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Measuring efficiency in allocating inputs among outputs with DEA

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  • Darold Barnum
  • John Gleason

Abstract

Building on Data Envelopment Analysis technical efficiency models developed by Fare et al. (2004) and Barnum and Gleason (2005), a procedure is illustrated for estimating a firm's efficiency in allocating inputs among the production technologies producing its outputs.

Suggested Citation

  • Darold Barnum & John Gleason, 2006. "Measuring efficiency in allocating inputs among outputs with DEA," Applied Economics Letters, Taylor & Francis Journals, vol. 13(6), pages 333-336.
    • Handle: RePEc:taf:apeclt:v:13:y:2006:i:6:p:333-336
    DOI: 10.1080/13504850500395340
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    References listed on IDEAS

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    1. Loren Tauer, 2001. "Input aggregation and computed technical efficiency," Applied Economics Letters, Taylor & Francis Journals, vol. 8(5), pages 295-297.
    2. Darold Barnum & John Gleason, 2005. "Technical efficiency bias caused by intra-input aggregation in data envelopment analysis," Applied Economics Letters, Taylor & Francis Journals, vol. 12(13), pages 785-788.
    3. Rolf Fare & Valentin Zelenyuk, 2002. "Input aggregation and technical efficiency," Applied Economics Letters, Taylor & Francis Journals, vol. 9(10), pages 635-636.
    4. Rolf Fare & Shawna Grosskopf & Valentin Zelenyuk, 2004. "Aggregation bias and its bounds in measuring technical efficiency," Applied Economics Letters, Taylor & Francis Journals, vol. 11(10), pages 657-660.
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    Cited by:

    1. Darold T. Barnum & John M. Gleason, 2007. "Technical efficiency bias in data envelopment analysis caused by intra-output aggregation," Applied Economics Letters, Taylor & Francis Journals, vol. 14(9), pages 623-626.
    2. Barnum, Darold T. & Karlaftis, Matthew G. & Tandon, Sonali, 2011. "Improving the efficiency of metropolitan area transit by joint analysis of its multiple providers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(6), pages 1160-1176.

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