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Cost constrained industry inefficiency

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  • Peyrache, Antonio

Abstract

In this paper a definition of industry inefficiency in cost constrained production environments is introduced. This definition uses the indirect directional distance function and quantifies the inefficiency of the industry in terms of the overall output loss, given the industry cost budget. The industry inefficiency indicator is then decomposed into sources components: reallocation inefficiency arising from sub-optimal configuration of the industry; firm inefficiency arising from a failure to select optimal input quantities (given the prevalent inputs prices); firm inefficiency due to lack of best practices. The method is illustrated using data on Ontario electricity distributors. These data show that lack of best practices is only a minor component of the overall inefficiency of the industry (less than 10 percent), with reallocation inefficiency accounting for more than 75 percent of the overall inefficiency of the system. An analysis based on counter-factual input prices is conducted in order to illustrate how the model can be used to estimate the effects of a change in the regulation regime.

Suggested Citation

  • Peyrache, Antonio, 2015. "Cost constrained industry inefficiency," European Journal of Operational Research, Elsevier, vol. 247(3), pages 996-1002.
  • Handle: RePEc:eee:ejores:v:247:y:2015:i:3:p:996-1002
    DOI: 10.1016/j.ejor.2015.06.067
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    Cited by:

    1. Ane Elixabete Ripoll-Zarraga & Sebastián Lozano, 2020. "A centralised DEA approach to resource reallocation in Spanish airports," Annals of Operations Research, Springer, vol. 288(2), pages 701-732, May.
    2. Valentin Zelenyuk, 2018. "Some Mathematical and Historical Clarifications on Aggregation in Efficiency and Productivity Analysis and Connection to Economic Theory," CEPA Working Papers Series WP032018, School of Economics, University of Queensland, Australia.
    3. Antonio Peyrache & Maria C. A. Silva, 2022. "Efficiency and Productivity Analysis from a System Perspective: Historical Overview," Springer Books, in: Duangkamon Chotikapanich & Alicia N. Rambaldi & Nicholas Rohde (ed.), Advances in Economic Measurement, chapter 0, pages 173-230, Springer.
    4. Walheer, Barnabé, 2019. "Aggregating Farrell efficiencies with private and public inputs," European Journal of Operational Research, Elsevier, vol. 276(3), pages 1170-1177.
    5. Hien Thu Pham & Antonio Peyrache, 2015. "Industry Inefficiency Measures: A Unifying Approximation Proposition," CEPA Working Papers Series WP102015, School of Economics, University of Queensland, Australia.
    6. Cesaroni, Giovanni, 2020. "Technically and cost-efficient centralized allocations in data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    7. Ali Homayoni & Reza Fallahnejad & Farhad Hosseinzadeh Lotfi, 2022. "Cross Malmquist Productivity Index in Data Envelopment Analysis," 4OR, Springer, vol. 20(4), pages 567-602, December.
    8. Antonio Peyrache & Maria C. A. Silva, 2019. "The Inefficiency of Production Systems and its decomposition," CEPA Working Papers Series WP052019, School of Economics, University of Queensland, Australia.
    9. Antonio Peyrache & Maria C. A. Silva, 2023. "Efficiency decomposition for multi-level multi-components production technologies," Journal of Productivity Analysis, Springer, vol. 60(3), pages 273-294, December.
    10. Walheer, Barnabe & Hudik, Marek, 2019. "Reallocation of resources in multidivisional firms: A nonparametric approach," International Journal of Production Economics, Elsevier, vol. 214(C), pages 196-205.
    11. Peyrache, Antonio & Zago, Angelo, 2016. "Large courts, small justice!," Omega, Elsevier, vol. 64(C), pages 42-56.

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