Literature DB >> 35813081

Estimating the efficiency of Brazilian electricity distribution utilities.

Marcus Gerardus L Nascimento1, Ralph S Silva1, Mario Jorge Mendonça2, Amaro Olimpio Pereira3.   

Abstract

This paper proposes a differing methodology from the Brazilian Electricity Regulatory Agency on the efficiency estimation for the Brazilian electricity distribution sector. Our proposal combines robust state-space models and stochastic frontier analysis to measure the operational cost efficiency in a panel data set from 60 Brazilian electricity distribution utilities. The modeling joins the main literature in energy economics with advanced econometric and statistic techniques in order to estimate the efficiencies. Moreover, the suggested model is able to deal with changes in the inefficiencies across time whilst the Bayesian paradigm - through Markov chain Monte Carlo techniques - facilitates the inference on all unknowns. The method enables a significant degree of flexibility in the resultant efficiencies and a complete photography about the distribution sector.
© 2021 Informa UK Limited, trading as Taylor & Francis Group.

Entities:  

Keywords:  Bayesian inference; Gibbs sampler; Stochastic frontier analysis; scale mixture of normal distributions; state-space models

Year:  2021        PMID: 35813081      PMCID: PMC9267423          DOI: 10.1080/02664763.2021.1890000

Source DB:  PubMed          Journal:  J Appl Stat        ISSN: 0266-4763            Impact factor:   1.416


  1 in total

1.  Bayesian inference for finite mixtures of univariate and multivariate skew-normal and skew-t distributions.

Authors:  Sylvia Frühwirth-Schnatter; Saumyadipta Pyne
Journal:  Biostatistics       Date:  2010-01-27       Impact factor: 5.899

  1 in total

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