IDEAS home Printed from https://ideas.repec.org/p/ecr/col027/44214.html
   My bibliography  Save this paper

Desagregación de datos en encuestas de hogares: metodologías de estimación en áreas pequeñas

Author

Listed:
  • Molina, Isabel

Abstract

Las encuestas de hogares son un instrumento ampliamente utilizado para obtener información sobre la situación socioeconómica y el bienestar de las personas. Sin embargo, la precisión de las estimaciones de las encuestas de hogares decrece sustancialmente cuando se trata de realizar inferencias para grupos poblacionales que representan desagregaciones para las cuales la encuesta no fue diseñada. En este contexto, es posible utilizar procesos de estimación que combinan la información de las encuestas de hogares con información auxiliar existente a nivel poblacional como censos o registros administrativos. Este documento presenta una guía metodológica de la conjunción de técnicas estadísticas de las encuestas y modelos probabilísticos con el fin de producir desagregaciones para grupos de interés, conocidas como técnicas de estimación de áreas pequeñas.

Suggested Citation

  • Molina, Isabel, 2019. "Desagregación de datos en encuestas de hogares: metodologías de estimación en áreas pequeñas," Estudios Estadísticos 44214, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL).
    • Handle: RePEc:ecr:col027:44214
    as

    Download full text from publisher

    File URL: http://repositorio.cepal.org/handle/11362/44214
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Corral Rodas,Paul Andres & Molina,Isabel & Nguyen,Minh Cong, 2020. "Pull Your Small Area Estimates up by the Bootstraps," Policy Research Working Paper Series 9256, The World Bank.
    2. Corral Rodas,Paul Andres & Kastelic,Kristen Himelein & Mcgee,Kevin Robert & Molina,Isabel, 2021. "A Map of the Poor or a Poor Map ?," Policy Research Working Paper Series 9620, The World Bank.
    3. Paul Corral & Kristen Himelein & Kevin McGee & Isabel Molina, 2021. "A Map of the Poor or a Poor Map?," Mathematics, MDPI, vol. 9(21), pages 1-40, November.
    4. Guadarrama, María & Morales, Domingo & Molina, Isabel, 2021. "Time stable empirical best predictors under a unit-level model," Computational Statistics & Data Analysis, Elsevier, vol. 160(C).

    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:ecr:col027:44214. 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: Biblioteca CEPAL (email available below). General contact details of provider: https://edirc.repec.org/data/eclaccl.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.