Highlights of Voluntary National Reviews since 2015

From 2016 many countries have reported progress towards multidimensional poverty reduction under Target 1.2 of the Sustainable Development Goals in their Voluntary National Reviews (VNRs). VNRs are presented to the UN during the High-Level Political Forum which takes place annually in July.

Full list of countries who have presented their VNRs.

Below we highlight excerpts of these documents and link to the full reports for reference. The current list is compiled from 2016-2020. 

Armenia (2020) “The assessment of multidimensional poverty complements the analysis on monetary poverty. The share of multi-dimensionally poor population, that is, the share deprived in at least one dimension, in 2018 was 23.6%, with most deprivations visible in housing and labor (Armstat 2019). 61.6 percent of children are deprived in two or more dimensions. The number was as high as 74.9 percent in rural areas, while it is 52 percent in urban settings. Children are mostly deprived in utilities, housing, and leisure.” (page 13)

Bangladesh (2020) provides details of the Bangladesh Multidimensional Poverty Index (MPI) “Bangladesh has constructed Multidimensional Poverty Index (MPI) to measure the deprivation of the population in three dimensions, viz. health, education, and living standard. Information from Table 1.5 reveals that the incidence of multidimensional poverty in Bangladesh is 37.5 per cent. On the other hand, the average intensity of poverty, which reflects the share of deprivations each poor person experiences on average, is 46.9 per cent. That is, each poor person is, on average, deprived in 47 per cent of the weighted indicators. The MPI, which is the product of H and A, ascends to 0.176. This means that multidimensional poor people in Bangladesh experience 17.6 per cent of the total deprivations that would be experienced if all people were deprived of all indicators.” (page 34)

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)

Burundi (2020) “Child poverty analysis reveals more children suffers monetary poverty (69%) and multidimensional poverty (78.2%) (MODA 2017).” (page 129)

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 (2020) shared details of the Bridge to Development strategy which makes use of MPI, and its work with the private sector including a partnership with Horizonte Positivo which launched a business MPI currently in use at 61 companies to monitor the socioeconomic relaity of more than 27,000 households to inform strategies to address deprivations.  “In the case of multidimensional poverty, since 2015, it has been reduced 2.7 pp, from 21.8% to
19.1% in the country between 2015 – 2018.” (page 128)

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.

Democratic Republic of the Congo (2020) reported “Definitely, the social and human development in the DRC remains precarious with a multidimensional poverty index (MPI) of 0.185. Over 40% of Congolese live in multidimensional poverty with several deprivations.” (page 67)

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 (2020) reported ‘policies have been designed to face multidimensional poverty, a condition that is measured in the country through the national Multidimensional Poverty Rate (MPR), which identifies the existence of multiple deprivations in the areas of health, education, work, and habitat. This indicator went from 37.5% to 35.2%, between 2014 and 2016, with a variation of 2.3 percentage points. Despite this, the current conditions influenced the indicator to reach 38, 1% in 2019.” (page 45)
Ecuador (2018) 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 (2020) confirmed a “comprehensive policy strategy has been developed” with SEDISS, CENISS and the United Nations Population Fund (UNFPA) which  prioritizes “22 municipalities in the departments of Colón, Cortés, Francisco Morazán, Gracias a Dios, Intibucá, La Paz, Lempira, Olancho, Valle and Yoro, due to the high prevalence of teenage pregnancy, the incidence of multidimensional poverty, and access to social services.” (page 73)

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 (2020) reported that “In its war against poverty, India with its focus on economic growth and social inclusion, has halved the incidence of multidimensional poverty by lifting 271 million from the most vulnerable sections of society out of poverty, while reducing extreme income poverty from 21.2 per cent in 2011 to 13.4 per cent in 2015. Deprivations have significantly reduced across nutrition, child mortality, education, sanitation and drinking water,
electricity and housing, and other basic services.” (page 18)

“The incidence of multidimensional poverty, as measured by the Multidimensional Poverty Index of OPHI and UNDP, reduced by half to 27.5 per cent between 2005-06 and 2015-16, implying that over 271 million people escaped poverty. Deprivations significantly reduced in all 10 indicators – nutrition, child mortality, years of schooling, school attendance, cooking fuel, sanitation, drinking water, electricity, housing and assets” (page 45)

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)

Kenya (2020) reported “A sizeable proportion of Kenya’s population continues to suffer multidimensional poverty and exclusion from basic social and economic benefits and opportunities for sustainable livelihoods.” (page 34)
“…during the 2017-2019 period, the multidimensional poverty among men, women and children was 38.9 per cent while geographically, the multidimensional poverty was 20.3 percent for urban areas and 48.4 per cent for rural areas.” (page 43)

Kyrgyzstan (2020) reported “The Multidimensional Poverty Index has been used in the Kyrgyz Republic since 2016, with the measurement methodology for assessing multidimensional poverty approved in 2020.” (page 11) “National data shows that there are substantial in-country geographic variations in the development level, with concentration of prevailing multidimensional poverty ‘hotspots’ in rural and remote areas in the Kyrgyz Republic.” (page 32)
“… on the basis of the global methodology for measuring the Multidimensional Poverty Index, a National Multidimensional Poverty Index (NMPI) has been developed, which includes eleven indicators in five areas of measurement: health, monetary poverty, housing conditions, food security and education” (page 139)

Malawi (2020) shared “To ensure data disaggregation and in-depth understanding of service delivery challenges and effectiveness, Malawi has rolled out the efforts of producing the Multidimensional Poverty Index Reports, which is being support by the UN.” (page 94)

“In 2018, the National Statistical Office and the Ministry of Finance’s Economic Planning and Development with support from UNICEF conducted the second multidimensional child poverty assessment in Malawi… The analysis showed that for a multidimensional poverty threshold of 2 deprivations or more, 60.5% of children in Malawi aged 0-17 years are multi-dimensionally poor, a slight decline from 63% in 2011.” (page 38)

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

State of Oaxaca, Mexico (2022) reports how Oaxaca has reduced poverty by 6.3 percentage points and extreme poverty by 3.6 percentage points over the period 2016-2020 according to the ‘Multidimensional Measurement of Poverty 2020’ published by the CONEVAL.

Macedonia (2020) “Based on the assessment of the most pronounced disparities and key factors of discrimination such as identity (e.g., age, sex, ethnicity, religion, and disability), geographical location, vulnerability to shocks, adverse governance effects and specific socio-economic status (facing multidimensional poverty and inequality), most vulnerable groups in North Macedonia include: Youth who are Not in Education Employment or Training (NEET); Women and Girls; Roma Community; Children; People with Disabilities; Refugees / Migrants / Asylum Seekers / Internally Displaced Persons / Stateless Persons; LGBTI; People Living in Rural Areas / Small Farmers; Elderly Persons.” (page 15)

Morocco (2020) reported a “downward trend has been observed for multidimensional poverty. Its rate has indeed decreased between 2004 and 2014, from 25% to 8.2% at the national level, from 9% to 2% in the middle urban and from 45% to 18% in rural areas. The number of poor people according to the 11 criteria of multidimensional poverty reached, in 2014, about 2.8 million of which 85% of them are rural”. (page 31)

“The analysis, by dimensions, of multidimensional poverty, shows that the educational deprivations of adults and children contribute to it with more than half, the deprivation of access to basic infrastructure with 20%, the housing conditions with 14% and health services with 11%. At the regional level, it was found that the poorest regions are the ones that experienced between 2004 and 2014 the largest decline in multidimensional poverty, especially the regions of Marrakech-Safi (from 34.0% to 11.3%), Tangier-Tetouan-Al Hoceima (from 30.3% to 9.5%) and Béni Mellal-Kénifra (from 31.0% to 13.4 %).” (page 32)

“In addition, multidimensional poverty varied in 2014 between 13.4% recorded in the region of
Béni Mellal-Khénifra and 4.1% in the Casablanca-Settat region and in the southern regions. The
education that represents its main source of deprivation, fluctuates between 48.2% in the region of Béni Mellal-Khénifra and 63.5% in the region of Casablanca-Settat. “(page 122)

Mozambique (2020) “Poverty still affects almost half the population, around 46% of children aged 0-17 are multidimensional poor while 49% are monetary poor” (page 3)

“The State Budget adopted criteria for resource allocation at provincial and district level that take into consideration the multidimensional index of Poverty, the population and the territory, as a way of compensating for inequalities between the Provinces within the country. ” (page 33)

“The multidimensional poverty of children (0 – 17 years), which includes eight dimensions -family, nutrition, education, work, health, water, sanitation and hygiene (WASH), participation and housing – is 46%.” (page 33)

“Currently, the allocation of resources by provinces follows two criteria, namely population (70%) and multidimensional poverty index (30%), with consumption – 30%, water and sanitation – 30%, health – 20% and education – 20%)103. The district has as indicators, the population, surface area, district own revenues and the multidimensional poverty index.” (page 85)

Nepal (2020) reported “Nepal has been able to maintain a high economic growth rate of around 7 per cent in the last few years, and the absolute poverty and multidimensional poverty levels have been gradually reducing every year. ” (page 26)

“A number of projects have been initiated and coordination needs to be further enhanced to ensure their effectiveness. With more detail mapping and disaggregated data on multidimensional poverty and targeted and comprehensive interventions, these programs will be further consolidated.” (page 30)

“Despite consistent efforts, low capital formation, low income, persistence of multidimensional poverty, difficult geographic terrain and high cost of infrastructure require huge resources for investment.” (page 59)

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”.

Nigeria (2020) “According to the Multidimensional Poverty Index, as reported in the Human Development Report, 2018, the proportion of men, women and children of all ages living in extreme poverty in all its dimensions according to national definitions was measured as 22.5 per cent.” (page 51)

“Nigeria is now home to the largest number of multidimensionally poor in the world. Ten states in north of Nigeria account for 70 per cent of the total who are multidimensionally poor. ” (page 51)

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  • Panama

    2020

    • reported how 'for 2017 19.1% of the population was in conditions of multidimensional poverty, for 2018 it went to 19%, obtaining a reduction of 0.1 percentage points. There were also reductions in intensity, that is, in the average deprivations experienced by people in multidimensional poverty, going from 43.5% to 42.4%, a reduction of 1.1 percentage points for the same period. On the other hand, the multidimensional poverty index went from 0.083 points in 2017 to 0.081 points in 2018.' (p. 65)
    • 'Panama also has an MPI at the township level (631 townships according to the 2010 political administrative division) that accounts for ten indicators (out of the 17 indicators of the National MPI) that can be calculated using population and housing censuses whose purpose is: to identify from the available evidence, the main deficiencies or non-monetary deprivations that occur simultaneously and directly affect the living conditions of the Panamanian population distributed in the townships of the country, thus for a better geographic targeting of the strategy for reduce poverty in all its dimensions, supporting the development of effective and sustained interventions that guide the design and implementation of public policies and use it as a complement to current national measurements of multidimensional poverty and income.' (p. 66)
    • For more info: Panama: Libre de Pobreza y Desigualdad, La Sexta Frontera 

    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'.
    • For more info: Objetivos de Desarrollo Sostenible Erradicar la Pobreza y Promover la Prosperidad en un Mundo Cambiante  

  • Paraguay

    2021

    • 'El reconocimiento de la multidimensionalidad de la pobreza ha sido un llamado al desarrollo de nuevas metodologías de identicación de pobreza. Es así que surgen nuevas metodologías para la medición multidimensional de la pobreza tal como la propuesta por Alkire-Foster (2011), para la construcción de un Índice de Pobreza Multidimensional (IPM). La metodología de doble corte de Alkire-Foster permite agregar diferentes dimensiones de pobreza e indicadores de privación para crear varias estadísticas de pobreza multidimensionales. Esta metodología satisface un conjunto de axiomas básicos para medir la pobreza multidimensional y se descompone fácilmente por regiones geográcas y subgrupos de población.' (p. 100)
    • 'En este sentido, se espera que con la adopción del Índice de Pobreza Multidimensional sea posible visibilizar a una parte de la población que hasta hoy ha sido invisible a las políticas públicas: los pobres multidimensionales, contribuyendo así a políticas públicas que promuevan la responsabilidad de no dejar a nadie atrás en Paraguay.' (p. 111) 
    • For more info: Segundo Informe Nacional Voluntario, Paraguay 2021

  • Republic of Congo

    • 'La problématique de la pauvreté est d’autant plus critique lorsqu’on s’intéresse à son volet multidimensionnel. Selon les données de RNDH de 2014, 43% de la population congolaise est touchée par la pauvreté multidimensionnelle et la proportion de personnes vivant dans une pauvreté extrême est de 12,2%. Par catégorie d’individus, la situation est très alarmante chez les enfants et les adolescents. Ce type de pauvreté touche près 61% d’enfants et 88% des adolescents.' (p. 21) 
    • 'La pauvreté étant multidimensionnelle et transversale, son éradication passe nécessairement par des mesures prises ou des actions entreprises par plusieurs ministères sectoriels. Ainsi, pour la période couverte par le PND 2018-2022, plusieurs programmes et projets sont définis pour lutter contre ce fléau. Il s’agit pour l’essentiel des programmes relevant des trois axes stratégiques du PND : (i) le renforcement de la gouvernance ; (ii) le renforcement et la valorisation du capital humain ; et (iii) la diversification et la transformation de l’économie.' (p. 22) 
    • For more info: Contribution Nationale Volontaire à la mise en œuvre des ODD 

  • Rwanda

    2019 

    'To fully understand the current situation of vulnerable and marginalized groups, in 2018, Rwanda launched the Multidimensional Poverty Index and analyzed child poverty using the Multiple Overlapping Deprivation Analysis. These will inform appropriate policy actions. The assessments look beyond income and provide an understanding of how vulnerable groups are left behind across three key dimensions - health, education and standard of living.' (p. 26) 

  • Seychelles

    2020

    • 'In the third quarter of 2019, the proportion of the population found to be poor according to the MPI (denoted as “H” below) was 11.88 per cent, and the average intensity (average proportion of dimensions in which poor people were deprived, denoted as “A”) was 33.26 per cent. The MPI, which is the product of H and A (H*A) was 0.040. This means that multidimensionally poor people in Seychelles experience 4 per cent of all the deprivations that would be experienced if all people were deprived in all indicators.” (page 24/25)
    • 'The four dimensions of the 2019 Seychelles MPI (Living Standards, Health, Education, and Employment) are quantified by a set of 14 indicators. Of these, the largest contributors to multidimensional poverty in the country are deprivations in the highest level of education attained, meaning that at least one household member has not completed secondary level of education (24.91 per cent); followed by deprivation in ‘Youth Not in Education, Employment, or Training (NEET)’ (12.81 per cent), and informal employment (12.40 per cent).' (p. 25)
    • 'It should be noted that the NEET rate for the final quarter of 2019 was 22 per cent, indicating the extent of untapped potential among the youth population, who could contribute to national development and poverty reduction through work. This was a 9.1 per cent increase from the previous quarter of 2019. Furthermore, the 2019 NEET rate was slightly higher for females (22.9 per cent), than for males (21 per cent). The 2019 NEET rate was 2.4 per cent higher than that for 2018 (19.8 per cent) With regard to labour force status, the results show that as expected, multidimensional poverty is more prevalent among the unemployed (with a headcount ratio of 57.35 per cent), than among those who are employed and those who are outside the labour force. Below shows the percentage contribution of each indicator and thus the composition of multidimensional poverty in Seychelles.' (p. 25)
    • 'In addition, those living in the largest households (with 7 or more occupants), appear to be more likely to experience multidimensional poverty (with a headcount ratio of 31.15 per cent), than those living in the smallest households (with a headcount ratio of 4.89 per cent). In fact, the relationship between household size and multidimensional poverty is quite clear: the poverty rate increases as household size increases.' (p. 25)
    • For more info: Voluntary National Review 2020 Republic of Seychelles

  • Sierra Leone

    2021

    • 'The country has made more gains in urban poverty reduction, currently estimating 34.8 percent (on 2018 survey calculation), compared to 46.9 in 2003/04; against rural poverty at 73.9 percent, compared to 78.7 percent in 2003/04—suggesting poverty remains a rural phenomenon in the country. Which is depicted in the multidimensional poverty index, the urban sector figure currently estimating 37.6 percent (on 2017 survey calculation), compared to 44.8 percent in 2015. This index jumped up from 78.9 percent to 86.3 percent for rural areas during 2015-2017. National level poverty measures 56.8 percent currently (on upward adjusted poverty line) or 47.3 percent on the same poverty line, compared to 52.9 percent in 2011 and 66.4 percent in 2003/04; multidimensional poverty overall dropping from 88.2 percent in 2003, to 68.3 percent in 2015 and 64.8 percent currently.' (p. 10) 
    • 'In general, prioritising both education (SDG4) and justice (SDG16) is central to pursuing other goals, such as 1 (ending poverty), 2 (zero hunger) and 10 (inequality), as well as 3 (healthcare) and 5 (gender). For instance, increasing access to justice as an entitlement and basic need is fundamental to stemming rural multidimensional poverty, currently estimated at 86.3 percent, as well as income poverty at 73.9 percent; compared to 37.6 and 34.8 percent for urban areas, respectively. Reducing school fee burden and related expenses on poor households will release resources to increase their access to other basic needs, including healthcare services and investment in small businesses consistent with SDG8 (decent work), and even 11 (responsible production and consumption) and 13 (climate change); and hence 17 (on state revenue mobilisation and partnerships) in the long-run. Since education is one of the dimensions of multidimensional poverty, strengthening access to education will contribute to reduction of both child and population level multidimensional poverty under SDG1.' (p. 15) 
    • 'The increased access to education associated with school feeding, reduced school fees and reduced household expenditure burden on learning materials also directly contributes to reduction in multidimensional child poverty.' (p. 41) 
    • 'Multidimensional poverty has been consistently dropping from 88.2 percent based on national census data of 2003, to 68.3 percent 2015 census data and 64.8 percent based on the country’s 2017 Multiple Indicator Cluster Survey (MICS); while acknowledging that the current estimate remains high to continue to induce rapid response from the state. The country has especially made substantial reduction in urban poverty, its income estimate currently standing at 34.8 percent compared to 46.9 in 2003/04; against rural poverty at 73.9 percent compared to 78.7 percent in 2003/04—suggesting that poverty remains a rural phenomenon in the country; which is reinforced by multidimensional measure, jumped up from 78.9 percent (based on the 2015 census) to 86.3 percent (based on the 2017 MICS), while urban estimates declined from 44.8 percent (2015 census) to 37.6 percent (2017 MICS). Multidimensional child poverty remains high, although it declined from 77 percent in 2010 to 66 percent in 2017.' (p. 51) 
    • For more info: 2021 VNR Report on SDGs in Sierra Leone

    2019

    • 'To ensure data disaggregation and in-depth understanding of service delivery challenges and effectiveness, Sierra Leone has joined other countries in the production of Multidimensional Poverty Index Reports; the first was launched in May 2019. In 2018, the first Child Multidimensional Poverty Report was launched and the second report is being finalised. The country has become a member of the Global Multidimensional Poverty Peer Network (MPPN).' (p.24)
    • 'There are other dimensions of poverty that necessitate the use of the multidimensional poverty methodology. It is for this reason that Sierra Leone introduced the Multidimensional Poverty Index (MPI). The Government launched the first MPI report, in May 2019, using the 2017 Multiple Indicator Cluster Survey (MICS), analysing five dimensions: education, health, housing, living standards, and energy with 14 indicators. Overall, the incidence of multidimensional poverty is 64.8 percent (almost two-thirds) in 2019; this is an improvement from an MPI estimate on 68.3 percent in 2017 based on National Housing and Population Census Data 2015, noting however that the dimensions/indicators used in both MPIs are not exactly the same for comparison. From a gender perspective, female-headed households have a higher multidimensional poverty rate (65.9 percent) compared to male-headed households (64.2 percent). And children younger than 14 years have the highest levels of multidimensional poverty (71.6 percent) compared to any other age group in 2019. The country produced the first Multidimensional Child Poverty Report (MCPR) in 2016 based on MICS 2010 data that estimated the incidence of child poverty at 77.4 percent. A draft 2019 Report based on MICS 2017 data suggests that child poverty has reduced to 66 percent using the same methodology.' (p. 32) 
    • 'The Multidimensional Poverty Report 2019 highlighted that more than 80 percent of the population is deprived in sanitation' (p. 33)
    • For more info:  2019 VNR Report on SDGs in 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.” (p. 10)

  • Sri Lanka

    2022

    • 'With jobs and earnings lost, over 500,000 people are estimated to have fallen into poverty as a result of the crisis.' (p. 112, citing MPI report) 
    • 'It has been identified in the multidimensional poverty analysis that people aged 65 and older are the poorest age group in Sri Lanka, with the highest headcount ratio (17.9%) as well as intensity of poverty and MPI, which has heightened the need for social safety nets for the aged people.' (p. 113) 
    • 'Despite these efforts, poverty levels in districts vary significantly from a low of 3.5% in Colombo to 44.2% in Nuwara Eliya. It is estimated that more than a third of the COVID-19-related job losses are expected to have occurred in the Western Province which reflects a rise in urban poverty. Further, shortages in access to health facilities, cooking fuel, drinking water, and basic facilities have the highest levels of disparities across different parts of the country. These indicate the prevailing income inequalities despite significant efforts by the government to improve social coverage. This necessitates policy formulation cognizant of income disparity, in addition to the formulation of high-impact policies guided by the indicator composition of multidimensional poverty analysis, in order to ensure the most cost-effective response.' (p. 114) 
    • 'Further, access to basic needs such as cooking fuel, drinking water show the highest levels of disparities, while the largest headcount in poverty is recorded amongst the population aged over 65. This indicates the need for targeted policy interventions that address this multi-dimensional aspect in poverty.' (p. 155) 
    • 'multidimensional poverty indicators reveal gaps in the country’s social protection nets, such as the large number of people above the age of 65, who have been employed in the informal sector and remain unprotected from the country’s social protection schemes. Targeted strategies cognizant of multi- dimensional aspects are required to respond to the growing income inequalities among the rural and vulnerable groups such as women, children and the disabled. Healthcare programs addressing NDCs, food security programmes addressing the nutritional needs of children and increasing the access to education for disabled children are some of the areas that need immediate interventions.' (p. 161) 
    • For more info:  Inclusive Transformation Towards A Sustainably Developed Nation for all: National Review on the Implementation of the 2030 Agenda for Sustainable Development in Sri Lanka. 

    2018

    • '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% respectively (Target 1.2).' (p. 66)
    • For more info: Voluntary National Review on the Status of Implementing the Sustainable Development Goals. 

  • Tajikistan

    2017

  • Thailand

    2021

    • 'Thailand’s measures to advance poverty eradication not only take into account the income dimension, but also seek to address other dimensions, such as social protection, access to essential services, and varying risk factors. Thailand has introduced a National Multi-Dimension Poverty Index (MPI), which covers four dimensions of poverty: education; healthy lifestyles; quality of life; and financial security. This has been developed in order to comprehensively and accurately reflect the current situation in the country. The Government’s measures have also led to an improvement in the country’s score on this index. Thailand’s MPI score stood at 0.051 in 2019, with the proportion of the population living in multi-dimensional poverty at 13.4 per cent (or equivalent to 9.1 million people). The Intensity of Poverty score stood at 38 per cent. This highlights the country’s improvement from 2017, when the MPI score stood at 0.068, with 17.6 per cent of the population living in poverty and an Intensity of Poverty score of 38.7 per cent.' (p. 10) 
    • For more info: Thailand's Voluntary National Review on the Implementation of the 2030 Agenda for Sustainable Development 2021 

  • Timor-Leste

    2023

    • 'According to the national multidimensional poverty index, 55% of population were living in multidimensional poverty and 54% of children were living in multidimensional poverty (GDS, MoF and UNICEF, 2021).' (p. 51)
    • 'In 2021, Timor-Leste introduced a national measure of multidimensional poverty, a landmark initiative to provide data for SDG indicator 1.2.2. This measure encompasses eight dimensions, enabling a more holistic view of poverty in the nation: Water and Sanitation (WASH); Living Standards; Information (specifically targeting adolescents and youth); Nutrition (focusing on children under 6); Health; Education (addressing people aged 6 years and older); Employment(centred on adolescents and youth); and Child Protection (aimed at children under 6). The index consists of 18 individual-level indicators, carefully selected to examine intra-household inequalities, which form the foundation of the eight dimensions.' (p. 55) 
    • 'Benefits of the multidimensional poverty index: 1) Enhancing understanding of poverty within the national context, thus complementing monetary measures; 2) Facilitating ongoing tracking, recording, and evaluation of progress in reducing multidimensional poverty; 3) Using data to refine policy strategies, target the most deeply impoverished individuals, and foster collaborative methods for implementing SDGs; 4) Encouraging wider national participation in and commitment to eradicating poverty in all forms. The data derived from the 2014 TLSLS using the multidimensional poverty index provides crucial evidence for policy formulation. Once the next TLSLS becomes available in 2024, the index will be updated, offering fresh, valuable insights for planning appropriate policy interventions and budget allocations. The development of the multidimensional poverty index was a consultative, inclusive process. The selection of indicators and thresholds was guided by international standards, national priorities, and data availability.' (p. 55) 
    • 'The national statistical office, GDS, expressed a preference for indicators and targets aligned with the Global Multidimensional Poverty Index and the SDG targets. The GDS also emphasized the necessity for a population-wide measure rather than a household-based one, requiring the definition of unique indicators and dimensions. Collaborative involvement by GDS, UNICEF, the World Bank, UNDP, and UN Women was instrumental in the successful development of the index. The national ownership of this measure is crucial for sustainability. The initial multidimensional poverty index showed a poverty headcount of 55%, with a higher prevalence in rural areas (70%) compared to urban regions (29%). It was found that young children, older individuals (60 years and above), and women are more likely to be multidimensionally poor. These insights serve as a robust baseline for measuring progress in reducing multidimensional poverty, offering a measure finely tailored to the unique context of Timor-Leste.' (p. 56)
    • For more info: Government of Timor-Leste (2023), The Second Voluntary National Review Report on Progress of the Implementation of the SDGs, 2023 (Timor-Leste VNR-2): People-Centred Sustainable Development: Leaving No One Behind, Dili: Timor-Leste. 

  • Tonga

    2019 

    • “Recently Tonga 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.' (p. 29)
    • '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.' (p. 30)
    • '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.' (p. 30)
    • 'Notably, the most common forms of deprivation among children have to do with household level items, i.e. items that are shared by all household members, such as electrical goods and making regular savings for emergencies...The same pattern is apparent for adults, with household level items showing the highest deprivation rates.' (p. 30) 
    • 'Risk factors have been identified for child and adult poverty. Households with a large number of children, as well as those with one or two adults are at higher risk of poverty.' (p. 30) 
    • 'Households where the head has university qualifications or higher are the least likely to be poor, followed by those with secondary school qualifications. The highest poverty rates correspond to households where the head has primary school or no qualifications.' (p. 30)
    • For more info: Voluntary National Review 2019 

  • Uganda

    2020

    •  'There have been general improvements in housing conditions, a critical factor in poverty reduction as poverty is multidimensional. Households may be deprived in areas other than income, and household living conditions and access to basic services are key indicators. The proportion of households that used canister wick lamps for lighting declined from 66 percent in 2012/13 to 28 percent in 2016/17, largely attributed to increased access to and use of grid electricity (22 percent) and solar energy (18 percent). Access to safe water has improved from 68 percent in 2013 to 78 percent in 2017, with the highest coverage in Eastern region (89.9 percent), compared with 82.7 percent in Northern, 76.6 percent in Central, and 64.7 percent in Western regions. However, the continued reliance on biomass (above 90 percent of the population) as a main source of cooking energy is continuing to threaten public health and the environment and is indicative of persistent financial and resource inaccessibility of alternative options.' (p. 22)
    • For more info: Voluntary National Review Report on the Implementation of the 2030 Agenda for Sustainable Development 

  • Viet Nam

    2023 VNR

    • 'Viet Nam’s multidimensional poverty rate tends to decrease sharply, from 9.2% in 2016 to 4.3% in 2022. The multidimensional poverty rate among children declined from 19.1% in 2016 to 11.7% in 2020.' (pp. 6, 31)
    • 'Viet Nam’s multi-dimensional poverty rate tended to plummet, from 9.2% in 2016 to 4.3% in 2022, an average annual decrease of 0.82 percentage points. This trend exists in both urban and rural areas and 6 socio-economic regions. In period 2016-2022, the multidimensional poverty rate in rural areas reduced more than 4 times faster than urban areas with an average annual reduction rate of 2 percentage points in rural areas and 0.25 percentage points in urban areas. Among socio-economic regions, the Northern Midlands and Mountainous Areas are the regions with the fastest reduction of multidimensional poverty rate, with an average annual decrease of 1.82 percentage points; followed by the Central Highlands, with an average decrease of 1.18 percentage points per year and the Southeast experienced the slowest reduction rate, averagely 0.05 percentage points per year in the period 2016-2022.' (p. 32)
    • 'Recently, Viet Nam has implemented various policies to ensure migrant workers and their families can access to basic social services at destination areas such as workers’ housing in industrial zones. The Law on Housing has provided preferential policies to reduce housing costs, provide opportunities to low-income workers who are struggling with settlement in access social housing and policies to support access to education and health care for children from migrant families, etc. The above impressive poverty reduction results are attributed by positive developments in all three channels affecting multidimensional poverty reduction: rapidly expanding productive jobs, significantly improved social services, and social welfare systems.' (p. 32)
    • 'Despite many achievements in poverty reduction, the poverty and near-poor rates among ethnic minority households are still 3.5 times as high as the national poverty and near-poor rates. The rate of children living in multidimensional poverty tended to decrease rapidly in the period 2016-2020, from 19.1% in 2016 to 11.7% in 2020, an average annual reduction of 1.85 percentage points. For the period of 2018-2020, the rate of children in multidimensional poverty tended to drop more slowly than in the period of 2016-2018. There is no clear difference in the rate of multidimensional poverty between girls and boys. In 2018, the difference in multidimensional poverty rates between girls and boys was 0.6 percentage points, but by 2020, this gap had descended to 0.3 percentage points.' (p. 32)
    • 'Multidimensional child poverty is decreasing across all geographic regions and population groups. However, there are still clear differences in the proportion of children in multidimensional poverty among different socio-economic regions, between urban-rural areas and among different ethnic groups. The Northern Midlands and Mountainous Areas and the Central Highlands are the two regions with the highest rates of multidimensional poverty (29.3% and 25.4% in 2018 respectively). The rate of children in multidimensional poverty in rural areas doubled that in urban areas, 14% versus 7.2% in 2020. Similar to general poverty, multidimensional poverty among children is also exceedingly high among ethnic minorities. The multidimensional poverty rate among children with disabilities is almost as twice as that among children without disabilities. In all dimensions of multidimensional poverty, children with disabilities have much higher rates of deprivation than the peers without disabilities.' (p. 33) 
    • For more info: Socialist Republic of Viet Nam: Voluntary National Review 2023 on the Implementation of the Sustainable Development Goals.

    2018 VNR 

    • '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.' (p. 14)
    • 'The multi-dimensional poverty rate also decreased from 9.9 per-cent in 2015 to 9.2 per-cent in 2016 and less than 7 per-cent in 2017, while improving the access of the poor to basic social services: access to health insurance and telecommunication use rose by 11.65 per-cent and 5.21 per-cent respectively. Although different methods are used to measure poverty, their results are relatively consistent, showing a reduction every year.' (p. 28)
    • 'The rate of ethnic minority poverty reduction from 2014-2016 was the highest it has been in two decades (poverty was reduced by 13 per-cent, from 57.8 per-cent in 2014 to 44.6 per-cent in 2016). The comparison of the multi-dimensional poverty line and the income poverty line shows a difference. In 2016, the national income poverty rate was 5.8 per-cent while the multi-dimensional poverty rate was 9.2 per-cent. In addition, the multi-dimensional poverty rate in rural areas (11.8 per-cent), the Northern mountainous region (23 per-cent) and the Central Highlands (18.5 per-cent) was very different from the national poverty line in 2016. This reveals that when the dimensions of poverty include access to all basic social services, the non-income dimensions need more improvement. According to a survey conducted by CEMA in 2015, the multi-dimensional poverty rate among ethnic minorities was 35.7 per-cent, 3.5 times higher than the national multi-dimensional poverty rate (9.8 per-cent). This results in a risk that girls get married early, have difficulty accessing educational opportunities, have a greater burden of housework, and have fewer livelihood options. Therefore, more attention should be paid to supporting vulnerable groups such as ethnic minorities, especially women and girls, to escape from poverty in a sustainable manner and, at the same time, reduce the poverty disparity between different regions of the country. (p. 28) 
    • For more info: Viet Nam's VNR on the Implementation of the SDGs 

  • Zambia

    2020 VNR

    • “Recently computed statistics on headcount multidimensional poverty show a reduction from 50 percent in 2016 to 44 percent in 2020. In rural areas, multidimensional poverty declined from 69 percent in 2016 to 59 percent in 2020 while in urban areas, poverty declined from 25 percent to 18 percent respectively. ” (page xii)
    • “Poverty headcount declined for all provinces except Western Province. In Western Province, poverty headcount rose from 61 percent of the population in 2016 to 67 percent in 2020. North Western Province had the largest decline in poverty headcount, from 60 percent in 2016 to 46 percent in 2020, representing a reduction of 24 percentage points. This means that access to education, living conditions and health services have risen in this province while living conditions have also improved.” (page 19)
    • Read more: Zambia Sustainable Development Goals VNR 2020 

  • Zimbabwe

    2017 VNR

    • 'Zimbabwe’s multidimensional poverty index (MPI) which is published by the UNDP and Oxford University declined from 0.172 in 2011 to 0.127 in 2014.' (p18)
    • 'The percentage of people who are MPI poor (also called the incidence or headcount ratio) declined significantly from 39.1 per cent in 2011 to 29.7 per cent in 2014.' (p18)
    • '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)
    • For more info: Zimbabwe Voluntary National Review (VNR) of SDGs For the High Level Political Forum 
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