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 MaterialNon-Material Market Household goods sold at full prices Services sold; insurance, transport,etc Non-Market a.Not sold b.Collective public goods c.Final household consumption of gov g&s Own farm production Emergency supplies Rations, Informal midwives, etc Security, street lighting Health housing & education

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 ExtentIncidenceSeverityLocation 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]. The use of qualitative methods to probe in depth, to identify issues and signal concerns [reducing non-sampling error, improving stratification criteria].