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Identifying traffic safety best practice: an application of DEA and Malmquist indices

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  • Odeck, James
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    Abstract

    DEA is used in this paper to investigate target achievements of the operational units of the Norwegian Public Roads Administration (NPRA) charged with traffic safety services. The DEA framework applied corresponds to a BCC model with a unique constant input, or equivalently, with no inputs. This framework is further extended to a DEA-based Malmquist index to measure productivity growth in target achievements. Finally, we use a bootstrapping method to ascertain confidence intervals for efficiency scores derived and to test hypotheses on the extent of productivity growth or regress. The mean efficiency scores by which targets are achieved across the sample years are in the range 0.81-0.93 and significant at the 5% level. Total productivity in target achievements shows progress with significance, on average at 7%. Much of the progress is attributed to technological progress. The results illustrate the usefulness of using a decomposable index for productivity measurement, and the use of bootstrapping for sensitivity tests.

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    Bibliographic Info

    Article provided by Elsevier in its journal Omega.

    Volume (Year): 34 (2006)
    Issue (Month): 1 (January)
    Pages: 28-40

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    Handle: RePEc:eee:jomega:v:34:y:2006:i:1:p:28-40

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    Related research

    Keywords: Target achievement Traffic safety Data envelopment analysis Malmquist indices Bootstrapping;

    References

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    1. Simar, L. & Wilson, P.W., 1999. "Statistical Inference in Nonparametric Frontier Models: the State of the Art," Papers 9904, Catholique de Louvain - Institut de statistique.
    2. Lovell, C. A. Knox & Pastor, Jesus T., 1999. "Radial DEA models without inputs or without outputs," European Journal of Operational Research, Elsevier, vol. 118(1), pages 46-51, October.
    3. Odeck, James, 2000. "Assessing the relative efficiency and productivity growth of vehicle inspection services: An application of DEA and Malmquist indices," European Journal of Operational Research, Elsevier, vol. 126(3), pages 501-514, November.
    4. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    5. C. Lovell, 2003. "The Decomposition of Malmquist Productivity Indexes," Journal of Productivity Analysis, Springer, vol. 20(3), pages 437-458, November.
    6. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity," Econometrica, Econometric Society, vol. 50(6), pages 1393-1414, November.
    7. Shawna Grosskopf, 2003. "Some Remarks on Productivity and its Decompositions," Journal of Productivity Analysis, Springer, vol. 20(3), pages 459-474, November.
    8. SIMAR, Léopold & WILSON, Paul, 1996. "Estimating and bootstrapping malmquist indices," CORE Discussion Papers 1996060, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    9. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    10. Bjurek, Hans & Hjalmarsson, Lennart, 1995. "Productivity in multiple output public service: A quadratic frontier function and Malmquist index approach," Journal of Public Economics, Elsevier, vol. 56(3), pages 447-460, March.
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    Cited by:
    1. Giannis Karagiannis & C. A. K. Lovell, 2013. "Productivity Measurement In Radial Dea Models With Multiple Constant Inputs," CEPA Working Papers Series WP082013, School of Economics, University of Queensland, Australia.
    2. Cruijssen, F.C.A.M. & Dullaert, W. & Joro, T., 2006. "Logistic Efficiency Through Horizontal Cooperation: The Case of Flemish Road Transportation Companies," Discussion Paper 2006-14, Tilburg University, Center for Economic Research.

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