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Using the latent class approach to cluster firms in benchmarking: An application to the US electricity transmission industry

机译:使用潜在类别方法对集群公司进行基准测试:在美国输电行业的应用

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In this paper we advocate using the latent class model (LCM) approach to control for technological differences in traditional efficiency analysis of regulated electricity networks. Our proposal relies on the fact that latent class models are designed to cluster firms by uncovering differences in technology parameters. Moreover, it can be viewed as a supervised method for clustering data that takes into account the same (production or cost) relationship that is analysed later, often using nonparametric frontier techniques. The simulation exercises show that the proposed approach outperforms other sample selection procedures. The proposed methodology is illustrated with an application to a sample of US electricity transmission firms for the period 2001–2009.
机译:在本文中,我们提倡使用潜在类别模型(LCM)方法来控制传统电力网效率分析中的技术差异。我们的建议基于以下事实:潜在类别模型旨在通过发现技术参数的差异来聚类企业。此外,它可以看作是一种对数据进行聚类的有监督方法,该方法考虑到了相同的(生产或成本)关系,以后通常使用非参数前沿技术对其进行分析。仿真实验表明,所提出的方法优于其他样本选择程序。举例说明了所建议的方法,并将其应用于2001-2009年间美国输电公司的样本中。

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