Demand elasticity under congestion pricing: Evidence from managed lanes in California

Abstract

Empirical evidence on price elasticities under congestion pricing remains scarce, typically relying on discrete policy changes or low-frequency data that limit identification. Evidence remains extremely limited for managed lanes in interurban environments with time-of-day-varying tolls. Using high-frequency hourly data from two major California corridors, we estimate demand elasticity within a panel regression framework exploiting continuous variation in tolls across routes, hours, and days of the week. This identification strategy overcomes key limitations in the existing literature and enables estimation of short-run demand responses. We also analyze how responsiveness evolves over time, shedding light on medium-run behavioral adjustments. The results provide new evidence on user price sensitivity in managed lanes and contribute to the broader debate on whether congestion pricing effectively reduces congestion or primarily redistributes traffic, with implications for the design and evaluation of pricing policies.