Congestion pricing and information provision under uncertainty: Responsive versus habitual pricing

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 ‘signals’, with weights depending on the capacity distribution and the ‘quality’ 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.