Problems with quantifying the gig economy


Posted on February 8, 2019  /  0 Comments

There has been a lot of hype and buzz surrounding the gig economy over recent years. Researchers and policymakers alike have been grappling with many questions around the future of work debate, with the rise of digital platforms: How will these work platforms impact the labor market? How can workers rights be protected? How can consumer rights be protected? What will the gig economy do for (or to harm) inclusion? One of the bigger questions has of course centered on quantifying the gig economy, specifically measuring how many people are actively engaged gig work.

Not much data exists for the rest of the world, but recent research in the US has underscored the difficulties in quantifying it accurately. Economists Katz and Kreuguer (of Harvard and Princeton, respectively) admitted in a paper published last month, that they had in fact got it wrong in their previous 2015 research, over-estimating the number of gig workers in the US due to three reasons: They did not account for the fact that the labor market had slowed down in 2015, leading to more people seeking other means of income through gigs; ‘differences in survey questions’ between their own 2015 survey and that used by the US Bureau of Labor Statistics (BLS) to gather the baseline data in 2005; and ‘sampling issues.’ After adjusting for these factors, they have now revised their estimate of growth in the US between 2005 to 2015 from 5% to between 1 and 2 percent. This highlights the difficulties in the reality of having to piece together numbers from different sources.

A separate New York Times article points out a further problem with the US BLS data, in that it may exclude those that are doing gig-work on top of a regular job (which gets counted, while the former may not). This is a reality for countries like India and Sri Lanka as we have seen in our research on microworkers in the two countries. We came across many who earn more online than they could offline, but held on to an offline job for the access to services (e..g., loans) and social recognition which microwork can not get them.

But what does the gig economy look like in the Global South? AfterAccess data can shed some light, through nationally representative surveys of ICT access and use across 20+ countries of the Global South among those aged 15-65. The AfterAccess survey specifically asked Internet users if they mobile and Internet platforms to ‘sell’ services such as transport and taxi services, or engage in microwork or online freelancing, providing hired help, etc. – essentially, capturing the demand side (we also asked about those who buy such services on platforms, but selling is the focus here). This approach allows us to count gig workers regardless of whether they have ‘regular’ jobs or not.

The data leads to an estimate of around 27 million for the 20 Global South countries studied so far (see graph below). The estimate for India alone is around 14 million (surveyed in late 2017).


While it can be argued that some data is better than none, it is crucial to recognize the limitations of the data, as above, to identify what the data can tell us and what it can’t. We recognize that the numbers in the graph are not a complete picture, they most definitely under-estimate the size of the gig economy. This is for a number of reasons. Firstly the AfterAccess survey does not cover those below 15 and those above 65 years of age; while the above 65s are negligible in gig work today, the under 15s could potentially include richer and more educated kids doing some kind of gig work. Secondly, particularly in the Asian countries (including India, the most populous) the survey questions did not cover the universe of types of gig work, just three types (transport/taxi services, micro-work and hired help). Finally, the bases are low in the Asian and African countries, as Internet use is still nothing higher than 36% of the 15-65 population in these two regions, therefore the precision of the estimates are reduced.

As mentioned, AfterAccess only covers 20-odd countries of the Global South; what about the rest? Clearly a lack of data is a problem. It may be tempting to look at the supply side, i.e., counting the number of gig workers or sellers on platforms. But the obvious problems are that there can be huge amounts of overlap between platforms; we know from our qualitative research that many platform workers tend to register with more than one. Moreover it would be impossible to enumerate the universe of platforms, even if platforms were willing to share data. The iLabour Project does attempt to quantify the gig economy by counting the numbers of projects/tasks posted on the five largest English-language online labor platforms (the researchers behind the initiative argue that this represents at least 70% of the market)—so from the supply side. Obviously a good portion of the market is left out, particularly non-English platforms are entirely left out; but the bigger limitation is that it doesn’t tell us anything about the number of human beings engaged in gig work.

At best, representative demand side surveys triangulated with multiple other data sources might be the best we can do to come up with conservative estimates. But this is as long as survey questions are asked in the right way, respondents understand them correctly, and sampling allows for representation at extrapolation at the national level, at a minimum.

But the larger question is who will fund these on a large scale and continuing basis: even the US Bureau of Labor Statistics took 12 years to rally up the will and funds to collect this kind of survey data, and it still had problems.

More on AfterAccess here. The survey has been carried out in 21 countries from 2017 to date, but only 20 are shown here, as the last country (Sri Lanka) data is still being analyzed.


The exact survey questions were as follows:

Asia:

Have you ever sold any of the following services or taken on any jobs through the Internet or apps? (a) Transport/ taxi services (e.g., through Uber,); (b) Microwork/freelancing work (e.g., through Upwork, Fiverr); (b) Hired help.

 Africa and Latin America:

Some people find paid jobs or tasks by connecting directly with people who want to hire them using a website or mobile app. In the last year, have you earned money by taking on jobs of this type? (For example: Uber)

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