Public transport fare elasticities from smartcard data: Evidence from a natural experiment

• Published in: Transport policy Vol. 105; pp. 35 - 43
• Main Authors: Kholodov, Yaroslav, Jenelius, Erik, Cats, Oded, van Oort, Niels, Mouter, Niek, Cebecauer, Matej, Vermeulen, Alex
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01-05-2021
• Subjects: Automatic fare collection data; Fare elasticity; Fare policy; Public transport; Smartcard data; Transit; Public transport; Fare policy; Transit; Fare elasticity; Smartcard data; Automatic fare collection data
• ISSN: 0967-070X; 1879-310X; 1879-310X
• DOI: 10.1016/j.tranpol.2021.03.001

This paper develops a method for analysing the elasticity of travel demand to public transport fares. The methodology utilizes public transport smartcard data for collecting disaggregate full population data about passengers’ travel behaviour. The study extends previous work by deriving specific fare elasticities for distinct socioeconomic (e.g., car ownership and income) groups and public transport modes (metro, trains and buses), and by considering the directionality of the fare change. The case study involves a public transport fare policy introduced by the regional administration of Stockholm County in January 2017, where the zonal fare system for single-trip tickets was replaced by a flat-fare policy. The overall fare elasticity of travel funds is found to be −0.46. User sensitivity grows along with the journey distance. Metro users demonstrate the lowest sensitivity, followed by bus and commuter train riders. Low socioeconomic groups, in particular with respect to car ownership, tend to be less sensitive than the high-factor groups. In addition to the direct effect of changed fares, simplification and unification of the fare scheme appears to have substantially contributed to its attractiveness. The flat fare may allow the geographic disparity of public transport travel to be reduced and new users to be attracted from remote areas who are more prone to own cars.
•Method for calculating fare elasticities from smart card validation records.•Impacts of zone-based to flat fare scheme change for different user groups.•Fare elasticities vary across socioeconomic groups and public transport modes.•Regular travel, low income, trip distance, train use increase fare sensitivity.•Fare scheme simplification contribute to attracting travel demand.