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Rarely enjoyed? A count data analysis of ridership in Germany's public transport

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  • Frondel, Manuel
  • Vance, Colin

Abstract

Focusing on adult members of German households, this paper investigates the determinants of public transit ridership with the aim of quantifying the effects of fuel prices, fares, person-level attributes, and characteristics of the transit system on transport counts over a five-day week. The reliance on individual data raises several conceptual and empirical issues, the most fundamental of which is the large proportion of zero values in transit counts. To accommodate this feature of the data, we employ modeling procedures referred to as zero-inflated models (ZIMs), which order observations into two latent regimes defined by whether the individual never uses public transport. Our estimates reveal fuel prices to have a positive and substantial influence on transit ridership, though there is no evidence for a statistically significant impact of the fare.

Suggested Citation

  • Frondel, Manuel & Vance, Colin, 2011. "Rarely enjoyed? A count data analysis of ridership in Germany's public transport," Transport Policy, Elsevier, vol. 18(2), pages 425-433, March.
  • Handle: RePEc:eee:trapol:v:18:y:2011:i:2:p:425-433
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    References listed on IDEAS

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    1. Daniel J. Graham & Stephen Glaister, 2002. "The Demand for Automobile Fuel: A Survey of Elasticities," Journal of Transport Economics and Policy, University of Bath, vol. 36(1), pages 1-25, January.
    2. Manuel Frondel & Jorg Peters & Colin Vance, 2008. "Identifying the Rebound: Evidence from a German Household Panel," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 145-164.
    3. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
    4. Cameron, A Colin & Trivedi, Pravin K, 1986. "Econometric Models Based on Count Data: Comparisons and Applications of Some Estimators and Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 1(1), pages 29-53, January.
    5. 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.
    6. Storchmann, K. -H., 2001. "The impact of fuel taxes on public transport -- an empirical assessment for Germany," Transport Policy, Elsevier, vol. 8(1), pages 19-28, January.
    7. Kayser, Hilke A., 2000. "Gasoline demand and car choice: estimating gasoline demand using household information," Energy Economics, Elsevier, vol. 22(3), pages 331-348, June.
    8. Holmgren, Johan, 2007. "Meta-analysis of public transport demand," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(10), pages 1021-1035, December.
    9. Frondel, Manuel & Vance, Colin, 2010. "Driving for fun? Comparing the effect of fuel prices on weekday and weekend fuel consumption," Energy Economics, Elsevier, vol. 32(1), pages 102-109, January.
    10. Colin Vance & Ralf Hedel, 2007. "The impact of urban form on automobile travel: disentangling causation from correlation," Transportation, Springer, vol. 34(5), pages 575-588, September.
    11. Manuel Frondel & Colin Vance, 2009. "Do High Oil Prices Matter? Evidence on the Mobility Behavior of German Households," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 43(1), pages 81-94, May.
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    Cited by:

    1. Nowak, William P. & Savage, Ian, 2013. "The cross elasticity between gasoline prices and transit use: Evidence from Chicago," Transport Policy, Elsevier, vol. 29(C), pages 38-45.
    2. Xiaohong Chen & Xiang Wang & Hua Zhang & Jia Li, 2014. "The Diversity and Evolution Process of Bus System Performance in Chinese Cities: An Empirical Study," Sustainability, MDPI, Open Access Journal, vol. 6(11), pages 1-17, November.

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