UNDP Inequalities RHDR zero draft (02.02.16)
Transcription
UNDP Inequalities RHDR zero draft (02.02.16)
UNDPREGIONALHUMANDEVELOPMENTREPORT ProgressatRisk:InequalitiesandHuman DevelopmentinEuropeandCentralAsia1 DraftFORCOMMENTS(2February2016) Abstract:ManyofthedevelopingandtransitioneconomiesofEurope,Turkey,andCentralAsiahaveenjoyed relativelyhighlevelsofsocio-economicequalities.Since2000incomeinequalitieshavegenerallybeenlowor falling,whichhashelpedtoreducepovertyandallowedthemiddleclasstostageacomeback.Relatively comprehensivepre-1990socialprotectionsystemsandhighlevelsofgenderequalityhaveensuredthatthe benefitsofeconomicgrowthhavebeenfairlyevenlyspread.However,theexpansionofinformal,vulnerable, andprecariousemploymentiscombiningwithgrowinggapsinsocialprotectionsystemsand(intheregion’s lesswealthycountries)newpressuresonhouseholdfoodandenergysecuritytoputtheseaccomplishments atrisk.ThisisparticularlythecaseforthosecountriesintheCommonwealthofIndependentStatesthathave madesomeofthebestprogressinreducinginequalities—andwhichnowfacegrowingsocio-economic pressures.Thisreportexaminesthehumandevelopmentaspectsofthesechallenges,withinthecontextof theSustainableDevelopmentGoalsandthepromiseoftheglobalsustainabledevelopmentagenda2030to “leavenoonebehind”. Tableofcontents Subject Page Executivesummary------------------------------------------------------------------------------------------------------ 2 Chapter1—Measuringincomeandnon-incomeinequalities-------------------------------------------------- 5 Chapter2—Inequalities,employment,andsocialprotection------------------------------------------------- 26 Chapter3—Theeconomicdimensionsofgenderinequalities-------------------------------------------------- 57 Chapter4—Inequalities,health,andHIV/AIDS-------------------------------------------------------------------- 77 Chapter5—NaturalCapital,Inequalities,andSustainableHumanDevelopment------------------------ 86 Chapter6—Inequalitiesandinclusivegovernance--------------------------------------------------------------- 97 References------------------------------------------------------------------------------------------------------------------ 134 1 ThispaperdoesnotnecessarilyreflecttheviewsoftheUnitedNationsDevelopmentProgramme,theUnitedNations,oritsMember States. 1 Executivesummary • • • • • • • Significantreductionsinincomeinequalitieshavebeenreportedinmuchoftheregion2sincetheturn ofthemillennium—particularlyBelarus,Kazakhstan,Moldova,andUkraine,andpossiblyalsoAlbania, Kosovo,3andtheKyrgyzRepublic.Bycontrast,incomeinequalitiesseemtohaveincreasedinGeorgia, Turkey,andpossiblytheformerYugoslavRepublicofMacedonia(fYRoM). Loworfallingincomeinequalitieshavehelpedeconomicgrowthreducepoverty—particularlyinthis firstgroupofcountries.InGeorgiaand fYRoM,bycontrast,highorrisinglevelsofincomeinequality haveslowedorfrustratedprogressinpovertyreduction.Thisunderscoreshow—inadditiontobeing desirable in and of themselves—low or falling inequalities are central to prospects for poverty reduction,inclusivegrowth,andsustainabledevelopmentintheregion. Thenumbersofpeopleintheregionlivinginpovertyfellfromatleast46millionin2001toabout5 millionin2013.Thenumbersofpeoplelivinginextremepovertydroppedbelow1millionduringthis time.Likewise,thenumbersofpeoplevulnerabletopovertydroppedfromabout115millionin2003 tosome70millionin2013.Bycontrast,thesizeofthemiddleclassgrewfromabout33millionin2001 to90millionin2013.Thenumbersofrelatively“wealthy”individuals(livingonmorethanPPP$50/day) hadrisentosome32millionin2013—mostofwhomwerelivinginTurkeyandKazakhstan. Theregion’smiddleclasseshavemadeacomebacksincetheturnofthemillennium,followingboth absoluteandrelativedeclinesduringthe1990s.Inmuchoftheregion,middleclasseshavegrownas the shares of national income claimed by wealthy households have declined. As of 2013, at least 80 millionpeopleintheregionhadachievedlivingstandardsthatarebroadlyconsistentwiththebounds ofthe“globalmiddleclass”. Progress in reducing income inequalities is now being put to the test in much of the region. The combination of low commodity prices, falling remittances, and slow or negative growth on key EuropeanandRussianexportmarketsisputtingpressuresonvulnerablehouseholdincomesthathave notbeenseensincetheturnofthemillennium.Thisposesnewchallengesastheimplementationof theglobalsustainabledevelopmentagenda2030beginsintheregion—particularlyforlabourmarkets and social protection systems, but also in light of the growing pressures on natural capital and ecosystemsinsomeoftheregion’slesswealthycountries. Labourmarketinequalitiesandexclusionlieattheheartoftheregion’sinequalitychallenges.Thisis thecasebothintermsoflabourmarketsperse,andbecauseaccesstosocialprotectionisoftenlinked toformallabourmarketparticipation.Peoplewithoutdecentjobsfacemuchhigherrisksofpoverty, vulnerability, and exclusion from social services and social protection. The share of workers in vulnerableinAlbania,Azerbaijan,Georgia,theKyrgyzRepublic,andTajikistanisestimatedataround 50%. Employment does not necessarily offer much protection against poverty and vulnerability, because informal, precarious, migratory, and vulnerable employment is widespread throughout the region. Women,youngworkers,migrants,thelong-termunemployed,peoplewithdisabilities,andotherswith unequal labour market positions are particularly vulnerable. While trends are improving in some countriesandforsomegroups,inothers,labourmarketinequalitiesareincreasing. 2 Unlessotherwisenoted,referenceinthispublicationistoAlbania,Armenia,Azerbaijan,Belarus,BosniaandHerzegovina,Georgia, Kazakhstan,Kosovo(asperUNSCR1244(1999)),theKyrgyzRepublic,theFormerYugoslavRepublicofMacedonia,Moldova, Montenegro,Serbia,Tajikistan,Turkey,Turkmenistan,Ukraine,andUzbekistan. 3 AllreferencestoKosovointhispublicationarewithintheframeworkofUNSCR1244(1999). 2 • • • • • • • The region faces important challenges in better measuring progress in reducing inequalities and promotingsustainabledevelopment.Thisisapparentinthedataonincomeinequalities,whichtendto report on disparities in consumption spending rather than income. It is apparent in the “employment”/”unemployment” statistical dichotomy, and in the infrequency with which publicly availablelabour-marketdataaredisaggregatedbyage,gender,ethnicity,andothercriteria.Anditis apparent in the paucity of indicators to measure the depletion of the region’s natural capital and environmentalsustainability. Long-termeffortstoformalizeemploymentarecrucial.Threedirectionsareparticularlyimportant:(i) effortstoboosttheinstitutionalcapacityoftheinstitutionschargedwithlabourmarketregulation,in order to better enforce legal protections for workers’ rights in the formal sector; (ii) the abolition of those labour market regulations that cannot be credibly enforced by state agencies and drive employment into the informal sector; and (iii) increased investment in active labour market policies, vocationaleducation,andothermeasurestoboostworkerproductivity. Policylinkagesbetweenlabourmarketsandsocialprotectionneedtobestrengthened.Whilepoorly aligned social policies can reduce incentives for labour market participation and hiring, this is not a reasonforreducingsocialprotectionspendingandcoverage.Instead,whereverpossible,thetaxation of labour to fund social benefits needs to be reduced in favour of other funding sources. These may include:(i)highertaxesonenvironmentallyunsustainableactivities;(ii)reductionsinbudgetsubsidies thataccruetothewealthy;(iii)moreaggressivemeasurestoreducethediversionofbudgetrevenues totaxhavens;and(iv)morerobustdirectionofbudgetaryprocurementandcontractingresourcesto companies(e.g.,socialenterprises)thatexplicitlypromotesocialinclusion. Socialprotectionisalsoaboutsocialservicesandthecareeconomy.Increasedinvestmentsinsocial service provision—particularly terms of care for children, the elderly, and persons with disabilities— canboostparticipationinlabourmarketsandvocationaltrainingprogrammes,particularlyforwomen. InTurkey,forexample,adecisiontobringstatebudgetspendingonsocialcareservicesuptoOECD levelswouldgenerateanestimated719,000socialcarejobs—morethan2.5timesthetotalnumberof jobs that would be created by devoting the same amount of budget funds to construction/infrastructureprojects.Anestimated84%oftheworkershiredintothesesocialcarejobs wouldhavepermanentcontractsofunlimitedduration(versus25%inconstruction);85%wouldhave socialsecuritycoverage(comparedto30%inconstruction). While the region compares favourably to many other developing countries in terms of gender equality, it also lags behind global best practices in many areas. Moreover, pre-1990s progress in genderequalitythathadbeenattainedinmanycountries—manyofwhichfeaturedrelativeequality betweenmenandwomen—hascomeundergrowingthreat. Gender-based inequalities tend to intersect with, and magnify the impact of, other forms and dimensions of inequalities, based on class, race, age, ethnicity, disability, occupation and income. Unequal labour market outcomes in particular can have major implications for broader gender inequalities and the exclusion of women. Women’s unequal access to social capital or their inferior positioninthenetworksthatconstitutesocialcapital(whicharemoremarkedinsomecountriesinthe regionthaninothers)isbothacauseandamanifestationofinequality. Adjustable net savings, the ecological footprint, and the sustainable human development index suggest that the depletion of natural capital, and environmental sustainability concerns more broadly, are relatively pronounced in the region’s lower-middle income countries—which are concentratedintheCaspianBasin.Inadditiontobeingthesiteofoneoftheworld’slargestman-made ecologicaldisasters(theAralSeatragedy),developmentmodelsinmanyofthesecountriesarebased on the extraction and processing of non-renewable fossil fuels, minerals, and non-ferrous metals. In 3 • some of these countries, this is accompanied by significant household food and energy insecurities. Thispointstoacertaingeographicinequity—environmentalriskstosustainabledevelopmenttendto beconcentratedintheeasternpartsoftheregion. Governancereformsmustbeattheheartofpolicyandprogrammaticresponsestothesechallenges. Efforts to improve labour market performance, strengthen social protection systems, and better address the region’s HIV/AIDS challenges require investments in the institutional capacity of labour inspectorates, public employment and public health services, the local authorities, and NGOs. Reductionsingender-basedandotherformsofdiscriminationrequireinvestmentsininstitutionsthat protect human rights, as well as judicial reforms and access to justice. Better quality and more extensiveandtimelydataonsocialexclusionandenvironmentalsustainabilityrequireinvestmentsin the institutional capacity of national statistical institutions—particularly in light of the reporting obligations associated with Agenda 2030 and the SDGs. Improvements in all of these areas require investments in public administrations and civil services, at both the central and local government levels. 4 Chapter1—Measuringincomeandnon-incomeinequalities4 Keymessages • Significantreductionsinincomeinequalitieshavebeenreportedinmuchoftheregionsincetheturn ofthemillennium—particularlyBelarus,Kazakhstan,Moldova,andUkraine,andpossiblyalsoAlbania, Kosovo,5andtheKyrgyzRepublic.Bycontrast,incomeinequalitiesseemtohaveincreasedinGeorgia, Turkey,andpossiblytheformerYugoslavRepublicofMacedonia(fYRoM). • Loworfallingincomeinequalitieshavehelpedeconomicgrowthreducepoverty—particularlyinthis firstgroupofcountries.InGeorgiaandfYRoM,bycontrast,highorrisinglevelsofincomeinequality haveslowedorfrustratedprogressinpovertyreduction.Thisunderscoreshow—inadditiontobeing desirable in and of themselves—low or falling inequalities are central to prospects for poverty reduction,inclusivegrowth,andsustainabledevelopmentintheregion. • Thenumbersofpeopleintheregionlivinginpovertyfellfromatleast46millionin2001toabout5 millionin2013.Thenumbersofpeoplelivinginextremepovertydroppedbelow1millionduringthis time.Likewise,thenumbersofpeoplevulnerabletopovertydroppedfromabout115millionin2003 tosome70millionin2013.Bycontrast,thesizeofthemiddleclassgrewfromabout33millionin2001 to90millionin2013.Thenumbersofrelatively“wealthy”individuals(livingonmorethanPPP$50/day) hadrisentosome32millionin2013—mostofwhomwerelivinginTurkeyandKazakhstan. • Theregion’smiddleclasseshavemadeacomebacksincetheturnofthemillennium,followingboth absoluteandrelativedeclinesduringthe1990s.Inmuchoftheregion,middleclasseshavegrownas the shares of national income claimed by wealthy households have declined. As of 2013, at least 80 millionpeopleintheregionhadachievedlivingstandardsthatarebroadlyconsistentwiththebounds ofthe“globalmiddleclass”. • Progress in reducing income inequalities is now being put to the test in much of the region. The combination of low commodity prices, falling remittances, and slow or negative growth on key EuropeanandRussianexportmarketsisputtingpressuresonvulnerablehouseholdincomesthathave notbeenseensincetheturnofthemillennium.Thisposesnewchallengesastheimplementationof theglobalsustainabledevelopmentagenda2030beginsintheregion. Introduction Quantitativedataconcerninginequalitiescanbedividedintothreeclasses:(1)incomeinequalities;(2) non-incomeinequalities;and(3)subjectiveperceptionsofinequalities(intheformofsurveydatagatheredvia representativesamples).Thischapterfocuseson(1)andelementsof(2)—particularlyasconcernsinequalities inthedistributionofwealth,butalsointermsofinequalitiesinaccesstobasicservices.(Manyotheraspectsof non-income inequalities are taken up in the subsequent chapters—particularly as concerns labour markets, gender,health,andsocialprotection).Bycontrast,subjectiveperceptionsofinequalitiesarenotamajorfocus of this chapter, or report—although, for reasons explained below, they almost certainly merit additional researchandanalysis. Analyses concerning inequalities and programming to respond to them are often hindered by the paucity of quantitative data—particularly once these discussions go beyond income inequalities, and particularly in the context the transition and developing economies of Europe and Central Asia.Despite this, 4 PleasesendcommentsonthischaptertoElenaDanilova-Cross([email protected])andBenSlay([email protected]). AllreferencestoKosovointhispublicationarewithintheframeworkofUNSCR1244(1999). 5 5 evenintheregion’slesswealthycountries,policymakersareincreasinglyfocusingoninequalities,exclusion, andvulnerability,ratherthanonextremeincomepoverty. This growing interest is accompanied by an emphasis within the Sustainable Development Goals (SDGs),whichunderpintheglobalAgenda2030forsustainabledevelopmentoninequalities,bothintermsof SDGs 10 (“reduce inequality within and among countries”) and 5 (“achieve gender equality and empower all womenandgirls”),andintermsofnumerousotherSDGtargetsand(prospective)indicators.Itisalsomatched by a renewed commitment on the part of the UN system to support national efforts to improve the quality, quantity,andavailabilityofsustainabledevelopmentdata—includingdatapertainingtoinequalities.The2014 publicationofAWorldThatCountsreportbytheUNSecretaryGeneral’sIndependentExpertAdvisoryGroup onaDataRevolutionforSustainableDevelopmentcalledfora“datarevolution”inordertosupporttheSDG indicatorsthatwillbeusedtomeasureandmonitortosustainabledevelopment. Incomeinequality Any assessment of the data on income inequality in the developing and transition economies of Europe,Turkey,andCentralAsiamustbeginbycallingattentiontotensionsbetweenmultipleandsometimes confusing data presented for the same country(s) on the one hand, versus the absence of publicly available, comparabledataforothercountriesintheregionontheother.Furthercomplicationsresultfromthefactthat the most common international data bases that show income distribution data for the countries of the region—such as POVCALNET or SWIID—often present data that differ from what can be found on the public websitesofthenationalstatisticalofficesintheregion. Table1—Ginicoefficientsforincomedistributionavailableonnationalstatisticalofficewebsites Year Country Albania Armenia Azerbaijan Belarus BiH Georgia Kazakhstan Kosovo KyrgyzRepublic fYRoM Moldova Montenegro Serbia Tajikistan Turkey Turkmenistan Ukraine Uzbekistan 2002 2005 2007 2008 2009 2010 Nodata 2011 2012 2013 2014 I 0.53 0.40 0.37 0.37 0.34 0.36 Nodata 0.36 0.37 0.37 0.37 - 0.26 - 0.27 0.33 0.33 0.30 - - - - 0.27 - 0.41 0.45 0.29 - 0.27 0.27 - 0.42 0.46 0.27 0.30 0.25 0.27 - 0.43 0.46 0.28 0.29 0.25 0.29 - 0.41 0.43 0.28 - 0.23 0.28 - 0.4 0.42 0.28 - 0.22 0.28 - 0.4 0.41 0.28 - 0.22 - - - - - - - - - - 0.37 - 0.30 0.37 0.37 0.41 0.30 0.35 0.42 0.39 0.27 0.34 0.46 0.37 0.27 0.33 0.26 - - 0.41 0.36 - 0.32 0.37 0.25 - - 0.41 0.28 - 0.42 0.46 0.29 0.28 0.25 0.38 0.39 0.29 0.34 0.26 - - 0.40 0.27 0.38 - 0.40 0.26 0.38 - 0.40 0.43 - 0.25 0.32 - - 0.29 - 0.25 0.26 0.23 0.24 0.23 0.29 0.23 I I C I I C C I I C I C I C I I C 0.30 0.41 0.46 0.31 - 0.32 0.42 - 0.33 0.37 0.26 0.24 - - - - 0.42 0.40 Nodata 0.26 0.25 0.3 6 I—income-baseddata;C—consumption-baseddata. Ginicoefficients.AlthoughitisnotlistedasprospectiveSDGindicator,theGinicoefficientremainsthe mostcommonlyused(andmostavailable)indicatortomeasureincomeinequalityintheregion—asreported bynationalstatisticaloffices(basedonhouseholdbudgetsurveydata).However,asthedatainTable1show, whileArmenia,Belarus,BosniaandHerzegovina(BiH),Kazakhstan,theformerYugoslavRepublicofMacedonia (fYRoM),Serbia,Turkey,andUkrainereportGinismeasuredintermsofincomeperse,Kosovo,Montenegro, Tajikistan,andUzbekistanreportGinismeasuredintermsofconsumptionspending—whileGeorgia,theKyrgyz Republic,andMoldovareportbothincome-andconsumption-basedGinisforincomedistribution.Asthedata for the Kyrgyz Republic show, differences in these series can be quite dramatic—suggesting very different conclusionsabouttheextentofincomeinequalityinagivencountry.Anevengreaterconcernisthefactthat these data seem to be publicly available to very limited degrees (or not at all) in Albania, Azerbaijan, Bosnia and Herzegovina, Tajikistan, Turkmenistan, and Uzbekistan. That is: judging from publicly available national sources,onlyArmenia,Belarus,Georgia,Kazakhstan,theKyrgyzRepublic,Moldova,Montenegro,Turkey,and Ukrainereportsignificanttimeseriesdataonincomeinequalities. AsecondperspectiveisofferedbytheGinicoefficientsforincomedistributionavailableintheWorld Bank’sPOVCALNETdatabase,whichareshowninTable2below.Thesedata,whichareallconsumption-based, indicate that reasonably complete and current time series are only available for Armenia, Belarus, Georgia, Kazakhstan,theKyrgyzRepublic,Moldova,Montenegro,Turkey,Ukraine,andpossiblyKosovo. AcomparisonofthedatainTables1and2suggestthat,intermsofincomeinequalitiesasmeasured bytheGinicoefficient,thecountriesoftheregioncanbeplacedinfourgroups: 1) Countries in which the available data on balance point to low or falling income inequality. This groupincludesBelarus,Kazakhstan,Moldova,andUkraine.Althoughthedataareshakier,Kosovo andpossiblyAlbaniacouldbeplacedinthisgroupaswell. 2) Countries in which the available data on balance point to high or rising income inequality. This group includes Georgia and Turkey, and possibly the former Yugoslav Republic of Macedonia (althoughthedataareshakier). 3) Countries for which data are available, but do not lend themselves to a clear judgement in this respect.ThisgroupincludesArmenia,theKyrgyzRepublic,andMontenegro. 4) Countriesforwhichtheavailabilityofnationalandinternationaldata(combined)isnotsufficient forsuchanassessment.ThisgroupincludesAzerbaijan,BosniaandHerzegovina,Serbia,Tajikistan, Turkmenistan,andUzbekistan. Table2—GinicoefficientsforincomedistributionfromthePOVCALNETdatabase Albania Armenia Azerbaijan Belarus BiH Georgia Kazakhstan Kosovo 2002 0.32 0.35 0.17 0.30 - 0.40 0.34 - 2003 - 0.33 0.19 0.30 - 0.40 0.33 0.29 2004 - 0.38 0.16 0.27 0.34 0.40 0.31 - 2005 0.31 0.36 0.17 0.28 - 0.40 0.30 0.31 2006 - 0.32 - 0.28 - 0.40 0.30 0.30 2007 - 0.30 - 0.29 0.33 0.41 0.29 - 2008 0.30 0.31 - 0.27 - 0.41 0.29 - 2009 - 0.30 - 0.28 - 0.42 0.29 0.32 2010 2011 2012 - - 0.29 0.31 0.31 0.30 - - - 0.28 0.26 0.26 - - - 0.42 0.42 0.41 0.29 0.27 0.27 0.33 0.28 0.29 2013 - 0.32 - - 0.40 0.26 0.27 7 KyrgyzRep. fYRoM Moldova Montenegro Serbia Tajikistan Turkey Turkmenistan Ukraine Uzbekistan** 0.30 0.39 0.36 - 0.33 0.41 - 0.29 0.33 0.29 0.39 0.35 - 0.33 0.33 0.42 - 0.29 0.35 0.35 0.39 0.35 - 0.33 0.33* 0.41 - 0.29 - 0.38 0.39 0.36 0.30 0.33 - 0.42 - 0.29 - 0.38 0.43 0.35 0.29 0.30 - 0.40 - 0.30 - 0.33 - 0.34 0.31 0.29 0.32 0.38 - 0.29 - 0.32 0.44 0.35 0.30 0.28 - 0.38 - 0.27 - 0.30 - 0.33 0.30 0.29 - 0.39 - 0.25 - 0.30 - 0.32 0.29 0.30 - 0.39 - 0.25 - 0.28 - 0.31 0.31 - - 0.40 - 0.25 - 0.27 - 0.29 0.32 - - 0.40 - 0.25 - - - 0.29 0.33 - - 0.00 - 0.25 - *Averageoftwodifferentvalues. **Basedoneconometricanalysis. Thesedifferencesnotwithstanding,acommonpatternacrosstheregioncanbeseenwhentheincome distributiondataareconsideredoveralongerperiodoftime—particularlyforthosetransitioneconomies(not countingTurkey)forwhichlongertimeseriesareavailable.Thatis,incomeinequalitiesjumpedsharplyduring the 1990s with the “transition recession”, as real incomes fell for the vast majorities of households, labour marketsloosened,andsocialprotectionsystemsbegantoencounterincreasingstrains.Theonsetof“recovery growth” in the new millennium then saw reductions in income inequalities, as the income growth that was recordedformiddle-classandlow-incomefamiliesapparentlyexceededthatreportedforwealthyhouseholds. Moreover,despitetheimpactoftheglobalfinancialcrisisof2008-2009andtheEurozonecrisisof2010-2012— both of which slowed growth in the region substantially—income inequality does not appear to have deteriorated(Figure1). Thus, for those countries for which longer time series are available, the data indicate that income inequalities have generally returned to “pre-transition levels”. A similar pattern is apparent (over a shorter time span) is apparent for Albania and Kosovo as well. Obvious exceptions to this pattern include Turkey (which is not a transition economy, and whose development since 1990 has followed a different logic) and Georgia—whichreportssimilarly(toTurkey)highlevelsofincomeinequality. Figure1—TrendsinGinicoefficientsforincomeinequalityinselectcountriesoftheregion 0.50 Belarus Kazakhstan Moldova Ukraine KyrgyzRep. 0.40 0.30 0.20 1988 1998 POVCALNETdata. 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 8 Figure2—Albania:Ratioofincomeofpooresttwo quintilestonationalincome(1996=100) Figure3—Armenia:Ratioofincomeofpooresttwo quintilestonationalincome(1996=100) 100 150 98 140 96 130 94 120 110 1996 1999 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 92 90 100 UNDPcalculations,basedonPOVCALNETdata. 110 110 105 105 100 100 95 95 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 1995 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 1996 2002 2005 2008 2012 UNDPcalculations,basedonPOVCALNETdata. Othermeasuresofincomeinequality.SDGtarget10.1callsfor“incomegrowthofthebottom 40%ofthepopulationataratehigherthanthenationalaverage”.Asthebelowfiguresshow,mostcountriesin the region perform well against this “bottom 40” indicator. A number (Armenia, Kazakhstan, the Kyrgyz Republic,Moldova,Ukraine)scorequitewell;others(Albania,Georgia,Montenegro)lessso. Figure4—Belarus:Ratioofincomeofpooresttwo Figure5—Georgia:Ratioofincomeofpooresttwo quintilestonationalincome(1995=100) quintilestonationalincome(1998=100) 9 Figure6—Kazakhstan:Ratioofincomeofpooresttwo quintilestonationalincome(1996=100) Figure7—Kosovo:Ratioofincomeofpoorest twoquintilestonationalincome(2003=100) 110 130 125 105 120 115 100 110 95 105 100 90 2003 2005 2006 2009 2010 2011 2012 2013 UNDPcalculations,basedonPOVCALNETdata. Other indicators (e.g., Palma ratios, or other ratios of the richest deciles to the poorest) of income inequality may be calculated on the basis of the quintile/decile income distribution data available on some nationalstatisticalofficewebsitesorPOVCALNET.However,theydonotshowdramaticallydifferentpictures fromwhathasbeenpresentedabove. Figure8—KyrgyzRep.:Ratioofincomeofpoorest Figure9—Moldova:Ratioofincomeofpooresttwo twoquintilestonationalincome(1993=100) quintilestonationalincome(1999=100) 250 140 130 200 120 150 UNDPcalculations,basedonPOVCALNETdata. 2013 2011 2012 2009 2010 2008 2007 2006 2005 2003 2004 2001 2002 1999 100 2000 1993 1998 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 110 100 10 Figure10—Montenegro:Ratioofincomeofpoorest twoquintilestonationalincome(2005=100) 105 Figure11—Turkey:Ratioofincomeofpooresttwo quintilestonationalincome(1987=100) 110 100 105 95 2011 2012 2009 2010 2008 2007 2006 2005 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2002 1987 90 1994 100 95 UNDPcalculations,basedonPOVCALNETdata. Poverty,inequality,andinclusivegrowth Mostofthecountriesoftheregionenjoyedstrongeconomicgrowthduringthefirstdecadeofthenew millennium. While the global financial crisis pushed many of these economies into recession, as a rule they experiencedarecoveryduring2010-2013.Thiseconomicgrowthclearlyhelpedreduceincomepovertyinthe region:themostrecentWorldBankinternationallycomparabledata(basedon2011globalpurchasing-powerparity exchange rates) indicate that poverty rates (measured at the PPP$3.10/day threshold) have fallen in most countries. In this sense, growth in the region has been “pro-poor”. Moreover, in a number of economies—suchasAlbania,Belarus,Kazakhstan,Kosovo,theKyrgyzRepublic,Moldova,andUkraine(Figures 13-19)—decliningpovertyrateshavebeenaccompaniedbylowfallingGinicoefficientsforincomeinequality. IncountriessuchasBelarusandUkraine,thesecontinuingdeclinesinpovertyandinequalityoccurredinspite ofsloweconomicgrowth,currencycrises,andothermacroeconomicchallenges. Figure12—Ukraine:Ratioofincomeofpoorest Figure13—Incomepovertyandinequality(Gini twoquintilestonationalincome(1995=100) coefficient)trendsinAlbania(1996-2012) 150 0.35 0.30 140 0.25 130 Incomepoverty 0.20 120 Incomeinequality 0.15 0.10 110 1995 1996 1999 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 0.05 100 0.00 1996 2002 2005 2008 2012 11 UNDPcalculations,basedonPOVCALNETdata. POVCALNETdata.Note—povertyratepercentagesare: • RelativetothePPP$3.10/daythreshold;and • Asarulegreaterthan1(i.e.,a.50valueimpliesa povertyrateof50%,not0.5%). Figure14—Incomepovertyandinequality(Gini coefficient)trendsinBelarus(1998-2012) Figure15—Incomepovertyandinequality(Gini coefficient)trendsinKazakhstan(1996-2013) 0.35 0.40 0.30 0.35 0.30 0.25 0.25 0.20 Incomepoverty 0.15 0.20 Incomeinequality 0.15 0.10 0.10 0.05 0.05 Incomepoverty Incomeinequality 0.00 0.00 POVCALNETdata.Note—povertyratepercentagesare: • RelativetothePPP$3.10/daythreshold;and • Asarulegreaterthan1(i.e.,a.50valueimpliesapovertyrateof50%,not0.5%). Figure16—Incomepovertyandinequality(Gini coefficient)trendsinKosovo2003-2013) Figure17—Incomepovertyandinequality(Gini coefficient)trendsintheKyrgyzRep.(1993-2012) 0.35 0.80 0.30 0.70 0.25 0.60 0.20 0.15 0.50 Incomepoverty Incomeinequality 0.40 Incomeinequality 0.10 0.30 0.05 0.20 0.00 Incomepoverty 0.10 2003 2005 2006 2009 2010 2011 2012 2013 POVCALNETdata.Note—povertyratepercentagesare: • RelativetothePPP$3.10/daythreshold;and • Asarulegreaterthan1(i.e.,a.50valueimpliesapovertyrateof50%,not0.5%). 12 Figure18—Incomepovertyandinequality(Gini coefficient)trendsinMoldova1997-2013) Figure19—Incomepovertyandinequality(Gini coefficient)trendsinUkraine(1995-2013) 0.70 0.40 Incomepoverty 0.60 0.35 Incomeinequality 0.50 0.30 2013 2012 2011 2010 2009 2008 0.05 2007 0.00 2006 0.10 2005 0.10 2004 Incomeinequality 2003 0.15 2002 0.20 2001 Incomepoverty 2000 0.20 1999 0.30 1998 0.25 1997 0.40 0.00 19951996200220032004200520062007200820092010201120122013 POVCALNETdata.Note—povertyratepercentagesare: • RelativetothePPP$3.10/daythreshold;and • Asarulegreaterthan1(i.e.,a.50valueimpliesapovertyrateof50%,not0.5%). Figure20—Incomepovertyandinequality(Gini coefficient)trendsinfYRoM1998-2008) Figure21—Incomepovertyandinequality(Gini coefficient)trendsinMontenegro(2005-2013) 0.45 0.35 0.40 0.30 0.35 0.30 0.25 0.25 Incomepoverty Incomeinequality 0.20 0.15 0.15 0.10 0.10 0.05 0.05 0.00 Incomepoverty 0.20 Incomeinequality 1998 2000 2002 2003 2004 2005 2006 2008 0.00 2005 2006 2007 2008 2009 2010 2011 2012 2013 POVCALNETdata.Note—povertyratepercentagesare: • RelativetothePPP$3.10/daythreshold;and • Asarulegreaterthan1(i.e.,a.50valueimpliesapovertyrateof50%,not0.5%). Bycontrast,incountriesliketheformerYugoslavRepublicofMacedoniaandMontenegro(Figures2021),prospectsforfurtherpovertyreductionseemtohavebeenfrustratedbyrelativelyhighorrisinglevelsof incomeinequality.Thesetrendsconfirmthat,inadditiontobeing“pro-poor”,economicgrowthintheregion hasalsobeen“inclusive”—inthesenseofreducingincomeinequalitiesaswellaspoverty.Theexperienceof countrieslikeBelarusandUkrainealsosuggestthatsloweconomicgrowthneednotmeanmorepovertyand inequality. 13 Non-incomeinequalitymeasures The Multiple Indicator Cluster Surveys (MICS) tool designed by UNICEF, to assess the well-being of women and children, has been used in more than 100 countries over the past twenty years, in five rounds. Mostofthecountriesoftheregionhavebeencovered.TheMICSdatabasecontainsdataforalargenumberof indicators that have been disaggregated by gender, age, education level, ethnicity, and other vulnerability criteria. Forpurposesofthisreport,theMICSdatabasewasexaminedforthecountriesoftheregioninterms ofdatacorrespondingto12proposedSDGindicators(Table3). Table3—MICSdataandproposedSDGindicators ProposedSDGindicator MICSdatabase 3.1.1Maternaldeathsper100,000livebirths Dataforthese indicators 5.b.1Proportionofindividualswhoownamobiletelephone,bysex wereonly 7.1.1Percentageofpopulationwithaccesstoelectricity 1.3.1Percentageofpopulationcoveredbysocialprotectionfloors/systems,disaggregated collectedfrom oneroundof bysex,anddistinguishingchildren,theunemployed,theelderly,peoplewithdisabilities, MICSsurvey pregnantwomen/newborns,workinjuryvictims,thepoorandvulnerable 3.2.1Under-fivemortalityrate(deathsper1,000livebirths) 3.2.2Neonatalmortalityrate(deathsper1,000livebirths) 3.7.2Adolescentbirthrate(10-14;15-19)per1,000womeninthatagegroup 4.2.1Percentageofchildrenunder5yearsofagewhoaredevelopmentallyontrackin health,learningandpsychosocialwell-being(disaggregatedbysex,location,wealth,and othercriteria,wherepossible). 6.1.1Percentageofpopulationusingsafelymanageddrinkingwaterservices Dataforthese indicators werecollected from2-3 roundsof MICSsurvey Dataforthese indicators werecollected from4rounds ofMICSsurvey 6.2.1Percentageofpopulationusingsafelymanagedsanitationservices IntermsofproposedSDGindicator3.7.2(adolescentbirthratesper1,000womeninthe10-14,15-19 agegroups,disaggregatedbyrural/urbanresidence—Figure22):Ingeneral,fertilityratesamongwomen15-19 yearsinSoutheastEuropeislowerthaninCIScountries.Inaddition,thesefiguresarealmosttwiceashighin ruralareasoftheCIScountriesastheyareinothercountries.Thesehighbirthratesmeanthatyoungwomen haveearlychildbearingandrearingresponsibilities,whiletheymayinfactstillbechildrenthemselves.Such circumstancescanturnlimittheirabilitytofullyparticipateinsocial,economic,andprofessionallife. Early childbearing may also increase the risks of infant and child mortality, which corresponds to proposed SDG indicators 3.2.1 (under-five mortality rate, deaths per 1,000 live births) and 3.2.2 (neonatal mortality rate, deaths per 1,000 live births). An important role is often played by maternal education levels: infant mortality rates are often higher among less well educated women. As the data from the available countries,theaverageinfantmortalityrateofmotherswithprimaryorincompletesecondaryeducationis50 (per 1,000 live births), versus 28 for women having secondary, vocational or higher education. Moreover, in almost all countries studied, infant and child mortality rates among the poorest 60% of the population were abovethoseforthewealthiest40%(Figures23-24). 14 Figure22—Fertilityratesamongyoungwomen15-19years(numberofbirthsper1,000womenofthesame age)inurbanandruralareas 60 Rural 50 48 Urban 44 40 31.5 29 30 21 22 22 20 18 20 24 19 17.1 9 10 2 2 0 BosniaandHerzegovina2012 Kosovo2014 Macedonia2011 Serbia2014 Kazakhstan2012 Moldova2012 Ukraine2012 Montenegro2013 IndicatorsmeasuringaccesstoeducationandindirectindicatorscoveringtheSDGindicatorPercentage of youth (15-24) not in education, employment or training (NEET), SDG target 8.6.1, it is an indicator of the proportion of eligible children attending secondary school. The data show that coverage is not universal. A significant role in the expansion of enrolment in secondary school is the level of household income. So, for bothboysandgirls,withanincreaseinthelevelofincomeisanincreaseintheproportionofeligiblechildren attending secondary school (Figures 25-26). Children in poor families are forced to abandon their education andgotoworktohelpsupportthehousehold. Figure23—Childmortalityrates(forchildrenunder5yearsofage)per1,000livebirths 54 Tajikistan2005 Turkmenistan2006 Uzbekistan2006 Georgia2005 Serbia2006 Kazakhstan2011 Albania2005 Macedonia2005 Moldova2012 Ukraine2012 64 46 22 26 33 24 6 100 62 44 35 26 11 5 10 0 73 25 19 20 40 Rischest40% 60 80 100 120 Poorest60% 15 Figure24—Infantmortalityratesper1,000livebirths 46 Tajikistan2005 Turkmenistan2006 79 61 54 39.5 Uzbekistan2006 20 Georgia2005 23 Serbia2006 30 21 Kazakhstan2011 6 Albania2005 52 38 30 23 Macedonia2005 22 11 Moldova2012 Ukraine2012 5 0 18 10 10 20 30 Rischest40% 40 50 60 70 80 90 Poorest60% Figure25—Percentageofchildrenofsecondaryschoolageattendingsecondaryschoolorhigher(adjusted netattendanceratio)bywealthindexquintiles,male 120.0 100.0 % 80.0 60.0 40.0 20.0 0.0 1 2 3 4 5 wealthindexquinmle Figure26—Percentageofchildrenofsecondaryschoolageattendingsecondaryschoolorhigher(adjusted netattendanceratio)bywealthindexquintiles,female 16 120.0 100.0 % 80.0 60.0 40.0 20.0 0.0 1 2 3 4 5 wealthindexquinmle MICS indicators concerning access to safe drinking water and sanitation services correspond to SDG targets6.1.1and6.2.1.MICSdataalsoshowthataccesstoimprovedsanitationanddrinkingriseswithincome levels(Figures27-28). Figure27—Usersofimprovedsanitationfacilities(4th,5throunddata)andusersofsanitarymeansofexcreta disposal(third-rounddata),%ofpopulationbywealthindexquintiles 110.0 100.0 90.0 % 80.0 70.0 60.0 50.0 40.0 1 2 3 4 5 wealthindexquinmle Figure28—Usersofimprovedwatersource,%populationbywealthindexquintiles 17 110.0 100.0 % 90.0 80.0 70.0 60.0 50.0 40.0 1 2 3 4 5 wealthindexquinmle Middleclassesintheregion Manystudiesofinequalitiesnaturallyfocusonthe“mostunequal”—therichestandthepoorest,how manyofthemthereare,whatmakesthemthisway,andhowdifferenttheyreallyarefromtherestofus.But analyses of the “tails” of the income distribution are implicitly also concerned with the “middle” of the distribution,sinceasmallermiddlemakesforbiggertails(andviceversa).Studiesofinequalitiescantherefore also be studies of the middle class—particularly since concerns about greater inequalities are often accompaniedbyconcernsaboutmiddleclasses. Such issues are particularly relevant among the developing and transition economies of Europe, Turkey, and Central Asia. Prior to the 1990s virtually all of the region’s transition economies had “socialist” middleclasses,consistingofwelleducatedblue-andwhite-collarworkers,engineers,andothermembersof the technical, creative, and administrative intelligentsia. While not necessarily commanding incomes or possessing wealth that corresponded to middle-class societies in OECD countries, these middle classes were forces of stability, and progress prior to the advent of transition. They certainly thought of themselves as possessingmiddle-classstatus. Moreover,sincethe1990s,manyofthesecountries—aswellasTurkey—haveexperiencedsignificant increasesinper-capitaincome.Theirrelativelylowincomeinequalitylevelsimplythatmillionsofpeopleinthe region’s upper middle-income countries (Albania, Azerbaijan, Belarus, BiH, Kazakhstan, Kosovo, fYRoM, Montenegro, Serbia, Turkey, and Turkmenistan) could today be considered members of the “global middle class”—possiblywithaspirationsandworldviewstomatch. How large are the region’s middle classes? How are they best defined and measured? Three approachestoansweringthesequestionsmaybeidentified: • Materialwell-being,asreflectedinsuchcriteriaasper-capitaincomeandwealth/propertyownership (e.g.,car(s),housing)andthecorrespondingabilitytoaccesscertainservices(e.g.,education,health, travel); • Subjective perceptions, concerning such issues as education, family background, and the associated socialimplications—basedonindividualself-identification;and • “Neitherrichnorpoor”.Tobeausefulcategoryofsocialanalysis,themiddleclass(thoseinthemiddle ofthesocio-economicdistribution)mustbequalitativelyandquantitivelydifferentfromthoseinthe tails. 18 Manydifferentapproachestodefiningandmeasuringthemiddleclasscanbefoundintheliterature (for a subset of these, see Box 1). A key question that must be faced is whether the middle class is to be defined in terms of absolute criteria (e.g., “members of the middle class earn between ‘X’ and ‘Y’ per day/month/year”);orrelativecriteria(e.g.,“ifthericharethetop10%andthepoorarethebottom20%,then themiddleclassisthemiddle70%”). Box1—Methodologiesfordefiningandmeasuringthemiddleclass • ILO:MembersofthemiddleclasshaveaveragedailypercapitaincomesinthePPP$4-13rangein developingcountries,andabovePPP$13/dayindevelopedcountries. • AfricanDevelopmentBank:Membersofthemiddleclasshaveaveragedailypercapitaincomesin thePPP$10-20range. • OECD:MembersofthemiddleclasshaveaveragedailypercapitaincomesinthePPP$10-100range. • Atkinson/Brandolini:Membersofthemiddleclasshaveaveragedailypercapitaincomesintherange of75-125%ofthemedianincome. Inthisreport,wepresenttheresultsoftheapplicationoftwosuchapproaches,bothofwhichembody twokeyelements:(i)theyarebasedonquantitativeindicatorsthataremethodologicallycompatiblewiththe income equality data presented above; and (ii) they reflect both the “material well being” and “neither rich, norpoor”logicdescribedabove.Theseare: • Arelativeapproach,whichdefinesthe: o Bottom two deciles of national household income distribution data as “lower-income” (i.e., relativelypoorerthanthemiddleclass); o Middlesixincomedecilesas“middleclass”;and o Toptwoincomedecilesas“upper-income”(i.e.,relativelyricherthanthemiddleclass);and • Anabsoluteapproach,whichdefinesthe: o Poor as those living below the World Bank’s new global poverty threshold of PPP$3.10/day (withtheextremepoorlivingbelowthePPP$1.90/daythreshold); o VulnerableasthoselivingbelowthePPP$10/daythreshold,butonmorethanPPP$3.10/day; o MiddleclassasthoselivingbelowthePPP$50/day,butonmorethanPPP$10/day;and o UpperclassasthoselivingonmorethanPPP$50/day. Results of the “relative” approach. Trends in the evolution of the middle classes in the region’s transition economies generally show similar pattern: their share of the national income fell in the 1900s (during transition recessions) and then recovered after the new millennium. In most of these countries, the middleclasses’sharesofnationalincomearenowat,orabove,pre-transitionlevels. Virtuallyallofthevariationinmiddleclasses’sharesofnationalincomecanbeexplainedbyoffsetting changes in upper-income classes’ shares of national income. The shares of national income received by the bottom two deciles have remained surprisingly constant over time (at around 8-10% of national income) in mostoftheregion. Inallbuttwocountriesintheregion(GeorgiaandTurkey—Figures29-30),themiddleclasses’sharesof nationalincomehavegenerallybeensignificantlylargerthantheupper-incomeclasses’share.InGeorgiaand Turkey,bycontrastthesetwosharesareroughlyconstant(at45-50%).Thesharesofnationalincomereceived bythebottomtwodecilesinthesecountrieshavebeenthesmallestintheregion(fluctuatingaround5%). 19 Figure29—Sharesofnationalincomereceivedby middle,otherclasses—Georgia(1996-2013) Figure30—Sharesofnationalincomereceivedby middle,otherclasses—Turkey(1987-2012) 60% 60% 50% 50% 40% 40% Lowerincome Lowerincome Middleclass Upperincome 30% 30% Middleclass 20% Upperincome 20% 10% 10% 199 199 199 199 200 200 200 200 200 200 200 200 200 200 201 201 201 201 0% 0% UNDPcalculations,basedonPOVCALNETdata.The“middleclass”isdefinedasthemiddlesixdeciles(“middle60%”)ofthe nationalincomedistribution.Theotherclassesaredefinedintermsofthetopandbottomtwodeciles(upperandlower 20%),respectively. Figure31—Sharesofnationalincomereceivedby middle,otherclasses—Belarus(1988-2012) 60% 60% 50% 50% 40% 40% Lowerincome 30% 20% 20% Upperincome 2013 2012 2011 2010 2009 2008 2007 2005 2004 2003 2002 0% 2001 0% 1996 10% 1993 10% 1988 198 199 199 199 199 200 200 200 200 200 200 200 200 200 200 201 201 201 Upperincome 30% Middleclass Middleclass 2006 Lowerincome Figure32—Sharesofnationalincomereceivedby middle,otherclasses—Kazakhstan(1988-2013) UNDPcalculations,basedonPOVCALNETdata.The“middleclass”isdefinedasthemiddlesixdeciles(“middle60%”)ofthe nationalincomedistribution.Theotherclassesaredefinedintermsofthetopandbottomtwodeciles(upperandlower 20%),respectively. 20 Figure33—Sharesofnationalincomereceived bymiddle,otherclasses—Kosovo(2003-2013) Figure34—Sharesofnationalincomereceivedbymiddle, otherclasses—Ukraine(1988-2013) 60% 60% 50% 50% 40% 40% 30% Lowerincome 30% Lowerincome Middleclass Middleclass 20% 20% Upperincome Upperincome 10% 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 1999 1996 1995 0% 1992 2003 2005 2006 2009 2010 2011 2012 2013 1988 10% 0% Economieswiththelargestmiddleclasses(e.g.,Belarus,Kazakhstan,Kosovo,Ukraine—Figures31-34) alsotendtohavethelargestsharesofnationalincomereceivedbythebottomtwodeciles,andthesmallest sharesofnationalincomereceivedbytherichest20%. Figure35—Changesinabsolutenumbersofmiddle,otherclassesintheregion(2000-2013) 10 7 28 103 8 7 26 100 25 14 31 2000 9 9 34 35 114 115 12 43 111 2 14 52 103 2 16 56 102 1 20 60 98 15 21 9 20 9 16 5 13 6 11 4 10 3 2001 2002 2003 2004 2005 2006 2007 Extremepoverty Poverty Vulnerable 6 20 8 18 61 65 92 96 8 2 8 2 2008 16 21 25 32 22 25 25 64 65 66 86 78 75 70 6 2 2010 2011 64 2009 Middleclass--lowermer 24 6 5 2012 Middleclass--uppermer 5 2013 Wealthy UNDPcalculations,basedonPOVCALNETdata.Figuresareinmillions.TurkmenistanandUzbekistanarenotincluded. Onthewhole,theincomedistributiondatadonotdescribearegionwhosemiddleclasseshavebeen decimated by transition or development. They instead broadly suggest a return to pre-transition income shares. In light of the region’s generally low Gini coefficients, this conclusion should not come as a surprise. Still,itstandsincontrastwithmanyofthenarratives.Itmaybethatthetrulyrelevantchangesareoccurring withinthedeciles(especiallythebottomtwo)ratherthanacrossthem—orthatquantitativedataareunableto 21 accurately capture the truly wrenching social changes that these countries have experienced in the past 25 years.Still,theseresultsprovidefoodforthought. Resultsofthe“absoluteapproach”.Comparedtotheaboveanalysis,thisapproachhasanumberof advantages.Theseincludeinteralia:(i)explicitlinkstoglobalpovertythresholds—therebylinkingabsoluteand relative poverty (i.e., inequality) measures; (ii) an extension of the previous approach’s three-tiered social stratification,toincludealsothosevulnerabletopoverty(i.e.,livingabovethepovertylinebutnotnecessarily in the middle class)—and also (if we so chose) those living in extreme poverty (i.e., below the World Bank’s new PPP$1.90/day threshold), as well as different tiers within the middle class (i.e., those living between PPP$10/dayandPPP$20/day,versusthoselivingbetweenPPP$20/dayandPPP$50/day);and(iii)answersto suchquestionsas“howmanypeopleincountryXhaveincomesabove$20/day?” Thisanalysissuggeststhat,during2000-2013,thenumbersofpeopleintheregionlivinginpovertyfell from 46 million in 2001 to about 5 million in 2013 (Figure 35).6 (The numbers of people living in extreme poverty,aspertheWorldBank’sPPP$1.90/daycriterion,droppedbelow1million.)Likewise,thenumbersof peoplevulnerabletopoverty(i.e.,inthePPP$3.10/day–PPP$10/dayrange)droppedfromabout115millionin 2003tosome70millionin2013.Bycontrast,thesizeofthemiddleclassgrewfromabout33millionin2001to 90 million in 2013. Interesting, after nearly disappearing 2002-2004, the numbers of “wealthy” individuals (livingonmorethanPPP$50/day)hadrisentosome32millionin2013—mostofwhomwerelivinginTurkey and Kazakhstan. Adding the 25 million individuals estimated to be living on between PPP$20/day and PPP$50/daytothisfiguresuggeststhatnearly80millionpeopleintheregionhaveachievedlivingstandards thatarebroadlyconsistentwiththeboundsofthe“globalmiddleclass”. Figure36—Changesinsharesofmiddle,otherclassesintheregion(2000-2013) 6% 4% 15% 55% 4% 4% 14% 54% 14% 17% 7% 2000 5% 5% 18% 19% 61% 61% 1% 6% 23% 59% 1% 7% 28% 54% 1% 8% 29% 54% 1% 10% 31% 51% 3% 10% 4% 10% 32% 34% 49% 48% 8% 11% 33% 44% 12% 13% 11% 13% 33% 33% 40% 38% 16% 12% 33% 35% 8% 11% 5% 11% 5% 9% 3% 7% 3% 6% 2% 5% 2% 4% 1% 4% 1% 3% 1% 3% 1% 2% 1% 2% 1% 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Extremepoverty Poverty Vulnerable Middleclass--lowermer Middleclass--uppermer UNDPcalculations,basedonPOVCALNETdata.TurkmenistanandUzbekistanarenotincluded. Wealthy Considerationofthesetrendsintermsofchangesintherelativesizeofthevariousclassesshowsthat, whereasmorethanthreequartersoftheregionwaslivinginpovertyorvulnerabletoitduring2000-2003,by 2013 this share had dropped to under 40%. While the middle classes were the chief beneficiaries of these improvements in living standards, it is interesting to note that the share of those living on more than PPP$50/dayhadrisento16%in2013(fromclosetozeroin2002-2003). 6 ThesedatadonotincludeTurkmenistanandUzbekistan. 22 In broad brush strokes, these results are quite consistent with those suggested by the “relative” approach to defining the region’s middle classes described above. They also do not describe a region whose middle classes have been decimated by transition or development. An important difference lies in the two approaches’ treatment of the wealthy, however. Whereas the relative approach shows the upper classes’ sharesofnationalincomeremainingroughlyconstantorshrinkinginmostoftheregion,theabsoluteapproach pointstotherapidgrowthinthisgroup’sshareoftotalincomefromvirtuallynothingin2003to16%adecade later.Thismaybeabletoexplainthewidespreadconcernsaboutgrowinginequalitiesintheregion—evenif thedistributionoftotalhouseholdincomes(asmeasuredindeciles)hasnotchangedsodramatically. Howricharetheregion’srich? Global household wealth is unequally distributed: there are an estimated 31 million millionaires and more than a thousand billionaires (in US dollar terms) in the world. As one authoritative source notes: “The bottom half of the global population together possess less than 1% of global wealth. In sharp contrast, the richest10%own86%oftheworld’swealth,withthetop1%aloneaccountingfor46%ofglobalassets”(Credit SuisseGlobalWealthDatabook,2013). Chart1--Theregion'sbillionaires(inbillionUS$) 3.9 topranking secondtothetop botomranking 5.3 2.3 1 2.2 1.9 1.4 5.2 1.4 1 Turkey 3.9 Kazakhstan 2.2 Ukraine 5.3 2.3 1.9 1.4 1 1.4 1 topranking secondtothetop Georgia 5.2 botomranking UNDPcalculationsbasedonForbes’slistofreal-timebillionaires. AquickbrowsethroughForbes’mostrecentbillionaireslist7showsthatonly33(2%)comefromthe developing and transition economies of Europe, Turkey, and Central Asia.8 Turkey is responsible for 22 of these,followedbyUkraineandKazakhstan(fiveeach)andGeorgia(withone).Fiveofthesearewomen(four from Turkey, one from Kazakhstan). Interestingly, large differences in wealth are apparent between these billionaires:therichestbillionaireinTurkeyissomefourtimesricherthanthe“poorest”billionaire;inUkraine thegapisfive-fold.Wealthispredominantlyandaccumulatedviathenaturalresourcesandbankingsectorsof economy; construction and pharmaceuticals are specific to Turkey. Interestingly, one billionaire in Ukraine makesmoneyintheagriculturalsector. 7 http://www.forbes.com/billionaires/list/#version:realtime(lastconsultedon16January2016)Ofcourse,richlistsarejustestimates. Theyarepopularpreciselybecausethey’rewillingtoputaharddollarnumberonthepersonalwealthofthesuper-rich.Yetintruth,no onereallyknowswhatmanyofthesuper-richareworthatanygivenmoment(includingthesuper-richthemselves).Manyofthemown privatecompanies,whicharehardtovalueuntilthey’resold.Andtheyoftenhavedebts,otheraccounts,financialobligationsand investmentsthatdon’tshowuptothepublic. 8 Referenceistotheprogrammecountries/territorieswhosedevelopmentaspirationsaresupportedbyUNDP’sRegionalBureaufor EuropeandCIS.Theseare:Albania,Armenia,Azerbaijan,Belarus,BosniaandHerzegovina,Georgia,Kazakhstan,Kosovo(asperUNSCR 1244(1999)),Kyrgyzstan,theFormerYugoslavRepublicofMacedonia,Moldova,Montenegro,Serbia,Tajikistan,Turkey,Turkmenistan, Ukraine,andUzbekistan 23 According to the Global Wealth Report, the numbers of millionaires in the region dropped by some 95% during 2010-2015 (Figure 37). Perhaps more usefully, the Global Wealth Report also estimates Ginis coefficientsforthedistributionofwealth,intheregionaswellasglobally(Table3).Anumberofconclusions aresuggestedbytheseestimates.First:withtheexceptionsofKazakhstan,Turkey,andUkraine,inequalitiesin the distribution of wealth generally remained the same or declined during this time. Second, inequalities in wealthinmostoftheregionaregenerallybelowworldaverages.Thisalsocanbeseenasalegacyfromthe region’s socialist past, when significant private holdings of wealth as such did not exist. (In light of the large shareofstatepropertythatremainsinstatehandsinmuchoftheregion,theroleofthestatemaynotbea legacy.) Figure37--Theregion'smillionaires 2259 1903 2010 2011 114 116 113 59 2012 2013 2014 2015 Table3—Ginicoefficientsforthedistributionofwealthintheregion(2010-2015) Albania Armenia Azerbaijan Belarus BiH Georgia Kazakhstan KyrgyzRepublic fYRoM Moldova Montenegro Serbia Tajikistan Turkey Turkmenistan Ukraine 2010 0.68 0.668 0.612 0.648 0.678 0.703 0.658 0.673 0.727 0.688 0.652 0.645 0.669 0.704 - 0.64 2011 0.654 0.644 0.595 0.637 0.665 0.684 0.863 0.659 0.694 0.671 0.669 0.635 0.657 0.844 - 0.889 2012 0.657 0.639 0.652 0.624 0.659 0.79 0.838 0.66 0.689 0.648 0.635 0.626 0.638 0.842 - 0.892 2013 0.656 0.639 0.651 0.622 0.658 0.68 0.867 0.659 0.688 0.647 0.634 0.625 0.638 0.837 0.68 0.9 2014 0.668 0.668 0.646 0.646 0.663 0.68 0.873 0.646 0.69 0.68 0.657 0.654 0.629 0.843 0.667 0.919 2015 0.658 0.628 0.591 0.65 0.67 0.666 0.874 0.633 0.693 0.674 0.658 0.661 0.624 0.821 0.673 0.916 Africa Asia-Pacific China 0.849 0.869 0.69 0.872 0.881 0.697 0.865 0.889 0.689 0.846 0.887 0.695 0.856 0.895 0.719 0.856 0.892 0.733 24 Europe India LatinAmerica NorthAmerica World 0.799 0.778 0.785 0.799 0.881 0.829 0.804 0.793 0.816 0.893 0.831 0.813 0.797 0.842 0.902 0.83 0.813 0.806 0.841 0.905 0.827 0.814 0.809 0.837 0.911 0.834 0.831 0.809 0.842 0.915 Conclusions Forthosewhoareconcernedabouttheglobaleffectsofincreasinginequalities,theaboveanalysisof the quantitative data on the distribution of income and wealth in the region suggests a reassuring picture. ManyofthedevelopingandtransitioneconomiesofEurope,Turkey,andCentralAsia(withafewexceptions) reportlow,ordeclining,levelsofincomeinequality;estimatesofthedistributionofwealththatarebasedon internationallycomparablemethodologiesproposethesameresults.However,suchapictureisatoddswith manycommonlyacceptednarrativesabouttheregion—whichtendtoreferencelargeandgrowinginequalities inincome,wealth,accesstobasicservices,andotherimportantaspectsofhumandevelopment. This raises the question: what’s wrong—the data, or the perceptions? To be sure, the quality of the dataonincomeandwealthinequalitiesintheregionisnotbeyondreproach.Forexample,thatthehousehold budgetsurveydatafromwhichtheincomeinequalityindicatorsthatpopulatebothnationalandinternational data bases are drawn are widely recognized as missing both the very poor (who typically slip between the cracks of national surveying activities) and at least a portion of the incomes of the very rich. It is telling, for example, that the POVCALNET database reports that virtually no one in the region earns more than PPP$100/day—millionairesandbillionaires(asreportedbyForbes)notwithstanding.Partofthismaybedueto the reliance on consumption-based surveys that underpin internationally comparable databases like POVCALNET.Suchsurveysdonotreflectincomesearnedbutnotspentonconsumption—which,inthecaseof wealthy households (with high average propensitiestosave)—mayfurtherunderstatethesharesofnational incomes distributed to wealthy households. All this underscores the need for more investment in national statisticaloffices’capacitytoconductregularhouseholdbudgetsurveysthataccuratelycapture(accordingto internationallycomparablemethodologies)theentiretyofhouseholdincomes—includingthosesharesthatare notconsumed. Still, these data should not be dismissed out of hand. Declines in income inequalities in many Latin American countries during the past decade have been well documented; there’s no reason that other developingregionscannotreportsimilartendencies.Perhapsmoreseriousquestionsconcernwhetherthose economiesintheregionthatseemtohavemadethemostprogressinreducingincomeinequalities—Albania, Belarus,Kazakhstan,Kosovo,Moldova,Ukraine—willbeabletomaintaintheseaccomplishmentsinthefaceof thesocio-economictensionsthatarenowpresentintheregion. 25 Chapter2—Inequalities,employment,andsocialprotection9 Keymessages • Labourmarketinequalitiesandexclusionlieattheheartoftheregion’s10inequalitychallenges.This is the case both in terms of labour markets per se, and because access to social protection is often linked to formal labour market participation. People without decent jobs face much higher risks of poverty,vulnerability,andexclusionfromsocialservicesandsocialprotection. • While labour market inequalities exist in many dimensions, they are particularly important when it comes to access to formal employment. Because informal, precarious, migratory, and vulnerable employment is widespread throughout the region, employment does not necessarily offer much protection against poverty and vulnerability. Women, young workers, migrants, the long-term unemployed,peoplewithdisabilities,andotherswithunequallabourmarketpositionsareparticularly vulnerabletobroaderrisksofpovertyandexclusion.Whiletrendsareimprovinginsomecountriesand forsomegroups,inothers,labourmarketinequalitiesareincreasing. • Many commonly used labour market indicators offer only limited insights into labour market performance and equalities. This is apparent in the “employment”/”unemployment” statistical dichotomy,andintheinfrequencywithwhichpubliclyavailablelabour-marketdataaredisaggregated by gender, ethnicity, and other vulnerability criteria. Different labour market statuses—inactivity, unemployment, underemployment, informal employment, formal employment, migrant work, etc.— should be understood as representing points along multi-dimensional continua of labour market positions, with much overlap and fluidity between the categories. Inequalities among the employed canbeasgreat,orgreater,thanthosebetweentheemployedandunemployed. • Long-termeffortstoformalizeemploymentarecrucial.Threedirectionsareparticularlyimportant:(i) effortstoboosttheinstitutionalcapacityoftheinstitutionschargedwithlabourmarketregulation,in order to better enforce legal protections for workers’ rights in the formal sector; (ii) the abolition of those labour market regulations that can not be credibly enforced by state agencies and drive employment into the informal sector; and (iii) increased investment in active labour market policies, vocationaleducation,andothermeasurestoboostworkerproductivity. • Policylinkagesbetweenlabourmarketsandsocialprotectionneedtobestrengthened.Whilepoorly aligned social policies can reduce incentives for labour market participation and hiring, this is not a reasonforreducingsocialprotectionspendingandcoverage.Instead,whereverpossible,thetaxation of labour to fund social benefits needs to be reduced in favour of other funding sources. These may include:(i)highertaxesonenvironmentallyunsustainableactivities;(ii)reductionsinbudgetsubsidies thataccruetothewealthy;(iii)moreaggressivemeasurestoreducethediversionofbudgetrevenues totaxhavens;and(iv)morerobustdirectionofbudgetaryprocurementandcontractingresourcesto companies (e.g., social enterprises) that explicitly promote social inclusion. The region’s prevailing demographictrendsindicatethatneedstofindnon-laboursourcesofbudgetrevenueswillsharpenin thefuture. • Socialprotectionisalsoaboutsocialservicesandthecareeconomy.Increasedinvestmentsinsocial service provision—particularly terms of care for children, the elderly, and persons with disabilities— canboostparticipationinlabourmarketsandvocationaltrainingprogrammes,particularlyforwomen. InTurkey,forexample,adecisiontobringstatebudgetspendingonsocialcareservicesuptoOECD 9 PleasesendcommentsonthischaptertoSheilaMarnie([email protected])andBenSlay([email protected]). Unlessotherwisenoted,referenceinthispublicationistoAlbania,Armenia,Azerbaijan,Belarus,BosniaandHerzegovina,Georgia, Kazakhstan,Kosovo(asperUNSCR1244(1999)),theKyrgyzRepublic,theFormerYugoslavRepublicofMacedonia,Moldova, Montenegro,Serbia,Tajikistan,Turkey,Turkmenistan,Ukraine,andUzbekistan. 10 26 • • levelswouldgenerateanestimated719,000socialcarejobs—morethan2.5timesthetotalnumberof jobs that would be created by devoting the same amount of budget funds to construction/infrastructureprojects.Anestimated84%oftheworkershiredintothesesocialcarejobs wouldhavepermanentcontractsofunlimitedduration(versus25%inconstruction);85%wouldhave socialsecuritycoverage(comparedto30%inconstruction). Inmanycountries,gapsbetweendejuresocialprotectionguaranteesanddefactoaccesstosocial benefitsandservicesaresignificantandgrowing.Addressingthesegapsbalancingcentralizedsocial protection and employment schemes with more scope for locally provided, more flexible and individual-focusedmodalitiesofinclusion. Manyofthoseexcludedfromthelabourmarketarenotreachedbytraditionalactive-labourmarket programmes. This is due in part to weaknesses in outreach to vulnerable communities (e.g., ethnic minorities,low-skilledworkersinruralcommunities),butalsotochronicunder-funding. Overview Labourmarketinequalitiesconcernnotonlydifferencesbetweenthosewhoareemployedandthose who are not, but also among those who are employed. In most countries of the region, those who are in precarious,informal,lowwage,lowproductivityjobscaneasilysufferthesame(orworse)risksofpovertyand exclusion as those who are without jobs. Inequalities among the employed can be as great, or greater, than thosebetweentheemployedandunemployed. However,thesedisparitiesarenoteasytounravelusingstandardlabourmarketindicatorsanddata. While these may help ensure international comparability, they often fail to capture critical dimensions of labour market and broader social inequalities. As such, they may provide a poor basis for policy design and implementation. Low labour force participation rates and (in some countries) high unemployment figures underscore problems of labour market exclusion for significant sections of the working age population. But evenwithintheemployedpopulationthereareclearlyinequalitiesaffectingindividualandhouseholdwelfare, asevidencedbythedataonthe“workingpoor”,andoninformalandvulnerableemployment.Manyofthose atthebottomoftheincomescalecannotaffordtobe“idle”;theymayhavelittlechoicebuttoengageinlow qualityorvulnerableemployment.Giventherestrictivecriteriafordefiningtheunemployed,andthelowlevel andlimiteddurationofsupportforregisteredunemployed,manyworkerswithoutjobsdonotregister.They eitherwithdrawfromthelabourforce,acceptlow-qualityjobs,orjointhearmyoflabourmigrants. Itisdifficulttocharacterizeorgeneralizeabouttheseinequalitieswithintheemployedpopulation.The ILO’s“decentwork”paradigm—asopposedtoprecarious,vulnerable,orinformalsectorwork—cancertainly help. But quantifying the share of the workforce enjoying decent work is extremely complex. Some authors refertoduallabourmarkets,betweenthoseinformalandthoseininformalemployment;orbetweenthosein decent jobs and those in non-decent jobs. But even here, reality is often more complex than dichotomous, black-and-white characterizations. For example, public sector employees may have more job security and betteraccesstosocialprotection—buttheirwagesmaybesolowastomakethempartofthe“workingpoor”. Informal sector workers may not enjoy labour rights or social protection, but they may be able generate incomes that are sufficient to keep themselves, and their families, out of poverty. Moreover, even workers who are formally employed may receive significant shares of their wages in the form of unregistered (and thereforeuntaxed)cashunderthetable. Unequalemploymentopportunitieshavealsoledtolargeinternalandexternalmigrationflows—many of which exhibit high degrees of irregularity/informality. While these movements can raise income and development opportunities for migrants and their families, they are also associated with many risks and insecurities.Theymayalsocontributetonewformsofinequalities,mostnotablybetweenthosehouseholds withmigrantmembersandaccesstoremittances,andthosewithout. 27 UNDP’s2011RegionalHumanDevelopmentReportshowedthat,whilejoblessnessheightenstherisk of economic exclusion, but it also tends to be associated with other forms of deprivation which together heighten individual risks of exclusion. Exclusion from employment opportunities were found to be a major driver of exclusion from economic life, which in turn contributed to exclusion from social and political processes.11 Driversoflabourmarketexclusionincludethecapital-andresource-(asopposedtolabour-)intensive economicgrowthpatternswhichhavetakenroot.Theseoftenresultinthepaucityofdecent,formal,private sectorjobs.Thiscanbeattributedtoalackofstructuralreformstostrengtheninstitutionalcapacityinboththe privateandstatesectors.Butitalsoreflectsthelowprioritiesoftenascribedtoemploymentgoals,reflecting the(oftenmistaken)beliefthateconomicgrowthwouldautomaticallyleadtomoreandbetterjobs.Butwhile it is now widely understood that this link is not automatic, governments have been slow to put in place the institutionalframeworksneededtodesignandimplementcomprehensivenationalemploymentpolicies.The successofeffortstoaddresstheconsiderableskillsmismatchesthatstandbehindmanycasesoflabourmarket exclusion(particularlyforyoungworkers)hasnotbeenespeciallynoteworthy. Helping economic growth to boost decent job opportunities requires holistic, whole-of-government approaches—particularly in terms of the links between employment and social protection policies. Most countriesintheregioninheritedsocialprotectionsystemsthatweredesignedtocomplementfullornear-tofullemploymentsituations.Incircumstancesofentrenchedjoblessness,however,proposalstocompensatefor the lack of formal employment opportunities by providing minimum income floors have often encountered opposition, in the form of concerns about excessive fiscal burdens and disincentives for labour market participation.Manyworkershavethereforehadtoseekinformalemployment—therebylosingaccesstosocial insurance(e.g.,healthandpensioninsurance)aswellasotherbenefits(e.g.,maternityleave)andprotections nominallyguaranteedbylaw. Effortstopromotedecentjobsandstrengthensocialprotectionintheregionmustthereforefocuson addressingdriversofinformality.Threedirectionsseemparticularlyimportantinthisrespect: • Effortstoboosttheinstitutionalcapacityoftheinstitutionschargedwithlabourmarketregulation, inordertobetterenforcelegalprotectionsforworkers’rightsintheformalsector.Intoomanycases, inspectionsthatidentifyviolationsofcommercial,labour,migration,orsocialprotectionlegislationare dealt with through payment of bribes—which are seen as necessary to provide a living wage for the (not always fully trained) civil servants working in these inspectorates. Civil service and public administration reforms to raise public-sector salaries and reduce other drivers of corruption and malfeasancethatdistortlabourmarketregulation. • Thereconsiderationoftaxesandregulationsthatcannotbecrediblycollectedorenforcedbystate agenciesanddriveemploymentintotheinformalsector.Regulationsandtaxesthatplaceinordinate burdensonSMEs,ormigrantsandothervulnerableworkers,needtobereconsideredorabolished. • Increased investment in active labour market policies, vocational education, and other measures to boostworkerproductivity. Labourmarketinequalities 11 SeeforexampleRHDR2011,pp18-19. 28 Inequalitiesinemploymentoutcomesandopportunitiesareinpracticedifficulttoseparate.Bothare reflectedin low employment rates, as well as in high rates of long term unemployment,as well as informal, vulnerable,andmigratoryemployment. Labour force participation rates in the region vary from relatively high (70-80% of the working age population)tobelow50%inothers( Figure),whiletheaverageregionalunemploymentratesofthosewhoareparticipatinginthelabour forcewas9.6percentin2014.12EmploymentandparticipationratestendtobeparticularlylowintheWestern Balkans,andmuchhigherinCentralAsia.Andwhereasemploymentratesdeclinedinmuchoftheregionafter theearly1990s,theyhavegenerallyreturnedto“pre-transition”levelsinCentralAsiaandtheCaucasus. Figure1.LabourMarketStatusofWorkingAgePopulationin2014 90 80 70 Unemploymentas%ofpopulamon Employmentrate Regionalemploymentrate(weightedaverage)** 60 50 40 30 20 10 0 KAZ AZE KGZ TJK GEO TKM UZB UKR ARM BLR ALB TUR SRB MNE MKD MDA BIH KOS* Source:ILO,2015,KILM9thed.*2012figure;**notincludingKosovounderUNSCR1244. Figure2.Labourforceparticipation(left)andemploymentrate(right),workingage 12 ILO,2015,WorldEmploymentandSocialOutlook.Figurefor2014. 29 70 65 CentralAsia CentralAsia 65 60 60 SouthCaucasusandWesternCIS 55 55 [SERIES NAME] 50 [SERIES NAME] SouthCaucasusandWesternCIS [SERIES NAME] 50 [SERIES NAME] 45 45 40 Source:CalculationsbasedonILO,2015,KILM9thed.*exceptfor2012and2013,averagesdonotinclude KosovounderUNSCR1244. Figure1.Unemploymentbysub-regionforworking-agepopulation,overtime(left)andin2014(right) 16 [SERIES NAME] 80% Acmve 14 100% 60% 12 [SERIES NAME] CentralAsia Jobless 10 40% 20% 0% CentralAsia 8 SouthCaucasusandWesternCIS 6 South South Caucasus Eastern and Europe* WesternCIS ECIS* Employmentrate Unemploymentas%ofpopulamon Inacmve Left:Regionalandsub-regionalunemploymentrates(weightedaverages).Right:Sub-regionalbreakdownof labourmarketforworkingagepopulation,2014.Source:CalculationsbasedonILO,2015,KILM9thed.*except for2012and2013,averagesdonotincludeKosovounderUNSCR1244. Insomecountries,andinalltheSoutheastEuropeaneconomies,employmentratesarebelow50%of theworkingagepopulation.Theeconomiccrisisof2008-2009resultedinthelossofmanyjobs,whichisclearly reflected in the unemployment trends (Figure 3). Although in most countries, economic growth recovered relatively quickly, in some countries employment rates have been slower to recover. The impact on youth participationandemploymentrateshasbeenparticularlystark(discussedfurtherbelow). 30 Long-term unemployment (LTU) is usually defined as unemployment lasting for over 12 months. Available data indicate high LTU incidence in the Western Balkans, where 70-90% of the unemployed have been searching for employment for longer than 12 months (Figure 4). Considering the overall high unemploymentratesinthesecountries,thismakesforasubstantialsectionoftheworkingagepopulation.A study using different data13 shows a high incidence of LTU in Azerbaijan, wherever 50% of the unemployed were found to have been searching for jobs for over 12 months, and 75% were not officially registered. (Of thoseregistered,lessthan5%werereceivingsocialbenefits.)Long-termunemploymentmanifestsitselfmore stronglyamongcertainsocialgroups,suchasRoma(discussedfurtherbelow). Figure2.UnemploymentandLTUforworking-agepopulation,latestavailabledata 35 30 25 20 15 10 5 0 Unemploymentratein2014 LTU Source:ILO,2015,KILM9 .Unemploymentdatafor2014*unemploymentdatafor2012;**averagedoes notincludeKosovounderUNSCR1244.LatestavailableLTUdataforvariousyears2009-2014(seeStatistical Annex). Labour market gender differences are significant throughout the region. These differences are particularly visible in the Caucasus and Central Asia, but also in some Southeast European countries such as BosniaandHerzegovinaandTurkey.Worryingly,inmostcountries,genderinequalitiesonthelabourmarket, as measured by the inactivity rate are increasing. Long-term unemployment has particularly strong gender dimensionsinCentralAsia:inallthecountriesofthissub-regionexceptforKazakhstan,gendergapsinlabourforceparticipationrateshavebeenincreasing. Figure3.Adultlabourforceparticipationrategendergap,maleminusfemale th 13 UNDP/MartinaLubyova,2013,TowardsDecentEmploymentthroughAcceleratedStructuralReforminAzerbaijan. 31 50 40 30 20 10 0 -10 TUR KOS* TKM UZB MKD BIH KGZ ALB GEO TJK ARM SRB MNE UKR BLR KAZ AZE MDA 2014-2005 2014 Gendergapinlabourforceparticipationfor2014,andchangeinthegendergapover2014-2005period. Source:CalculationsbasedonILO,2015,KILM9thed. Overall, standard labour market indicators point to worrying disparities in employment outcomes, which in turn suggest considerable inequalities in employment opportunities. They also point to significant differencesinemploymentoutcomesbysub-region,withSoutheastEuropeancountrieshavingmoretroubling indicatorsthanCentralAsia,theSouthCaucasusandWesternCIScountries.However,asdiscussedbelow,the standardindicatorsmaybeunabletofullycapturelabourmarketdisparitiesintheregion,largelybecausethey do not capture the quality of employment. Central Asia may have higher participation rates and lower unemployment rates than the Southeast European countries, but few would argue that the quality of employmentisbetter,orthatthereislessvulnerability. Limitationsofstandardemploymentindicators Suchstandardlabourmarketindicatorsaslabourforceparticipation,employment,andunemployment ratescannotinthemselvescapturethefullextentofinequalitiesinthelabourmarketintheregion,forseveral reasons. First: the employment rate shows the share of the working-age population that is engaged in a productiveactivity—irrespectiveofwhetherthisactivitycorrespondstofulltime,regular,formalanddecent employment.Thisindicatordoesnotdistinguishbetweenthosewhowork“normal”orregularworkhourson regular contracts, versus those on shorter and unstable work schedules. Nor does it indicate whether the activity is in the formal or informal sector, and therefore whether the individuals in question have rights to protection, a safe working environment, and to social insurance coverage. This indicator thus gives no indicationofthequalityoftheemploymentenjoyedbydifferentsectionsoftheworkforce,andtheextentof under-employment and low quality, low wage employment.14 A person working a 40-hour week as an employeeofaformalsectorenterprisewillbecountedasemployed,inthesamewayassomebodyworkingin atemporaryjobfor1-2hoursaday,orasaself-employedfarmer,workinginformallyonasmallplot.Togive someexamples: 14 seeILO’sstandarddefinition,usedtoderiveemploymentindicatorsfromLabourForceSurveys. 32 • • Kazakhstan has the highest participation rate in the region (at just under 80% of the working age population),butsome30%oftheemployedworkforceisself-employed,withthemajorityengagedin smallscalelow-productivityagriculturalactivities.15 In Azerbaijan (the country with the second highest participation rate in the region), 37% of the workforce(and44%ofthefemaleworkforce)isemployedinagriculture,whichaccountsforjustover 5% of GDP.16 This disparity results in low rates of labour productivity, and therefore low agricultural incomes. KyrgyzstanandTajikistanhavehighparticipationrates,butalsosomeofthelargestsharesofworking poor and vulnerable employment (see below), as well as labour migrants in the region—suggesting thatthenumberandqualityofemploymentopportunitiesareinsufficient. Second:theunemploymentrateisusuallyseenasameasureofthelackofemploymentopportunities: the proportion of people who do not have a job but are “actively” looking for one. This definition is also problematic, particularly in those countries with low labour force participation rates. As one analyst puts it: “most‘potentially’unemployedpersonseitherdonot‘actively’searchforemployment,fallinginthecategory of‘discouragedworkers’,orseekoutalivingintheovercrowdedinformaleconomy,inastateoftendescribed as‘disguisedunemployment’”.17Variationsintheeligibilitycriteriausedforregisteringthenatureandduration of unemployed status may also affect incentives for job-seekers to register as unemployed or engage in job search activities (i.e., stay in the labour force)—thereby influencing reported labour-market trends. In some countries these criteria are more restrictive, in order to limit entitlements to unemployment and other benefits;whereasinothercountriestheyaremoregenerous.(Insomecountriesoftheregion,lessthanone percentoftheunemployedreceivebenefits.18)Seeninthislight,thequalityoftheunemploymentrateasan indicatorforcapturingthoseaffectedbylackofemploymentopportunitiesisproblematic. Third: assessments of labour market performance in the region are sometimes confused by data quality questions for those indicators that are reported. Differences in reported unemployment rates sometimes reflecting differing methodologies used to collect the underlying data (e.g., labour force surveys versus registration data reported by employment offices). The region’s large circular and irregular migration flowstendtodepressreportedlabourforceparticipationrates,asmigrantsworkingabroadmaybeincludedin domestic populations (as per national census data) but not counted by labour force surveys as labour force participantsoramongtheemployed.WhilenotuniquetothetransitionanddevelopingeconomiesofEurope, Turkey,andCentralAsia,theselacunaemayfurthercomplicatetheinterpretationoflabourmarketdatainthe region. Measures to improve labour market statistics are crucial for more effective policy making. So are efforts to ensure the regularity of published data on employment and/or migration flows, which allow disaggregation by socio-economic (gender, age, rural/urban location, conflict impact) vulnerability criteria. Innovative ways of combining quantitative and qualitative data collection and analytical methods are also required in order to understand the inequalities within the employed, and the barriers facing those not participatinginthelabourmarket. Employmentqualityandthedisadvantagedwithinthelabourforce While the ILO manual on Decent Work Concepts and Indicatorssets out 10 different types of work, these can be generally be treated in terms of: (i) productive work delivering a fair income; (2) safety in the • 15 ЭкономическаяактивностьнаселенияКазахстана2010-2014,KazakhstanStateStatisticalCommittee2015 http://www.worldbank.org/en/news/feature/2015/01/06/jobs-challenge-in-the-south-caucasus-azerbaijan;Lyubova/UNDP Ghai,D.,2003,DecentWork:ConceptsandIndicators.InternationalLabourReview,142(2),113-145. 18 ILO,2014,WorldSocialProtectionReport2014/15. 16 17 33 workplace;and(3)accesstosocialprotectionforworkersandtheirfamilies.Lowqualityemploymentcanbe “precarious” if it entails unfavourable or short-term contracts. Informal employment (much of which is precarious) falls into two main categories: work in informal (unregistered) enterprises, and paid work in the formalsector(registeredenterprise)butunderinformalconditions(withoutcorebenefits,workers’rights,ora writtencontract).Whiletheformerismorecommoninruralareas(whereagriculturalworkisprominent),the latterismorecommonlyfoundinurbanareas. Figure4.Shareofinformalemployment,2013 70 60 Total Outsideagriculture Inagriculture 50 40 30 20 10 0 ALB ARM TUR MDA KAZ MKD SRB Source:ILOSTAT,2015,countrieswithavailabledata. Precariousandinformalemploymentintheregionisparticularlyprominentinagriculture:inmany countries agriculture accounts for more than a third of the employed population (Figure 7). In Ukraine, for example, two-thirds of informal employment take place in agriculture;19 in Armenia, this share has been reportedascloseto100%.20Suchemploymentoftenconsistsoflow-productivityagriculturalself-employment on small plots. Incomes from such work are highly unstable, due to poor harvests or fluctuating farm gate prices. For these reasons, agriculture is often considered to be a buffer between employment and unemployment or inactivity, or as “hidden unemployment”. For example, following the 2008-20099 financial crisisinArmenia,agriculturewastheonlysectortoreportemploymentgrowth.21Employmentinagriculture thereforeoftenmeetsthecriteriafornon-decentwork:lowandunstableincome,andnoorinsufficientsocial protectioncoverage. Ontheotherhand,formalsectoremploymentisnotalways“decent”,andcanalsobeassociatedwith low wages and poverty risk. For example, while public sector workers in Kazakhstan may enjoy regular contractsandaccesstosocialprotection,2009householdbudgetsurveydataindicatedthatupto50%ofthe poorinsomeregionsofthecountrylivedinhouseholdsthatwereheadedbyapublicsectoremployee.22 Figure7.Employmentbysector 19 ILO,2013,DecentWorkCountryProfile:Ukraine. ILO,2011,DecentWorkCountryProfile:Armenia. ILO,2011,DecentWorkCountryProfile:Armenia. 22 ADB/UNDPPovertyAssessment,Astana2012,p19(basedonhouseholdbudgetsurveydatafor2009) 20 21 34 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% GEO TJK ALB AZE ARM KGZ MDA KAZ SRB BIH TUR MKD UKR BLR MNE KOS ECIS 2007 2009 2009 2014 2013 2013 2013 2013 2013 2012 2014 2014 2014 2013 2014 2012 2012 Agriculture Industry Service Source:ILO,2015,KILM9thed;HDRO,2015. TheILOdefines“vulnerableemployment”astheshareofcontributing(non-paid)familyworkersand own-account(self-employed)workers.Theshareoftheworkingpoor,definedasthosewhoareemployedwith per-capita incomes below international poverty lines can be another indicator of vulnerable and low quality employment.AsshowninFigure8(left),overhalfoftheemployedintheSouthernCaucasusandCentralAsia liveonincomesbelowtheILOupperthresholdusedtomeasuretheshareofworkingpoor(i.e.,thosewithper capita incomes below PPP$4/day). Figure 8 (right) shows the share of the workforce who are self-employed (own-accountworkers)andcontributingfamilyworkers. Figure8.WorkingPoorandVulnerableEmployment 80 Workingpoor 70 70 AtPPP$2aday(2003–2012) 60 AtPPP$4aday(2008–2012) 50 Vulnerableemployment (2008-2013) 60 50 40 40 30 30 20 20 0 TJK KGZ GEO ARM ALB AZE MDA MKD KAZ TUR BLR MNE SRB UKR BIH ECIS 0 GEO ALB AZE KGZ TJK TUR MDA ARM KAZ SRB BIH MKD UKR BLR ECIS 10 10 35 Left:ShareofworkingpoorataPPPUS$2andPPPUS$4thresholds,forcountrieswheredataisavailable, latestavailableyear.Sources:HDRO,2015;ILO,2015,KILM9thEd.Right:Shareofvulnerableemployment(sum ofcontributingfamilyworkersandown-accountworkers).Source:HDRO,2015. TheILOworkingpoorandvulnerableemploymentdatamayimplyareconsiderationoftheconclusions suggested by the above-mentioned employment and labour force participation data. Whereas workers in SoutheastEuropemayfacegreaterdifficultiesinfindingajobthanworkersintheSouthCaucasusandCentral Asia,jobsinSoutheastEuropearemorelikelytobedecent,andlesslikelytobeprecarious,thaninthesesubregions.(ItshouldalsobenotedthatbothBelarusandUkraineperformquitewellintermsofthese“working poor”and“vulnerableemployment”indicators.)Thecountrieswiththelargestsharesofemploymentinlowproductivityagriculturemayfacethemostproblemswiththequalityofemployment. Labour productivity, inernational comparison 2012 Output per worker (constant 2005 international USD) 200 000 180 000 160 000 140 000 120 000 100 000 80 000 60 000 40 000 20 000 Lu xe m bo ur N g o Sw rw itz ay D ev er U ni el te land op d ed St Ec a G tes on om erm an ie s an y C M dE en id dl U tr. e &S Ea ou s Sl th ov t -E en as tE Sl ia C ze ov ur a o p ch e R kia e (n on pu La -E blic tin U )& Am C I er Es S ic a to an ni a d Tu th e C rke ar y ib be W an O R Li LD th ua ni a N Lat v or th ia A R fri us c si Eas a an t Fe Asi de a ra t R ion om an FY Bu ia R l M gar So ia ac ed ut hon Ea ia B st e As Ka lar ia u an zak s h d th sta e n Tu Pa c rk m ific en So ista n ut h Su A b- Aze sia Sa rb ha a ra ijan n Af ri Ar ca m en G ia e U org zb i ek a is Ta tan jik is ta n 0 Source:ILOGlobalEmploymentTrends2014 However, alternate measures of labour market vulnerability may produce different results. For example, data produced by the Eurostat-compatible Statistics on Income and Living Conditions (EU-SILC) surveysthathavebeenadministeredinSerbiaandtheformerYugoslavRepublicofMacedoniahavefoundthat those“atriskofpovertyorsocialexclusion”were28%and35%%oftheworkingpopulation,respectively.23 Whilethesefiguresarehigherthanthesharesofworkingpoorreportedforthesecountriesinfigure8,they areclosetoILOestimatesofvulnerableemployment. Public opinion surveys that gather information on individual perceptions of their employment status may also provide insights into the quality and precariousness of employment. For example, Caucasus Barometer data24 indicate that fewer people report having a job than what would be suggested by the employment rates generated from national labour force survey data. In Armenia, these figures were 44% (Caucasus Barometer) compared to 53% (labour force survey); in Azerbaijan they were 41% (Caucasus Barometer)comparedto63%(labourforcesurvey);inGeorgiatheywere40%(CaucasusBarometer)compared 23 EUROSTAT,figuresfor2013. CaucasusBarometer,2013. 24 36 to 56% (labour force survey). These disparities may reflect popular beliefs that informal engagement in agricultureismoreacopingmechanismthanaformofemployment. Figure9.BalkanBarometer2015 Howconfidentareyouinyourabilityto keepyourjobinthecoming12months? Howconfidentareyouinhavingajobin 2years'lme? SRB SRB MNE MNE MKD MKD KOS KOS BIH BIH ALB ALB 0% 25% 50% 75% 100% 0% 25% 50% 75% 100% AsimilarsurveyintheWestBalkansalsofoundsome(albeitsmaller)disparitiesbetweenofficialand self-reportedemploymentrates.25Manyrespondentsalsoreportedhighlevelsofuncertaintyregardingtheir futureemploymentstatus(Figure9right).Thisstudyconcludedthatthecategoriesofemployment,informal employment, unemployment, discouraged worker status, and inactivity should be viewed as points on a continuumratherthanasdiscretecategories.Significantmovementbetweenthesecategoriesmayexist,and theboundariesbetweenthemmaybeveryfluid.Still,therecanbelittledoubtthatmanyworkersintheregion labourinconditionsofinformal,precarious,andvulnerableemployment. These results are consistent with previous estimates of those vulnerable to falling into poverty, (i.e., those who are located not far above poverty thresholds). Slay et al (2015) use poverty thresholds of PPP$5.40/day and PPP$10/day and POLCALNET data to show that the vast majority of the population in Tajikistan, Kyrgyzstan, Georgia, Armenia and Moldova has been either poor or vulnerable to income poverty over the last two decades. They also find that, despite improvements in poverty (measured using the PPP$4.30/day threshold), there has been little progress in reducing the numbers of people vulnerable to poverty (measured using the PPP$10/day threshold). Approximately 67 million people in the 15 countries examined were found to be living in poverty, or vulnerable to poverty, using the PPP$4.30/day and the PPP$5.40/day thresholds, respectively. (Slay et al, 2015, pp29-39). Assuming that labour income accounts significant shares of vulnerable household incomes, low quality employment can be assumed to be affecting thevulnerabilityriskofquitesizeablesharesofthepopulation. Labourmigrants 25 WorldBank,2015,PromotingLaborMarketParticipationandSocialInclusioninEuropeandCentralAsia’sPoorestCountries. 37 Labour migration is another response to unequal access to employment opportunities in the region. Migration varies in character (formal, informal), nature (seasonal, circular, permanent), and vis-à-vis state borders(internalversusexternalmigration).Butformanyvulnerablehouseholds—especiallyinruralareas— externalmigrationhasbecomeaprimarycopingstrategyinresponsetothelackofdecentworkopportunities. Likewise,remittanceshavebecomeasubstituteforsocialprotectionsystemsformigrants’families.26 FigureXX—Sharesofpopulationoutsideofthecountryoforigin(2013) 45% 43% 40% 26% 25% 22% 21% 18% 17% 15% 13% 12% 12% 7% 7% 5% 4% 3% UNDPcalculations,basedonUNDESAmigration(countryoforigin)andpopulationdata. MigrationandremittanceflowsareparticularlyimportantinCentralAsia:asofmid-2015citizensfrom Kyrgyzstan, Tajikistan, and Uzbekistan accounted for around one third of registered foreigners in Russia (despite the absence of common borders) and for nearly three quarters of registered foreigners in Kazakhstan.27 Whereas Russia is the primary destination for migrant workers from the Caucasus and Central Asia, EU countries are the primary destination for migrants from the Western Balkans—more than 100,000 temporary residence permits are issued annually in EU countries for citizens from the Western Balkans. Migration flows from Ukraine and Moldova are more evenly split. Remittance flows from Russia to these countries are likewise substantial: four CIS countries (Tajikistan, Kyrgyzstan, Moldova, and Armenia) are typicallyamongtheworld’slargestrecipientsofremittances(relativetoGDP);dataindicatemorethan90%of theseflowscomefromRussia.28 Figure10.RemittancesinflowasshareofGDPin2013 26 InternationalOrganizationforMigration,2015,MigrationFactsandTrends:South-EasternEurope,EasternEuropeandCentralAsia. Asaresultofhighlabourmigration,someoftheregion’seconomieshavebecomehighlyreliantonremittanceincomes:remittance flowsareamongthehighestintheworld-Armenia,Kyrgyzstan,MoldovaandTajikistanareallamongtop10countriesforremittances asaproportionofGDP 27 UNDP,2015,LabourMigration,Remittances,andHumanDevelopmentinCentralAsia. 28 UNDP,2015.Georgia,Kosovo,andsometimesUzbekistanareoftenintheworld’stop20bythisindicator. 38 60% 50% Globalcountry rankofshareof remi_ancesinGDP [CELLRANGE] 40% [CELLRANGE] 30% [CELLRANGE] [CELLRANGE] 20% [CELLRANGE] [CELLRANGE] 10% [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] 0% ALB ARM AZE BLR BIH GEO KAZ KOS KGZ MKD MDA MNE SRB TJK TUR TKM UKR UZB Source:WorldBankstaffcalculationshttp://go.worldbank.org/092X1CHHD0 Thesemigrationandremittanceflowscanclearlyhelptoreducepoverty.InKyrgyzstan,forexample, householdbudgetsurveydataindicatethatremittancesyearlyreducethenumbersofpeoplelivingbelowthe poverty line by 250,000-300,000. One study finds that labour migration is absorbing a third to one half of Kosovo’snewlabourmarketentrantseveryyear.Kosovarmigrantsreportthatspendingtimeabroadimproves theirprospectsforfindingdecentemploymentuponreturninghome.29However,theseflowsalsohavetheir drawbacks. For one thing, they are strongly pro-cyclical, meaning that an economic downturn or tighter migrationrulesinRussiacanleadtodramaticdeclinesinremittanceflows.Becausemuchofthismigrationis highly irregular, workers often have no choice but to engage in more precarious forms of migratory employment,withoutsocialprotection.Migrationmayalsoincreasedisparitiesbetweenremittance-receiving and other households.30 And because migrants workers rarely contribute to social insurance funds in either countriesoforiginordestination,migrationflowsarelikelytomeangrowingfuturepressuresonthefinancial sustainabilityofold-agepensionsystems. Youthemployment Youngpeopleoftenhaveparticularlyunequallabourmarketstatusintheregion.Onlyonethirdofthe youthpopulationisemployed,andarecentILOstudyfundsthatyouthunemploymentisexpectedtoincrease inthenextfiveyears.31Labourforceparticipationratesamongtheyouthareoftenwellbelow50%;insome countries, such as Moldova, it is as low as 20% (Figure 11 below). While low participation rates among the youth do not necessarily imply poor labour market performance (many young people may choose to study longer), low youth employment rates in the region are often accompanied by high rates of youth not in education,employmentortraining(NEET).32Thelabourmarketimpactofthe2008-2009globalfinancialcrisis 29 UNDP,2014,KosovoHumanDevelopmentReport2014:Migrationasaforcefordevelopment. SeeFalzoni,A.andSoldano,K.,2014,RemittancesandinequalityinEasternEuropeancountries;andPeterski,M.andJovanovic,B., 2013,“DoRemittancesReducePovertyandInequalityintheWesternBalkans?EvidencefromMacedonia”. 31 ILO,2015,Globalemploymenttrendsforyouth2015:scalingupinvestmentsindecentjobsforyouth. 32 Mauro,J.A.andMitra,S.,2015,Understandingout-of-workandout-of-schoolyouthinEuropeandCentralAsia.Figuresfor15-24age group,post-2009. 30 39 withintheregionwasmuchgreaterforyouththanforotherworkers.33Youthemploymentratescontinueto declineorarestagnant. The highest rates of youth unemployment are reported in Southeast Europe: in Bosnia and Herzegovina, Serbia, and the former Yugoslav Republic of Macedonia more than half of young people are unemployed. These are some of the highest youth unemployment rates reported globally. The youth labour market situation is particularly severe in the former Yugoslav Republic of Macedonia, where a recent study foundthatonlyaboutathirdofyouthsareeconomicallyactive(ofwhichmorethanone-halfisunemployed)— and only a sixth are in regular employment.34 Three quarters of those seeking a job have been doing so for more than a year. While many youth who are not in employment are studying, one-quarter of the youth populationisbothout-of-schoolandout-of-work. LabourmarketexclusionconcernsarealsoapparentintheSouthCaucasusandWesternCIScountries, wherethelabourparticipationrateforyouthfellfrom55%in2000to37%in2013.Youthunemploymentrates likewise range from around 30% (in Armenia and Georgia) to 14% (in Moldova)—slightly above the global averageof13%.InallofthesecountiesexceptforMoldova,overhalfofthisyouthunemploymenthasalongtermcharacter(oneyearorlonger).35Migrationisalsoacommoncopingstrategy—particularlyinArmeniaand Moldova (which typically rank in the world’s top 10 countries in terms of the ratio of remittance inflows to GDP). Youth unemployment rates tend to be particularly high among the less-educated: in Ukraine, for example,closeto70%ofyouthwithonlyprimaryeducationareunemployed.36 Figure5.Youthlabourforceparticipation(left),employmentrate(right) 50 Youthparmcipamon 40 Youthemployment CentralAsia CentralAsia 45 [SERIES NAME] 40 35 30 SouthCaucasusandWesternCIS [SERIES NAME] [SERIES NAME] 35 30 South Caucasus and Western CIS [SERIES NAME] 25 33 ILO,2014,GlobalEmploymentTrends.Figurefor2013.ILOregionalestimatesincludeCroatiaandtheRussianFederation. Elder,S.,Novkovska,B.,Krsteva,V.,2013,LabourmarkettransitionsofyoungwomenandmenintheformerYugoslavRepublicof Macedonia.SeealsoMojsovska,S.andJaneska,V.,2014,EconomicandSocialImplicationsoftheYouthUnemploymentintheRepublic ofMacedonia.JournalofSocialPolicy,7(11),11-44. 35 Elder,S.,Barcucci,V,Gurbuzer,Y.,Perardel,Y.andPrincipi,M.,2015,LabourmarkettransitionsofyoungwomenandmeninEastern EuropeandCentralAsia.Basedonasurveyoffivecountriesoftheregion(Armenia,Moldova,FYRMacedonia,Ukraine,Kyrgyzstan), th andRussia.FigureforGeorgiaisobtainedfromILOKILM8 ed. 36 Ibid. 34 40 20 Youthunemployment [SERIES NAME] 15 [SERIES NAME] 10 CentralAsia SouthCaucasusandWesternCIS 5 Source:CalculationsbasedonILO,2015,KILM9thed.*exceptfor2012,averagesdonotincludeKosovounder UNSCR1244. Figure6.Youthlabourforcein2014 100% 100% 90% 90% 80% 80% 70% 70% 60% 50% 60% 40% 50% 30% 40% 20% 30% 10% 20% CentralAsia South South Eastern Caucasus andWestern Europe* CIS ECIS* Employmentrate Unemploymentas%ofpopulamon Inacmve 10% 0% ALB ARM AZE BLR BIH GEO KAZ KOS* KGZ MKD MDA MNE SRB TJK TUR TKM UKR UZB 0% NEET2009 NEET2013 NEET2014 Source:CalculationsbasedonILO,2015,KILM9thed.*AveragesdonotincludeKosovounderUNSCR1244; Kosovodatafor2012. Youthlabourforceparticipationdatamaybemisleadinginthatyoungpeoplemayimprovetheirjob market prospects by remaining in school rather than actively seeking employment. However, in most of the region, between a quarter and a third of youth populations are “not in employment, education, or training” 41 (NEET). NEET rates reported in the region range from around 40% (Armenia, 2009) to around 12% (Belarus), withmanycountriesinthe25-30%range(Figure12).37 Inmostoftheregion,youngwomenaremorelikelytobeout-of-workandout-of-schoolthanyoung men.ThisdifferenceisparticularlypronouncedinCentralAsia,wherethesub-regionalNEETaverageis37%for womencomparedto19%formen.38AsimilarpatternisapparentinTurkey:whereasfemaleNEETratesreach 35%,foryoungmentheyarearound15%.Youngmenaremorelikelytobeunemployednon-students,while youngwomentendtobeinactivenon-students:youngmenarelookingfor(regular)jobswhileyoungwomen arenot. While unemployment and NEET rates among youth in the region are worrisome, the quality of employmentofthosewhoareworkingmaybeofequalconcern.Thedatathatareavailablesuggestthatyouth are more likely to work informally, without written employment contracts (in Armenia this is the case for almostoneinfouryouthemployees39),orascontributingworkersintheirfamilies’businesses—oftenwithout social protection or regular remuneration. In Armenia and the former Yugoslav Republic of Macedonia, this form of employment has been assessed at 17% and 22% of total youth employment, respectively.40 In Kyrgyzstan, one study found that more than a third of young people in rural areas were working on family farms(orinfamilybusinesses)sixyearsafterleavingeducation.41 Groupsatparticularriskoflabourmarketexclusion UNDP’s 2011 Regional Human Development Report found that individuals living with disabilities, or who are members of an ethnic minority, are at greater risk of economic and social exclusion. However, whether these risks are translated into actual exclusion depends on how they interact with risk drivers (i.e., institutions,norms,policies)andcontexts(i.e.,suchlocalfactorsasresidenceinruralorurbanareas,aswellas inmono-companytowns;accesstopublictransportandeconomicinfrastructure).Whenpoliciestopromote inclusion(ortheinstitutionalcapacityneededtoimplementsuchpolicies)areabsent,labourmarketexclusion can trigger vicious circles of social and economic exclusion—further depressing prospects for labour market inclusion.42 Drivers of labour market exclusion may differ between countries. Barriers to employment can arise fromsystemicexclusionbasedongender,ethnicity,orgeography.InMontenegro,geographyisanimportant factoraslong-termunemploymentratesinthecountry’sruggednortherninterioraremorethandoublethose reported in the southern coastal regions.43 The position of Roma—one of the region’s largest ethnic minorities—isanillustrativeexampleofagroupfacinganelevatedrisksoflabourmarketexclusion,andfrom there exclusion more broadly. Survey data indicate that Roma unemployment rates in 2011 in much of the WesternBalkansreached50%—wellabovenotonlynationalunemploymentrates,butalsotheunemployment ratesreportedfornon-RomacommunitieslocatedincloseproximitytoRomaneighbourhoodsorsettlements (Figure 13). These survey data also show that joblessness rates (reflecting both the unemployed and discouraged workers) reported for Roma women were well above those for Roma men—as well as for nonRomawomen(Figure14).44 37 Mauro,J.A.andMitra,S.,2015.Tajikistandatafrom2007and2009. Ibid.Sub-regionalaveragesuseavailabledata;somecountrydataismissing. 39 YouthStudiesInstitute,Armenia,2013. 40 Elder,S.etal.2015.SWTSsurveys2012-2013. 41 ETF(2013),TransitionfromschooltoworkinKyrgyzstan.Resultsofthe2011/12transitionsurvey,Turin. 42 UNDP,2011,BeyondTransition:TowardsInclusiveSocieties. 43 ETF,2011,Long-TermUnemploymentinNorthernMontenegro:FromAnalysistoAction. 44 TheUNDP/WB/ECRegionalRomaSurvey,2011comparedsocio-economicpositionofRomacommunitieswithnon-Roma communitieslivingincloseproximityinAlbania,BiH,Kosovo,Macedonia,Moldova,MontenegroandSerbia(andNewEUMember States) 38 42 Figure13.RomaandNon-RomaUnemployment,andnationalunemploymentrate,2011 60% 54% 53% 49% 50% 44% 37% 40% 30% 30% 30% 27% 23% 20% 18% 20% 27% 10% 0% ALB BIH MKD Romaunemploymentrate MDA Non-Romaunemployment MNE SRB Namonalunemploymentrate15+ Source:UNDP/WB/ECRegionalRomaSurvey2011. UnequalemploymentoutcomesarealsoapparentinthewagesearnedbythoseRomawhodomanage to find jobs—which in 2011 were found to be 45%-80% of the wages earned by non-Roma. Roma women’s wageswerefoundtoamounttoonly45%ofthoseearnedbynon-Romamen,and54%ofthewagesearnedby non-Romawomen.RomayoutharelikewiseatgreaterriskofexperiencinglabourmarketexclusionthannonRomayouth:the2011surveydataindicatethatunemploymentratesforRomayoutharewellabovenational andnon-Romaunemploymentrates(Figure16). Figure14.Romajoblessnessrates,maleandfemale JoblessratesofmaleRomaandnonRoma(%,2011) JoblessratesoffemaleRomaand non-Roma(%,2011) 90 63 42 69 59 49 38 36 Roma 55 34 38 63 85 67 89 83 73 59 56 57 81 50 41 26 Non-Roma Source:UNDP/WB/ECRegionalRomaSurvey2011. Roma Non-Roma 43 The2011surveydataalsosuggestthatdiscriminationcontributestoRomalabour-marketexclusion.As thedatainFigure15show,differencesinjoblessnessbetweenRomaandnon-Romalivingincloseproximityto Romasettlementsareminimalforpersonswithnoformaleducation.However,whilejoblessnessratesdecline aseducationlevelsriseforbothRomaandnon-Roma,thesedeclinesaremuchsteeperfornon-Roma.Since neithereducationlevelsnorlocationcanexplainthesedifferences,employerreticencetohire“theother”may offeratleastapartialexplanation. Figure15.JoblessnessratesbyeducationlevelsinSoutheast(andCentral)Europe,2011 Post-secondary 40 24 Uppersecondary 52 40 Lowersecondary 66 51 Primaryeducamon 69 61 Noformaleducamon 76 0 10 20 30 Roma 40 50 60 70 80 80 90 Non-Roma Source:UNDP/WB/ECRegionalRomaSurvey2011. Figure16.YouthRomaandNon-RomaUnemployment,andnationalyouthunemploymentrate,2011 80% 69% 70% 71% 56% 60% 56% 47% 43% 50% 40% 65% 61% 39% 37% 49% 50% 30% 20% 10% 0% ALB BIH Romaunemploymentrate MKD MDA Non-Romaunemployment Source:UNDP/WB/ECRegionalRomaSurvey2011. MNE SRB Namonalunemploymentrate15+ 44 ThesesurveydataalsopointtoextensiveRomaengagementintheinformaleconomy.InAlbania,87% ofworkingRomamen,and79%ofRomawomen,wereemployedinformallyin2011.Theintensityofinformal employment was particularly strong in Bosnia and Herzegovina, as well as in Montenegro (Figure 17). As formal-sector employment is a precondition for eligibility for many forms of social protection, Roma households’extensiveengagementintheinformalsectormayalsoimplytheirexclusionfromsocialprotection and social services. More than one half of Roma respondents participating in the 2011 survey reported difficultiesinacquiringmedicines,comparedtooneinfournon-Romasurveyrespondents.45 Figure17.RatioofRomatonon-Romaprevalenceofinformalemployment 7 4.6 5.1 4.8 2.6 4.3 3.1 3.9 2.8 2.6 1.3 1.5 BiH Macedonia Montenegro Male Serbia Albania Moldova Female Source:UNDP/WB/ECRegionalRomaSurvey2011.Involvementininformalemploymentisdefinedasthe percentageofworkers(15-64)whoarenotpayinghealthorpensioncontributions. The above analysis strongly suggests that significant numbers of workers in the region are facing significant risks of labour market exclusion, which can easily translate into risks of social exclusion more broadly. The problem is not just lack of jobs—it is a lack of decent jobs. These numbers correspond to estimatesofthenumbersofindividualswhohaveincomesclosetopovertylines,andwhocouldeasilyslipinto poverty—which,giventhepredominanceofprecariousandvulnerableemploymentintheregion,couldeasily happen.Sincewagesarethemainsourceofincomeforpoorandvulnerablehouseholds,shiftingthepatternof growthsothatthebenefitsaccruemostrobustlytolow-incomehouseholdsrequires,firstandforemost,the acceleratedcreationofwell-payingincome-andemployment-generationopportunities. Policiesandprogrammingforlabourmarketinclusion Insomerespects,prospectsforgeneratingsignificantnumbersofdecentjobsintheregiondependon factorsbeyondgovernmentcontrol.Theseincludeinparticulargrowthratesinkeyglobalandregionalexport markets,thepricesofkeyexports,andthe like.However,governmentscan undertakemeasurestoincrease employers’willingnesstohigherworkersintheformalsector.Theseinclude: • Reducingsocial-securityandothertaxesonlabour.Theserevenuelossescanbeoffsetby:(i)higher taxes on carbon-intensive and other environmentally unsustainable activities; (ii) reductions in tax 45 UNDP/Ivanov,A.,Kagin,J.,2014,Romapovertyfromahumandevelopmentperspective. 45 • • • breaks or budget subsidies that accrue primarily to wealthy households; and (iii) more aggressive measurestoreducethediversionofbudgetrevenuestotaxhavens. Raisingtheprofileofemploymentpolicieswithinoverallpolicyframeworks.While“gettingtheoverall growth framework right”, and improvements in business and commercial environments are clearly necessaryconditionforemploymentgrowth,theyarenotsufficientconditions.Whole-of-government approaches, in which responsibilities for implementing national employment strategies are clearly assigned to all relevant government bodies needed instead. In practice, however, employment is typically“embracedbyeveryone,butownedbynoone”. Investmentsinstatecapacityareoftenneededinsuchareasaspublicemploymentservices,national labour policy coordination structures, and platforms for dialogue and employment partnerships between the private sector, government, and civil society partners (including labour unions). Public employmentservicesinparticularhaveparticularlyimportantrolestoplayinaddressinglabourmarket exclusion. Stronger regional- and local-level presences, better use of employment-relevant egovernanceplatforms,andstrongerabilitiestocoordinateandpartnerwithotherinstitutions—inthe state (e.g., social service offices, vocational training centres), private sector (employers) and in civil society(e.g.,NGOsrepresentingvulnerablegroups)—allthis(andmore)isneeded. Be willing to address labour-market discrimination, particularly as concerns ethnic minorities (e.g., Roma) but also women. In some cases, improvements in institutional capacity among labour offices and NGOs may be enough to redress deep-seated labour market exclusion. In other cases, however, publicawarenesscampaignsandother,legalmeasurestotacklediscriminationmaybeneeded. Socialprotectionandsocialinclusion Inequalities in employment opportunities, and their links to social exclusion, have important implications for social protection systems. The emergence of extensive informal employment has put considerablefinancialstrainonpoorly-financedsocialprotectionsystems.Atthesametime,employmentand social protection systems that were designed to work in near-full employment conditions have not been flexibleenoughtomeettheneedsofthosemostatriskoflabourmarketorsocialexclusion.Thiscombination hascommonlyledtothedesignandimplementationofsocialpolicyreformsthathavefocusedonreducingthe sizeandcoverageofsocialassistancebenefits—despitethepaucityofdecentjobs. When combined with labour market policies, social protection has the double role of: (i) promoting decent employment (with social insurance coverage); and (ii) providing income support to those who find themselves without employment. When social protection systems are ineffective, the loss or lack of employmentcancreateviciouscyclesofexclusion.Theseinturncanbeaggravatedbythelackofreformsin, and inadequate coordination between, public employment services and social protection agencies—with the latter focusing on mediation, and the former on administration of benefits. Vocational education, labour market, and social protection policies are often fragmented across different sectors, with inadequate instrumentsforinter-departmentalcoordination.Thesignificanceoftheseproblemscanbefurthermagnified bythefactthatlabourmarketdataandindicatorsarenotalways“fitforpurpose”(asexplainedabove). Social protection can be understood in different ways. Here we refer to social insurance (pensions, maternityleave,sickleave,invaliditypension)basedoncontributoryschemes;(ii)socialassistancebasedon tax-financed support to the poor or vulnerable; (iii) locally provided social support services to households (including for the elderly living alone, families with members who have disabilities); and (iv) active labour marketmeasuresaimedathelpingtheunemployedpopulationfindajob. 46 In all the countries of the region except Turkey, broad social protection systems featuring both contributory social insurance46 components and non-contributory47 components were in place prior to the 1990s.Combinedwithgenerallytightlabourmarketconditions,thesubsidiesforbasicgoodsandservicesthat wereavailablepriortothe1990s,andextensivepublicinvestmentintheprovisionofhealth,education,and othersocialandcommunalservices(someofwhichwereprovidedbythestate-orsociallyownedenterprises, orpublicadministration,inwhichmostpeopleworked),thesesystemsprovidedhouseholdswithhighdegrees ofeconomicsecurity—muchofwhichwascodifiedinlegal/constitutional“rights”to“free”health,education andotherservices.However,thesesystemswerealsoquitebureaucraticinnature,andwerelesseffectivein resolving problems of social exclusion that required local solutions, or could not otherwise be addressed by regionaldevelopmentorpublicworksprogramming. The economic transitions that took hold in the 1990s presented huge challenges for these social protectionsystems.Theemergenceofextensivelabour-marketinformalityandirregularmigrationflows,often combinedwithdemographictrendsthathaveincreasedthenumbersofpensionersrelativetotheworkforce, have threatened the financial sustainability of contributory pension schemes and left growing numbers of workersuncoveredbysocialinsurancesystems.Socialassistanceprogrammeshavebeenexpanded,inorderto both address these challenges and compensate for reductions in labour market security and in subsidies for basic goods and services. However, fiscal considerations, concerns about further weakening incentives for labourforceparticipation,andtechnicaldifficultiesinsettingappropriateeligibilitycriteria(minimizingerrors of inclusion and exclusion) have limited the scope and effectiveness of these programmes. Moreover, some countrieshaveemphasizedtheprovisionofsocialassistanceto“deserving”socialgroups(e.g.,warveterans) whosemembersmaynotnecessarilybeamongthemostpoororvulnerable. TheWorldBank’sASPIREdatabasecanbeusedtoaddressquestionsaboutthesizeandnatureofthe resulting gaps in social protection coverage. Data in Figure 18 indicate that both social insurance and social assistanceprogrammesreducepovertyandinequality(Gini)indicatorsacrosstheregion.However(apartfrom in Azerbaijan), social insurance (presumably pensions) has the greater impact—reflecting relatively large benefitsizesandnumbersofbeneficiaries.However,thedatainFigure19indicatethatinmostcountries,less thanquarterofallsocialprotectionbeneficiariesareinthepoorestquintile—suggestinglargecoveragegaps amongthemostvulnerable.Moreover,non-contributorysocialassistancecoversonlyasmallproportionofthe poorest 20%. Social protection systems in Kazakhstan, Kyrgyzstan, and Tajikistan seem to be particularly lacking:incoverageofthepoorest,spending,andinpovertyandinequalityimpact.Bycontrast,Ukraineand Belarus appear to achieve impressive reductions in poverty and inequality thanks to higher-than-average spendingandgoodcoverageofthepoorestquintile. Social protection in Central Asia. Coverage of both social insurance and social assistance in Kazakhstan,Kyrgyzstan,andTajikistanisthemostlimitedintheregion—particularlyforthepoorestsectionof thepopulation(Figure19).48Theimportanceofformallabourmarketstatusindeterminingeligibilityformany forms of social insurance excludes significant portions of the labour force in the latter two countries, who engage in irregular migration. Moreover, support for the so-called working poor (i.e., households with employed adults) is almost total absent. Remittance inflows therefore serve as a substitute for formal social protectionsystems(atleastinKyrgyzstanandTajikistan).However,thelabourmigrationthatgeneratesthese inflowsalsoreducescontributionstosocialinsurancesystems,whichbothreducestheirfinancialsustainability anddeprivesmigrantsofaccesstofuturepensionsandotherbenefits.SocialprotectionsystemsinTajikistan and Kazakhstan appear to be quite ineffective in relieving poverty among the poorest, while Kyrgyzstan can reportmoderatesuccessinthisrespect(Figure19).Tajikistaninparticularisfacingurgentchallengesofbetter targetingsocialassistancetopoorfamiliesthatdonotreceiveremittances.49 46 Insuranceagainstrisksofunemployment,employmentinjury,disability,sickness,maternity,andoldage. Socialassistanceoflastresort;socialpensions,somedisabilityrelatedallowance,childandbirthallowance,housingandutility support. 48 ComparabledataforTurkmenistanandUzbekistanarenotavailable. 49 Amir,O.andBerry,A.,2013,ChallengesofTransitionEconomies:EconomicReforms,EmigrationandEmploymentinTajikistan.In: UNDP,SocialProtection,GrowthandEmployment:EvidencefromIndia,Kenya,Malawi,MexicoandTajikistan,2013. 47 47 SocialprotectioninSoutheastEurope.WiththeexceptionofKosovo,socialprotectionsystemsinthis sub-regionarepoorlytargeted,withthepoorestquintileoftenreceivinglessthan20%oftotalbenefits(Figure 19topleft).Thisresultsinpartfromthepresenceofcategoricalbenefitsthatarenotlinkedtoincomestatus. InBosniaandHerzegovina,forexample,overhalfofallsocialprotectionspendingisallocatedtowarveterans; highspendingoncategoricalbenefitsisalsopresentinAlbaniaandSerbia. 48 Figure18.ImpactofSocialProtectiononInequalityandPoverty50 50 Inthesescatterplots,countrypointsarecolor-codedbysub-region:SEE–orange;CA–green;SCandWCIS–blue. 49 Figure19.Socialprotectionforthepoorest20percentError!Bookmarknotdefined. Source:WorldBankASPIREdatabase.NodataforMKD,UZBandTKM.ALB2012;ARM2013;AZE2008;BLR 2012;BIH2007;GEO2011;KAZ2010;KSV2011;KGZ2011;MDA2013;MNE2011SRB2010;TJK2011;TUR 2012;UKR2013.Adequacyisdefinedastheamountoftransfersreceivedbythepoorestquintiledividedby thetotalincomeorconsumptionofthebeneficiariesinthatquintile.Beneficiaryincidenceisdefinedasthe numberofbeneficiariesinthepoorestquintilerelativetothetotalnumberofbeneficiariesinthepopulation. Bottom-left:AZEexcludedfromtrendlinecalculation Throughout the Western Balkans, large numbers of elderly are not covered by any kind of pension (Albania—whereold-agepensioncoverageisquasi-universal—isanotableexception51).InSerbia,uptoonethirdoftheover-65populationelderlymaynotbecoveredbyanykindofpension.52InKosovo,bycontrast,a completere-designofthesocialprotectionsystemseemstohavecontributedtoimprovementsinpovertyand inequality(Figure19Error!Referencesourcenotfound.top)—thanksinparttotheintroductionofasimple, universalold-agepension.Eligibilityforunemploymentbenefitstendstobequitebroadinthissub-region,and registering and receiving unemployment status makes further benefits available 51 EuropeanCommission,2009,SocialProtectionandSocialInclusionintheWesternBalkans:ASynthesisReport. EuropeanCommission,2008,SocialProtectionandSocialInclusionintheRepublicofSerbia:ExecutiveSummary. 52 50 (child/maternity/welfare/veteran benefits, as well as health insurance and pensions). This is not the case in Turkey, where only unemployment benefits are available for the registered unemployed. In the former YugoslavRepublicofMacedonia,however,accesstounemploymentbenefitsisveryrestricted.InAlbania,as well as in the former Yugoslav Republic of Macedonia, individual farmers cannot register for unemployment benefits53—aparticularissueinAlbania,wheresome40%oftheworkforceisengagedinagriculture.Onthe other hand, recipients of unemployment benefits in other countries may be involved in informal economic activities. However, those unemployed for long periods of time are often ineligible for adequate support. A recent European Commission study which included fYR Macedonia, Serbia, and Turkey found that most servicesaddressingthelong-termunemployedarenotparticularlyeffective.54 Social protection in the South Caucasus and Western CIS. Wide variance in social protection performanceisapparentinthesecountries.Ontheonehand,inUkraineandBelarusbothsocialassistanceand socialinsuranceprogrammesenjoyrelativelygoodcoverageofthosemostinneed(Figure19bottom),andare overall quite successful in both reducing poverty and inequality (Figure 19 top). However, the replacement ratesofsocialinsurance(contributory)programmes,andinparticularofunemploymentinsurance,arelow— reducing their effectiveness. (This is particularly the case in Moldova, where the entitlement period is very short and where contributions are limited by high rates of labour emigration.) While poverty in Belarus and Ukraine is far less widespread than in other parts of the region, it is more concentrated in certain social groups—suchasthosewithoutformalincomes,orpeoplelivingwithdisability. IntheSouthCaucasuscountries,bycontrast,socialinsurancesystems(i.e.,pensions)appeartohave generous coverage among the poorest—but social assistance is much less effective. Oil-rich Azerbaijan is an exception,whereover90%ofthepoorestreceivesomesortofbenefit(Figure19topright),andwheresocial protection makes up over 80% of the poorest quintile beneficiaries’ consumption (Figure 19 top left). Many structuralshortcomingsareapparentinthesesystems—inGeorgia,forexample,unemploymentbenefitsare non-existent.WhileunemploymentbenefitsexistintheotherSouthCaucasuscountries,theirlevelsarequite low.Moreover,becausethesearefinancedonacontributorybasis,workersintheinformalsectorwhodonot contributetotheunemploymentcompensationfundareunabletoclaimbenefitsfromit. Whilesocialprotectionsystemsacrosstheregionhavegenerallyretainedtheircoverageandscopeon paper(seeAnnex1),largegapsincoverageandqualityhaveemergedinpractice.Inequalitiesinlabourmarket access are in this way extended and amplified as social exclusion. Limitations on state abilities to deliver on social protection obligations are often offset via such coping mechanisms such as remittances, precarious employment, and family support. This “informalized” social protection55 can also lead to large out-of-pocket spendingforrequiredservices,furtherdiminishingequalityofopportunitiesandoutcomesandincreasingrisk ofsocialexclusion. Socialprotectionandlabourmarketpolicies—Gettingthelinksright Extensivelabourmarketinformalityintheregionexcludessignificantnumbersofworkersfromsocial protection systems and threatens their financial sustainability. Many governments have sought to address thesechallengesby(further)raisingalreadyhighsocialsecuritytaxes:arecentWorldBankreport56notesthat, intheWesternBalkans,socialsecurityleviesandothertaxesinlabouraccountforover30%ofwages.Thistax wedgeisevenlargerforlow-wageandpart-timeworkers.However,thesehightaxesthemselvesplayamajor 53 ETF,2011,ActivatingtheUnemployed:OptimisingActivationPoliciesintheWesternBalkansandTurkey.EuropeanTraining Foundation. 54 Bouget,D.,Frazer,H.,andMarlier,E.withPeña-Casas,R.andVanhercke,B.,2015,Integratedsupportforthelong-termunemployed: Astudyofnationalpolicies.EuropeanCommission. 55 Drahokoupil,J.andMyant,M.(2009)VarietiesofCapitalism,VarietiesofVulnerabilities:financialcrisisanditsimpactonwelfare statesinEasternEuroeandtheCommonwealthofIndependentStates.HistoricalSocialResearch35,266-298. 56 Arias,O.,andSánchez-Pármo,C.,2014. 51 roleindrivingemployment,andeconomicactivity,intotheinformalsector.Effortstobreakthisviciouscycle mustthereforefocusonreducingthistaxburdenonlabour. Box3.DoesitpaytoformalizeinformalemploymentinSerbia? InSerbia,theformalizationofinformalemploymentmeansthatsocialsecuritycontributions(e.g.,tothe pensionandhealthfunds,unemploymentinsurancefund)willhavetobepaidbybothworkersand employers.Itmeansthatincometaxwillbewithheldfromworker’spaychecks.Giventhehightaxwedge andlowprogressivityoflabourtaxationinSerbia,theeffectivetaxrateishigh.Furthermore,unlikeinthe formerYugoslavRepublicofMacedoniaandBosniaandHerzegovina,socialsecuritycontributionsinSerbia donotvarywithhoursworked,sopart-timeworkersaredisproportionatelyaffected.Thiscantheoretically resultinnegativenetwagesforpart-timeworkers.Ifitleadstothereportingofincomesthatwould otherwisebehidden,formalizationcanalsomeanlosingsocialassistancepaymentsthatarelinkedtoformal reportedincomelevels.57 Asaresult,aSerbianworkerwhotakesalow-wageformaljobandloseseligibilityforunemployment benefitscansee90%ofthenominalincreaseinincomeduetoengaginginformalemploymentbelost,due tohighertaxesandunemploymentbenefitsforegone.58FormanyworkingpeopleinSerbia,formal employmentsimplydoesnotpay.Onestudyfoundthatmorethan40%ofinformalworkersinSerbiawere earninglessthanthelegalminimumwagein2008.59Despitethelowearningsofinformalwork,theirnet incomewasstillhigherthanwhatwasavailableinformaljobs. Forthesereasons,manyworkersinSerbiachoosetoremaininprecariousinformalemployment.Facedwith similarcircumstancesandincentives,thefactthatmanyworkersinothercountriesoftheregionbehaveina similarmannershouldnotcomeasasurprise. This vicious cycle also suggests that concerns that social assistance may reduce incentives for labour forceparticipationmaybeexaggerated.Instead,itistheanticipatedlossofunemployment(orother)benefits, combinedwiththehightaxationoflabourintheformalsector,thatreducesincentivesforworkerstoabandon informallabour(seeBox3).Anumberofstudiesfromtheregionbearthisout.InArmenia,forexample,the receipt of social assistance seems not to have an impact on participation in the formal labour force.60 In Tajikistan, social assistance has been found to have a positive effect on employment rates in female-headed households—suggesting that such transfer payments can actually promote social inclusion by strengthening incentivesforformallabourforceparticipation.61 Whenalignedwithwelldesignedactivelabourmarketpolicies,socialprotectionsystemscanfurther strengthen incentives for formal labour force participation, reducing social exclusion.62 Other labour marketrelated social services that can promote social inclusion include the care of children, the elderly, and others whoareunabletofullytakecareofthemselves.Unfortunately,publicprovisionofchildcareisnotavailablein some countries of the region, namely Azerbaijan, Kazakhstan, Tajikistan and Turkey.63 Support for part-time 57 Koettl,J.,2013,DoesFormalWorkPayinSerbia?TheRoleofLaborTaxesandSocialbenefitDesigninProvidingDisincentivesfor FormalWork.In:C.RuggeriLaderchiandS.Savastano(eds.)PovertyandExclusionintheWesternBalkans. 58 Arias,O.,andSánchez-Pármo,C.,2014. 59 Comparisonof2008LFSandHBSinKoettl,J.,2013. 60 WorldBank,2011,Armenia:SocialAssistanceProgramsandWorkDisincentives. 61 WorldBank,forthcoming,Ethnicity,ConflictandDevelopmentOutcomesintheECARegion.CitedinArias,O.andSánchez-Pármo,C., 2014 62 SeeKuddo,A.,2009,EmploymentServicesandActiveLaborMarketProgramsinEasternEuropeanandCentralAsianCountries. WorldBank,SocialProtectionDiscussionPaperNo.0918.SeealsoLehmann,H.andMurayev,A.,2010,LaborMarketInstitutionsand LaborMarketPerformance:WhatCanWeLearnfromTransitionCountries?WorkingPaper714,DipartimentoScienzeEconomiche, UniversitádiBologna. 63 WorldBank,2012,WomenBusinessandtheLawDatabasehttp://wbl.worldbank.org/. 52 formal employment is other means through which formal employment can be increased, particularly for women and youth whose other obligations do not allow for full-time labour force participation. This means adjustingthetaxburdenorsocialcontributionstohoursworked,andallowingforaflexiblerangeofpart-time contractsintermsofduration. Ofcourse,manyofthesemeasureshavefiscalimplications.However,alternativesourcesforfunding social services and labour market policies that can reduce social exclusion, and which can offset revenues lossesfromreductionsintaxesonlabour,exist.Thesemayinclude: • higher taxes on environmentally unsustainable activities (e.g., the use of high-sulphur coal to generateelectricity); • reductionsinbudgetsubsidiesthatsupportenvironmentallyunsustainableactivities(e.g.,fossilfuel productionandconsumptionsubsidies),orwhichaccrueprimarilytothemiddleclass(e.g.,categorical benefitsforwarveterans)orthewealthy; • moreaggressivemeasurestoreducethediversionofbudgetrevenuestotaxhavens;64and • morerobustdirectionofbudgetaryprocurementandcontractingresourcestocompanies(e.g.,social enterprises)thatexplicitlypromotesocialinclusion. 64 ThemostrecentreportoftheGlobalFinancialInstituteonIllicitFinancialFlowsfromDevelopingCountries:2004-2013findsthatthe countriesintheregiononaveragelose$65billionannuallyinillicitfinancialflows.Iffivepercentoftheseflowscouldbecapturedas taxes,thiswouldgenerateanadditional$3.2billioninbudgetrevenues.(Formore,seeDevKarandJosephSpanjers,IllicitFinancial FlowsfromDevelopingCountries:2004-2013,GlobalFinancialInstitute,December2015.) 53