GLOBAL POVERTY INDEX 2019 ILLUMINATING INEQUALITIES
OPHIOxford Poverty & HumanDevelopment InitiativeGLOBALMULTIDIMENSIONALPOVERTY INDEX 2019ILLUMINATINGINEQUALITIES
The team that created this report includes Sabina Alkire, PedroConceição, Ann Barham, Cecilia Calderón, Adriana Conconi, JakobDirksen, 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, SophieScharlin-Pettee, Suman Seth, Ana Vaz, Frank Vollmer and Claire Walkey.Printed in the US, by the AGS, an RR Donnelley Company, on Forest Stewardship Council certified and elemental chlorine-free papers. Printed usingvegetable-based ink.For a list of any errors and omissions found subsequent to printing, please visit http://hdr.undp.org and /.Copyright @ 2019By the United Nations Development Programme and Oxford Poverty and Human Development Initiative
Global Multidimensional Poverty Index 2019Illuminating InequalitiesOPHIOxford Poverty & HumanDevelopment InitiativeEmpowered lives.Resilient nations.
ContentsSTATISTICAL TABLESWhat is the global Multidimensional Poverty Index?1What can the global Multidimensional Poverty Index tell us aboutinequality?2Inequality between and within countries4Children bear the greatest burden6FIGURESInside the home: a spotlight on children in South Asia71Structure of the global Multidimensional Poverty Index2Leaving no one behind92Both low- and middle-income countries have a wide range ofmultidimensional poverty33Going beyond averages shows great subnational disparities in Uganda54A higher proportion of children than of adults are multidimensionally poor,and the youngest children bear the greatest burden6155Child-level data in the global Multidimensional Poverty Index7Notes176References17In South Asia the percentage of school-age children who aremultidimensionally poor and out of school varies by country8How the global Multidimensional Poverty Index is calculated187Ethiopia, India and Peru significantly reduced deprivations in all 10 indicators,each in different ways8Trends in poverty reduction in subnational regions for selected countries109Ethiopia has made substantial improvements in all MultidimensionalPoverty Index indicators1110Deprivations among multidimensionally poor people in Ethiopia areparticularly high for standard of living indicators1211Inequality among multidimensionally poor people tends to increase withMultidimensional Poverty Index value, but there is wide variation acrosscountries1312There is no correlation between economic inequality and MultidimensionalPoverty Index value1413The incidence of multidimensional poverty is strongly but imperfectlycorrelated with inequality in education.1514Of eight selected countries with data, only Peru and Viet Nam saw highergrowth in income or consumption per capita among the poorest 40 percentthan among the total population1515In all but one of the 10 selected countries the bottom 40 percent areimproving Multidimensional Poverty Index attainments faster than thetotal population16Case study: Ethiopia11Inequality among multidimensionally poor people13Multidimensional poverty and economic inequality13The bottom 40 percent: growing together?ii GLOBAL MULTIDIMENSIONAL POVERTY INDEX 20191Multidimensional Poverty Index: developing countries202Multidimensional Poverty Index: changes over time229
Global Multidimensional Poverty Index 2019Illuminating inequalitiesWhat is the globalMultidimensional Poverty Index?Sustainable Development Goal (SDG) 1 aimsto end poverty in all its forms and dimensions.1Although often defined according to income,poverty can also be defined in terms of thedeprivations people face in their daily lives.The global Multidimensional Poverty Index(MPI) is one tool for measuring progressagainst SDG 1. It compares acute multidimensional poverty for more than 100 countriesand 5.7 billion people and monitors changesover time.The global MPI scrutinizes a person’s deprivations across 10 indicators in health, education and standard of living (figure 1) and offersa high-resolution lens to identify both who ispoor and how they are poor. It complementsthe international 1.90 a day poverty rate byshowing the nature and extent of overlappingdeprivations for each person. The 2019 updateof the global MPI covers 101 countries—31low income, 68 middle income and 2 highincome—and uses data from 50 Demographicand Health Surveys (DHS), 42 MultipleIndicator Cluster Surveys (MICS), one DHSMICS and eight national surveys that providecomparable information to DHS and MICS.2Data are from 2007–2018, though 5.2 billionof the 5.7 billion people covered and 1.2 billion of the 1.3 billion multidimensionally poorpeople identified are captured by surveys from2013 or later.The global MPI is disaggregated by agegroup and geographic area to show povertypatterns within countries. It is also brokendown by indicator to highlight which deprivations characterize poverty and drive itsreduction or increase. These analyses are vitalfor policymakers.The global MPI was developed in 2010 bythe Oxford Poverty and Human DevelopmentInitiative (OPHI) at the University ofOxford and the Human Development ReportOffice of the United Nations DevelopmentProgramme (UNDP) for the flagship HumanDevelopment Report. The figures and analysisare updated at least once a year using newly released data. See the back cover for more detailson the global MPI.Key findings Across 101 countries, 1.3 billion people—23.1 percent—are multidimensionallypoor.3 Two-thirds of multidimensionally poor people live in middle-income countries (p. 3). There is massive variation in multidimensional poverty within countries. For example, Uganda’s national multidimensionalpoverty rate (55.1 percent) is similar to theSub-Saharan Africa average (57.5 percent),but the incidence of multidimensionalpoverty in Uganda’s provinces rangesfrom 6.0 percent to 96.3 percent, a rangesimilar to that of national multidimensional poverty rates in Sub-Saharan Africa(6.3–91.9 percent). Half of the 1.3 billion multidimensionallypoor people are children under age 18. Athird are children under age 10 (p. 6). This year’s spotlight on child poverty inSouth Asia reveals considerable diversity.While 10.7 percent of South Asian girls areout of school and live in a multidimensionally poor household, that average hides variation: in Afghanistan 44.0 percent do (p. 7). In South Asia 22.7 percent of children underage 5 experience intrahousehold inequalityin deprivation in nutrition (where at leastone child in the household is malnourishedand at least one child in the household isnot). In Pakistan over a third of childrenunder age 5 experience such intrahouseholdinequality (p. 8). Of 10 selected countries for which changes over time were analysed, India andCambodia reduced their MPI values thefastest—and they did not leave the poorestgroups behind (p. 9).The globalMultidimensionalPoverty Index (MPI)compares acutemultidimensionalpoverty for morethan 100 countriesand 5.7 billionpeople and monitorschanges over timeIlluminating Inequalities 1
There is wide variationacross countries ininequality amongmultidimensionallypoor people—thatis, in the intensity ofpoverty experiencedby each poor person There is wide variation across countries ininequality among multidimensionally poorpeople—that is, in the intensity of povertyexperienced by each poor person. For example, Egypt and Paraguay have similar MPIvalues, but inequality among multidimensionally poor people is considerably higher inParaguay (p. 13). There is little or no association between economic inequality (measured using the Ginicoefficient) and the MPI value (p. 13). In the 10 selected countries for which changes over time were analysed, deprivationsdeclined faster among the poorest 40 percentof the population than among the total population (p. 15).What can the globalMultidimensional Poverty Indextell us about inequality?The world is increasingly troubled by inequality. Citizens and politicians alike recognize thegrowing inequality in many societies and its potential influence on political stability, economic growth, social cohesion and even happiness.But how is inequality linked to poverty?Poverty identifies people whose attainmentsplace them at the bottom of the distribution.Inequality considers the shape of the distribution: how far those at the bottom are fromthe highest treetops and what lies in between.Though inequality is complex, if the bottom ofthe distribution rises—if the poorest improvethe fastest—one troubling aspect of inequalityis addressed.FIGURE 1Structure of the global Multidimensional Poverty IndexNutritionHealthChild mortalityYears of schoolingThreedimensionsEducationof povertySchool attendanceCooking fuelSanitationStandardof livingDrinking waterElectricityHousingAssetsSource: Oxford Poverty and Human Development Initiative 2018.2 GLOBAL MULTIDIMENSIONAL POVERTY INDEX 2019
Showcasing inequalitiesmultidimensionallyreduce multidimensional poverty are leavingno one behind.The SDGs call for disaggregated information inorder to identify who is catching up and who isbeing left behind. To meet this need, the MPIhas been disaggregated by 1,119 subnationalregions as well as by age and rural-urban area.This report uses that information to highlightgender and intrahousehold inequalities inSouth Asia and track whether countries thatBeyond averagesLow- and middle-income countries haveextensive subnational inequality (figure 2).4Of the 1.3 billion multidimensionally poorpeople worldwide, 886 million—more thantwo-thirds of them—live in middle-incomecountries:FIGURE 2Both low- and middle-income countries have a wide range of multidimensional povertyUpper-middle-income countries (94 million multidimensionally poor people)Intensity 90100Lower-middle-income countries (792 million multidimensionally poor people)Intensity (percent)7060504030010203040506070Low-income countries (440 million multidimensionally poor people)Intensity (percent)7060504030010203040506070Incidence (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 18countries. 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.Illuminating Inequalities 3
Across the 101countries coveredby the global MPI,23.1 percent of peopleare multidimensionallypoor, but the incidenceof multidimensionalpoverty varies acrossdeveloping regions—from 1.1 percent inEurope and CentralAsia to 57.5 percent inSub-Saharan Africa 94 million multidimensionally poor peoplelive in upper-middle-income countries,where the subnational incidence of multidimensional poverty ranges from 0 percent to69.9 percent. 792 million multidimensionally poorlive in lower-middle-income countries,where the subnational incidence of multidimensional poverty ranges from 0 percentto 86.7 percent. 440 million multidimensionally poor peoplelive in low-income countries, where the subnational incidence of multidimensional poverty ranges from 0.2 percent to 99.4 percent.This shows that the challenge of reducingmulti dimensional poverty is not confined tolow-income countries.Inequality between andwithin countriesThe global MPI highlights inequalities at theglobal, regional, national, subnational and evenhousehold level. Each layer of analysis yields anew understanding of inequality and providesa far richer picture than the 1.90 a day povertyrate. Two examples illustrate how subnationaldisaggregations shine a light on inequality.Where multidimensionallypoor people liveThe global MPI indicates that 1.3 billion people live in multidimensional poverty. But whereare they? Increasing levels of disaggregation canhelp locate them: Poorest two developing regions: Rankingdeveloping regions by average MPI value reveals that Sub-Saharan Africa and South Asiaare the poorest (figure 3). Poorest 49 countries: Ranking countries byMPI value reveals that the poorest 49 countries are home to as many multidimensionallypoor people as Sub-Saharan Africa andSouth Asia. These 49 countries are spreadacross all developing regions except Europeand Central Asia. Poorest 675 subnational regions: Rankingsubnational regions by MPI value reveals thatthe poorest 675 subnational regions, locatedin 65 countries in all developing regions4 GLOBAL MULTIDIMENSIONAL POVERTY INDEX 2019except Europe and Central Asia, are home toas many poor people as Sub-Saharan Africaand South Asia combined.5Without disaggregation, the striking inequalitywithin countries is easily missed.Disaggregation mattersAcross the 101 countries covered by theglobal MPI, 23.1 percent of people are multidimensionally poor, but the incidence ofmultidimensional poverty varies across developing regions—from 1.1 percent in Europe andCentral Asia to 57.5 percent in Sub-SaharanAfrica. In Sub-Saharan Africa the incidencevaries across countries—from 6.3 percent inSouth Africa to 91.9 percent in South Sudan(see figure 3). And within countries the incidence varies across subnational regions. Forinstance, the incidence of multidimensionalpoverty in Uganda is 55.1 percent—similarto the Sub-Saharan Africa average. But withinUganda the incidence ranges from 6.0 percentin Kampala to 96.3 percent in Karamoja—meaning that some regions of the country havean incidence similar to that of South Africa,while others have an incidence similar to thatof South Sudan.Poverty is everywhereAction against poverty is needed in all developing regions. While Sub-Saharan Africa andSouth Asia are home to the largest proportionsof multidimensionally poor people (84.5 percent of all multidimensionally poor people livein the two regions), countries in other parts ofthe world also have a high incidence of multidimensional poverty: Sudan (52.3 percent),Yemen (47.7 percent), Timor-Leste (45.8 percent) and Haiti (41.3 percent).Stark inequalities across countriesin the same developing regionIn Sub-Saharan Africa the incidence ofmultidimensional poverty is 91.9 percent inSouth Sudan and 90.5 percent in Niger but14.9 percent in Gabon and 6.3 percent inSouth Africa. In South Asia it is 55.9 percent inAfghanistan but 0.8 percent in the Maldives. Inthe Arab States it is 52.3 percent in Sudan and
FIGURE 3Going beyond averages shows great subnational disparities in UgandaContribution of deprivation in each indicator to overall multidimensional povertyPercent values represent incidence of multidimensional povertySub-Saharan Africa57.5%South Sudan, 201091.9%Uganda, 201655.1%Developing regions23.1%Karamoja96.3%Sub-Saharan AfricaSouth AsiaArab StatesLatin America and the CaribbeanEast Asia and the PacificUgandaEurope and Central Asia1.1%Kampala6.0%South Africa, 20166.3%NutritionChild mortalityYears of schoolingSchool attendanceCooking fuelSanitationDrinking waterElectricityHousingAssetsSource: 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 percentin Jordan. In Latin America it is 41.3 percent inHaiti but 0.6 percent in Trinidad and Tobago.In East Asia and the Pacific it is 45.8 percentin Timor-Leste but 3.9 percent in China and0.8 percent in Thailand. In Europe and CentralAsia it is 7.4 percent in Tajikistan but 0.2 percent in Armenia.What intensity addsThe MPI is the product of the incidence andthe intensity of multidimensional poverty, andboth are important aspects. Any reductionin intensity reduces MPI (even if incidenceremains unchanged) and reflects progress towards moving people out of poverty. The poorest countries exhibit not just higher incidenceof multidimensional poverty, but also higherintensity, with each poor person deprived inmore indicators. Some countries have similarincidences but very different intensities. Theincidence of multidimensional poverty inPakistan and Myanmar is 38.3 percent, butthe intensity is considerably higher in Pakistan(51.7 percent) than in Myanmar (45.9 percent). Another stark contrast is Nigeria, withincidence of 51.4 percent and intensity of56.6 percent, and Malawi, with incidence of52.6 percent, and intensity of 46.2 percent.Illuminating Inequalities 5
Children bear the greatest burdenDisaggregating the global MPI by age revealsinequality across age groups. Children underage 18 bear the greatest burden of multidimensional poverty. This section spotlights the 2 billion children—1.1 billion of whom are underage 10—living in the 101 countries covered bythe global MPI.Half of multidimensionally poorpeople are children, and a thirdare children under age 10Of the 1.3 billion people who are multidimensionally poor, 663 million are children—and428 million of them (32.3 percent) are underage 10.One adult in six is multidimensionallypoor—compared with one child in threeWhile 17.5 percent of adults in the countriescovered by the MPI are multidimensionallypoor, the incidence of multidimensional poverty among children is 33.8 percent.Over 85 percent of multidimensionallypoor children live in South Asiaand Sub-Saharan Africa Most of the 663 million multidimensionallypoor children live in South Asia and SubSaharan Africa, split roughly equally betweenboth regions.6 Some 63.5 percent of children in SubSaharan Africa are multidimensionallypoor—the highest incidence among all developing regions. In Burkina Faso, Chad, Ethiopia, Niger andSouth Sudan 90 percent or more of childrenunder age 10 are multidimensionally poor.Children are more likely than adultsto be multidimensionally poorand deprived in all indicatorsA higher proportion of children than of adultsare multidimensionally poor and deprivedin every one of the MPI indicators, and theyoungest children bear the greatest burden (figure 4). This is a clarion call for action.FIGURE 4A higher proportion of children than of adults are multidimensionally poor, and the youngest children bearthe greatest burdenShare of individuals who are multidimensionally poor and deprived (percent)403020100NutritionChildmortalityYears ofSchoolCookingschooling attendancefuelChildren ages 0–9Sanitation DrinkingwaterAge groupsChildren ages 10– 17ElectricityHousingAssetsAdults ages 18 and olderNote: 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 GLOBAL MULTIDIMENSIONAL POVERTY INDEX 2019
Inside the home: a spotlighton children in South AsiaThere are many lenses through which to viewthe experience of children in poverty.7 Theglobal MPI identifies each child’s deprivationby gender and age and places it in the contextof the deprivation of other children in thehousehold and of the household as a whole.This section synthesizes a new UnitedNations Children’s Fund–supported study ofindividual child-level data for three of the globalMPI indicators in South Asia: nutrition, schoolattendance and years of schooling (figure 5).NutritionIn South Asia 70 million children underage 5—42.8 percent—are stunted or underweight.8 Intrahousehold disparities in deprivation in nutrition among children under age 5 inthe region are stark. Some 22.7 percent of children under age 5 live in a household in which atleast one child is malnourished and at least onechild is not. In Pakistan over a third of childrenunder age 5 experience intrahousehold inequality in deprivation in nutrition.Out-of-school childrenAcross South Asia 36.7 million children do notattend school through grade 8. Some
poverty for more than 100 countries and 5.7 billion people and monitors changes over time 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,
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Abbreviations xxix PC Carli price index PCSWD Carruthers, Sellwood, Ward, and Dalén price index PD Dutot price index PDR Drobisch index PF Fisher price index PGL Geometric Laspeyres price index PGP Geometric Paasche price index PH Harmonic average of price relatives PIT Implicit Törnqvist price index PJ Jevons price index PJW Geometric Laspeyres price index (weighted Jevons index)
S&P BARRA Value Index RU.S.sell Indices: RU.S.sell 1000 Growth Index RU.S.sell 2000 Index RU.S.sell LEAP Set RU.S.sell 3000 Value Index S&P/TSX Composite Index S&P/TSX Venture Composite Index S&P/TSX 60 Canadian Energy TrU.S.t Index S&P/TSX Capped Telecommunications Index Sector-based Indices: Airline Index Bank Index
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Reaching and Teaching Students in Poverty: Strategies for Erasing the Opportunity Gap By Paul C. Gorski Slidehood.com A Book Study by: Kim Cole, Molly Hawley, Kara Nunn and Sarah Weyer. POVERTY IS INCREASING In our district, we are noticing that more kids are coming toFile Size: 1MBPage Count: 10Explore further5 Concrete Ways to Help Students Living in Poverty - The .theartofeducation.edu5 Activity Ideas for Teaching about World Povertyletscultivategreatness.com5 Ways Teachers Can Address Socioeconomic Gaps in the .blog.socialstudies.comReaching and teaching students in poverty : strategies for .searchworks.stanford.eduYou Can Teach Children Living in Poverty - The Educators Roomtheeducatorsroom.comRecommended to you b
the properties of three measures of poverty: the official U.S. poverty rate; the new Supplemental Poverty Measure first released by the U.S. Census Bureau in fall 2011; and a consumption-based measure of poverty. We will focus on two fundamental goals of these measures: to identify the most disadvantaged and to assess changes
2015-2019. The change in poverty rates was not statistically significant in 2,300 counties. 5 Overall, from 2005-2009 to 2015-2019, the per-centage of people in the United States living in poverty areas decreased by 0.2 percentage points. The percentage of people living in poverty areas increased in 25 states and decreased in 23 .
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