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Modeling joint production of multiple outputs in StoNED: Directional distance function approach

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  1. Zhao, Yu & Zhong, Honglin & Kong, Fanbin & Zhang, Ning, 2023. "Can China achieve carbon neutrality without power shortage? A substitutability perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
  2. Yin, Kai & Yao, Xin, 2025. "How has China's urban compactness affected urban CO2 abatement costs?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 211(C).
  3. 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.
  4. 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.
  5. Guillen, Maria D. & Charles, Vincent & Aparicio, Juan, 2025. "Estimating non-overfitted convex production technologies: A stochastic machine learning approach," European Journal of Operational Research, Elsevier, vol. 323(1), pages 224-240.
  6. Timo Kuosmanen & Sheng Dai, 2025. "Modeling economies of scope in joint production: Convex regression of input distance function," Journal of Productivity Analysis, Springer, vol. 63(1), pages 69-86, February.
  7. Haleh Delnava & Kristiaan Kerstens & Timo Kuosmanen & Zhiyang Shen, 2024. "Semi-parametric Estimation of Convex and Nonconvex By-Production Technologies," Working Papers 2024-EQM-02, IESEG School of Management.
  8. Josiah Aduda & Stephen Obondy, 2021. "Credit Risk Management and Efficiency of Savings and Credit Cooperative Societies: A Review of Literature," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 11(1), pages 1-7.
  9. Kuosmanen, Natalia & Kuosmanen, Timo & Zhou, Xun, 2026. "Do R&D Spillovers Support Low-carbon Transition? Firm-level Evidence from Finnish Energy-intensive Manufacturing," ETLA Working Papers 136, The Research Institute of the Finnish Economy.
  10. 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.
  11. 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.
  12. Yang, Min & Wang, Zixuan & Liang, Liang, 2025. "A novel centralized cross-efficiency evaluation via explainable artificial intelligence in the context of big data," European Journal of Operational Research, Elsevier, vol. 327(1), pages 247-262.
  13. Arabmaldar, Aliasghar & Sahoo, Biresh K. & Ghiyasi, Mojtaba, 2023. "A generalized robust data envelopment analysis model based on directional distance function," European Journal of Operational Research, Elsevier, vol. 311(2), pages 617-632.
  14. Hu, Shuo & Wang, Ailun & Lin, Boqiang, 2024. "Marginal abatement cost of CO2: A convex quantile non-radial directional distance function regression method considering noise and inefficiency," Energy, Elsevier, vol. 297(C).
  15. Alexander Arévalo S & V�ctor Gim�nez G & Diego Prior J, 2022. "Análisis de eficiencia en educación: una aplicación del método StoNED," Revista Desarrollo y Sociedad, Universidad de los Andes,Facultad de Economía, CEDE, vol. 92(2), pages 45-91.
  16. repec:bcp:journl:v:7:y:2023:i:3:p:505-515 is not listed on IDEAS
  17. 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.
  18. Tsionas, Mike G., 2023. "Clustering and meta-envelopment in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 304(2), pages 763-778.
  19. Ya Chen & Mike Tsionas & Valentin Zelenyuk, 2020. "LASSO DEA for small and big data," CEPA Working Papers Series WP022020, School of Economics, University of Queensland, Australia.
  20. Esteve, Miriam & Aparicio, Juan & Rodriguez-Sala, Jesus J. & Zhu, Joe, 2023. "Random Forests and the measurement of super-efficiency in the context of Free Disposal Hull," European Journal of Operational Research, Elsevier, vol. 304(2), pages 729-744.
  21. 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.
  22. Nadia M. Guerrero & Juan Aparicio & Daniel Valero-Carreras, 2022. "Combining Data Envelopment Analysis and Machine Learning," Mathematics, MDPI, vol. 10(6), pages 1-22, March.
  23. España, Victor J. & Aparicio, Juan & Barber, Xavier & Esteve, Miriam, 2024. "Estimating production functions through additive models based on regression splines," European Journal of Operational Research, Elsevier, vol. 312(2), pages 684-699.
  24. Zhang, Yue-Jun & Sun, Ya-Fang & Huang, Junling, 2018. "Energy efficiency, carbon emission performance, and technology gaps: Evidence from CDM project investment," Energy Policy, Elsevier, vol. 115(C), pages 119-130.
  25. Alexandre Repkine, 2023. "The Estimation of a Polluting By-Production Technology Using Statistical Copulas," Journal of Productivity Analysis, Springer, vol. 60(1), pages 49-62, August.
  26. Sueyoshi, Toshiyuki & Li, Aijun & Liu, Xiaohong, 2019. "Exploring sources of China's CO2 emission: Decomposition analysis under different technology changes," European Journal of Operational Research, Elsevier, vol. 279(3), pages 984-995.
  27. Tsionas, Mike G., 2023. "Joint production in stochastic non-parametric envelopment of data with firm-specific directions," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1336-1347.
  28. Léopold Simar & Paul W. Wilson, 2023. "Nonparametric, Stochastic Frontier Models with Multiple Inputs and Outputs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(4), pages 1391-1403, October.
  29. Tsionas, Mike G., 2020. "On a model of environmental performance and technology gaps," European Journal of Operational Research, Elsevier, vol. 285(3), pages 1141-1152.
  30. De la Cruz, Marco & Mergoni, Anna, 2024. "Assessing the performance of Peruvian education system from a governance perspective," Socio-Economic Planning Sciences, Elsevier, vol. 93(C).
  31. Lee, Chia-Yen & Cai, Jia-Ying, 2020. "LASSO variable selection in data envelopment analysis with small datasets," Omega, Elsevier, vol. 91(C).
  32. Agrell, Per J. & Teusch, Jonas, 2020. "Predictability and strategic behavior under frontier regulation," Energy Policy, Elsevier, vol. 137(C).
  33. Layer, Kevin & Johnson, Andrew L. & Sickles, Robin C. & Ferrier, Gary D., 2020. "Direction selection in stochastic directional distance functions," European Journal of Operational Research, Elsevier, vol. 280(1), pages 351-364.
  34. Chen, Ya & Tsionas, Mike G. & Zelenyuk, Valentin, 2021. "LASSO+DEA for small and big wide data," Omega, Elsevier, vol. 102(C).
  35. Quinn, Barry & Gallagher, Ronan & Kuosmanen, Timo, 2021. "Lurking in the Shadows: The Impact of Emissions Target Setting on Carbon Pricing and Environmental Efficiency," QBS Working Paper Series 2021/05, Queen's University Belfast, Queen's Business School.
  36. Kuosmanen, Timo & Zhou, Xun, 2021. "Shadow prices and marginal abatement costs: Convex quantile regression approach," European Journal of Operational Research, Elsevier, vol. 289(2), pages 666-675.
  37. Kuosmanen, Timo & Zhou, Xun & Dai, Sheng, 2020. "How much climate policy has cost for OECD countries?," World Development, Elsevier, vol. 125(C).
  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. Kounetas, Konstantinos E. & Polemis, Michael L. & Tzeremes, Nickolaos G., 2021. "Measurement of eco-efficiency and convergence: Evidence from a non-parametric frontier analysis," European Journal of Operational Research, Elsevier, vol. 291(1), pages 365-378.
  40. Kalundu Kimanzi & Prof. Mirie Mwangi & Dr. Duncan Elly Ochieng & Prof. Josephat Lishenga, 2020. "Moderating Effect of Board Gender Diversity on the Relationship between Financial Structure and Operating Efficiency," Journal of Finance and Investment Analysis, SCIENPRESS Ltd, vol. 9(1), pages 1-1.
  41. Rødseth, Kenneth Løvold & Kuosmanen, Timo & Holmen, Rasmus Bøgh, 2025. "Mitigating simultaneity bias in seaport efficiency measurement," Transportation Research Part A: Policy and Practice, Elsevier, vol. 192(C).
  42. Ali Emrouznejad & Victor Podinovski & Vincent Charles & Chixiao Lu & Amir Moradi-Motlagh, 2025. "Rajiv Banker’s lasting impact on data envelopment analysis," Annals of Operations Research, Springer, vol. 351(2), pages 1225-1264, August.
  43. Timo Kuosmanen & Andrew L. Johnson, 2020. "Conditional Yardstick Competition in Energy Regulation," The Energy Journal, , vol. 41(1_suppl), pages 67-92, June.
  44. Valero-Carreras, Daniel & Aparicio, Juan & Guerrero, Nadia M., 2021. "Support vector frontiers: A new approach for estimating production functions through support vector machines," Omega, Elsevier, vol. 104(C).
  45. Wen, Xiaojie & Yao, Shunbo & Sauer, Johannes, 2022. "Shadow prices and abatement cost of soil erosion in Shaanxi Province, China: Convex expectile regression approach," Ecological Economics, Elsevier, vol. 201(C).
  46. Cinzia Daraio & Léopold Simar, 2024. "Approximations and inference for envelopment estimators of production frontiers," Journal of Productivity Analysis, Springer, vol. 62(2), pages 197-215, October.
  47. Zhang, Tao & Li, Hong-Zhou & Xie, Bai-Chen, 2022. "Have renewables and market-oriented reforms constrained the technical efficiency improvement of China's electric grid utilities?," Energy Economics, Elsevier, vol. 114(C).
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