NAMIBIA MULTIDIMENSIONAL POVERTY INDEX (MPI) REPORT …

NAMIBIA MULTIDIMENSIONAL POVERTY INDEX (MPI) REPORT 2021

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POVERTY INDEX REPORT

Mission Statement

Leveraging on partnerships and innovative technologies, to produce and disseminate relevant, quality, timely statistics and spatial data that are fit-for-purpose in accordance with international standards and best practice.

Vision Statement

Be a high performance institution in quality statistics delivery.

Core Values

IntegrityExcellent Performance AccuracyTeam Work Accountability Transparency

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Contents.

LIST OF FIGURESLIST OF TABLESPREFACEFOREWORD – NPC | National Planning CommissionEXECUTIVE SUMMARY

1. INTRODUCTION 1.1 What is the Multidimensional Poverty Index (MPI) 1.2 Purpose of Namibia’s MPI

2. METHODOLOGY 2.1 The Alkire-Foster methodology 2.2Unitofidentificationandanalysis 2.3NamibiaMPIpovertycutoff 2.4StructureofNamibiaMPI 2.5NamibiaMPIdatasource 2.6 Limitations and usage of Namibia MPI 2.7 Institutional framework

3. POVERTY MEASURES BASED ON TOTAL POPULATION 3.1ProfilingmultidimensionalpovertyinNamibia a.UncensoredheadcountratiosoftheMPIindicators b. The level of multidimensional poverty in Namibia c.CensoredheadcountratiosoftheMPIindicators d.PercentagecontributionofeachindicatortoMPI 3.2. Disaggregation of Poverty Measures a.PerformanceacrossUrban/Rural b.PerformanceacrossRegion c.PerformanceacrossSexofHeadofHousehold d.PerformanceacrossMainlanguagespokenintheHousehold e.PerformanceacrossHouseholdsize f.PerformanceacrossAgeGroups 3.3.DecompositionofCensoredHeadcountRatios 3.4.ComparisonoftheMPItothemonetarymeasure

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4. POVERTY MEASURES BASED ON THE CHILD POPULATION 4.1Profilingchild-basedmultidimensionalpovertyinNamibia a.UncensoredheadcountratiosoftheMPIindicators b.ThelevelofmultidimensionalpovertyamongstchildreninNamibia c.ChildandAdult-basedcensoredheadcountratiosoftheMPIindicators d.Percentagecontributionofeachindicatortothechildandadultspecific MPI 4.2.Decompositionofchild-basedpovertyindicators a.PerformanceacrossUrban/Rural b.PerformanceacrossRegions c.PerformanceacrossSexofheadofHousehold d.Performanceacrosschild-specificagegroups 4.3.Comparisonofthechild-basedMPItothemonetarymeasure

5. ROBUSTNESS CHECKS

6. WAY FOWARD

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List of Figures.

Figure 1:NationalUncensoredHeadcountRatioFigure 2:NationalCensoredHeadcountRatioFigure 3: PercentageContributionofeachIndicatortotheNationalMPIFigure 4: IncidenceofMultidimensionalPoverty(H)byUrban/RuralResidenceFigure 5: IncidenceofMultidimensionalPoverty(H)byRegionFigure 6: PovertyMeasures(HeadcountandIntensity)byRegionFigure 7:PovertyMeasures(Headcountrateandactualcountofpeople)byRegionFigure 8: IncidenceofMultidimensionalPoverty(H)bySexofHeadofHouseholdFigure 9: IncidenceofMultidimensionalPoverty(H)byMainLanguageSpokenFigure 10: Distribution of the Number of Multidimensionally Poor People by Main Language Spoken Figure 11: IncidenceofMultidimensionalPoverty(H)byHouseholdSizeFigure 12: IncidenceofMultidimensionalPoverty(H)AgeGroupsFigure 13: CensoredHeadcountRatiosbyUrban/RuralFigure 14:SpatialcomparisonofpovertymeasuresFigure 15: Venn Diagram Showing Overlaps between National Monetary and MultidimensionalPovertyRatesFigure 16: ChildandAdultSpecificNationalUncensoredHeadcountRatioFigure 17: ChildandAdultSpecificNationalCensoredHeadcountRatioFigure 18: PercentageContributionofeachIndicatortoChildandAdultMPIFigure 19: Child-BasedIncidenceofMultidimensionalPoverty(H)byUrban/RuralFigure 20: Child-BasedIncidenceofMultidimensionalPoverty(H)byRegionFigure 21:SpatialDistributionofChildPovertyMeasuresbyRegionFigure 22: Child-basedPovertyMeasures(Headcountrateandactualcountofchildren) byRegionFigure 23:Child-BasedIncidenceofMultidimensionalPoverty(H)bySexofHeadof HouseholdFigure 24:Child-BasedIncidenceofMultidimensionalPoverty(H)byAgeGroupsFigure 25:Comparisonbetweenmonetaryandnon-monetarychildpovertyratesFigure 26:HeadcountRatioAcrossRegionsBasedonDifferentPovertyCutoffs

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List of Tables.

Table 1:StructureoftheMPITable 2:Incidence,intensityandMultidimensionalPovertyIndexTable 3:PovertyMeasuresbyUrban/RuralTable 4:PovertyMeasuresbyRegionTable 5: PovertyIndicatorsbySexofHeadofHouseholdTable 6:PovertyIndicatorsbyMainSpokenLanguageTable 7:PovertyMeasuresbyHouseholdSizeTable 8:PovertyIndicatorsbyAgeGroups(years)Table 9: CensoredHeadcountRatiosbyRegionsTable 10: Comparisonofpovertymeasures,byregionsTable 11:ChildandAdultSpecificIncidence,intensityand Multidimensional Poverty IndexTable 12: Child-basedPovertymeasuresbyurban/ruralTable 13:Child-basedPovertymeasuresbyRegionTable 14:Child-basedPovertymeasuresbySexofheadofhouseholdTable 15:ChildPovertyIndicatorsbyage-groupsTable 16: Spearman and Kendall Tau-b

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Preface.

The main purpose of this report is to present multidimensional poverty measurement and analysis for Namibia at national and regional levels. In so doing, this report details how the Namibia Multidimensional

PovertyIndex(MPI)wasconceptualizedandconstructedusingdatacollectedbyNamibiaStatisticsAgency(NSA)throughtheNamibiaHouseholdIncomeandExpenditureSurvey(NHIES)2015/2016(thelatestsuchsurveywehave).TheNamibiaMPIisbasedontheAlkire-Fostermethod(aflexibletechniquefor measuring poverty or wellbeing) and provides another powerful tool in NSA’songoingeffortstomeasurepovertyanddeprivationsinthecountry.

Unlike themonetary poverty analysis that is often reported in theNHIESwhich isbasedon incomeonly, theMPIhas theadvantageofbeing fullydecomposablefromavarietyofdemographicandsocialvariables(suchasavailabilityofsafedrinkingwater,education,accesstohealthandnutritionas well as social protection) that keeps people trapped in poverty. MPIalsorevealstheinterconnectionsamongthosevariablesthatleadtothesedeprivations. Hence, the MPI will enable policymakers to better allocateresourcesandmoreeffectivelyformulatetargetedpolicies.

OneofthekeyindicatorsoftheSDGsismeasurementofpovertyinallitsdimensions.Hence,theconstructionoftheMPIwillassistinprovidingdatatomonitorprogresstowardsSDGindicators(specificallyindicator1.2.2).TheNSAwillendeavortocontinuepublishingandenhancingtheMPIoncenewdata set becomes available in order to provide evidence thatwill informpovertyreductionstrategiesaspertheNationalDevelopmentPlans(NDPs).

This report, therefore, seeks to create a reliable and nationally ownedmechanism that can credibly identify those that are mostly deprived,beyondthetraditionalmoney-metricmeasuresofpoverty.Thisisparticularlyimportant given that poverty, especially in an upper middle-incomecountry like Namibia, is complex andmultifaceted and as such, requiresamultidimensional approach for measuring it. Hence, theMPI has beenadoptedandadaptedtonationallydefinedsetsofdimensionsandindicatorsthatreflectthecountrycontextanddevelopmentprioritiesforNamibia.

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Theproductionprocessofthisreportistheresultoftheon-goingpartnershipandcollaborationbetweentheNSA,UNDP,UNFPA,UNICEFandotherUNagencies.TheimmensetechnicalexpertisefromOxfordPovertyandHumanDevelopmentInitiative(OPHI)resultedinthedevelopmentofcapacityandskills of theNSA and other lineministries’ staffmembers, as well as thesupervision of the report. Furthermore, OPHI provided technical supportthroughouttheprocessofdevelopingthenationalMPI.

We will forever remain thankful to these partners and the entire stakeholders inourquesttoprovidedataandstatisticsforthedevelopmentofthelandofthebrave,Namibia.Furthermore,wewouldliketothankUNICEFforthefinancialsupportinproducingthisinformativereport.

We are excited to have this MPI report to serve as a strategic tool toinformbudgetingandpolicymaking,whilstalsoprovidingbaselinedataformeasuring progress towards eliminating poverty in all its forms.

ALEX SHIMUAFENI RACHEL ODEDEStatistician-General and CEO Representative UNICEF-NAMIBIA

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Foreword.NPC | National Planning Commission

In Namibia, over the past years, mapping poverty and understandingtherootcauses thereofhas takencenterstageat thecourseofnationaldevelopment through National Development Plans (NDPs). Income

Poverty rates have, therefore, fallen over the years as per the NamibiaHouseholdand IncomeandExpenditureSurvey (NHIES) reports. In2004,theproportionof households thatwerepoor stood at 27.6percent. Thisfigurehassincefallento17.4percent in2016.Similarly,theproportionofseverelypoorhouseholdshasfallenfrom13.8percentto10.7percentoverthe abovementioned timeframe. These figures represent effective policyinterventions towards improving the standards of living and enhancingthe wellbeing of the Namibian population. Notwithstanding the afore-mentionedsuccess,thelevelsofunevendeclineinthesefiguresacrosstheregions remains an issue.

Asthestudyofpovertyevolved,itcameclearthatpovertyisamultidimensionalconcept relatingnotonly to lackof resources toacquirebasicgoodsandservices,butalsotoastateofdeprivationsresultingfromexclusion.Amoretruth-reflectingmeasure of poverty can therefore not be based solely onmonetary measure but rather on multiple dimension measure of poverty.

Thismulti-dimensionalpovertyindexreportisanothermilestoneindirectingtheprocessofNationalDevelopmentPlanningandaddsvaluetopreviousknowledge. The measure used gives broader insight in setting development prioritiescustom-madetoaddresstheneedsofregionsacrossthecountry.Asper theFifthNationalDevelopmentPlan,prioritizing thealleviationofpoverty inNamibia required accurate and in-depth understanding of thedifferentdimensionsofpovertythatpeopleface.

Theconceptofsustainabledevelopmenttakescenterstageduringnationaldevelopment planning in Namibia. This means that our development planning is anchored towards the upliftment of both current and futuregenerations and responds to the SDGs. This multi-dimensional index,therefore,enhanceseffortsbythecountrytorigorouslystrivetoendpovertyinallitsformsinallcornersofthecountryforgenerationstocome.Theindexrevealsthemagnitudeofpovertyintheregions,withinethnicgroups,areas

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ofresidenceandthecountryatlarge.Understandinghowdifferentgroupsofthepopulationaredeprivedandwhattheyaredeprivedof,willhelppolicymakersinmakingtargetedpolicieswhichwillcreateefficiencyandhelpinallocationofresourcesinthecountry.

Maythismeasure,andreportthereof,createaplatformfornationaldialogueforpolicyformulationtoliftNamibiansoutofmulti-dimensionalpoverty.

OBETH MBUIPAHA KANDJOZEDirector-General of the National Planning Commission

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Executive summary.

The MPI is a multidimensional measure of poverty developed by the Oxford Poverty and Human Development Initiative (OPHI) at theUniversity of Oxford. The index assesses the simultaneous deprivations

that are experienced by people in a society, based on several identifieddimensionsofpovertyinaparticularsetting.

Whilst drawing from the Global MPI, the National MPI for Namibia hasbeen adjusted and contextualized to better reflect the specific contextand development priorities of the country. As per the Global MPI, theNationalMPIisbasedonthreedimensions:‘Livingstandards’,‘Health’and‘Education’,albeitmeasuredacross11indicators,deemedbythenationalMPI steering committee to be reflective of the Namibian context, andinformedbyavailabledata.Poverty indiceswerealsodecomposedacrossvariouspopulationsub-groupssuchasUrban/rural,Region,Sexofheadofhousehold,Main language spoken in the household,Household-size andage-group.

BasedondatafromtheNamibianHouseholdIncomeandExpenditureSurvey(NHIES2015/16),themultidimensionalpovertyincidence(H)isreportedat43.3percent,meaningthat43.3percentofthepopulationofNamibiaaremultidimensionallypoor.Theaverageintensity(A)is44.0percent,meaningthatpoorpeople inNamibiaexperience,onaverage,44.0percentof theweighteddeprivations.TheMultidimensionalPovertyIndex(MPI),whichistheproductofHandA(H*A),is0.191,thereforethepoorinNamibiaface19.1percentofthepossibledeprivationsifeveryonewaspooranddeprivedinalltheindicatorsincludedintheindex.

With regards to area of residence, the rural area population was multidimensionally poorer than the urban population, reported at 59.3and25.3percent, respectively. This indicates that persons in rural areashaveahigherchanceofexperiencingmultipledeprivationsthanthoseinurbanareas.Povertyindiceswerealsoexaminedacrossthefourteen(14)administrative regions of Namibia. An obvious gradient was observed in theheadcountratiosbyregion,wherebytheincidenceofmultidimensionalpovertywashighestinKavangoWest(79.6%),KavangoEast(70.0%)andKunene (64.1 %).

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Thereportalsoexaminesperformanceacrosscharacteristicsofhouseholdheads. With regards to sex of the heads of households, resultsshowthattheincidenceofmultidimensionalpovertyishigheramongfemale-headedhouseholds (with a rate of 46%), than male-headed households (with arate of 41%). With regards to the main language spoken in the household decomposition,thehighestheadcountratioofmultidimensionalpovertywasreported amongst the population whose main language spoken at home was Khoisan(93%),followedbyRukavango(68%)andZambezilanguages(54%).The population whose main spoken language was English, and Germanreportedthelowestheadcountratiosofmultidimensionalpoverty,eachwith3percent.

Another decomposition was on household size. The results indicate thatas household size increases, the rate of multi-dimensional poverty alsoincreases.Theheadcountratioishighestforhouseholdsthathave16ormoremembers,at72.8percentcomparedto33.4percentforahouseholdwithlessthan6members.Abreakdownofthepovertyindicesbyage group was alsoconsidered.Thehighestheadcountratioisreportedamongchildrenof1-4years(56%),5-9years(50%)and10-14years(48%).Thelowestheadcountratio(33%)isreportedfortheagegroupof25-29years,toimplythatofallpersonsaged25-29years,33percentaremultidimensionallypoor.

A child-specificanalysisontheMPIwasalsocarriedoutinthereport,fromwhichapproximately16percentofchildrenaged0-17yearsinNamibiaareboth multi-dimensionally and monetarily poor. Further, the proportion ofchildrenwhoaremulti-dimensionallypoorisremarkablyhigherinruralareasthaninurbanareas.About64percentofchildrenwholiveinruralareasaremultidimensional poor compared to 30 percent in urban areas, followingthe general population trend. There are also regional level disparities indeprivation rates. In5of the14 regions inNamibia, thepercentageofchildrenwho aremulti-dimensionally poor is above 60percent, includingKavangoWest (82.3%), Kavango East (74.7%), and Kunene (69.2%). ThelowestratesarefoundintheregionsofErongo(15.7%)and//Karas(21.1%).

In conclusion, it isnoted thatwhilstprogresshasbeenmade in reducingmonetary poverty to 16.7 percent, more than 43.3 percent of Namibia’spopulationarestilllivinginmultidimensionalpoverty.Thiscallsforadeliberateandcoordinatedpolicyresponsetodealwiththevariousdeprivationsthatcontinuetoimpactonthewellbeingofmanyhouseholdsandtheirchildren.TheNSAwillendeavortocontinuepublishingandenhancingtheMPIoncenew data set becomes available, to provide evidence to inform povertyreductionsstrategiesaspertheNationalDevelopmentPlans(NDPs)whilstalsoprovidingastrategictoolformonitoringprogresstowardsSDGsaswellas NDPs implementation.

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1. Introduction.

This section looks at the definition of Multidimensional poverty as well as the motivation for producing an MPI for Namibia.

1.1 What is the Multidimensional Poverty Index (MPI)

The MPI is a multidimensional measure of poverty developed by the Oxford PovertyandHumanDevelopmentInitiative(OPHI)attheUniversityofOxford.Theindexassessesthesimultaneousdeprivationsthatareexperiencedbypeopleinasociety,basedonseveralidentifieddimensionsofpovertyinaparticularsetting.

Many countries now measure multidimensional poverty alongsidemonetarypoverty.Thismeansthatacountrywillestimateandreleasetwocomplementaryofficialnationalmeasuresofpoverty.Themonetarypovertymeasure assesses incomeor consumption-expenditurepoverty, accordingto national poverty lines. The multidimensional poverty measure reflectsrelevantnon-monetaryaspectsofpovertythatmayexist.Multidimensionalpoverty considers the many overlapping deprivations that poor peopleexperienceatvariouslevelsofsociety.

TheMPIreflectsboththeincidenceofpoverty–whatproportionofpeoplearepoor -andthe intensityofpoverty–howpoor theyare.Assuch, themeasurerevealswhoispoor,thedimensionstheyarepoorinandthebreadthof their deprivations. The MPI is broken down by different dimensions and indicators,toprovideusefulinformationforthetargetingofpublicresources.Furthermore,itcanalsobedisaggregatedbypopulationsub-groups,tohelpinensuringthatnooneis leftbehind,ascalledforbytheUnitedNation’s2030 agenda for sustainable development.

Since2010,OPHIandUNDPhavejointlycomputedandpublishedtheglobalMPIintheHumanDevelopmentReporttocompareacutemultidimensionalpovertyacrossmorethan100developingcountries.However,thismeasureisintendedforinternationalcomparabilityandisnotadaptedforthespecificcircumstancesofagivencountry.Thus,manycountrieshavedevelopedtheirownnationalMPIs to inform targetedpolicy interventionsatnationalandsub-national levels.

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1.2 Purpose of Namibia’s MPI

The national MPI for Namibia was designed mainly for two main reasons. Thefirstistoprovideupdatedmultidimensionalpovertystatisticstoinformpolicy and programmatic design and implementation. A national MPIcan guide coordinated policy actions by several Offices, Ministries andAgencies (OMAs), provide cleargoals and targets for each indicator, andactasamonitoringandaccountabilitytool.Secondly,themeasureisaimedat complementing monetary poverty statistics released by the NSA, byproviding an understanding of the multidimensional nature of poverty and thevariousdeprivationsfacedbydifferentgroupsofpeopleinNamibia,bylocationanddemographicgroups.Theevidencegeneratedonthedriversof multidimensional poverty will be used to monitor progress on NDPs and SustainableDevelopmentGoals(SDGs),particularlySDG1,ofreducing,byhalf,theproportionofmen,womenandchildrenofallageslivinginpovertyin all its dimensions by 2030.

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This chapter presents the methodology adopted for this study. It begins with a description of the Alkire-Foster method, which is then followed by an explanatory of the data source. The chapter further presents the structure of Namibia’s national MPI, in terms of dimensions; indicators; deprivation cut-offs and weights. The chapter further discusses the limitations and usage of the index. Thereafter, it concludes with a presentation of the institutional framework put in place to guide and coordinate the development of the index.

2.1 The Alkire-Foster methodology

Namibia’snationalMPIisbasedontheAlkire-Foster(AF)methodology,aflexibletechnique formeasuring poverty orwellbeing developed by SabinaAlkire andJamesFosteratOPHI.TheAFmethodologycanincorporatedifferentdimensionsandindicatorstocreatemeasuresadaptedtospecificcontexts.

In summary, theAFmethodology first identifieswho is poor, by constructing apoverty profile for each individual or household, which shows which indicatorstheyaredeprivedin,accordingtothedeprivationcut-offs.Thesedeprivationsareaggregated intoaweighteddeprivationscore.Theweights foreachdimensionand each indicator are based on normative judgments related to the purposeof themeasure.Thenextstepwastochooseapovertycut-off,k.An individualis classified tobe living inmultidimensionalpoverty if his/herdeprivation scoremeetsorexceedsthepovertycut-offk,oftheweightedindicators.

Afteridentifyingeachpersonaspoorornon-poor,theinformationwasaggregatedintothreeinformativestatistics.

• The incidence of poverty (denotedbyH),which is theproportionofpeopleidentifiedasmultidimensionallypoor,alsoreferredtoasthe“headcountratio”.It is the percentage of people out of the total populationwhoseweighteddeprivationscoreisgreaterthanorequaltothepovertycut-offk.

• The intensity of poverty (denoted by A), which is the average proportionof weighted indicators in which poor people are deprived—the averagedeprivationscoreacrossallpoorpeople.

• TheMPIiscomputedastheproductofthesetwocomponents[i.e.,MPI=HxA].TheMPIalwaysrangesfromzerotoone,andahighernumbersignifiesgreaterpoverty.Thismethodnotonlyidentifieswhoispoorbutalsoprovidesaninnovativemeansbywhichonecanincorporatehowacuteorintensethesituation of multidimensional poverty is for the poor.

2. Methodology.

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2.2 Unit of identification and analysis

The unit of identification refers to the level at which deprivations aremeasured.Itisthereforetheentitythatisidentifiedaspoorornon-poor–usually the individual or the household. Namibia’s MPI uses a household as theunitofidentification.Allmembersforagivenhouseholdarecollectivelyclassifiedaspoorornon-poordependingoneachindicator.Thisimpliesthatindividual-levelindicatorslikethoseoneducationornutritionarecombinedacrosshouseholdmembers.AspecificexampleisthatfortheNamibiaMPI,ifthere’satleastoneschool-agedchildwhoisnotgoingtoschool(thereforedeprived in the indicator), then all his/her household members are alsoconsideredtobedeprivedintheindicator.

Thisapproachallowsthemeasuretoincludeindicatorsthatarespecifictocertainagegroups(for instance,schoolattendance),whileacknowledgingintra-household caring and sharing – for example, educated householdmembersreadingforothermembersorhouseholdmembersbeingaffectedbyachild’smalnutrition.

The unit of analysis refers to how the results are reported and analyzed.Namibia’sMPIusestheindividual(person)astheunitofanalysis.Thatis,theresultspresentedinthisreportarebasedonthepercentageofpeoplewhoareidentifiedaspoorratherthanthepercentageofhouseholds.

2.3 Namibia MPI poverty cut off

TheNamibiaMPIusesapovertycut-offof30percent.Therefore,apersonisconsideredtobemultidimensionallypoor ifheorshe isdeprived in30percentormore,ofthesumoftheweightedindicators.Thechosencut-offnearlyreflectstheglobalMPIi.e.33percent,whichsuggeststhatapersonmustbedeprivedinatleastonefulldimension’sworthofindicatorstobeconsideredmultidimensionallypoor.

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2.4 Structure of Namibia MPI

A number of factors guided the creation of Namibia’s MPI. Mainly, theselectionofdimensions,indicators,andcut-offswasdeterminedthroughaconsultativeprocessoftheSteeringCommittee(summarizedinsection2.7),drawing on expertise frommany different sectors and reflectingNationalDevelopment Plans (NDPs) and priorities.

Other factors that were considered include the availability of data fromtheselecteddatasourceaswellasanexaminationoftheglobalMPIandits dimensions and indicators (see report at https://ophi.org.uk/global-mpi-2020/).TheglobalMPIconsistsofthreedimensions:‘Livingstandards’,‘Health’and‘Education’,measuredacross10indicators.

WhiletheNamibiaMPIretainsthesethreedimensions,theindicatorshavebeen adjusted to better reflect the specific context and priorities of thecountry.

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Asaresult,Table1presentsthedimensions,indicatorsandthedeprivationcut-offsthatwereestablishedasthemostsuitablefromthedatasourceforNamibia:

DIM

ENSI

ON

DIM

ENSI

ON

W

EIG

HT

IND

ICAT

OR

IND

ICAT

OR

WEI

GH

T W

ITH

IN

DIM

ENSI

ON

(%)

Educ

atio

n

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SCHOOL ATTENDANCE: A household is deprived if at least one school aged child (aged 7-17 years) is not attendingschool.

2/15

YEARS OF SCHOOLING: A household is deprived if all household members aged 16 years or older have not completed7yearsofschooling.

1/5

Living

stan

dard

s

1/3

DRINKING WATER: A household is deprived if it does not haveaccesstoimproveddrinkingwater1(accordingtoSDG-6).

1/18

SANITATION:Ahouseholdisdeprivedifitssanitationfacilityis not improved2 (according toSDG-6)or it is improvedbutshared with other households.

HOUSING: A household is deprived if it has inadequatehousing–therooforwallaremadeofrudimentarymaterials3 -ORthedwellingisanimprovisedhousingunit.

TRANSPORTATION ASSETS: A household is deprived if it does not own at least one of theseassets:car,busorbakkie.

ICT: A household is deprived if it does not own any of these assets:radio,TV,smartphone,orcomputer;andthehouseholddoesnothaveinternetaccessathomeorelsewhere.

COOKING AND LIGHTING ENERGY: Ahouseholdisdeprivedifitusesuncleansources4forcookingand lighting.

Health

1/3

ACCESS TO CLINIC/HOSPITALS: Ahouseholdisdeprivedifahospitalorclinicismorethana20-kmdistanceormorethan30minutesonewayfromhome.

1/15

FOOD SECURITY: A household is deprived if it did not have enough food in the 7 days prior to the survey.

2/15CHILD NUTRITION: A household is deprived if it has at least onechildunder5whoisunderweightorstunted.

1Piped (tap) water into dwelling; piped (tap) water on site or in yard/plot; public tap/standpipe; private tube well/borehole; protected dug well; protected spring and bottled water.2Pit latrine with slab; pit latrine without slab/open pit; bucket toilet; no facilities/bush or field, other) or it is improved but shared with other households.3Wooden poles, sticks and grass, sticks, mud, clay and/or cow-dung, thatch, grass, other or none4Paraffin, firewood, charcoal, coal, animal dung, other or none for cooking energy; and Wood or wood charcoal, other, none, battery lamp/torch/cell phone, candles and paraffin for lighting energy.

Table 1: Structure of the MPI

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As listed in Table 1, Namibia’s MPI has 11 indicators in total.

EDUCATION - Under this dimension, the two (2) indicators of school attendance and years of schooling resemble those found in the global MPI. TheindicatorsaimtomonitorandevaluatethefifthNDP’sprimaryeducationcompletionrateto100percentbytheyear2022,aswellastheMinistryofEducation,ArtsandCulture’s2013implementationofuniversal,freeprimaryeducation.Additionally,theindicatorsareattributedtoSDG4,whosetargetis to ensure that all girls and boys complete free, equitable and quality primary and secondary education leading to relevant and effective learning outcomes. Furthermore, within this dimension the indicator for years ofschooling is allocated a higher weight of 60 percent, with the normativejustificationthatahouseholdwherealladultshavenotcompletedseven(7)yearsofschoolingmayhaveahigherchanceofbeinginpovertymorethanahouseholdwithmanychildrenandonlyfewofthemarenotgoingtoschool.ThisjustificationwaspertheadvicegivenbytheMinistryofEducation,ArtsandCulture.

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LIVING STANDARD -Thisdimensionhasthehighestnumberofindicators,six(6).Theindicatorsareequallyweightedwithinthedimension,toreflecttheirequal importanceasdescribed in theSDGsandNDP5 targets.Thedrinking water and sanitationindicatorsarebasedonSDG6,whichaimedat ensuring availability and sustainable management of water and sanitation for all.Theseindicators,whicharealsopartoftheGlobalMPI,arefurthermotivatedbySDG3,whichcallsto ensure healthy lives and promote well-being for all at all ages.

Goal11oftheSDGstargetsto make cities and human settlements inclusive, safe, resilient and sustainable. Thefirsttargetofthisgoal,whichistoensureaccessforalltoadequate,safeandaffordablehousingandbasicservicesandtoupgradeslums,motivatedtheMPI’sindicatoronhousing.TheNDP5highlights that as of 2016, 19 percent of theNamibian populationwerelivinginimprovisedhousingunits,whileonly53.4percentofthepopulationhad access to improved sanitation. Furthermore,while the proportion ofhouseholdswithaccesstosafewaterwasreportedhighforurbanareasat98percentin2016,theruralpopulationproportionwasmuchloweratabout84percent.Theindicatorsarethereforeaimedatprovidinginformationonthese deprivations.

Furthermore,theindicatorontransportationassetsisbuiltonthebasisofthesecondtargetofSDG11.Ittargetsto provide access to safe, affordable, accessible and sustainable transport systems for all, improving road safety, notably by expanding public transport, with special attention to the needs of those in vulnerable situations including women, children, persons with disabilities and the elderly. In order to provide information linked to safe and accessibletransportinNamibia,theMPIthereforeconsideredownershipoftransportationassetsasopposedtoonlyhavingaccess.

Cooking and lighting energyisanothercrucialindicator,whichisintendedtohighlightthetypeoffuel/energyusedbyhouseholdsandisattributedtothequalityofventilationandrespiratoryhealth.TheNDP5targetstopromoterenewable energy and accelerate rural electrification. The last indicatorunderthisdimensionisICT,whichstatesthatahouseholdisdeprivedifitdoesnotownanyoftheseassets:radio,TV,smartphone,orcomputer;and

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the householddoes not have internet access at homeor elsewhere. TheNDP5 targets by 2022, thatNamibia has universal access to information,affordablecommunicationandtechnologyinfrastructureandservices.

HEALTH - Lastly,threeindicatorsmeasurethedimensionofhealth.TheSDG3 targets to achieve universal health coverage, including access to quality essential health-care services and access to safe, effective, quality and affordable essential medicines and vaccines for all.Furthermore,theNDP5’sdesired outcome on healthcare is that “by 2022, all Namibians will haveaccess toqualityhealthcare”.Finally, the indicatorson food security and child nutrition arelinkedtoSDG2,whichcallsto end hunger, achieve food security and improved nutrition and promote sustainable agriculture. The NDP5targetsthat“By2022,theproportionoffoodinsecurehouseholdshasdroppedfrom25percentto12percentandfoodproductionhasincreasedby 30%”.Within this dimension,access to clinics/hospitals is comparablyallocateda lesserweightof20percent, and thedistanceof20kmor30minutes’thresholdwasprovidedandguidedbytheMinistryofHealthandSocialServices(MoHSS).

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2.5 Namibia MPI data source

AstheMPIrequiresacompletedeprivationprofileforeachunit(individualor household), information on all indicators must be available for eachperson and come from the same source of data. Amongst the nationallyrepresentative surveys and censuses in Namibia, the 2015/16 NamibiaHousehold Income and Expenditure Survey (NHIES) which is conductedevery5years,wasselectedfortwomainreasons.Firstly,theyear-longsurveycollectsdataacrossseveralsocio-economicindicators.Secondly,sincethemonetarypovertystatisticsarededucedfromtheNHIES,usingitallowsforcomparisonsofmonetaryandnon-monetarypovertyrates,whichprovidesusefulinformationindescribingthenatureofpovertyinthecountry.

2.6 Limitations and usage of Namibia MPI

Since 2003/4, poverty in Namibia has been officially measured throughthe Cost of Basic Needs approach, which is monetary-based. However,the consideration of non-monetary dimensions in understanding povertyhas gained importance in poverty analysis, especiallywith theUN’s 2030SustainableDevelopmentGoals(SDGs)callingforanendofpovertyinallitsforms and leaving no one behind. Namibia’sMPIisnotintendedtoreplacethemoney-metricpovertystatistics,whichisbasedonnationalpovertylines(namely,thefoodpovertyline,thelower-boundpovertylineandtheupper-boundpovertyline).Rather,theMPIshouldbeconsideredasacomplementarymeasuretothesemoney-metricmeasures,byprovidinganassessmentofdeprivationofbasicsurvivalneeds.

Asmentionedabove,Namibia’sMPIisbasedonthe2015/16NHIES.Whilethedimensionofeconomicactivitywasdeemedcriticaltothemeasure,thissurveycouldnotprovidedesirableindicatorsonlaborforce(unemployment)forthisdimension.However,this limitationwillbeaddressedinthefutureNHIES, as a continuous improvement of theMPI measure. Additionally,the survey’s sample design does not allow for disaggregation of results in geographicalareasbelowregions,suchastownsandconstituencies.

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2.7 Institutional framework

The structure of the measure is the result of a series of discussions ledby the Namibia Statistics Agency (NSA), National Planning Commission(NPC),UnitedNationsChildren’sFund (UNICEF)Namibia,UnitedNationsDevelopment Programme (UNDP) - Namibia and the United Nations PopulationFund(UNFPA)–Namibia.

ThedesignandcomputationoftheNationalMPIhasincludedconsultationsanddiscussionswiththenationalSteeringCommittee,whichwascomprisedofvariousOMAs(MinistryofFinance,MinistryofEducation,ArtsandCulture,MinistryofAgriculture,WaterandLandReform,MinistryofUrbanandRuralDevelopment,NamibiaUniversityofScienceandTechnology,UniversityofNamibia,InstituteforPublicPolicyResearch,NationalPlanningCommission,MinistryofGenderEquality,PovertyEradicationandSocialWelfare,MinistryofHealth and Social Services), to ensure that theMPI is tailored to localcontext using Namibia-specific indicators to provide a comprehensiveunderstandingofcountry-levelmultidimensionalpoverty.

These consultations were necessary for stakeholders to understand theirroles of revising the measure every ten years and making sure the proposed indicatorsarecollectedinthesurveyTheNSAastheleadinstitutioninthedevelopmentoftheNAMPIisresponsibleforupdatingtheestimationswhichwouldbedoneeveryfiveyears.

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This section presents the multidimensional poverty results for Namibia,based on the 2015/16 NHIES data. Firstly, the national multidimensionalpovertyresultsarepresented,followedbythedisaggregatedresultsacrossdemographiccharacteristicssuchasregionandurbanandrural;agegroups;householdsize;mainspoken languageand, sexofheadofhousehold. Inconclusion,thesectionpresentsaregionalcomparisonofmultidimensionalpoverty to the traditional monetary poverty results.

3.1 Profiling multidimensional poverty in Namibia

a. Uncensored headcount ratios of the MPI indicators

Theuncensoredheadcountratioofanindicatorisdefinedastheproportionofthetotalpopulationthatisdeprivedinthatspecificindicator,regardlessof whether they are multidimensionally poor or not.

Figure1 shows theproportionof thepopulation that isdeprived ineachof the11 indicatorsof theMPI.Atnational level, thehighestdeprivationlevels were reported in Transportation Assets (proportion of people from householdsthatdonotownat leastacar,busorbakkie)at76.2percent.This is followed by Sanitation (proportion of people from households where sanitation facility is not improved (according to SDG guidelines) or it is

3. Poverty measures based on total population.

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improvedbutsharedwithotherhouseholds)at68.9percent,andthenbyCookingand Lighting Energy (proportion of people from households that uses uncleansourcesforcookingandlighting)at64.8percent.

The lowest deprivation levelswere reported in ICT (proportion of people fromhouseholds who do not own any of these assets: radio, TV, smartphone, orcomputer;andthehouseholddoesnothaveinternetaccessathomeorelsewhere)at3.4percent.ThisisfollowedbySchoolAttendance(proportionofpeoplelivinginahouseholdwhereatleastoneschool-agedchildisnotattendingschool)at9.6percentandYearsofSchooling(proportionofpeoplefromhouseholdswhereallmembersaged16yearsorolderhavenotcompletedseven(7)yearsofschooling)at10.1percent.

Figure 1. National Uncensored Headcount Ratio

9.6 10.114.8

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b. The level of multidimensional poverty in Namibia

Table 2 shows the three main measures of multidimensional poverty: Headcount ratio (H), Intensity (A)andtheAdjustedheadcount ratio (MPI).TheHeadcountratio(H)representstheproportionofpersonsidentifiedasmultidimensionallypoor,outofthetotalpopulation,basedontheselectedpoverty cutoff. The intensity (A) index represents the average proportionofweighted indicators inwhich poor people are deprived. TheAdjustedheadcountratio(MPI),whichistheproductoftheincidence(H)andintensity(A)ofpoverty,representsthedeprivationspoorpeopleareexperiencingasashareofthetotalpossibledeprivationsthatcouldbeexperiencediftheentirepopulationwaspooranddeprivedinall indicators.TheMPIalwaysrangesfromzerotoone,andahighernumbersignifiesgreaterpoverty.

FromTable2,theincidenceofmultidimensionalpoverty (H) inNamibia is43.3percent.Thisistheproportionofpeoplewhoaredeprivedinatleastk=30percentoftheweightedindicators.Theintensityofmultidimensionalpoverty (A) is44.0percent,whichmeans thatonaverage, thosewhoaremultidimensionallypooraredeprivedinabout44.0percentoftheweightedindicators.TheNationalMPIis0.191.

Table 2. Incidence, intensity and Multidimensional Poverty Index

Poverty cutoff (k value)

Index Value Confidence Interval

k=30%Headcountratio(H,%) 4.3 41.0 45.6

Intensity(A,%) 44.0 43.2 44.9

MPI 0.191 0.180 0.202

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c. Censored headcount ratios of the MPI indicators

It is important tounderstandhowpeoplearepooraccording todifferentindicators,asthisinformationisvitaltoshapingpoliciestoreducepoverty.Figure 2 shows the censored headcount ratio for each of the weightedindicators.Thisistheshareofthepopulationthatisdeprivedinthatindicatorandisalsomultidimensionallypoor.TheNationalMPIcanalsobecomputedas the sumof theweightedcensoredheadcount ratios.This implies that,reducing any of the indicators’ censored headcount ratios changes theoverall multidimensional poverty index MPI.

FromFigure2,resultsshowthatatnationallevel,thehighestproportionof people that are multidimensionally poor and deprived per specificindicator are reported for Transportation Assets (41.2%). This meansthat41.2percentof thepopulation isdeprived inTransportationAssetsandalsomultidimensionallypoor.ThisisfollowedbySanitation(40.4%),Cooking and LightingEnergy (40.0%) andHousing (30.9%). The lowestcensoredheadcountratioisreportedforICT(3.1%)andAccesstoClinics/Hospitals(8.5%).

Figure 2. National Censored Headcount Ratio

9.3 9.1 11.4

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d. Percentage contribution of each indicator to MPI

OneoftheadvantagesoftheAlkire-FostermethodologyisthattheMPIcanlookatthecontributionofeachdimension/indicatortotheoverallpovertyscoretoseewhatiscontributingmoreorlessataparticularpointintime.

Figure3showsthepercentagecontributionofeachweightedindicatortothe overall national multidimensional poverty index. The graph shows that the indicators thatcontribute thehighest tomultidimensionalpoverty inNamibiaareFoodSecurity(17.4%),ChildNutrition(15.0%),TransportationAssets (12.0%), Sanitation (11.8%), and Cooking and Lighting Energy(11.7%).TheleastcontributorstopovertyareICT(0.9%),AccesstoClinic/Hospital(3.0%)andDrinkingWater(3.3%),thisisbecausetheseindicatorshavelowcensoredheadcountratiosandhence,theycontributesolittle.

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Figure 3. Percentage Contribution of each Indicator to the National MPI

9.7 6.4 3.3 11.8 9.0 12.0 0.9 11.6 3.0 17.4 15.0

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0%

School attendance Years of schooling Drinking water

Sanitation Housing Transportation assets

ICT Cooking and lighting energy Access to clinics/hospitals

Food security Child nutrition

3.2. Disaggregation of Poverty Measures

Inordertoexaminethedisparitiesintheprevalenceanddistributionofmultidimensionalpoverty in Namibia, a section on the MPI results disaggregated across variouspopulation sub-groups is presented. This provides a better understanding of the nature ofmultidimensionaldeprivations,whichcanenabletargetedpolicyinterventions,forinstanceimprovingstandardsoflivinginbothurbanandruralareas.

The following sectionpresents results for poverty indices bydifferent subgroups/characteristics:Urban/Rural,Region,Sexofheadofhousehold,Mainlanguagespokeninthehousehold,Household-sizeandAge-group.

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a. Performance across Urban/Rural

Table3showsthedecompositionofpovertyresultsacrosstheurbanandruralareasinNamibia.Ofthetotalurbanpopulationinthecountry,25.3percentaremultidimensionallypoor. The proportion out of the rural area total population that is multidimensionally poor is59.3percent.

Theintensitylevelsindicatetheproportionofindicatorsinwhichmultidimensionallypoorpeoplearedeprived.Onaverage,everypoorindividualinurbanareasisdeprivedin39.6percentoftheweightedindicators,comparedto45.7percentforpoorindividualsinruralareas.

Furthermore,theMPIforurbanareasisreportedat0.100,whichislowerthantheruralareas MPI of 0.271. This reveals that multidimensional poverty is relatively more prevalent in rural areas.

Table 3. Poverty Measures by Urban/Rural

Area Population share (%) H A MPI

Value (%) CI Value

(%) CI Value (%) CI

Urban 47.0 25.3 22.2 28.3 39.6 38.6 40.6 0.100 0.087 0.113

Rural 53.1 59.3 56.5 62.2 45.7 44.7 46.8 0.271 0.256 0.287

National 100 43.3 41.0 45.6 44.0 43.2 44.9 0.191 0.180 0.202

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Figure4indicateswhetherthedifferencethatwasreportedintheincidenceofmultidimensionalpovertyacrossurbanand ruralareas fromTable3, isstatisticallysignificant.Sincethereisnooverlapintheconfidenceintervalsbetween urban and rural areas, the difference is statistically significant.Therefore, persons in rural areas have a significantly higher chance ofexperiencingmultipledeprivationsthanthoseinurbanareas.

Figure 4. Incidence of Multidimensional Poverty (H) by Urban/Rural Residence

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b. Performance across Region

Table 4 shows the decomposition of poverty results across the fourteen(14)administrative regionsofNamibia.The incidenceofmultidimensionalpoverty is highest in Kavango West (79.6%), Kavango East (70.0%) andKunene (64.1%).

Asforthepovertyintensitylevels,Kuneneregionreportedthehighestrateof59.2percent,whichindicatesthatonaverage,themultidimensionallypoorindividualsintheregionaredeprivedinabout59percentoftheweightedindicators.

This is followedbyOtjozondjupa (50.9%)andKavangoWest (48.5%).TheMPIishighestinKavangoWest(0.386),Kunene(0.379)andKavangoEast(0.332).

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Region Population share (%) H A MPI

Value (%) CI Value

(%) CI Value (%) CI

//Karas 3.8 19.6 12.9 26.2 39.4 35.8 43.1 0.077 0.047 0.107

Erongo 7.7 16.6 11.7 21.6 38.0 35.9 40.1 0.063 0.044 0.083

Hardap 3.8 26.9 18.3 35.5 40.4 38.4 42.4 0.109 0.071 0.146

Kavango East 5.8 70.0 62.3 77.7 47.4 45.0 49.7 0.332 0.291 0.372

Kavango West 4.0 79.6 73.0 86.2 48.5 46.7 50.3 0.386 0.348 0.424

Khomas 17.6 25.5 19.5 31.4 39.5 37.3 41.6 0.101 0.076 0.125

Kunene 4.0 64.1 54.2 74.1 59.2 55.0 63.3 0.379 0.304 0.455

Ohangwena 11.4 56.6 50.3 62.8 42.7 41.3 44.2 0.242 0.212 0.272

Omaheke 3.3 51.4 38.0 64.9 43.8 40.5 47.1 0.225 0.171 0.280

Omusati 11.2 50.7 43.8 57.7 41.2 39.1 43.2 0.209 0.177 0.241

Oshana 8.1 33.1 27.1 39.1 37.8 36.3 39.3 0.125 0.102 0.148

Oshikoto 8.3 50.0 43.1 56.9 42.8 40.6 45.0 0.214 0.181 0.247

Otjozondjupa 6.8 40.5 31.5 49.5 50.9 45.2 56.6 0.206 0.149 0.264

Zambezi 4.3 60.7 51.8 69.5 42.9 41.2 44.6 0.261 0.224 0.297

National 100.0 43.3 41.0 45.6 44.0 43.2 44.9 0.191 0.180 0.202

Table 4. Poverty Measures by Region

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Figure 5 indicates whether the differences that were reported in theincidence of multidimensional poverty across regions from Table 4, arestatisticallysignificant.SincetheconfidenceintervalreportedforKavangoWest, Kavango East and Kunene do overlap, it can be concluded thatpersons from these regions have equal chance of experiencingmultipledeprivations.Figure5also reveals that there is a significantdifference intheincidencereportedforKhomasandZambeziregions,sincethereisnooverlapintheirconfidenceintervals.

Figure 5. Incidence of Multidimensional Poverty (H) by Region

19.616.6

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Figure6shows thespatialdistributionof the incidenceofmultidimensionalpovertyin the country, aswell as the intensity levels. Just asobserved inTable4, Figure6indicatesthatKavangoWest,KavangoEastandKuneneregionshavethehighestratesofboththeprevalenceandthedepthofmultidimensionalpoverty.Incontrast,KarasandErongoregionsareamongstthosewiththelowestrateforboththeincidenceandseverity of multidimensional poverty.

Figure 6. Poverty Measures (Headcount and Intensity) by Region

Zambezi

Erongo

Hardap

//Karas

Kavango West

Khomas

Kunene

Ohangwena

Omaheke

OmusatiOshanaOshikoto

Otjozondjupa

Kavango East

(69.99,79.61](64.11,69.99](60.67,64.11](56.55,60.67](51.44,56.55](50.37,51.44](40.50,50.37](33.11,40.50](26.90,33.11](25.47,26.90](19.58,25.47][16.64,19.58]

Headcount Ratio

Incidence of Multidimensional Poverty Hin Namibia, k=30%

Zambezi

Erongo

Hardap

//Karas

Kavango West

Khomas

Kunene

Ohangwena

Omaheke


Otjozondjupa

Kavango East

(50.91,59.16](48.48,50.91](47.38,48.48](43.78,47.38](42.94,43.78](42.77,42.94](41.16,42.77](40.40,41.16](39.48,40.40](39.45,39.48](38.00,39.45][37.82,38.00]

Intensity

Intensity (A) of Multidimensional Povertyin Namibia, k=30%

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Figure7showsthespatialdistributionoftheincidenceofmultidimensionalpovertyinthecountry,i.e.,regionalmultidimensionalpovertyratesandnumberofpoorpeoplebyregionrespectively. The analysis was necessary to show that there may be some regions withrelativelylowerincidencerates,buthighnumbersofpoorpeoplebecausetheyhavelargerpopulations.Figure7indicatesthatKavangoWest,KavangoEastandKuneneregionshavethehighestratesofmultidimensionalpoverty.However,intermsofthepopulationcounts,theregionswiththehighestnumberofpoorpeopleareOhangwena,KhomasandOmusati.

Figure 7. Poverty Measures (Headcount rate and actual count of people) by Region

Zambezi

Erongo

Hardap

//Karas

Kavango West

Khomas

Kunene

Ohangwena

Omaheke


Otjozondjupa

Kavango East

(69.99,79.61](64.11,69.99](60.67,64.11](56.55,60.67](51.44,56.55](50.37,51.44](40.50,50.37](33.11,40.50](26.90,33.11](25.47,26.90](19.58,25.47][16.64,19.58]

Headcount Ratio


Zambezi

Erongo

Hardap

//Karas

Kavango West

Khomas

Kunene

Ohangwena

Omaheke


Otjozondjupa

Kavango East

(122097,138382](96066,122097](89180,96066](86989,89180](68353,86989](58770,68353](56198,58770](55057,56198](36269,55057](27478,36269](21966,27478][15771,21966]

Number of poor people

Number of people living inmultidimensional poverty

in Namibia, k=30%

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c. Performance across Sex of Head of Household

Table5showsthedecompositionofpovertyresultsbetweenmaleandfemale-headedhouseholds in Namibia. Of the total population that comes from female-headedhouseholds,46.2percentaremultidimensionalpoor.Conversely,theproportionoutofthemale-headedhouseholds’populationisloweratabout40.8percent.

Theintensitylevelsindicatethatonaverage,everypoorindividualinafemale-headedhouseholdisdeprivedinabout43.4percentoftheindicators,comparedtoabout44.7percentforpoorindividualsinmale-headedhouseholds.

Furthermore, theMPI for thepopulation that resides in female-headedhouseholds isreportedat0.201,whilethepopulationthatresidesinmale-headedhouseholdsreportedan MPI of 0.182.

Table 5. Poverty Indicators by Sex of Head of Household

Sex of head of house-hold

Population share (%) H A MPI

Value (%) CI Value

(%) CI Value (%) CI

Female 47.2 46.2 43.5 48.9 43.4 42.3 44.5 0.201 0.187 0.214

Male 52.8 40.8 38.0 43.5 44.7 43.6 45.9 0.182 0.169 0.196

National 100 43.3 41.0 45.6 44.0 43.2 44.9 0.191 0.180 0.202

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Figure8indicateswhetherthedifferencethatwasreportedintheincidenceof multidimensional poverty across female andmale headed householdsfromTable5, isstatisticallysignificant.Althoughthe incidencefor female-headedhouseholdsishigherthanthatofthemale-headedhouseholds,asreportedintable5,thedifferenceisnotstatisticallysignificantsincethereisanoverlapintheconfidenceintervals.

Figure 8. Incidence of Multidimensional Poverty (H) by Sex of Head of Household

d. Performance across Main language spoken in the Household

Table6showsthedecompositionofpovertyresultsacrossdifferentlanguagegroupsspokeninNamibia.Thehighestheadcountratioofmultidimensionalpoverty is reported amongst the population whose main language spoken athome isKhoisan (93.4%), followedbyRukavango (67.8%)andZambezilanguages (54.2%). The population whose main spoken language is English and German reported the lowest headcount ratios of multidimensionalpoverty,eachwithabout3percent.

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The intensity levels indicate that on average, the depth of poverty is higher amongst thepopulationwhosemain spoken language at home is Khoisan (61.5%),Otjiherero (54.3%),OtherAfricanlanguages(47.5%)andRukavango(47.2%).Thelowestintensityratioisreportedamongst the population whose main spoken language is other European (37.2%), whichindicatesthatofthispopulationsub-group,thosethataremultidimensionallypooraredeprivedin37.2percentofthetotalnumberofindicators.

Furthermore,thehighestMPIwasreportedforthepopulationthatmainlyspeaksKhoisan,at0.575.

Language Population share (%) H A MPI

Value (%) CI Value

(%) CI Value (%) CI

Khoisan 1.4 93.4 85.9 100.9 61.5 54.5 68.6 0.575 0.482 0.667

Zambezilanguages 4.3 54.2 45.0 63.5 42.5 40.8 44.1 0.230 0.193 0.267

Otjiherero 8.8 43.6 35.6 51.7 54.3 50.5 58.0 0.237 0.185 0.288

Rukavango 11.4 67.8 62.9 72.7 47.2 45.8 48.6 0.320 0.294 0.346

Nama/Damara 12.0 43.3 37.9 48.8 43.4 41.5 45.4 0.188 0.162 0.214

Oshiwambo 51.3 42.9 39.9 45.8 40.6 39.7 41.4 0.174 0.160 0.188

Setswana 0.2 15.0 0.4 29.6 40.3 31.8 48.8 0.060 0.001 0.120

Afrikaans 6.5 7.4 4.0 10.8 38.2 34.2 42.3 0.028 0.014 0.043

German 0.2 2.6 -2.7 7.9 38.9 38.9 38.9 0.010 -0.011 0.031

English 1.1 3.3 -0.7 7.3 39.6 29.7 49.4 0.013 -0.004 0.030

Other European 0.4 9.9 1.7 18.1 37.2 33.2 41.3 0.037 0.009 0.065

OtherAfrican 0.7 14.6 9.2 20.1 47.5 43.0 51.9 0.069 0.045 0.094

Other 1.7 14.8 5.8 23.9 43.7 38.0 49.4 0.065 0.022 0.108

National 100.0 43.3 41.0 45.6 44.0 43.2 44.9 0.191 0.180 0.202

Table 6: Poverty Indicators by Main Spoken language

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Figure 9 indicates whether the differences that were reported in theincidence of multidimensional poverty across main language spoken inTable 6 are statistically significant or not. Since the standard error barsreported for persons whose main spoken language is Khoisan does not overlapwithotherlanguages,itcanbeconcludedthatpersonswhomainlyspeakKhoisanhaveasignificantlyhigherchanceofexperiencingmultipledeprivations.Figure9alsorevealsthatthereisnosignificantdifferenceinthe incidencereportedforZambezi languages,Otjiherero,Nama/DamaraandOshiwambolanguages,sincethereisanoverlapintheirstandarderrorbars.

Figure 9. Incidence of Multidimensional Poverty (H) by Main Language Spoken

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Figure 10 shows the distribution of the number of multidimensionally poor peopleacrossmainlanguagespoken.Theanalysiswasnecessarytoshowthattheremaybesomelanguageswithrelativelylowerincidencerates,buthighnumbersofpoorpeoplebecausetheyhavelargerpopulations.Whiletable6indicatesthatthehighestincidencerateswerereportedforKhoisan,followedbyRukavangoandZambezi languages,figure10shows thatoutofthemultidimensionallypoorpeople,thehighestpopulationcountswerereported for people who mainly speak Oshiwambo (50.7%), Rukavango(17.9%)andNama/Damara(12.0%)languages.

Figure 10. Distribution of the Number of Multidimensionally Poor People by Main Language Spoken

3.1% Khoisan 5.3% Zambezi languages 8.8% Otjiherero 17.9% Rukavango

12.0% Nama/Damara 50.7% Oshiwambo 0.1% Setswana 1.1% Afrikaans

0.0% German 0.1% English 0.1% Other European 0.2% Other African

0.6% Other

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e. Performance across Household size

Table7showsthedecompositionofpovertyresultsacrossvarioushouseholdsizegroupsinthecountry.

Table 7 indicates that the headcount ratio increases as the household size increases.Thehighestheadcountratioisfoundamonghouseholdsthathave7ormoremembers,reportedat55.2percentandthelowestisreportedforthehouseholdswithlessthan4members,reportedat31.1percent.

The highest intensity level of multidimensional poverty is reported amongst persons whosehouseholdsizeis4-6;and7ormoremembersat44.5percenteach.

The MPI value is highest for the population that resides in households with 7 or more members.

Table 7. Poverty Measures by Household Size

HH Size Population share (%) H A MPI

Value (%) CI Value

(%) CI Value (%) CI

1-3 23.3 31.1 28.8 33.4 41.6 40.9 42.4 0.129 0.120 0.139

4-6 36.7 38.2 35.6 40.8 44.5 43.5 45.5 0.170 0.158 0.182

7+ 40.0 55.2 51.7 58.7 44.5 43.3 45.8 0.246 0.229 0.263

National 100 43.3 41.0 45.6 44.0 43.2 44.9 0.191 0.180 0.202

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Figure 11 indicates whether the differences that were reported in theincidenceofmultidimensionalpovertyacrosshouseholdsizefromTable7,arestatisticallysignificant.Sincetheconfidenceintervalsdonotoverlapforall the reportedhouseholdsizes, itcanbeconcluded that thechancesofexperiencingmultipledeprivationsincreaseashouseholdsizealsoincrease.

Figure 11. Incidence of Multidimensional Poverty (H) by Household Size

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f. Performance across Age Groups

Table8 shows thedecompositionofpoverty resultsacrossvariousagegroups in thecountry.

Thehighestheadcountratioisreportedfortheyoungeragegroupsi.e.0-4years(56.2%),5-9years(49.9%)and10-14years(48.5%).Thelowestheadcountratio(32.7%)isreportedfortheagegroupof25-29years,toimplythatofallpersonsaged25-29years,about33percentaremultidimensionallypoor.

The highest intensity level of multidimensional poverty is reported amongst the 5-9 years’ age group (45.7%). The depth of poverty is lowest for the age group of 25-29 years (41.0 %).

Furthermore,thehighestMPIvaluewasreportedforthepopulationaged0-4years.

Table 8. Poverty Indicators by Age Groups (years)

Age groups


Value (%) CI Value

(%) CI Value (%) CI

0-4 13.6 56.2 53.5 59.0 45.2 44.2 46.3 0.254 0.240 0.269

5-9 11.9 49.9 47.0 52.9 45.7 44.4 47.0 0.228 0.213 0.244

10-14 10.4 48.5 45.4 51.5 44.8 43.7 45.8 0.217 0.202 0.232

15-19 10.7 46.3 43.2 49.4 43.4 42.3 44.5 0.201 0.186 0.216

20-24 10.2 36.9 34.0 39.9 42.0 40.8 43.1 0.155 0.142 0.169

25-29 9.0 32.7 29.9 35.4 41.0 39.9 42.1 0.134 0.123 0.145

30-34 7.2 35.0 32.1 37.9 43.5 42.3 44.7 0.152 0.139 0.166

35-60 21.0 37.1 34.7 39.4 43.7 42.8 44.6 0.162 0.151 0.173

61+ 6.1 45.4 42.3 48.4 44.5 43.5 45.4 0.202 0.187 0.216

Total 100 43.3 41.0 45.6 44.0 43.2 44.9 0.191 0.180 0.202

41


MULTIDIMENSIONAL

Figure12indicateswhetherthedifferencesthatwerereportedintheincidenceofmultidimensionalpovertyacrossagegroupsfromTable8,arestatisticallysignificantornot.Sincetheconfidenceintervalsreportedforagegroup0-4doesnotoverlapwithanyotheragegroup,itcanbeconcludedthatpersonsaged0-4yearshaveasignificantlyhigherchanceofexperiencingmultipledeprivations.Figure12furthershowsthatthereisnosignificantdifferenceintheincidencesreportedforagegroups5-9,10-14,15-19and61+sincethereisanoverlapintheconfidenceintervals,whilethereisnosignificantdifferencebetweentheagegroups20-24,25-29,30-34and35-60.

Figure 12. Incidence of Multidimensional Poverty (H) Age Groups

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

0-4 5-9 10-14 15-19 20-24 25-29 30-34 35-60 61+

Incid

ence

of

mul

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over

ty (H

) In

cide

nce

of M

ultid

imen

sion

al P

over

ty(H

)

42


MULTIDIMENSIONAL

3.3. Decomposition of Censored Headcount Ratios

This sub-section presents the censored headcount ratio of indicators across urban/rural and regions. The censored headcount ratio of a certain indicator is defined as the proportion of the total population that is deprived in that specific indicator, and also multidimensionally poor.

Figure 13 shows the censoredheadcount ratiosbetweenurban and ruralareas.Resultsshowthatoverall,ruralareashavethehighestproportionofpeoplethataremultidimensionallypooranddeprivedinall the indicatorscomparedtourbanareas.CookingandLightingEnergy,aswellasSanitationarethetwoindicatorswiththehighestcensoredheadcountratiosforruralandalmostinurbanareasrespectively.ThelowestcensoredheadcountratioforurbanareasisreportedforDrinkingWater(0.5%)whileforruralareas,ICTreportedthelowestat5.1percent.

Figure 13. Censored Headcount Ratios by Urban/Rural

4.1 4.70.5

22.516.8

24.2

0.8

19.3

1.2

16.312.313.9 13.0

21.0

56.3

43.4

56.2

5.1

58.4

15.0

32.4 29.5

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

%

UrbanRural

43


MULTIDIMENSIONAL

Table 9 on page 44, shows the censored headcount ratios across the 14administrative regions of Namibia. The table shows that ICT is the onlyindicatorwiththelowestproportionofpeoplethatarepooranddeprivedacross all regions. Indicators such as Sanitation, Housing, TransportationAssets,andCookingandLightingEnergyareamongsttheindicatorswiththehighestproportionsofpeoplethatarepooranddeprivedinthosespecificindicatorsacrossall regions.Furthermore, the table shows thatKunene isone of the regions that has the highest proportion of the poor and deprived in most of the indicators such as Cooking and Lighting Energy (63.0%),TransportationAssets(61.3%),Sanitation(59.3%)andHousing(52.6%).

44


MULTIDIMENSIONAL

Similarly,Erongoisamongtheregionswiththelowestproportionofitspopulationthatispooranddeprivedinmostoftheindicatorsi.e.ICT(0.4%),DrinkingWater(2.7%),SchoolAttendance(3.5%)andAccesstoClinics/Hospitals(4.8%).

Region

Popu

latio

n sh

are

(%)

Scho

ol a

tten

danc

e

Year

s of

sch

oolin

g

Drin

king

wat

er

Sani

tatio

n

Hou

sing

Tran

spor

tatio

n A

sset

s

ICT

Cook

ing

and

Ligh

ting

Ener

gy

Acc

ess

to C

linic

s/H

ospi

tals

Food

sec

urity

Child

Nut

ritio

n

//Karas 3.8 3.5 6.2 2.7 13.6 10.4 19.0 0.4 13.9 4.8 9.3 9.9

Erongo 7.7 3.9 2.2 2.2 15.0 12.8 14.5 0.7 10.2 1.7 10.8 4.6

Hardap 3.8 6.4 8.6 1.2 21.1 18.5 26.2 2.7 19.7 3.7 12.5 11.7

Kavango East 5.8 11.1 13.4 28.9 68.4 52.9 68.7 8.9 69.2 8.0 60.2 30.9

Kavango West 4.0 14.4 21.3 32.1 76.2 71.0 78.2 6.7 79.3 11.8 63.8 33.8

Khomas 17.6 4.3 4.2 0.0 23.7 16.9 24.5 0.7 16.9 2.8 15.2 13.6

Kunene 4.0 37.4 36.5 36.0 59.3 52.6 61.3 11.7 63.0 31.0 36.6 21.5

Ohangwena 11.4 7.9 8.4 19.5 54.7 41.4 54.1 1.6 56.3 12.0 24.7 35.6

Omaheke 3.3 18.1 17.2 5.8 42.3 26.5 47.3 6.4 49.6 24.6 15.8 22.4

Omusati 11.2 8.2 8.0 16.7 50.2 32.0 46.3 3.0 50.5 6.9 18.9 31.2

Oshana 8.1 4.8 4.5 1.6 26.9 22.1 31.7 0.9 32.1 1.2 17.3 16.2

Oshikoto 8.3 9.4 7.3 12.2 49.3 32.3 46.5 1.9 49.5 14.3 26.9 25.1

Otjozondjupa 6.8 17.7 13.1 9.3 34.6 25.9 38.3 4.3 34.6 14.8 25.3 21.0

Zambezi 4.3 7.9 6.5 13.7 58.7 57.1 59.2 6.3 58.8 3.4 51.7 17.9

Table 9. Censored Headcount Ratios by Regions

45


MULTIDIMENSIONAL

3.4. Comparison of the MPI to the monetary measure

As mentioned earlier, since 2003, Namibia has adopted the Cost-Of-Basic-NeedsApproach(CBNA)tomeasuremonetarypoverty.To-date,threepovertylineshavebeenreleasedbytheNSA,namely,theFoodPovertyLine(FPL)–thresholdforfoodpoverty;TheLowerBoundPovertyLine(LBPL)–thresholdfortheseverelypoor;andtheUpperBoundPovertyLine(UBPL)–thresholdforthepoor.

This sub-section presents a comparison between the Multidimensional Poverty index and the 2015/16 monetary poverty rates by region using the UBPL. Table 10 (page 46) and Figure 14 show a comparison of the monetary and multidimensional poverty rates, and indicates that Kavango East, Kavango West, Kunene, Omaheke, Omusati, Zambezi regions are amongst those with the highest poverty rates for both measures. Conversely, Erongo and Karas regions are amongst those with the least poverty rates for both monetary and multidimensional poverty measures.

Figure 14. Spatial comparison of poverty measures

Zambezi

Erongo

Hardap

//Karas

Kavango West

Khomas

Kunene

Ohangwena

Omaheke


Otjozondjupa

Kavango East

(69.99,79.61](64.11,69.99](60.67,64.11](56.55,60.67](51.44,56.55](50.37,51.44](40.50,50.37](33.11,40.50](26.90,33.11](25.47,26.90](19.58,25.47][16.64,19.58]

Headcount Ratio


Zambezi

Erongo

Hardap

//Karas

Kavango West

Khomas

Kunene

Ohangwena

Omaheke


Otjozondjupa

Kavango East

(37.9,41.5](34.2,37.9](33.4,34.2](27.8,33.4](20.2,27.8](17.15,20.2](14,17.15](10.7,14](9.7,10.7](9.2,9.7](4.7,9.2][3.7,4.7]

Poverty rate

Money−metric poverty measure based on the Upper Bound Poverty Line (UPBL)

in Namibia

46


MULTIDIMENSIONAL

Region Total Population Monetary poor MPI poor

//Karas 80561 7409 9.2 15771 19.6

Erongo 165138 6106 3.7 27478 16.6

Hardap 81650 8726 10.7 21966 26.9

Kavango East 124286 51538 41.5 86989 70.0

Kavango West 85863 23854 27.8 68353 79.6

Khomas 377192 17846 4.7 96066 25.5

Kunene 85883 32536 37.9 55057 64.1

Ohangwena 244704 35738 14.6 138382 56.6

Omaheke 70511 24087 34.2 36269 51.4

Omusati 240629 48520 20.2 122097 50.7

Oshana 175053 16930 9.7 57966 33.1

Oshikoto 178370 25010 14.0 89180 50.0

Otjozondjupa 147087 29045 19.7 59574 40.5

Zambezi 92630 30910 33.4 56198 60.7

Namibia 2149556 358254 16.7* 931345 43.3

Table 10. Comparison of poverty measures, by regions

*Cautionary note: The monetary poverty rate differs from the one published in the NHIES 2015/16 basic report, due to a difference in sample size based on the MPI methodology

47


MULTIDIMENSIONAL

Given thatmonetary poverty assessment using consumption expenditurehasbeen theconventionalmeasureofpoverty inNamibia, it is crucial tocompare the twomeasures in this contextual analysis. Figure15presentsthecomparisonbetweenmulti-dimensionalpovertywith theconsumptionexpenditurepovertyestimate.Figure15indicatesthatapproximately12.5percentofpeople inNamibiaarebothmulti-dimensionally andmonetarypoor. The figure further displays that 30.8 percent of the population aremulti-dimensionally poor but notmonetary poor, suggesting that incomealoneisnotagoodpredictorofpovertyacrossthepopulation.Moreover,52.5percentofpeopleareneithermulti-dimensionallynormonetarypoor.

Figure 15. Venn Diagram Showing Overlaps between National Monetary and Multidimensional Poverty Rates*


Non-poor = 52.5%

4.2% 12.5% 30.8%

Total Population Monetary Multidimensional

48


MULTIDIMENSIONAL

4. Poverty measures based on the child population.

This sectionpresents themultidimensionalpoverty results that aremainlybasedonchildren,aged0-17years,whosepopulationshareis42.6percentout of the total population. In order to provide an insight on the nature anddepthofmultidimensional poverty amongst children inNamibia, thesections begin by comparing poverty measures between children (aged0-17years)andadults(aged18yearsorolder).Thesectionfurtherpresentsa decomposition of the child-based poverty measures, across variousdemographic characteristics. The section concludeswith a comparisonofchildmultidimensionalandmonetarypovertyrates.

4.1 Profiling child-based multidimensional poverty in Namibia

a. Uncensored headcount ratios of the MPI indicators

49


MULTIDIMENSIONAL

Figure 16. Child and Adult Specific National Uncensored Headcount Ratio

10.5 13.6 17.9

72.7

51.5

79.5

3.8

71.3

12.5

32.1 34.5

9.0 7.5 12.4

66.1

44.7

73.8

3.2

60.0

11.4

26.5 20.9

0.010.020.030.040.050.060.070.080.090.0

%

Children(0-17)

Adults (>17)

Figure16showstheproportionthatisdeprivedineachofthe11indicatorsoftheMPI,bythetwo-agegroups:childrenandadults.Thedatashowthatchildren(0-17)aremoredeprivedinallindicatorscompareadults.WhilethehighestdeprivationlevelswerereportedinTransportationAssets,CookingandLightingEnergyandSanitationforbothagegroups,theproportionsarerelativelyhigheramongstthechildrenpopulation.

ThelowestdeprivationlevelsamongstthechildrenpopulationwerereportedinICT(3.8%),followedbySchoolAttendance(10.5%)andthirdlybyAccesstoClinics/Hospitals(12.5%).

50


MULTIDIMENSIONAL

b. The level of multidimensional poverty amongst children in Namibia

Table11showsthethreemainindicatorsofmultidimensionalpoverty;Headcountratio(H),Intensity(A)andtheAdjustedheadcountratio(MPI)basedonthetwopopulationagegroups(childrenandadults).

ThetableshowsthatoutofthepopulationofchildreninNamibia51.3percentarelivingin multidimensional poverty. The intensity of multidimensional poverty (A) amongst the childrenpopulationis45.1percent,whiletheadultpopulation’sintensityrateisreportedat43.0percent.

TheMPIis0.231forchildren(0-17years),whichishigherthanofadults(18+years)of0.161.

Table 11. Child and Adult Specific Incidence, intensity and Multidimensional Poverty Index


Value (%) CI Value

(%) CI Value (%) CI

Children(0-17) 42.6 51.3 0.49 0.54 45.1 0.44 0.46 0.231 0.218 0.244

Adults (>17) 57.4 37.4 0.35 0.40 43.0 0.42 0.44 0.161 0.151 0.171

National 100 43.3 41.0 45.6 44.0 43.2 44.9 0.191 0.180 0.202

51


MULTIDIMENSIONAL

c. Child and Adult-based censored headcount ratios of the MPI indicators

Figure17showsthecensoredheadcount ratiopereachof the indicators,forthetwo(2)agegroups.FromFigure17,resultsshowthatforbothagegroups,thehighestproportionofpeoplethataremultidimensionallypooranddeprivedperspecificindicatorarereportedforInadequatetransportationassets, followedbyadequatesanitation,cookingand lightingenergyandadequate housing. It is worth noting that the censored headcount ratiosarerelativelyhigherforthechildrenpopulation,inallindicators.Thelowestcensored headcount ratio for the children population is reported for ICTequipment(3.4%)andAccesstoclinics/hospitals(9.9%).

Figure 17. Child and Adult Specific National Censored Headcount Ratio

10.212.4

14.2

48.1

37.0

48.7

3.4

48.0

9.9

28.7 28.7

8.66.6

9.2

34.7

26.4

35.6

2.8

34.1

7.5

22.0

16.0

0.0

10.0

20.0

30.0

40.0

50.0

60.0

%

Children(0-17)

Adults (>17)

52


MULTIDIMENSIONAL

d. Percentage contribution of each indicator to the child and adult specific MPI

Figure 18 shows the percentage contribution of eachweighted indicatortotheoverallmultidimensionalpovertyindexfortherespectiveagegrouppopulations,childrenandadults.Figure18shows that the indicators thatcontribute the highest to children multidimensional poverty in NamibiaareFoodSecurityandChildUndernutritionallat16.6percent,InadequateTransportationAssets(11.7%),Sanitation(11.6%),andUnsafeCookingandLighting Energy (11.5%).

Figure 18. Percentage Contribution of each Indicator to Child and Adult MPI

8.9

10.6

7.2

5.5

3.4

3.2

11.6

12.0

8.9

9.1

11.7

12.3

0.8

1.0

11.5

11.8

2.9

3.1

16.6

18.2

16.6

13.3

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0

Children(0-17)

Adults (>17)

%

School attendance Years of schooling Drinking water

Toilet Housing Transportation Assets

ICT Cooking and Lighting Energy Access to Clinics/Hospitals

Food security Child Nutrition

53


MULTIDIMENSIONAL

4.2. Decomposition of child-based poverty indicators

In order to examine the disparities in the prevalence and distribution of childrenmultidimensionalpovertyinNamibia,thissectionpresentsthedecompositionsofchild-basedmultidimensionalpovertyindicatorsacrossUrban/ruralareas,Region,Sexofheadofhousehold,andchildspecificage-groups.

a. Performance across Urban/Rural

Table12 shows thedecompositionof childpoverty results across theurbanand ruralareasinNamibia.Ofthetotalpopulationofchildreninurbanareas,about30.4percentaremultidimensionalpoor,while,theproportionoutofthetotalpopulationofchildreninruralareasthatismultidimensionallypooris64.4percent.

The intensity levels indicate the proportion of indicators in which multidimensionallypoorchildrenaredeprived.Onaverage,everypoorchildinurbanareasisdeprivedin40.3percentoftheindicators,comparedto46.5percentforpoorchildreninruralareas.Furthermore,MPIforruralareasisreportedat0.299,whichishigherthantheMPIvaluefor urban areas reported at 0.123.

Table 12. Child-based Poverty measures by urban/rural

Area Population share (%) H A MPI

Value (%) CI Value

(%) CI Value (%) CI

Urban 38.6 30.4 26.6 34.3 40.3 39.2 41.4 0.123 0.106 0.139

Rural 61.4 64.4 61.4 67.3 46.5 45.3 47.7 0.299 0.283 0.316

National 100.0 51.3 48.7 53.8 45.1 44.1 46.1 0.231 0.218 0.244

54


MULTIDIMENSIONAL

Figure19 indicateswhetherthedifferencethatwasreported inthechild-based incidence of multidimensional poverty across urban and ruralareas from table12 is statistically significant. Since there is nooverlap inthe confidence intervals between urban and rural areas, thedifference isstatisticallysignificant.Therefore,childreninruralareashaveasignificantlyhigher chance of experiencingmultiple deprivations than those in urbanareas.

Figure 19. Child-Based Incidence of Multidimensional Poverty (H) by Urban/Rural

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

Urban Rural

Incid

ence

of

mul

tidim

ensio

nal p

over

ty (H

) In

cide

nce

of M

ultid

imen

sion

al P

over

ty(H

)

55


MULTIDIMENSIONAL

b. Performance across Regions

Table13(page56)showsthedecompositionofchildren-basedpovertyresultsacrossthefourteen(14)administrativeregionsofNamibia.TheincidenceofmultidimensionalpovertyishighestinKavangoWest(82.3%),KavangoEast(74.7%)andKunene(69.2%).Asforthechildpovertyintensitylevels,Kuneneregion reported thehighest rateof 62.9percent,which indicates thatonaverage, themultidimensionally poor children in the region are deprivedin about 63 percent of the indicators. This is followed by Otjozondjupa,reportedat52.6percent.

56


MULTIDIMENSIONAL

Region Population share (%) H A MPI

Value (%) CI Value

(%) CI Value (%) CI

//Karas 3.1 21.1 13.4 28.9 39.8 35.1 44.5 0.084 0.048 0.121

Erongo 5.7 15.7 9.2 22.1 37.5 34.8 40.3 0.059 0.033 0.084

Hardap 3.4 30.0 19.3 40.6 40.3 38.0 42.6 0.121 0.074 0.167

Kavango East 6.7 74.7 67.5 81.9 48.7 46.1 51.3 0.363 0.323 0.404

Kavango West 5.2 82.3 76.1 88.5 48.9 47.2 50.6 0.402 0.365 0.439

Khomas 13.3 32.6 24.3 40.9 40.2 37.9 42.4 0.131 0.096 0.166

Kunene 4.5 69.2 58.5 79.8 62.9 58.5 67.3 0.435 0.348 0.522

Ohangwena 13.9 64.1 58.1 70.0 43.3 41.9 44.8 0.278 0.248 0.307

Omaheke 3.4 53.6 37.7 69.6 43.7 39.6 47.8 0.234 0.170 0.298

Omusati 12.6 55.8 48.7 62.9 41.6 39.5 43.8 0.232 0.199 0.266

Oshana 7.5 38.5 31.1 45.9 38.1 36.6 39.6 0.147 0.118 0.175

Oshikoto 9.1 57.4 50.5 64.4 43.5 40.8 46.1 0.250 0.214 0.285

Otjozondjupa 6.9 43.5 33.5 53.6 52.6 46.3 58.9 0.229 0.163 0.295

Zambezi 4.7 66.2 57.4 75.0 44.0 42.0 46.0 0.291 0.253 0.330

National 100.0 51.3 48.7 53.8 45.1 44.1 46.1 0.231 0.218 0.244

Table 13. Child-based Poverty measures by urban/rural

57


MULTIDIMENSIONAL

Figure20indicateswhetherthedifferencesthatwerereportedinthechild-basedincidenceofmultidimensionalpovertyacrossregionsfromTable13,arestatisticallysignificant.Sincetheconfidenceintervalsreportedfor//Karas,ErongoandHardapregionsdooverlap, itcanbeconcludedthatpersonsfromtheseregionshaveequalchanceofexperiencingmultipledeprivations.Figure20alsorevealsthatthereisasignificantdifferenceintheincidencereportedforKuneneandOshanaregions,sincethereisnooverlapintheirconfidenceintervals.

Figure 20. Child-Based Incidence of Multidimensional Poverty (H) by Region

21.1

15.7

30.0

74.782.3

32.6

69.2

64.1 53.655.8

38.5

57.4

43.5

66.2

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

Incid

ence

of

mul

tidim

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nal p

over

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) In

cide

nce

of M

ultid

imen

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over

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)

58


MULTIDIMENSIONAL

Figure 21 shows the spatial distribution of the prevalence of childmultidimensionalpovertyinthecountry,aswellastheintensitylevels.

ThefigurealsoindicatesthatKavangoWest,KavangoEastandKuneneregionshavethehighestratesofboththeprevalenceandthedepthofchildmultidimensionalpovertyinthecountry.

Figure 21. Spatial Distribution of Child Poverty Measures by Region

Zambezi

Erongo

Hardap

//Karas

Kavango West

Khomas

Kunene

Ohangwena

Omaheke


Otjozondjupa

Kavango East

(74.7,82.3](69.2,74.7](66.2,69.2](64.1,66.2](57.4,64.1](54.7,57.4](43.5,54.7](38.5,43.5](32.6,38.5](30,32.6](21.1,30][15.7,21.1]

Poverty Rate

Child Specific Incidence ofMultidimensional Poverty (H)

in Namibia, k=30%

Zambezi

Erongo

Hardap

//Karas

Kavango West

Khomas

Kunene

Ohangwena

Omaheke


Otjozondjupa

Kavango East

(52.6,62.9](48.9,52.6](48.7,48.9](44,48.7](43.7,44](43.4,43.7](41.6,43.4](40.3,41.6](40.2,40.3](39.8,40.2](38.1,39.8][37.5,38.1]

Intensity

Child Specific Intensity (A) ofMultidimensional Poverty

in Namibia, k=30%

59


MULTIDIMENSIONAL

Figure 22 shows the spatial distribution of the incidence ofmultidimensional povertyamongstchildrenaged0-17yearsinthecountry,i.e.,regionalmultidimensionalpovertyratesandnumberofpoorpeoplebyregionrespectively.Theanalysiswasnecessarytoshowthattheremaybesomeregionswithrelativelylowerincidencerates,buthighnumbersofpoorpeoplebecausetheyhavelargerpopulations.Figure22indicatesthatKavangoWest,Kavango East and Kunene regions have the highest rates of multidimensional poverty. However, in terms of the population counts of children, the regions with the highestnumberofmultidimensionallypoorchildrenareOhangwena,OmusatiandOshikoto.

Figure 22. Child-based Poverty Measures (Headcount rate and actual count of children) by Region

Zambezi

Erongo

Hardap

//Karas

Kavango West

Khomas

Kunene

Ohangwena

Omaheke


Otjozondjupa

Kavango East

(74.7,82.3](69.2,74.7](66.2,69.2](64.1,66.2](57.4,64.1](54.7,57.4](43.5,54.7](38.5,43.5](32.6,38.5](30,32.6](21.1,30][15.7,21.1]

Poverty Rate

Child Specific Incidence ofMultidimensional Poverty (H)

in Namibia, k=30%

Zambezi

Erongo

Hardap

//Karas

Kavango West

Khomas

Kunene

Ohangwena

Omaheke


Otjozondjupa

Kavango East

(64611,81605](47640,64611](45701,47640](39660,45701](38979,39660](28378,38979](27388,28378](26603,27388](16858,26603](9425,16858](8144,9425][6081,8144]

Number of poor children (0−17 years)

Number of children living inmultidimensional poverty

in Namibia, k=30%

60


MULTIDIMENSIONAL

c. Performance across Sex of head of Household

Table14 shows thedecompositionof childpoverty resultsbetweenmaleand femaleheadedhouseholdsinNamibia.Ofthetotalchildrenpopulationthatresidesinfemaleheaded households, about 53 percent are multidimensional poor. Conversely, theproportionoutofthechildrenpopulationthatresidesinmaleheadedhouseholdswhoaremultidimensionalpoorisabout50percent.

The intensity levels indicate that on average, every multidimensionally poor child ina female headed household is deprived in 44.5 percent of the weighted indicatorscomparedto45.8percentforthepoorchildreninmaleheadedhouseholds.

Furthermore,theMPIforthechildrenpopulationwhoresidesinfemaleheadedhouseholdsis reported at 0.234 while for those children residing in male headed households isreported at 0.228

Table 14. Child-based Poverty measures by Sex of head of household

Sex of head of house-hold


Value (%) CI Value

(%) CI Value (%) CI

Female 53.1 52.7 49.7 55.6 44.5 43.2 45.7 0.234 0.219 0.249

Male 46.9 49.7 46.3 53.0 45.8 44.5 47.2 22.8 21.1 24.5

National 100.0 51.3 48.7 53.8 45.1 44.1 46.1 0.231 0.218 0.244

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Figure23 indicateswhether thedifference thatwas reported in thechild-based incidence of multidimensional poverty across female and maleheadedhouseholds fromTable14, is statistically significant.Although thechild-basedincidenceforfemale-headedhouseholdsishigherthanthatofthemale-headedhouseholds,asreportedintable14,thedifferenceisnotstatisticallysignificantsincethereisanoverlapintheconfidenceintervals.

Figure 23. Child-Based Incidence of Multidimensional Poverty (H) by Sex of Head of Household

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d. Performance across child-specific age group

Table15 shows thedecompositionof child-basedpoverty results across child-specificage groups.

Thehighestheadcountratioisreportedfortheagegroupof2-4years(57.3%)followedby the age group of 1 years or less (54.7%).

Thetablefurthershowsthattheintensitylevelsofchild-basedmultidimensionalpovertyis fairlyconstantacrossagegroups,thehighestreportedforthe2-4years’agegroup(45.6%) and the lowest reported for the 15-17 years’ age group (44.2%).

Furthermore,thehighestMPIwasreportedforchildrenintheage-groupof2-4years,at0.261.

Table 15. Child Poverty Indicators by age-groups

Age group


Value (%) CI Value

(%) CI Value (%) CI

<=1 13.2 54.7 51.4 58.0 44.7 43.6 45.8 0.245 0.229 0.260

2-4 18.7 57.3 54.3 60.2 45.6 44.4 46.8 0.261 0.246 0.277

5-14 52.4 49.2 46.5 52.0 45.3 44.2 46.4 0.223 0.209 0.237

15-17 15.7 47.9 44.6 51.2 44.2 43.0 45.4 0.212 0.196 0.227

National 100 51.3 48.7 53.8 45.1 44.1 46.1 0.231 0.218 0.244

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Figure 24. Child-Based Incidence of Multidimensional Poverty (H) by Age Groups

Figure 24 indicates whether the differences that were reported in thechild-based incidence of multidimensional poverty across age groupsfromTable15,arestatisticallysignificantornot.Althoughthechild-basedincidencereportedforagegroup2-4ismorethanthatofagegroup<=1,thedifferenceisnotstatisticallysignificantsincethereisanoverlapintheconfidenceintervals.

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4.3. Comparison of the child-based MPI to the monetary measure

Figure25indicatesthatapproximately16.1percentofchildrenaged0-17years in Namibia are both multi-dimensionally and monetary poor. About 35.2percentofchildrenaremulti-dimensionallypoorbutnotmonetarypoor,suggesting that income alone is not a good predictor of poverty amongchildren. The figure further shows that that 44.2 percent of children areneither multi-dimensionally nor monetary poor.

Figure 25. Comparison between monetary and non-monetary child poverty rates*


Non-poor = 44.2%

4.5% 16.1% 35.2%

Total Population Monetary Multidimensional

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Robustness checkswere carriedout inorder toassess the stabilityof theMPImeasuresandconfirmthattheresultspresentedwouldnothavebeensignificantlydifferent,evenifapovertycutoff(k)thatisdifferentfrom30%wasused.Table16presentstheSpearmanandKendalltaubrankcorrelationcoefficients using the poverty cut-off k=30%, and the ranking of the 14regionsforalternativepovertycut-offsof20%and40%.Table16showsthattheKendallTau-bis0.87atk=20%and0.89atk=40%indicatingthatamongthewholepopulation,theregionalrankingsarepreservedtoalargeextentunderthesealternativechoices.

SimilarresultsareobtainedwhenusingtheSpearmancoefficient.Table16showsthatSpearmancoefficientis0.96atk=20%and0.97atk=40%.Thismeansthattherankcorrelationbetweenthepovertycut-offs(from20%to30%,from30%to40%)ispreservedtoalargeextentunderthesealternativechoices.

Robustness checks.

Table 16. Spearman and Kendall Tau-b

K=30%

Alternativek=20% Spearman 0.96

Kendall Tau-b 0.87

Alternativek=40% Spearman 0.97

Kendall Tau-b 0.89

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Totestthestabilityofthemeasure,variouscomputationsoftheheadcountratio (H)werecalculatedbasedonvariouspovertycut-offs (k).Figures26showsthedistributionofHacrossvariouspovertycut-offs,forall14regions.Thefigureindicatesthatthepovertyratesarequitestable,astheorderoftheregionsremainsfairlysimilaracrossallvaluesofk.

Figure 26. Headcount Ratio Across Regions Based on Different Poverty Cutoffs

Note: The Namibian regions are alphabetically ordered and then ordered as Reg. 1 to Reg. 14, where //Karas is Reg. 1 and Zambezi is Reg. 14

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Reg. 8 Reg. 9 Reg. 10 Reg. 11 Reg. 12 Reg. 13 Reg. 14

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We acknowledge the shortcomings of the Namibian MPI (particularlypertainingtotheEconomicactivitydimensionandLandownership),whichwasconstrainedbytheavailabilityofdata.

TheAgency’slong-termvisionfortheNamibianMPIistocontinuegeneratingthis index whenever new NHIES data becomes available, to allow forcomparisonswithmonetarypovertymeasurement.

ThenextNHIESistentativelyplannedfor2022/23pendingfunding,hopefullythiswouldhaveprovidedenoughtimeforpolicyinterventions.Further,theMPIwillbeusedtoreportontheSDG1aswellasamonitoringtoolfortheNational Development Plans (NDPs).

Way forward.

Namibia Statistics Agency P.O.Box2133FGIHouse,PostStreetMallWindhoek,Namibia

Tel: +264 61 431 3200Fax: +264 61 431 3253Email: [email protected]

NAMIBIA MULTIDIMENSIONAL POVERTY INDEX (MPI) REPORT …

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