IDEAS home Printed from https://ideas.repec.org/a/spr/joecin/v22y2024i4d10.1007_s10888-023-09617-2.html
   My bibliography  Save this article

Recovering income distribution in the presence of interval-censored data

Author

Listed:
  • Fernando Rios-Avila

    (Levy Institute at Bard College)

  • Gustavo Canavire-Bacarreza

    (The World Bank
    Universidad Privada Boliviana)

  • Flavia Sacco-Capurro

    (The World Bank)

Abstract

We propose a method to analyze interval-censored data using a multiple imputation based on a Heteroskedastic Interval regression approach. The proposed model aims to obtain a synthetic dataset that can be used for standard analysis, including standard linear regression, quantile regression, or poverty and inequality estimation. We present two applications to show the performance of our method. First, we run a Monte Carlo simulation to show the method's performance under the assumption of multiplicative heteroskedasticity, with and without conditional normality. Second, we use the proposed methodology to analyze labor income data in Grenada for 2013-2020, where the salary data are interval-censored according to the salary intervals prespecified in the survey questionnaire. The results obtained are consistent across both exercises.

Suggested Citation

  • Fernando Rios-Avila & Gustavo Canavire-Bacarreza & Flavia Sacco-Capurro, 2024. "Recovering income distribution in the presence of interval-censored data," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 22(4), pages 1039-1060, December.
    • Handle: RePEc:spr:joecin:v:22:y:2024:i:4:d:10.1007_s10888-023-09617-2
    DOI: 10.1007/s10888-023-09617-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10888-023-09617-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10888-023-09617-2?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.

    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:spr:joecin:v:22:y:2024:i:4:d:10.1007_s10888-023-09617-2. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.