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On the Joint Estimation of Heterogeneous Technologies, Technical, and Allocative Inefficiency

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  • Efthymios G. Tsionas
  • Kien C. Tran

Abstract

In this article, we provide a semiparametric approach to the joint measurement of technical and allocative inefficiency in a way that the internal consistency of the specification of allocative errors in the objective function (e.g., cost function) and the derivative equations (e.g., share or input demand functions) is assured. We start from the Cobb--Douglas production and shadow cost system. We show that the shadow cost system has a closed-form likelihood function contrary to what was previously thought. In turn, we use the method of local maximum likelihood applied to a system of equations to obtain firm-specific parameter estimates (which reveal heterogeneity in production) as well as measures of technical and allocative inefficiency and its cost. We illustrate its practical application using data on U.S. electric utilities.

Suggested Citation

  • Efthymios G. Tsionas & Kien C. Tran, 2016. "On the Joint Estimation of Heterogeneous Technologies, Technical, and Allocative Inefficiency," Econometric Reviews, Taylor & Francis Journals, vol. 35(5), pages 871-893, May.
    • Handle: RePEc:taf:emetrv:v:35:y:2016:i:5:p:871-893
    DOI: 10.1080/07474938.2014.975635
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    References listed on IDEAS

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    1. Kumbhakar, Subal C. & Tsionas, Efthymios G., 2005. "Measuring technical and allocative inefficiency in the translog cost system: a Bayesian approach," Journal of Econometrics, Elsevier, vol. 126(2), pages 355-384, June.
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    Cited by:

    1. Christine Amsler & Artem Prokhorov & Peter Schmidt, 2021. "A new family of copulas, with application to estimation of a production frontier system," Journal of Productivity Analysis, Springer, vol. 55(1), pages 1-14, February.

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