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Ordinal principal component analysis for a common ranking of stochastic frontiers

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  • Sergio Scippacercola
  • Enrica Sepe

Abstract

The Stochastic Frontier Analysis (SFA) is a model to evaluate the Technical Efficiency (TE) for Production Units (PU). When SFA is applied on different output variables with same input, the analysis estimates different TEs for the PU. We refer to these TEs as the Multiple Technical Efficiency (MTE) of the PU. In this work, we present a method to unify the MTE in one ranking, in order to compute a synthetic index of the TE based on a parametric model. Our approach transforms the measures of efficiency into values on an ordinal scale. Then, using the Ordinal Principal Component Analysis and a genetic algorithm, we merge the multiple rankings.

Suggested Citation

  • Sergio Scippacercola & Enrica Sepe, 2016. "Ordinal principal component analysis for a common ranking of stochastic frontiers," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(13), pages 2442-2451, October.
    • Handle: RePEc:taf:japsta:v:43:y:2016:i:13:p:2442-2451
    DOI: 10.1080/02664763.2016.1163530
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    1. Kumbhakar,Subal C. & Lovell,C. A. Knox, 2003. "Stochastic Frontier Analysis," Cambridge Books, Cambridge University Press, number 9780521666633, January.
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