There are hundreds of millions of people across the world who, every day, face severe poverty and hardships. To help them, we need to know who they are, where they are and, also, what causes them to be poor.

The blog has been written by the UNDP Rwanda Resident Representative, Mr. Stephen Rodriques

For decades, the global community has been looking at income – counting the number of

people who earn less than US$1.90 per day – to determine who is poor. Although income is a good measure, it does not tell the full story of whether people have enough to eat, can attend school, have proper health care, and so on.

In 2010 UNDP and the Oxford Poverty and Human Development Initiative (OPHI) combined efforts globally to create and introduce the Multidimensional Poverty Index (MPI) to complement the monetary or income-based measurement of poverty.

The aim was to assist countries to better understand the multiple faces of poverty, and the reasons people are poor and remain poor even when incomes rise. Since then, UNDP has published the MPI annually, covering over 105 countries.

The global MPI has three dimensions - education, health and standard of living. It uses 10 robust indicators covering these dimensions to analyse whether people are poor only in income terms alone or also poor in other dimensions, and in how many of these dimensions they are poor.

For example, it tells us whether the poor have access to proper education, to good health care, and to a decent standard of living and whether people have access to one, two or all three of these dimensions. People who are poor in more than one dimension are referred to as being multidimensionally poor.

From the 2018 global MPI,  we found that over 1.3 billion people live in multidimensional poverty and that 83% of these people live in Sub-Saharan Africa and South Asia. Furthermore, 85% of the poor live in rural areas, and half are children and youth aged 0-17 with nutrition being the largest contributor to their poverty.

The trend on multidimensional poverty in Africa is encouraging - it has declined in 30 out of 35 countries over the last two decades, with Rwanda being among the top performers in reducing multidimensional poverty over this period.

Poverty often takes different forms across Africa; for example, East African countries have greater deprivations in living standards such as inadequate cooking fuel, electricity, flooring, and sanitation, while in West Africa child mortality and poor educational performance are significant challenges.

This kind of data can help policy makers across the region design more effective policies and programmes to address their specific challenges.

Earlier this year, UNDP Rwanda was very pleased to join with UNICEF Rwanda and the National Institute of Statistics Rwanda (NISR) to develop and publish Rwanda’s national Multidimensional Poverty report and the Multiple Overlapping Deprivation Analysis (MODA) of Child Poverty report.

Rwanda is the first East African country to develop these national measures and the third in Africa, following Mozambique and Nigeria. These tools are extremely important if Rwanda is to achieve its national goal to eradicate poverty in all its forms.

Using the national MPI, multidimensional poverty declined from 32.9% in 2013/14 to 28.9% in 2016/17. In the same period, income poverty using the national poverty line only declined from 39.5% to 38.5%, which is minimal. It is also notable that close to 18.4% of the population is both income and multidimensionally poor.

While Rwanda has now joined the select group of countries using this measure, this is a first step. Experience of other countries suggest that the real benefit of MPI is when it is used as a tool to inform and shape responses by national and subnational governments to eradicate poverty.

The MPI is useful in at least 4 critical ways. First, it can help improve targeting of the poorest groups in a country. Second, the MPI can help to enhance monitoring and accountability of national development plans.

Third, the MPI can also be used by countries to effectively address geographical disparities through budget allocations – that is, by identifying regions which are the poorest and using the MPI data to inform how much resources are transferred to those regions.

Last, but not least, the MPI can help to enhance policy coordination by revealing the interconnections between deprivations and encouraging multisectoral and integrated responses. Several developing nations, such as Mexico, China, Vietnam, and Senegal have successfully used one or more of these above strategies to both identify and alleviate poverty.

There are more lessons to be learned, including from MPI pioneers such as Colombia and Mexico. One lesson, from the case of Colombia, is that the MPI yields maximum results when it is institutionalised and is championed by the highest levels of government.

When the National Development Plan to reduce poverty was introduced in 2011, the MPI was used to establish a Poverty and Inequality Round Table – a committee involving executive branches of the government responsible for addressing and monitoring poverty reduction.

The MPI helped create accountability and transparency in the national implementation process and also led to the design of national programmes to support the plan, such as the Families in Action Plus- covering over 13 million people with conditional cash transfers, accompanied by safety net initiatives covering over 7 million people.

A second lesson comes from Mexico, which adopted the MPI in 2009. The MPI was used to hold cabinet ministers accountable for the results in all the dimensions related to their portfolios. Accordingly, the MPI became an integral part of the policy cycle, affecting government programme design, implementation and monitoring, as well as public expenditure allocation.

As a result, two major social security programmes were created: the “National Crusade Against Hunger” (CNCH), targeting over 7 million people, and the “Pension Programme for the Elderly” (PPE), guaranteeing a minimum income for all Mexicans above 65 years.

In conclusion, while the experiences of these countries are encouraging, it is unfortunate that only few countries in Africa are using the MPI and MODA to guide policy or programming. I believe there is an opportunity for Rwanda to once again be a pioneer in demonstrating the effective use of these measures in combatting poverty and inequality.

I commend the Government of Rwanda for taking the initial decisive step to adopt the MPI and MODA.