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Maximum entropy: a stochastic frontier approach for electricity distribution regulation
Journal of Regulatory Economics ( IF 1.553 ) Pub Date : 2019-06-01 , DOI: 10.1007/s11149-019-09383-y
Elvira Silva , Pedro Macedo , Isabel Soares

The literature on incentive-based regulation in the electricity sector indicates that the size of this sector in a country constrains the choice of frontier methods as well as the model specification itself to measure economic efficiency of regulated firms. The aim of this study is to propose a stochastic frontier approach with maximum entropy estimation, which is designed to extract information from limited and noisy data with minimal statements on the data generation process. Stochastic frontier analysis with generalized maximum entropy and data envelopment analysis—the latter one has been widely used by national regulators—are applied to a cross-section data on thirteen European electricity distribution companies. Technical efficiency scores and rankings of the distribution companies generated by both approaches are sensitive to model specification. Nevertheless, the stochastic frontier analysis with generalized maximum entropy results indicate that technical efficiency scores have similar distributional properties and these scores as well as the rankings of the companies are not very sensitive to the prior information. In general, the same electricity distribution companies are found to be in the highest and lowest efficient groups, reflecting weak sensitivity to the prior information considered in the estimation procedure.

中文翻译:

最大熵:用于配电监管的随机前沿方法

有关电力部门基于激励的监管的文献表明,一个国家中该部门的规模限制了边界方法的选择以及模型规范本身的使用,从而无法衡量受监管企业的经济效率。这项研究的目的是提出一种具有最大熵估计的随机前沿方法,该方法旨在以最少的数据生成过程语句从有限且嘈杂的数据中提取信息。带有广义最大熵的随机边界分析和数据包络分析(后者已被国家监管机构广泛使用)已应用于13家欧洲配电公司的横截面数据。两种方法所产生的分销公司的技术效率得分和排名对模型规格很敏感。尽管如此,具有广义最大熵结果的随机前沿分析表明,技术效率得分具有相似的分布特性,并且这些得分以及公司的排名对现有信息并不十分敏感。通常,发现同一配电公司属于效率最高和最低的组,这反映了对估算程序中考虑的先验信息的敏感性较弱。具有广义最大熵结果的随机前沿分析表明,技术效率得分具有相似的分布特性,并且这些得分以及公司的排名对现有信息不太敏感。通常,发现同一配电公司属于效率最高和最低的组,这反映了对估算程序中考虑的先验信息的敏感性较弱。具有广义最大熵结果的随机前沿分析表明,技术效率得分具有相似的分布特性,并且这些得分以及公司的排名对现有信息不太敏感。通常,发现同一配电公司属于效率最高和最低的组,这反映了对估算程序中考虑的先验信息的敏感性较弱。
更新日期:2019-06-01
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