Abstract
Problems in transit fare equity affect the daily commute of specific groups that depend mostly on public transportation. Previous studies showed that some routes present operational characteristics that increased the price charged to the users. To address this issue, a methodology to identify the routes that have fares much higher than expected, after considering operational parameters, is developed. This paper presents a methodology implemented to evaluate fare inequities in public transport networks. The case study is the bus public transport network in Costa Rica. The evaluation is performed using fare per kilometer as independent variable and operational variables, such as route length, monthly ridership and vehicle occupancy by using cluster analysis and Bayesian multilevel modelling. The results indicate that random coefficients models perform better than independent models for clustered data. Furthermore, the routes with higher differences between observed and estimated (i.e. expected) fares are the ones to be addressed first in individual audits, because these are the routes who charge higher operational costs into the fare, increasing inequity among the population.