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The Quarterly Journal of Economics - Why you can't find a taxi in the wet and other job-related lessons from taxi drivers
Replicating and expanding the groundbreaking work of Camerer et al. ("Labor supply of New York City Cabdrivers: Quarterly Journal of Economics, 112, 407-441), who find that the pay resilience of New York taxi drivers' working times is negatively affected and that their labour offer behaviour is in line with dependency.
Conversely, my full recording of all journeys in New York taxi booths from 2009 to 2013 shows that riders are tending to react favorably to unexpected and expected gains in revenue potential. In addition, the likelihood of a change in shifts when using a discreet electoral stop scheme is strongly related in a positive way to the working time worked, but at best poorly related to the salary received.
While I find considerable disparity between the driver elasticity, the estimates of elasticity are generally favorable and seldom substantially so. In my opinion, new riders with lower elasticity are more likely to leave the sector, while riders who quickly adapt to being better optimisers (have higher elasticity of labour offer that grows with experience).
The results are in line with the neo-classical labour optimisation paradigm and suggest that the inclusion of profit losses and revenue references is not an important element in the day-to-day labour choices of taxi operators.
How New Yorkers can't find a taxi when it's raining
It takes exactly one wet night in New York City to realize that it is incredibly hard to find a taxi in New York City when it is raining. It' also incredibly hard to find out why. Of course, there might be more who are looking for a taxi when it is raining, but New York is a place that constantly strives to fulfill all wishes, sensible and distorted as well.
Cal Tech's first approach, kindly endorsed by Colin Camerer, is known as "Income Targeting". Taxi riders aspire every single passing working day to a certain level of revenue, and when they have reached that goal, they call it quitting. This means that on good dates, a taxi driver can stop early. Thus, the revenue pervertedly aimed at predicting that taxi riders will stop early on good mornings.
If you make $15 an h, you have to go 10hrs. Camerers and some researchers analysed 3,000 taximeter values to calculate drivers' revenues and found great backing for the revenue goal. From a taxi driver's point of view, rain should be "good" weather conditions - which is the case with the large number of possible tariffs - so taxi-drivers are probably quicker to reach their destination and go home.
So more New Yorkers hail in futile rains. However, in a new working document by Princeton economics expert Henry Farber, the concept of "income targeting" is relegated to the background. Farber compiled a sub-sample of this information (more than 116 million journeys in total) with the New York City Taxi movement's full five-year 2009-2013 traffic rain fall rate in Central Park every hour over the same amount of time.
No significant relationship was found between the driver per hour and urban rainfall. This alone is enough to disparage the concept of the target salary, Farber says, since it means that riders no longer make money in the rainy season and therefore have no incentives to stop early. So, if the taxi request is higher during a storm, why aren't the salaries higher?
Farber's brief response is that riding in the cold is uncomfortable. A few riders stop, but that is not because they have reached their revenue targets. A few riders just stop because it is less comfortable to ride in the wet, and there is no added advantage to continue.
There will be more in the way of brain discussion about why it is so difficult to get a taxi in the cold, like so many unanswered strokes of the hand, but an end to the real issue is in the offing. Excessive prices raise concern about justice and consumers' equity, especially when cabs are seen as part of the city's wider transport system, but the opportunity to make a boat load is certainly sufficient to lure the driver onto the road.
Over the long run, the problems with the advent of unmanned taxi fleet could disappear completely. They will not be concerned about achieving an earning goal, nor will they fear that riding in the cold will not be enjoyable. In the NIMBY mood, regulation at the location is a major driver of cost for low-income residential construction companies.