Produced in collaboration with Gig Workers Rising, Gig Workers Collective, Mobile Workers Alliance, We Drive Progress, Rideshare Drivers United, and Philadelphia Drivers Union, October 2021.
Rosenblat, Alex. 2018. “When Your Boss Is an Algorithm.” New York Times, October 12, 2018.
Schneider, Daniel, and Kristen Harknett. 2019. “Consequences of Routine Work-Schedule Instability for Worker Health and Well-Being.” American Sociological Review 84, no. 1 (February 2019): 82–114, https://doi.org/10.1177/0003122418823184.
Schneider, Daniel, and Kristen Harknett. 2022. “What’s to Like? Facebook as a Tool for Survey Data Collection.” Sociological Methods and Research 51, no. 1 (February 2022): 108–140, https://journals.sagepub.com/doi/full/10.1177/0049124119882477.
Upwork. 2020. Freelance Forward 2020: The U.S. Independent Workforce Report. September 2020.