• Graduate Programs
  • Research
  • Browse our Courses
  • Events
    • Events Calendar
    • Events Archive
    • Summer School
      • Applied Public Policy Evaluation
      • Deep Learning
      • Development Economics
      • Economics of Blockchain and Digital Currencies
      • Economics of Climate Change
      • The Economics of Crime
      • Foundations of Machine Learning with Applications in Python
      • From Preference to Choice: The Economic Theory of Decision-Making
      • Inequalities in Health and Healthcare
      • Marketing Research with Purpose
      • Markets with Frictions
      • Modern Toolbox for Spatial and Functional Data
      • Sustainable Finance
      • Tuition Fees and Payment
      • Business Data Science Summer School Program
    • Tinbergen Institute Lectures
    • 2026 Tinbergen Institute Opening Conference
    • Annual Tinbergen Institute Conference
  • News
  • Summer School
    • Applied Public Policy Evaluation
    • Deep Learning
    • Development Economics
    • Economics of Blockchain and Digital Currencies
    • Economics of Climate Change
    • The Economics of Crime
    • Foundations of Machine Learning with Applications in Python
    • From Preference to Choice: The Economic Theory of Decision-Making
    • Inequalities in Health and Healthcare
    • Marketing Research with Purpose
    • Markets with Frictions
    • Modern Toolbox for Spatial and Functional Data
    • Sustainable Finance
    • Tuition Fees and Payment
  • Alumni

Yu, X., van den Berg, VincentA.C. and Li, Z.C. (2023). Congestion pricing and information provision under uncertainty: Responsive versus habitual pricing Transportation Research Part E: Logistics and Transportation Review, 175:1--28.


  • Journal
    Transportation Research Part E: Logistics and Transportation Review

In the face of capacity disruptions (due, for example, to traffic incidents or poor weather), information provision and congestion pricing are alleviating policies. We compare responsive pricing, whereby tolls vary with known or predicted traffic conditions, with habitual pricing, which only considers the probability distribution of possible traffic conditions. We do so under perfect information and imperfect information where travelers receive information from, for example, a weather report or route planning app. We find analytically that the habitual toll is a weighted average of the expected marginal external costs (MECs) over all states/information {\textquoteleft}signals{\textquoteright}, with weights depending on the capacity distribution and the {\textquoteleft}quality{\textquoteright} of the information. The responsive toll depends on the information received and equals the information-specific expected MEC. The two tolls will be more similar the more imperfect the information quality or the lower the uncertainty, and they are identical under no information or no uncertainty. Although responsive pricing raises welfare and lowers travel prices, the differences in effects between the two tolls tend to be tiny even under perfect information and high uncertainty. Considering that responsive pricing may be even more unpopular with the populace and costly to implement than habitual tolls, our study reveals the significance of the quality of information and the degree of uncertainty in deciding how to manage our roads.