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Poverty Mapping

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  • Collection Overview
  • Methods
    • Global Subnational Poverty Data
    • National-level Poverty Data Sets
    • Indirect Estimation Techniques
    • Small Area Estimates Poverty & Inequality Data Set
    • Poverty and Food Security Country Case Studies
    • Other Indirect Estimation Techniques
    • Combining Surveys with Remote Sensing Data
    • Direct Estimation Techniques
    • Unsatisfied Basic Needs Data Set
  • Data Sets (6)
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  • Poverty Atlas

Poverty and Food Security Case Studies

The basic method used to construct these data sets is the same as those used for consumption-based small area poverty and inequality methods above. Namely, the richness of household surveys is combined with the depth in coverage of censuses to generate food security/welfare estimates for subnational areas in the following countries: Mexico, Ecuador, Kenya, Malawi, Bangladesh, Sri Lanka, and Vietnam. These studies illustrate spatial analysis approaches to poverty and food security assessments examining the impact of environment and geographic location on rural poverty and agricultural development.

For an overview of these cases studies see:

Hyman, G., C. Larrea, and A. Farrow. 2005.  "Methods, Results and Policy Implications of Poverty and Food Security Mapping Assessments." Food Policy.30(5-6): 453–460. [Document]

Papers/documentation of individual country level poverty and food security case studies are available at: http://www.povertymap.net/casestudy/

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