Emily Badger of Atlantic Cities draws on the work of NYU Stern economist Arun Sundararajan to think through the hidden employment effects of the sharing economy:
Take a person who was completely unemployed and now does some kind of work as a sharing economy supplier, maybe driving an Uber car, or providing services on TaskRabbit. If that person reports this new work for profit in a response on a BLS survey, they would be counted as an additional job. However, Sundararajan adds, unemployment (or employment) numbers reported by the BLS don’t capture the additional “employment” or “work” generated by underemployed people who were already working at least an hour a week (like a software contractor who now also does Lyft on the side).
Additionally, that data isn’t good at reflecting people who dip into the sharing economy while holding regular full-time jobs (a lawyer who rents out a room on Airbnb, a furniture supplier who creates and sells his own work on Etsy on the side). It can’t capture the effect when a previously existing small business owner now receives substantially more employment thanks to Etsy. It also can’t tell us anything about one of Sundararajan’s key questions: Are these micro-entrepreneurship platforms enabling people to create more traditional new businesses that wouldn’t have existed without the launching pad of the sharing economy?
Part of the challenge also lies in how people who do these activities think of them. Sundararajan worries that survey questions that ask about your “job,” your “main job,” your “other job,” or your “business” may lead people in the sharing economy to under-report what they’re up to simply because they don’t think of their activities in those terms. A knitter on Etsy thinks she’s selling the products of her “hobby.” A driver on SideCar thinks he’s taking gas money to drop people off while he’s already on his way across town to his part-time job. And an Airbnb host doesn’t quantify how many hours she spent last week “hosting” tourists from Chicago. Airbnb in particular leverages excess space, not excess time, making it difficult to measure that “work” in hours.
The underlying point here isn’t necessarily a critique of official statistics. Sundararajan believes the only way you measure the impact on the economy of this kind of technological change is to go to the source of the technology itself: these companies. Only they can answer how many sellers use their platforms, or how much money the average vendor is earning, or how many people are served by their products, enabling ripple effects throughout the economy. Which brings us back to our starting point: It’s time for companies in the sharing economy to begin rounding up their own data.
It’s easy to understand why firms would be reluctant to share this information — they’d be sharing with competitors and would-be competitors. And perhaps sharing economy enthusiasts are overestimating the economic impact of platforms like Etsy and Uber. But as Badger and Sundararajan suggest, the real impact could be indirect:
Sundararajan also suspects that many of these platforms are quietly operating as “finishing schools” for tentative entrepreneurs, another effect that so far hasn’t been measured. You can test out selling some of your crafts on Etsy, for example, without quitting your job and cashing in your 401K to open a brick-and-mortar store. Whole new companies will start this way, he predicts. And that would have an impact on the economy, too, that would be inarguably positive.
That is, these platforms are platforms for building human capital, including risk tolerance. They can be understood as educational institutions as much as marketplaces for many of their users.