Why You Can't Find a Taxi in the Rain and Other Labor Supply Lessons from Cab Drivers

By Henry S. Farber. Social Science Research Network, 2015

239 citations recorded by the source corpus.

I replicate and extend the seminal work of Camerer et al. ("Labor Supply of New York City Cabdrivers: One Day at a Time," Quarterly Journal of Economics, 112 [1997], 407–441), who find that the wage elasticity of daily hours of work for New York City taxi drivers is negative and conclude that their labor supply behavior is consistent with reference dependence. In contrast, my analysis of the complete record of all trips taken in NYC taxi cabs from 2009 to 2013 shows that drivers tend to respond positively to unanticipated as well as anticipated increases in earnings opportunities. Additionally, using a discrete choice stopping model, the probability of a shift ending is strongly positively related to hours worked but at best weakly related to income earned. I find substantial heterogeneity across drivers in their elasticities, but the estimated elasticities are generally positive and rarely substantially negative. I find that new drivers with smaller elasticities are more likely to exit the industry, whereas drivers who remain quickly learn to be better optimizers (have positive labor supply elasticities that grow with experience). These results are consistent with the neoclassical optimizing model of labor supply and suggest that consideration of gain-loss utility and income reference dependence is not an important factor in the daily labor supply decisions of taxi drivers. JEL Codes: D01, D03, J22.

Subfields: Automotive Engineering, Renewable Energy, Sustainability and the Environment, Transportation

View Paper: https://www.semanticscholar.org/paper/e111271cf4c1f183f8846f5e053400a1ddb0bf81

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Automotive Engineering

In Renewable Energy, Sustainability and the Environment

In Transportation

Citations in the corpus

The Value of Flexible Work: Evidence from Uber Drivers (2019, unknown): “In contrast, the “active” state is probably an underestimate of labor supply because it includes minutes on trip en route to obtain a passenger but does not include minutes in which the driver is waiting to be matched with a passengers.”
Using Big Data to Estimate Consumer Surplus: The Case of Uber (2016, background): “12 More specific to the literature on taxis, there are a very rich set of papers that have attempted to understand the supply side of the taxi market (see Camerer et al., 1997; Farber, 2005, 2008, 2015; Crawford and Meng, 2011).”
Ride-Sourcing modeling and pricing in non-equilibrium two-sided markets (2020, background): “There is little empirical consensus on whether one theory outperforms the other ( Farber, 2015 ).”
The Role of Surge Pricing on a Service Platform with Self-Scheduling Capacity (2017, background): “(See Farber 2015 and Chen and Sheldon 2017 for evidence that taxi drivers and Uber providers respectively make decisions based on rational expectations to maximize their return.)”
Surge pricing and labor supply in the ride-sourcing market (2018, background): “The neoclassical theory expects drivers to work longer when their wage rate is higher, while the income-targeting theory speculates that drivers have target levels after which they are more likely to stop (Camerer et al., 1997; Farber, 2015).”
Ridesourcing systems: A framework and review (2019, background): “The most influential and representative work is by Farber (2005, 2015 ), who also uses hours worked as the measure of labor supply and all drivers’ average hourly income as an instrumental variable to individual driver’s income rate.”