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Efficiency Analysis with Stochastic Frontier Models using Popular Statistical Softwares

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  • Nguyen, B.H.

    (School of Economics, University of Queensland, Brisbane, Qld 4072, Australia)

  • Sickles, R.

    (Economics Department, Rice University, Houston, TX 77251-1892, USA)

  • Zelenyuk, V.

    (School of Economics and Centre for Efficiency and Productivity Analysis, University of Queensland, Brisbane, Qld 4072, Australia)

Abstract

Our chapter provides a brief introduction to the stochastic frontier paradigm - one of the most powerful techniques for performance analysis developed over the last few decades to address various research questions for many contexts with empirical applications in a wide variety of economic sectors such as banking, healthcare, agriculture, and so on. We also document the estimation routines used to implement the classical models as well as the recent developments in this research area for practitioners, especially those who are willing to use Stata, but also with tips on sources for R and Matlab users.

Suggested Citation

  • Nguyen, B.H. & Sickles, R. & Zelenyuk, V., "undated". "Efficiency Analysis with Stochastic Frontier Models using Popular Statistical Softwares," Working Papers 1, International Society for Efficiency and Productivity Analysis.
    • Handle: RePEc:aso:wpaper:wp0001
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    Keywords

    Technical efficiency; Stochastic frontier analysis; Panel data; Semi-parametric; Stata; Matlab; R.;
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