For example, one of the big differences in the studies was how they accounted for "working." One did with app open and the other did idle time that directly led to rides. So if Uber and Lyft are required to pay for idle time, how are they going to handle people that pass on rides and just sit idle? Do you get banned from the platform if you pass on x amount of rides? I'd imagine whatever the policy (not stated in the article) is going to get harsher if they aren't paid by the ride and rather by a combination of hourly and ride. Since it is clearly difficult to actually determine hours working. Or maybe I'm over thinking it and the amount of people sitting idle is actually really low where it isn't a big deal. Does anyone know?
[0] Berkeley released this comparison which is kinda odd and biases towards the lower wage study. The odd things are like #4 how they say the high wage study is void because it includes tips and technically the state doesn't count tips as hourly wage, but if we're talking about take-home that's an important number. https://irle.berkeley.edu/files/2020/07/Comparison-of-two-Se...
I wish EVERY policy decision was structured this way. Tell me the groups, tell me the trade offs, then say why you've chosen X perspective as paramount, and explain what policy helps most from that perspective, and the costs to other groups.
I am fully aware that is never going to happen, but it would be lovely if it did.
It's hard to summarize, but I pasted the closest to a summary below. The Parrott and Reich study is the one commissioned by the Seattle Office of Labor Standards and City Council:
> At this point, there’s no real point in groping through the wage, expense or hours calculations for either study; the underlying data in the Parrott and Reich study is garbage, and both studies skew their analysis and recommendations in the direction that favors the one who commissioned their study. Instead, we should be focused on the key policy questions, and forcing city officials to be transparent about who they are prioritizing in the policy decisions they are making in setting a minimum wage. Once the policy questions are answered, there is enough raw data in the Cornell report to calculate out the proper minimum wage.
> The key policy question, one that drives so many others, is whether the city should prioritize full-time drivers over part-time and casual drivers. As we’ve seen above, it affects almost everything: what expenses to include, how much the system needs to try to maximize paid hours for full-time drivers, the economic model for the companies. According to the Uber/Lyft data set that Cornell analyzed, only 15% of TNC drivers are full-time, but for them the job is their livelihood. Should they be prioritized over people driving as a second job to help make ends meet or deal with emergency expenses? Should the city try to increase the number of full-time TNC driver jobs? Should the city be picking winners and losers at all between full-time and part-time drivers?