Lael Brainard gave a nice overview talk on "The "Gig" Economy: Implications of the Growth of Contingent Work," (November 16, 2017). She notes some of the underlying economic forces that drive alternative work arrangements, how the changes will affect various macroeconomic measures, and the social tradeoffs that arise:
If market forces and technology are driving the growing prevalence of gig work, these trends will likely continue, and policymakers must better understand these changes. ... One possibility is that new technologies, by lowering the barriers to workforce entry, could raise employment and labor force participation. Because there are fixed costs to obtaining and maintaining a job--such as searching for the job, learning about the job, and traveling to the job site every workday--the traditional work arrangement embeds incentives for individuals to work only one job, thus minimizing these fixed costs. And for those individuals who desire to work relatively few hours, these fixed costs in the past may have led to a decision to remain out of the labor force. But if technology makes it less costly for individuals to find work, manage multiple work relationships, and flexibly work more or fewer hours as their schedule permits, this could significantly increase workers' options and have important effects on labor market behavior. Importantly, any such increases in participation and employment would likely be structural, not cyclical, enabling the economy to run at a sustainably higher level.
New technologies could also make it easier for individuals' actual hours to match their desired hours of work in a day or a week. Instead of seeing hours per week bunched around 40, we may see greater variation in the hours that individuals work. Lower barriers to workforce entry may make it more attractive for more individuals to work only a few hours a week if they desire--and can afford--to do so. At the same time, by making it easier to find additional work, new technologies may lead to more individuals working greater-than-full-time hours every week. In addition, we may see individuals changing the number of hours they work more frequently, as these changes become less costly. ...
The increasing prevalence of gig work may also affect the unemployment rate and productivity. To the extent that gigs provide an easy entryway to employment, unemployment may decrease. However, if gig work is less stable, it may increase job loss. The net effect on unemployment is, thus, unclear. Regarding productivity, gig work could lower aggregate productivity to the extent that it requires less human capital or specialized knowledge than traditional jobs, or if it primarily increases hours worked by lower-skilled individuals. That said, gig work, especially when enabled by new technologies, may allow hours to respond more flexibly to changes in demand and individuals to more easily connect with many different clients or employers. As a result, workers' downtime and the time required to acquire new clients and manage existing clients may decrease, in which case resource utilization and productivity may increase.
It is also possible that the increasing prevalence of gig work will cause the cyclical behavior of unemployment, participation, and the workweek to change, with implications for how we assess the amount of slack. We know that contingent work increases when the economy worsens. If new technologies make it easier to find gig work, then we could see unemployment rise less in recessions, to the extent that gig workers are counted as employed. However, it could be that individuals who are able to avoid unemployment through contingent work would still be underemployed if it is difficult to cobble together enough gigs to achieve full-time employment. This would likely show up as lower average workweeks and higher levels of involuntary part-time employment during downturns. As a result, cyclical changes in resource utilization could be reflected less in movements in the unemployment rate and more in variation in hours per worker.
Beyond the behavior of macroeconomic variables, it is unclear how the growth of different types of gig work affects the welfare of workers. Welfare should increase in cases where gig work meets the needs of workers by providing a low-barrier means of accessing employment and by allowing workers to better match actual hours worked with desired hours of work, especially if the gig work is available at times and in places where traditional work opportunities are in short supply. There is some evidence that this has, indeed, been the case. ...
However, there are likely many workers who would prefer regular full-time traditional work to contingent work, particularly if much of the power in determining hours worked in alternative work arrangements belongs to the employer. Technological advances have enabled firms to use just-in-time strategies for their employees, making them in effect on-call workers. This is a rising trend in industries such as retail and food preparation. Several recent articles describe the challenges faced by these just-in-time workers, who must conform their hours to the daily and even hourly ebbs and flows of business, often not knowing whether they will have work on a given day until they call in that morning to inquire. These arrangements can leave workers scrambling to patch together child care, elder care, and transportation to meet the often unpredictable demands of their workplace, while making it difficult to engage in regularly scheduled activities to enhance their income and opportunities, such as a second job or career training. While such workers often are not given full-time work, they often must make themselves available to work full-time hours. According to one survey, 71 percent of retail workers in New York stated that their hours fluctuated from week to week, while half said their employers could change their hours at will. It is also notable that the increase in contingent work over the past decade has coincided with an increase of one-third in the share of employees working part time but who would prefer to work full time from 3 percent prior to the Great Recession to close to 4 percent today.
In addition, contingent workers may receive lower wages, less training, and fewer benefits than their counterparts with traditional jobs. Typically, the wages of low-skilled employees within a company are boosted by social norms regarding pay equity, and nonpecuniary benefits are often equalized across a company's employees, in certain cases as mandated by law. However, the wages that contractors receive are unlikely to reflect the same equity considerations. Moreover, contingent work generally does not offer employer-based benefits and workplace protections that come with traditional employment opportunities, like overtime compensation, minimum wage protections, health insurance, family leave, employer-sponsored retirement plans, workers' compensation, and paid sick leave. As a result, for some, contingent work may entail greater risks than in traditional full-time employment, with more variable and less predictable hours and earnings. ...
These findings suggest that employers, policymakers, and workers should seek ways to help individuals better manage the risks inherent in most forms of contingent work. For example, we may need to enhance social safety net programs, such as unemployment and disability insurance, to better support some types of contingent work. Another possibility is to make benefits, such as health insurance and retirement saving, portable across different employers. We may also want to encourage the additional saving that many contingent workers need to ensure that their basic consumption needs are not sacrificed when demand for their work declines, perhaps by providing monetary or other types of incentives.The Pew Foundation has just published a report on "Gig Work, Online Selling and Home Sharing" (November 17, 2016). "a new Pew Research Center survey of U.S. adults finds that a relatively substantial share of the public has earned money recently from a digital commerce platform. In the context of gig employment, nearly one-in-ten Americans (8%) have earned money in the last year using digital platforms to take on a job or task. Meanwhile, nearly one-in-five Americans (18%) have earned money in the last year by selling something online, while 1% have rented out their properties on a home-sharing site. Adding up everyone who has performed at least one of these three activities, some 24% of American adults have earned money in the “platform economy” over the last year."
Here's a figure from the report that I found interesting, focused on the 8% who earned money using a digital platform. Of that group, more than half--that is, about 4% of US workers--view these earnings as "essential or important." Also, the biggest activity for this group is
Finally, the Federal Trade Commission has published "The “Sharing” Economy: Issues Facing Platforms, Participants & Regulators," which is a report that summarizes various issues and viewpoints from a mid-2015 workshop, as well as over 2,000 responses to an FTC "request for comments." The report is an even-handed discussion of various issues: for example, how digital platforms might deal with trust issues through methods including rating mechanisms; how the regulations for such firms might differ from those for incumbent competitors in, say, the taxi or hotel business; what the rise of these platforms could mean for competition policy. Here's a snippet (footnotes omitted for readability):
Finally, the Federal Trade Commission has published "The “Sharing” Economy: Issues Facing Platforms, Participants & Regulators," which is a report that summarizes various issues and viewpoints from a mid-2015 workshop, as well as over 2,000 responses to an FTC "request for comments." The report is an even-handed discussion of various issues: for example, how digital platforms might deal with trust issues through methods including rating mechanisms; how the regulations for such firms might differ from those for incumbent competitors in, say, the taxi or hotel business; what the rise of these platforms could mean for competition policy. Here's a snippet (footnotes omitted for readability):
PricewaterhouseCoopers estimates that sharing economy marketplaces in five sectors – peer-to-peer finance, online staffing, peer-to-peer accommodation, car sharing, and music/video streaming – generated $15 billion in revenues worldwide in 2013, and projects that these revenues will rise more than twentyfold to $335 billion by 2025. The magnitude of the sharing economy’s impact has registered in the financial world as well. Some of the largest companies in this space have gone through multiple rounds of funding, in some cases reflecting valuations in the tens of billions of dollars. Based on a round of funding in December 2015, Uber was valued at $62.5 billion, while a November 2015 financing placed Airbnb’s valuation at $25.5 billion. Etsy, the peer-to-peer marketplace for handmade or vintage items, went public in April 2015 and opened with a value of nearly $4 billion. Incumbent businesses are also providing financing to sharing economy marketplaces – partnering with, investing in, or acquiring sharing economy platforms. Since the beginning of 2015, General Motors made a $500 million investment in Lyft, valuing Lyft’s equity interest at $5.5 billion, and Apple invested $1 billion in Didi Chuxing, China’s biggest for-hire transportation platform. Hotelier Hyatt has purchased a stake in British accommodations platform OneFineStay, while Expedia paid $3.9 billion to acquire the lodging site HomeAway.
Two sectors of the travel industry have been at the epicenter of the explosion of sharing economy activity: short-term lodging (specifically, rental stays like those provided by hotels and bed-and-breakfasts) and for-hire transportation service (specifically, services akin to those provided by traditional taxis and limousines). Airbnb has become a leading platform for facilitating short-term rental transactions. Started in 2008 by roommates who rented out space in their apartment during a local convention, Airbnb reported over two million listings in over 34,000 cities, and a cumulative total of 60 million guests by the end of 2015. Platforms facilitating the provision of for-hire transportation service are often referred to as transportation network companies (or “TNCs”). The leading TNC, Uber, began operations in 2009 in San Francisco, and as of 2014 reported providing 140 million rides (including one million rides per day by year-end) and a driver base of over 162,000. Pew Research Center found that by 2015, 11 percent of American adults had used an “on-line home-sharing service” and 15 percent had used “ride-hailing apps.” ...
[T]he sharing economy has expanded well beyond the accommodation and transportation sectors. A panelist observed that a start-up tracking site lists “about 600 peer-to-peer startups.”One expert has developed an infographic “honeycomb” describing 16 broad sectors and approximately 40 subsectors in which sharing economy platforms operate, and specifying the location of 280 platforms within these categories. His research reveals that the sharing economy model now extends to small businesses or individuals providing a wide range of goods and services, including, but by no means limited to: preparing meals, shipping or storing goods, renting tools or clothing, performing household tasks, providing health services, ordering custom-made goods, and obtaining funding for projects. And the expansion continues, as new platforms arise, each vowing to become the “Uber” or “Airbnb” of some other market sector.
