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Technical efficiency measurement and explanation of French urban transit companies

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  • Kerstens, K.

Abstract

The performance of a sample of French urban transit companies is evaluated using a broad selection of nonparametric reference technologies for two specifications of the production process. In particular, the variable returns to scale Data Envelopment Analysis (DEA) models with either strong or weak disposability in both inputs and outputs, and the Free Disposal Hull (FDH) are applied. An extensive comparison of the resulting radial output efficiency measures yields the following major methodological conclusions. First, the location of the efficiency distributions differs substantially depending on the methodology and especially on the output specification considered. The latter differences vanish if the impact of outliers is eliminated. Second, convexity has a stronger influence on the efficient-inefficient dichotomy than allowing for congestion by means of a weakly disposable DEA model. For policy purposes, these efficiency distributions are explained using a Tobit model. The findings corroborate results reported elsewhere: the relevance of ownership, the use of risk-sharing incentives in contracting, the harmful impact of subsidies, etc. Furthermore, the network structure seems to account for some differences in performance. Finally, a novelty in the urban transit context is the indirect monitoring effect of the French earmarked transportation tax.

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Bibliographic Info

Article provided by Elsevier in its journal Transportation Research Part A: Policy and Practice.

Volume (Year): 30 (1996)
Issue (Month): 6 (November)
Pages: 431-452

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Handle: RePEc:eee:transa:v:30:y:1996:i:6:p:431-452

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  1. Banister, David & Berechman, Joseph & De Rus, Gines, 1992. "Competitive regimes within the European bus industry: Theory and practice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 26(2), pages 167-178, March.
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  3. Wilson, Paul W, 1993. "Detecting Outliers in Deterministic Nonparametric Frontier Models with Multiple Outputs," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(3), pages 319-23, July.
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  5. Button, Kenneth J & Weyman-Jones, Thomas G, 1994. " X-Efficiency and Technical Efficiency," Public Choice, Springer, vol. 80(1-2), pages 83-104, July.
  6. Dusansky, Richard & Wilson, Paul W, 1994. "Technical Efficiency in the Decentralized Care of the Developmentally Disabled," The Review of Economics and Statistics, MIT Press, vol. 76(2), pages 340-45, May.
  7. Oum, Tae H. & Tretheway, Michael W. & Waters, W. G., 1992. "Concepts, methods and purposes of productivity measurement in transportation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 26(6), pages 493-505, November.
  8. KERSTENs, Kris & VANDEN EECKAUT, Philippe, 1995. "Technical Efficiency Measures on DEA and FDH : A Reconsideration of the Axiomatic Literature," CORE Discussion Papers 1995013, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  9. Richard H. Spady & Ann F. Friedlaender, 1978. "Hedonic Cost Functions for the Regulated Trucking Industry," Bell Journal of Economics, The RAND Corporation, vol. 9(1), pages 159-179, Spring.
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  11. Davis, Michael L & Hayes, Kathy, 1993. "The Demand for Good Government," The Review of Economics and Statistics, MIT Press, vol. 75(1), pages 148-52, February.
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