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Productivity Growth in European Railways: Technological Progress,Efficiency Change and Scale Effects

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  • Heike Wetzel

    ()
    (Institute of Economics, University of Lüneburg)

Abstract

This paper analyzes the performance of the European railway sector in the period of deregulation (1990-2005). Using a stochastic frontier panel data model that controls for unobserved heterogeneity a multiple-output multiple input distance function model is estimated in order to evaluate the sources of productivity growth: technological progress, technical efficiency change and scale effects. The results indicate that technology improvements were by far the most important driver of productivity growth, followed by gains in technical efficiency, and to a lesser extent by exploitation of scale economies. Overall, we find an average productivity growth of 39 per cent within the sample period.

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Bibliographic Info

Paper provided by University of Lüneburg, Institute of Economics in its series Working Paper Series in Economics with number 101.

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Length: 31 pages
Date of creation: Oct 2008
Date of revision:
Handle: RePEc:lue:wpaper:101

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Related research

Keywords: European railways; Deregulation; Stochastic frontier analysis; Total factor productivity;

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  13. John Loizides & Efthymios G. Tsionas, 2004. "Dynamic Distributions of Productivity Growth in European Railways," Journal of Transport Economics and Policy, London School of Economics and University of Bath, London School of Economics and University of Bath, vol. 38(1), pages 45-75, January.
  14. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-44, June.
  15. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, Elsevier, vol. 6(1), pages 21-37, July.
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  17. Luis Orea, 2002. "Parametric Decomposition of a Generalized Malmquist Productivity Index," Journal of Productivity Analysis, Springer, Springer, vol. 18(1), pages 5-22, July.
  18. David Saal & David Parker & Tom Weyman-Jones, 2007. "Determining the contribution of technical change, efficiency change and scale change to productivity growth in the privatized English and Welsh water and sewerage industry: 1985–2000," Journal of Productivity Analysis, Springer, Springer, vol. 28(1), pages 127-139, October.
  19. Coelli, Tim & Perelman, Sergio, 1999. "A comparison of parametric and non-parametric distance functions: With application to European railways," European Journal of Operational Research, Elsevier, Elsevier, vol. 117(2), pages 326-339, September.
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