Some Thoughts from the Feds on the Gig Economy

In recent months, the gig economy has increasingly been the subject of articles, blog posts, studies, and podcasts.  In June, not wanting to miss the party, the U.S. Department of Commerce contributed a twenty-seven page paper on the subject, coining the new name “digital matching firms.”

About that name: the Commerce Department takes issue with the names “sharing” or “collaborative” economies, explaining in one of several text boxes that these names imply services are being provided for free. For anyone who believed that they could Uber for free or stay gratis in a Maui condo courtesy of Airbnb, the feds have cleared that up for you.

The paper lists four characteristics to define “digital matching firms.” First, digital matching firms use IT, typically via an app on a smartphone, to facilitate peer-to-peer transactions. Second, they rely on user-based rating systems to create trust between people who are often strangers. Third, they offer workers flexibility, allowing them to work when they choose. And fourth, they rely on workers to provide any needed tools or assets to perform the service. While these companies may share other attributes, such as bilateral rating systems and a range of pricing structures, the Commerce Department did not find those characteristics critical to its definition.

In addition to identifying key characteristics, the paper lists examples of companies that fall outside its definition, such as Craigslist, Amazon, and freecycle. The Commerce Department excludes these companies from its new definition either because they don’t use a rating system (Craigslist), no money is exchanged (freecycle and others), or for other reasons. A categorized appendix lists more than 100 companies that the Commerce Department identifies as “digital matching firms,” noting that the list is neither authoritative nor comprehensive.

With its new definition (ostensibly) clarified, the paper then discusses data, or, more accurately, the lack of data. While offering some estimates of the size and scope of these companies, the paper points out that available information is speculative because many of them are privately held. Relying on available data compiled by PwC, MBO Partners, PiperJaffrey, and JPMorgan Chase, the paper estimates that about 3 million Americans (9% of independent workers) provide services through on-demand platforms. About 500,000 of those provide services through Uber, Lyft, and Airbnb. That’s not surprising, given that Airbnb makes up about 2% of the American accommodations market (and is currently valued at more than $25 billion – more than the Marriott hotel chain and closing in on that of the Hilton hotel chain), and Uber and other rideshare companies make up more than 5% of the $90 billion global taxi marketplace.

The paper next lists benefits of and challenges to digital matching firms, while again noting “insufficient data to make any definitive judgments.” Neatly tucked into statements preceding the benefits, the authors recognize that these companies have “the potential to provide a number of benefits.” Those benefits are significant: lower prices for consumers (check out the table on page 12, which illustrates the difference - ranging from 32% to 67% lower for the peer-to-peer rentals than hotels - between the price of hotels and rentals available through digital platforms, like Airbnb), flexibility and extra income for workers, increased overall consumption, and an improved consumer experience (like the convenience of paying for your Uber ride via the app versus fumbling for your wallet in a taxi). 

The listed challenges in the paper primarily relate to possible downsides to the workers, such as potential income instability, lack of benefits, and the shift of training responsibility from the company to the workers. Another challenge? Safe handling of consumer and service provider information. No real surprises here, and most of these are certainly not unique to the gig economy.

The last few pages of the report address how these companies fit into the regulatory framework. First on the list of issues is worker classification, with a nod to the multiple challenges in this area.  Here, the paper references a Brookings Institute report questioning whether American labor should recognize a third class of worker – neither employee nor independent contractor – for gig economy workers. Others have posed similar questions. No doubt we’ll see more written on this. 

Another interesting issue the paper raises is whether digital matching firms are required to provide accessible services to disabled individuals under Title III of the Americans with Disabilities Act, a requirement for places of “public accommodations,” which include hotels and taxi services. This is an area to watch, as we will likely see increasing ADA accessibility challenges in the gig economy space.

The paper circles back to the subject of data availability in the last text box, pointing out that “efforts are underway to expand the availability of data.” The U.S. Department of Labor and Census Bureau are leading that charge by reintroducing the Contingent Worker Supplement, with updates relevant to the gig economy, as part of the Current Population Survey in 2017. There is also reference to possible changes to the tax code to allow federal statistical agencies access to federal tax information to allow them to measure, for example, income from payments to non-employees.

While we won’t see it on any lists of summer best beach reads, the feds’ first report on the gig economy is worth the read, as it compiles some interesting information about these business models and sheds some light on issues on which the government intends to focus.