IDEAS home Printed from https://ideas.repec.org/a/eee/juipol/v18y2010i2p86-93.html
   My bibliography  Save this article

The role of international benchmarking in developing rail infrastructure efficiency estimates

Author

Listed:
  • Smith, Andrew
  • Wheat, Phill
  • Smith, Gregory

Abstract

International cost efficiency benchmarking played a central role in informing the Office of Rail Regulation's (ORR) determination of Network Rail's future funding during the 2008 periodic review (PR08) of the company's finances. This paper sets out how international benchmarking can inform a regulator's decisions on efficiency and, in particular, how international econometric studies can be used alongside other evidence in the regulatory context. We start by reviewing the use of previous international benchmarking work. We then set out the data, methodology and results in respect of the two separate econometric studies carried out as part of PR08. The further work that was done in support of the econometric results is then described. The paper shows that top-down econometric techniques, combined with bottom-up engineering analysis produced a robust comparison between Network Rail and its peers. We conclude by outlining how the econometric results were used, in conjunction with other evidence, to reach a final efficiency determination, and how we consider that international benchmarking can be applied by other regulators.

Suggested Citation

  • Smith, Andrew & Wheat, Phill & Smith, Gregory, 2010. "The role of international benchmarking in developing rail infrastructure efficiency estimates," Utilities Policy, Elsevier, vol. 18(2), pages 86-93, June.
    • Handle: RePEc:eee:juipol:v:18:y:2010:i:2:p:86-93
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0957-1787(09)00043-5
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Rafael Cuesta, 2000. "A Production Model With Firm-Specific Temporal Variation in Technical Inefficiency: With Application to Spanish Dairy Farms," Journal of Productivity Analysis, Springer, vol. 13(2), pages 139-158, March.
    2. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-374, October.
    3. Pitt, Mark M. & Lee, Lung-Fei, 1981. "The measurement and sources of technical inefficiency in the Indonesian weaving industry," Journal of Development Economics, Elsevier, vol. 9(1), pages 43-64, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gillies-Smith, Andrew & Wheat, Phill, 2016. "Do network industries plan to eliminate inefficiencies in response to regulatory pressure? The case of railways in Great Britain," Utilities Policy, Elsevier, vol. 43(PB), pages 165-173.
    2. Jonathan Cowie & Sarah Loynes, 2012. "An assessment of cost management regimes in British rail infrastructure provision," Transportation, Springer, vol. 39(6), pages 1281-1299, November.
    3. Wheat, Phill, 2017. "Scale, quality and efficiency in road maintenance: Evidence for English local authorities," Transport Policy, Elsevier, vol. 59(C), pages 46-53.
    4. Odolinski, Kristofer & Wheat, Phill, 2018. "Dynamics in rail infrastructure provision: Maintenance and renewal costs in Sweden," Economics of Transportation, Elsevier, vol. 14(C), pages 21-30.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Young Hoon Lee, 2009. "Frontier Models and their Application to the Sports Industry," Working Papers 0903, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy), revised 2009.
    2. Kellermann, Magnus A., 2015. "Total Factor Productivity Decomposition and Unobserved Heterogeneity in Stochastic Frontier Models," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 44(1), pages 1-25, April.
    3. Meryem Duygun & Jiaqi Hao & Anders Isaksson & Robin C. Sickles, 2017. "World Productivity Growth: A Model Averaging Approach," Pacific Economic Review, Wiley Blackwell, vol. 22(4), pages 587-619, October.
    4. Giannis Karagiannis & Vangelis Tzouvelekas, 1999. "Measuring Technical Efficiency with Panel Data: Results from Competing Models," Working Papers 9914, University of Crete, Department of Economics.
    5. Tandon, Suranjali & Rao, R. Kavita, 2019. "Frontier analysis for State Excise in India," Working Papers 19/276, National Institute of Public Finance and Policy.
    6. Pavlos Almanidis & Giannis Karagiannis & Robin Sickles, 2015. "Semi-nonparametric spline modifications to the Cornwell–Schmidt–Sickles estimator: an analysis of US banking productivity," Empirical Economics, Springer, vol. 48(1), pages 169-191, February.
    7. Massimo Filippini & William Greene, 2016. "Persistent and transient productive inefficiency: a maximum simulated likelihood approach," Journal of Productivity Analysis, Springer, vol. 45(2), pages 187-196, April.
    8. Sickles, Robin C. & Hao, Jiaqi & Shang, Chenjun, 2015. "Panel Data and Productivity Measurement," Working Papers 15-018, Rice University, Department of Economics.
    9. Peter Dawson & Stephen Dobson & Bill Gerrard, 2000. "Stochastic Frontiers and the Temporal Structure of Managerial Efficiency in English Soccer," Journal of Sports Economics, , vol. 1(4), pages 341-362, November.
    10. Darío Ezequiel Díaz, 2013. "La Distribución Eléctrica en Argentina y su Eficiencia Técnica:Una Aplicación del Análisis de Fronteras Estocásticas (SFA) Utilizando Funciones Distancia," Revista de Economía y Estadística, Universidad Nacional de Córdoba, Facultad de Ciencias Económicas, Instituto de Economía y Finanzas, vol. 51(1), pages 85-118, Diciembre.
    11. Kim, Sangho & Park, Donghyun & Park, Jong-Ho, 2009. "Productivity Growth in Different Firm Sizes in the Malaysian Manufacturing Sector: An Empirical Investigation," ADB Economics Working Paper Series 176, Asian Development Bank.
    12. Federico Belotti & Silvio Daidone & Giuseppe Ilardi & Vincenzo Atella, 2013. "Stochastic frontier analysis using Stata," Stata Journal, StataCorp LP, vol. 13(4), pages 718-758, December.
    13. Lee, Young Hoon, 2006. "A stochastic production frontier model with group-specific temporal variation in technical efficiency," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1616-1630, November.
    14. Martín Rossi, 2015. "The Econometrics Approach to the Measurement of Efficiency: A Survey," Working Papers 117, Universidad de San Andres, Departamento de Economia, revised Feb 2015.
    15. 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.
    16. Karagiannis, Giannis & Tzouvelekas, Vangelis, 2009. "Parametric Measurement of Time-Varying Technical Inefficiency: Results from Competing Models," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 10(1), pages 1-30.
    17. Chen, Yueh H. & Lin, Winston T., 2009. "Analyzing the relationships between information technology, inputs substitution and national characteristics based on CES stochastic frontier production models," International Journal of Production Economics, Elsevier, vol. 120(2), pages 552-569, August.
    18. Victor Moutinho & Mara Madaleno, 2021. "Assessing Eco-Efficiency in Asian and African Countries Using Stochastic Frontier Analysis," Energies, MDPI, vol. 14(4), pages 1-17, February.
    19. Chen, Yi-Yi & Schmidt, Peter & Wang, Hung-Jen, 2014. "Consistent estimation of the fixed effects stochastic frontier model," Journal of Econometrics, Elsevier, vol. 181(2), pages 65-76.
    20. Banfi, Silvia & Filippini, Massimo, 2010. "Resource rent taxation and benchmarking--A new perspective for the Swiss hydropower sector," Energy Policy, Elsevier, vol. 38(5), pages 2302-2308, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:juipol:v:18:y:2010:i:2:p:86-93. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.sciencedirect.com/journal/utilities-policy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.