Spatial statistical methods applied to the 2015 brazilian energy distribution benchmarking model: accounting for unobserved determinants of inefficiencies

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Universidade Federal de Minas Gerais

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Artigo de periódico

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Membros da banca

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In 2015 the Brazilian regulator presented a DEA benchmarking model to set the regulatory operational cost goals, to be reached in four years for 61 electricity distribution utilities. The DEA model uses: adjusted operational cost as the input variable, seven output variables and weight restrictions. Although non-discretionary variables or en vironmental variables are available in the dataset, the regulator argued that no statistically signicant correlation was found between the DEA efciency scores and the non-discretionary variables. This study evaluates the sta tistical correlation between the DEA efciency scores and the available environmental variables. Spatial statistic methods are used to show that the efciency scores are geographically correlated. Furthermore, due to Brazil's environmental diversity and large territory it is unlikely that only one environmental component is sufcient to adjust inefciencies across the Brazilian territory. Thus, a new combined environmental variable is proposed. Finally, a second stage model using the proposed environmental variable and accounting for a spatial latent struc ture is presented. Results show major differences between original and corrected efciency scores, mainly for utilities located in harsh environments and which originally achieved lower efciency scores

Abstract

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Energia

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Data Envelopment Analysis, Second stage analysis, Spatial statistics, Bayesian analysis

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http://www.sciencedirect.com/science/article/pii/S0140988317301160doi:10.1016/j.eneco.2017.04.009

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