Multidimensional Poverty in the Voluntary National Reviews

In 2016, 2017, 2018 and 2019 many countries reported progress on multidimensional poverty reduction in their Voluntary National Reviews (VNR) presented to the UN. Below we highlight excerpts of these documents and link to the full reports for reference.

Bangladesh (2017) writes of plans “for introducing a Multidimensional Poverty Index (MPI) measurement in future” (page 13).

Belize (2017) writes that “the enhanced methodology due to be employed in the Caribbean Development Bank (COB) sponsored country poverty assessment will allow Belize to measure poverty using a national multidimensional definition, which is currently being finalised after a draft was developed as part of the Comprehensive Review of the Social Protection System in Belize conducted last year. This follows the methodology of the Oxford Poverty and Human Development Initiative (OPHI) (page 20).

Bhutan (2018) mentioned its national MPI and the Child MPI as tools to help eradicate poverty (SDG1): “While multidimensional poverty has reduced significantly rural poverty is much higher than urban poverty: 8.1 per cent compared to 1.2 per cent and children between 0-9 years of age are found to be poorest age group in Bhutan” (page 28).

Chile (2017) shared that their national MPI identifies 20.9% of the population as poor. Chile’s MPI is disaggregated by subnational regions, rural-urban, gender, age cohort, indigenous status. And policy reflects not just the level but also the composition of poverty in terms of education, health, work, housing and environment, and social networks.  In Chile’s consultations preparing for the VNR, they found that one of the most relevant challenges was Poverty in all its dimensions – monetary, and multidimensional.

Colombia (2016) confirmed poverty reduction in the country is experienced in all its dimensions. Non-monetary reductions were tracked and accelerated using a multidimensional measure that implemented the Alkire-Foster method. In 2010, 30.4% of the population were MPI poor where as in 2015 it was 20.2%. Colombia’s MPI is disaggregated by gender, age, urban/rural, and regions.

Costa Rica  (2017) also uses the MPI based on Alkire-Foster method, since it sees the challenge of Poverty reduction should be approached in a multidimensional form, as it is national strategy outlines. Since October 2015, Costa Rica has used its MPI to coordinate policies and implement novel initiatives – especially those that address traditionally excluded populations like those with disability, indigenous persons, women, and migrants.

Dominican Republic (2018) indicates in its VNR that the government, with the United Nations System support, identified five policy areas (accelerators) that would help to speed up the achievement of the SDGs, one of them is multidimensional poverty reduction.

Ecuador (2018). Its NVR described the multidimensional poverty index as part of its strategy for the ODS1.

Egypt (2016) drew attention to its reduction of the global MPI published by UNDP and Oxford University, which is a recommended indicator for SDG Target 1.2

El Salvador (2019) uses a National MPI as an official measure of poverty to track SDG indicator 1.2.2.

Guatemala (2017) uses the Global MPI as measure of poverty to track SDG indicator 1.2.2 as a provisional basis. Nowadays, Guatemala is in the first phase of a national MPI construction process, which would imply to estimate this index in an official way at country level for the first time, in order to complement the income poverty measure.

Honduras (2017) uses a national MPI as an official measure of poverty to track SDG1. It observed that its MPI helps it to advance not only in SDG1 but also in other SDGs such as food security (SDG2), Education (SDG4), Water and sanitation (SDG6) and others.

India (2017) made a significant move towards addressing multidimensional poverty by using a multidimensional targeting approach, in order to leave no one behind.

Indonesia  (2017) flagged multidimensional Poverty as an ‘emerging issue’ that is related to education, health, living standards. Indonesia is working “to ascertain multidimensional poverty in order to improve poverty alleviation programs to be effective in identifying the roots causes of poverty, which are different in each region.” (page 19 and 20)

Jamaica (2019) indicates that “A critical next step for Jamaica is the development of a tailored multidimensional poverty index for the country. The approach being considered departs from the conventional, as it seeks to engage community participation in determining the indicators most relevant to the country” (page 25).

Jordan (2015) described that it is developing “a multi-dimensional poverty index specific to Jordan (still in progress), based on the right to a decent and dignified life as opposed to the fulfilment of basic-needs approach” (page 40).

Mexico (2018) described the poverty situation of Mexican people. 

Nepal  (2017) stated: “Multi-dimensional poverty reduced from 64.7 percent in 2006 to 44.2 percent in 2015 (OPHI 2016) dropping by an average of two percentage points per year. These achievements were largely due to improved health and education and increased remittances incomes.” …  “The government aims to bring down the percentage of people living below the poverty line to 4.9 percent and to reduce multi-dimensional poverty to 10 percent by 2030. The NPC has set targets of an annual economic growth rate of 7.2 percent and 4.7 percent annual growth in the agriculture sector during the Fourteenth Plan period (2016/17- 2018/19) and to increase per capita gross national incomes to $2,500 by 2030”.

Panama (2017) extensively described its official MPI as one of the principle instruments to progressively improve public policies. For example, its main messages were: “The multidimensional poverty index was established as a principal instrument for shaping public policy. To that end, dimensions and indicators were selected, the disadvantages and gaps characterising poverty were defined, deprivation was quantified, and poverty was defined in multidimensional terms”.

Philippines (2016) indicated an intention to conduct studies on MPI. The country launched its national MPI in December 2018.

Rwanda (2019) reports the MPI to inform the SDG1.2.2. (page 79).

Sierra Leone (2016), which is reporting MPI as an SDG indicator, indicated an intention to measure multidimensional Poverty, explaining that during its public, regional, and national engagements, one key point that emerged was the “relevance of a multidimensional approach to poverty measurement for the success of the SDGs” (page 10).

Sri Lanka (2019) indicates that “Multidimensional poverty Index also recorded poverty levels lower than those estimated based on the national (income) poverty line. The multi- dimensional poverty level at the aggregate level was 3.8% in 2012/1343 (compared to 6.7% based on the national poverty line), while that for males and females were 3.9% and 3.7% respectively44 (Target 1.2)” (page 66).

Tajikistan (2017) reported the incidence of MPI in its country, with urban and rural disaggregations. Its strategy to address the urgent issue of Poverty is multidimensional and includes “addressing food security, food quality and safety, energy security, water sector issues, climate change, other SDGs, affecting the standard of living and well-being of the population” (page 9).

Tonga (2019) “has developed a robust multidimensional poverty measure which is scientifically valid, reliable, additive and contextually appropriate. It has been adopted as the national poverty measure, and is the first of its kind in the Pacific. This is important because recent research has suggested that income poverty measures can underestimate the true extent of poverty. Therefore, effective poverty reduction policies require measures that go beyond income and appropriately reflect the hardship and life experiences of the poor and disadvantaged groups.

In the spirit of the 2030 Development Agenda, this measure identifies the ‘proportion of men, women and children of all ages living in poverty in all its dimensions according to national definition’. While the impact on an adult falling into poverty temporarily may be felt immediately, for children the effects can last a lifetime as children need access to education and healthcare to gain the best start in life. Child poverty costs society in terms of missed opportunities and wasted potential. This measurement is a new development for Tonga as child poverty is no longer lumped together with general poverty assessments which often focus solely on income levels, and do not consider basic necessities. The measure allows Tonga to fully understand child poverty.

Using this measure, it is estimated that 27% of the population are poor. Furthermore, 14% of the population is estimated to be vulnerable as a result of deprivation, and 22% vulnerable in terms of income measures. Child and adult poverty rates indicate that one in five adults are poor compared to one in three children” (pages 29-30).

Vietnam (2018). In the report, Vietnam indicated: “The multidimensional poverty rate was reduced from 9.2 percent in 2016 to less than 7 percent in 2017. However, based on multidimensional poverty criteria, the poverty rate for ethnic minority groups remains relatively high. Social security policies have been implemented nationwide and achieved positive results. By the end of December 2017, more than 13.9 million people had social insurance; by the end of 2015, 100 per-cent of the poor and social protection beneficiaries were provided free insurance cards, and about 81 per-cent of near-poor people had health insurance. The access to basic social services such as electricity, hygienic water has been on a rising trend. Monthly social support is now provided for the social protection beneficiaries in almost 60 provinces/cities.” (page 14).

Zimbabwe (2019) reports that “Zimbabwe’s multidimensional poverty index (MPI) declined from 0.172 in 2011 to 0.127 in 2014, and the percentage of people who are MPI poor declined significantly from 39.1 per cent in 2011 to 29.7 per cent in 2014.” (page 6). “The MPI is a recommended indicator for SDG Target 1.2 that seeks to ‘reduce at least half the proportion of men, women and children of all ages living in poverty in all its dimensions’ by 2030. These positive developments show Zimbabwe’s progress in tackling extreme poverty and deprivation of its vulnerable populations” (page 18).