Here is the money quote:<p>> We can explain the entire gap with three factors. First, through the logic of
compensating differentials, hourly earnings on Uber vary predictably by location and time of week,
and men tend to drive in more lucrative locations. The second factor is work experience. Even
in the relatively simple production of a passenger’s ride, past experience is valuable for drivers. A
driver with more than 2,500 lifetime trips completed earns 14% more per hour than a driver who
has completed fewer than 100 trips in her time on the platform, in part because she learn where
to drive, when to drive, and how to strategically cancel and accept trips. Male drivers accumulate
more experience than women by driving more each week and being less likely to stop driving with
Uber. Because of these returns to experience and because the typical male Uber driver has more
experience than the typical female—putting them higher on the learning curve—men earn more
money per hour.
The residual gender earnings gap that persists after controlling for these two factors can be
explained by a single variable: average driving speed.
"Furthermore, while Uber now allows riders to tip their drivers in-app, this did not become available until June 2017, which is outside the scope of our data. We do not believe that cash tips – which were possible before
in-app tipping – had a material impact on driver earnings."<p>The study did not have any actual tip data for drivers. Tipping was always an option in Uber before June 2017, it just became mandatory for the app to ask a user after each ride. I really think the study is missing some crucial data surrounding tips.
This is interesting. What interventions can be made to reduce this pay gap? With the reasons in the paper, should this gap be corrected (eg, force maximum speed, pay higher for slow drivers but only gender specific, etc etc).
The entire point of the paper is to show that you can observe a statistical anomaly like wage disparity whenever you compare two different populations, even when you essentially control for job effectiveness and isolate out any influence from malicious discrimination. The Uber case is being used to crystallize an example where there exists a bias in the results, and yet it is clearly not due to prejudice. It is illustrating the point that just because there is a pay-gap doesn't mean the source of the pay-gap is employers who don't properly compensate their female employees. Non-malicious systematic influences can easily cause such an effect.<p>And yet you still have people in here wondering what we can do about this new problem, or how this just goes to show that it's really the SYSTEM that's biased, man. All I can do is shake my head at this point.
>Overall, our results suggest that, even in the gender-blind, transactional, flexible environment of the gig economy, gender-based preferences (especially the value of time not spent at paid work and, for drivers, preferences for driving speed) can open gender earnings gaps.<p>Not sure this is the right conclusion to draw. If Uber driving is less safe for female drivers, it's hardly a "gender-based preference" that's driving the gap. If women are spending more of their flexible hours doing housework or caring for children than men do, this may not be a "preference". While the paper does a great job identifying factors correlated with lower income, does it really indicate an individual's "preference", or does it indicate that the situation they find themselves in either enables or prevents uber participation?