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 build 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, and 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 3.66% of gross revenue. Only riders benefit: rider surplus increases by 6.52% of gross revenue, whereas driver surplus and Uber’s short-run profits decrease by 1.63% and 1.18% of gross revenue, respectively.