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Background information on the poverty mapping initiative
Recognizing the growing demand for high-resolution poverty data1 and with increased awareness of the possibilities of poverty mapping, the International Food Policy Research Institute (IFPRI) in 1999 developed a proposal soliciting funds to support the creation of poverty maps in Malawi and Mozambique. At the time, IFPRI was already involved in a Danish (DANIDA)-funded project in Malawi focused on providing technical assistance to develop a poverty monitoring system. As part of this project, IFPRI worked jointly with Malawi’s National Statistics Office (NSO), National Economic Council (NEC), and Center for Social Research (CSR) to conduct a poverty analysis of the 1997-1998 Integrated Household Survey (IHS) data. Funds earmarked for poverty mapping were successfully obtained from the Rockefeller Foundation. Development of the poverty map began in earnest in January 2001 and is due for completion in March 2002.
While poverty mapping is new to Malawi, the country did conduct Vulnerability Assessment and Mapping (VAM) in 1996 as part of a USAID-funded Famine Early Warning Systems (FEWS) project. The VAM developed three vulnerability maps.on poverty, food deficiency, and malnutrition.based on a principal components analysis using numerous variables (such as agricultural yields, percentage children enrolled in school, and access to safe water).2 A composite vulnerability map was also developed at an Extension Planning Area (EPA) level (Moriniere, Chimwaza, and Weiss 1996).3 The VAM maps have been used by various agencies, particularly FEWS and the Ministry of Agriculture, to help identify areas in need of food security interventions.
Footnotes:
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There is considerable and growing demand for highly disaggregated poverty data in Malawi, particularly
due to considering the country’s current move toward decentralization. In 1998, the Local Government Act gave new responsibilities to district- and local-level government, ranging from infrastructure planning and development to making and enforcing local- and district-level policy.
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Various data sources were used in this analysis, including the 1991 census, UNICEF data, and NASA’s
Normalized Differentiated Vegetation Index (NDVI) data.
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In addition to principal components analysis, time-series analysis was used for variables for which data
were available (e.g., on agricultural yields) to offer a greater understanding of the temporal patterns of vulnerability.
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