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Enhancing Poverty Analysis: Diverse Data Sources for a Multidimensional Perspective

Understanding the complex nature of poverty requires an array of data sources that capture its multiple dimensions. The MDGs highlight the necessity of diverse information to reveal various facets of poverty, from access and exclusion to the tangible and intangible aspects of living conditions. By utilizing censuses, community studies, qualitative surveys, and other methodologies, we can better comprehend poverty's extent, incidence, severity, and characteristics. This multifaceted approach ensures a more comprehensive analysis, supporting the development of effective solutions for the poor.

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Enhancing Poverty Analysis: Diverse Data Sources for a Multidimensional Perspective

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  1. Capturing the Multidimensionality of Poverty Alternative and Complementary Sources of Poverty related Data

  2. The MDG Imperative • The MDGs, in focusing on the multiple dimensions of development, emphasize the need to draw on a wide range of data sources to reveal different facets of poverty and to cross-check on findings • These sources can generate information on the tangible and non-tangible aspects of living levels and the strength and importance of various ‘sentiments’ and conditions

  3. Coverage of Items

  4. Aspects • Issues above ignore questions of ‘access’ and ‘exclusion’ and role of civil society • In handling questions of ‘who’, ‘how many’, ‘how much’, ‘where found’ and ‘what people do’ who are poor, we need to know at least the • Extent • Incidence • Severity • Location • Characteristics of poverty

  5. Types of Data Sources • Censuses and sample censuses – population, housing, agriculture, etc • Ministerial Records • Civil registration • Official commissions of Enquiry • Community Level Studies by NGOs • Qualitative Surveys

  6. Non Formal Approaches • Key informants • Focus groups • Interpreters and independent observers • Opinion surveys • Market surveys • Sensory studies • Rapid rural appraisals • Social weather stations [perceptions and their ‘strength’] • Self assessments • Miscellaneous indicators

  7. ‘Mapping’ • The CWIQ as a filter and CWIQ Plus • LSMS Community Surveys • SDA priority surveys • Triangulation [attenuation?] techniques The use of qualitative methods to probe in depth, to identify issues and signal concerns [reducing non-sampling error, improving stratification criteria].

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