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The application of stochastic frontier panel models in economic regulation: Experience from the European rail sector

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  • Smith, Andrew S.J.

Abstract

This paper shows how stochastic frontier panel techniques can be used by economic regulators to benchmark regulated firms against international best practice. We utilise a unique, panel dataset of European rail infrastructure managers (1996–2006). A time-varying inefficiency model, with firm-specific time paths for inefficiency, is adopted. The results were used in the 2008 regulatory review of the British infrastructure manager, Network Rail, and showed that the company faced an efficiency gap of around 40% against European best practice – in line with engineering-based evidence. More widely, the paper highlights the advantages of the inefficiency specification adopted for use in economic regulation.

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  • Smith, Andrew S.J., 2012. "The application of stochastic frontier panel models in economic regulation: Experience from the European rail sector," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(2), pages 503-515.
    • Handle: RePEc:eee:transe:v:48:y:2012:i:2:p:503-515
    DOI: 10.1016/j.tre.2011.10.003
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    1. Michael G. Pollitt & Andrew S. J. Smith, 2002. "The restructuring and privatisation of British Rail: was it really that bad?," Fiscal Studies, Institute for Fiscal Studies, vol. 23(4), pages 463-502, December.
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    13. Farsi, Mehdi & Filippini, Massimo, 2009. "An analysis of cost efficiency in Swiss multi-utilities," Energy Economics, Elsevier, vol. 31(2), pages 306-315, March.
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    16. Antonio Alvarez & Christine Amsler & Luis Orea & Peter Schmidt, 2006. "Interpreting and Testing the Scaling Property in Models where Inefficiency Depends on Firm Characteristics," Journal of Productivity Analysis, Springer, vol. 25(3), pages 201-212, June.
    17. W. Kip Viscusi & Joseph E. Harrington & John M. Vernon, 2005. "Economics of Regulation and Antitrust, 4th Edition," MIT Press Books, The MIT Press, edition 4, volume 1, number 026222075x, April.
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    Cited by:

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    2. Baños-Pino, José F. & Boto-García, David & Zapico, Emma, 2021. "Persistence and dynamics in the efficiency of toll motorways: The Spanish case," Efficiency Series Papers 2021/03, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    3. Piening, J. & Ehrmann, T. & Meiseberg, B., 2013. "Competing risks for train tickets – An empirical investigation of customer behavior and performance in the railway industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 51(C), pages 1-16.
    4. Baños-Pino, José F. & Boto-García, David & Zapico, Emma, 2022. "Persistence and dynamics in the efficiency of toll motorways: The Spanish case," Economics of Transportation, Elsevier, vol. 31(C).
    5. Odolinski, Kristofer & Smith, Andrew & Wheat, Phill & Nilsson, Jan-Eric & Dheilly, Clement, 2023. "Damage or no damage from traffic: Re-examining marginal cost pricing for rail signalling maintenance," Transport Policy, Elsevier, vol. 131(C), pages 13-21.
    6. Richard D Knowles, 2013. "Railway Franchising in Great Britain and Effects of the 2008/09 Economic Recession," Environment and Planning A, , vol. 45(1), pages 197-216, January.
    7. Antonio Ramos Andrade & Julian Stow, 2017. "Assessing the efficiency of maintenance operators: A case study of turning railway wheelsets on an under-floor wheel lathe," Journal of Risk and Reliability, , vol. 231(2), pages 155-163, April.
    8. Odolinski, Kristofer & Smith, Andrew S.J., 2014. "Assessing the Cost Impact of Competitive Tendering in Rail Infrastructure Maintenance Services: Evidence from the Swedish Reforms (1999 to 2011)," Working papers in Transport Economics 2014:17, CTS - Centre for Transport Studies Stockholm (KTH and VTI), revised 22 May 2015.
    9. Phill Wheat & Alexander D. Stead & Yue Huang & Andrew Smith, 2019. "Lowering Transport Costs and Prices by Competition: Regulatory and Institutional Reforms in Low Income Countries," Sustainability, MDPI, vol. 11(21), pages 1-19, October.

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