Tackling Child Poverty: A Holistic Approach on Measurement and Programme Design

As part of the Sustainable Development Goals (SDGs), countries have committed to eradicate extreme child poverty and cut in half the number of children living in poverty. Nonetheless, the economic downturn since these pledges were made, alongside soaring prices of essential commodities and the escalating climate crisis, have exacerbated household financial strains and overall well-being, disproportionately impacting children.

Amidst this global challenge, it is crucial to comprehensively understand various facets of child vulnerability to inform the design and implementation of effective policies. However, there is a live debate on which methodological approaches can best support this, addressing the multidimensional nature of child poverty and deprivation. Similarly, integrating child poverty considerations into social policy has the potential to both directly reduce vulnerability and enhance the benefits of existing programming.

To guide countries through this complex array of monitoring methodologies and enable the evidence-based design of child benefit programmes, the Development Analytics team has established partnerships with multilateral agencies, including multiple UNICEF offices, to support child poverty reduction efforts. We are at the forefront of crafting and executing methodological approaches to measure monetary and multidimensional child poverty, alongside providing specialized insights for designing relevant child benefit policy and programme framework.

Our team possesses the data and tools to measure child poverty across diverse national contexts. Rather than solely employing a singular approach to measure child poverty, we are able to utilize varied methodologies based on requirements in the country context, in order to measure both monetary and multidimensional child poverty. Examining child poverty from various perspectives allows us to identify which children are more susceptible to living in vulnerability under different criteria, considering their unique needs and characteristics. This comprehensive understanding empowers us to design child benefit programs that take a holistic approach, effectively defining and targeting the most vulnerable children.

Our Approach

We cover all major methodologies utilized in both monetary poverty and multidimensional poverty analysis. Our team has built significant expertise and experience in the technical and analytic skills needed for each of these approaches. Because of this, we can leverage and draw on the full range of available options for measuring child poverty, uniquely equipping us to identify the most appropriate and insightful approaches to examine the various dimensions of child poverty within diverse national contexts.

By employing various measurement approaches, we can capture different aspects of poverty that may be missed by relying solely on one method. For instance, while one method might focus on expenditure-based indicators, another might consider factors like access to education, healthcare, and basic amenities. By having expertise in multiple methodologies, we can tailor our analysis to suit the specific needs and characteristics of different communities and regions. Our team has considerable expertise in employing diverse approaches to measure child poverty, emphasizing:

Monetary child poverty assessment: Various methods are employed for poverty analysis in the literature, with monetary poverty being the most commonly utilized. This method is based on income or expenditures and assumes that individuals/households can satisfy their basic needs with a certain level of purchasing power determined through a monetary threshold.

The Multiple Overlapping Deprivations Analysis (MODA), initially developed through collaboration between the UNICEF Office of Research and the UNICEF Social Inclusion Unit of the Programme Division⁴: This approach aims to provide an approach on measuring child well-being with a particular focus on the access to various goods and services. MODA also focuses on children as the unit of analysis, offers a life-cycle approach to analyse children at different age groups and provides insights into the various levels of child deprivation.

The Multidimensional Poverty Index (MPI), developed by the Oxford Poverty and Human Development Initiative: This methodology also focuses on overlapping deprivation affecting people in poverty and aims to identify the poor through measuring the breadth, depth and severity of multidimensional poverty. The MPI is built with a selection of indicators chosen to reflect important characteristics of the lived experience of poor people, often categorized into areas such as health, education, living standards, and work.

Acknowledging the diversity of perspectives on measuring and comprehending child poverty, Development Analytics offers invaluable support in leveraging various methodologies. By doing so, it facilitates a nuanced understanding of the multifaceted nature of child poverty, thereby assisting in the formulation of targeted interventions and policies to empower vulnerable children across different country contexts.

In this capacity, our team utilizes various approaches developed in the literature as foundational information to design and simulate child benefit programmes that effectively tackle child poverty. Recognizing the role of programme staff and donors in understanding child poverty and crafting child benefit programs, we have developed The Interactive Social Policy Simulator (ISPS). This innovative tool allows program implementers to directly engage with data, observe the impacts of various targeting scenarios, and refine their decisions accordingly. This platform empowers partnering agencies, donors and governments to interact with data and simulate diverse policy scenarios aimed at addressing child poverty.

Case Studies

Development Analytics has led studies measuring monetary and multidimensional child poverty also with an applied approach on designing child benefit programmes in Azerbaijan, Georgia, Madagascar, Moldova, Nigeria, St. Lucia and Türkiye.

Assessment of Potential Impact of Different Social Protection Measures on Child Deprivation and Poverty in Georgia.

A considerable portion of children in Georgia grapple with monetary poverty. In 2022, while the overall poverty rate for the population stood at 15.6%, the child poverty rate was notably higher, reaching 20.4%. Material deprivation also remains a pressing concern among Georgian children, with 37.8% lacking at least 3 out of 16 essential items.

Given this background, our expert team designed an approach to analyse the potential effects of different social protection interventions (such as cash transfers) in Georgia on child poverty as well as material deprivation, while also estimating the cost implications of the interventions. To accomplish this, microsimulation models were constructed by utilizing nationally representative surveys.

Through this collaboration, we supported UNICEF Georgia to incorporate both monetary and multidimensional approaches in measuring child poverty in Georgia. We enhanced this analytical component with a holistic and applied approach to designing child benefit interventions and estimated the cost implications of interventions with a focus on empowering policymakers in their endeavour to efficiently design at-scale social policy programs in the country.

Developing a Shock Responsive Social Protection Model for Children in Türkiye in the Aftermath of the Earthquakes using the Interactive Social Policy Simulator (ISPS).

As a response to the recent major earthquakes on February 6, 2023, affecting 11 provinces and a population of 14 million people, UNICEF Türkiye planned to design and implement a cash transfer program with a budget of at least $40 million as part of the United Nations Flash Appeal and UNICEF Humanitarian Action for Children Appeal.

In this capacity, our team estimated the potential impact of the earthquakes on household poverty and child poverty and then designed and analysed the poverty-alleviating impacts of various cash transfer scenarios. An interactive social policy simulator (ISPS) was also designed to allow UNICEF to see the results of cash transfer scenarios interactively by choosing from various targeting and transfer level options.

The study's initial outputs were used to develop a business case that demonstrates the added value and models of cash transfer programs in the short term and will assist technical preparations and advocacy of UNICEF vis-a-vis the government, donors, and International Financial Institutions (IFIs) in the medium term.

Multidimensional Child Poverty Measurement in Nigeria.

Nigeria is Africa’s largest economy with a nominal GDP of around US$440 billion (World Bank, 2021) and the largest population of over 213 million in 2021.⁷ However, almost half of the population lives below the international poverty line, and child poverty is particularly high in the country.⁸

Considering the multifaceted challenges that Nigerian children face in the country, this study examined the extent and depth of multidimensional child poverty using the MODA (Multiple Overlapping Deprivation Analysis) approach. The study tailored the approach to Nigeria, designing nationally-relevant dimensions and indicators of child deprivation in consultation with experts from UNICEF Nigeria.

By analysing these contextually-tailored dimensions of child deprivation, our team provided valuable insights for policymakers and practitioners looking to address the issue of child poverty in Nigeria. The empirical evidence shed light on the multidimensional nature of child poverty in the country, serving as an important step to inform the design and implementation of effective policies and programs aimed at reducing child poverty and promoting the well-being of children.

If you would like to get in touch with us and discuss the details of carrying out such a study in your country, please click to arrange a meeting with our technical team.

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Key Sources

¹ UNICEF (2023). Key Asks 2023 Voluntary National Reviews: SDG 1. Retrieved from: https://www.unicef.org/documents/sdg-issue-brief-1 [Access date: 10 March 2024].
² Roelen, K., Gassman, F., & de Neubourg, C. (2011). False positives or hidden dimensions: what can monetary and multidimensional tell us about child poverty in Vietnam?. International Journal of Social Welfare, 21 (4), 393-407. https://doi.org/10.1111/j.1468-2397.2011.00836.x
³ Thorbecke E (2008). Multidimensional Poverty: Conceptual and Measurement Issues. The Many Dimensions of Poverty. In: Kakwani N, Silber J, eds. The Many Dimensions of Poverty, pp. 3–19. New York, Palgrave Macmillan.
⁴ de Neubourg, C., Chai, J., de Milliano, M., Plavgo, I. and Wei, Z. (2012). Step-by-step Guidelines to the Multiple Overlapping Deprivation Analysis (MODA), Innocenti Working Paper 2012-10, UNICEF Office of Research, Florence.
⁵ Alkire, S. and Foster, J. (2011). ’Counting and Multidimensional Poverty Measurement‘, Journal of Public Economics, 95, 476–487.
⁶ Ibid.
⁷ United Nations Population Division. World Population Prospects: 2022 Revision. (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics
⁸ World Bank statistics (2019) cited by NBS Nigeria (2022). Nigeria Multidimensional Poverty Index (2022), National Bureau of Statistics of the Federal Republic of Nigeria, FCT Abuja.

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