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Identifying Short-Run and Long-Run Public Transport Demand Elasticities in Sydney A Pseudo Panel Approach

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  • Chi-Hong (Patrick) Tsai
  • Corinne Mulley

Abstract

This paper applies a pseudo panel approach to analyse public transport demand and estimate short-run and long-run demand elasticities in Sydney. A dynamic Partial Adjustment Model is employed to capture the lagged adjustments of public transport users' travel behaviour, which differentiate long-run demand from short-run demand. The public transport demand model incorporates different drivers of demand determinants, including public transport price, the socio-economics of travellers, land use characteristics, and the level of public transport service. The impacts on public transport demand are presented in terms of short-run and long-run demand elasticities. © 2014 LSE and the University of Bath

Suggested Citation

  • Chi-Hong (Patrick) Tsai & Corinne Mulley, 2014. "Identifying Short-Run and Long-Run Public Transport Demand Elasticities in Sydney A Pseudo Panel Approach," Journal of Transport Economics and Policy, University of Bath, vol. 48(2), pages 241-259, May.
    • Handle: RePEc:tpe:jtecpo:v:48:y:2014:i:2:p:241-259
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    Cited by:

    1. Mária Ďurišová & Emese Tokarčíková & Florina Oana Virlanuta & Zuzana Chodasová, 2019. "The Corporate Performance Measurement and Its Importance for the Pricing in a Transport Enterprise," Sustainability, MDPI, vol. 11(21), pages 1-17, November.
    2. Kasraian, Dena & Maat, Kees & van Wee, Bert, 2018. "Urban developments and daily travel distances: Fixed, random and hybrid effects models using a Dutch pseudo-panel over three decades," Journal of Transport Geography, Elsevier, vol. 72(C), pages 228-236.
    3. Alexandre Pavlov & Charles Vaillancourt & Michel Poitevin, 2020. "Tarification optimale du gaz carbonique et élasticités dans les transports," CIRANO Project Reports 2020rp-20, CIRANO.
    4. Antonín Pavlíček & František Sudzina, 2020. "Intergroup Comparison of Personalities in the Preferred Pricing of Public Transport in Rush Hours: Data Revisited," Sustainability, MDPI, vol. 12(12), pages 1-9, June.

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