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Directional output distance functions: endogenous directions based on exogenous normalization constraints

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Cited by:

  1. Paulo Matos & Guilherme Padilha & Maurício Benegas, 2016. "On the management efficiency of Brazilian stock mutual funds," Operational Research, Springer, vol. 16(3), pages 365-399, October.
  2. 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.
  3. Krüger, Jens J., 2018. "Direct targeting of efficient DMUs for benchmarking," International Journal of Production Economics, Elsevier, vol. 199(C), pages 1-6.
  4. Jens J. Krüger & Moritz Tarach, 2022. "Greenhouse Gas Emission Reduction Potentials in Europe by Sector: A Bootstrap-Based Nonparametric Efficiency Analysis," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 81(4), pages 867-898, April.
  5. Pedro Macedo & Elvira Silva, 2017. "Sensitivity of directional technical inefficiency measures to the choice of the direction vector: a simulation study," Economics Bulletin, AccessEcon, vol. 37(1), pages 52-62.
  6. Wang, Yun & Sun, Xiaohua & Wang, Baocai & Liu, Xiaoling, 2020. "Energy saving, GHG abatement and industrial growth in OECD countries: A green productivity approach," Energy, Elsevier, vol. 194(C).
  7. Kapelko, Magdalena & Oude Lansink, Alfons & Zofío, José L., 2022. "Endogenous dynamic inefficiency and optimal resource allocation: An application to the European Dietetic Food Industry," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1444-1457.
  8. Atkinson, Scott E. & Tsionas, Mike G., 2016. "Directional distance functions: Optimal endogenous directions," Journal of Econometrics, Elsevier, vol. 190(2), pages 301-314.
  9. Ke Wang & Yujiao Xian & Chia-Yen Lee & Yi-Ming Wei & Zhimin Huang, 2019. "On selecting directions for directional distance functions in a non-parametric framework: a review," Annals of Operations Research, Springer, vol. 278(1), pages 43-76, July.
  10. Daraio, Cinzia & Simar, Léopold, 2014. "Directional distances and their robust versions: Computational and testing issues," European Journal of Operational Research, Elsevier, vol. 237(1), pages 358-369.
  11. Lee, Chia-Yen & Wang, Ke, 2019. "Nash marginal abatement cost estimation of air pollutant emissions using the stochastic semi-nonparametric frontier," European Journal of Operational Research, Elsevier, vol. 273(1), pages 390-400.
  12. Chia-Yen Lee, 2017. "Directional marginal productivity: a foundation of meta-data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(5), pages 544-555, May.
  13. Krüger, Jens J., 2021. "Nonparametric portfolio efficiency measurement with higher moments," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 130825, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
  14. Frederic Ang & Alfons Oude Lansink, 2018. "Decomposing dynamic profit inefficiency of Belgian dairy farms," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 45(1), pages 81-99.
  15. Pang, Rui-Zhi & Deng, Zhong-Qi & Hu, Jin-li, 2015. "Clean energy use and total-factor efficiencies: An international comparison," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1158-1171.
  16. Lee, Chia-Yen, 2016. "Nash-profit efficiency: A measure of changes in market structures," European Journal of Operational Research, Elsevier, vol. 255(2), pages 659-663.
  17. Malin Song & Jianlin Wang & Jiajia Zhao & Tomas Baležentis & Zhiyang Shen, 2020. "Production and safety efficiency evaluation in Chinese coal mines: accident deaths as undesirable output," Annals of Operations Research, Springer, vol. 291(1), pages 827-845, August.
  18. Scott E. Atkinson & Mike G. Tsionas, 2018. "Shadow directional distance functions with bads: GMM estimation of optimal directions and efficiencies," Empirical Economics, Springer, vol. 54(1), pages 207-230, February.
  19. Song, Malin & Wang, Jianlin & Zhao, Jiajia, 2023. "Effects of rising and extreme temperatures on production factor efficiency: Evidence from China's cities," International Journal of Production Economics, Elsevier, vol. 260(C).
  20. Aparicio, Juan & Pastor, Jesus T. & Zofio, Jose L., 2015. "How to properly decompose economic efficiency using technical and allocative criteria with non-homothetic DEA technologies," European Journal of Operational Research, Elsevier, vol. 240(3), pages 882-891.
  21. Vardanyan, Michael & Valdmanis, Vivian G. & Leleu, Hervé & Ferrier, Gary D., 2022. "Estimating technology characteristics of the U.S. hospital industry using directional distance functions with optimal directions," Omega, Elsevier, vol. 113(C).
  22. Ke Wang & Jieming Zhang & Yi-Ming Wei, 2017. "Operational and environmental performance in China¡¯s thermal power industry: Taking an effectiveness measure as complement to an efficiency measure," CEEP-BIT Working Papers 100, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
  23. Song, Malin & Zhu, Shuai & Wang, Jianlin & Zhao, Jiajia, 2020. "Share green growth: Regional evaluation of green output performance in China," International Journal of Production Economics, Elsevier, vol. 219(C), pages 152-163.
  24. Rolf Färe & Giannis Karagiannis, 2023. "Translation efficiency and directionally optimal scale," Journal of Economics, Springer, vol. 140(3), pages 259-273, December.
  25. Shuguang Lin & Paul Rouse & Ying-Ming Wang & Lin Lin & Zhen-Quan Zheng, 2023. "Performance measurement of nonhomogeneous Hong Kong hospitals using directional distance functions," Health Care Management Science, Springer, vol. 26(2), pages 330-343, June.
  26. Shulei Cheng & Wei Fan & Jianlin Wang, 2022. "Investigating the humanitarian labor efficiency of China: a factor-specific model," Annals of Operations Research, Springer, vol. 319(1), pages 439-461, December.
  27. Yongqiao Wang & He Ni & Stan Uryasev, 2023. "Buffered-ranking intervals for virtual profit efficiency analysis," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 31(4), pages 1149-1181, December.
  28. Lee, Chia-Yen, 2014. "Meta-data envelopment analysis: Finding a direction towards marginal profit maximization," European Journal of Operational Research, Elsevier, vol. 237(1), pages 207-216.
  29. Deng, Zhongqi & Jiang, Nan & Pang, Ruizhi, 2021. "Factor-analysis-based directional distance function: The case of New Zealand hospitals," Omega, Elsevier, vol. 98(C).
  30. Yujiao Xian & Ke Wang & Xunpeng Shi & Chi Zhang & Yi-Ming Wei & Zhimin Huang, 2018. "Carbon emissions intensity reduction target for China¡¯s power industry: An efficiency and productivity perspective," CEEP-BIT Working Papers 117, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
  31. Christian Stetter & Philipp Mennig & Johannes Sauer, 2022. "Using Machine Learning to Identify Heterogeneous Impacts of Agri-Environment Schemes in the EU: A Case Study," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 49(4), pages 723-759.
  32. Cinzia Daraio & Léopold Simar, 2016. "Efficiency and benchmarking with directional distances: a data-driven approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(7), pages 928-944, July.
  33. Minh‐Anh Thi Nguyen & Ming‐Miin Yu, 2020. "Decomposing the operational efficiency of major cruise lines: A network data envelopment analysis approach in the presence of shared input and quasi‐fixed input," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(8), pages 1501-1516, December.
  34. Fangqing Wei & Junfei Chu & Jiayun Song & Feng Yang, 2019. "A cross-bargaining game approach for direction selection in the directional distance function," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(3), pages 787-807, September.
  35. Färe, Rolf & Pasurka, Carl & Vardanyan, Michael, 2017. "On endogenizing direction vectors in parametric directional distance function-based models," European Journal of Operational Research, Elsevier, vol. 262(1), pages 361-369.
  36. Shawna Grosskopf & Kathy Hayes & Lori L. Taylor, 2014. "Applied efficiency analysis in education," Economics and Business Letters, Oviedo University Press, vol. 3(1), pages 19-26.
  37. Rolf Färe & Xinju He & Sungko Li & Valentin Zelenyuk, 2019. "A Unifying Framework for Farrell Profit Efficiency Measurement," Operations Research, INFORMS, vol. 67(1), pages 183-197, January.
  38. Lozano, Sebastián & Khezri, Somayeh, 2021. "Network DEA smallest improvement approach," Omega, Elsevier, vol. 98(C).
  39. Wang, Yun & Sun, Xiaohua & Guo, Xu, 2019. "Environmental regulation and green productivity growth: Empirical evidence on the Porter Hypothesis from OECD industrial sectors," Energy Policy, Elsevier, vol. 132(C), pages 611-619.
  40. Adler, Nicole & Volta, Nicola, 2016. "Accounting for externalities and disposability: A directional economic environmental distance function," European Journal of Operational Research, Elsevier, vol. 250(1), pages 314-327.
  41. Engida, Tadesse Getacher & Rao, Xudong & Oude Lansink, Alfons G.J.M., 2020. "A dynamic by-production framework for analyzing inefficiency associated with corporate social responsibility," European Journal of Operational Research, Elsevier, vol. 287(3), pages 1170-1179.
  42. Sebastián Lozano & Narges Soltani, 2018. "DEA target setting using lexicographic and endogenous directional distance function approaches," Journal of Productivity Analysis, Springer, vol. 50(1), pages 55-70, October.
  43. Chen, Lei & Wang, Ying-Ming, 2023. "Game directional distance function in meta-frontier data envelopment analysis," Omega, Elsevier, vol. 121(C).
  44. Ke Wang & Yujiao Xian & Yi-Ming Wei & Zhimin Huang, 2016. "Sources of carbon productivity change: A decomposition and disaggregation analysis based on global Luenberger productivity indicator and endogenous directional distance function," CEEP-BIT Working Papers 91, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
  45. 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.
  46. 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.
  47. Jens J. Krüger, 2017. "Revisiting the world technology frontier: a directional distance function approach," Journal of Economic Growth, Springer, vol. 22(1), pages 67-95, March.
  48. Färe, Rolf & Grosskopf, Shawna & Karagiannis, Giannis, 2018. "On technical inefficiency indicators at the industry level," International Journal of Production Economics, Elsevier, vol. 196(C), pages 333-334.
  49. Krüger, Jens J., 2024. "Nonparametric portfolio efficiency measurement with higher moments," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 144371, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
  50. Atkinson, Scott E. & Primont, Daniel & Tsionas, Mike G., 2018. "Statistical inference in efficient production with bad inputs and outputs using latent prices and optimal directions," Journal of Econometrics, Elsevier, vol. 204(2), pages 131-146.
  51. Alexandre Repkine & Dongki Min, 2018. "An iterative approach to the estimation of the abatement costs of harmful emissions," Journal of Productivity Analysis, Springer, vol. 49(2), pages 123-136, June.
  52. Deng, Zhongqi & Song, Shunfeng & Jiang, Nan & Pang, Ruizhi, 2023. "Sustainable development in China? A nonparametric decomposition of economic growth," China Economic Review, Elsevier, vol. 81(C).
  53. Sebastián Lozano & Narges Soltani & Akram Dehnokhalaji, 2020. "A compromise programming approach for target setting in DEA," Annals of Operations Research, Springer, vol. 288(1), pages 363-390, May.
  54. Kumbhakar, Subal C. & Tsionas, Mike G., 2021. "Dissections of input and output efficiency: A generalized stochastic frontier model," International Journal of Production Economics, Elsevier, vol. 232(C).
  55. Justas Streimikis & Z. Y. Shen & Tomas Balezentis, 2024. "Does the energy-related greenhouse gas emission abatement cost depend on the optimization direction: shadow pricing based on the weak disposability technology in the European Union agriculture," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 32(3), pages 593-619, September.
  56. Chiang Kao & Shiuh-Nan Hwang, 2019. "Efficiency evaluation in the presence of undesirable outputs: the most favorable shadow price approach," Annals of Operations Research, Springer, vol. 278(1), pages 5-16, July.
  57. Badau, Flavius & Färe, Rolf & Gopinath, Munisamy, 2016. "Global resilience to climate change: Examining global economic and environmental performance resulting from a global carbon dioxide market," Resource and Energy Economics, Elsevier, vol. 45(C), pages 46-64.
  58. Emir Malikov & Subal C. Kumbhakar & Mike G. Tsionas, 2016. "A Cost System Approach to the Stochastic Directional Technology Distance Function with Undesirable Outputs: The Case of us Banks in 2001–2010," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1407-1429, November.
  59. Zhang, Zibin & Ye, Jianliang, 2015. "Decomposition of environmental total factor productivity growth using hyperbolic distance functions: A panel data analysis for China," Energy Economics, Elsevier, vol. 47(C), pages 87-97.
  60. Chen, Zhenling & Zhang, Xiaoling & Ni, Guohua, 2020. "Decomposing capacity utilization under carbon dioxide emissions reduction constraints in data envelopment analysis: An application to Chinese regions," Energy Policy, Elsevier, vol. 139(C).
  61. Lee, Chia-Yen & Zhou, Peng, 2015. "Directional shadow price estimation of CO2, SO2 and NOx in the United States coal power industry 1990–2010," Energy Economics, Elsevier, vol. 51(C), pages 493-502.
  62. Tao, Xiangyang & An, Qingxian & Goh, Mark, 2024. "Plant capacity utilization with piecewise Cobb-Douglas technology: Definition and interpretation," European Journal of Operational Research, Elsevier, vol. 316(3), pages 1034-1043.
  63. Lee, Chia-Yen & Charles, Vincent, 2022. "A robust capacity expansion integrating the perspectives of marginal productivity and capacity regret," European Journal of Operational Research, Elsevier, vol. 296(2), pages 557-569.
  64. Tsionas, Mike G., 2024. "A generalized inefficiency model with input and output dependence," European Journal of Operational Research, Elsevier, vol. 312(1), pages 315-323.
  65. Jorge Bonilla & Jessica Coria & Thomas Sterner, 2018. "Technical Synergies and Trade-Offs Between Abatement of Global and Local Air Pollution," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 70(1), pages 191-221, May.
  66. Ma, Chunbo & Hailu, Atakelty & You, Chaoying, 2019. "A critical review of distance function based economic research on China’s marginal abatement cost of carbon dioxide emissions," Energy Economics, Elsevier, vol. 84(C).
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