IDEAS home Printed from https://ideas.repec.org/p/aiz/louvar/2023008.html

Further Improvements of Finite Sample Approximation of Central Limit Theorems for Envelopment Estimators

Author

Listed:
  • Simar, Léopold

    (Université catholique de Louvain, LIDAM/ISBA, Belgium)

  • Zelenyuk, Valentin
  • Zhao, Shirong

Abstract

A simple yet easy to implement method is proposed to further improve the finite sample approximation of the recently developed central limit theorems for aggregates of envelopment estimators. Focusing on the simple mean efficiency, we propose using the bias-corrected individual efficiency estimate to improve the variance estimator. The extensive Monte-Carlo experiments confirm that, for relatively small sample sizes (≤ 100), with both low dimensions and especially for high dimensions, our new method combined with the data sharpening method generally provides better ‘coverage’ (of the true values by the estimated confidence intervals) than the previously developed approaches.

Suggested Citation

  • Simar, Léopold & Zelenyuk, Valentin & Zhao, Shirong, 2023. "Further Improvements of Finite Sample Approximation of Central Limit Theorems for Envelopment Estimators," LIDAM Reprints ISBA 2023008, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    • Handle: RePEc:aiz:louvar:2023008
    DOI: https://doi.org/10.1007/s11123-023-00661-8
    Note: In: Journal of Productivity Analysis, 2023, vol. 59(2), p. 189-194
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Léopold Simar & Valentin Zelenyuk & Shirong Zhao, 2025. "Statistical inference for Hicks–Moorsteen productivity indices," Annals of Operations Research, Springer, vol. 351(2), pages 1675-1703, August.
    2. Zelenyuk, Valentin & Zhao, Shirong, 2024. "Russell and slack-based measures of efficiency: A unifying framework," European Journal of Operational Research, Elsevier, vol. 318(3), pages 867-876.
    3. Sokol, Ondřej & Frýd, Lukáš, 2023. "DEA efficiency in agriculture: Measurement unit issues," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
    4. Simar, Léopold & Zelenyuk, Valentin & Zhao, Shirong, 2024. "Inference for aggregate efficiency: Theory and guidelines for practitioners," European Journal of Operational Research, Elsevier, vol. 316(1), pages 240-254.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aiz:louvar:2023008. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Nadja Peiffer (email available below). General contact details of provider: https://edirc.repec.org/data/isuclbe.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.