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An empirical analysis of taxi, Lyft and Uber rides: Evidence from weather shocks in NYC

Abel Brodeur and Kerry Nield

Journal of Economic Behavior & Organization, 2018, vol. 152, issue C, 1-16

Abstract: Using all taxi, Lyft and Uber rides in New York City, we show that the number of Uber and Lyft rides is significantly correlated with whether it rained. The number of Uber (Lyft) rides per hour is about 22 (19)% higher when it is raining, while the number of taxi rides per hour increases by only 5% in rainy hours-suggesting that surge pricing (prime time) encourages an increase in supply. We show that while the number of taxi rides, passengers and fare income all significantly decreased after Uber entered the market in May 2011, taxis do not respond differently to increased demand in rainy hours than non-rainy hours since the entrance of Uber. Last, we test whether Lyft’s entry in the market affected Uber. Our estimates suggest that Uber was still growing after Lyft entered the market, but that Uber rides during rainy hours decreased by about 9%. Our findings suggest that dynamic pricing make Lyft and Uber drivers compete for rides when demand suddenly increases, i.e., during rainy hours.

Keywords: Rain; Taxi; Uber; Lyft; Dynamic pricing (search for similar items in EconPapers)
JEL-codes: D01 D03 L92 J22 (search for similar items in EconPapers)
Date: 2018
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Related works:
Working Paper: Has Uber Made It Easier to Get a Ride in the Rain? (2017) Downloads
Working Paper: Has Uber Made It Easier to Get a Ride in the Rain? (2016) Downloads
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Journal of Economic Behavior & Organization is currently edited by Houser, D. and Puzzello, D.

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