Simple vs. Optimal Congestion Pricing

Devansh Jalota, Xuan Di and Adam N. Elmachtoub

Papers from arXiv.org

Abstract: Congestion pricing has emerged as an effective tool for mitigating traffic congestion, yet implementing welfare or revenue-optimal dynamic tolls is often impractical. Most real-world congestion pricing deployments, including New York City's recent program, rely on significantly simpler, often static, tolls. This discrepancy motivates the question of how much revenue and welfare loss there is when real-world traffic systems use static rather than optimal dynamic pricing. We address this question by analyzing the performance gap between static (simple) and dynamic (optimal) congestion pricing schemes in two canonical frameworks: Vickrey's bottleneck model with a public transit outside option and its city-scale extension based on the Macroscopic Fundamental Diagram. In both models, we first analyze the revenue-optimal static and dynamic tolls, which have received limited attention in prior work. Across many practically relevant regimes, we show that revenue-optimal static tolls achieve at least two-thirds of the maximum achievable revenue and incur at most twice the minimum achievable system cost, with stronger and more general guarantees in the bottleneck model. We corroborate our theory with numerical results demonstrating that static tolls achieve roughly 80-90% of the dynamic optimal revenue while incurring at most an 8-25% higher total system cost than the minimum achievable.

Date: 2026-02, Revised 2026-10
New Economics Papers: this item is included in nep-des and nep-tre
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