Social exclusion

Quantifying social exclusion

Gathering and analysing statistical information relating to social exclusion can help to identify which groups are excluded, identify the forms and levels of exclusion they face, and quantify the impact of exclusion. Disaggregated data allows progress to be monitored and change relating to specific groups to be tracked over time. Statistical information can also draw attention to exclusion, strengthening influencing strategies and creating leverage. Raising the profile and visibility of excluded groups can be a powerful act in itself.

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Where is a good place to start?

Carraro, L., 2005, ‘A Quantitative Assessment of Social Exclusion in Pakistan’, Oxford Policy Management, London
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Identifying, mapping and measuring social exclusion

Some forms of social exclusion are relatively easy to measure, while others are quite difficult. Many forms of social exclusion are represented by clear divisions between groups, but multiple identities can blur group boundaries, and some excluded groups can be ‘invisible’. For example, it can be difficult to collect information on mobile populations, and some sensitive information such as HIV status can be difficult to collect using traditional methods such as surveys. This has implications for how data are collected and reported.

Gacitua-Mario, E., and Woden, Q., 2001, ‘Measurement and Meaning: Combining Quantitative and Qualitative Methods for the Analysis of Poverty and Social Exclusion in Latin America’ World Bank, Washington
What policy implications do integrated poverty analyses, incorporating quantitative and qualitative methods, present to decision-makers in Latin America? This paper from the World Bank examines three case studies, from Argentina, Chile and Uruguay, to survey the recommendations produced by research combining quantitative and qualitative approaches. It argues that governments need to improve service provision to marginal communities by expanding public information campaigns and developing their collection of data on poverty in these areas.
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Stewart, F., Brown, G., and Mancini, L., 2005, ‘Why Horizontal Inequalities Matter: Some Implications for Measurement’, CRISE, Queen Elizabeth House, Oxford
Why do inequalities between groups matter as well as inequalities between individuals? What is the best way to measure such horizontal inequalities? This paper for the Centre of Research on Inequality, Human Security, and Ethnicity (CRISE) argues that horizontal inequalities (HI) matter for the well being of individuals within groups, and for their impact on wider growth and conflict.
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McKay, A., 2002, ‘Defining and Measuring Inequality’, Briefing Paper 1, Overseas Development Institute, London
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Bennett, L., 2005, ‘Gender, Caste and Ethnic Exclusion in Nepal’, World Bank, Washington
Gender, caste and ethnicity-based social exclusion is deeply embedded in Nepalese society. This draft paper, presented at the World Bank Conference on New Frontiers in Social Policy, examines the joint policy reform initiative of the World Bank and DFID to address the persistent legacy of caste, ethnic and gender-based exclusion in Nepal. In order to move from policy-level analysis to active implementation, policy reform should not be viewed as a technocratic act, but rather as part of a wider process of social, cultural and institutional change.
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Camara, G. et al, 2001, ‘Mapping Social Exclusion/ Inclusion in Developing Countries: Social Dynamics of Sao Paulo in the 1990s’, National Institute for Space Research, Brazil
How can spatial analysis of socio-economic indicators mapped over geographical areas enhance understanding of social exclusion patterns in developing world cities? This draft paper from the National Institute for Space Research, Brazil 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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Monitoring social exclusion

Masset, E., and White, H., 2004, ‘Are Chronically Poor People Being Left Out of Progress Towards the Millennium Development Goals? A Quantitative Analysis of Older People, Disabled People and Orphans’ in Journal for Human Development Volume 5, no. 2
The Millennium Development Goals (MDGs) set ambitious targets for poverty reduction, however, there is a dearth of analysis on how specific groups are faring with respect to these goals. This article, from the Journal of Human Development, aims to close this gap by illustrating that the progress made by three relatively disadvantaged groups – orphans, people with disabilities and older people – is lower than among the general population. Targeted interventions are required to ensure that chronically poor people are not excluded from progress towards the MDGs.
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DFID Nepal, in partnership with others, including the Government of Nepal, the World Bank, ADB, and UNDP, helped to form the Social Inclusion Action Group (SIAG) in Nepal. SIAG is a multi-stakeholder forum for discussing and taking forward a harmonised approach to monitoring social inclusion. Livelihoods and Social Inclusion (LSI) Monitoring is one of the three pillars of DFID-Nepal’s Country Assistance Plan (CAP) reporting system.

Nepal’s Country Assistance Plan includes guidelines for LSI monitoring:

Department for International Development, 2005, ‘Nepal Country Assistance Plan: Monitoring in a Fragile State’, Department for International Development, London
The DFID Nepal Country Assistance Plan (CAP), published in February 2004, aims to reduce poverty and social exclusion and help establish the basis for lasting peace. To this end, CAP commits DFID Nepal to developing improved, locally accountable and transparent systems for monitoring progress. This DFID paper describes the main elements of the CAP Monitoring Framework (CAPMF), setting out how DFID Nepal (DFIDN) proposes to monitor the operating environment for development activities and measure progress towards outputs.
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Additional information resources

The Minorities at Risk Dataset
This is a project run by the University of Maryland which tracks politically active ethnic groups on political, economic and cultural dimensions. 

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