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What is the best practice for benchmark regulation of electricity distribution? Comparison of DEA, SFA and StoNED methods

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Cited by:

  1. Agrell, Per J. & Teusch, Jonas, 2020. "Predictability and strategic behavior under frontier regulation," Energy Policy, Elsevier, vol. 137(C).
  2. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
  3. Pavala Malar Kannan & Govindan Marthandan & Rathimala Kannan, 2021. "Modelling Efficiency of Electric Utilities Using Three Stage Virtual Frontier Data Envelopment Analysis with Variable Selection by Loads Method," Energies, MDPI, vol. 14(12), pages 1-21, June.
  4. Nguyen, Trang T.T. & Prior, Diego & Van Hemmen, Stefan, 2020. "Stochastic semi-nonparametric frontier approach for tax administration efficiency measure: Evidence from a cross-country study," Economic Analysis and Policy, Elsevier, vol. 66(C), pages 137-153.
  5. Papadopoulos, Alecos & Parmeter, Christopher F., 2021. "Type II failure and specification testing in the Stochastic Frontier Model," European Journal of Operational Research, Elsevier, vol. 293(3), pages 990-1001.
  6. Jose M. Cordero & Cristina Polo & Daniel Santín, 2020. "Assessment of new methods for incorporating contextual variables into efficiency measures: a Monte Carlo simulation," Operational Research, Springer, vol. 20(4), pages 2245-2265, December.
  7. Kuosmanen, Timo & Johnson, Andrew, 2017. "Modeling joint production of multiple outputs in StoNED: Directional distance function approach," European Journal of Operational Research, Elsevier, vol. 262(2), pages 792-801.
  8. Andor, Mark A. & Parmeter, Christopher & Sommer, Stephan, 2019. "Combining uncertainty with uncertainty to get certainty? Efficiency analysis for regulation purposes," European Journal of Operational Research, Elsevier, vol. 274(1), pages 240-252.
  9. Daniel Leite & José Pessanha & Paulo Simões & Rodrigo Calili & Reinaldo Souza, 2020. "A Stochastic Frontier Model for Definition of Non-Technical Loss Targets," Energies, MDPI, vol. 13(12), pages 1-20, June.
  10. Proskuryakova, Liliana & Starodubtseva, Alena & Bianco, Vincenzo, 2020. "Modelling a household tariff for reducing sectoral cross-subsidies in the Russian power market," Energy, Elsevier, vol. 213(C).
  11. Mountain, Bruce R., 2019. "Ownership, regulation, and financial disparity: The case of electricity distribution in Australia," Utilities Policy, Elsevier, vol. 60(C), pages 1-1.
  12. Saastamoinen, Antti & Bjørndal, Endre & Bjørndal, Mette, 2017. "Specification of merger gains in the Norwegian electricity distribution industry," Energy Policy, Elsevier, vol. 102(C), pages 96-107.
  13. José Luis Preciado Arreola & Daisuke Yagi & Andrew L. Johnson, 2020. "Insights from machine learning for evaluating production function estimators on manufacturing survey data," Journal of Productivity Analysis, Springer, vol. 53(2), pages 181-225, April.
  14. Al Aali-Bujari & Francisco Venegas-Mart nez & Roberto J. Santill n-Salgado, 2018. "On the Stock Market-Electricity Sector Nexus in Latin America: A Dynamic Panel Data Model," International Journal of Energy Economics and Policy, Econjournals, vol. 8(6), pages 148-154.
  15. Kuosmanen, Timo & Nguyen, Tuan, 2020. "Capital bias in the Nordic revenue cap regulation: Averch-Johnson critique revisited," Energy Policy, Elsevier, vol. 139(C).
  16. Sugathan, Anish & Malghan, Deepak & Chandrashekar, S. & Sinha, Deepak K., 2019. "Downstream electric utility restructuring and upstream generation efficiency: Productivity dynamics of Indian coal and gas based electricity generators," Energy, Elsevier, vol. 178(C), pages 832-852.
  17. Ørjan Mydland, 2020. "Lost economies of scope and potential merger gains in the Norwegian electricity industry," Empirical Economics, Springer, vol. 58(6), pages 3077-3100, June.
  18. Maziotis, Alexandros & Sala-Garrido, Ramon & Mocholi-Arce, Manuel & Molinos-Senante, Maria, 2023. "Cost and quality of service performance in the Chilean water industry: A comparison of stochastic approaches," Structural Change and Economic Dynamics, Elsevier, vol. 67(C), pages 211-219.
  19. Agrell, Per J. & Brea-Solís, Humberto, 2017. "Capturing heterogeneity in electricity distribution operations: A critical review of latent class modelling," Energy Policy, Elsevier, vol. 104(C), pages 361-372.
  20. Afsharian, Mohsen & Kamali, Sara & Ahn, Heinz & Bogetoft, Peter, 2024. "Individualized second stage corrections in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 317(2), pages 563-577.
  21. L sara Fabr cia Rodrigues & Matheus Alves Madeira de Souza & Thamara Paula dos Santos Dias, 2017. "Performance Assessment of Brazilian Power Transmission and Distribution Segments using Data Envelopment Analysis," International Journal of Energy Economics and Policy, Econjournals, vol. 7(3), pages 14-23.
  22. Lee, Boon L. & Wilson, Clevo & Simshauser, Paul & Majiwa, Eucabeth, 2021. "Deregulation, efficiency and policy determination: An analysis of Australia's electricity distribution sector," Energy Economics, Elsevier, vol. 98(C).
  23. Antti Saastamoinen, 2015. "Heteroscedasticity Or Production Risk? A Synthetic View," Journal of Economic Surveys, Wiley Blackwell, vol. 29(3), pages 459-478, July.
  24. Chen, Zhongfei & Barros, Carlos Pestana & Borges, Maria Rosa, 2015. "A Bayesian stochastic frontier analysis of Chinese fossil-fuel electricity generation companies," Energy Economics, Elsevier, vol. 48(C), pages 136-144.
  25. Ricardo F. Díaz & Blanca Sanchez-Robles, 2020. "Non-Parametric Analysis of Efficiency: An Application to the Pharmaceutical Industry," Mathematics, MDPI, vol. 8(9), pages 1-27, September.
  26. Janda, Karel & Krska, Stepan, 2014. "Benchmarking Methods in the Regulation of Electricity Distribution System Operators," MPRA Paper 59442, University Library of Munich, Germany.
  27. Olesen, Ole B. & Petersen, Niels Christian, 2016. "Stochastic Data Envelopment Analysis—A review," European Journal of Operational Research, Elsevier, vol. 251(1), pages 2-21.
  28. Julia Schaefer & Marcel Clermont, 2018. "Stochastic non-smooth envelopment of data for multi-dimensional output," Journal of Productivity Analysis, Springer, vol. 50(3), pages 139-154, December.
  29. Saastamoinen, Antti & Kuosmanen, Timo, 2016. "Quality frontier of electricity distribution: Supply security, best practices, and underground cabling in Finland," Energy Economics, Elsevier, vol. 53(C), pages 281-292.
  30. Cheng, Xiaomei & Bjørndal, Endre & Lien, Gudbrand & Bjørndal, Mette, 2015. "Productivity Development for Norwegian Electricity Distribution Companies 2004-2013," Discussion Papers 2015/27, Norwegian School of Economics, Department of Business and Management Science.
  31. Zhengxiao Yan & Wei Zhou & Yuyi Wang & Xi Chen, 2022. "Comprehensive Analysis of Grain Production Based on Three-Stage Super-SBM DEA and Machine Learning in Hexi Corridor, China," Sustainability, MDPI, vol. 14(14), pages 1-21, July.
  32. Collan, Mikael & Savolainen, Jyrki & Lilja, Emma, 2022. "Analyzing the returns and rate of return regulation of Finnish electricity distribution system operators 2015–2019," Energy Policy, Elsevier, vol. 160(C).
  33. Cheng, Xiaomei & Bjørndal, Endre & Bjørndal, Mette, 2015. "Malmquist Productivity Analysis based on StoNED," Discussion Papers 2015/25, Norwegian School of Economics, Department of Business and Management Science.
  34. Zakaria, Muhammad & Noureen, Rabia, 2016. "Benchmarking and regulation of power distribution companies in Pakistan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1095-1099.
  35. Cardoso de Mendonça, Mário Jorge & Pereira, Amaro Olimpio & Medrano, Luis Alberto & Pessanha, José Francisco M., 2021. "Analysis of electric distribution utilities efficiency levels by stochastic frontier in Brazilian power sector," Socio-Economic Planning Sciences, Elsevier, vol. 76(C).
  36. Llorca, Manuel & Orea, Luis & Pollitt, Michael G., 2014. "Using the latent class approach to cluster firms in benchmarking: An application to the US electricity transmission industry," Operations Research Perspectives, Elsevier, vol. 1(1), pages 6-17.
  37. Maria Nieswand & Stefan Seifert, 2016. "Operational Conditions in Regulatory Benchmarking Models: A Monte Carlo Analysis," Discussion Papers of DIW Berlin 1585, DIW Berlin, German Institute for Economic Research.
  38. Lin, Sheng-Wei & Lu, Wen-Min, 2024. "A comparison of chance-constrained data envelopment analysis, stochastic nonparametric envelopment of data and bootstrap method: A case study of cultural regeneration performance of cities," European Journal of Operational Research, Elsevier, vol. 316(3), pages 1179-1191.
  39. Kao, Chiang & Liu, Shiang-Tai, 2019. "Stochastic efficiency measures for production units with correlated data," European Journal of Operational Research, Elsevier, vol. 273(1), pages 278-287.
  40. Nieswand, Maria & Seifert, Stefan, 2018. "Environmental factors in frontier estimation – A Monte Carlo analysis," European Journal of Operational Research, Elsevier, vol. 265(1), pages 133-148.
  41. Yao, Xin & Huang, Ruting & Du, Kerui, 2019. "The impacts of market power on power grid efficiency: Evidence from China," China Economic Review, Elsevier, vol. 55(C), pages 99-110.
  42. Ouyang, Xiaoling & Wei, Xiaoyun & Sun, Chuanwang & Du, Gang, 2018. "Impact of factor price distortions on energy efficiency: Evidence from provincial-level panel data in China," Energy Policy, Elsevier, vol. 118(C), pages 573-583.
  43. Janjic, Aleksandar & Velimirovic, Lazar Z. & Vranic, Petar, 2021. "Designing an electricity distribution reward-penalty scheme based on spatial reliability statistics," Utilities Policy, Elsevier, vol. 70(C).
  44. Kuosmanen, Timo, 2012. "Stochastic semi-nonparametric frontier estimation of electricity distribution networks: Application of the StoNED method in the Finnish regulatory model," Energy Economics, Elsevier, vol. 34(6), pages 2189-2199.
  45. Ferrara, Giancarlo & Vidoli, Francesco, 2017. "Semiparametric stochastic frontier models: A generalized additive model approach," European Journal of Operational Research, Elsevier, vol. 258(2), pages 761-777.
  46. Li, Hong-Zhou & Tian, Xian-Liang & Zou, Tao, 2015. "Impact analysis of coal-electricity pricing linkage scheme in China based on stochastic frontier cost function," Applied Energy, Elsevier, vol. 151(C), pages 296-305.
  47. Campbell, Alrick, 2018. "Cap prices or cap revenues? The dilemma of electric utility networks," Energy Economics, Elsevier, vol. 74(C), pages 802-812.
  48. Molinos-Senante, Maria & Maziotis, Alexandros, 2022. "Evaluation of energy efficiency of wastewater treatment plants: The influence of the technology and aging factors," Applied Energy, Elsevier, vol. 310(C).
  49. Saastamoinen, Antti & Bjørndal, Endre & Bjørndal, Mette, 2016. "Specification of merger gains in the Norwegian electricity distribution industry," Discussion Papers 2016/7, Norwegian School of Economics, Department of Business and Management Science.
  50. Papadopoulos, Alecos & Parmeter, Christopher F., 2023. "A specification test for the composed error term in the stochastic frontier model," Economics Letters, Elsevier, vol. 233(C).
  51. Liu, Fangmei & Li, Li & Ye, Bin & Qin, Quande, 2023. "A novel stochastic semi-parametric frontier-based three-stage DEA window model to evaluate China's industrial green economic efficiency," Energy Economics, Elsevier, vol. 119(C).
  52. Chao Wang & Xi Chu & Jinyan Zhan & Pei Wang & Fan Zhang & Zhongling Xin, 2019. "Factors Contributing to Efficient Forest Production in the Region of the Three-North Shelter Forest Program, China," Sustainability, MDPI, vol. 12(1), pages 1-19, December.
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