IDEAS home Printed from https://ideas.repec.org/p/hhs/hastef/0091.html
   My bibliography  Save this paper

Scale Efficiency and Scale Elasticity in DEA-models - A Bootstrapping Approach

Author

Listed:
  • Löthgren, Mickael

    (Department of Economic Statistics)

  • Tambour, Magnus

    (Centre for Health Economics)

Abstract

This paper presents and applies different approaches to estimate returns to scale in multiple-input muliple-output technologies. Scale efficiency gives quantitative information of scale characteristics. A primal based approach to estimate the scale elasticity is proposed as an alternative to the earlier established dual based hyperplane approach. The different scale measures are defined in terms of technical efficiency measures, that can be estimated byb Data Envelopment Analysis (DEA). The DEA- method is inherently deterministic and hence offers no measures of uncertainty in the returns to scale estimates. Conditional on the sample at hand, the bootstrap offers a possibility to perform formal statistical hypotheses testing of the scale efficiencies and elasticities. Empirical evidence from (public) eye-care departments in Sweden from the years 1992 and 1993 is presented.

Suggested Citation

  • Löthgren, Mickael & Tambour, Magnus, 1996. "Scale Efficiency and Scale Elasticity in DEA-models - A Bootstrapping Approach," SSE/EFI Working Paper Series in Economics and Finance 91, Stockholm School of Economics.
  • Handle: RePEc:hhs:hastef:0091
    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 search for a similarly titled item that would be available.

    More about this item

    Keywords

    DEA; scale efficiency; bootstrap; eye-care services;
    All these keywords.

    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
    • H42 - Public Economics - - Publicly Provided Goods - - - Publicly Provided Private Goods

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:hhs:hastef:0091. 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: Helena Lundin (email available below). General contact details of provider: https://edirc.repec.org/data/erhhsse.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.