Click here for search results
The use of random geographic cluster sampling to survey pastoralists, Volume 1
Author:Himelein, Kristen; Eckman, Stephanie; Murray, Siobhan; Country:Ethiopia; Africa;
Date Stored:2013/09/04Document Date:2013/09/01
Document Type:Policy Research Working PaperSubTopics:Wildlife Resources; Scientific Research & Science Parks; Livestock and Animal Husbandry; Science Education; Rural Development Knowledge & Information Systems
Language:EnglishMajor Sector:Education; Agriculture, fishing, and forestry; Health and other social services; Transportation
Rel. Proj ID:3A-Lsms Integrated Surveys On Agriculture -- -- P114487;Region:Africa
Report Number:WPS6589Sub Sectors:Health; General agriculture, fishing and forestry sector; General education sector; General transportation sector
Collection Title:Policy Research working paper ; no. WPS 6589TF No/Name:TF098893-KCP II - Measuring Development Indicators for Pastoralists Populations; TF098007-Improved Measurement of Welfare in Niger; TF014269-Improving the Quality and Policy Relevance of Household-level Data on-1; TF013481-Financial Capability Project; TF093624-Improving the quality and policy relevance of household-level data on a
Volume No:1  

Summary: Livestock are an important component of rural livelihoods in developing countries, but data about this source of income and wealth are difficult to collect because of the nomadic and semi-nomadic nature of many pastoralist populations. Most household surveys exclude those without permanent dwellings, leading to undercoverage. This study explores the use of a random geographic cluster sample as an alternative to the household-based sample. In this design, points are randomly selected and all eligible respondents found inside circles drawn around the selected points are interviewed. This approach should eliminate undercoverage of mobile populations. The results of a random geographic cluster sample survey are presented with a total sample size of 784 households to measure livestock ownership in the Afar region of Ethiopia in 2012. The paper explores the data quality of the random geographic cluster sample relative to a recent household survey and discusses the implementation challenges.

Official Documents
Official, scanned versions of documents (may include signatures, etc.)
File TypeDescriptionFile Size (mb)
PDF 25 pagesOfficial version*1.75 (approx.)
TextText version**
How To Order

See documents related to this project
* The official version is derived from scanning the final, paper copy of the document and is the official,
archived version including all signatures, charts, etc.
** The text version is the OCR text of the final scanned version and is not an accurate representation of the final text.
It is provided solely to benefit users with slow connectivity.

Permanent URL for this page: