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How to Bootstrap DEA Estimators: A Monte Carlo Comparison

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  • Löthgren, Mickael

    () (Dept. of Economic Statistics, Stockholm School of Economics)

Abstract

This paper evaluates the performance of three bootstrap algorithms for the data envelopment analysis (DEA) estimator using a Monte Carlo simulation study. The Löthgren and Tambour (1997) (LT) algorithm; the Simar and Wilson (1997b) (SW) algorithm; and a combination of the LT and SW algorithms (the LSW-algorithm) are considered in the study. The empirical coverage accuracy of bootstrap confidence intervals are simulated under both variable returns to scale (VRS) and constant return-to-scale (CRS) restricted DEA estimators. The results indicate that the LSW-algorithm performs slightly better than the LT-algorithm, which in turn performs better than the SW-algorithm.

Suggested Citation

  • Löthgren, Mickael, 1998. "How to Bootstrap DEA Estimators: A Monte Carlo Comparison," SSE/EFI Working Paper Series in Economics and Finance 223, Stockholm School of Economics.
  • Handle: RePEc:hhs:hastef:0223
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    Citations

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    Cited by:

    1. Michaelides, Panayotis G. & Vouldis, Angelos T. & Tsionas, Efthymios G., 2010. "Globally flexible functional forms: The neural distance function," European Journal of Operational Research, Elsevier, vol. 206(2), pages 456-469, October.
    2. Wijesiri, Mahinda & Viganò, Laura & Meoli, Michele, 2015. "Efficiency of microfinance institutions in Sri Lanka: a two-stage double bootstrap DEA approach," Economic Modelling, Elsevier, vol. 47(C), pages 74-83.
    3. Hawdon, David, 2003. "Efficiency, performance and regulation of the international gas industry--a bootstrap DEA approach," Energy Policy, Elsevier, vol. 31(11), pages 1167-1178, September.
    4. Carlos Barros & Pedro Garcia-del-Barrio, 2011. "Productivity drivers and market dynamics in the Spanish first division football league," Journal of Productivity Analysis, Springer, vol. 35(1), pages 5-13, February.

    More about this item

    Keywords

    Bootstrap; Confidence Intervals; Data Envelopment Analysis; Monte Carlo Simulation;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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