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As part of UNICEF's continued effort to generate quality evidence on child poverty and disparities, the Multiple Overlapping Deprivation Analysis (MODA) tool has been developed with support from Division of Data, Research and Policy, to enhance the equity focus of child poverty and deprivation analyses around the world.

MODA is a child rights and child centered analytical tool that can be used to identify and quantify child deprivation in order to more precisely target those suffering multiple and overlapping deprivations. A key contributor to the equity policy agenda, this new approach analyses data from Demographic and Health (DHS) and Multiple Indicator Cluster (MICS) surveys and other sources to allow a disaggregated description of child poverty and deprivation.

The Cross-Country MODA initiative analyzes a standard set of deprivation indicators across 40 lower income countries, placing these results in an interactive platform for public analysis. The MODA approach has also been adapted to allow for comparison of living conditions of children across the European Union member states, using harmonized data from the EU-SILC .

In addition, OoR conducts and supports a number of National MODA studies (N-MODA), with the general aim to collect evidence on specific aspects of child poverty and deprivation, tailoring the method to the context of the country. N-MODAs analysis are particularly strategic in view of the SDGs, where this analysis can contribute to construct a child multidimensional poverty measure that is based on local conditions and norms.

As part of UNICEF's continued effort to generate quality evidence on child poverty and disparities, the Multiple Overlapping Deprivation Analysis (MODA) tool has been developed with support from Division of Data, Research and Policy, to enhance the equity focus of child poverty and deprivation analyses around the world.

MODA is a child rights and child centered analytical tool that can be used to identify and quantify child deprivation in order to more precisely target those suffering multiple and overlapping deprivations. A key contributor to the equity policy agenda, this new approach analyses data from Demographic and Health (DHS) and Multiple Indicator Cluster (MICS) surveys and other sources to allow a disaggregated description of child poverty and deprivation.

The Cross-Country MODA initiative analyzes a standard set of deprivation indicators across 40 lower income countries, placing these results in an interactive platform for public analysis. The MODA approach has also been adapted to allow for comparison of living conditions of children across the European Union member states, using harmonized data from the EU-SILC .

In addition, OoR conducts and supports a number of National MODA studies (N-MODA), with the general aim to collect evidence on specific aspects of child poverty and deprivation, tailoring the method to the context of the country. N-MODAs analysis are particularly strategic in view of the SDGs, where this analysis can contribute to construct a child multidimensional poverty measure that is based on local conditions and norms.

LATEST PUBLICATIONS

Based on nationally representative data from the Armenian Integrated Living Conditions Survey 2013/14, the study finds that 64 per cent of children under 18 are deprived in 2 or more dimensions, with a substantially higher rate in rural than in urban areas. The highest rates of deprivation are in access to utilities, quality housing and leisure activities. More than one in four children are both multidimensionally deprived and live in consumption-poor households, while more than one in three are deprived but do not live in poor households.

AUTHOR(S)

Lucia Ferrone; Yekaterina Chzhen
This study provides the first estimates of national multidimensional child deprivation rates in Bosnia and Herzegovina using the National Multiple Overlapping Deprivation Analysis (MODA) pioneered by UNICEF. Amongst the findings of the analysis, it is seen that a reduction in child poverty and deprivation may be achieved by improving both the spending power of households and the availability of services/infrastructure in local areas.

AUTHOR(S)

Yekaterina Chzhen; Lucia Ferrone
This paper brings together the results of multidimensional deprivation analyses for thirty countries in sub-Saharan Africa. As these thirty countries represent 78% of the total population in the region, the paper also tries to shed light on the incidence and depth of child poverty across sub-Saharan Africa as a whole.

CO-AUTHOR(S)

Marlous de Milliano; Ilze Plavgo
This paper investigates child deprivation and its relationship to monetary child poverty in the European Union (EU) using the Multiple Overlapping Deprivation Analysis (MODA) methodology. MODA provides both a conceptual framework and a methodology to estimate the rates of monetary child poverty and multidimensional child deprivation, as well as the overlaps between these measures.

CO-AUTHOR(S)

Yekaterina Chzhen; Chris De Neubourg; Ilze Plavgo; Marlous de Milliano
The Multiple Overlapping Deprivation Analysis for the European Union (EU-MODA) compares the material well-being of children across the EU member states, using data from the child material deprivation module of the European Union Statistics on Income and Living Conditions (EU-SILC) 2009.

AUTHOR(S)

Yekaterina Chzhen; Chris De Neubourg
This technical note refers to a special application of MODA, and applies a multidimensional deprivation analysis to a cross-country setting (CC-MODA). The CC-MODA study gives insights to child deprivation within and across countries, and provides an indication on who the multiply-deprived children are, where they live and what aspects of child well-being they are deprived of. This paper offers an in depth explanation of the technical decisions that have been made to obtain these results.

Chris De Neubourg; Jingqing Chai; Marlous de Milliano; Ilze Plavgo
These guidelines present a detailed step-by-step procedure of how to carry out a multiple overlapping deprivation analysis. They aim at providing technical guidance by capturing lessons acquired from previous research, indicating the range of decisions to be made and the various risks each of the different choices may lead to.

CO-AUTHOR(S)

Chris De Neubourg; Jingqing Chai; Marlous de Milliano; Ilze Plavgo
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