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Combining the Virtues of Stochastic Frontier and Data Envelopment Analysis

Citations

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Cited by:

  1. Tsionas, Mike & Parmeter, Christopher F. & Zelenyuk, Valentin, 2023. "Bayesian Artificial Neural Networks for frontier efficiency analysis," Journal of Econometrics, Elsevier, vol. 236(2).
  2. Mark A. Andor & David H. Bernstein & Stephan Sommer, 2021. "Determining the efficiency of residential electricity consumption," Empirical Economics, Springer, vol. 60(6), pages 2897-2923, June.
  3. Tsionas, Mike & Zelenyuk, Valentin & Zhang, Xibin, 2025. "Goodness-of-fit in production models: A Bayesian perspective," European Journal of Operational Research, Elsevier, vol. 324(2), pages 644-653.
  4. Bao Hoang Nguyen & Valentin Zelenyuk, 2020. "Robust efficiency analysis of public hospitals in Queensland, Australia," CEPA Working Papers Series WP052020, School of Economics, University of Queensland, Australia.
  5. Kamil Makieła & Błażej Mazur, 2022. "Model uncertainty and efficiency measurement in stochastic frontier analysis with generalized errors," Journal of Productivity Analysis, Springer, vol. 58(1), pages 35-54, August.
  6. Alizadeh, Reza & Gharizadeh Beiragh, Ramin & Soltanisehat, Leili & Soltanzadeh, Elham & Lund, Peter D., 2020. "Performance evaluation of complex electricity generation systems: A dynamic network-based data envelopment analysis approach," Energy Economics, Elsevier, vol. 91(C).
  7. Dan Ben-Moshe & David Genesove, 2025. "Identifying the Frontier Structural Function and Bounding Mean Deviations," Papers 2504.19832, arXiv.org, revised May 2025.
  8. Bogetoft, Peter & Ramírez-Ayerbe, Jasone & Romero Morales, Dolores, 2024. "Counterfactual analysis and target setting in benchmarking," European Journal of Operational Research, Elsevier, vol. 315(3), pages 1083-1095.
  9. Huang, Xuhui & Zhou, Tao & Zhang, Ning, 2025. "How does the carbon market influence the marginal abatement cost? Evidence from China's coal-fired power plants," Applied Energy, Elsevier, vol. 378(PA).
  10. Mamonov Mikhail E. & Parmeter Christopher F. & Prokhorov Artem B., 2022. "Dependence modeling in stochastic frontier analysis," Dependence Modeling, De Gruyter, vol. 10(1), pages 123-144, January.
  11. Shirong Zhao & Jeremy Losak, 2024. "Two-tiered stochastic frontier models: a Bayesian perspective," Journal of Productivity Analysis, Springer, vol. 61(2), pages 85-106, April.
  12. Juan Agar & William C. Horrace & Christopher F. Parmeter, 2022. "Overcapacity in Gulf of Mexico reef fish IFQ fisheries: 12 years after the adoption of IFQs," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 82(2), pages 483-506, June.
  13. Otsuka, Akihiro, 2023. "Industrial electricity consumption efficiency and energy policy in Japan," Utilities Policy, Elsevier, vol. 81(C).
  14. Khezrimotlagh, Dariush, 2022. "Simulation designs for production frontiers," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1321-1334.
  15. Akihiro Otsuka, 2023. "Stochastic demand frontier analysis of residential electricity demands in Japan," Asia-Pacific Journal of Regional Science, Springer, vol. 7(1), pages 179-195, March.
  16. Zhou, Jianhua & Parmeter, Christopher F. & Kumbhakar, Subal C., 2020. "Nonparametric estimation of the determinants of inefficiency in the presence of firm heterogeneity," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1142-1152.
  17. Radovanović, Sandro & Savić, Gordana & Delibašić, Boris & Suknović, Milija, 2022. "FairDEA—Removing disparate impact from efficiency scores," European Journal of Operational Research, Elsevier, vol. 301(3), pages 1088-1098.
  18. Centorrino, Samuele & Parmeter, Christopher F., 2024. "Nonparametric estimation of stochastic frontier models with weak separability," Journal of Econometrics, Elsevier, vol. 238(2).
  19. Yan Meng & Christopher F. Parmeter & Valentin Zelenyuk, 2023. "Is newer always better? A reinvestigation of productivity dynamics using updated PWT data," Journal of Productivity Analysis, Springer, vol. 59(1), pages 1-13, February.
  20. Zhichao Wang & Bao Hoang Nguyen & Valentin Zelenyuk, 2024. "Performance analysis of hospitals in Australia and its peers: a systematic and critical review," Journal of Productivity Analysis, Springer, vol. 62(2), pages 139-173, October.
  21. Mike Tsionas & Valentin Zelenyuk, 2021. "Goodness-of-fit in Optimizing Models of Production: A Generalization with a Bayesian Perspective," CEPA Working Papers Series WP182021, School of Economics, University of Queensland, Australia.
  22. Du, Kai & Zelenyuk, Valentin, 2025. "Likelihood-ratio test for technological differences in two-stage data envelopment analysis for panel data," European Journal of Operational Research, Elsevier, vol. 321(2), pages 644-663.
  23. Mike G. Tsionas & Valentin Zelenyuk, 2022. "Testing for Optimization Behavior in Production when Data is with Measurement Errors: A Bayesian Approach," CEPA Working Papers Series WP012022, School of Economics, University of Queensland, Australia.
  24. Tsionas, Mike G., 2023. "Clustering and meta-envelopment in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 304(2), pages 763-778.
  25. Mike Tsionas & Christopher F. Parmeter & Valentin Zelenyuk, 2021. "Bridging the Divide? Bayesian Artificial Neural Networks for Frontier Efficiency Analysis," CEPA Working Papers Series WP082021, School of Economics, University of Queensland, Australia.
  26. Yongseung Han & Arthur Snow & Ronald S. Warren, 2021. "Changes in the productive efficiency of U.S. flour mills in the late nineteenth century: an input-distance-function approach," Journal of Productivity Analysis, Springer, vol. 56(2), pages 115-132, December.
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