Estimating multimodal transit ridership with a varying fare structure
This paper studies public transport demand by estimating a system of equations for multimodal transit systems where different modes may act competitively or cooperatively. Using data from Athens, Greece, we explicitly correct for higher-order serial correlation in the error terms and investigate two, largely overlooked, questions in the transit literature; first, whether a varying fare structure in a multimodal transit system affects demand and, second, what the determinants of ticket versus travelcard sales may be. Model estimation results suggest that the effect of fare type on ridership levels in a multimodal system varies by mode and by relative ticket to travelcard prices. Further, regardless of competition or cooperation between modes, fare increases will have limited effects on ridership, but the magnitude of these effects does depend on the relative ticket to travelcard prices. Finally, incorrectly assuming serial independence for the error terms during model estimation could yield upward or downward biased parameters and hence result in incorrect inferences and policy recommendations.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 45 (2011)
Issue (Month): 2 (February)
|Contact details of provider:|| Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description|
|Order Information:|| Postal: http://www.elsevier.com/wps/find/supportfaq.cws_home/regional|
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Antonio García-Ferrer & Marcos Bujosa & Aránzazu de Juan & Pilar Poncela, 2006. "Demand Forecast and Elasticities Estimation of Public Transport," Journal of Transport Economics and Policy, University of Bath, vol. 40(1), pages 45-67, January.
- Beach, Charles M. & MacKinnon, James G., 1978.
"Full maximum likelihood estimation of second- order autoregressive error models,"
Journal of Econometrics,
Elsevier, vol. 7(2), pages 187-198, June.
- Charles M. Beach & James G. MacKinnon, 1977. "Full Maximum Likelihood Estimation of Second-Order Autoregressive Error Models," Working Papers 259, Queen's University, Department of Economics.
- Vande Walle, Stefaan & Steenberghen, Therese, 2006. "Space and time related determinants of public transport use in trip chains," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(2), pages 151-162, February.
- Hensher, David A., 2008. "Assessing systematic sources of variation in public transport elasticities: Some comparative warnings," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(7), pages 1031-1042, August.
- Granger, C. W. J., 1981. "Some properties of time series data and their use in econometric model specification," Journal of Econometrics, Elsevier, vol. 16(1), pages 121-130, May.
- Chiou, Yu-Chiun & Wen, Chieh-Hua & Tsai, Shih-Hsun & Wang, Wei-Ying, 2009. "Integrated modeling of car/motorcycle ownership, type and usage for estimating energy consumption and emissions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(7), pages 665-684, August.
- Su, Qing, 2010. "Travel demand in the US urban areas: A system dynamic panel data approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(2), pages 110-117, February.
- Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 39(3), pages 106-135.
- Engle, Robert F & Granger, Clive W J, 1987. "Co-integration and Error Correction: Representation, Estimation, and Testing," Econometrica, Econometric Society, vol. 55(2), pages 251-276, March.
- Peter Romilly, 2001. "Subsidy and Local Bus Service Deregulation in Britain: A Re-evaluation," Journal of Transport Economics and Policy, University of Bath, vol. 35(2), pages 161-193, May.
- Joyce M. Dargay & Mark Hanly, 2002. "The Demand for Local Bus Services in England," Journal of Transport Economics and Policy, University of Bath, vol. 36(1), pages 73-91, January.
- Ben-Akiva, Moshe & Morikawa, Takayuki, 2002. "Comparing ridership attraction of rail and bus," Transport Policy, Elsevier, vol. 9(2), pages 107-116, April.
- Paulley, Neil & Balcombe, Richard & Mackett, Roger & Titheridge, Helena & Preston, John & Wardman, Mark & Shires, Jeremy & White, Peter, 2006. "The demand for public transport: The effects of fares, quality of service, income and car ownership," Transport Policy, Elsevier, vol. 13(4), pages 295-306, July.
- Graham, Daniel J. & Crotte, Amado & Anderson, Richard J., 2009. "A dynamic panel analysis of urban metro demand," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(5), pages 787-794, September.
- Beach, Charles M & MacKinnon, James G, 1978. "A Maximum Likelihood Procedure for Regression with Autocorrelated Errors," Econometrica, Econometric Society, vol. 46(1), pages 51-58, January.
- Mackett, Roger L. & Edwards, Marion, 1998. "The impact of new urban public transport systems: will the expectations be met?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 32(4), pages 231-245, May.
- Karlaftis, Matthew & McCarthy, Patrick, 1999. "The Effect of Privatization on Public Transit Costs," Journal of Regulatory Economics, Springer, vol. 16(1), pages 27-43, July.
- FitzRoy, Felix & Smith, Ian, 1999. "Season Tickets and the Demand for Public Transport," Kyklos, Wiley Blackwell, vol. 52(2), pages 219-238.
- Li, Zheng & Rose, John M. & Hensher, David A., 2010. "Forecasting automobile petrol demand in Australia: An evaluation of empirical models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(1), pages 16-38, January. Full references (including those not matched with items on IDEAS)