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The Measurement Of Efficiency Where There Are Multiple Outputs

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  • John L. Whiteman

Abstract

This paper is motivated by the empirical observation that in many studies the elasticity of output with respect to labour is often negative and/or insignificant. The present study applies multiple output models to estimate the technical efficiency of enterprises in the international electricity, gas and telecom-munications industries. The results support the contention that single output production models may yield misleading results in respect of the elasticities of inputs such as labour. The results also suggest that relatively simple DEA and ordinary least squares models may be preferred to more complex stochastic frontier models in estimating the technical efficiency of enterprises.

Suggested Citation

  • John L. Whiteman, 1999. "The Measurement Of Efficiency Where There Are Multiple Outputs," Centre of Policy Studies/IMPACT Centre Working Papers g-134, Victoria University, Centre of Policy Studies/IMPACT Centre.
    • Handle: RePEc:cop:wpaper:g-134
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    References listed on IDEAS

    as
    1. 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.
    2. John Quiggin, 1997. "Estimating the Benefits of Hilmer and Related Reforms," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 30(3), pages 256-272, September.
    3. Greene, William H., 1980. "Maximum likelihood estimation of econometric frontier functions," Journal of Econometrics, Elsevier, vol. 13(1), pages 27-56, May.
    4. John Whiteman, 1999. "The Potential Benefits of Hilmer and Related Reforms: Electricity Supply," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 32(1), pages 17-30, March.
    5. Löthgren, Mickael, 1997. "A Multiple Output Stochastic Ray Frontier Production Model," SSE/EFI Working Paper Series in Economics and Finance 158, Stockholm School of Economics.
    6. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
    7. Löthgren, Mickael, 1996. "Generalized Stochastic Frontier Production Models," SSE/EFI Working Paper Series in Economics and Finance 149, Stockholm School of Economics, revised 03 Sep 1997.
    8. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

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    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • L95 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Gas Utilities; Pipelines; Water Utilities
    • L96 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Telecommunications

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