Surge Pricing Solves the Wild Goose Chase

29 Pages Posted: 28 Dec 2016 Last revised: 14 Feb 2017

Juan Camilo Castillo

Stanford University - Department of Economics

Daniel T. Knoepfle

Uber Technologies Inc.

E. Glen Weyl

Microsoft Research; Yale University

Date Written: February 13, 2017

Abstract

Why is dynamic pricing more prevalent in ride-hailing apps than movies and restaurants? Arnott (1996) observed that an over-burdened taxi dispatch system may be forced to send cars on a wild goose chase to pick up distant customers when few taxis are free. These chases occupy taxis and reduce earnings, effectively removing cars from the road and exacerbating the problem. While Arnott dismissed this outcome as a Pareto-dominated equilibrium, we show that when prices are too low relative to demand it is the unique equilibrium of a system that uses a first-dispatch protocol (as many ride-hailing services have committed to). This effect dominates more traditional price theoretic considerations and implies that welfare and profits fall dramatically as price falls below a certain threshold and then decline only gradually move in price above this point. A platform forced to charge uniform prices over time will therefore have to set very high prices to avoid catastrophic chases. Dynamic “surge pricing” can avoid these high prices while maintaining system functioning when demand is high. We show that pooling can complicate and exacerbate these problems.

Keywords: wild goose chases, ride-hailing, surge pricing, dynamic pricing, hypercongestion

JEL Classification: D42, D45, D47, L91, R41

Suggested Citation

Castillo, Juan Camilo and Knoepfle, Daniel T. and Weyl, E. Glen, Surge Pricing Solves the Wild Goose Chase (February 13, 2017). Available at SSRN: https://ssrn.com/abstract=2890666

Juan Camilo Castillo

Stanford University - Department of Economics ( email )

Landau Economics Building
579 Serra Mall
Stanford, CA 94305-6072
United States

Daniel T. Knoepfle

Uber Technologies Inc. ( email )

1455 Market St
San Francisco, CA 94103-1331
United States

Eric Glen Weyl (Contact Author)

Microsoft Research ( email )

641 Avenue of the Americas
7th Floor
New York, NY 10011
United States
(857) 998-4513 (Phone)

HOME PAGE: http://www.glenweyl.com

Yale University ( email )

28 Hillhouse Ave
New Haven, CT 06520-8268
United States

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