Hop on - hop off: TransMilenio's demand reaction to a fare increase
This research uses the fare change occurred in February 2018 in Bogota´s Bus Rapid Transit System (TransMilenio) to estimate the short-run reaction of general and low-income users when facing a fare increase. Moreover, the exercise identifies differences between sporadic and frequent users. The fare...
- Autores:
-
Beltrán Sánchez, Carlos Andrés
- Tipo de recurso:
- Fecha de publicación:
- 2021
- Institución:
- Universidad de los Andes
- Repositorio:
- Séneca: repositorio Uniandes
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.uniandes.edu.co:1992/55430
- Acceso en línea:
- http://hdl.handle.net/1992/55430
- Palabra clave:
- Fare
Elasticity
Ridership
Public transportation
Equity
Economía
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
Summary: | This research uses the fare change occurred in February 2018 in Bogota´s Bus Rapid Transit System (TransMilenio) to estimate the short-run reaction of general and low-income users when facing a fare increase. Moreover, the exercise identifies differences between sporadic and frequent users. The fare policy increased fares in 5% for the user groups studied. The results found show that, two months after the fare policy implementation, ridership responded in the expected direction, implying reduction of 18% in demand of general-sporadic users and a reduction of 9.5% in demand of general-frequent users. Low-income users showed reductions of 5.4% and 2.2% in sporadic and frequent users respectively. Implied elasticities are also calculated using the arc method showing equivalent results. In addition, to estimate fare sensitivities considering spatial, socioeconomic and time-of-day heterogeneity within groups, I used a clustering algorithm methodology based on the station-demand profiles and an indicative average per capita income associated with the station catchment area. Results revealed that general users in low income areas showed the lowest elasticity values, while low-income users in low income areas showed the highest reactions facing the policy, in particular during peak hours. These estimates are relevant for policymakers considering alternative pricing structures for Bus Rapid Transit (BRT) systems. |
---|