IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v38y2011i10p2327-2343.html
   My bibliography  Save this article

District-level poverty estimation: a proposed method

Author

Listed:
  • Dipankor Coondoo
  • Amita Majumder
  • Somnath Chattopadhyay

Abstract

This paper develops a method of estimating micro-level poverty in cases where data are scarce. The method is applied to estimate district-level poverty using the household level Indian national sample survey data for two states, viz., West Bengal and Madhya Pradesh. The method involves estimation of state-level poverty indices from the data formed by pooling data of all the districts (each time excluding one district) and multiplying this poverty vector with a known weight matrix to obtain the unknown district-level poverty vector. The proposed method is expected to yield reliable estimates at the district level, because the district-level estimate is now based on a much larger sample size obtained by pooling data of several districts. This method can be an alternative to the “small area estimation technique” for estimating poverty at sub-state levels in developing countries.

Suggested Citation

  • Dipankor Coondoo & Amita Majumder & Somnath Chattopadhyay, 2011. "District-level poverty estimation: a proposed method," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(10), pages 2327-2343.
    • Handle: RePEc:taf:japsta:v:38:y:2011:i:10:p:2327-2343
    DOI: 10.1080/02664763.2010.547568
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/02664763.2010.547568
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/02664763.2010.547568?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. Hukum Chandra, 2021. "District-Level Estimates of Poverty Incidence for the State of West Bengal in India: Application of Small Area Estimation Technique Combining NSSO Survey and Census Data," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(2), pages 375-391, June.
    2. Priyanka Anjoy & Hukum Chandra & Pradip Basak, 2019. "Estimation of Disaggregate-Level Poverty Incidence in Odisha Under Area-Level Hierarchical Bayes Small Area Model," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 144(1), pages 251-273, July.

    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:japsta:v:38:y:2011:i:10:p:2327-2343. 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/CJAS20 .

    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.