Robust stochastic frontier analysis applied to the Brazilian electricity distribution benchmarking method.

• Autor(a) principal: Campos, Magno Silvério
• Data de Publicação: 2022
• Outros Autores: Costa, Marcelo Azevedo, Gontijo, Tiago Silveira, Lopes-Ahn, Ana Lúcia
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UFOP
• Texto Completo: http://www.repositorio.ufop.br/jspui/handle/123456789/16859; https://doi.org/10.1016/j.dajour.2022.100051
• topic: Data envelopment analysis; Stochastic frontier analysis; Bayesian statistic

A Data Envelopment Analysis (DEA) method has been applied by the Brazilian regulator to set regulatory operational costs for 61 electricity distribution utilities. Recent studies show evidence that the current method still requires improvements. This study evaluates the use of Stochastic Frontier Analysis (SFA) as an alternative method. Pros and cons are evaluated. Results show that the SFA is more flexible to deal with outliers. However, the SFA has major convergence problems. Convergence issues can be overcome using Bayesian computations. This study advocates the use of both DEA and SFA as the best alternatives, as indicated by European regulators.