Energy performance evaluation of OECD countries using Bayesian stochastic frontier analysis and Bayesian network classifiers

Cengiz M. A., Dünder E., ŞENEL T.

JOURNAL OF APPLIED STATISTICS, vol.45, no.1, pp.17-25, 2018 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 45 Issue: 1
  • Publication Date: 2018
  • Doi Number: 10.1080/02664763.2016.1257586
  • Journal Name: JOURNAL OF APPLIED STATISTICS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus
  • Page Numbers: pp.17-25
  • Keywords: Bayesian, stochastic frontier analysis, Bayesian network, energy, PRODUCTION EFFICIENCY, INFERENCE, MODELS, INDUSTRY
  • Ondokuz Mayıs University Affiliated: Yes

Abstract

More recently a large amount of interest has been devoted to the use of Bayesian methods for deriving parameter estimates of the stochastic frontier analysis. Bayesian stochastic frontier analysis (BSFA) seems to be a useful method to assess the efficiency in energy sector. However, BSFA results do not expose the multiple relationships between input and output variables and energy efficiency. This study proposes a framework to make inferences about BSFA efficiencies, recognizing the underlying relationships between variables and efficiency, using Bayesian network (BN) approach. BN classifiers are proposed as a method to analyze the results obtained from BSFA.