SavedAdd your journal

Journals / Gazi University Journal of Science / 2026 / Volume: 29 Issue: 1

USING DATA ENVELOPMENT ANALYSIS AND STOCHASTIC FRONTIER ANALYSIS METHODS TO EVALUATE EFFICIENCY OF HYDROELECTRICITY CENTERS

Hydroelectricity Centers

Harun Kınacı
Vadoud Najjari
İhsan Alp
Pages
—
Publication Date
2016-03-21
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Applying copula technique in the stochastic frontier analysis is an advantage to our study between similar activities.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study clarifies efficiency scores and also ranks of hydroelectricity centers by using data envelopment analysis and stochastic frontier analysis methods.
📊
Key Findings & Data:This study clarifies efficiency scores and also ranks of hydroelectricity centers by using data envelopment analysis and stochastic frontier analysis methods.
💡
Conclusion & Impact:Applying copula technique in the stochastic frontier analysis is an advantage to our study between similar activities.
🔬Design:Article
📍Scope:Comprehensive Sample
⚙️Variables:Data Envelopment Analysis · Stochastic Frontier Analysis · Copulas

Abstract

This study clarifies efficiency scores and also ranks of hydroelectricity centers by using data envelopment analysis and stochastic frontier analysis methods. Applying copula technique in the stochastic frontier analysis is an advantage to our study between similar activities.

🔖

Cite This Article

Kınacı, H., Najjari, V., Alp, İ. (2016). USING DATA ENVELOPMENT ANALYSIS AND STOCHASTIC FRONTIER ANALYSIS METHODS TO EVALUATE EFFICIENCY OF HYDROELECTRICITY CENTERS. Gazi University Journal of Science, Volume: 29 Issue: 1. https://ajindex.com/articles/1269543

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (22)

  1. Aigner, D. J.,Lovell, C. A. K.,Schmidt, P., (1977). Formulation and estimation of stochastic frontier production functions. Journal of Econometrics, 6, 21-37.
  2. Alp,İ., (2006). Performance of evaluation of Goalkeepers of World Cup.GUJournal of Science, 19 (2), 119-125.
  3. Alp, İ., Sözen, A., (2011). Efficiency Assessment of Turkey's Carbonization Index. Energy Sources, Part A:
  4. Recovery, Utilization, and Environmental Effects, 33(18),1678-1691.
  5. Amsler, C., Prokhorov, A., Schmidt, P., (2014). Using copulas to model time dependence in stochastic frontier models. Econometric Reviews, 33 (5-6), 497-522.
  6. Anderson,T., Sharp,G., (1997). A New Measure of Baseball Batters Using DEA. Annals of Operations Research, 73, 141-155.
  7. Banker, R.D., Charnes, A., Cooper, W.W., (1984). Some Models For Estimating Technical And Scale Inefficiencies In Data Envelopment Analysis. Management Science, 30, 1078–1092.
  8. Carta, A. M., Steel, F. J., (2012). Modelling multi-output stochastic frontiers using copulas. Computational Statistics and Data Analysis, 56, 3757-3773.
  9. Charnes, A., Cooper, W.W., Rhodes, E., (1978). Measuring The Efficiency Of Decision Making Units. European Journal of Operation Research, 2, 429–444.
  10. Dedoussis, V., Konstas, K., Kassimis, A., Sofianopoulou, S., (2010).Efficiency evaluation of hydroelectric power plants using Data envelopment analysis. Proceedings of 2nd international conference on applied operational research.
  11. El Mehdi, R., Hafner, C. M., (2013). Inferences in stochastic frontier analysis with dependent error terms. Mathematics and computers in simulation.
  12. Kumbhakar, S.C., Knox Lovell, C. A., (2000). Stochastic frontier analysis. Cambridge University Press.
  13. Meeusen,W., Van Den Broeck, J., (1977). Efficiency estimation from Cobb-Douglas production functions with composed error. International Economic Review, 18, 435-444.
  14. Mercan,M.,Reisman,A., Yoalan,R., Emel,A.B., (2003). The Effect of Scale and Mode of Ownership on the Financial Performance of the Turkish Banking Sector: Results of A DEA Based Analysis. Social-Economic Planning Sciences, 37, 185-202.
  15. Najjari, V., Mirzapour, A., (in press). Investigating location of solar plants by several methods. Journal of Applied Statistics.
  16. Najjari, V.,Bal, H., Özturk, F., Alp, İ., (in press) Stochastic frontier models by copulas and an application. Scientific Bulletin.
  17. Nelsen, R. B., (2006). An Introduction to copulas, Second Edition, New York, Springer.
  18. Ramanathan, R., (2003). An Introduction to Data Envelopment Analysis: A Tool for Performance Measurement. SAGE Publications, India.
  19. Sklar, A., (1959). Fonctions de répartition á n dimensions etleursmarges. Publ. Inst. Statist. Univ. Paris, 8, 229-231.
  20. Smith, M. D., (2008). Stochastic frontier models with dependent error components. The Econometrics Journal, 11, 172-192.
  21. Sözen,A., Alp,İ.,(2009). Comparison of Turkey's performance of greenhouse gas emissions and local/ regional pollutants with EU countries. Energy Policy. 37, 5007-5018.
  22. Vaz, C.B., Ferreira, Â. P., (2012). Performance assessment of hydroelectric power plants. 4th Workshop on Efficiency and Productivity Analysis Efficiency in the Health Sector.