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Nonparametric quantile frontier estimation under shape restriction

Citations

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Cited by:

  1. Atwood, Joseph & Shaik, Saleem, 2020. "Theory and statistical properties of Quantile Data Envelopment Analysis," European Journal of Operational Research, Elsevier, vol. 286(2), pages 649-661.
  2. 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.
  3. Tsionas, Mike G., 2020. "Quantile Stochastic Frontiers," European Journal of Operational Research, Elsevier, vol. 282(3), pages 1177-1184.
  4. Zhou, Xun & Kuosmanen, Timo, 2020. "What drives decarbonization of new passenger cars?," European Journal of Operational Research, Elsevier, vol. 284(3), pages 1043-1057.
  5. K. Hervé Dakpo & Yann Desjeux & Laure Latruffe, 2023. "Cost of abating excess nitrogen on wheat plots in France: An assessment with multi‐technology modelling," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(3), pages 800-815, September.
  6. Tsionas, Mike G. & Assaf, A. George & Andrikopoulos, Athanasios, 2020. "Quantile stochastic frontier models with endogeneity," Economics Letters, Elsevier, vol. 188(C).
  7. Bei Gao & Zuoren Sun, 2023. "Marginal CO 2 and SO 2 Abatement Costs and Determinants of Coal-Fired Power Plants in China: Considering a Two-Stage Production System with Different Emission Reduction Approaches," Energies, MDPI, vol. 16(8), pages 1-26, April.
  8. 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.
  9. 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.
  10. 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.
  11. Dai, Sheng & Zhou, Xun & Kuosmanen, Timo, 2020. "Forward-looking assessment of the GHG abatement cost: Application to China," Energy Economics, Elsevier, vol. 88(C).
  12. Zangin Zeebari & Kristofer Månsson & Pär Sjölander & Magnus Söderberg, 2023. "Regularized conditional estimators of unit inefficiency in stochastic frontier analysis, with application to electricity distribution market," Journal of Productivity Analysis, Springer, vol. 59(1), pages 79-97, February.
  13. Dai, Sheng & Kuosmanen, Timo & Zhou, Xun, 2023. "Non-crossing convex quantile regression," Economics Letters, Elsevier, vol. 233(C).
  14. 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.
  15. 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.
  16. 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.
  17. Dai, Sheng, 2023. "Variable selection in convex quantile regression: L1-norm or L0-norm regularization?," European Journal of Operational Research, Elsevier, vol. 305(1), pages 338-355.
  18. Kuosmanen, Timo & Zhou, Xun & Dai, Sheng, 2020. "How much climate policy has cost for OECD countries?," World Development, Elsevier, vol. 125(C).
  19. Hung-pin Lai & Cliff J. Huang & Tsu-Tan Fu, 2020. "Estimation of the production profile and metafrontier technology gap: a quantile approach," Empirical Economics, Springer, vol. 58(6), pages 2709-2731, June.
  20. Dai, Sheng & Kuosmanen, Timo & Zhou, Xun, 2023. "Generalized quantile and expectile properties for shape constrained nonparametric estimation," European Journal of Operational Research, Elsevier, vol. 310(2), pages 914-927.
  21. E. Fusco & R. Benedetti & F. Vidoli, 2023. "Stochastic frontier estimation through parametric modelling of quantile regression coefficients," Empirical Economics, Springer, vol. 64(2), pages 869-896, February.
  22. Liao, Zhiqiang & Dai, Sheng & Kuosmanen, Timo, 2024. "Convex support vector regression," European Journal of Operational Research, Elsevier, vol. 313(3), pages 858-870.
  23. 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.
  24. 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.
  25. 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.
  26. 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).
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