Working Paper: NBER ID: w27087
Authors: Nicholas Buchholz; Laura Doval; Jakub Kastl; Filip Matějka; Tobias Salz
Abstract: We recover valuations of time using detailed data from a large ride-hail platform, where drivers bid on trips and consumers choose between a set of rides with different prices and wait times. Leveraging a consumer panel, we estimate demand as a function of both prices and wait times and use the resulting estimates to recover heterogeneity in the value of time across consumers. We study the welfare implications of personalized pricing and its effect on the platform, drivers, and consumers. Taking into account drivers’ optimal reaction to the platform’s pricing policy, personalized pricing lowers consumer surplus by 2.5% and increases overall surplus by 5.2%. Like the platform, drivers benefit from personalized pricing. ETA-based pricing– where different prices are set for various wait times and where extensive use of consumer data is not required–can capture a significant portion of the profits garnered from personalized pricing, while simultaneously benefiting consumers.
Keywords: Value of Time; Ride-Hailing; Consumer Choice; Elasticity; Transportation Economics
JEL Codes: L0
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| price elasticities (D12) | waiting-time elasticities (J29) |
| net value of time (NVOT) (J17) | consumer willingness to pay (D11) |
| value of time during non-work hours (J17) | value of time during work hours (J29) |
| individual differences (L15) | variation in value of time (D46) |
| uniform value of time for highway procurement (R48) | mispricing of time costs (D15) |