IDEAS home Printed from https://ideas.repec.org/r/kap/jproda/v38y2012i1p11-28.html
   My bibliography  Save this item

Stochastic non-smooth envelopment of data: semi-parametric frontier estimation subject to shape constraints

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Keshvari, Abolfazl & Kuosmanen, Timo, 2013. "Stochastic non-convex envelopment of data: Applying isotonic regression to frontier estimation," European Journal of Operational Research, Elsevier, vol. 231(2), pages 481-491.
  2. Jean-Pierre Florens & Léopold Simar & Ingrid Van Keilegom, 2020. "Estimation of the Boundary of a Variable Observed With Symmetric Error," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(529), pages 425-441, January.
  3. Timo Kuosmanen & Mogens Fosgerau, 2009. "Neoclassical versus Frontier Production Models? Testing for the Skewness of Regression Residuals," Scandinavian Journal of Economics, Wiley Blackwell, vol. 111(2), pages 351-367, June.
  4. Jose Manuel Cordero & Cristina Polo & Javier Salinas-Jiménez, 2021. "Subjective Well-Being and Heterogeneous Contexts: A Cross-National Study Using Semi-Nonparametric Frontier Methods," Journal of Happiness Studies, Springer, vol. 22(2), pages 867-886, February.
  5. Chiang Kao & Shiang-Tai Liu, 2022. "Stochastic efficiencies of network production systems with correlated stochastic data: the case of Taiwanese commercial banks," Annals of Operations Research, Springer, vol. 315(2), pages 1151-1174, August.
  6. Mark Andor & Frederik Hesse, 2014. "The StoNED age: the departure into a new era of efficiency analysis? A monte carlo comparison of StoNED and the “oldies” (SFA and DEA)," Journal of Productivity Analysis, Springer, vol. 41(1), pages 85-109, February.
  7. Mark Andor & Frederik Hesse, "undated". "The StoNED age: The Departure Into a New Era of Efficiency Analysis? An MC study Comparing StoNED and the "Oldies" (SFA and DEA)," Working Papers 201285, Institute of Spatial and Housing Economics, Munster Universitary.
  8. Mark Andor & Frederik Hesse, "undated". "A Monte Carlo Simulation comparing DEA, SFA and two simple approaches to combine efficiency estimates," Working Papers 201177, Institute of Spatial and Housing Economics, Munster Universitary.
  9. Elvira Silva & Pedro Macedo & Isabel Soares, 2019. "Maximum entropy: a stochastic frontier approach for electricity distribution regulation," Journal of Regulatory Economics, Springer, vol. 55(3), pages 237-257, June.
  10. Subal C. Kumbhakar & Christopher F. Parmeter & Valentin Zelenyuk, 2022. "Stochastic Frontier Analysis: Foundations and Advances I," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 8, pages 331-370, Springer.
  11. Cheng, Xiaomei & Andersson, Jonas & Bjørndal, Endre, 2015. "On the Distributional Assumptions in the StoNED model," Discussion Papers 2015/24, Norwegian School of Economics, Department of Business and Management Science.
  12. Tai-Hsin Huang & Yi-Huang Chiu & Chih-Ying Mao, 2021. "Imposing Regularity Conditions to Measure Banks’ Productivity Changes in Taiwan Using a Stochastic Approach," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(2), pages 273-303, June.
  13. Michaelides, Panayotis G. & Tsionas, Efthymios G. & Vouldis, Angelos T. & Konstantakis, Konstantinos N., 2015. "Global approximation to arbitrary cost functions: A Bayesian approach with application to US banking," European Journal of Operational Research, Elsevier, vol. 241(1), pages 148-160.
  14. 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.
  15. 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.
  16. Xian, Yujiao & Yu, Dan & Wang, Ke & Yu, Jian & Huang, Zhimin, 2022. "Capturing the least costly measure of CO2 emission abatement: Evidence from the iron and steel industry in China," Energy Economics, Elsevier, vol. 106(C).
  17. Fabio Pammolli & Francesco Porcelli & Francesco Vidoli & Guido Borà, 2014. "La spesa sanitaria delle Regioni in Italia - Saniregio 3," Working Papers CERM 02-2014, Competitività, Regole, Mercati (CERM).
  18. E Thanassoulis & M Kortelainen & G Johnes & J Johnes, 2011. "Costs and efficiency of higher education institutions in England: a DEA analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(7), pages 1282-1297, July.
  19. 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.
  20. Fabio Pammolli & Francesco Porcelli & Francesco Vidoli & Monica Auteri & Guido Borà, 2017. "La spesa sanitaria delle Regioni in Italia - Saniregio2017," Working Papers CERM 01-2017, Competitività, Regole, Mercati (CERM).
  21. Młynarski, Wojciech & Prędki, Artur & Kaliszewski, Adam, 2021. "Efficiency and factors influencing it in forest districts in southern Poland: Application of Data Envelopment Analysis," Forest Policy and Economics, Elsevier, vol. 130(C).
  22. Timo Kuosmanen & Sheng Dai, 2023. "Modeling economies of scope in joint production: Convex regression of input distance function," Papers 2311.11637, arXiv.org.
  23. 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.
  24. 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.
  25. Ahn, Heinz & Clermont, Marcel & Langner, Julia, 2023. "Comparative performance analysis of frontier-based efficiency measurement methods – A Monte Carlo simulation," European Journal of Operational Research, Elsevier, vol. 307(1), pages 294-312.
  26. Dai, Xiaofeng, 2016. "Non-parametric efficiency estimation using Richardson–Lucy blind deconvolution," European Journal of Operational Research, Elsevier, vol. 248(2), pages 731-739.
  27. 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.
  28. 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.
  29. Kuosmanen, Timo & Nguyen, Tuan, 2020. "Capital bias in the Nordic revenue cap regulation: Averch-Johnson critique revisited," Energy Policy, Elsevier, vol. 139(C).
  30. Tsionas, Mike G., 2020. "Quantile Stochastic Frontiers," European Journal of Operational Research, Elsevier, vol. 282(3), pages 1177-1184.
  31. Zhou, Xun & Kuosmanen, Timo, 2020. "What drives decarbonization of new passenger cars?," European Journal of Operational Research, Elsevier, vol. 284(3), pages 1043-1057.
  32. Adwoa Asantewaa & Tooraj Jamasb & Manuel Llorca, 2022. "Electricity Sector Reform Performance in Sub-Saharan Africa: A Parametric Distance Function Approach," Energies, MDPI, vol. 15(6), pages 1-29, March.
  33. Vijesh Krishna & Prakashan Veettil, 2015. "Productivity and Efficiency Impacts of Zero Tillage Wheat in Northwest Indo-Gangetic Plains," Working Papers id:7716, eSocialSciences.
  34. Hazarika, Gautam & Khraiche, Maroula & Kutlu, Levent, 2023. "Gender Equity in Labor Market Opportunities and Aggregate Technical Efficiency: A Case of Equity Promoting Efficiency," IZA Discussion Papers 16096, Institute of Labor Economics (IZA).
  35. Parmeter, Christopher F., 2021. "Is it MOLS or COLS?," Efficiency Series Papers 2021/04, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
  36. Gil, Guilherme Dôco Roberti & Costa, Marcelo Azevedo & Lopes, Ana Lúcia Miranda & Mayrink, Vinícius Diniz, 2017. "Spatial statistical methods applied to the 2015 Brazilian energy distribution benchmarking model: Accounting for unobserved determinants of inefficiencies," Energy Economics, Elsevier, vol. 64(C), pages 373-383.
  37. Li, Hong-Zhou & Kopsakangas-Savolainen, Maria & Xiao, Xing-Zhi & Tian, Zhen-Zhen & Yang, Xiao-Yuan & Wang, Jian-Lin, 2016. "Cost efficiency of electric grid utilities in China: A comparison of estimates from SFA–MLE, SFA–Bayes and StoNED–CNLS," Energy Economics, Elsevier, vol. 55(C), pages 272-283.
  38. Cheng, Xiaomei & Bjørndal, Endre & Bjørndal, Mette, 2015. "Optimal Scale in Different Environments – The Case of Norwegian Electricity Distribution Companies," Discussion Papers 2015/22, Norwegian School of Economics, Department of Business and Management Science.
  39. Mattsson, Pontus & Tidanå, Claes, 2019. "Potential efficiency effects of merging the Swedish district courts," Socio-Economic Planning Sciences, Elsevier, vol. 67(C), pages 58-68.
  40. Fabio Pammolli & Francesco Porcelli & Francesco Vidoli & Guido Borà, 2015. "La spesa sanitaria delle Regioni in Italia - Saniregio 2015," Working Papers CERM 01-2015, Competitività, Regole, Mercati (CERM), revised 04 Jan 2016.
  41. 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.
  42. 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.
  43. Picazo-Tadeo, Andrés J. & Beltrán-Esteve, Mercedes & Gómez-Limón, José A., 2012. "Assessing eco-efficiency with directional distance functions," European Journal of Operational Research, Elsevier, vol. 220(3), pages 798-809.
  44. Kortelainen, Mika, 2008. "Estimation of semiparametric stochastic frontiers under shape constraints with application to pollution generating technologies," MPRA Paper 9257, University Library of Munich, Germany.
  45. Marijn Verschelde & Michel Dumont & Glenn Rayp & Bruno Merlevede, 2016. "Semiparametric stochastic metafrontier efficiency of European manufacturing firms," Journal of Productivity Analysis, Springer, vol. 45(1), pages 53-69, February.
  46. Wei, Xiao & Zhang, Ning, 2020. "The shadow prices of CO2 and SO2 for Chinese Coal-fired Power Plants: A partial frontier approach," Energy Economics, Elsevier, vol. 85(C).
  47. Wang, Yongqiao & Wang, Shouyang & Dang, Chuangyin & Ge, Wenxiu, 2014. "Nonparametric quantile frontier estimation under shape restriction," European Journal of Operational Research, Elsevier, vol. 232(3), pages 671-678.
  48. Boussemart, Jean-Philippe & Leleu, Hervé & Ojo, Oluwaseun, 2011. "Could society's willingness to reduce pesticide use be aligned with farmers' economic self-interest?," Ecological Economics, Elsevier, vol. 70(10), pages 1797-1804, August.
  49. Saeideh Fallah-Fini & Konstantinos Triantis & Andrew Johnson, 2014. "Reviewing the literature on non-parametric dynamic efficiency measurement: state-of-the-art," Journal of Productivity Analysis, Springer, vol. 41(1), pages 51-67, February.
  50. 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.
  51. Waidelich, Paul & Haug, Tomas & Wieshammer, Lorenz, 2022. "German efficiency gone wrong: Unintended incentives arising from the gas TSOs’ benchmarking," Energy Policy, Elsevier, vol. 160(C).
  52. Jakub Growiec & Anna Pajor & Dorota Gorniak & Artur Predki, 2015. "The shape of aggregate production functions: evidence from estimates of the World Technology Frontier," Bank i Kredyt, Narodowy Bank Polski, vol. 46(4), pages 299-326.
  53. Centorrino, Samuele & Parmeter, Christopher F., 2024. "Nonparametric estimation of stochastic frontier models with weak separability," Journal of Econometrics, Elsevier, vol. 238(2).
  54. Mekaroonreung, Maethee & Johnson, Andrew L., 2014. "A nonparametric method to estimate a technical change effect on marginal abatement costs of U.S. coal power plants," Energy Economics, Elsevier, vol. 46(C), pages 45-55.
  55. Bjørndal, Endre & Bjørndal, Mette & Cullmann, Astrid & Nieswand, Maria, 2018. "Finding the right yardstick: Regulation of electricity networks under heterogeneous environments," European Journal of Operational Research, Elsevier, vol. 265(2), pages 710-722.
  56. Delnava, Haleh & Khosravi, Ali & El Haj Assad, Mamdouh, 2023. "Metafrontier frameworks for estimating solar power efficiency in the United States using stochastic nonparametric envelopment of data (StoNED)," Renewable Energy, Elsevier, vol. 213(C), pages 195-204.
  57. Qiao Guangshun, 2023. "Survival of the Fittest: The Long-run Productivity Analysis of the Listed Information Technology Companies in the US Stock Market," Economics - The Open-Access, Open-Assessment Journal, De Gruyter, vol. 17(1), pages 1-11, January.
  58. Christopher F. Parmeter & Valentin Zelenyuk, 2019. "Combining the Virtues of Stochastic Frontier and Data Envelopment Analysis," Operations Research, INFORMS, vol. 67(6), pages 1628-1658, November.
  59. Liesiö, Juuso & Andelmin, Juho & Salo, Ahti, 2020. "Efficient allocation of resources to a portfolio of decision making units," European Journal of Operational Research, Elsevier, vol. 286(2), pages 619-636.
  60. 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.
  61. Shen, Xiaobo & Lin, Boqiang, 2017. "The shadow prices and demand elasticities of agricultural water in China: A StoNED-based analysis," Resources, Conservation & Recycling, Elsevier, vol. 127(C), pages 21-28.
  62. 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).
  63. Stefan Seifert, 2016. "Semi-Parametric Measures of Scale Characteristics of German Natural Gas-Fired Electricity Generation," Discussion Papers of DIW Berlin 1571, DIW Berlin, German Institute for Economic Research.
  64. Jradi, Samah & Ruggiero, John, 2019. "Stochastic data envelopment analysis: A quantile regression approach to estimate the production frontier," European Journal of Operational Research, Elsevier, vol. 278(2), pages 385-393.
  65. Alexander Arévalo S & Víctor Giménez 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, October.
  66. 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.
  67. Rødseth, Kenneth Løvold & Wangsness, Paal Brevik & Alexander Gregersen, Fredrik, 2024. "Panel data analysis of drivers under an evolving cordon tolling system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
  68. 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.
  69. 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.
  70. Olesen, O.B. & Ruggiero, J., 2018. "An improved Afriat–Diewert–Parkan nonparametric production function estimator," European Journal of Operational Research, Elsevier, vol. 264(3), pages 1172-1188.
  71. Quaranta, Anna Grazia & Raffoni, Anna & Visani, Franco, 2018. "A multidimensional approach to measuring bank branch efficiency," European Journal of Operational Research, Elsevier, vol. 266(2), pages 746-760.
  72. 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.
  73. Seifert, Stefan, 2015. "Productivity Growth and its Sources - A StoNED Metafrontier Analyis of the German Electricity Generating Sector," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112975, Verein für Socialpolitik / German Economic Association.
  74. Levent Kutlu & Shasha Liu & Robin C. Sickles, 2022. "Cost, Revenue, and Profit Function Estimates," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 16, pages 641-679, Springer.
  75. Olga Kutnohorská & Dana Strachotová & Marek Botek & Stanislava Grosová, 0000. "The Influence Of The Field Of Business On The Development Of Productivity In Selected Companies Of The Czech Chemical Industry," Proceedings of Economics and Finance Conferences 14716504, International Institute of Social and Economic Sciences.
  76. 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.
  77. Rødseth, Kenneth Løvold, 2023. "Shadow pricing of electricity generation using stochastic and deterministic materials balance models," Applied Energy, Elsevier, vol. 341(C).
  78. Agrell, Per J. & Niknazar, Pooria, 2014. "Structural and behavioral robustness in applied best-practice regulation," Socio-Economic Planning Sciences, Elsevier, vol. 48(1), pages 89-103.
  79. Chung, William & Yeung, Iris M.H., 2017. "Benchmarking by convex non-parametric least squares with application on the energy performance of office buildings," Applied Energy, Elsevier, vol. 203(C), pages 454-462.
  80. Tsionas, Mike, 2022. "Efficiency estimation using probabilistic regression trees with an application to Chilean manufacturing industries," International Journal of Production Economics, Elsevier, vol. 249(C).
  81. Min Zhou & Teng Wang & Liang Yan & Xiong-Biao Xie, 2018. "Has Economic Competition Improved China’s Provincial Energy Ecological Efficiency under Fiscal Decentralization?," Sustainability, MDPI, vol. 10(7), pages 1-20, July.
  82. Tsionas, Mike G., 2023. "Performance estimation when the distribution of inefficiency is unknown," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1212-1222.
  83. Lee, Chia-Yen & Johnson, Andrew L., 2014. "Proactive data envelopment analysis: Effective production and capacity expansion in stochastic environments," European Journal of Operational Research, Elsevier, vol. 232(3), pages 537-548.
  84. Zervopoulos, Panagiotis & Emrouznejad, Ali & Sklavos, Sokratis, 2019. "A Bayesian approach for correcting bias of data envelopment analysis estimators," MPRA Paper 91886, University Library of Munich, Germany.
  85. Dai, Sheng & Zhou, Xun & Kuosmanen, Timo, 2020. "Forward-looking assessment of the GHG abatement cost: Application to China," Energy Economics, Elsevier, vol. 88(C).
  86. Stefan Seifert, 2015. "Measuring Productivity When Technologies Are Heterogeneous: A Semi-Parametric Approach for Electricity Generation," Discussion Papers of DIW Berlin 1526, DIW Berlin, German Institute for Economic Research.
  87. 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.
  88. Tsionas, Mike G. & Izzeldin, Marwan, 2018. "Smooth approximations to monotone concave functions in production analysis: An alternative to nonparametric concave least squares," European Journal of Operational Research, Elsevier, vol. 271(3), pages 797-807.
  89. Léopold Simar & Paul W. Wilson, 2015. "Statistical Approaches for Non-parametric Frontier Models: A Guided Tour," International Statistical Review, International Statistical Institute, vol. 83(1), pages 77-110, April.
  90. Minegishi, Kota, 2013. "Explaining Production Heterogeneity By Contextual Environments: Two-Stage DEA Application to Technical Change Measurement," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150289, Agricultural and Applied Economics Association.
  91. Tsionas, Mike G., 2021. "Optimal combinations of stochastic frontier and data envelopment analysis models," European Journal of Operational Research, Elsevier, vol. 294(2), pages 790-800.
  92. George Halkos & Nickolaos Tzeremes, 2013. "National culture and eco-efficiency: an application of conditional partial nonparametric frontiers," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 15(4), pages 423-441, October.
  93. 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.
  94. 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).
  95. Lee, Chia-Yen & Cai, Jia-Ying, 2020. "LASSO variable selection in data envelopment analysis with small datasets," Omega, Elsevier, vol. 91(C).
  96. Qi Yang & Zhonggen Sun & Hubiao Zhang, 2022. "Assessment of Urban Green Development Efficiency Based on Three-Stage DEA: A Case Study from China’s Yangtze River Delta," Sustainability, MDPI, vol. 14(19), pages 1-20, September.
  97. Asha Gunawardena, 2016. "Cost of Controlling Water Pollution and its Impact on Industrial Efficiency," Working Papers id:11537, eSocialSciences.
  98. Cheng, Xiaomei & Bjørndal, Endre & Bjørndal, Mette, 2014. "Cost Efficiency Analysis based on The DEA and StoNED Models: Case of Norwegian Electricity Distribution Companies," Discussion Papers 2014/28, Norwegian School of Economics, Department of Business and Management Science.
  99. Chen, Ya & Tsionas, Mike G. & Zelenyuk, Valentin, 2021. "LASSO+DEA for small and big wide data," Omega, Elsevier, vol. 102(C).
  100. Kuosmanen, Natalia & Kuosmanen, Timo & Maczulskij, Terhi & Zhou, Xun, 2024. "Least-cost Decarbonization Pathways for Electricity Generation in Finland: A Convex Quantile Regression Approach," ETLA Working Papers 114, The Research Institute of the Finnish Economy.
  101. 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.
  102. 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.
  103. Kuosmanen, Timo & Kuosmanen, Natalia, 2009. "How not to measure sustainable value (and how one might)," Ecological Economics, Elsevier, vol. 69(2), pages 235-243, December.
  104. Kenneth Rødseth & Eirik Romstad, 2014. "Environmental Regulations, Producer Responses, and Secondary Benefits: Carbon Dioxide Reductions Under the Acid Rain Program," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 59(1), pages 111-135, September.
  105. Preciado Arreola, José Luis & Johnson, Andrew L. & Chen, Xun C. & Morita, Hiroshi, 2020. "Estimating stochastic production frontiers: A one-stage multivariate semiparametric Bayesian concave regression method," European Journal of Operational Research, Elsevier, vol. 287(2), pages 699-711.
  106. Francesco Vidoli & Giancarlo Ferrara, 2015. "Analyzing Italian citrus sector by semi-nonparametric frontier efficiency models," Empirical Economics, Springer, vol. 49(2), pages 641-658, September.
  107. Kuosmanen, Timo & Zhou, Xun & Dai, Sheng, 2020. "How much climate policy has cost for OECD countries?," World Development, Elsevier, vol. 125(C).
  108. Stefan Seifert, 2014. "Effizienzanalysemethoden in der Regulierung deutscher Elektrizitäts- und Gasversorgungsunternehmen," DIW Roundup: Politik im Fokus 40, DIW Berlin, German Institute for Economic Research.
  109. 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.
  110. Shirong Zhao & Guangshun Qiao, 2022. "The shadow prices of CO2, SO2 and NOx for U.S. coal power industry 2010–2017: a convex quantile regression method," Journal of Productivity Analysis, Springer, vol. 57(3), pages 243-253, June.
  111. Garshasbi, Alireza & Khosropour, Hossein & Rahimian, Narges & Behrooz, Aref & Sedighi, Somaye, 2014. "Determining the Role of Inefficiency on Elasticity of Output Supply and Input Demand: A Case Study of Irrigated Wheat in 27 provinces of Iran," Asian Journal of Agriculture and Rural Development, Asian Economic and Social Society (AESS), vol. 4(01), pages 1-14, January.
  112. Lin, Rung-Chuan & Sir, Mustafa Y. & Pasupathy, Kalyan S., 2013. "Multi-objective simulation optimization using data envelopment analysis and genetic algorithm: Specific application to determining optimal resource levels in surgical services," Omega, Elsevier, vol. 41(5), pages 881-892.
  113. Eskelinen, Juha & Kuosmanen, Timo, 2013. "Intertemporal efficiency analysis of sales teams of a bank: Stochastic semi-nonparametric approach," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5163-5175.
  114. Tsionas, Mike G., 2022. "Convex non-parametric least squares, causal structures and productivity," European Journal of Operational Research, Elsevier, vol. 303(1), pages 370-387.
  115. Badunenko, Oleg & Cordero, Jose M. & Kumbhakar, Subal C., 2021. "Are you slacking? Where do you and your country stand in the happiness pursuit?," MPRA Paper 108316, University Library of Munich, Germany.
  116. Anaya, Karim L. & Pollitt, Michael G., 2017. "Using stochastic frontier analysis to measure the impact of weather on the efficiency of electricity distribution businesses in developing economies," European Journal of Operational Research, Elsevier, vol. 263(3), pages 1078-1094.
  117. Zhiqiang Liao, 2024. "Variable selection in convex nonparametric least squares via structured Lasso: An application to the Swedish electricity distribution networks," Papers 2409.01911, arXiv.org, revised Nov 2024.
  118. Hideyuki Mizobuchi, 2017. "Incorporating Sustainability Concerns in the Better Life Index: Application of Corrected Convex Non-parametric Least Squares Method," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 131(3), pages 947-971, April.
  119. Zhou, P. & Zhou, X. & Fan, L.W., 2014. "On estimating shadow prices of undesirable outputs with efficiency models: A literature review," Applied Energy, Elsevier, vol. 130(C), pages 799-806.
  120. Christopher F. Parmeter & Valentin Zelenyuk, 2016. "A Bridge Too Far? The State of the Art in Combining the Virtues of Stochastic Frontier Analysis and Data Envelopement Analysis," Working Papers 2016-10, University of Miami, Department of Economics.
  121. Krishna, Vijesh V. & Veettil, Prakashan C., 2014. "Productivity and efficiency impacts of conservation tillage in northwest Indo-Gangetic Plains," Agricultural Systems, Elsevier, vol. 127(C), pages 126-138.
  122. Mekaroonreung, Maethee & Johnson, Andrew L., 2012. "Estimating the shadow prices of SO2 and NOx for U.S. coal power plants: A convex nonparametric least squares approach," Energy Economics, Elsevier, vol. 34(3), pages 723-732.
  123. Yongrok Choi & Yanni Yu & Hyoung Seok Lee, 2018. "A Study on the Sustainable Performance of the Steel Industry in Korea Based on SBM-DEA," Sustainability, MDPI, vol. 10(1), pages 1-15, January.
  124. Atta Mills, Ebenezer Fiifi Emire & Zeng, Kailin & Fangbiao, Liu & Fangyan, Li, 2021. "Modeling innovation efficiency, its micro-level drivers, and its impact on stock returns," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
  125. Li, Hongkuan & He, Haiyan & Shan, Jiefei & Cai, Jingjing, 2019. "Innovation efficiency of semiconductor industry in China: A new framework based on generalized three-stage DEA analysis," Socio-Economic Planning Sciences, Elsevier, vol. 66(C), pages 136-148.
  126. Kuosmanen, Timo & Saastamoinen, Antti & Sipiläinen, Timo, 2013. "What is the best practice for benchmark regulation of electricity distribution? Comparison of DEA, SFA and StoNED methods," Energy Policy, Elsevier, vol. 61(C), pages 740-750.
  127. 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.
  128. 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.
  129. Heinz Ahn & Marcel Clermont & Julia Langner, 2022. "The impact of selected input and output factors on measuring research efficiency of university research fields: insights from a purpose-, field-, and method-specific perspective," Journal of Business Economics, Springer, vol. 92(8), pages 1303-1335, October.
  130. Alfons Oude Lansink & Spiro Stefanou & Magdalena Kapelko, 2015. "The impact of inefficiency on diversification," Journal of Productivity Analysis, Springer, vol. 44(2), pages 189-198, October.
  131. Kamil Makieła, 2014. "Bayesian Stochastic Frontier Analysis of Economic Growth and Productivity Change in the EU, USA, Japan and Switzerland," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 6(3), pages 193-216, September.
  132. 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).
  133. AGRELL, Per J. & NIKNAZAR, Pooria, 2014. "Structural and behavioral robustness in applied best practice regulation," LIDAM Reprints CORE 2557, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  134. Yantuan Yu & Jianhuan Huang & Yanmin Shao, 2019. "The Sustainability Performance of Chinese Banks: A New Network Data Envelopment Analysis Approach and Panel Regression," Sustainability, MDPI, vol. 11(6), pages 1-25, March.
  135. 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.
  136. Lee, Chia-Yen & Johnson, Andrew L. & Moreno-Centeno, Erick & Kuosmanen, Timo, 2013. "A more efficient algorithm for Convex Nonparametric Least Squares," European Journal of Operational Research, Elsevier, vol. 227(2), pages 391-400.
  137. 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.
  138. Andrew Johnson & Timo Kuosmanen, 2011. "One-stage estimation of the effects of operational conditions and practices on productive performance: asymptotically normal and efficient, root-n consistent StoNEZD method," Journal of Productivity Analysis, Springer, vol. 36(2), pages 219-230, October.
  139. Rasmus Bøgh Holmen & Timo Kuosmanen & Jaan Masso & Per Botolf Maurseth & Kenneth Løvold Rødseth, 2024. "Optimal Intertemporal Broadband Investments To Promote Regional Economic Development," University of Tartu - Faculty of Economics and Business Administration Working Paper Series 149, Faculty of Economics and Business Administration, University of Tartu (Estonia).
  140. Timo Kuosmanen & Yong Tan & Sheng Dai, 2023. "Performance analysis of English hospitals during the first and second waves of the coronavirus pandemic," Health Care Management Science, Springer, vol. 26(3), pages 447-460, September.
  141. Keshvari, Abolfazl, 2017. "A penalized method for multivariate concave least squares with application to productivity analysis," European Journal of Operational Research, Elsevier, vol. 257(3), pages 1016-1029.
  142. 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).
  143. 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).
  144. Hampf, Benjamin & Rødseth, Kenneth Løvold, 2019. "Environmental efficiency measurement with heterogeneous input quality: A nonparametric analysis of U.S. power plants," Energy Economics, Elsevier, vol. 81(C), pages 610-625.
  145. Qingxian An & Xiangyang Tao & Bo Dai & Jinlin Li, 2020. "Modified Distance Friction Minimization Model with Undesirable Output: An Application to the Environmental Efficiency of China’s Regional Industry," Computational Economics, Springer;Society for Computational Economics, vol. 55(4), pages 1047-1071, April.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.