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2024年6月19日发(作者：)
OPHI
Oxford Poverty & Human
Development Initiative
GLOBAL
MULTIDIMENSIONAL
POVERTY INDEX 2019
ILLUMINATING
INEQUALITIES
The team that created this report includes Sabina Alkire, Pedro
Conceição, Ann Barham, Cecilia Calderón, Adriana Conconi, Jakob
Dirksen, Fedora Carbajal Espinal, Maya Evans, Jon Hall, Admir Jahic,
Usha Kanagaratnam, Maarit Kivilo, Milorad Kovacevic, Fanni Kovesdi,
Corinne Mitchell, Ricardo Nogales, Christian Oldiges, Anna Ortubia,
Mónica Pinilla-Roncancio, Carolina Rivera, María Emma Santos, Sophie
Scharlin-Pettee, Suman Seth, Ana Vaz, Frank Vollmer and Claire Walkey.
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For a list of any errors and omissions found subsequent to printing, please visit and /multidimensional-poverty-index/.
Copyright @ 2019
By the United Nations Development Programme and Oxford Poverty and Human Development Initiative
Global Multidimensional Poverty Index 2019
Illuminating Inequalities
OPHI
Oxford Poverty & Human
Development Initiative
Empowered lives.
Resilient nations.
Contents
What is the global Multidimensional Poverty Index? 1
What can the global Multidimensional Poverty Index tell us about
inequality? 2
Inequality between and within countries 4
Children bear the greatest burden 6
Inside the home: a spotlight on children in South Asia 7
Leaving no one behind 9
Case study: Ethiopia 11
Inequality among multidimensionally poor people 13
Multidimensional poverty and economic inequality 13
The bottom 40 percent: growing together? 15
Notes 17
References 17
How the global Multidimensional Poverty Index is calculated 18
ii | GLOBAL MULTIDIMENSIONAL POVERTY INDEX 2019
STATISTICAL TABLES
1 Multidimensional Poverty Index: developing countries 20
2 Multidimensional Poverty Index: changes over time 22
FIGURES
1 Structure of the global Multidimensional Poverty Index 2
2 Both low- and middle-income countries have a wide range of
multidimensional poverty 3
3 Going beyond averages shows great subnational disparities in Uganda 5
4 A higher proportion of children than of adults are multidimensionally poor,
and the youngest children bear the greatest burden 6
5 Child-level data in the global Multidimensional Poverty Index 7
6 In South Asia the percentage of school-age children who are
multidimensionally poor and out of school varies by country 8
7 Ethiopia, India and Peru significantly reduced deprivations in all 10 indicators,
each in different ways 9
8 Trends in poverty reduction in subnational regions for selected countries 10
9 Ethiopia has made substantial improvements in all Multidimensional
Poverty Index indicators 11
10 Deprivations among multidimensionally poor people in Ethiopia are
particularly high for standard of living indicators 12
11 Inequality among multidimensionally poor people tends to increase with
Multidimensional Poverty Index value, but there is wide variation across
countries 13
12 There is no correlation between economic inequality and Multidimensional
Poverty Index value 14
13 The incidence of multidimensional poverty is strongly but imperfectly
correlated with inequality in education. 15
14 Of eight selected countries with data, only Peru and Viet Nam saw higher
growth in income or consumption per capita among the poorest 40 percent
than among the total population 15
15 In all but one of the 10 selected countries the bottom 40 percent are
improving Multidimensional Poverty Index attainments faster than the
total population 16
Global Multidimensional Poverty Index 2019
Illuminating inequalities
What is the global
Multidimensional Poverty Index?
Sustainable Development Goal (SDG) 1 aims
to end poverty in all its forms and dimensions.
1
Although often defined according to income,
poverty can also be defined in terms of the
deprivations people face in their daily lives.
The global Multidimensional Poverty Index
(MPI) is one tool for measuring progress
against SDG 1. It compares acute multidimen-
sional poverty for more than 100 countries
and 5.7 billion people and monitors changes
over time.
vations across 10 indicators in health, educa-
The global MPI scrutinizes a person’s depri-
tion and standard of living (figure 1) and offers
a high-resolution lens to identify both who is
poor and how they are poor. It complements
the international $1.90 a day poverty rate by
showing the nature and extent of overlapping
deprivations for each person. The 2019 update
of the global MPI covers 101 countries—31
low income, 68 middle income and 2 high
income—and uses data from 50 Demographic
and Health Surveys (DHS), 42 Multiple
Indicator Cluster Surveys (MICS), one DHS-
MICS and eight national surveys that provide
comparable information to DHS and MICS.
2
Data are from 2007–2018, though 5.2 billion
of the 5.7 billion people covered and 1.2 bil-
lion of the 1.3 billion multidimensionally poor
people identified are captured by surveys from
2013 or later.
group and geographic area to show poverty
The global MPI is disaggregated by age
patterns within countries. It is also broken
down by indicator to highlight which dep-
rivations characterize poverty and drive its
reduction or increase. These analyses are vital
for policymakers.
the Oxford Poverty and Human Development
The global MPI was developed in 2010 by
Initiative (OPHI) at the University of
Oxford and the Human Development Report
Office of the United Nations Development
Programme (UNDP) for the flagship Human
Development Report. The figures and analysis
are updated at least once a year using newly re-
leased data. See the back cover for more details
on the global MPI.
Key findings
•
Across 101 countries, 1.3
ple—23.1 percent—are multidimensionally
billion peo-
•
poor.
3
Two-thirds of multidimensionally poor peo-
•
ple live in middle-income countries (p. 3).
There is massive variation in multidimen-
sional poverty within countries. For exam-
ple, Uganda’s national multidimensional
poverty rate (55.1 percent) is similar to the
Sub-Saharan Africa average (57.5 percent),
but the incidence of multidimensional
poverty in Uganda’s provinces ranges
from 6.0
similar to that of national multidimen-
percent to 96.3 percent, a range
sional poverty rates in Sub-Saharan Africa
•
(6.3–91.9 percent).
Half of the 1.3 billion multidimensionally
poor people are children under age 18. A
•
third are children under age 10 (p. 6).
This year’s spotlight on child poverty in
South Asia reveals considerable diversity.
While 10.7 percent of South Asian girls are
out of school and live in a multidimension-
ally poor household, that average hides vari-
•
ation: in Afghanistan 44.0 percent do (p. 7).
In South Asia 22.7 percent of children under
age 5 experience intrahousehold inequality
in deprivation in nutrition (where at least
one child in the household is malnourished
and at least one child in the household is
not). In Pakistan over a third of children
under age 5 experience such intrahousehold
•
inequality (p. 8).
Of 10 selected countries for which chang-
es over time were analysed, India and
Cambodia reduced their MPI values the
fastest—and they did not leave the poorest
groups behind (p. 9).
The global
Multidimensional
Poverty Index (MPI)
compares acute
multidimensional
poverty for more
than 100 countries
and 5.7 billion
people and monitors
changes over time
Illuminating Inequalities | 1
There is wide variation
across countries in
inequality among
multidimensionally
poor people—that
is, in the intensity of
poverty experienced
by each poor person
•
There is wide variation across countries in
inequality among multidimensionally poor
people—that is, in the intensity of poverty
experienced by each poor person. For exam-
ple, Egypt and Paraguay have similar MPI
values, but inequality among multidimen-
sionally poor people is considerably higher in
Paraguay (p. 13).
•
There is little or no association between eco-
nomic inequality (measured using the Gini
coefficient) and the MPI value (p. 13).
•
In the 10 selected countries for which chang-
es over time were analysed, deprivations
declined faster among the poorest 40 percent
of the population than among the total pop-
ulation (p. 15).
What can the global
Multidimensional Poverty Index
tell us about inequality?
The world is increasingly troubled by inequali-
ty. Citizens and politicians alike recognize the
growing inequality in many societies and its po-
tential influence on political stability, econom-
ic growth, social cohesion and even happiness.
But how is inequality linked to poverty?
Poverty identifies people whose attainments
place them at the bottom of the distribution.
Inequality considers the shape of the distri-
bution: how far those at the bottom are from
the highest treetops and what lies in between.
Though inequality is complex, if the bottom of
the distribution rises—if the poorest improve
the fastest—one troubling aspect of inequality
is addressed.
FIGURE 1
Structure of the global Multidimensional Poverty Index
Nutrition
Health
Child mortality
Three
dimensions
of poverty
Education
Years of schooling
School attendance
Cooking fuel
Sanitation
Standard
of living
Drinking water
Electricity
Housing
Assets
Source: Oxford Poverty and Human Development Initiative 2018.
2 | GLOBAL MULTIDIMENSIONAL POVERTY INDEX 2019
Showcasing inequalities
multidimensionally
The SDGs call for disaggregated information in
order to identify who is catching up and who is
being left behind. To meet this need, the MPI
has been disaggregated by 1,119 subnational
regions as well as by age and rural-urban area.
This report uses that information to highlight
gender and intrahousehold inequalities in
South Asia and track whether countries that
FIGURE 2
reduce multidimensional poverty are leaving
no one behind.
Beyond averages
Low- and middle-income countries have
extensive subnational inequality (figure 2).
4
Of the 1.3 billion multidimensionally poor
people worldwide, 886 million—more than
two-thirds of them—live in middle-income
countries:
Both low- and middle-income countries have a wide range of multidimensional poverty
Upper-middle-income countries (94 million multidimensionally poor people)
Intensity (percent)
70
60
50
40
30
Lower-middle-income countries (792 million multidimensionally poor people)
Intensity (percent)
70
60
50
40
30
Low-income countries (440 million multidimensionally poor people)
Intensity (percent)
70
60
50
40
30
Incidence (percent)
Note: Each bubble represents a subnational region; the size of the bubble reflects the number of multidimensionally poor people. The figure is based on 1,119 subnational regions in 83 countries plus national averages for 18
countries. Data are from surveys conducted between 2007 and 2018.
Source: Alkire, Kanagaratnam and Suppa (2019) based on Human Development Report Office and Oxford Poverty and Human Development Initiative calculations.
6
Illuminating Inequalities | 3
Across the 101
countries covered
by the global MPI,
23.1 percent of people
are multidimensionally
poor, but the incidence
•
94 million multidimensionally poor people
live in upper-middle-income countries,
where the subnational incidence of multidi-
mensional poverty ranges from 0 percent to
69.9 percent.
•
792 million multidimensionally poor
live in lower-middle-income countries,
except Europe and Central Asia, are home to
as many poor people as Sub-Saharan Africa
and South Asia combined.
5
Without disaggregation, the striking inequality
within countries is easily missed.
Disaggregation matters
of multidimensional
where the subnational incidence of multi-
dimensional poverty ranges from 0 percent
poverty varies across
developing regions—
•
to 86.7 percent.
440 million multidimensionally poor people
from 1.1 percent in
live in low-income countries, where the sub-
Europe and Central
national incidence of multidimensional pov-
Asia to 57.5 percent in
This shows that the challenge of reducing
erty ranges from 0.2 percent to 99.4 percent.
Sub-Saharan Africa
multi
low-income countries.
dimensional poverty is not confined to
Inequality between and
within countries
The global MPI highlights inequalities at the
global, regional, national, subnational and even
household level. Each layer of analysis yields a
new understanding of inequality and provides
a far richer picture than the $1.90 a day poverty
rate. Two examples illustrate how subnational
disaggregations shine a light on inequality.
Where multidimensionally
poor people live
The global MPI indicates that 1.3 billion peo-
ple live in multidimensional poverty. But where
are they? Increasing levels of disaggregation can
help locate them:
•
Poorest two developing regions:
developing regions by average MPI value re-
Ranking
veals that Sub-Saharan Africa and South Asia
•
are the poorest (figure 3).
Poorest 49 countries:
MPI value reveals that the poorest 49 coun-
Ranking countries by
tries are home to as many multidimensionally
poor people as Sub-Saharan Africa and
South Asia. These 49 countries are spread
across all developing regions except Europe
•
and Central Asia.
Poorest 675 subnational regions:
subnational regions by MPI value reveals that
Ranking
the poorest 675 subnational regions, located
in 65 countries in all developing regions
4 | GLOBAL MULTIDIMENSIONAL POVERTY INDEX 2019
Across the 101 countries covered by the
global MPI, 23.1 percent of people are multi-
dimensionally poor, but the incidence of
multidimensional poverty varies across devel-
oping regions—from 1.1 percent in Europe and
Central Asia to 57.5 percent in Sub-Saharan
Africa. In Sub-Saharan Africa the incidence
varies across countries—from 6.3
South Africa to 91.9 percent in South Sudan
percent in
(see figure 3). And within countries the inci-
dence varies across subnational regions. For
instance, the incidence of multidimensional
poverty in Uganda is 55.1
to the Sub-Saharan Africa average. But within
percent—similar
Uganda the incidence ranges from 6.0 percent
in Kampala to 96.3
meaning that some regions of the country have
percent in Karamoja—
an incidence similar to that of South Africa,
while others have an incidence similar to that
of South Sudan.
Poverty is everywhere
Action against poverty is needed in all devel-
oping regions.
South Asia are home to the largest proportions
While Sub-Saharan Africa and
of multidimensionally poor people (84.5 per-
cent of all multidimensionally poor people live
in the two regions), countries in other parts of
the world also have a high incidence of multi-
dimensional poverty: Sudan (52.3
Yemen (47.7 percent), Timor-Leste (45.8 per-
percent),
cent) and Haiti (41.3 percent).
Stark inequalities across countries
in the same developing region
In Sub-Saharan Africa the incidence of
multidimensional poverty is 91.9
South Sudan and 90.5
percent in
14.9
South Africa. In South Asia it is 55.9 percent in
percent in Gabon and 6.3
percent in Niger but
percent in
Afghanistan but 0.8 percent in the Maldives. In
the Arab States it is 52.3 percent in Sudan and
FIGURE 3
Going beyond averages shows great subnational disparities in Uganda
Contribution of deprivation in each indicator to overall multidimensional poverty
Percent values represent incidence of multidimensional poverty
Sub-Saharan Africa
57.5%
South Sudan, 2010
91.9%
Developing regions
23.1%
Sub-Saharan Africa
South Asia
Arab States
Latin America and the Caribbean
East Asia and the Pacific
Europe and Central Asia
1.1%
Uganda
Uganda, 2016
55.1%
Karamoja
96.3%
Kampala
6.0%
South Africa, 2016
6.3%
NutritionChild mortalityYears of schoolingSchool attendanceCooking fuelSanitationDrinking waterElectricityHousingAssets
Source: Alkire, Kanagaratnam and Suppa (2019) based on Human Development Report Office and Oxford Poverty and Human Development Initiative calculations.
47.7 percent in Yemen but less than 1.0 percent
in Jordan. In Latin America it is 41.3 percent in
Haiti but 0.6 percent in Trinidad and Tobago.
In East Asia and the Pacific it is 45.8 percent
in Timor-Leste but 3.9 percent in China and
0.8 percent in Thailand. In Europe and Central
Asia it is 7.4 percent in Tajikistan but 0.2 per-
cent in Armenia.
remains unchanged) and reflects progress to-
wards moving people out of poverty. The poor-
est countries exhibit not just higher incidence
of multidimensional poverty, but also higher
intensity, with each poor person deprived in
more indicators. Some countries have similar
incidences but very different intensities. The
incidence of multidimensional poverty in
Pakistan and Myanmar is 38.3 percent, but
What intensity adds
the intensity is considerably higher in Pakistan
(51.7 percent) than in Myanmar (45.9 per-
The MPI is the product of the incidence and
cent). Another stark contrast is Nigeria, with
the intensity of multidimensional poverty, and
incidence of 51.4 percent and intensity of
both are important aspects. Any reduction
56.6 percent, and Malawi, with incidence of
in intensity reduces MPI (even if incidence
52.6 percent, and intensity of 46.2 percent.
Illuminating Inequalities | 5
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