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<p>Recently, a toolkit of stochastic frontier models using Skew-Normal distributions was developed for efficiency analysis. The Skew-Normal based stochastic frontier model (SN-SFM), a model based on Skew-Normal distribution, provides a solution to rectify the issue of incorrect skewness that poses a challenge for the conventional frontier model. This paper primarily focuses on reviewing the SN-SFM and discusses the expectation conditional maximization algorithm which tackles challenges in parameter estimation. A dataset from a U.S. electric utility is employed to illustrate the advantages of the SN-SFM with the Bayesian estimation approach.</p>

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Recent development in skew-normal based stochastic frontier analysis

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年5月27日

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  • Nene Coulibaly,
  • Baokun Li,
  • Xiaonan Zhu,
  • Zheng Wei

摘要

Recently, a toolkit of stochastic frontier models using Skew-Normal distributions was developed for efficiency analysis. The Skew-Normal based stochastic frontier model (SN-SFM), a model based on Skew-Normal distribution, provides a solution to rectify the issue of incorrect skewness that poses a challenge for the conventional frontier model. This paper primarily focuses on reviewing the SN-SFM and discusses the expectation conditional maximization algorithm which tackles challenges in parameter estimation. A dataset from a U.S. electric utility is employed to illustrate the advantages of the SN-SFM with the Bayesian estimation approach.