Do users respond to congestion pricing? Evidence on demand elasticity from managed lanes

Abstract

While congestion pricing has been widely implemented, empirical evidence on price elasticities remains limited and often relies on discrete policy changes or low-frequency data, which constrain identification. Moreover, there is virtually no econometric evidence on demand elasticity in 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 that exploits variation in tolls across routes, hours, and days of the week. This approach allows us to identify short-run demand responses from continuous within-sample price variation, overcoming key limitations in the existing literature. We also analyze how responsiveness evolves over time, capturing medium-run behavioral adjustments. Our results provide new evidence on user price sensitivity in managed lanes settings and contribute to a more robust understanding of congestion pricing as a demand management tool. The findings have implications for the design and evaluation of pricing policies, particularly in assessing whether such schemes effectively mitigate congestion or primarily redistribute traffic.