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Poverty in Malawi, 1998

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  • Todd Benson
  • Charles Machinjili
  • Lawrence Kachikopa

Abstract

A description of the poverty analysis of the 1997/8 Malawi Integrated Household Survey is presented. Basic needs poverty lines were developed and used with consumption-based measures of welfare to classify households and individuals as poor or non-poor. As the quality of the consumption data was not uniform across survey sample households, adjustments were made in the analysis to derive a more accurate assessment of the prevalence of poverty across the country. Poverty and inequality estimates for the population of Malawi are made. About 65 per cent of Malawi's population are unable to meet their basic needs. Poverty in Malawi is deep and pervasive. Within the context of the Malawi Poverty Reduction Strategy, the distribution of household welfare is examined more closely to guide government action to assist poor households in improving their own well-being.

Suggested Citation

  • Todd Benson & Charles Machinjili & Lawrence Kachikopa, 2004. "Poverty in Malawi, 1998," Development Southern Africa, Taylor & Francis Journals, vol. 21(3), pages 419-441.
    • Handle: RePEc:taf:deveza:v:21:y:2004:i:3:p:419-441
    DOI: 10.1080/0376835042000265423
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    1. Foster, James & Greer, Joel & Thorbecke, Erik, 1984. "A Class of Decomposable Poverty Measures," Econometrica, Econometric Society, vol. 52(3), pages 761-766, May.
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    3. Haddad, Lawrence James & Adato, Michelle, 2001. "How effectively do public works programs transfer benefits to the poor?," FCND briefs 108, International Food Policy Research Institute (IFPRI).
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    Cited by:

    1. Benson, Todd, 2006. "Insights from poverty maps for development and food relief program targeting: an application to Malawi," FCND briefs 205, International Food Policy Research Institute (IFPRI).
    2. Kenneth R. Simler & Channing Arndt, 2007. "Poverty Comparisons With Absolute Poverty Lines Estimated From Survey Data," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 53(2), pages 275-294, June.
    3. Deluna, Roperto Jr, 2011. "Factors Affecting the Magnitude of Poor Families Across the Philippines: A Cross Section Data Analysis," MPRA Paper 36606, University Library of Munich, Germany.
    4. Mogues, Tewodaj & Petracco, Carly & Randriamamonjy, Josee, 2011. "The wealth and gender distribution of rural services in Ethiopia: A public expenditure benefit incidence analysis," IFPRI discussion papers 1057, International Food Policy Research Institute (IFPRI).
    5. Kraybill, David S. & Bashaasha, Bernard, 2005. "Regression-Based Simulation of Anti- Poverty Policies in Uganda," 2005 Annual meeting, July 24-27, Providence, RI 19203, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    6. Kraybill, David S. & Bashaasha, Bernard, 2004. "Explaining Poverty in Uganda: Evidence from the Uganda National Household Survey," 2004 Inaugural Symposium, December 6-8, 2004, Nairobi, Kenya 9537, African Association of Agricultural Economists (AAAE).
    7. L. Cuna, 2004. "Assessing Household Vulnerability to Employment Shocks: A Simulation Methodology Applied to Bosnia and Herzegovina," Working Papers 528, Dipartimento Scienze Economiche, Universita' di Bologna.

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