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Economic Measures of Capacity Utilization: A Nonparametric Cost Function Analysis

Author

Listed:
  • Subhash C. Ray

    (University of Connecticut)

  • John Walden

    (National Marine Fisheries Service)

  • Lei Chen

    (Jianghan University)

Abstract

Cost based measures of capacity utilization and capacity output are important metrics for evaluating firm performance. Understanding where firms are producing on their average cost curve provides information about whether capacity utilization is greater then, less than or equal to one. Most firms are multi-output, multi-input in nature which makes estimation of capacity utilization and capacity output challenging if a cost based measure is desired. For a multi-output firm, the relevant concept is ray average cost (RAC) which can be estimated through non-linear DEA models. This paper offers a simple transformation that linearizes the non-linear DEA program to estimate average, or ray average cost, and to determine capacity utilization and optimal output. The methods are empirically tested on data from a number of U.S. electricity producers for the single output case, and a sample of dental practices for the multi-output case. Results show that for both industries, most firms were operating at less than full capacity, and needed to expand output to minimize their costs. For the dental practices, examination of results from six randomly chosen firms showed the importance of operatories in determining optimal levels of output.

Suggested Citation

  • Subhash C. Ray & John Walden & Lei Chen, 2018. "Economic Measures of Capacity Utilization: A Nonparametric Cost Function Analysis," Working papers 2018-02, University of Connecticut, Department of Economics.
  • Handle: RePEc:uct:uconnp:2018-02
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    References listed on IDEAS

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    Cited by:

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    2. Wang, Miao & Feng, Chao, 2023. "Measuring capacity utilization under the constraints of energy consumption and CO2 emissions using meta-frontier DEA: A case of China's non-ferrous metal industries," Resources Policy, Elsevier, vol. 80(C).
    3. Wang, Delu & Wan, Kaidi & Song, Xuefeng & Liu, Yun, 2019. "Provincial allocation of coal de-capacity targets in China in terms of cost, efficiency, and fairness," Energy Economics, Elsevier, vol. 78(C), pages 109-128.
    4. Dale Squires & Kathleen Segerson, 2022. "Capacity and Capacity Utilization in Production Economics," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 24, pages 1001-1037, Springer.
    5. Wang, Delu & Liu, Yifei & Wang, Yadong & Shi, Xunpeng & Song, Xuefeng, 2020. "Allocation of coal de-capacity quota among provinces in China: A bi-level multi-objective combinatorial optimization approach," Energy Economics, Elsevier, vol. 87(C).

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    More about this item

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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