IDEAS home Printed from https://ideas.repec.org/c/boc/bocode/s453601.html
 

SVYGEI_SVYATK: Stata module to derive the sampling variances of Generalized Entropy and Atkinson inequality indices when estimated from complex survey data

Author

Listed:
  • Stephen P. Jenkins

    (London School of Economics and Political Science)

  • Martin Biewen

    (University of Tuebingen)

Programming Language

Stata

Abstract

-svygei- and -svyatk- are programs to estimate Generalized Entropy and Atkinson inequality indices, together with their sampling variances. Sampling variances are calculated using a linearization method proposed by Woodruff (JASA, 1971). The program may also be used to calculate sampling variances in the case where there are i.i.d. observations.

Suggested Citation

  • Stephen P. Jenkins & Martin Biewen, 2005. "SVYGEI_SVYATK: Stata module to derive the sampling variances of Generalized Entropy and Atkinson inequality indices when estimated from complex survey data," Statistical Software Components S453601, Boston College Department of Economics, revised 31 Aug 2017.
  • Handle: RePEc:boc:bocode:s453601
    Note: This module should be installed from within Stata 8 by typing "ssc install svygei_svyatk". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
    as

    Download full text from publisher

    File URL: http://fmwww.bc.edu/repec/bocode/s/svygei.ado
    File Function: program code
    Download Restriction: no

    File URL: http://fmwww.bc.edu/repec/bocode/s/svyatk.ado
    File Function: program code
    Download Restriction: no

    File URL: http://fmwww.bc.edu/repec/bocode/s/svygei.sthlp
    File Function: help file
    Download Restriction: no

    File URL: http://fmwww.bc.edu/repec/bocode/s/svyatk.sthlp
    File Function: help file
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Stephen P. Jenkins & Richard V. Burkhauser & Shuaizhang Feng & Jeff Larrimore, 2009. "Measuring Inequality Using Censored Data: A Multiple Imputation Approach," Discussion Papers of DIW Berlin 866, DIW Berlin, German Institute for Economic Research.

    More about this item

    Keywords

    inequality; generalized entropy; Atkinson index; variances; Stata;
    All these keywords.

    Lists

    This item is featured on the following reading lists, Wikipedia, or ReplicationWiki pages:
    1. Atkinson index in Wikipedia English

    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:boc:bocode:s453601. 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: Christopher F Baum (email available below). General contact details of provider: https://edirc.repec.org/data/debocus.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.