IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2512.07709.html

Bounds on inequality with incomplete data

Author

Listed:
  • James Banks
  • Thomas Glinnan
  • Tatiana Komarova

Abstract

We study inequality measures when outcomes are observed only in intervals, as in historical tabulations, privacy-protected grouped data, and modern surveys. We develop a nonparametric framework for sharp identification and inference with grouped and interval-valued data, covering brackets and overlapping intervals. For a class of inequality indices, sharp bounds are attained by discrete distributions with finite support, reducing the problem to optimization; linear-fractional indices, including the Gini and quantile ratios, yield linear or quadratic programs. Plug-in bound endpoints have a $\sqrt{n}$ asymptotic distribution, using an $m$-out-of-$n$ bootstrap. Applications to wealth and historical income data compare identified sets with imputation-based estimates.

Suggested Citation

  • James Banks & Thomas Glinnan & Tatiana Komarova, 2025. "Bounds on inequality with incomplete data," Papers 2512.07709, arXiv.org, revised Aug 2026.
    • Handle: RePEc:arx:papers:2512.07709
    as

    Download full text from publisher

    File URL: https://arxiv.org/pdf/2512.07709
    File Function: Latest version
    Download Restriction: no
    ---><---

    More about this item

    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:arx:papers:2512.07709. 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: arXiv administrators (email available below). General contact details of provider: https://arxiv.org/ .

    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.