Female Uber drivers make different driving decisions, either by choice or constraints, than male drivers, and it shows in their paychecks. | iStock/Republica
If you drive for car-sharing company Uber, you likely earn a bigger paycheck if you’re young and male.
Research from Stanford Graduate School of Business shows that a 60-year-old driver makes about 10% less per hour than a 30-year-old does, while a female driver makes about 7% less than a male. The discrepancies aren’t the result of unfair compensation packages; instead, driver preferences and constraints create the gaps, the research shows.
Uber pays drivers based on miles driven and minutes driving, with special bonuses award for, among other reasons, driving in certain rider-heavy locations or during busier times of the day. Younger, male drivers head to high-traffic areas during peak times, better understand how to use the platform, and drive faster. That translates to more riders per hour and more incentive-based pay.
“Uber was an exciting place to look at pay gaps and labor supply differences,” says Rebecca Diamond, a Stanford GSB professor of economics and coauthor of the pair of studies. Outside factors that might contribute to unfair bias in pay — such as a manager’s preference for hiring younger workers — don’t play into this market, she notes. “Because the pay structure of Uber is so simple and transparent, we had all the necessary ingredients to decompose the gender and age gaps.”
Youth’s Advantage
To examine income imbalance among age groups, the researchers analyzed data from 292,514 drivers in the Chicago area on six metrics that make a difference in pay: wait time, distance to pick up passengers, distance on trips, speed, surge bonus, and incentive payments (for example, Uber offers drivers extra pay if they complete a certain number of rides by a certain date).
Younger drivers dominate four of these six factors. They wait almost a minute less for each ride, are closer to each pickup, drive more during surge price times, and earn higher incentive pay. They tend to drive downtown where traffic is heavier and where they can find more riders with less downtime between rides. They also are more likely to work on Friday and Saturday nights, more lucrative hours for an Uber driver.
Older drivers spend more time in the suburbs and thus have farther to go to pick up passengers. They’re also more likely to work on weekdays during daylight hours.
The data presents an interesting dilemma for those looking to the gig economy as a transition to full retirement, Diamond notes. “At first blush you would think Uber could be this perfect job. It’s super flexible, you can still get paid, and they’re not ageist when it comes to hiring older people,” Diamond says. But traditional careers usually don’t penalize a dip in productivity as you age — you might be most productive in your 40s and 50s but you won’t get a pay-cut in your 60s. At Uber, “you’re really getting paid for your productivity level. Switching away from a career job to this flexible job might entail quite large pay cuts.”
Women’s Preferences
Next, Diamond and researchers studied data from over a million drivers and found that women on average drive more slowly (which means fewer overall passengers), drive in less crowded areas, work fewer hours, spend more time away from the app, and have less experience using the app than the male drivers do. Experience makes a significant difference. Drivers who have completed 2,500 trips earn 14% more per hour than drivers who have fewer than 100 trips, because the experienced driver learns where and when to drive and how to strategically cancel or accept trips.
Women also are less likely to drive in areas of higher crime or with more bars, “suggesting women are willing to take a pay cut in exchange for avoiding picking up drunk riders or dealing with unsafe areas,” Diamond notes. “It’s not really fair that you should be paid less because people are more likely to give you a hard time.”
Minding the Gap
Overall, the findings show how different driver choices, propelled either by preferences or constraints, have a real impact on hourly earnings outside of gender or age bias, she says.
Whether male or female, old or young, “you’re basically being paid for how quickly you can get to places and take good routes,” Diamond says. Companies might be able to tighten their pay gaps by offering more education on how to use their platform, for example, or making it easier to return to the platform after an absence. “If you can make a worker more productive, that’s great,” she says.
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