Who Benefits from Surge Pricing?

Résumé

In the last decade, new technologies have led to a boom in dynamic pricing. I analyze the most salient example, surge pricing in ride hailing. Using data from Uber in Houston, I develop an empirical model of spatial equilibrium to measure the welfare effects of surge pricing. My model is composed of demand, supply, and a matching technology. It allows for temporal and spatial heterogeneity as well as randomness in supply and demand. I find that, relative to a counterfactual with uniform pricing, surge pricing increases total welfare by 3.53% of gross revenue. The gains mainly go to riders: rider surplus increases by 6.97% of gross revenue, whereas driver surplus and platform profits decrease by 1.97% and 1.42% of gross revenue, respectively. Disparities in driver surplus are magnified. Riders, on the other hand, are overwhelmingly better off.