Skip to main content
Log in

Fare discrimination and daily demand distribution in the BRT system in Bogotá

  • Case Study and Application
  • Published:
Public Transport Aims and scope Submit manuscript

Abstract

Bogotá transport authority changed Bus Rapid Transit (Transmilenio) fares in August 2012 to manage congestion, particularly during peak hours. They reduced fares and implemented fare discrimination between peak and off-peak hours to balance demand and make the system more affordable. To estimate the variation in the relative distribution of daily demand between peak and off-peak hours, we used information pertaining to passenger demand on working days. Our main data source was the number of entrances into Transmilenio stations daily between 2011 and 2013. The data before the fare intervention was gathered between March 2011 and July 2012. Post intervention data was gathered between August 2012 and December 2013. We assumed that the users’ observable characteristics did not change either before or after the intervention was carried out. The fares decreased from a flat fare of COP 1750 (1 USD = 1780 COP in August 2012) to COP 1700 in peak hours and to COP 1400 in off-peak hours. This paper proposes a fixed effects model to estimate the effect of fare reduction in the ratio between peak and off-peak ridership hours. The results suggest that fare reduction produced changes in demand behaviour between peak and off-peak hours, reducing the peak to off-peak demand ratio (P/oP) by around 9%. This change has different levels of impact depending on the income levels associated with each Transmilenio station, with a stronger impact in low-income zones.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Source: own elaboration with 2011 mobility survey

Fig. 2

Source: own elaboration with 2005, 2011 and 2015 mobility surveys

Fig. 3

Source: entrances by station for the TM system 2011–2013

Fig. 4

Source: entrances by station for the TM system 2011–2013

Fig. 5

Source: own elaboration

Fig. 6
Fig. 7

Source: own elaboration

Fig. 8

Similar content being viewed by others

Notes

  1. Between 2010 and 2016 the number of motorcycles increased by 124% (CCB 2017).

  2. Currently the authors are working on an estimation of price/demand elasticities for TM.

  3. Soacha is the most important of the Bogotá’s neighborhood municipalities. This municipality has about 510,000 inhabitants. In practice, it is part of Bogotá city forming a functional area, which has been emerging as the city gradually extends beyond its administrative boundaries.

  4. 2011 USD.

  5. This is not part of our study.

References

  • Batarce M, Muñoz JC, Ortúzar JdD (2016) Valuing crowding in public transport: implications for cost-benefit analysis. Transp Res Part A Policy Pract 91:358–378

    Article  Google Scholar 

  • CCB (2017) Observatorio de Movilidad de Bogotá. Balance de Movilidad 2007–2016. In: Reporte anual de Movilidad 2016. Cámara de Comercio de Bogotá, Universidad de los Andes, Bogotá. ISSN 2027-209X. http://hdl.handle.net/11520/19561

  • Cirillo C, Liu Y (2015) Measuring transit service impacts on vehicle ownership and use. Public Transport 7(2):203–222

    Article  Google Scholar 

  • Cirillo C, Serulle NU (2016) Transportation needs of low income population: a policy analysis for the Washington D.C. metropolitan region. Public Transport 8(1):103–123

    Article  Google Scholar 

  • Cullinane S (2002) The relationship between car ownership and public transport provision: a case study of Hong Kong. Transp Policy 9(1):29–39

    Article  Google Scholar 

  • Dargay J, Gately D (1997) The demand for transportation fuels: imperfect price-reversibility? Transp Res Part B 31(1):71–82

    Article  Google Scholar 

  • Gilbert A (2008) Bus rapid transit: is Transmilenio a miracle cure? Transport Rev 28(4):439–467

    Article  Google Scholar 

  • Glaister S (1974) Generalised consumer surplus and public transport pricing. Econ J 84(336):849–867

    Article  Google Scholar 

  • Guerra G, Bocarejo JP (2013) Congestion cost in mass transit systems; pricing and investment policy implications—case study: Bogota’s BRT system. In: 13th world conference on transportation research, Rio de Janeiro

  • Guzman LA, Oviedo D, Bocarejo JP (2017) City profile: the Bogotá metropolitan area that never was. Cities 60(Part A):202–215

    Article  Google Scholar 

  • Haywood L, Koning M (2015) The distribution of crowding costs in public transport: new evidence from Paris. Transp Res Part A Policy Pract 77:182–201

    Article  Google Scholar 

  • Hensher DA (2008) Assessing systematic sources of variation in public transport elasticities: some comparative warnings. Transp Res Part A 42(7):1031–1042

    Google Scholar 

  • Hidalgo D, Pereira L, Estupiñán N, Jiménez PL (2013) TransMilenio BRT system in Bogota, high performance and positive impact—main results of an ex-post evaluation. Res Transp Econ 39(1):133–138

    Article  Google Scholar 

  • Jara-Díaz SR, Gschwender A, Ortega M (2014) The impact of a financial constraint on the spatial structure of public transport services. Transportation 41(1):21–36

    Article  Google Scholar 

  • Kash G, Hidalgo D (2014) The promise and challenges of integrating public transportation in Bogotá, Colombia. Public Transport 6(1):107–135

    Article  Google Scholar 

  • Litman T (2012) Transit price elasticities and cross-elasticities. Victoria Transport Policy Institute, Victoria. http://www.vtpi.org/tranelas.pdf

  • McCollom BE, Pratt RH (2004) Transit pricing and fares, traveler response to transportation system change, chap 12. In: Report 95. TCRP report. http://onlinepubs.trb.org/onlinepubs/tcrp/tcrp_rpt_95c12.pdf

  • Monchambert G, Haywood L, Koning M (2017) Crowding in public transport: who cares and why? Transp Res Part A Policy Pract 100:215–227

    Article  Google Scholar 

  • Oum TH, Waters WG, Yong J (1992) Concepts of price elasticities of transport demand and recent empirical estimates. J Transport Econ Policy 26(2):139–154

    Google Scholar 

  • Panzar JC (1976) A neoclassical approach to peak load pricing. Bell J Econ 7(2):521–530

    Article  Google Scholar 

  • Paulley N, Balcombe R, Mackett R, Titheridge H, Preston J, Wardman M, Shires J, White P (2006) The demand for public transport: the effects of fares, quality of service, income and car ownership. Transp Policy 13(4):295–306

    Article  Google Scholar 

  • Prud’homme R, Koning M, Lenormand L, Fehr A (2012) Public transport congestion costs: the case of the Paris subway. Transp Policy 21:101–109

    Article  Google Scholar 

  • PTEG (2002) Overcrowding on public transport, vol I. Passenger Transport Executive Group, House of Commons Transport Select Committee, London. https://publications.parliament.uk/pa/cm200203/cmselect/cmtran/201/201.pdf

  • SDM (2016) Encuesta de Movilidad de Bogotá 2015, Cartilla final. Secretaría Distrital de Movilidad de Bogotá, Secretaría de Movilidad de Bogotá. http://www.movilidadbogota.gov.co/web/?q=node/1990

  • Tirachini A, Hensher DA, Rose JM (2013) Crowding in public transport systems: effects on users, operation and implications for the estimation of demand. Transp Res Part A Policy Pract 53:36–52

    Article  Google Scholar 

  • Vickrey WS (1963) Pricing in urban and suburban transport. Am Econ Rev 53(2):452–465

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Luis A. Guzman.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Guzman, L.A., Moncada, C.A. & Gómez, S. Fare discrimination and daily demand distribution in the BRT system in Bogotá. Public Transp 10, 191–216 (2018). https://doi.org/10.1007/s12469-018-0181-7

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12469-018-0181-7

Keywords

Navigation