IDEAS home Printed from https://ideas.repec.org/a/taf/recsxx/v25y2022i1p339-360.html
   My bibliography  Save this article

Model definitions to identify appropriate benchmarks in judiciary

Author

Listed:
  • G. Falavigna
  • R. Ippoliti

Abstract

In this manuscript we present a comparative analysis of benchmarks based on technical efficiency scores computed using Data Envelopment Analysis with two different model specifications. In one case, we adopt the number of settled cases as output and human resources as input; in the other case, we adopt the same model definition but with judicial expenditure as additional key input. Our findings show that the model specification containing both judicial expenditure and human resources is more appropriate than the model based only on human resources. Moreover, we show that, without considering the additional variable costs generated within the production process, those courts incorrectly identified as benchmarks might mislead the policy makers dealing with the reform process.

Suggested Citation

  • G. Falavigna & R. Ippoliti, 2022. "Model definitions to identify appropriate benchmarks in judiciary," Journal of Applied Economics, Taylor & Francis Journals, vol. 25(1), pages 339-360, December.
  • Handle: RePEc:taf:recsxx:v:25:y:2022:i:1:p:339-360
    DOI: 10.1080/15140326.2021.2021128
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/15140326.2021.2021128
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/15140326.2021.2021128?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Fernando Freire Vasconcelos & Renato Máximo Sátiro & Luiz Paulo Lopes Fávero & Gabriela Troyano Bortoloto & Hamilton Luiz Corrêa, 2023. "Analysis of Judiciary Expenditure and Productivity Using Machine Learning Techniques," Mathematics, MDPI, vol. 11(14), pages 1-19, July.

    More about this item

    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:taf:recsxx:v:25:y:2022:i:1:p:339-360. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/recs .

    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.