Skip to main content

Advertisement

Log in

Public transport demand: dynamic panel model analysis

  • Published:
Transportation Aims and scope Submit manuscript

Abstract

This paper presents an original essay that explains the mobility behaviour towards the public transport supply in Tunisia. This research aims to determine the key variables affecting an individual’s decision to travel by public transport and explains how the use of these means fits the mobility strategies. The dynamic panel model is applied to twelve Tunisian Regional companies, where we aim to analyze the behaviours of Tunisian citizens in the regions where Regional Transport Companies ensure the total service supply of urban, interurban and suburban public transport of travellers. The results show that mobility behaviours are subject to various variables. In particular, service quality, mean price and active population are the most significant variables regarding public transport demand in Tunisia.

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

Access this article

Price includes VAT (Finland)

Instant access to the full article PDF.

Similar content being viewed by others

Notes

  1. RTC of Béja, RTC of Bizerte, RTC of Gabés, RTC of Gafsa, RTC of Jendouba, RTC of Kairouan, RTC of Kasserine, RTC of Kef, RTC of Médenine, RTC of Nabeul, RTC of Sfax, RTC of Sousse.

  2. The basic model contains all the explicative variables. Following a correlation between the global income of all the inhabitants and the general occupation rate of population, we have estimated two other models where each of these variables is included in one model.

  3. RTC of Sousse serves 3 departments: Sousse, Monastir and Mahdia. RTC of Gabes serves 2 departments: Gabes and Gabéli. RTC of Gafsa serves 3 departments: Sidi Bouzid, Gafsa and Tozeur. RTC of Kef serves 2 departments: Kef and Siliana. RTC of Mednine serves 2 departments: Mednine and Tataouine. RTC of Nabeul serves 2 departments: Nabeul and Zaghouan.

References

  • Arellano, M., Bond, S.: Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Rev. Econ. Stud. 58, 277–297 (1991)

  • Balcombe, R., Mackett, R., Paulley, N., Preston, J., Shires, J., Titheridge, H., Wardman, M., White, P.: The demand for public transport: a practical guide. Transportation Research Laboratory Report, Transportation Research Laboratory, London (2004)

    Google Scholar 

  • Benham, J.L.: Analysis of a fare increase by use of a time-series and before-andafter data. Transp. Res. Rec. 877, 84–90 (1982)

  • Bates, J., : Transit operating costs and fare requirements forecasting by using regression modelling. Transp. Res. Rec. 877, 75–79 (1982)

  • Berechman, J.: Public transit economics and deregulation policy. North-Holland, Amsterdam (1993)

    Google Scholar 

  • Blundell, R., Bond, S.: Initial conditions and moment restrictions in dynamic panel data models. J. Econom. 68, 29–51 (1998)

  • Bonnel, P.: Prévoir la Demande de Transport, Presses de l'ENPC, pp. 425 (2004)

  • Bresson, G., Dargay, J., Madre, J.L., Pirotte, A.: The main determinants of the demand for public transport: A comparative analysis of England and France using shrinkage estimators. Transp. Res. Part A 37(7), 605–627 (2003)

    Google Scholar 

  • Cervero, R.: Transit pricing research: a review and synthesis. Transportation 17, 117–139 (1990)

    Article  Google Scholar 

  • Dargay, J, Hanly M.:Bus Fare Elasticities. Report to the UK Department of the Environment, Transport and the Regions. London, ESRC Transport Studies Unit, University College London, 132.25, (1999)

  • Dargay, J.M., Hanly, M.: The demand for local bus services in England. J. Transp. Econ. Policy 36(1), 73–91 (2002)

    Google Scholar 

  • De Palma, A.., Lindsey, R.: Optimal timetables for public transportation. Transp. Res. 35(8), 789–813 (2001)

  • Deb, K., Filippini, M.: Public bus transport demand elasticities in India. J. Transp. Econ. Policy 47(3), 419–436 (2013)

    Google Scholar 

  • Fitzroy, F.R., Smith I.: The Demand for Public Transport: some estimates from Zurich. CRIEFF Discussion Papers 9308.Centre for Research into Industry, Enterprise, Finance and the Firm, Fife, (1993)

  • FitzRoy, F., Smith, I.: The demand for public transport: some estimates from Zurich. Int. J. Transp. Econ. 21, 197–207 (1994)

    Google Scholar 

  • Fitzroy, F.R., Smith, I.: Season tickets and the demand for public transport. Kyklos 52(2), 219–238 (1999)

  • Gagnepain, P., Ivaldi, M.: Incentive regulatory policies: the case of public transit systems in France. RAND J. Econ. 33, 605–629 (2002)

    Article  Google Scholar 

  • Gakenheimer, R.: Urban mobility in the developing world. Transp. Res. Part A 33, 671–689 (1999)

    Google Scholar 

  • Ghazouani, S., Goaïed, M.: Analyse micro-économétrique de la demande de transport urbain pour la ville de Tunis», Économie & prévision. Numéro 108(2), 47–62 (1993)

  • Goodwin, P.B.: A review of new demand elasticities with special reference to short and long-run effects of price changes. J. Transp. Econ. Policy 26(2), 155–169 (1992)

    Google Scholar 

  • Goodwin, P.B., Williams, H.C.L.: Public transport demand models and elasticity measures: An overviews of recent British experience. Transp. Res. Part B 19(3), 253–259 (1985)

    Article  Google Scholar 

  • Goulias, K.G.: Traveler behavior and values research for human-centered transportation systems. The Pennsylvania State University, Committee on Traveler Behaviour and Values (2000). 6 p

    Google Scholar 

  • Jarboui, S.: Managerial psychology and transport firms efficiency: a stochastic frontier analysis. RMS (2014). doi:10.1007/s11846-014-0149-1

    Google Scholar 

  • Jarboui, S., Forget, P., Boujelbene, Y.: The efficiency of public road transport: a literature review via the classification scheme. Public Transp. 4(2), 101–128 (2012)

    Article  Google Scholar 

  • Jarboui, S., Forget, P., Boujelbene, Y.: Efficiency evaluation in public road transport: a stochastic frontier analysis. Transport (2013a). doi:10.3846/16484142.2013.785019

    Google Scholar 

  • Jarboui, S., Forget, P., Boujelbene, Y.: Public road transport efficiency: a stochastic frontier analysis. J. Transp. Syst. Eng. Inform. Technol. 13(5), 64–71 (2013b)

    Google Scholar 

  • Lyons, G., Chatterjee, K., Beecroft, M., Marsden, G.: Determinants of travel demand—exploring the future of society and lifestyles in the UK. Transp. Policy 9, 17–27 (2002)

    Article  Google Scholar 

  • Matas, A.: Demand and revenue implications of an integrated public transport policy: the case of Madrid. Transp. Rev. 24, 195–217 (2004)

    Article  Google Scholar 

  • Oum, T.H.: Alternative demand models and their elasticity estimates. J. Transp. Econ. Policy. 23(2), 163–187 (1989)

  • Romilly, P.: Subsidy and local bus service deregulation in Britain: A re-evaluation. J. Transp. Econ. Policy 35(2), 161–193 (2001)

    Google Scholar 

  • Roodman, D.: How to do xtabond2: an introduction to “difference” and “system” GMM in stata. Working Paper, vol.103. Center for Global Development, Washington (2006)

  • Small, K.A., Winston, C.: The demand for transportation: models and applications. In: Gómez-Iba ez, J., Tye, W.B., Winston, C.A. (eds.) Essays in Transportation Economics and Policy, pp. 11–56. Brookings Institution Press, Washington, D.C (1999)

  • Souche, S.: Measuring the structural determinants of urban travel demand. Transp. Policy. 17(3), 127–134 (2010)

Download references

Acknowledgments

We thank three anonymous referees for making a range of interesting suggestions based on a previous version of this paper. We would also like to thank Louafi Bouzouina and Hind Aissaoui of the “Laboratory of Transport Economics” for rereading our paper and their comments.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sami Jarboui.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Daldoul, M., Jarboui, S. & Dakhlaoui, A. Public transport demand: dynamic panel model analysis. Transportation 43, 491–505 (2016). https://doi.org/10.1007/s11116-015-9586-1

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11116-015-9586-1

Keywords

JEL Classification

Navigation