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Structure and dynamics of non-suburban passenger travel demand in Indian railways

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  • Mudit Kulsreshtha
  • Barnali Nag

Abstract

In this paper we derive long run structural relationships for all the three classes, viz. upper, second and ordinary second class, of non-suburban long distance passenger transport demand for Indian railways using annual time series data for 1970–1995. We employ some of the recent developments in multivariate dynamic econometric time series modeling including estimation of long-run structural cointegrating relationships, short-run dynamics and measurement of the effects of shocks and their persistence on evolution of the dynamic passenger transport demand system. The models are estimated using a cointegrating vector autoregressive (VAR) modeling framework, which allows for endogeneity of regressors. The demand systems are found to be stable for all the classes in the long run and they converge to equilibrium in a period of around 2–4 years after a typical system-wide shock. Any disequilibrium in the short-run is corrected in the long-run with adjustments in passenger transport demand and the price variable, i.e. real rate charged per passenger kilometer. Results show that travel demand in all classes would rise with income, although the rise is less than proportionate in the case of ordinary class. High price elasticity in long-run and short-run impulse responses indicate that passenger fare hike could lead to substantial decline in travel demand leading to decline in revenue earnings of the railways. Copyright Kluwer Academic Publishers 2000

Suggested Citation

  • Mudit Kulsreshtha & Barnali Nag, 2000. "Structure and dynamics of non-suburban passenger travel demand in Indian railways," Transportation, Springer, vol. 27(2), pages 221-241, May.
  • Handle: RePEc:kap:transp:v:27:y:2000:i:2:p:221-241
    DOI: 10.1023/A:1005252524145
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    References listed on IDEAS

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    Cited by:

    1. Wardman, Mark & Lythgoe, William & Whelan, Gerard, 2007. "Rail Passenger Demand Forecasting: Cross-Sectional Models Revisited," Research in Transportation Economics, Elsevier, vol. 20(1), pages 119-152, January.
    2. Muhammad Shafique & Anam Azam & Muhammad Rafiq & Xiaowei Luo, 2020. "Evaluating the Relationship between Freight Transport, Economic Prosperity, Urbanization, and CO 2 Emissions: Evidence from Hong Kong, Singapore, and South Korea," Sustainability, MDPI, vol. 12(24), pages 1-14, December.
    3. Chen, Mu-Chen & Wei, Yu, 2011. "Exploring time variants for short-term passenger flow," Journal of Transport Geography, Elsevier, vol. 19(4), pages 488-498.

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