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Fractional regression models for second stage DEA efficiency analyses

Author

Listed:
  • Esmeralda A. Ramalho,

    (Departamento de Economia, Universidade de Evora and CEFAGE-UE)

  • Joaquim J.S. Ramalho

    (Departamento de Economia, Universidade de Evora and CEFAGE-UE)

  • Pedro D. Henriques

    (Departamento de Economia, Universidade de Evora and CEFAGE-UE)

Abstract

Data envelopment analysis (DEA) is commonly used to measure the relative efficiency of decision-making units. Often, in a second stage, a regression model is estimated to relate DEA efficiency scores to exogenous factors. In this paper, we argue that the traditional linear or tobit approaches to second-stage DEA analysis do not constitute a reasonable data-generating process for DEA scores. Under the assumption that DEA scores can be treated as descriptive measures of the relative performance of units in the sample, we show that using fractional regression models are the most natural way of modeling bounded, proportional response variables such as DEA scores. We also propose generalizations of these models and, given that DEA scores take frequently the value of unity, examine the use of two-part models in this framework. Several tests suitable for assessing the specification of each alternative model are also discussed.

Suggested Citation

  • Esmeralda A. Ramalho, & Joaquim J.S. Ramalho & Pedro D. Henriques, 2010. "Fractional regression models for second stage DEA efficiency analyses," CEFAGE-UE Working Papers 2010_01, University of Evora, CEFAGE-UE (Portugal).
    • Handle: RePEc:cfe:wpcefa:2010_01
    as

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    References listed on IDEAS

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    More about this item

    Keywords

    Second-stage DEA; Fractional data; Specification tests; One outcomes; Two-part models.;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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