Abstract
Exponential development of solar photovoltaic projects during the past decades has vastly relied on findings from location identification analyses. This article draws upon the most important site selection factors in order to identify optimum locations for development of solar plants in Turkey from a subset of thirty selected Turkish cities. This study applies CCR, BCC, stochastic frontier analysis (SFA) and Kourosh and Arash Model (KAM) methods in decision-making. KAM method is a new powerful technique in measuring efficiency of firms (DMUs) and has obtained an important role in economy and managements. It also benefits from the novelty of using copula technique in the SFA methods which has been only recently presented to the literature.
Keywords
References
- [1] Aigner, D.J., Lovell, C.A.K., Schmidt, P., Formulation and estimation of stochastic frontier production functions, Journal of Econometrics, 6 (1977), 21–37.
- [2] Amsler, C., Prokhorov, A., Schmidt, P., Using copulas to model time dependence in stochastic frontier models, Econometric Reviews, 33 (56)(2014), 497–522. [3] Bal, H., Najjari, V., Archimedean copulas family via hyperbolic generator, GU J Sci. 26:(2)(2013), 195–200 .
- [4] Carta, A., Steel, M. F. J., Modelling multi-output stochastic frontiers using copulas, Computational Statistics and Data Analysis, 56 (2012), 3757–3773.
- [5] Charnes, A., Cooper, W. W., Lewin, A. Y., Morey, R. C., Rousseau, J., Sensitivity and stability analysis in DEA. Annals of Operations Research, 2(1985), 139–156. 13
- [6] El Mehdi, R., Hafner, C.M., Inferences in stochastic frontier analysis with dependent error terms, Mathematics and computers in simulation, (2013).
- [7] Khezrimotlagh, D., Salleh, S., Mohsenpour, Z., A new method for evaluating decision making units in DEA, Journal of the Operational Research Society, 65(1) (2013), 694–707.
- [8] Nelsen, R. B., An Introduction to copulas, second edition, Springer, New York, 2006.
- [9] Meeusen, W., Van Den Broeck, J., Efficiency estimation from CobbDouglas production functions with composed error, International Economic Review, 18 (1977) 435–444.
- [10] Najjari, V., Baciga´l, T., Bal, H., An Archimedean copula family with hyperbolic cotangent generator, IJUFKS, 2014-in press.
- [11] Sklar, A., Fonctions de r´epartition a` n dimensions et leurs marges, Publ. Inst. Statist. Univ. Paris, 8 (1959) 229–231.
- [12] Smith, M. D., Stochastic frontier models with dependent error components, The Econometrics Journal, 11 (2008), 172–192.
- [13] Sozen, A., Mirzapour, A., Tariik Cakir, M. Selection of best location for solar plants by the DEA approach in turkish cities, Renewable Energy·November 2015 , 26(4):52-63 .
Abstract
Exponential development of solar photovoltaic projects during the past decades has vastly relied on findings from location identification analyses. This article draws upon the most important site selection factors in order to identify optimum locations for development of solar plants in Turkey from a subset of thirty selected Turkish cities. This study applies CCR, BCC, stochastic frontier analysis (SFA) and Kourosh and Arash Model (KAM) methods in decision-making. KAM method is a new powerful technique in measuring efficiency of firms (DMUs) and has obtained an important role in economy and managements. It also benefits from the novelty of using copula technique in the SFA methods which has been only recently presented to the literature.
Keywords
References
- [1] Aigner, D.J., Lovell, C.A.K., Schmidt, P., Formulation and estimation of stochastic frontier production functions, Journal of Econometrics, 6 (1977), 21–37.
- [2] Amsler, C., Prokhorov, A., Schmidt, P., Using copulas to model time dependence in stochastic frontier models, Econometric Reviews, 33 (56)(2014), 497–522. [3] Bal, H., Najjari, V., Archimedean copulas family via hyperbolic generator, GU J Sci. 26:(2)(2013), 195–200 .
- [4] Carta, A., Steel, M. F. J., Modelling multi-output stochastic frontiers using copulas, Computational Statistics and Data Analysis, 56 (2012), 3757–3773.
- [5] Charnes, A., Cooper, W. W., Lewin, A. Y., Morey, R. C., Rousseau, J., Sensitivity and stability analysis in DEA. Annals of Operations Research, 2(1985), 139–156. 13
- [6] El Mehdi, R., Hafner, C.M., Inferences in stochastic frontier analysis with dependent error terms, Mathematics and computers in simulation, (2013).
- [7] Khezrimotlagh, D., Salleh, S., Mohsenpour, Z., A new method for evaluating decision making units in DEA, Journal of the Operational Research Society, 65(1) (2013), 694–707.
- [8] Nelsen, R. B., An Introduction to copulas, second edition, Springer, New York, 2006.
- [9] Meeusen, W., Van Den Broeck, J., Efficiency estimation from CobbDouglas production functions with composed error, International Economic Review, 18 (1977) 435–444.
- [10] Najjari, V., Baciga´l, T., Bal, H., An Archimedean copula family with hyperbolic cotangent generator, IJUFKS, 2014-in press.
- [11] Sklar, A., Fonctions de r´epartition a` n dimensions et leurs marges, Publ. Inst. Statist. Univ. Paris, 8 (1959) 229–231.
- [12] Smith, M. D., Stochastic frontier models with dependent error components, The Econometrics Journal, 11 (2008), 172–192.
- [13] Sozen, A., Mirzapour, A., Tariik Cakir, M. Selection of best location for solar plants by the DEA approach in turkish cities, Renewable Energy·November 2015 , 26(4):52-63 .
Details
| Primary Language | English |
|---|---|
| Subjects | Engineering |
| Journal Section | Research Article |
| Authors | |
| Publication Date | December 1, 2020 |
| Submission Date | August 10, 2019 |
| Published in Issue | Year 2020 |
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