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A note on the impact of multiple 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 using multiple positive lineal aggregators of the same inputs instead of the original variables increases the accuracy of the Data Envelopment Analysis (DEA) technical efficiency estimator in data sets beset by dimensionality problems. Aggregation of the inputs achieves more than the mere reduction of 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., 2016. "A note on the impact of multiple input aggregators in technical efficiency estimation," MPRA Paper 75290, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:75290
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    File URL: https://mpra.ub.uni-muenchen.de/75290/1/MPRA_paper_75290.pdf
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    References listed on IDEAS

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    1. Aldanondo-Ochoa, Ana M. & Casasnovas-Oliva, Valero L. & Almansa-Sáez, M. Carmen, 2017. "Cross-constrained Measuring the Cost-environment Efficiency in Material Balance Based Frontier Models," Ecological Economics, Elsevier, vol. 142(C), pages 46-55.

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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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