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Assessing the Relative Efficiency for Listed Manufacturing Firms in Jordan Using Data Envelopment Analysis

Author

Listed:
  • Lamees Al-Durgham

    (Department of Industrial Engineering, School of Engineering, University of Jordan, Jordan)

  • Mohammad Adeinat

    (Department of Business Economics, School of Business, University of Jordan, Jordan.)

Abstract

The purpose of this study is to measure and compare the efficiencies for 35 manufacturing firms listed in Amman Stock exchange (ASE) in Jordan over the period 2009-2017. A panel data was collected for the firms over the nine years, the data was collected from the annual reports of the firms. The Data Envelopment Analysis (DEA) was used to measure an average efficiency score for each firm, the DEA was also used to find a panel data for efficiency scores, since the data was available for a short period of nine years the bootstrap technique was used to estimate a confidence interval for the efficiency score for each firm. The linear transformation form of Cobb- Douglas production function with two inputs (capital and labor) and one output (production) was used in DEA. The study revealed that among the 35 firms only 4 firms were efficient, and the rank for the firms efficiency were also obtained.

Suggested Citation

  • Lamees Al-Durgham & Mohammad Adeinat, 2021. "Assessing the Relative Efficiency for Listed Manufacturing Firms in Jordan Using Data Envelopment Analysis," International Journal of Economics and Financial Issues, Econjournals, vol. 11(1), pages 135-139.
    • Handle: RePEc:eco:journ1:2021-01-14
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Data envelopment analysis; efficiency; manufacturing firm; bootstrap technique; Cobb- Douglas.;
    All these keywords.

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory

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