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Empirical Consequences of Direction Choice in Technical Efficiency Analysis

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  • Álvarez, Antonio
  • Arias, Carlos
  • Kumbhakar, Subal

Abstract

This paper examines the effects of using input- and output-oriented measures of technical inefficiency (direction choice) on the estimated technology, its characteristics and efficiency rankings. If one assumes that the technology is known (as is done in theory) then this issue is trivial. Since the technology is rarely known, and both the technology and inefficiency are to be estimated simultaneously, the choice of direction is very important from an empirical point of view. Using a sample of dairy farms, we show that the estimated characteristics of the technology and efficiency rankings of farms depend on the choice of direction.

Suggested Citation

  • Álvarez, Antonio & Arias, Carlos & Kumbhakar, Subal, 2003. "Empirical Consequences of Direction Choice in Technical Efficiency Analysis," Efficiency Series Papers 2003/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    • Handle: RePEc:oeg:wpaper:2003/02
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    References listed on IDEAS

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    1. Luis Orea & David Roibás & Alan Wall, 2004. "Choosing the Technical Efficiency Orientation to Analyze Firms' Technology: A Model Selection Test Approach," Journal of Productivity Analysis, Springer, vol. 22(1), pages 51-71, July.
    2. Fare, Rolf & Knox Lovell, C. A., 1978. "Measuring the technical efficiency of production," Journal of Economic Theory, Elsevier, vol. 19(1), pages 150-162, October.
    3. Atkinson, Scott E & Cornwell, Christopher, 1994. "Estimation of Output and Input Technical Efficiency Using a Flexible Form and Panel Data," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(1), pages 245-255, February.
    4. Lau, Lawrence J & Yotopoulos, Pan A, 1971. "A Test for Relative Efficiency and Application to Indian Agriculture," American Economic Review, American Economic Association, vol. 61(1), pages 94-109, March.
    5. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-374, October.
    6. 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.
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    Cited by:

    1. Kumbhakar, Subal C. & Tsionas, Efthymios G., 2006. "Estimation of stochastic frontier production functions with input-oriented technical efficiency," Journal of Econometrics, Elsevier, vol. 133(1), pages 71-96, July.
    2. Antonio Alvarez & Carlos Arias, 2014. "A selection of relevant issues in applied stochastic frontier analysis," Economics and Business Letters, Oviedo University Press, vol. 3(1), pages 3-11.
    3. Kumbhakar, Subal & Tsionas, Efthymios, 2003. "Recent Developments in Stochastic Frontier Modeling," Efficiency Series Papers 2003/06, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    4. Efthymios G. Tsionas, 2007. "Efficiency Measurement with the Weibull Stochastic Frontier," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 69(5), pages 693-706, October.
    5. Subal C. Kumbhakar & Efthymios G. Tsionas, 2008. "Estimation of input‐oriented technical efficiency using a nonhomogeneous stochastic production frontier model," Agricultural Economics, International Association of Agricultural Economists, vol. 38(1), pages 99-108, January.

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