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Evaluating target achievements in the public sector: An application or a rare non-parametric DEA and Malmquist indices

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Abstract

This paper provides an assessment of the extent to which targets set by a public authority are achieved by its operational units. A rare DEA framework and its subsequent Malmquist indices are applied on data comprising 19 units over a four year period of 1996 to 1999. The mean efficiency scores by which targets are achieved across the sample years are moderate, in the range 0.81 to 0.93. Average productivity progress across the sample years has been 26 percent. The results illustrate the usefulness of DEA even when there are no inputs and the decomposable Malmquist index for productivity is an asset in exploring causes of productivity growth.

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  • James Odeck, 2005. "Evaluating target achievements in the public sector: An application or a rare non-parametric DEA and Malmquist indices," Journal of Applied Economics, Universidad del CEMA, vol. 8, pages 171-190, May.
    • Handle: RePEc:cem:jaecon:v:8:y:2005:n:1:p:171-190
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    1. 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.
    2. 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.
    3. Knox Lovell, C. A. & Pastor, Jesus T., 1997. "Target setting: An application to a bank branch network," European Journal of Operational Research, Elsevier, vol. 98(2), pages 290-299, April.
    4. 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.
    5. 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.
    6. 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.
    7. Rikard Althin, 2001. "Measurement of Productivity Changes: Two Malmquist Index Approaches," Journal of Productivity Analysis, Springer, vol. 16(2), pages 107-128, September.
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    Cited by:

    1. Joanicjusz Nazarko & Marta Komuda & Katarzyna Kuźmicz & Elżbieta Szubzda & Joanna Urban, 2008. "The DEA method in public sector institutions efficiency analysis on the basis of higher education institutions," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 18(4), pages 89-105.
    2. Byeong U. Park & Léopold Simar & Valentin Zelenyuk, 2013. "Non-Parametric Approach to Dynamic Time Series Discrete Choice Models," CEPA Working Papers Series WP092013, School of Economics, University of Queensland, Australia.
    3. Magnus Söderberg, 2009. "A Broad Performance Benchmark Based On Citizens’ Preferences: The Case Of Swedish Public Transportation," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 80(4), pages 579-603, December.
    4. Karagiannis, Giannis & Knox Lovell, C.A., 2016. "Productivity measurement in radial DEA models with a single constant input," European Journal of Operational Research, Elsevier, vol. 251(1), pages 323-328.
    5. António Afonso & Sónia Fernandes, 2008. "Assessing Hospital Efficiency: Non-parametric Evidence for Portugal," Working Papers Department of Economics 2008/07, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.

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    More about this item

    Keywords

    target achievement; traffic safety; data envelopment analysis; Malmquist indices;
    All these keywords.

    JEL classification:

    • L92 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Railroads and Other Surface Transportation
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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