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economics Gig economy

Between the Gigs and the Reels: novel approaches to understanding the gig economy

The rise and rise of companies like Uber, Lyft, TaskRabbit, UpWork, JustEat and Deliveroo has been termed the “gig economy”. Even the term itself can be wince-inducing to labour lawyers who are uncomfortable with the implications of the term “gig”. But there are broader issues, and a lot of ink has already been devoted to the economic and regulatory issues that arise as a result of this new form of working. At its heart, the issues tend to arise initially from the introduction of technology into the labour market that enables informal work. This has allowed the regulatory and statutory protections that workers have campaigned and fought for over the past two centuries to be summarily side-stepped. Sure, there are benefits, and it can present opportunities for people to get out of the house and supplement their income. But the problem is when this form of working begins to challenge the main, or more formal, economy.

The gig economy really took off in the wake of the 2008 financial crisis and the unemployment wave that followed, and is rooted in the informal sector which lacks government oversight, creating dilemmas about regulation and worker protections. Not that this is a completely new issue. The matter of informal sector work with a lack of recognition and worker protections and rights is a problem that women have been facing since labour rights came onto the scene. Women’s work – work generally done in the home – has yet to receive the same recognition as work done in the formal sector. Informal sector work includes not only a lack of pay, but also rights, holidays, sickness, insurance and so on. This analogy tends to be underplayed in the public debate about gig economy pros and cons. As Catherine Powell notes, the gig economy is business as usual for women. What’s new here is that the advent of technology and the self-employment or contractor-status of (usually) men has been sold to us as the epitome of the free market “in which app-driven services are seen as an example of unfettered market activity that is free of the intrusive, cumbersome hand of government regulation”.

At the same time, drivers working for Uber are contractors rather than employees, and therefore do not have access to the regulatory protections that employees do, like holiday pay, sick pay, pensions, national insurance contributions, and so on, although there are legal and regulatory challenges underway. In her recent book, “Hustle and Gig”, Alexandrea Ravenelle also argues that society is the poorer for this labour market model, as reduced tax incomes and reduced provision of social security nets by employers as well as the state have wider detriments throughout society.

In a different approach to most of the literature on the gig economy, economist and Stanford Professor Paul Oyer signed up with Uber and worked as a driver for them to understand the gig economy from the inside. This article links to an interview with him about his research and findings.

If you’ve read any of my previous posts, you’ll be expecting a comment here about economic methodology and how exciting it is to have an economist taking a sociological, quasi-ethnographic approach to understanding how a market works. Oyer notes that he took care not to tell his Uber customers that he was an undercover economist, and as he was employed by Stanford, his Uber wages were donated to charity. Nevertheless, his observations are valuable for their insight into the inner workings of companies leading and shaping the gig economy, like Uber. One observation that stands out here is the lack of social interaction among gig economy workers. If you work in an office, you see the same people every day, and a sense of community can develop. But working as a contractor in a car or on a bike can mean that you are isolated and solitary, and the loneliness of this was highlighted by Oyer’s undercover work; a sociological commentary on an economic phenomenon.

There are few insider accounts in general, and little literature on the importance of algorithms that form the backbone of the company like Uber. These are being developed by economists brought in by the firms, and have unpleasant, although perhaps unsurprising, side effects. The algorithms tend to channel higher paying work to men who are prepared to work at short notice, during “surges” in demand where prices are higher, and at periods of scarcity. Thus, male Uber drivers earn on average 7% more than female drivers. Male drivers are also more likely to “game” the system, learning how to be strategic in their pick ups and how to cancel less profitable journeys without incurring a penalty, provoking angry discussions like this online. Women are less likely to engage is this less-than-honest behaviour, putting their wages further behind.