Global MPI 2021
The global Multidimensional Poverty Index 2021 compares acute multidimensional poverty for 109 countries in developing regions. These countries are home to 5.9 billion people, three-quarters of the world’s population. Of these people, 1.3 billion (21.7%) are identified by the 2021 global MPI as multidimensionally poor.
The 2021 global MPI shows both who is poor – in terms of their age group, subnational region, and whether they live in an urban or rural area – and how they are poor – in terms of which overlapping deprivations they face.
Global MPI 2021 report and key findings
This year’s report, Global Multidimensional Poverty Index 2021: Unmasking disparities by ethnicity, caste and gender, produced in partnership with the United Nations Development Programme Human Development Report Office (UNDP HDRO), examines inequalities along the lines of ethnicity, case and gender across multidimensionally poor people globally. These disparities are likely to have been further exacerbated by the COVID-19 pandemic. Using the data that are available, the report presents for the first time disaggregations by the gender of the household head for 108 countries, and by ethnicity or race or caste for 41 countries. The analysis aims to highlight groups that are being left behind and show which interlinked deprivations hinder progress in poverty reduction, so that the global community can act effectively.
The report provides an intrahousehold analysis of multidimensional poverty relating to girls and women’s education in 109 countries and household headship in 108.
- Two-thirds of multidimensionally poor people – 836 million – live in households in which no girl or woman has completed at least six years of schooling.
- One-sixth of all multidimensionally poor people (215 million) live in households in which at least one boy or man has completed at least six years of schooling, but no girl or woman has.
- One in six multidimensionally poor people live in female-headed households.
- The incidence of multidimensional poverty is positively associated with the rate of intimate partner violence against women and girls.
Ethnicity, race and caste findings
The report explores the data available for ethnicity, race and caste in the global MPI (41 countries and 291 groups) finding stark inequalities among ethnic groups in some countries in developing regions.
- Nearly 128 million people belong to ethnic groups in which 70 percent or more of the population of those groups is multidimensionally poor
- Indigenous peoples are among the poorest in all Latin American countries covered. In the Plurinational State of Bolivia indigenous communities account for about 44 percent of the population but 75 percent of multidimensionally poor people.
- The two poorest ethnic groups in Gambia – the Wollof and the Sarahule – have roughly the same MPI value but different compositions of multidimensional poverty.
While the impact of COVID-19 on developed countries is already an active area of research, the report offers a multidimensional poverty perspective on the experience of developing countries. It explores how the pandemic has affected three key development indicators (social protection, livelihoods and school attendance), in association with multidimensional poverty, with a focus predominantly on Sub-Saharan Africa. To shed light on COVID-19 impacts and its risks, this section draws on data collected through high-frequency phone surveys during the pandemic, covering 45 countries across six regions:
- Emergency social protection coverage is less prevalent in high-MPI countries.
- The percentage of employed nonwage workers is particularly high in high-MPI countries.
- The percentage of households with children who stopped participating in formal education during the pandemic is larger in higher MPI countries.
- The relationship between MPI value and these additional deprivations and socioeconomic risks is not uniform: Some high-MPI countries defy the pattern, against the odds.
What is the composition of multidimensional poverty around the world?
The report includes the annual update of global multidimensional poverty levels and trends.
- Across 109 countries 1.3 billion people— 21.7 percent—live in acute multidimensional poverty.
- About half (644 million) are children under age 18.
- Nearly 85 percent live in Sub-Saharan Africa (556 million) or South Asia (532 million).
- Roughly, 84 percent (1.1 billion) live in rural areas, and 16 percent (about 209 million) live in urban areas.
- In 43 of the 60 countries with both multidimensional and monetary poverty estimates, the incidence of multidimensional poverty was higher than the incidence of monetary poverty.
- More than 67 percent live in middle-income countries, where the incidence ranges from 0.1 percent to 66.8 percent nationally and from 0.0 percent to 89.5 percent subnationally.
- Of the 80 countries permitting study of trend data, covering roughly 5 billion people, 70 experienced a statistically significant reduction of the MPI value during at least one period.
- Of the 20 countries that reduced their MPI value the fastest, 14 were in Sub-Saharan Africa, 3 were in South Asia, 2 were in East Asia and the Pacific and 1 was in Latin America and the Caribbean. The fastest reduction was in Sierra Leone (2013–2017) during the Ebola epidemic, followed by Togo (2013/2014–2017), Mauritania (2011–2015) and Ethiopia (2016–2019).
- In 24 countries studied for trends there was no statistically significant reduction in multidimensional poverty among children (individuals under age 18) during at least one period. In 15 countries the MPI among children did fall but fell more slowly than the MPI value among adults during at least one period.
- Global MPI Databank – visualisations for exploring the data intuitively.
- Country Briefings – detailed summaries of the global MPI for each country including changes over time data.
- Data Tables – all of the detailed numbers for all countries in seven excel tables.
- MPI Methodological Note 51 – technical details behind the measure.
- Stata do-files – for researchers who wish to understand or use the code.
OPHI gratefully acknowledges support from the Swedish International Development Cooperation Agency (Sida) for the update and further analysis of the global MPI and from the Canadian Government’s Department of Foreign Affairs, Trade and Development for the gendered analysis of the global MPI.