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More is better than one: the impact of different numbers of input aggregators in technical efficiency estimation

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  • Aldanondo, Ana M.
  • Casasnovas, Valero L.

Abstract

The results of an experiment with simulated data show that combining inputs with different criteria (as cost, material inputs aggregates and other) increases the accuracy of the Data Envelopment Analysis (DEA) technical efficiency estimator in data sets with dimensionality problems. The positive impact of this approach surpasses that of reducing the number of variables, since replacement of the original inputs with an equal number of aggregates improves DEA performance in a wide range of cases.

Suggested Citation

  • Aldanondo, Ana M. & Casasnovas, Valero L., 2015. "More is better than one: the impact of different numbers of input aggregators in technical efficiency estimation," MPRA Paper 64120, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:64120
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    File URL: https://mpra.ub.uni-muenchen.de/64120/1/MPRA_paper_64120.pdf
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    References listed on IDEAS

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    Cited by:

    1. Aldanondo, Ana M. & Casasnovas, Valero L. & Almansa, M. Carmen, 2016. "Cost-constrained measures of environmental efficiency: a material balance approach," MPRA Paper 72490, University Library of Munich, Germany.

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    More about this item

    Keywords

    Technical efficiency; Aggregation bias; Monte Carlo; DEA Estimator accuracy;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D20 - Microeconomics - - Production and Organizations - - - General

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