Fickle Fingers: Ride-Hail Surge Factors and Taxi Bookings

Abstract

We study the role of ride-hailing surge factors on the allocative efficiency of taxis by combining a reduced form estimation with structural analyses using machine-learning-based demand predictions. We estimate an upper-bound of the cross-price elasticity of taxi bookings to surge factors of only 0.26, but incorporating surge factors into a demand-prediction model improves the out-of-sample accuracy by 12-15%. Our structural analyses based on a driver guidance system finds the improved accuracy reduces drivers' vacant roaming times by 9.4% and increases average trips per taxi by 2.3%, suggesting the price information is valuable across platforms, even if elasticities are low.