Bayesian detection of clusters in efficiency score maps: An application to Brazilian energy regulation

Abstract An original application of an approach first used in epidemiology investigation was developed and implemented in energy regulation benchmarking. Using Brazilian electricity energy distribution utilities, the proposed methodology applies spatial Bayesian analysis to estimate the number of clusters and the utilities in each cluster. By dividing the utilities into smaller, but geographically closer groups, it can be argued that local determinants of production or environmental components are accounted in the benchmarking model. Thus, the proposed method requires the spatial location of the utilities and their cost efficiencies, estimated previously by the regulator. Results show two detected clusters with high and low efficiencies located in the east and west of Brazil. After applying the regulator model to the detected groups, significant changes in cost efficiencies were estimated for a few utilities. This is important information that can be used by the regulator to estimate future cost incentives.

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