Using non-income measures

While income poverty is an important indicator of social exclusion, it is not the only one. There are various non-monetary and subjective indicators, which should be explored at the cross-sectional level and also longitudinally.

McKenzie, D. J. (2005). Measuring Inequality with Asset Indicators. Journal of Population Economics18(2), 229-260.
Are household infrastructure, building materials and ownership of certain durable assets significant in measuring inequality in living standards? This paper focuses on poverty in Mexico and shows that where there is no information on household income and consumption, asset indicators can be used to provide a reasonable measure of inequalities in living standards. When used in practice, the study found that, after controlling for household income and demographics, school attendance of boys in Mexico is negatively related to state-level inequality.
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Verner, D.  & Alda, E. (2004). Youth At Risk, Social Exclusion and Intergenerational Poverty Dynamics: A New Survey Instrument with Application to Brazil. Washington DC: World Bank.
What risk factors face poor youth in Northeastern Brazil and how are these risks transferred from one generation to the next? This paper documents the results of a survey conducted in the very poorest urban neighbourhoods of Fortaleza. The new survey instrument used covers five areas: i) socio-economic background; ii) education; iii) health and sexuality; iv) social capital and violence; and v) employment and economic activity. The survey results reveal that youth face significant environmental challenges.
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Innovative measuring techniques, such as the socio-economic mapping technique described below, can also help raise public awareness of social exclusion issues.

Camara, G., Monteiro, A. M., Ramos, F. R., Sposati, A., Koga, D. (2004). Mapping Social Exclusion/Inclusion in Developing Countries: Social Dynamics of São Paulo in the 1990s. Centre for Spatially Integrated Social Science.
How can spatial analysis of socio-economic indicators mapped over geographical areas enhance understanding of social exclusion patterns in developing world cities? This paper reviews previous social indicator mapping projects in Sao Paolo and presents methodologies for mapping social exclusion in urban areas. It argues that social scientists and policymakers could benefit from socio-economic mapping techniques, for instance in redrawing Sao Paulo’s administrative zones according to social exclusion indicators.
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For another longitudinal model that integrates multiple dimensions of social exclusion, see the following (based on UK data):

Peruzzi, A. (2014). Understanding Social Exclusion from a Longitudinal Perspective: A Capability-Based Approach. Journal of Human Development and Capabilities, 15(4), 335–354.
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