Learning to accept welfare-enhancing policies: an experimental investigation of congestion pricing

Welfare-enhancing policies such as congestion pricing are argued to improve efficiency in situations with externalities. Unfamiliarity and lack of any personal experience with such policies, however, can hinder their implementation; particularly the ex-ante uncertainties of incidences of gains and losses as well as debates regarding equity concerns and how to recycle revenues often stymies implementation. This paper employs a laboratory experiment with heterogeneous users to investigate the effectiveness and acceptability of a toll in a six-player-two-route congestion game. To measure acceptability and how it is affected by experience with the toll, we conduct referenda before, during, and after subjects experience a congestion problem and a toll. The experiment employs a $$2\times 2$$ 2 × 2 design that varies two treatments: the rate of revenue reallocation and the level of information before the final vote. After an experiential learning phase, congestion pricing is found to curb congestion effectively, and although some subjects do not vote in their monetary self-interest initially, the majority does so after experiencing the congestion pricing policy. Data on worldviews and beliefs are collected and matched to voting behavior to examine the evolution of how experience determines acceptability. Some worldviews and beliefs can predict voting behavior and the timing of when an individual finds a toll (un)acceptable.