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Measuring Productive Efficiency in Input-Output Models by Means of Data Envelopment Analysis


  • Jose L. Zofio
  • Angel M. Prieto


The goal of the present research is to evaluate productive efficiency in an input-output framework by means of data envelopment analysis (DEA). This mathematical programming technique allows researchers to assess potential efficiency improvements in the form of input requirements reduction. By constructing envelopment unitary isoquants corresponding to comparable sectors across different local, regional or national economies, e.g. agriculture and manufacturing, DEA identifies as productive benchmarks those economies that exhibit the lowest technical coefficients, i.e. lowest input amount to produce one unit of output. Once these reference frontiers have been defined, it is possible to assess what would be the potential efficiency improvements available to the inefficient economies if they were to produce according to the best practice technologies of their benchmark peers. From an equivalent perspective, these simulations identify the necessary changes that each productive sector needs to undertake in order to reach the efficiency levels of the most successful economies. Finally, within Leontief's analytical construction, these calculations allow us to assess what would have been the economy-wid,e benefits for the inefficient economies—in terms of intermediate consumption reductions and final demand increases—of producing with best practice technologies. The model is empirically illustrated using the input-output tables for a set of OECD countries.

Suggested Citation

  • Jose L. Zofio & Angel M. Prieto, 2007. "Measuring Productive Efficiency in Input-Output Models by Means of Data Envelopment Analysis," International Review of Applied Economics, Taylor & Francis Journals, vol. 21(4), pages 519-537.
  • Handle: RePEc:taf:irapec:v:21:y:2007:i:4:p:519-537
    DOI: 10.1080/02692170701189219

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    Cited by:

    1. Friesner, Daniel & Mittelhammer, Ron & Rosenman, Robert, 2013. "Inferring the incidence of industry inefficiency from DEA estimates," European Journal of Operational Research, Elsevier, vol. 224(2), pages 414-424.


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