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Using the latent class approach to cluster firms in benchmarking: An application to the US electricity transmission industry

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Cited by:

  1. Christian Grovermann & Tesfamicheal Wossen & Adrian Muller & Karin Nichterlein, 2019. "Eco-efficiency and agricultural innovation systems in developing countries: Evidence from macro-level analysis," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-16, April.
  2. Kerstens, Kristiaan & O’Donnell, Christopher & Van de Woestyne, Ignace, 2019. "Metatechnology frontier and convexity: A restatement," European Journal of Operational Research, Elsevier, vol. 275(2), pages 780-792.
  3. Chinmoy, Lakshmi & Iniyan, S. & Goic, Ranko, 2019. "Modeling wind power investments, policies and social benefits for deregulated electricity market – A review," Applied Energy, Elsevier, vol. 242(C), pages 364-377.
  4. Ronald G. McGarvey & Andreas Thorsen & Maggie L. Thorsen & Rohith Madhi Reddy, 2019. "Measuring efficiency of community health centers: a multi-model approach considering quality of care and heterogeneous operating environments," Health Care Management Science, Springer, vol. 22(3), pages 489-511, September.
  5. Llorca, Manuel & Rodriguez-Alvarez, Ana & Jamasb, Tooraj, 2020. "Objective vs. subjective fuel poverty and self-assessed health," Energy Economics, Elsevier, vol. 87(C).
  6. 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.
  7. Llorca, Manuel & Orea, Luis & Pollitt, Michael G., 2016. "Efficiency and environmental factors in the US electricity transmission industry," Energy Economics, Elsevier, vol. 55(C), pages 234-246.
  8. Pavala Malar Kannan & Govindan Marthandan & Rathimala Kannan, 2021. "Modelling Efficiency of Electric Utilities Using Three Stage Virtual Frontier Data Envelopment Analysis with Variable Selection by Loads Method," Energies, MDPI, vol. 14(12), pages 1-21, June.
  9. Luis Orea & Inmaculada C. Álvarez & Tooraj Jamasb, 2016. "Using a spatial econometric approach to mitigate omitted variables in stochastic frontier models: An application to Norwegian electricity distribution networks," Working Papers EPRG 1630, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
  10. 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.
  11. Feder, Christophe, 2018. "The effects of disruptive innovations on productivity," Technological Forecasting and Social Change, Elsevier, vol. 126(C), pages 186-193.
  12. Rita, Rui & Marques, Vitor & Lúcia Costa, Ana & Matos Chaves, Inês & Gomes, Joana & Paulino, Paulo, 2018. "Efficiency performance and cost structure of Portuguese energy “utilities” – Non-parametric and parametric analysis," Energy, Elsevier, vol. 155(C), pages 35-45.
  13. Orea, Luis & Álvarez, Inmaculada C. & Jamasb, Tooraj, 2016. "A spatial approach to control for unobserved environmental conditions when measuring firms’ technology: an application to Norwegian electricity distribution networks," Efficiency Series Papers 2016/06, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
  14. Just, Lisa, 2021. "Unobserved technological heterogeneity among German electricity distribution network operators - a latent class analysis," EWI Working Papers 2021-5, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
  15. Jamasb, Tooraj & Llorca, Manuel & Khetrapal, Pavan & Thakur, Tripta, 2021. "Institutions and performance of regulated firms: Evidence from electricity distribution in India," Economic Analysis and Policy, Elsevier, vol. 70(C), pages 68-82.
  16. Massimo Filippini & Luis Orea, 2014. "Applications of the stochastic frontier approach in Energy Economics," Economics and Business Letters, Oviedo University Press, vol. 3(1), pages 35-42.
  17. Juan Cabas Monje & Bouali Guesmi & Amer Ait Sidhoum & José María Gil, 2023. "Measuring technical efficiency of Spanish pig farming: Quantile stochastic frontier approach," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 67(4), pages 688-703, October.
  18. Francisco Benita & Serhad Sarica & Garvit Bansal, 2020. "Testing the static and dynamic performance of statistical methods for the detection of national industrial clusters," Papers in Regional Science, Wiley Blackwell, vol. 99(4), pages 1137-1157, August.
  19. 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.
  20. Romano, Teresa & Cambini, Carlo & Fumagalli, Elena & Rondi, Laura, 2022. "Setting network tariffs with heterogeneous firms: The case of natural gas distribution," European Journal of Operational Research, Elsevier, vol. 297(1), pages 280-290.
  21. Luis Orea & Tooraj Jamasb, 2017. "Regulating Heterogeneous Utilities: A New Latent Class Approach with Application to the Norwegian Electricity Distribution Networks," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
  22. da Silva, Aline Veronese & Costa, Marcelo Azevedo & Lopes, Ana Lúcia Miranda & do Carmo, Gabriela Miranda, 2019. "A close look at second stage data envelopment analysis using compound error models and the Tobit model," Socio-Economic Planning Sciences, Elsevier, vol. 65(C), pages 111-126.
  23. Agrell, P & Brea-Solís, H., 2015. "Stationarity of Heterogeneity in Production Technology using Latent Class Modelling," LIDAM Discussion Papers CORE 2015047, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  24. Vesterberg, Mattias & Zhou, Wenchao & Lundgren, Tommy, 2021. "Wind of change: Small-scale electricity production and distribution-grid efficiency in Sweden," Utilities Policy, Elsevier, vol. 69(C).
  25. Magdalena Kapelko & Alfons Oude Lansink, 2022. "Measuring firms' dynamic inefficiency accounting for corporate social responsibility in the U.S. food and beverage manufacturing industry," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 44(4), pages 1702-1721, December.
  26. 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.
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