Uber is changing more than the transportation business; it’s changing how economists think about rational behavior.
For decades, economists have been trying to understand how we humans make economic decisions. Their observations of how, when and why we buy have led to “laws” that we all have incorporated into our daily lives, such as the law of supply and demand. When something costs more, we buy less of it; when it becomes less costly, we buy more. But do we act as rationally about earning as we do spending?
Economists have spent decades studying the working habits of independent cab drivers to determine patterns of rational economic behavior. In a 1997 study, economists observed that drivers worked longer hours when business is slow, and quit earlier when business was brisk. This is the opposite of what would seem to be rational behavior, and has real implications in this era of on-demand and self-directed work.
Enter Uber, the company that contracts with independent drivers who can set their own hours based on personal preference. An Uber data scientist published a paper in 2016 that used Uber’s database of Chicago driver hours and salary to determine how they made decisions about when and how much to work. The previous economic theory about drivers’ behavior was that they had an earning target in mind for the day, say $200. On busy days, they hit their goal early, so they quit early. Slow days meant they had to work longer to try to hit their target.
The problem with this theory is that drivers were giving up both income opportunity and leisure opportunity on slow days, making their choice irrational. The Uber study author writes that “While violations of rationality are not uncommon, they are rarely found in decisions with high stakes and repeated opportunities to learn.” Uber drivers determines their own schedules of work and leisure, and they learn quickly that leisure is not free — it has an opportunity cost, that is the amount of money the driver could have earned by working.
Uber drivers earn more during peak hours, since Uber charges higher rates when demand spikes. Specific drivers may take time to figure out demand patterns in their preferred driving area. After exhaustive economic analysis, the Uber study author found that drivers learn quickly how to maximize earning and leisure. Income targeting behavior (quitting early on good days, staying later on slow days) was a rookie mistake, and quickly corrected by drivers after about 30 shifts’ worth of experience.
This is an important principle, since many more workers are entering the Gig Economy. Workers use target earnings as a proxy for success until they learn over time when to work, how much to do, and what kind of work is most profitable. Workers who don’t figure it out drop out, claiming that the job just doesn’t pay. In the future, when more and more of us will rely on side gigs and 1099 opportunities to supplement our income, we’ll all need to become our own data scientists. We all have the opportunity to earn more and have more leisure if we use our time well. Becoming a rational economic actor means staying long enough in the market to learn from what you earn.
Candace Moody is vice president of communications for CareerSource Northeast Florida. Her column appears every Wednesday in the Times-Union, and she can be reached at firstname.lastname@example.org.