Breaking the Gig Ceiling: Unveiling the Gender Pay Gap in the Freelance Frontier

In the United States, women are more likely than men to work in service-related occupations, including health care, education, leisure, and other services, accounting for over 43.2% of women's jobs compared to only 24.8% of men's jobs. Despite that, a pay gap still exists. On average through all industries, women earned a staggering 17% less than men. But today, we are honing in on one industry: the rideshare industry, the black horse of transportation in recent years ever since the pioneer and popularization of Uber and Lyft. But before we dive into the pay gap, what makes the pay gap situation in ridesharing companies different?

First, critics of the platform economy cite the conditions of workers who have less job security than those in the traditional labor market and are subject to algorithmic control and

manipulation. It has already been explored in this blog the controversies and potential risks of the misclassification between "employee" and "independent contractors." To sum up, a rideshare driver is classified as an independent contractors but only possesses certain rights endowed to the traditional classification of the independent contractors. For example, they are not able to have exert control over their own wages.

Second, wage volatility in the gig economy is much more prominent than the traditional economy, especially in the service industry, where tipping culture greatly affects a drivers wage. But wage volatility exerts another negative effect: it disproportionately affects women.

Women have greater earnings volatility than men, partly because they are more likely to shift between full- and part-time jobs or leave the workforce. This greater likelihood of transitioning between different employment statuses contributes to fluctuations in their earnings, no different to the patterns observed in the ridesharing economy.

Furthermore, research indicates that when considering labor market volatility and trade preferences, working women express more negative employment prospects than men. This suggests that women may be more sensitive to labor market volatility, potentially due to structural discrimination and greater concerns for job flexibility.

This suggests that wage volatility may exert a more negative impact on women compared to men, and in a job like rideshare freelancing where wage volatility is prevalent, its gendered impacts and existence is undeniable.

So, what is the wage gap? Why does it exist? And finally, and most difficultly, what can be done?

Simply put, the wage gap is the phenomena which is that men in the ridesharing industry earn roughly 7% more per hour than women on average. A data conducted in Chicago with over 1 million + Uber drivers found a marginal, but yet stark difference in pay differences, along with other factors.

This table shows that men, on average, seem to earn more but also work much more than the average women in Uber.

But why?

Existing literature attributes four primary reasons. Two of which are more "direct" - per se, and two of which are more systemically entrenched, which will be explored in future posts.

First, men are more "efficent" - that is saying they have a higher driving speed compared to women, so they are able to perform more tasks in a shorter amount of time. According to a study from UChicago, increasing speed also increases driver earnings. Men’s higher driving speed appears to result from preferences as we see no evidence that drivers respond to the incentive to drive faster. Men’s higher average speed and the productive value of speed for Uber and the drivers (and, presumably, the passengers) enlarges the pay gap in this labor market.

Moreover, men also appear to have more "experience" - according to existing literature, an unitary increase in the work experience approximated as time spent in the workforce increases earnings by one percent. Moreover, an additional month spent using the platform increases earnings by five and a half percent. This is applicable in the gendered case as when a person learns how to better gamify the app, they may be able to optimize their working time around high-value rides, for instance. As is the same case for taxi drivers, men have conventionally been historically and presently using the app for a much longer time, leading to higher earnings.

The other two causes - living area and domestic duty - will be explored in a later article.