Dergiler / Gazi University Journal of Science / 2016 / Cilt: 29 - Sayı: 1

Hydroelectricity Centers

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

Sayfa
167–176
Yayın Tarihi
2016-03-21
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

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

📌 3 Maddede Bu Makale

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Amaç & Hipotez:This study clarifies efficiency scores and also ranks of hydroelectricity centers by using data envelopment analysis and stochastic frontier analysis methods.
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Temel Bulgular & Veri:This study clarifies efficiency scores and also ranks of hydroelectricity centers by using data envelopment analysis and stochastic frontier analysis methods.
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Sonuç & Katkı:Applying copula technique in the stochastic frontier analysis is an advantage to our study between similar activities.
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler: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.

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Bu Makaleye Atıf Yap

Kınacı, H., Najjari, V., Alp, İ. (2016). Hydroelectricity Centers. Gazi University Journal of Science, Cilt: 29 - Sayı: 1, 167–176. https://ajindex.com/articles/254643

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Kaynakça (10)

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  2. Alp, İ., Sözen, A., (2011). Efficiency Assessment of Turkey's Carbonization Index. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 33(18),1678-1691.
  3. Amsler, C., Prokhorov, A., Schmidt, P., (2014). Using copulas to model time dependence in stochastic frontier models. Econometric Reviews, 33 (5-6), 497-522. Anderson,T., Sharp,G., (1997). A New Measure of Baseball Batters Using DEA. Annals of Operations Research, 73, 141-155.
  4. 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.
  5. Carta, A. M., Steel, F. J., (2012). Modelling multi-output stochastic frontiers using copulas. Computational Statistics and Data Analysis, 56, 3757-3773.
  6. Charnes, A., Cooper, W.W., Rhodes, E., (1978). Measuring The Efficiency Of Decision Making Units. European Journal of Operation Research, 2, 429–444.
  7. 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. El Mehdi, R., Hafner, C. M., (2013). Inferences in stochastic frontier analysis with dependent error terms. Mathematics and computers in simulation. Kumbhakar, S.C., Knox Lovell, C. A., (2000). Stochastic frontier analysis. Cambridge University Press. Meeusen,W., Van Den Broeck, J., (1977). Efficiency estimation from Cobb-Douglas production functions with composed error. International Economic Review, 18, 435-444. 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.
  8. Najjari, V., Mirzapour, A., (in press). Investigating location of solar plants by several methods. Journal of Applied Statistics. Najjari, V.,Bal, H., Özturk, F., Alp, İ., (in press) Stochastic frontier models by copulas and an application. Scientific Bulletin. Nelsen, R. B., (2006).
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  10. New York, Springer. Ramanathan, R., (2003). An Introduction to Data Envelopment Analysi