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Estimating returns to scale using non-parametric deterministic technologies: A new method based on goodness-of-fit

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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. Kerstens, Kristiaan & Sadeghi, Jafar & Toloo, Mehdi & Van de Woestyne, Ignace, 2022. "Procedures for ranking technical and cost efficient units: With a focus on nonconvexity," European Journal of Operational Research, Elsevier, vol. 300(1), pages 269-281.
  3. Kristiaan Kerstens & Ignace Van de Woestyne, 2018. "Enumeration algorithms for FDH directional distance functions under different returns to scale assumptions," Annals of Operations Research, Springer, vol. 271(2), pages 1067-1078, December.
  4. Walter Briec & Kristiaan Kerstens, 2006. "Input, output and graph technical efficiency measures on non-convex FDH models with various scaling laws: An integrated approach based upon implicit enumeration algorithms," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 14(1), pages 135-166, June.
  5. Kristiaan Kerstens & Ignace Van de Woestyne, 2021. "Cost functions are nonconvex in the outputs when the technology is nonconvex: convexification is not harmless," Annals of Operations Research, Springer, vol. 305(1), pages 81-106, October.
  6. François Mairesse & Philippe Vanden Eeckaut, 2002. "Museum Assessment and FDH Technology: Towards a Global Approach," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 26(4), pages 261-286, November.
  7. KERSTENS , Kristiaan & VANDEN EECKAUT, Philippe, 1998. "Distinguishing technical and scale efficiency on non-convex and convex technologies: theoretical analysis and empirical illustrations," LIDAM Discussion Papers CORE 1998055, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  8. J. Vakili & R. Sadighi Dizaji, 2021. "The closest strong efficient targets in the FDH technology: an enumeration method," Journal of Productivity Analysis, Springer, vol. 55(2), pages 91-105, April.
  9. Walheer, Barnabé, 2018. "Aggregation of metafrontier technology gap ratios: the case of European sectors in 1995–2015," European Journal of Operational Research, Elsevier, vol. 269(3), pages 1013-1026.
  10. Subhash C. Ray, 2014. "Data Envelopment Analysis: An Overview," Working papers 2014-33, University of Connecticut, Department of Economics.
  11. Destefanis, Sergio, 2000. "Differenziali territoriali di produttività ed efficienza e sviluppo dualistico [Territorial differences in productivity and efficiency and Italian dualism]," MPRA Paper 62065, University Library of Munich, Germany.
  12. Peter Bogetoft & Joseph M. Tama & Jørgen Tind, 2000. "Convex Input and Output Projections of Nonconvex Production Possibility Sets," Management Science, INFORMS, vol. 46(6), pages 858-869, June.
  13. Sergio Destefanis, 2002. "The Verdoorn Law: Some Evidence from Non-Parametric Frontier Analysis," Palgrave Macmillan Books, in: John McCombie & Maurizio Pugno & Bruno Soro (ed.), Productivity Growth and Economic Performance, chapter 6, pages 136-164, Palgrave Macmillan.
  14. Titl, Vitezslav & De Witte, Kristof, 2022. "How politics influence public good provision," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
  15. Leleu, Herve, 2006. "A linear programming framework for free disposal hull technologies and cost functions: Primal and dual models," European Journal of Operational Research, Elsevier, vol. 168(2), pages 340-344, January.
  16. Ramón Mª-Dolores, 2004. "Public capital effects on spanish regions productivity: a non-parametric approach (1965-1998)," Hacienda Pública Española / Review of Public Economics, IEF, vol. 171(4), pages 57-74, december.
  17. H Leleu, 2009. "Mixing DEA and FDH models together," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(12), pages 1730-1737, December.
  18. S Blancard & J-P Boussemart & H Leleu, 2011. "Measuring potential gains from specialization under non-convex technologies," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(10), pages 1871-1880, October.
  19. Jean-Philippe Boussemart & Walter Briec & Raluca Parvulescu & Paola Ravelojaona, 2022. "$\Lambda$-Returns to Scale and Individual Minimum Extrapolation Principle," Papers 2212.04724, arXiv.org, revised Dec 2023.
  20. Michael Zschille, 2014. "Nonparametric measures of returns to scale: an application to German water supply," Empirical Economics, Springer, vol. 47(3), pages 1029-1053, November.
  21. Kuosmanen, Timo, 2001. "DEA with efficiency classification preserving conditional convexity," European Journal of Operational Research, Elsevier, vol. 132(2), pages 326-342, July.
  22. Victor Podinovski, 2009. "Production technologies based on combined proportionality assumptions," Journal of Productivity Analysis, Springer, vol. 32(1), pages 21-26, August.
  23. MAIRESSE, François & VANDEN EECKAUT, Philippe, 1999. "Museum assessment and FDH technology: a global approach," LIDAM Discussion Papers CORE 1999038, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  24. Marques, Rui Cunha & De Witte, Kristof, 2011. "Is big better? On scale and scope economies in the Portuguese water sector," Economic Modelling, Elsevier, vol. 28(3), pages 1009-1016, May.
  25. Mehdiloo, Mahmood & Podinovski, Victor V., 2019. "Selective strong and weak disposability in efficiency analysis," European Journal of Operational Research, Elsevier, vol. 276(3), pages 1154-1169.
  26. Cesaroni, Giovanni & Kerstens, Kristiaan & Van de Woestyne, Ignace, 2017. "Global and local scale characteristics in convex and nonconvex nonparametric technologies: A first empirical exploration," European Journal of Operational Research, Elsevier, vol. 259(2), pages 576-586.
  27. Walter Briec & Kristiaan Kerstens & Philippe Venden Eeckaut, 2004. "Non-convex Technologies and Cost Functions: Definitions, Duality and Nonparametric Tests of Convexity," Journal of Economics, Springer, vol. 81(2), pages 155-192, February.
  28. Fukuyama, Hirofumi, 2003. "Scale characterizations in a DEA directional technology distance function framework," European Journal of Operational Research, Elsevier, vol. 144(1), pages 108-127, January.
  29. Walter Briec & Kristiaan Kerstens & Ignace Van de Woestyne, 2022. "Nonconvexity in Production and Cost Functions: An Exploratory and Selective Review," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 18, pages 721-754, Springer.
  30. Hennebel, Veerle & Simper, Richard & Verschelde, Marijn, 2017. "Is there a prison size dilemma? An empirical analysis of output-specific economies of scale," European Journal of Operational Research, Elsevier, vol. 262(1), pages 306-321.
  31. Tavakoli, Ibrahim M. & Mostafaee, Amin, 2019. "Free disposal hull efficiency scores of units with network structures," European Journal of Operational Research, Elsevier, vol. 277(3), pages 1027-1036.
  32. Trigo Gamarra, Lucinda, 2007. "Single- versus multi-channel distribution strategies in the German life insurance market: A cost and profit efficiency analysis," Thuenen-Series of Applied Economic Theory 81, University of Rostock, Institute of Economics.
  33. Kneip, Alois & Simar, Léopold & Wilson, Paul W., 2022. "Conical FDH Estimators of General Technologies, with Applications to Returns to Scale and Malmquist Productivity Indices," LIDAM Discussion Papers ISBA 2022024, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  34. Podinovski, Victor V., 2017. "Returns to scale in convex production technologies," European Journal of Operational Research, Elsevier, vol. 258(3), pages 970-982.
  35. Xiaoqing Chen & Xinwang Liu, 2023. "Comparing Malmquist and Hicks–Moorsteen productivity changes in China’s high-tech industries: exploring convexity implications," 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 1209-1237, December.
  36. Kristof Witte & Rui Marques, 2011. "Big and beautiful? On non-parametrically measuring scale economies in non-convex technologies," Journal of Productivity Analysis, Springer, vol. 35(3), pages 213-226, June.
  37. Kleine, A., 2004. "A general model framework for DEA," Omega, Elsevier, vol. 32(1), pages 17-23, February.
  38. Chavas, Jean-Paul & Kim, Kwansoo, 2013. "Nonparametric Analysis of Technology and Productivity under Non-Convexity," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 149684, Agricultural and Applied Economics Association.
  39. Soleimani-damaneh, M. & Mostafaee, A., 2009. "Stability of the classification of returns to scale in FDH models," European Journal of Operational Research, Elsevier, vol. 196(3), pages 1223-1228, August.
  40. J-P Boussemart & W Briec & H Leleu, 2010. "Linear programming solutions and distance functions under α-returns to scale," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(8), pages 1297-1301, August.
  41. Briec, Walter & Liang, Qi Bin, 2011. "On some semilattice structures for production technologies," European Journal of Operational Research, Elsevier, vol. 215(3), pages 740-749, December.
  42. M. Soleimani-damaneh, 2013. "Another approach for estimating RTS in dynamic DEA," Journal of Productivity Analysis, Springer, vol. 39(1), pages 75-81, February.
  43. Emrouznejad, Ali & De Witte, Kristof, 2010. "COOPER-framework: A unified process for non-parametric projects," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1573-1586, December.
  44. Antonio Peyrache, 2024. "Homothetic Data Generated Production Metatechnologies," CEPA Working Papers Series WP022024, School of Economics, University of Queensland, Australia.
  45. Xiaoqing Chen & Kristiaan Kerstens & Qingyuan Zhu, 2021. "Exploring Horizontal Mergers in Swedish District Courts Using Convex and Nonconvex Technologies: Usefulness of a Conservative Approach," Working Papers 2021-EQM-05, IESEG School of Management.
  46. Xiao, Helu & Zhou, Zhongbao & Ren, Teng & Liu, Wenbin, 2022. "Estimation of portfolio efficiency in nonconvex settings: A free disposal hull estimator with non-increasing returns to scale," Omega, Elsevier, vol. 111(C).
  47. Barnabé Walheer, 2022. "Global Malmquist and cost Malmquist indexes for group comparison," Journal of Productivity Analysis, Springer, vol. 58(1), pages 75-93, August.
  48. Subhash C. Ray, 2010. "A One-Step Procedure for Returns to Scale Classification of Decision Making Units in Data Envelopment Analysis," Working papers 2010-07, University of Connecticut, Department of Economics.
  49. Jean-Paul Chavas & Kwansoo Kim, 2015. "Nonparametric analysis of technology and productivity under non-convexity: a neighborhood-based approach," Journal of Productivity Analysis, Springer, vol. 43(1), pages 59-74, February.
  50. Antonio Peyrache, 2022. "A Homothetic Data Generated Technology," CEPA Working Papers Series WP042022, School of Economics, University of Queensland, Australia.
  51. Sergio Destefanis & Giuseppe Storti, 2002. "Measuring cross-country technological catch-up through variable-parameter FDH," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 11(1), pages 109-125, February.
  52. Sahoo, Biresh K & Khoveyni, Mohammad & Eslami, Robabeh & Chaudhury, Pradipta, 2016. "Returns to scale and most productive scale size in DEA with negative data," European Journal of Operational Research, Elsevier, vol. 255(2), pages 545-558.
  53. Crosato, Lisa & Destefanis, Sergio & Ganugi, Piero, 2007. "Technology and Firm Size Distribution:Evidence from Italian Manufacturing," CELPE Discussion Papers 102, CELPE - CEnter for Labor and Political Economics, University of Salerno, Italy.
  54. Subhash C. Ray, 2018. "Data Envelopment Analysis with Alternative Returns to Scale," Working papers 2018-20, University of Connecticut, Department of Economics.
  55. Peyrache, Antonio, 2024. "A homothetic data generated technology," European Journal of Operational Research, Elsevier, vol. 316(1), pages 255-267.
  56. Victor Podinovski, 2004. "Efficiency and Global Scale Characteristics on the “No Free Lunch” Assumption Only," Journal of Productivity Analysis, Springer, vol. 22(3), pages 227-257, November.
  57. Erbetta, Fabrizio & Rappuoli, Luca, 2008. "Optimal scale in the Italian gas distribution industry using data envelopment analysis," Omega, Elsevier, vol. 36(2), pages 325-336, April.
  58. Giovanni Cesaroni & Kristiaan Kerstens & Ignace Van de Woestyne, 2017. "Estimating scale economies in non-convex production models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(11), pages 1442-1451, November.
  59. Walter Briec & Kristiaan Kerstens & Hervé Leleu & Philippe Eeckaut, 2000. "Returns to Scale on Nonparametric Deterministic Technologies: Simplifying Goodness-of-Fit Methods Using Operations on Technologies," Journal of Productivity Analysis, Springer, vol. 14(3), pages 267-274, November.
  60. Podinovski, V. V., 2004. "On the linearisation of reference technologies for testing returns to scale in FDH models," European Journal of Operational Research, Elsevier, vol. 152(3), pages 800-802, February.
  61. Mohammad Mahdi Mousavi & Jamal Ouenniche, 2018. "Multi-criteria ranking of corporate distress prediction models: empirical evaluation and methodological contributions," Annals of Operations Research, Springer, vol. 271(2), pages 853-886, December.
  62. Podinovski, Victor V. & Bouzdine-Chameeva, Tatiana, 2019. "Cone extensions of polyhedral production technologies," European Journal of Operational Research, Elsevier, vol. 276(2), pages 736-743.
  63. Mahmood Mehdiloo & Jafar Sadeghi & Kristiaan Kerstens, 2024. "Top Down Axiomatic Modeling of Metatechnologies and Evaluating Directional Economic Efficiency," Working Papers 2024-EQM-03, IESEG School of Management.
  64. Cesaroni, Giovanni & Giovannola, Daniele, 2015. "Average-cost efficiency and optimal scale sizes in non-parametric analysis," European Journal of Operational Research, Elsevier, vol. 242(1), pages 121-133.
  65. Sergio Destefanis & Vania Sena, 2005. "Public capital and total factor productivity: New evidence from the Italian regions, 1970-98," Regional Studies, Taylor & Francis Journals, vol. 39(5), pages 603-617.
  66. Soleimani-damaneh, M. & Jahanshahloo, G.R. & Reshadi, M., 2006. "On the estimation of returns-to-scale in FDH models," European Journal of Operational Research, Elsevier, vol. 174(2), pages 1055-1059, October.
  67. Soleimani-damaneh, Majid & Mostafaee, Amin, 2015. "Identification of the anchor points in FDH models," European Journal of Operational Research, Elsevier, vol. 246(3), pages 936-943.
  68. Alirezaee, Mohammadreza & Hajinezhad, Ensie & Paradi, Joseph C., 2018. "Objective identification of technological returns to scale for data envelopment analysis models," European Journal of Operational Research, Elsevier, vol. 266(2), pages 678-688.
  69. M Soleimani-damaneh, 2009. "A fast algorithm for determining some characteristics in DEA," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(11), pages 1528-1534, November.
  70. V V Podinovski, 2004. "Local and global returns to scale in performance measurement," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(2), pages 170-178, February.
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