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, cilt.45, sa.1, ss.17-25, 2018 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 45 Sayı: 1
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1080/02664763.2016.1257586
  • Dergi Adı: JOURNAL OF APPLIED STATISTICS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus
  • Sayfa Sayıları: ss.17-25
  • Anahtar Kelimeler: Bayesian, stochastic frontier analysis, Bayesian network, energy, PRODUCTION EFFICIENCY, INFERENCE, MODELS, INDUSTRY
  • Ondokuz Mayıs Üniversitesi Adresli: Evet

Özet

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.