IDEAS home Printed from https://ideas.repec.org/p/ags/aare09/47651.html
   My bibliography  Save this paper

An Empirical Evaluation of Poverty Mapping Methodology: Explicitly Spatial versus Implicitly Spatial Approach

Author

Listed:
  • Olivia, Susan
  • Gibson, John
  • Smith, Aaron D.
  • Rozelle, Scott
  • Deng, Xiangzheng

Abstract

Poverty maps provide information on the spatial distribution of welfare and can predict poverty levels for small geographic units like counties and townships. Typically regression methods are used to estimate coefficients from the detailed information in household surveys, which are then applied to the more extensive coverage of a census. One problem with standard regression techniques is that they do not take into account the ‗spatial dependencies‘ that often exist in the data. Ignoring spatial autocorrelation in the regression providing the coefficient estimates could lead to misleading predictions of poverty, and estimates of standard errors. Household survey data usually lack exact measures of location so it is not possible to fully account for this spatial autocorrelation. In this paper, we use data from Shaanxi, China with exact measures of distance between each household to explicitly model this spatial autocorrelation. We also investigate which set of augmenting variables (i) census means or (ii) environmental variables mainly from satellite imagery have the most impact in soaking up unwanted spatial autocorrelation.

Suggested Citation

  • Olivia, Susan & Gibson, John & Smith, Aaron D. & Rozelle, Scott & Deng, Xiangzheng, 2009. "An Empirical Evaluation of Poverty Mapping Methodology: Explicitly Spatial versus Implicitly Spatial Approach," 2009 Conference (53rd), February 11-13, 2009, Cairns, Australia 47651, Australian Agricultural and Resource Economics Society.
    • Handle: RePEc:ags:aare09:47651
    as

    Download full text from publisher

    File URL: http://purl.umn.edu/47651
    Download Restriction: no

    References listed on IDEAS

    as
    1. Baulch, Bob & Minot, Nicholas, 2002. "Poverty mapping with aggregate census data," MTID discussion papers 49, International Food Policy Research Institute (IFPRI).
    2. John Gibson & David McKenzie, 2007. "Using Global Positioning Systems in Household Surveys for Better Economics and Better Policy," World Bank Research Observer, World Bank Group, vol. 22(2), pages 217-241, September.
    3. Tara Bedi & Aline Coudouel & Kenneth Simler, 2007. "More Than a Pretty Picture : Using Poverty Maps to Design Better Policies and Interventions," World Bank Publications, The World Bank, number 6800, June.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Tauisi Taupo & Harold Cuffe & Ilan Noy, 2016. "Household Vulnerability on the Frontline of Climate Change: The Pacific Atoll Nation of Tuvalu," CESifo Working Paper Series 6128, CESifo Group Munich.

    More about this item

    Keywords

    China; Poverty; Small Area Estimation; Survey Methods; Spatial Models;

    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:ags:aare09:47651. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (AgEcon Search). General contact details of provider: http://edirc.repec.org/data/aaresea.html .

    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.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.