Deliverable 4.1 National Briefing Papers ... - YOUNG ADULLLT

H2020-YOUNG-SOCIETY-2015 YOUNG_ADULLLT Deliverable 4.1

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Deliverable report for

YOUNG_ADULLLT

Grant Agreement Number 693167

Deliverable 4.1 National Briefing Papers with national and regional data

sets

Due date of deliverable: 1/10/2017 Actual submission date: 7/11/2017

Lead beneficiary for this deliverable: University of Granada (UGR)

Dissemination Level: PU Public X PP Restricted to other programme participants (including the Commission

Services)

RE Restricted to a group specified by the consortium (including the Commission Services)

CO Confidential, only for members of the consortium (including the Commission Services)


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TableofContents1. Descriptionoftask...........................................................................................................................3

2. Descriptionofwork&mainachievements...........................................................................4

2.1Activities.......................................................................................................................................4

2.2ExecutiveSummary.................................................................................................................5

3. DeviationsfromtheWorkplan.................................................................................................16

4. Performanceofthepartners.....................................................................................................16

5. Conclusions.......................................................................................................................................16

6. Annex–allnationalreportsandintroductiontothereports.....................................16


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1. DescriptionoftaskTask4.1:Developaframeworkforthecollectionandanalysesofquantitativedata(months9-13):Developingaframeworkforthecollectionandanalysesofquantitativedatainvolvesidentifyingandselecting relevant sources and dimensions of the labour market and education/training atinternational/national (macro)andregional levels.The frameworkwill alsoaddress issuesofdataquality, reliability and validity necessary for its implementation and for analysing the results. Tocreate synergies, this task will draw from insights and experiences of previous research andmethodological guides (e.g., COE,2005; Iacovouet al., 2012; ISS,2008)and focuson the followingdimensions:• The socio-economic dimension (indicators: national youth work structures, youth work in theregionalsettings,qualification,noformalqualification,migrants,andtypesofoccupation);• The labour dimension (indicators: employment/ unemployment rate, youth unemployment rate,job quality levels, precarious forms of employment level; temporary or involuntary part-timecontractlevels);• The education, training and learning dimension (indicators: access to education, schooling form,drop-out rates, early school leavers, literacy levels, level of official language teaching, access tocommunicationtechnologieseducation,youngpopulationhavingcompletedcompulsoryeducation,populationhavingcompletedhigheducationlevel,accesstoparticipationinlifelonglearning);•TheSocialdimension(indicator:nationalLLLpoliciesforyoungadults)The data collection will be gathered according to gender, age, and other relevant differentiationcriteria.Roleofparticipants:WPleader(UGR)andcoreteams(GU,UNIVIE)developandcirculatetheresearchframeworkandprovideagridforthereportingtonationalparticipants,whoread,reviewandgivefeedbackontheframeworkdevelopedbytheWPleader.Task4.2:Obtainingspecificinformationanddatacollection(months13-17):The purpose is to obtain and analyse comparable information and data compiled by internationalorganisations suchas theEU (Eurostatgeneral and regional indicators, and surveys:LabourForceSurvey, EU-SILC, European Social Survey, Adult Education Survey) and the OECD (Education at aGlance,OECDSkillsOutlookwith resultsof theSurveyofAdult Skills -PIAAC,OECDEmploymentOutlook2013).Theanalyseswillallowforcontextualisedcomparisonofthedifferentnationalcases.Role of participants: National partners use the framework developed by theWP leader and coreteamstocollectandprepareallrelevantdataforanalyses.Task4.3:Conductanalysesofstatisticaldataonthespecificlivingconditionsofyoungadultsintheregionalsettings(months:17-19):Thistaskinvolvestheanalysisofstatisticaldataonthespecific livingconditionsofyoungadults inthe regional settings about LLL. It also includes interpreting data according to standards of livingconditions of young adults in the countries. Each national research team will be guided by thequestion as to themeaning of data on youth unemployment/employment, educational levels, andqualificationformal/non-formal,inthespecificcontexts.Roleofparticipants:Eachpartnerconductstheanalysesat thenationalandregional levelaccording to theWP framework,producingnationalbriefingpaperswithnationalandregionaldatasets,briefdescriptiveanalysisandcontextualisationofdata.


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2. Descriptionofwork&mainachievements

2.1ActivitiesTheoverallobjectiveoftheWP4focusesontheinterplayatmacro,mesoandlocallevel between Life Long Learning (LLL) policies, young people’s living conditionsand country and region specific contexts in promoting or deterring growth andsocialinclusion.ResearchconcerningthisWPinvolves:1)developingaframeworkfor analysingquantitativedataon the specific living conditionsof youngadults inregional contexts; 2) collating and analysing the data from international datasources3)conducttheanalysisandwritingthenationalreports.

ToattaintheseobjectivestheworkinvolvingWP4forthefirstyearconcentratedondevelopingaworkingpaperproposalwiththetheoreticalapproachandworktobedevelopedbynationalpartners.Differentversionsoftheworkingpaperwerefirst discussed with the core partners (UNIVIE & UG) and the Coordinator(WWU) and later with the rest of partners. After taking into account, thefeedback received from all partners, the final version ofWP4 proposal has beenusedastheguidelines.

To facilitate the attainment of the different objectives of the WP4nationalreports twomilestone activities were set. All partners had to conduct themand upload their pieces of work on the internal project server used by theConsortium.UGRandUNIVIEteamswereprovidingawork-in-progressexampleoftheworktobedoneforeachmilestoneactivityandprovidingindividualandgeneralfeedbacktoallpartnersforeachactivity.Thethreemilestoneactivities

referred to the three objectives mentioned above: 1) interpretating and solvingdoubtsabout thedata collation;2)evaluating the youngadults living conditionsacross different regionalunitsandcountry, and, 3) assessandcomplementthedataqualityprovidedbyinternationaldatasources.

Thesemilestoneactivitieswereusedasastartingpointtowritethefirstdraftofthenational reports.Allpartners submitteda firstdraftof thenational reports at theend of July 2017. TheUGR teamprovided feedback bymid-August. Each nationalpartnerintroducedthefeedbackasdeemedappropriateandsubmittedthefinalsubmission of the national report by mid-October,sothattheUGRteamcouldworkonDeliverable4.1.

Presentations and further discussions on the work to be done and theorganisation bymilestoneactivitiestookplaceduringtheconsortiummeetings inPorto(November2016)andinGranada(June2017),aswellasinthecoordinationmeetingwithallempiricalWPswithintheprojectinBarcelona(January2017).


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2.2ExecutiveSummaryTheoreticalframework

WP4conductsaquantitativeanalysisofyoungadults’socialand livingconditions,byanalysingsocio-economicdata(macrodata)aggregatedatthenationalandlocallevel on different dimensions in participating countries. YA living conditions aredefinedasresultingfromyoungpeople’spositionintheeducationsystems,orinthetransition fromeducation to employment, but their riskprofile requires a refinedmethodological operation. In WP4, we consider these risk profiles and analysecountry/regionspecificsettingsofyoungpeople’s livingconditions(seeFigure1)to set the stage for the investigation of LLL policies implications, which areaddressedinthesubsequentWPs(fromWP5toWP7).Thisapproachinformsaboutthe contextual dimensions that correlate with the production of different riskprofiles. We aim at identifying different profiles of young people at risk, to gainunderstanding of the contextual configurations of risks affecting young people indifferentcountriesandregions.

The complexity and multidimensionality of the phenomena analysed require anintegration of different methods of research. To set the stage for furtherinvestigation of how LLL policies affect young adults six basic dimensions areselected. Definitions and descriptions of these dimensions, as well as a list ofindicatorsanddataforeachofthem,isgiveninsection1.Thedatacollectedbythecore team fromofficial andcomparable statistical sourcesareaggregatedat threedifferent levels: national (the more widely comparable); regional (NUTS2). For acomplete discussion of the approach used, see the introduction section whichprecedesthenationalreports.

Belowitfollowsasummaryofthemainfindings:

Austria: The national briefing paper will provide a short overview of the livingconditionsofyoungpeople inAustriaand,morespecifically, in the two functionalregionsselected,namely theregionofViennaandUpperAustria.The tworegionssharesomecharacteristicswithinthesamefederalregulatoryframework,buttheypresentdifferencesinthesocio-economicstructure,politicaltraditionanddegreeofurbanization, as well as in the way they react to common challenges like youthunemployment.

Population:Austriahasanincreasingold-dependencyrateandadecreasingyoung-agedependency.ValuesforUpperAustriaareclosetothecountryaveragewhileinViennatheweightofyoungpeopleisstrongerbecauseofmigrationinflows.

Economy:ViennahasaleadingroleintheAustrianeconomy,confirmedbythehighGDP per capita. Also, the industrial region of Upper Austria shows a remarkable


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economicperformance,astheGDPperinhabitantisabovethenationalaverage.

Education: in Upper Austria young people heavily participate especially in uppersecondary education, while higher education is more widespread in Vienna. Thepercentage of low-educated young adults increased after 2014. The link betweeneducationandthelabourmarketstillappearstobestrongerinAustriaifcomparedto theEuropeanaverage.However, the rateofyoungpeopleoutofeducationandworkishigherintheViennaregion,whileextremelylowinUpperAustria.

Labourmarket:EmploymentinAustriahasbeenincreasingespeciallyintemporaryand part-time jobs. However, the economy cannot fully absorb the growth in thelabourforce:thishasledtorecentincreasesinunemployment,especiallyforyounglow-skilledpeople.InVienna,youngpeoplefaceahigherunemploymentrisk,whileyouthunemploymentratesinUpperAustriaarelowerthanthecountryaverage.

Social protection: Austrian expenditure for social protection benefits to protectpeopleinneedisaboveEUaverage.Socialwelfarestandardsarestillhighoverall,astheproportionofthepopulationatriskofpovertyorsocialexclusionisoneofthelowest among EU Member States, but some groups must face greater risks, inparticular,olderwomenandchildrenofforeign-bornparents.

Bulgaria:The quantitative characteristics describing living conditions, education,structure of the economy and labor market in Bulgarian conditions are veryimportant for understanding the transitions of young adults from education toemploymentandtheopportunitiesforlifelonglearning.Thereportfocusesontwofunctionalregions:BlagoevgradandPlovdiv.

Bulgaria has very high shares of people with higher education compared toEuropean partners, and in 2014 two thirds (66.5%) of the 20-24 age group arestudents.Thisisasignthateducationisstillperceivedasavalue-added,beingalsoaresultofthehighereducationactivepolicytowardsyoungadults.Theproportionofpeople aged between 30 and 34 with upper secondary education (ISCED 3-4) ishigher than in the UK, and is comparable to Germany. When it comes to adulteducation,theshareoflearners(24-34years)ismuchlowerthantheEU27average.Afterhavingcompletedtheireducationqualification,peopletendtointerrupttheirformation,whichrequiresamoreactive involvementof the trainingorganizationsinformalandnon-formaleducationandlifelonglearning.

Important differences emerge in education characteristics between BlagoevgradandPlovdivregion.Apartfromeducation,InBulgaria,almostallotherdimensionsexamined in the report show poorer conditions compared to EU average. Socialprotectionexpenditurepercapita increasedfrom2005to2014butremainsmuchlowerthanthatofotherEUcountries.TheHouseholdsdisposableincomein2013is


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muchlowerthaninotherEUcountries.Theshareofpeopleatriskofpovertyandsocialexclusion inBulgariadecreased in theperiod2006-2015,and from2008 to2015itisrelativelystablebetween40%and50%.ThesevaluesdescribeBulgariaasthe poorest European countrywith low standard and poor living conditions. Theoverall satisfaction for those aged18-30years inBulgaria (-1.161) ismuch lowerthantheaverageforEU28(-0.014)asmen(-1.211)aremoresatisfiedthanwomen(-1.109). The overall conditions are characterized by a process of slow economicstabilization, income growth, poverty reduction, increasing youth employment,growthindisposablehouseholdincomeandhigheducationalattainment.However,thereisstillalottobedonetoreachtheaveragevaluesdescribingthequantitativecharacteristicsofthequalityoflifeintheotherEUcountries.

Croatia: This paper provides a short overview of the living conditions of youngpeople in Croatia, focusing on two Croatian functional regions (Istria County andOsijek-BaranjaCounty).Basedontheobtaineddata,youngpeopleinCroatialiveinconditionsarelessfavourableincomparisonwiththeEU28average.Thisconcernsyouth inboth functionalregions,eventhoughtheIstriaCounty ismoredevelopedthantheOsijek-BaranjaCounty.

Themaindemographiccharacteristic isadeclineof therateofnaturalpopulation(including increasing the average age of the population and low fertility rate).Croatian economic conditions are significantly below the EU28 average (theCroatianGDPissignificantlylowerthantheEU28average,andtheCroatianlabourproductivity is significantly under the EU28 and Euro area countries average).Comparing Croatia with other EU countries, the share of youth living with theirparentsisveryhigh.ThemainstrengthsoftheCroatianeducationsystemareaverylowearlyschoolleavingrateandthehighproportionofsecondaryvocationalschoolgraduates entering higher education. The main weaknesses are low results ininternational studies of numeracy, literacy and reading skills of youth, aswell asextremely low participation in early childhood education and care and adulteducation.Theeconomicactivityrateofyouth(age15-24)hasdecreasedinthelastten years. Croatia is one of the three EU28 countries with the highest youthunemployment. The key issues faced by young people when entering the labourmarketinCroatiaarethelackofpreviousworkexperienceandmismatchbetweentheir qualifications and the skill demand.Moreover, economic active youth in thelabour market shows a great gender gap. Characteristics of the Croatian socialwelfaresystemshowthatthesocialprotectionexpendituresinthenationalGDParebehindtheexpendituresintheGDPofEU28average,whilethematerialdeprivationrateismuchhigher.However,thelivingconditionsforyoungpeopleinCroatiaandthe Gini index have a tendency to be similar to the European average. The bestaspect of healthcare in Croatia is the broadness that encompasses the population


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with free healthcare including persons in the regular system of education andpersons with low income. However, Croatian people are less satisfied than theaverage European citizens in the field of satisfaction with the financial situation,overall life, recreational and green areas and living environment. Moreover, theavailability of health services is not uniform in all regions of Croatia and it issignificantlyweakeraboutotherEUcountries.AllanalyseddatashowthatthelivingconditionsofyoungpeoplearebetterinIstriathaninthefunctionalregionOsijek-Baranja.

Germany: This report analyses young adults living conditions in Germany byfocusingontwofunctionalregionsasRhein-MainandBremen.TheGermansocietyis undergoing demographic changes due to an ageing society and an inflow ofmigrants.However, thegrowthof thetworegionsdiffers largely,as theFRRhein-Main is constantly growing due to worker inflow, whereas the population in FRBremen is shrinking. While in FR Bremen young adults are more likely to beresponsible in a young age for children, interrupting training and work in earlycareerstages,intheFRFrankfurt,especiallyinthemetropolitancore,youngpeoplearemore prone to postponing life projects of family and own children. The datashowsthattoday’syoungadultsgrowupunderdifferentcircumstancesanddealingwith different limitations (high living costs, uncertain career path, prolongededucational trajectories, etc.), which hinders them to move out of their parents’homeandachievefinancialindependentlives.Specifically,youngadultsunder25–who are recipients of welfare benefits (Harz IV) – are further prevented fromgaining autonomy by the legal regulations of social programs and labourmarketpolicies.

Wealth and economic productivity are unevenly distributed in the researchedlocales: While the core of both regions is rather wealthy, its periphery hardlyparticipatesfromtheeconomicturnover.Atthesametime,thehighlivingcostsinthe core areas hinder young adults to live and work in themore profitable coreareas. As a result, amismatch of economic opportunities and financial limitationsarises,especiallyconcerningyoungadultslivinginFRRhein-Main.Simultaneously,the regions face structural changes creating risks for career paths, particularlyaffecting young adults in FRBremen.While traditionally dominant sectors are onthedecline(suchaslogistics),otherlow-wagesectorsaregrowing,whichcouldleadtoarethinkingofyoungadults’careerchoices.

TheGermaneducationsystemischaracterisedbyatightcouplingofcertificatesandoccupationalbiographies.Withtheincreasingtrendtowardsacademisation,youngadults face a prolongation of formal education. However, this follows a peculiarinstitutional fragmentation due to themulti-tiered school system,which caters tolabourmarketswithsubstantiallydifferentneeds.Theopportunitiesforeducation,


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andthusoccupation,arelargelydeterminedbytheregiontheyoungadultsgrowup:GrowingupintheneighbouringpartsofFrankfurtamMainas,forinstance,thecityofOffenbachorAschaffenburg(theBavarianpartoftheFR)orintheruralareasofFR Bremen exponentially increases the odds of achieving at most the lowersecondary education certificate (Haupschule). Young adults living there areespecially at risk of exclusion, as this school track is continuously reduced inGermany thus also diminishing their chances in the transition into the labourmarket.Although youth unemployment rates are under the EU average, for young adultsliving in the FR Bremen, the risk is higher than in the FR Rhein-Main. Particularregionaldifferencesincontrastinglabourmarketspromoteandfostertheneedforspecific jobs as consequence of the regional structural changes. Especially the FRBremenhasahighlydynamicandcontrastinglabourmarket,howeverstilloffersalargenumberofjobsinproductionplants.Asaresult,thelabourmarketsarehighlypolarised, with focus on high and low skilled worker constantly reducing themedium-skilledworkers.Incontrast,theFRRhein-Mainoffersabroadervarietyofjobs in finance,air transportation,serviceandmedia,however,attractworkersallover Germany and worldwide who compete with the potential workers on site.Particularly as both Functional Regions attract high skilled worker in the corespreadingtheremainingskilled jobs in itsperipherycausingprecarioussituationsforNEETsandearlyschoolleavers.Being at riskof social exclusion andpoverty varies remarkablywithin andacrossboth Functional Regions. Living in the core of both regions enhances the risk ofreceivingbenefits for long term-unemployment.However, the riskvarieswith theregions.Theabove-mentionedpovertyriskprofilesaresimilarregardinghealth,asgrowingupinpoorfamiliesleadstoadecreasedhealthstatus.Thisriskenhancesforyoungadultslivinginmoreruralareas,astheaccesstohealthcareislimited.Asdetailedlocaldata ismissing,weconcludedbasedondataonpovertyandunemployment,that the health risk is also high in the cities of Bremerhaven andWilhelmshaven(bothFRBremen)andWormsandOffenbach(bothFRRhein-Main).

Finland: The Finnish education system, especially the comprehensive school, ischaracteristically intertwined with the Scandinavian notion of the welfare state,whichentailsastrongemphasisonequaleducationalopportunities.Asoneof thekeyelementsoftheScandinavianwelfaremodel,thecomprehensiveschoolsystemis identified by universal, non-selective, and free basic education provided by thepublicsector.PISAresultsfromtheearly2000’sonhaveshownthatnotonlyistheaverage level in reading, mathematics, and sciences high in Finland, but also theshareoflowachieversiscomparativelysmall.Theotherimportantsignisthatthe


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Finnish school system has been successful in compensating for the poorsocioeconomicbackgroundofpupils.Also,thebetweenschoolvariationinlearningoutcomesisoneofthesmallestintheOECDworld.Theschoolsystemhasprovedtobe homogeneous in quality. Young people have relatively good educationalopportunitiesattheuppersecondaryandtertiarylevel.However,about10percentineachagecohortyoungpeopledonotcontinueineducationortrainingafterbasiceducation. Their situation is getting worse while the competition in the labourmarket gets tighter. The other phenomenon is the decreasing level of averagelearningoutcomes tested inPISA,TIMSS, andPIRLS.The shareof lowperformershasbeengrowing.

Finnisheconomyhassufferedtwoseverecrisessince the1980’s, first in theearly1990’sandthenasaneffectoftheglobalfinancialcrisisfrom2008onwards,whichhave had drastic effects on youth employment. After the financial crisis,unemployment for young people has increased, more heavily for males than forfemales.Long-termunemploymentof20-29agedmaleswasseventimeshigherandfemaleseighttimeshigherin2016thanin2008.Uncertainemploymentprospectshavealsodiscouragingeffectsoneducationalmotivationespeciallyofyoungpeopleinthelowendoftheachievementcurve.Incertainregionsofthecountrygettingajobwithoutworkexperienceandvocationaltrainingispracticallynon-existent.ThenumberofNEETyounghasbeen slightly increasingduring thepastdecadeor so.Actually, young adults living in the two functional regions, FR Southwest FinlandandFRKainuu,liveinquitedifferentrealitieswhatcomestotheirprospects.Peopleborn innorthernandeasternpartsof thecountry tendtomovetosoutherncitiesafter completing compulsory or upper secondary education. The overallemploymentinFRKainuuhasdecreasedquitedramaticallywithinthepastdecades:thenumberofemployedinFRKainuuisonlyabout70percentofthelevelitwasatthe beginning of the 1990’s. However, Finnish young people are clearly moresatisfied with several areas of their life than their peers in Europe on average.Especially large differences between Finnish youth and European average are inaccommodation,jobsatisfaction,andoveralllifesatisfaction.

Beingatriskofpovertyandsocialexclusion is lower inFinlandthan it is inEU27countriesonaverage.About17%ofthepopulationhasbeenatriskofpovertyorexclusionbetween2005and2015.Thegapbetweendifferentpartsofthecountryhasbeengrowingduringthepastdecade.TheriskofpovertyandsocialexclusionhasgrownbiggerespeciallyinnorthernandeasternregionsofFinland.

ThenumberofchildrenborninFinlandwillbelowerthaneversincethelastfamineyears 1866-68, although the size of the population has more than doubled.According to the projection, the share of people aged under 15 in the populationwould decrease to 14 per cent by 2060. The share of people with foreign


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background has been very low compared to other European countries. Hostilitytowardspeoplewithforeignbackgroundhasincreasedduringrecentyearsamongthenativepopulation.Thesedevelopmentswill have severe consequences for thedependenceratiointhefuture.

Italy:The contextual living conditions of young adults are analysed by looking atavailable indicators at national and regional (NUTS 2) level, focusing on twofunctional regions Liguria and Lombardia and integratedwithNUTS 3 datawhenavailable.Italyisoneoftheoldestcountrieswiththelowestreplacementrate.Thismakes thedemographicstabilityand thesamesystemofsocial securitymoreandmoredependentonmigrations,which,however,aretodayoneofthemostseriouschallenges. The old dependency ratio confirms a worst demographic dynamic inLiguria incomparisonwithLombardy.Productivitygrowthremainsweak,slowingthecorrectionofItaly’smacroeconomicimbalances.Ithasbeenaproblemforyears.Makingthe labourmarketmoreflexibleandreducingthe indirectcostshavebeenconsidered a pivotal part of a wider strategy aimed at reducing high structuralItalianunemployment. LombardyandLiguria remainaround theEUaveragewithregards to theGDP,butwhile the firstone is firmlyabove ItalianandEUaverage,thesecondismuchclosertotheaverage.

Participationinadultlearningremainsapersistentconcern,inparticularforthoseneedingitmost.Italylacksofshortdegrees(EQF5)makestheaveragerateofyoungwithtertiaryeducationlevellowerthanEUaverage(andfarfromtheLisboa2020target), but at the same time the absence of technical short degrees causes theoverqualificationofworkforce,becausetherateofdegreesthatdonotuseenoughtheirqualificationinthejobishigh(moreinLiguriathaninLombardy),andtherateof highly educated youngs that migrates is growing. Despite the gradualimprovement of the labour market, long-term and youth unemployment remainhigh.Theimplementationoftheactivelabourmarketpoliciesreform,includingthereinforcementofpublicemploymentservices, is stillatanearlystage.Also, in thepublicdebate,mismatchprevailsoverthelackingcapacityofproductivecontexttoabsorb skilled workers. In the last 15 years, profits have risen, and wages havefallen, but companies did not devote their highest profits to greater investments.Thepotentialof female labourmarketparticipationremains largelyunderutilised.Access to affordable childcare remains limited with wide regional disparities,paternityleaveisamongthelowestinEU,andtheeffectivenessofcashallowancesfor childcare has not been assessed. Young people and women are confirmedtheless protectedand needystrataof society, even if the female employment hasdeveloped over time (if less than the strong EU countries). The structure of theeconomy explains a large part of the different internal outcomes. For examples,aboutourfunctionalregions,thedatashowsthatinLiguriatheriskofpovertyand


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socialexclusionishigherthaninLombardy.

Significant barriers to competition remain in important sectors, includingprofessional services, local public services, concessions and the transport sector.Thepublicsectorisbeingreformedtotacklelongstandinginefficiencies.Newsocialpolicieshavebeenput forward to respond to the risingpoverty rate. It isunclearwhether the financial resources will be sufficient to address Italy’s povertychallenge.Activationpoliciesarenotyetwidespreadenough.TherateofpeopleatriskofpovertyorsocialexclusioniswellabovetheEUaverageandisparticularlyhighforchildren,temporaryworkersandindividualswithamigrantbackground.IngenerallivingconditionsinLombardyarebetter,andthisevaluationemergesbothfrom objective data, both from perceptions of citizens. We must consider thatLiguria is the region with the oldest population, as said heavily affected by theeconomic and demographic crisis, caused serious disturbance in educational andsocialsectors.Lessyoungpeopleinanageingcontextwithfeweropportunitiesandagreaterpartof thepopulationatriskofsocialexclusionalsocontributeto lowerlevelsofsubjectivewell-beingandlowerexpectationsforthefuture.

Tosummarise,thecurrentproblemsoftheItalianeconomicandsocialcontext(lowproductivity, high public debt, inefficiencies in some sectors, poor innovation,populationageing,overcrowdedsocialpolicycosts,oftenpassive)donotfavortheconditionofYoungAdults,whotoalargeextentcontinuetoliveinthefamily(78%of people aged 20-29, vs a EU average of 55,4%). Inatime of crisis such as this,familiesarethemainsafetyvalve,reducingtheautonomyofyoungpeople.

Portugal:Thecontextuallivingconditionsofyoungpeopleareanalysedbylookingatavailable indicatorsat thenationalandregional(NUTS2) level, integratedwithNUTS 3 data when available or provided by the Portuguese National StatisticsInstitute(INE)andtheDatabaseofContemporaryPortugal(PORDATA),aswellasbyotherinstitutionalsources.Twoofthemaindemographiccharacteristicarethegrowing ageingof thePortuguesepopulationboth at national and regional levels,andthehighpercentageofyoungadultsaged20-29livingwiththeirparents.Duringthetimespan,andinspiteofthefinancialcrisisandTroika’sinterventiontheGDPandtheGVAincreasedatnationalandregionallevels.However,theperformanceofthePortugueseeconomymeasuredbyGDPperinhabitantandlabourproductivityisstillconsiderablylowerthantheEU28average.

Between2005and2016,thestructureofacademicqualificationsofthePortuguesepopulationhas improved significantly bothnationally and regionally. The rates ofschoolattainmentincreasedinallagegroups,theratioofearlyschool leaversandtherateofNEETdeclinedsignificantly.However,whencomparedtootherEuropeanpartnercountries,Portugalstillrevealsthe lowestratesofschoolattainmenteven


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amongtheyoungergenerations.

In spite of an important skills upgrading during the decade, the occupationalstructureofthePortuguese labourmarket is lessqualifiedthantheEU27average.The Portuguese youth employment rate (15-24 years old) is one of the lowest inEU27 and decreased consistently during the time span 2005-2015, showingimportantdifferencesat regional level.Unemployment ismainlyayouthproblem,particularly after 2011. In 2015, the Portuguese youth unemployment rate wasmorethanthedoubletherateofpeopleagedbetween20and64yearsandhigherthan the EU28 average. Once again, significant regional differences can be found.Generally, the Norte labour market seems to be more youth-friendly than theAlentejoone.

InPortugal, resourcesspent forsocialprotectionbenefits,provided tohouseholdsand individuals affected by a specific set of social risks and needs is one of thelowestinEU27.Inspiteofthefinancialcrisisandthegrowthofunemploymentrate,theexpenditureper inhabitantdidnotrisesignificantly,andtheexpenditurewithfamilyandchildrenandsocialexclusionare thosewere theunderfunding ismoresevere when compared with EU27. The income inequality started to increasestronglyafter2011,transformingPortugalinoneofthemostunequalcountriesinEU.

Duringthetimespan2005-2015,self-perceivedhealthinPortugalhasalwaysbeenlowerthantheEU27average.PortugalwasalsothecountryparticipatinginYOUNGADULLLT project with the lowest self-perceived health. In general, Portuguesepeopleagedbetween25-34yearsarecomparativelylesssatisfiedwiththeirlives.

ThedatashowthatthelivingconditionsofyoungpeopleinPortugalareworsethantheEU28average.TheyalsorevealsomeregionaldifferenceswhichpointtothefactthatthelivingconditionsareslightlybetterinNorte,whereValedoAveis locatedthaninAlentejowhereLitoralAlentejano’syoungpeoplelive.

Scotland: This report analyses the contextual living conditionsof youngadults intwofunctionalregionswithinScotland,theGlasgowCityRegionandAberdeenshire.It iswillwell-known in Scotland that risk profiles of young adults correlatewithsocioeconomicbackground,asforinstancemanifestedintheeducationattainmentgradientandaccesstouniversities,issuesthatarethesubjectofanongoingpublicdebate. The analysis presented here, also illustrates regional differences acrossseveraldomains.

Fortuitously, the four NUTS2 statistical regions in Scotland represent anapproximate fit with major metropolitan areas of Glasgow, Edinburgh andAberdeen,inadditiontotheHighlandandIslands.Therefore,usefulinsightscanbe


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gained from using harmonised indicators. However, many policies operate at asmallerspatialscaleandthereforesuchaggregatedataisoftenunsatisfactory.TherearegoodexamplesofrichdatasetsmaintainedataUK-level,butalsospecificallyforScotland.However,thesearelimitedintermsoftimelinessandabilitytoregionaliseresults. Efforts are beingmade to rationalise, link and exploit administrative datasourcesinScotlandmoreeffectively,butthisisstillatanearlystage.

Population:Scotlandhasarisingdependencyration,albeitfromalowerlevelthanthe UK. Greater Glasgow is in line with Scottish average, but Aberdeenshire isstarting froma lowerbase.Economy:GDPpercapita inScotland is slightlybelowthe UK average. Whilst greater Glasgow is further below this average,Aberdeenshire,withitsoilandgasindustry,isoneoftheUK'smostaffluentregions.Youthemployment inScotlandonaverage is slightly stronger than in theUKasawhole and markedly so in Aberdeenshire. On the whole, the UK comparesfavourablytoanEUaverage.Educationandlabourmarket:Intermsoftheshareoftertiary education in the working age population, Scotland is the most educatedcountry in Europe. Overall, theUK compares favourably on thismetric. However,thisclaimisdoubtfulwhentheshareoflessqualifiedworkersisexamined.Inthisregards Scotland, and the UK, compare unfavourably with Eastern Europe andGerman-speaking countries. Social protection: Average household disposableincome (GDHI) in Scotland was just over EUR 16,000 in 2013, which is aboutEUR500belowtheUKaverage.GreatGlasgowtrails theScottishaveragebyaboutEUR1000,whenAberdeenshireisapproximatelyEUR3,000abovetheaverage.

Overall, regional variation inGDHI is starkacross theUKand the rangeof spatialinequalityisfarhigherthaninanyotherEuropeancountry.ThiscastsdoubtontheanalyticalmeritofbenchmarkingScotlandagainstaUKaverage,astheUKaveragemasks a stark contrast between the South East of England and the rest. Grossdisposablehousehold income in InnerLondon,where it ishighest, isnearly threetimesthatoftheWestMidlands,whereitislowest.

Spain: The contextual living conditions of Spanish young people are analysed bylookingatnationalandregional (NUTS2) indicators, integratedwithNUTS3datawhenavailableorprovidedby localsources.Limitations in theavailabilityofdataproduceascatteredoverviewoftheyoungadultslivingconditions.Inthissense,thepresentreportraisesawarenessofhugechallengesforfurtherresearchandpolicyevaluation.Limitedinformationconstrainsthescopeofacademicdebates,butalsothe partnership between the local administrative units both in Andalusia andCatalonia represents a huge challenge ahead. Although this briefing paper,unfortunately,cannotprovidedetailsatthelevelsofautonomouscommunitiesandNUTS3, a brief glance at data for the whole of Spain inspires a few generalconclusionsonthesocialconditionsofyoungadults.Themainresultsfromavailable


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dataaresummarizedbelow.

The impact of the economic crisis seems to have hit the general conditions ofSpanish economy, although some signs of recovery seem tobe emerging togetherwithgrowingsocio-economicdisparitieswithin thecountry.SpanishdemographicdependencyratioislowercomparedtoEUpartners,althoughafastincreaseintheshareofdependentamongthepopulationisregisteredsince2009onwards.

SpainstilllagsbehinditsEuropeanpartnersiregardingeducationalattainment.Thisisinpartduetoahighlyunequaldistributionofeducationacrosstheagecohorts.Athirdofthepopulation(34.7%)agedbetween25and64yearshaveatleastattainedISCED5withanincreaseof22%from2005.Thestockoftertiaryeducatedpeopleislower compared to other European partners, and it has strongly increased.However, there is important and increasing variation between regions. Whenconsidering young adults education attainment, (people aged between 30 and 34years),theirtertiaryeducationalattainmentishigherthanotherEuropeanpartners;in2005almost2outof5peopleaged30-34haveattainedtertiaryeducation,whilein2014theproportionincreasedbyroughly6%.In2005,inAndalusia,31%ofthepopulation aged between 30 and 34 had tertiary education, and this remainedalmoststableoverthepastdecade(theincreasewas0.9%),whileforCataloniatheattainmentwas41.2%and it increased to47% in2014.However, there is a highunequalterritorialdistribution.Theratioofearlyschoolleavers(ESL)wasequalto19% in 2016, compared to the EU28 rate of 10.7%. Marked gender differencesemerged;theprevalenceofearlyschoolleaversamongwomenwas15.1%in2016,whileformenitwas22.7%.SimilarlytoESL,theproportionofyoungpeopleneitherinemploymentnoreducationand trainingagedbetween15and24years (NEET)diminished from18.6%(13.1%in theEU27) in2005 to14.6%in2016(11.5%intheEU27),althoughimportantterritorialdifferencesemerge.

Thelabourmarkethastraditionallysufferedfromveryhighunemployment,butthiswasgraduallyreducedinthe20-yearperiodupto2009.Youthunemploymenthasbeenespeciallyhighduringtherecentyearsastheeconomiccrisishasloweredtheaccesstothelabourmarket,andthetransitionbetweeneducationandthefirstjobbecame especially precarious. Additionally, employment is more concentrated inlowskilledoccupations,whilehighskilledwhite-collaroccupationrepresentsonly19%vs27%comparedtoEU27ofthepopulationemployedin2015.ThisfeatureoftheSpanish labourmarketandskills levelof theoverallpopulationplaya centralrole in explaining the divergence in labour market access across Europeancountries. Many young adults are foreign-born, these cohorts are divided bypolarisededucational inequalities,andagrowingshareofyoungadultshavebeenexposedtoincomepovertysincethefinancialcrisis.Thesetrendshighlightboththecrucial relevanceof thepolicies addressed to this age-based target group and the


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hugechallengesthatthesepolicieshavetoovercome.

3. DeviationsfromtheWorkplan

Therehasbeenonevariationfromtheworkplan:

WP4 feeded was supposed to make an in depth triangulation and use of theempirical material produced in WP5 and WP6. However, the overlap of thefieldwork of the data collection WPs made it challenging to use the emergingevidencetorefineandfeedtheanalysesofWP4.

4. Performanceofthepartners

All partners have fulfilled their tasks satisfactorily. There was an intensecollaboration with UNIVIE during the elaboration of the proposal and the datacollation that was crucial to meet the challenging deadlines. The partners haveprovidedgoodqualityoutputsandhavemettheimportantdeadlines.

5. Conclusions

TheFullAssemblydeemsthisdeliverabletobefulfilledsatisfactory.

6. Annex–allnationalreportsandintroductiontothereports

OverviewIntroductiontotheNationalReports


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Work Package 4 Quantitative Analysis Young Adults’ Data

National Reports Overview

Introduction p. 18 Austria p. 32 Bulgaria p. 56 Croatia p. 85 Finland p. 119 Germany p. 152 Italy p. 203 Portugal p. 233 Scotland p. 259 Spain p. 290


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IntroductiontotheNationalReportsWP4conductsaquantitativeanalysisofyoungadults’socialand livingconditions,byanalysingsocio-economicdata(macrodata)aggregatedatthenationalandlocallevelondifferentdimensionsinparticipatingcountries.Theresearchquestionsthatderivecouldbesummarizedintotwomaintype:whatarethedataavailabilityandgaps at regional level about the living conditions of young adults?Andwhat datacouldtellaboutthelivingconditionsofyoungadultsandtheidentificationofrisksprofilesattheregionallevel?

Thespecifictargetgroupsfordatacollectionareyoungadultsagedbetween18and29 years, the indicators are disaggregated by gender, when suitable. However,different age range are considered in the data collection when suitable for thevalidityoftheindicators.AstargetgroupofLLLpolicies,youngadultsrepresentahighlydynamicandheterogeneousgroupconcerningoflivingconditionsincludingsocio-economicstratification, lifeprojectsandperspectives(cf.Weileretal,2016).Thisgroupvariessubstantiallyregardingthedifferentrealitiesofyoungpeople inthe participating countries, i.e. specific living conditions, levels of participation,individual perceptions and life projects are, for instance, different in Bulgaria,Finland,Germany,Italy,SpainandScotland(cf.Weileretal.,2017,p.73ff).Theyareaffectedbystructuraldevelopments,suchaseconomictrends,demographicchangeand life-course de-standardization processes, common trends that are howevermediated by the institutional frames in which individuals’ lives are embedded:institutions build the set of opportunities and constraints for individual’s choices.On the one hand, the interactions among labour market, welfare, education andtraining systems define different political economies of skills, as a result ofnegotiationprocessesofskillssupplyanddemand(cf.alsoParreiraetal.,2017).Ontheotherhand,theroleofthewelfarestatealsohastobespecificallyconsidered,asvarieties of welfare states perform differently at different stages of the life andsocial groups (Anxo et al., 2010). As noted by Esping-Andersen (1999), existingwelfare regimes differentiate by the ways they socialize risks: depending on therange of risks that are addressed and on the groups to be protected, thewelfarestate can assume a minimal-residual or, on the contrary, an inclusive andinstitutional rolewith respect toother sourcesofwelfare (family/communityandmarket).

The undergoing changes in contemporary societies are transforming thecharacteristicsanddimensionsofsocialproblems,causingaspreadingsituationofsocial vulnerability in the population (Ranci, 2010). Structural changes havegeneratedanewconfigurationofsocialrisks,stronglyaffectingyoungpeople,whicharelesspredictableandthereforedifficulttoaddressbytraditionalwelfaresystemsandpolicyinterventionsbasedonsocialinsurances(Moreletal.,2012;Palier2010).


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The diffusion and intensity of those risks seem to show a considerable degree ofvariationamongcountriesandregions,aswellasdifferent reactionsbyEuropeanwelfarestates(Hemerijck,2013).Insomecountries,thisledtoarecalibrationofthewelfare system to render it better able to protect people against these changingdifficulties affecting the life course. In other countries, as in Italy, this did nothappen(Ranci&Migliavacca,2015).Therefore,topursuetheaimoftheprojectbyanalysing how LLL policies define, target and affect young people life courses inEurope,weneed first to assess young adults’ living conditions, their vulnerabilityandtheirconnectedrisksprofilesinnationalandregionalcontexts.

How do we define YA’s living conditions? YA living conditions are defined asresultingfromyoungpeople’spositionintheeducationsystems,orinthetransitionfrom education to employment, but their risk profile requires a refinedmethodological operation. It is WP4 task to define these profiles. In WP4, weconsider these risk profiles and analyse country/region specific settings of youngpeople’slivingconditions(seeFigure1)tosetthestagefortheinvestigationofLLLpolicies implications, which are addressed in the subsequentWPs (fromWP5 toWP7).Thisapproach informsabout thecontextualdimensions that correlatewiththeproductionofdifferentriskprofiles.Weaimat identifyingdifferentprofilesofyoungpeopleatrisk,togainunderstandingofthecontextualconfigurationsofrisksaffectingyoungpeopleindifferentcountriesandregions.

Figure1:Livingconditionsandriskprofiles

The complexity and multidimensionality of the phenomena analysed requires an


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integrationofdifferentmethodsofresearch.ThequantitativeanalysiscarriedoutinWP4 integrates with the other WPs to triangulate and inform each step of theresearch. In developing a research design appropriate for answering the project’squestions, WP4 develop research hypotheses that are grounded in the scientificliterature andwill drawon the full breadthof available data. To set the stage forfurther investigationof howLLLpolicies affect young adults six basic dimensionsare selected. Definitions and descriptions of these dimensions, aswell as a list ofindicatorsanddataforeachofthemisgiveninsection1.Thedatacollectedbythecore team fromofficial andcomparable statistical sourcesareaggregatedat threedifferent levels: national (the more widely comparable); regional (NUTS2). Anessential part of the research is to develop a complementary set of indicators atregional level.Thissetof indicatorswascomplementedbyeach teamthrough thecollection of specific indicators available at local level that could be relevant forshedding light on context specificity. These indicators are in line with thedimensionsidentifiedintheframeworkoftheanalysis.Moreover,animportantstepis to assess the quality and comparability of the indicators across the Europeanregions. In this line, every national briefing provides a quality assessment on theavailabilityandqualityofthedatainrelationtotheobjectivesoftheWP4.

1. DefinitionofthedimensionsofcontextuallivingconditionsWe identified six dimensions of contextual living conditions which representdifferent aspects of young adults’ experience and are strongly correlated oneanother. To identify these dimensions, we extensively relied on literature oncompositeindicatorsonsocialjusticeandqualityoflife(Mazziotta&Pareto,2016;Schraad & Tischler, 2016; Noll, 2016; UrBes, 2015; European Commission, 2015;Eurostat,2015;Schepelmannetal.,2010;OECD,2008,2013),aswellasonwelfarepolicies (Kazepov&Ranci, 2016;Moreletal., 2012;Esping-Andersenetal., 2002;Esping-Andersen, 1999), life course (Walther, 2006; Verdier, 2012) and school towork transition (Raffe, 2014; Ryan, 2008). The dimensions we consider are thefollowing:

A=Demographicstructure

B=Generalstateoftheeconomy

C=Education

D=Labourmarket

E=Welfareandsocialinclusion

F=Healthandwell-being


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1.1Demographicstructure(A)ThedimensionDemographicstructure(A)referstodemographiccharacteristicsthatcanbeusedtodescribethepopulationanditssubgroups.Livingconditionsofyoungpeople are shaped by the demographic context, as the structure of a populationdeeply affects the characteristics and intensity of social needs of its varioussubgroups. Population ageing and the dynamics of migration are commonlyidentified as drivers of transformation within European societies and socialprotection systems (Castles et al., 2010; Brandolini et al., 2009; UNHCR, 2015).Moreover, the role of the households with respect to living conditions of youngpeople is widely recognised (Esping-Andersen et al., 2002; Saraceno, 2015): thefamily is considered as a source of welfare and redistribution of resources,according to the principle of reciprocity (Esping-Andersen, 1999); and it alsostronglycontributesinshapingeducationalpaths, labourmarketparticipationandpovertyrisks.However,theorganizationoffamilylifeandtherelationshipbetweenthefamily,thestateandthemarketvarywithinandacrossnationalsettings(Daly,2010; Bahle, 2009). Accordingly, this dimension analyses the structure of thepopulation by looking at its composition, as well at the fields of genderrelationships, households’ characteristics (type and size), fertility and degree ofurbanisation(OECD,2013;Rhodes,2005).

The demographic dimension includes four sub-dimensions. Sub-dimensions onpopulation structure and population density, urbanization and territory includeindicators related to the population structure (including migration and ethnicaldiversity of societies), its characteristics regarding density, urbanization andterritory. The sub-dimension household structure focuses on the households’structureandsize.Finally,thesub-dimensionbirthandlifeexpectancycoversissuesrelatedtofertilityandlifeexpectancy.

1.2Generalstateoftheeconomy(B)ThedimensionGeneralstateoftheeconomy(B)referstotheeconomiccontextandthe structure of the productive system, as elements framing living conditions ofyoungpeople indifferentnationaland local contexts. It canbebroadlydefinedasthenetworkofconnectionsandinteractionsamongeconomicactorsinvolvedintheproductionandexchangeofgoodsandserviceswithinthemarket.Thisdimensionisrelated to the impact of economic trends related to technological innovation,terziarization,economicandfinancialglobalization(Ferrera,1996),onthestructureof Europeannational and local economies.Here,wemainly look at themarket assource ofwelfare,where the allocation of resources followsmarket relationships(Esping-Andersen,1999). Inthe lightof theYAproject,acorrectunderstandingofthe characteristics of the economy, as embedded within various forms of social


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organization (Mingione, 1997), helps explain the preconditions for policiespromotingbotheconomicgrowthandsocialdevelopment(OECD,2001;Moreletal.,2012).Thecurrentphaseofcapitalismhasbeenvariouslydescribedas“knowledge-basedeconomy”or“globalisinglearningeconomy”(Brownetal.,2001;Lundvall&Lorenz, 2011; Jensen et al., 2007), thus stressing the relevance of innovation,research and skills for the competitiveness of firms. Accordingly, a competitiveproductive systems can result in an improvement of the quality of goods andservices, creating jobs and addressing societal challenges (European Commission,2015). As an example, labour productivity is regarded as ameasure of economicgrowthand livingstandardswithinaneconomy(OECD,2014b), stronglyaffectingyoungpeople’sopportunitiesindifferentcontexts.

The Economy dimension includes three sub-dimensions. First, the sub-dimensionstructureoftheeconomyconsidersindicatorsrelatedtothegeneralstructureoftheeconomicsystem.Second,thesub-dimensioninnovationcapturesthespecializationofenterprisesaswellastheinvestmentininnovativeandhigh-technologysectors.Finally, the sub-dimension labour productivity relates to the efficient use ofresourcesintermsoflabourproductivity.

1.3Education(C)The Education dimension (C), refers to access, process and outputs of education(Checchietal.,2014;Pawson&Tilley1997).Thecomparativeeducationliteratureshowshowtheinstitutionaldesignofeducationandtraininghasavarietyofeffectson the acquisition and distribution of educational attainments and achievements(Dupriez, Dumay, & Vause, 2008; Green, Green, & Pensiero, 2015; Hanushek,Woessmann, & Zhang, 2011; Heisig & Solga, 2015; Mons, 2007). This stream ofliteraturehasessentiallyfocusedonwhatisaneffectiveinstitutionalarchitectureineducation provision focusing on macro institutional differentiation. It has useddifferent dimensions such as the levels of stratification and standardisation, thedegrees of access and accessibility, the levels of state control and expenditure(Allmendinger & Leibfried 2003; Green 2007; West & Nikolai 2013; Biggart,Järvinen & Parreira do Amaral 2015). These studies identify a range of differenteducational and training systems that are closely associated with a country’sspecific history and culture, which have in turn shaped the development of therespective nation-state (Busemeyer & Trampusch, 2012; Green, 2013; Mayer &Solga,2008).

Moreover,theliteratureonschool-to-worktransitionsandskillsmismatchassesseshow the nexus between education outputs and labour market varies amongcountries, thus affecting youth living conditions and shaping life trajectories(Gambetta1987;Allmendinger,1989;Raffe,2014;Pastore,2011;Quintini&Martin,


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2006). In this field, VET systems and dual education experiences are gainingincreasingattention,asbridgespotentiallysmoothingthepassagefromeducationtoemployment (Eichhorst et al., 2015; Popiunik & Ryan, 2011). Accordingly, thisdimensioncoverstheavailableindicatorsoneducationandtraining,withaspecificattention directed to VET. We integrate them with diverse young adults’ skillsmeasures. In detail, we consider indicators related to input and outputs of theeducationsystems(OECD,2014a).

Theeducationandtrainingdimensionincludesfoursub-dimensions.Thefirstsub-dimension on education access considers indicators related to the access to theeducationsystemindifferentnationalandlocalcontexts.Thesecondsub-dimensioncovers indicatorsrelated toeducationalattainments (qualifications).The thirdsub-dimensionlooksateducationoutputs,concerningskills’achievement,dropoutsandlack of participation. Finally, in the sub-dimension education policy,we consideravailableindicatorsontheinstitutionalsetting,expenditureandpoliciesinthefieldofeducation.

1.4Labourmarket(D)TheLabourmarketdimension(D)focusesontheinteractionamonglabourmarket,welfare state and education structures, by looking specifically at the demand andsupplysideoflabourandyoungadultsskills(Busemeyer&Trampusch,2012;Hall& Soskice, 2001). The participation of young people in the labourmarket deeplyaffects their life opportunities and social identities. Moreover, it is seen as a keyobjectiveofpolicystrategiestryingtoconnecteconomicgrowthandsocialinclusion(Morel et al., 2012). However, young people in contemporary societiesmust faceincreasing disadvantages in the labour market: on the one hand, they often lackworking experience and related skills that are highly valued by employers (Ryan,2008);ontheotherhand,economicandlabourdevelopmentswithinpost-industrialsocieties deteriorate employment prospects for low-qualified people (Bonoli &Mouline,2012).Asaresult,youngpeopleareoftendepictedasagroupofoutsidersregarding labourmarketaccessandoutputs (Lindbeck&Snower,2001),butsuchoutcomes strongly vary across countries (Emmenegger et al., 2012). This reflectstheinteractionbetweendifferentcontextualandinstitutionalconditionsatstake.Inthe social science, scholars have written extensively on the association betweenoccupational attainment, education, skills, showingpositive relationshipsbetweenthose dimensions (Abrassart, 2013; Bol & van de Werfhorst, 2013; Heckman,Stixrud,&Urzua,2006;Psacharopoulos&Patrinos,2004;vandeWerfhorst,2011).Theincreasingcomplexityoflabourmarketsrequiresselectionandallocationbasedon education attainment associated with cognitive and non-cognitive skills(Heckmanet al., 2006).Against thisbackground, thehumancapital theoryarguesthat education provides individual with enhancing skills which make themmore


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productive.Ontheotherhand,goodpositionalapproachescontendthateducationacts as a screening device for employers and establish a proxy for the marginalproductivityof theemployees.Thus,weconsider theavailableempirical evidencerelatedtothelabourmarket,employmentdynamics.

The labour market dimension includes four sub-dimensions. The first sub-dimension on labour market access considers indicators related to access andparticipation. The second sub-dimensions on labour market demand looks atindicatorsmeasuring the characteristics of the demand for labour.With the thirdsub-dimensionon labourmarketoutput,weexamineindicatorsrelatedtothetypeofparticipation(contractualarrangements)andthematchingofskillsdemandandsupply. Finally, the sub-dimension on labour market policy considers availableindicatorsontheinstitutionalsetting,expenditureandpolicies.

1.5Redistributionandsocialinclusion(E)ThedimensionRedistributionandsocialinclusion(E)focusesonthemateriallivingconditions of young people, on social policy interventions and theparticipation ofcitizens to the political and civic life. Participation fosters cooperation and socialcohesion.Thusitstimulatessocialtrust,aswellasastrongerattentiontoefficiencyandefficacyofpublicpolicies,includingLLLpolicies(UrBes,2015).However,underconditionsofpovertyandsocialexclusion,socialparticipationbecomesharder,anda-selfdeterminedlifeispossibleonlywithgreatdifficulty(EuropeanUnion,2015).This iswhymeasuringmaterial conditionsand theirdegreesofparticipation isofutmost relevance in the investigation of contextual living conditions of youngpeople.Povertyanddeprivedmaterialconditionsharmindividuallivesbyaffectingtheir health andwellbeing and lowering educational outcomes. This limits youngpeople’s chances to achieve their full potential, that is, according to a capabilityapproach,theirrealopportunitiestodoandbewhattheyhavereasontovalue(Sen,1992;Deneulin,2009;Venkatapuram,2011).Thisdimensionexaminestheextenttowhich trends towards social exclusion and polarization have an impact on youngadults’ livingconditions,alsoconsideringtowhatdegreetheyarecounteractedbypolicy interventions. Thus, we look at the available empirical evidence related topovertyandsocialexclusion;attheroleofsocialpolicyintheredistributionandre-allocation of resources; at the general participation of young people within theirbelongingsociety.

The Social inclusion and participation dimension includes three sub-dimensions.Thefirstsub-dimensiononmaterialconditionsgathersindicatorsrelatedtomaterialconditionsofyoungpeople,incorporatingindicatorsonmonetarypoverty,materialdeprivationandlowworkintensity.Thesecondsub-dimensiononsocialpolicyandredistribution includesavailable indicatorsonincomeinequalitiesandexpenditure


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onredistributivepolicyinterventions.Thethirdsub-dimensioncoversmeasuresofpolitical and civic participation, measuring individual attitudes towardsengagement.

1.6Healthandwell-being(F)This dimension combines health and individual well-being. Health hasconsequencesonalldimensionsandalldifferentphasesofpeople’s life,modifyingtheir life conditions and influencing their behaviour, social relationships,opportunities andprospects. Further, health is amultidimensional feature (WorldHealthOrganization,1948)anditcomprisestoenjoya"completephysical,mentaland social well-being" and cannot be intended only as the absence of disease.Moreover, the concept of well-being is here used regarding perceptions andopinions expressed by the individuals in their own life. Here, elements of theindividuals’well-beingthroughthelifecourseareseenfromtheperspectiveoftheirwelfare(Sen,1992).Forthesereasons,weintegrateintothisbroaddimensionthewell-being as perceived by people. This subjective perspective gives additionalinformation to that provided by objective data, which are useful to measure thegeneralqualityof lifeof individualsand toenrich theanalysisof contextual livingconditionsofyoungpeople.

TheHealthandwell-beingdimensionincludesthreesub-dimensions.Thefirstsub-dimension on dealswithhealth accesswithin different national and local context.Thesecondsub-dimensiononhealthstatusandsubjectivewell-beingcovershealthconditions and more subjective-driven information about young adult conditionsoverarangeoftopics.Finally,thethirdsub-dimensiononsocialexpenditurelooksatexpenditureandpolicieswithinthisfield.

2. ProcessofdatacollationThedatacollation is constrainedby theavailabilityofpre-existingdatawhicharemainly produced by Eurostat. Within the EU, the official statistical approach ofgatheringdataonstructuralinformationisusingahierarchicalcategorisationofEUterritories and regions. As a geographical system, a division was developed byEurostat to structure and classify the regional statistics resulting into thenomenclature of territorial units for statistics (Nomenclature des Unitésterritorialesstatistiques–NUTS).Theaimistoprovideasingleaswellasacoherentsystemfor“comparableandharmoniseddatafortheEuropeanUniontouseinthedefinition,implementationandanalysisofCommunitypolicies.”(Eurostat,2007,p.3). Therefore, the EU vastly uses a national state driven concept for producing,describingandimplementingregionalstatistics.However,duetochangingrealities,suchasinternationalisation,Europeanisationandglobalisationprocesses,aswellastotrendstowardsrescalingandsubsidiarization(Kazepov,2010),theconceptofthe


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nationalentitiesusingadministrativeunitsisincreasinglyquestionedbeingausefultooltodescribesocialrealities(cf.D2.3,StateoftheArtReport,p.10).

TheprojectYOUNG_ADULLLTderivesfromtheassumptionthattheimplementationofLLLpoliciesisbeststudiedattheregional/localleveltounderstandthecontext-specificity of young adult life courses beyond the national level. Therefore, theconceptofFunctionalRegionswhichwasadoptedwithin theprojectsharpens thefocusonregionaldifferencesandvariations.However, italsoraiseschallenges forthevalidityofquantitativeresearchbasedonavailableindicatorsonyoungpeopleliving conditions, as the different FRs can match/mismatch with the territorialand/oradministrativeregions thatarevastlyusedwithinestablishedstatistics,aswell as creating challenges in data availability of different sources. For instance,statistical data on socioeconomic and socio-demographic aspects, education andtraining, labour market and welfare is not limited to given administrative units(countries,states,districts,provinces,orcities).

Departingformthetensionbetweenofficialdescriptionsofcommunities,changingrealitiesanddataavailability,WP4dealswiththisintwoways:thedevelopmentofa practical approach to data collection as well as an assessment of the dataproductionprocessoftheEU.Inthecaseofthelatter,thedatagapsintheEuropeanStatistical Systems also imply how data is collected within the EU regarding ourFunctionalRegions.Thisprovidesinsighttothequestion,howdataisusedtosteerpoliticalprocessesonLLLpoliciesandthusintheprocessofdefinition,coordinationand implementationofpolicy. In the caseof thedatagatheringprocess, theWP4collectsdataascloseaspossibletotheregionallevelusingpre-existingdatasets.Inthisway, thepre-existingdata on theNUTSLevel is used, however, enriched andspecified by local/regional information. This is relevant, as subdivisions in somelevelsdonotnecessarilycorrespondtoadministrativedivisionswithinthecountry.

The data availability onNUTS-3 level is not exhaustive for all FRs. Therefore, theanalysiscombinestheselevelsofanalysisregardingtheavailabilityofthedataandwill reach NUTS2 whenever it is possible, which is derived from the system ofdivisionofEuropeanterritoryfromEUROSTAT1.ThelevelofanalysisofWP4inthissense is constrained from the existing territorial division which reflects the dataavailable.

The functional regionsare shown inTable2,with thecorresponding informationaboutthefunctionalregionsandterritorialdivision.ItshouldbeborneinmindthatdatawillbeprovidedatNUTS2.Havingestablishedtheobjectivesandtheessential1 Detailed information about territorial division of the European territory could be found at http://ec.europa.eu/eurostat/web/nuts/overview. In the EUROSTAT division, NUTS 1 corresponds to major socio-economic regions; NUTS 2 are the basic regions for the application of regional policies and; NUTS 3 are the small regions for specific diagnoses, which are generally metropolitan area.


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dimensionsandsub-dimensionsthatneedtobecovered,theindicatorsarechosenbased on their analytical soundness, measurability, country coverage(comparability),andrelevancetothephenomenabeingmeasured.

Table2.DescriptionoftheFunctionalregionswiththecorrespondingcodesat

NUTS2level.

Country Territory name intheproposal

Name in thecorrespondinglanguage

NUTS2 name inthe correspondinglanguage

Code2016 atNUTS2

TerritoryisNUTS3

Finland Kainuu Pohjois-jaItä-Suomi Pohjois- ja Itä-Suomi FI1D x

Southwest FinlandRegion Etelä-Suomi Varsinais-Suomi’ FI1C x

UK Aberdeen City &Aberdeenshire

Aberdeen City &Aberdeenshire

North EasternScotland UKM5

Glasgow CityRegion GlasgowCity West Central

Scotland UKM8 x

Germany Bremen Bremen Bremen DE50 Frankfurt Rhein-

MainAreaFrankfurt Rhein-MainArea Darmstadt DE71 x

Austria UpperAustria Oberösterreich AT31 Vienna Wien AT13 Portugal ValedoAve Ave Norte PT11 x LitoralAlentejano AlentejoLitoral Alentejo PT18 xSpain Girona Girona Catalunya ES51 x Malaga Málaga Andalucia ES61 xItaly Milan Milano Lombardia ITC4 x Genoa Genova Liguria ITC3 x

Croatia Istria-County Istarskažupanija JadranskaHrvatska HR03 x

Osijek-BaranjaCounty

Osječko-baranjskažupanija

KontinentalnaHrvatska HR04 x

Bulgaria Blagoevgrad Благоевград Югозападен BG41 x Plovdiv Пловдив Юженцентрален BG42 x

Like all concepts in the social sciences and all discipline in general, the act ofconstructing measures implies a selection of the dimensions (in Ancient GreekκατηγοριαorLatincategoria),whichhavetobeoperationalizedandthus,leadstoasimplificationoftheobjectofstudy.Thismeansatransformationofsomequalitiesintoametricwhichisnotjustatechnicalprocess,butanimportantfeatureofsociallife(Desrosières,2008;Hacking,1999).Thisprocessiscalledcommensurationandhas been largely examined by different historians, statisticians, sociologist andphilosophers(Espeland&Stevens,1998).FromPlatoandAristotletoMarx,Weber,


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SimmelandFoucault,theimplicationsofcommensurationhavebeenanalysedasaprocessthatinfluencesourvaluationandthewayweinvestingoodsandservices.The research ofWP4 could not escape the process of commensuration. First, theestablishment,recognition,anduseofastatisticalobjectareveryappealing.Second,theinterpretationandpoliticaluseofeachmeasureisaverypowerfulwaytopushforwardaspecificapproachorevenapoliticalagenda(Meyer&Benavot,2013).Inthis sense, the research objectives are constrained from existing and availablesources, their comparability and statistical issues such as representativeness.Therefore,weconsideredtheEuropeanLabourForceSurveyandtheEuropeanSocial and Income Living Conditions as themost relevant survey data sourceswhichhaveimportantinformationfortheresearchobjectivesofWP4.ThesearethefewsurveysavailableandcomparableattheNUTS2levelwhichcollectinformationonlivingconditionsofyoungadults.

3. OperationalizationThissectiondescribestheoperationalizationprocesscarriedoutinconductingthequantitative research on young adults’ contextual living conditions and lifelonglearningpolicies.Theprocessconsistedof5phases.First,thecoreteamdesignedaframeworkofanalysisandselectedthedimensionsand sub-dimensions of interest for the overall research, finally the indicatorsconnectedtothesub-dimensionswereselected.Second,theteamleaderidentifiedadministrativesourcesandcomparativesurveysandassessedthedataqualityatnationalandregionallevel.Toexploreyoungadults’conditions on the different dimensions in the participating countries, it wasnecessarytoestablishanddelimitatargetgroupbasedondifferentcharacteristics.Consideringtheheterogeneoustargetgroupsof theyoungadults in termsof theirsocio-economic stratification and living conditions, WP3 analysis and dataavailabilityconstraints,ad-hocindicatorscouldbeincludedinthedatacollectionforeachfunctionalregion.Third,thecoregroupproducedasetofindicatorsatnationalandregionallevel.TheWP4offeredacriticalreviewofthedatalimitationsandgapsattheEuropeanlevelandproposedpossiblewaystosolve it,by integrating internationaland localdatathroughthedatacollectionprocessofeachpartner.Fourth, as a first milestone in the data collection and analysis, the core teamproducedareducedsetofindicatorsthatwereusedforthecountryreport.As a final stage the core team produces an international report with acomprehensivelistofindicators.To have a clear overview, theWP4 process is outlined below and comprises thefollowingsteps:

1) DefinitionandselectionoftheresearchquestionsBased on a first proposal, the core team togetherwith the other teamsworking ondata collection established a list of research questions. The research questionswere


Page29of31

discussedinsmallgroupsandifneededredefinedandclarified.Atthisstage,someofthe research questions were redirected to the other working packages if they werelikelytoaddressmorespecificallythroughouttheirresearch.

2) Selectionofdimensionsandsub-dimensionsThe UGR team together with the core team made a first proposal of dimensions,includingtheirdefinitionandtheirtheoreticalrelationship.ThisstepwascoordinatedthroughinanonlinemeetingheldinFebruary.

3) SelectioncriteriaandindicatorsproposalThecoreteamdiscussedtheindicatorscriteriawhichincludedvalidity,reliabilityfortheoverallresearchquestionsoftheWPandcomparabilityandsimplicityofthedata.Thecore teamproposedanddiscusseda first selectionof the indicators for the sub-dimensions of the data collection, which was discussed online. This work was thenintegrated in the working package proposal and circulated among the partners. Atemplatefordatacollectionwasprovided.

4) ProvisionofspecificindicatorsbyeachpartnerIn addition to the list of indicators provided by the core team, every partner wereaskedtoprovidespecific-contextindicatorsatthelocallevel.

5) DevelopmentofindicatordescriptionsheetsConstruction of a detailed description for each indicator selected in the initialscreeninground.

6) RefinementoffinalindicatorsbasedonfeedbackTheindicatorswererefinedbasedontheinternalfeedbacks.

7) DisseminationoffinalindicatorsetThesetof indicatorswasdisseminatedamongall thepartners.A firstreleasewithashort list of indicators was sent to the partners at the end of May. The full list ofindicatorswasreleasedthroughtheplatformoftheproject.Context-specificindicatorsnot collected through harmonized data setswere collated via a template circulatedamongthepartners.

8) IndicatorsdevelopmentDevelopmentofthesetofindicatorstogetherwiththeirdescription.

References

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Bol,T.,&vandeWerfhorst,H.G.(2013).EducationalSystemsandtheTrade-OffbetweenLaborMarketAllocationandEqualityofEducationalOpportunity.


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Desrosières,A.(2008).Lastatistique,outildegouvernementetoutildepreuve.L’argumentStatistiqueI :PourUneSociologieHistoriquedeLaQuantification,7–20.

Dupriez,V.,Dumay,X.,&Vause,A.(2008).Howdoschoolsystemsmanagepupils’heterogeneity.ComparativeEducationReview,52(2),245–266.

Espeland,W.N.,&Stevens,M.L.(1998).Commensuration.pdf.AnnualReviewofSociology,24,313–343.

Green,A.(2013).Educationandstateformation(third).London:PalgraveMacmillan.

Green,A.,Green,F.,&Pensiero,N.(2015).Cross-countryvariationinadultskillsinequality:Whyareskilllevelsandopportunitiessounequalinanglophonecountries?ComparativeEducationReview,59(4),595–618.http://doi.org/10.1086/683101

Hacking,I.(1999).Thesocialconstructionofwhat?History.Cambridge:HarvardUniversityPress.

Hall,P.a,&Soskice,D.(2001).VaritiesofCapitalism.TheInstitutionalFoundationsofComparativeAdvantage.OxfordUniversityPress(OxfordUni).NewYork:OxfordUniversityPress.http://doi.org/10.1093/0199247757.001.0001

Hanushek,E.A.,Woessmann,L.,&Zhang,L.(2011).GeneralEducation,VocationalEducation,andLabor-MarketOutcomesOvertheLife-Cycle.NationalBureauofEconomicResearch,1–51.

Heckman,J.J.,Stixrud,J.,&Urzua,S.(2006).TheEffectsofCognitiveandNoncognitiveAbilitiesonLaborMarketOutcomesandSocialBehavior.JournalofLaborEconomics,24(3),411–482.http://doi.org/10.1086/504455

Heisig,J.P.,&Solga,H.(2015).SecondaryEducationSystemsandtheGeneralSkillsofLess-andIntermediate-educatedAdults:AComparisonof18Countries.SociologyofEducation,88(3),202–225.http://doi.org/10.1177/0038040715588603

Mayer,K.U.,&Solga,H.(2008).SkillFormationInterdisciplinaryandCross-NationalPerspectives.Cambridge:CambridgeUniversityPress.

Meyer,H.-D.,&Benavot,A.(2013).PISA,Power,andPolicy:theemergenceofglobaleducationalgovernance.Oxford:SymposiumBooks.

Mons,N.(2007).Lesnouvellespolitiqueséducatives:LaFrancefait-ellelesbonschoix?Paris:PressesUniversitairesdeFrance.

ParreiradoAmaral,M.,Schaufler,S.&Weiler,A.(2017b).DocumentationofDatabase.YOUNG_ADULLLTWorkingPaper.Münster:WestfälischeWilhelms-UniversitätMünster.Psacharopoulos,G.,&Patrinos,H.A.(2004).Returntoinvestmentineducation:a

furtherupdate.EducationEconomics,12(2),111–134.http://doi.org/10.1080/0964529042000239140

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Weiler,A.,Schaufler,S.,ParreiradoAmaral,M.,GanterdeOtero,J.P.&Wutzkowsky,F.(201a).LaunchingandResearchDesign.StateoftheArtReport.YOUNG_ADULLLTWorkingPaper.Münster:WestfälischeWil-helms-UniversitätMünster.

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1

Work Package 4

Quantitative Analysis Young Adults’ Data

Austria – National Briefing Paper with national and regional

data sets Ruggero Cefalo, Yuri Kazepov University of Vienna Date: 31-08-2017 Work Package 4 – Quantitative Analysis of Young Adults’ Data Deliverable D 4.1


2

TableofContentsExecutiveSummary............................................................................................................................................................................2

Introduction............................................................................................................................................................................................3

Descriptionofthedatacollatedandqualitydataassessment..................................................................................3

1. Findings...........................................................................................................................................................................................4

1.1 Demographicstructure...................................................................................................................................................4

1.2 GeneralstateoftheEconomy.......................................................................................................................................6

1.3 Education..............................................................................................................................................................................9

1.4 Labourmarket..................................................................................................................................................................14

1.5 Redistributionandsocialinclusion.........................................................................................................................18

1.6 Healthandwell-being....................................................................................................................................................21

2. Emergingissues........................................................................................................................................................................23

3. References...................................................................................................................................................................................24

Figures

Figure1:Migrationrates(leftaxe,‰),olddependencyandfertilityrates(rightaxe),naturalpopulation

change(rightaxe,‰changeoverpreviousyear),Austria,UpperAustriaandVienna,2005-2015................6

Figure2:GDPineuroperinhabitantsinPPS(leftaxe)andlabourproductivityperhourworked(rightaxe,

EU=100),Austria,UpperAustriaandVienna,2006-2015....................................................................................................8

Figure3:Educationalattainment(30-34,%)andparticipationineducationandtraining(25-34,%),

Austria,2005-2015..............................................................................................................................................................................12

Figure4:NEETrate(15-24,%)andearlyschoolleavingrate(18-24,%),Austria,UpperAustriaand

Vienna,2005-2015...............................................................................................................................................................................14

Figure5:youthemploymentandunemploymentrates(leftaxe,15-24,%),youthunemploymentratioof

youngpeople15-24(rightaxe),EU27,Austria,UpperAustriaandVienna,2005-2015......................................18

Figure6:GINIindexbeforeandaftertransfers(leftaxe,0:100),netdisposableincomeinhouseholdinPPS

(Europerinhabitant,rightaxe),EU27,Austria,UpperAustriaandVienna,2005-2015......................................19

Figure7:Highsatisfactioninvariouslifedomains(25-34,%),EU28andAustria,2013.....................................22

ExecutiveSummary

Thisnationalbriefingpaperprovidesashortoverviewofthelivingconditionsofyoungadultsin

AustriabyanalyzingthefunctionalregionsofViennaandUpperAustria,selectedascasestudies

fortheYOUNG_ADULLLTproject.

Thecontextuallivingconditionsofyoungpeopleareanalyzedbylookingatavailableindicators

atNUTS0andNUTS2level,collectedbytheworkingpackageleadersandintegratedwithlocal

data(whenavailable),alongthefollowingdimensions:demographicstructureofthepopulation


3

anditssubgroups;generalstateoftheeconomy;education;labourmarket;redistributionand

socialinclusion;healthandindividualwell-being.

Introduction

Thisnationalbriefingpaperwillprovideashortoverviewofthelivingconditionsofyoung

peopleinAustriaand,morespecifically,inthetwofunctionalregionsselectedforthe

YOUNG_ADULLLTproject,namelytheregionofViennaandUpperAustria.Thetworegions

sharesomecharacteristicswithinthesamefederalregulatoryframework,buttheypresent

differencesinthesocio-economicstructure,politicaltraditionanddegreeofurbanization,as

wellasinthewaytheyreacttocommonchallengeslikeyouthunemployment.Datawas

collectedatnational(NUTS0)andregional(NUTS2)levelaccordingtosixdimensionof

contextuallivingconditionsagreeduponintheWP4guidelines1.Eurostatonlinedatabasesat

aggregatednationalandregionallevelandmicrodatafromdifferentsurveys(LFS,EU-SILC,

PISA,PIAAC)wereusedassources.Themaincorpusofinternational,harmonizedand

consequentlycomparabledatawassuccessivelycomplementedbydatacollatedatthelocal

level.ContextuallivingconditionsofyoungpeopleinAustriaareanalyzedbylookingatthe

demographiccharacteristicsofthepopulationanditssubgroups;atthestructureofthe

economy;attheinputsandoutputsoftheeducationsystem;atthelabourmarketsituation;at

themateriallivingconditionsofyoungpeopleandattheirparticipationascitizenstothe

politicalandciviclife;athealthconditionsandindividualwell-being.

Descriptionofthedatacollatedandqualitydataassessment

EurostatandOECDprovideavastamountofdatathatcanbeusedtocomparativelyassessliving

conditionsofyoungpeopleindifferentdomainsandinvariouscountries/regions.However,

mostofthedataareprovidedatnationallevel,whiledataavailabilityattheregional/locallevel

islimitedatNUTS2levelandstronglylimitedatNUTS3level.Thisrestrainstheopportunityof

comparabilityamongregionstolimitedrangeofindicators.Moreover,harmonizeddataarehard

tocomplementwithlocaldata,oftensufferingfromafragmentedlandscapeofsources,asthey

arecollectedformoreorlessspecificpurposesandusuallynotwiththeobjectiveofinteraction

withotherdatasources.Inaddition,localdataareusuallyalreadyaggregatedanditisn’t

possibletofurtherelaboratethem.Thismakesdifficultthecomparabilityamongregionsandat

theEUlevel.AsfortheavailabledatapublishedbyEurostat,datacoverseveralfieldsandare

complementedwithmetadataandinformationabouttimeseries.However,accessibilityofdata

maybeaproblematicissue,asdatabasesonEurostatarenotcompletelycombinedandflexible

1Thedatacollectionwascarriedoninaworkinggroupofwhichalsothefollowingstudentswerepart:GeorgBayerl,Paul Marius Benjes, Philipp Gschnitzer, Alesja Kicaj, Hannes Kofler, Philipp Molitor, Tatjana Neuhuber, Niklas

Pernhaupt.


4

sothatthecollectionisattimesdifficult:asanexample,thesameinformationontwodifferent

agegroupsmaybeavailableonlylookingattwodifferentdatabasesindifferentsectionsofthe

website(theNEETratefor15-24isavailableamonglabourmarketstatisticswhiletheNEET

rate15-29isavailableamongyouthstatistics).Ofcourse,thecomplexityandvarietyofthedata

publishedmakeacomprehensiveintegrationdifficulttoachieve.InthecaseofAustria,the

selectedfunctionalregionsmatchwithadministrativeboundariesofthefederalstatesandofthe

NUTS2regions,sothatagoodcompromisebetweentheexistingdataandtheresearchobjective

canbeestablished.Notwithstanding,itisimportanttobeawarethatthedatacanonly

approximatelygraspthecomplexityofthecontextualconditionsandinterdependenciesyoung

adultareembeddedin.

Forthereasonswereported,thenationalbriefingpapermakeslimiteduseoflocaldatafrom

Austriansources,asinternationalsourcesprovideawideamountofvaluableinformationfor

ourpurpose.Localdataontopiclikedemography,economicsystem,educationandlabour

market,redistribution,healthandwell-beingaremainlymadeavailablebyStatistikAustria,the

nationalstatisticalagency.Someadditionalinformationwasretrievedbyofficialwebsitesand

reportsofAustrianInstitutions(Ministers,CriminalPoliceOffice,ChambersofLabourand

EconomicChambers).TheroleofStatistikAustriaistoprovidereliablycollectedandexpertly

analyzedpolitical,socialandeconomicinformationonAustriaanditsregions.Theagencyis

committedtocreatestatisticsforadministrativepurposesandpoliticaldecision-making,butit

alsooffersreportsandinformationtogeneral-publicandresearchusers.

1. Findings

1.1 Demographicstructure

Austriaisarelativelysmallcountry,coveringatotalareaof83,879squarekilometers,thearea

oftheregionofViennais415squarekilometers,whileUpperAustriais11,980square

kilometers.Thepopulationincreasedgraduallyinthelasttenyears,goingfrom8.2millionin

2005to8.7millioninhabitantsin2016(equalto1.7%ofthetotalEU28population),butitis

unevenlydistributedoverthecountry:thepopulationdensityisequalto104individualsper

squarekilometer(122inUpperAustria),butintherelativelysmallareaoftheregionofVienna

live4,507inhabitantspersquarekilometer.Migrationisincreasinglyaffectingthedemographic

structureofthecountry,asthecruderateofnetmigrationroseupfrom2.9per1,000in2008to

7.7in2013,andjumpedto13per1,000in2015(inthesameyear,theratewas14.3%for

Germanyand5.1%fortheUK):thepeakwasinVienna(21.6%,seeFigure1).Thelargestshare

ofmigrantscomesfromGermany,Bosnia-Herzegovina,Turkey,SerbiaandRomania.


5

ViennaisthecapitalofAustriaandatthesametimeoneoftheninefederalstates

(Bundesländer)ofAustria.Itisthe7thlargestcitywithintheEuropeanUnionandbyfarthe

largestcityinAustria.Viennaisatthesametimethemostpopulatedandthesmallestfederal

state.Morethan20%ofAustrianslivesinVienna,andthepopulationintheregionisalso

increasingatafasterpacethanthecountry’saverage(1.8%against0.4%inAustriaand0.7%in

UpperAustriain2015),reaching1.8millioninhabitantsin2014(with107.7womenevery100

men),around20%oftotalAustrianpopulation.Thecityissupposedtogrowupto2million

inhabitantsuntil2025,duetomigrationflows.Currently,42%ofthepopulationhasamigration

background,whilemorethan20%oftheVienneseinhabitantsarenon-Austrians,havingmainly

SerbiaandTurkeyascountryoforigin(StadtWien,2015).Moreover,inJune2016

approximately21,000refugeeswerelivinginViennaandseekingforasylum.

UpperAustriaislocatedintheNorthofAustria,itisthethirdlargestAustrianfederalstatein

termsofitspopulation:thenumberofinhabitantsin2014was1.4million(102.9womenevery

100men).TheregionalcapitalofLinzisthethirdlargestcityofAustria,withlittlelessthan

200,000inhabitants.InUpperAustria17.1%ofthepopulationhasamigrationbackgroundand

9.3%hasacitizenshipotherthanAustrian.ThelargestshareofmigrantscomefromBosnia-

HerzegovinaandGermany.

Lookingatavailabledemographicdata,generallivingconditionsinAustriaarecomparatively

goodwithrespecttootherEuropeancountries.Infantmortalityinthefirstyearafterbirthis

medium-low,andittouchedaminimumof3.1deathsperthousandin2015.Inthesameyear,

themedianagewas43yearsandthelifeexpectancy81.6years,attheleveloftheEuropean

average.Thelatteroverallvalueistheresultofrelevantgenderdifferences:anAustrianfemale

in2015couldexpecttolive83.7years,whileamalehadalifeexpectancyof78.8years.Austria

shareswithotheradvancedEUcountriesaconditionoflowfertilityandgradualageing.Asfor

thefirstpoint,thefertilityratewas1.47in2015.Again,thenationalvalueresultsfromregional

variations:theregionofViennaismoreaffectedthanUpperAustriabylowfertility,asthe

respectiveratewere1.42and1.61in2014.Duringthepasttwodecades,fertilityfellmostly

amongwomenintheirtwentiesandincreasedforwomenintheirthirties.Asforthesecond

point,thedemographicstructureoftheAustrianpopulationhasbeenageinginthelastten

years.Thisisshownbytheincreaseoftheold-dependencyrate(ratiobetweenpopulationaged

65andovertopopulation15-64),thatwentfrom23.5%to27.5%inthetime-span2005-2016.

Inparallel,theyoung-agedependencyisgoingdown(from23.8%in2005to21.3%in2016).

Youthpopulationaged20-24and25-29accountedrespectivelyfor6.4%and6.7%oftotal

inhabitantsin2015.WhilethevaluesforUpperAustriaareclosetothecountryaverage

(respectively6.3%and6.5%),intheregionofViennatheweightofyoungpeopleontheoverall

populationisstrongerandincreasinginthelastyears(respectively7.3%and8.5%),mostly

becauseoftheincreaseofmigrationflows(Figure1).


6

Figure1:Migrationrates(leftaxe,‰),olddependencyandfertilityrates(rightaxe),natural

populationchange(rightaxe,‰changeoverpreviousyear),Austria,UpperAustriaandVienna,

2005-2015

Source:EurostatDemographyandmigrationdatabase

Amongyoungpeople,in201352.7%ofthoseaged20-29livedwiththeparents.Thispercentage

hasshownacertainstability,fluctuatingbetween50and54%inthelasttenyears.Comparing

AustriawithotherEUcountries,theshareofyouthstilllivingwiththefamilyisslightlylower

thantheEUaverage,butitishigherthanotherCentralEuropeancountrieslikeFranceandthe

Netherlands,aswellasthanNortherncountrieslikeUKandFinland.However,theaverage

valuescoversstronggenderdifferences.Thepercentageofyoungmaleslivingwithparentsis

62.1%against41.8%forfemales,anditisworthtonotethatthis20-percentage-points

differenceiswiderthantheEU27averagedifferenceof15points,recallingthepersistenceof

genderdifferencesrelatedtotraditionalfamilystructures.

1.2 GeneralstateoftheEconomy

Austria’seconomyisleavingbehindsomeyearsofslowgrowthintheaftermathofthefinancial

crisis.GDPmeasuresshowthat,generallyspeaking,theAustriancontextismarkedbypositive


7

economicconditions.Theimpactofthecrisiswasevidentbetween2008and2009,asshownby

thedropinGDPforinhabitant(from32,500to30,900,seeFigure2).Alsotherealgrowthrate

ofregionalgrossvalueadded(GVA)showedanegativesignin2009(-4.2%).However,after

2010theeconomyofthecountrybegantorecover:theGDP,theGVAandthelabour

productivitymeasuredinGDPperhourworkedstartedincreasing,evenifataslowerpacewith

respecttothepre-crisisyears.Afterastagnationin2012-2013,thegrossdomesticproducthas

beengrowingagainsincethen(OECD,2017a).In2015theGDPinEuroperinhabitant(PPS)was

36,900,whichisupto128%oftheEUaverage.

Allinalllabourproductivitygrowthhasslowedoverthepastdecade,especiallyinservices

(OECD,2017b),butit’shigheranddevelopingatafasterpacethantheEuropeanaverage:in

2015,theGDPperhourworkedwasequalto117.1%oftheEU28.Productivityperhourworked

hasgrownconstantlysince2000and,unliketheEUaverage,didnotdropevenduringthecrisis

years,butproductivityperemployeeremainedflatafter2008-2009.Theexplanationisthatthe

increaseinemploymentsincethecrisishascreatedmorepart-timejobsandfewerfull-time

ones,sothatproductivityissharedamongarisingnumberofemployees(European

Commission,2017).

TheleadingroleofViennaintheAustrianeconomyisconfirmedbythehighGDPpercapita

(44,700europerinhabitant,asopposedto36,900inAustria),closertosomeoftherichest

Europeanregionsandequalto155%oftheEUaverage.Howeverthisdistanceisshrinking,as

thesamevaluewasupto165%in2012.TheregionofViennaaccountsformorethan25%of

valuecreationinthecountry.RealGVAattheNUTS2leveliscontinuouslygrowinginthelast

years,atafasterpacethantheAustrianaverage.Approximately86%oftheViennesegross

productiscreatedinthetertiarysector,whileapproximately14%inthesecondarysector.The

Vienneseeconomyhasgonethroughstructuralchangesduringthelastdecades.Thisis

especiallyreflectedinthegrowingamountofpeopleemployedintheservicesector(currently

around85%).Inthesub-sectorsoftheservicesector,likeaccommodationandgastronomy,

financeandinsuranceservices,knowledge-intensecorporateservices,educationandteachingas

wellashealthandsocialservices,anincreaseinemploymentof25%couldbewitnessedinthe

lastdecade.Apartfromthat,thecityfunctionsasahubforbusinesswithEasternEuropean

countriesandisstillamajortouristdestination.Relevantroleintheeconomicstructureofthe

regionisalsoplayedbythegrowingcreationofgreenandbythefurtherdevelopmentofVienna

asacenterforhighereducationandservicesinthefieldsofICT,LifeSciences,andR&D

(Eichmann&Nocker,2015).

TheeconomicperformanceofUpperAustriaappearsalsoremarkable,astheGDPper

inhabitantsisoverthenationalaverage(37,700).UnlikethecaseofVienna,thedistancefrom

theEUaveragehasshrunkenonlyslightly(from134%in2013to131%in2015),followingthe

generaltrendofthecountry.UpperAustriaisoneofthemaincentersofindustrialproductionin


8

thecountry,accountingforaround25%ofAustrianindustrialproduction.Especiallysteel

productionandautomotivesupplyrepresenttwoimportantbranches.Approximately5%ofthe

grossproductiscreatedintheprimarysector,30%inthesecondary,and64%inthetertiary

sector.

Figure2:GDPineuroperinhabitantsinPPS(leftaxe)andlabourproductivityperhourworked

(rightaxe,EU=100),Austria,UpperAustriaandVienna,2006-2015

Source:EurostatEconomyandfinancedatabase

Theeconomicstructureofthecountryismainlymadeupbysmallfirms:enterpriseswithless

than10employeescover87.3%ofthetotal(93%intheregionofViennaand94%inUpper

Austria),enterpriseswith10-19employeesareequalto7.1%,enterpriseswith20-49

employeesto3.7%,whilebigenterpriseswithmorethan50employeesrepresentlessthan2%

ofthebusinesspopulation.AustrianbusinessenterprisesspendmuchmoreinR&DthantheEU

average(inpurchasingpowerstandardperinhabitantatconstant2005prices:676.5against

307.4euroin2014),whilemorethanhalfofthetotalcountry’sexpenditureinR&Dinthe

governmentsectorisconcentratedinthecapital(205millionsinPPSonatotalof390millions

in2013).Allinall,totalexpenditureonresearchanddevelopmentaccountedfor3.06%of

AustrianGDPin2014,whichisaveryhighvalueincomparativeperspective(EU28averagewas

2.14inthesameyear).Thepercentageofresearchersinallthesectorsoftheeconomyis

comparativelyhigh(1.53%in2013),withthehighlynotablepeakof2.33%intheregionof

Vienna.However,UpperAustriaperformsabovethenationalaverageaswell(1.59%of

researchers).Theshareofpeopleemployedinthepublicsectorisroughlystableafter2008and


9

equalto6.8%oftotalemploymentin2014,withastrongconcentrationinVienna(7.5%in

Vienna,only5.4%inUpperAustria),whileemploymentineducationiscontinuouslygrowing

andwasequalto6.9%in2014with,again,apeakintheregionofVienna(8.7%).Beingthe

capitalofAustriaandastronglyattractivehighereducationcenter,thesehighvaluesfor

employmentinpublicandeducationsectorsareeasilyexplainable.Finally,peopleemployedin

thehealthsectorandinsocialworkmakeupalmost10%oftotalemployment(8.9%Upper

Austria,10.8%inVienna).

1.3 Education

Educationplaysakeyroleinprovidingindividualswiththeknowledge,skillsandcompetences

neededtoparticipateeffectivelyinsocietyandintheeconomy.LikewiseGermany,theAustrian

educationsystemischaracterizedbytheearlytrackingofpupils.Thefirstdivisionintotracks

takesplacewhentheyare10yearsold,atthebeginningoflowersecondaryeducation.Atthe

beginningofuppersecondaryeducation,thesystemismadeupof4tracks.

Roughly80%ofyoungcohortsafterlowersecondaryeducationentersavocationaleducation

andtraining(VET)course,37%indualapprenticeshipand43%inavocationalschool(BMS)or

college(BHS)(Bliemetal.,2016).Theexpenditureperstudentinvocationalprogrammesis

muchhigherthanforgeneralprogrammes(16,554against13,260USdollars).TheVETsystem

ischaracterizedbythecompetitionbetweenapprenticeshipandschool-basedvocational

courses(Lassnig,2011).However,itishighlydiversewithmanydifferentprogrammesand

institutionsofferingaccesstodifferentsocialgroups,andwithrangeofoptionsforstudentsto

accesshighereducation.SocialpartnersarealsoincludedinthemanagementoftheVETsystem,

throughtheEconomicChamberandtheChamberofLabour.

Thehighereducationsystem(HE)combinespost-secondaryandshort-cyclevocationalcourses

withbachelorandmastercoursesofferedbyuniversitiesanduniversitiesofappliedsciences.In

particular,Viennahosts9publicuniversities,4privateuniversitiesandateachertraining

college,6universitiesofappliedsciences.UpperAustriahasoneuniversity(Linz)andtwo

universitiesofappliedsciences.

In2013thepublicexpenditureontheeducationsysteminAustriawasequivalentto5.6%ofthe

nationalGDP.ExpenditureinHE(mainlyuniversityofappliedscienceanduniversity)makesup

toalmost24%oftotalexpenditureineducation,whiletheresourcesdirectedtoVETareequal

to14%ofthetotalamount.Asfortheexpenditurewhichisbrokendownbyfederalstates,the

largestshareisspentinVienna(20%),whileUpperAustriaranksthird,with12%.

Internationalvariationinthestructureofeducationsystemsbringsthenecessitytocomparenot

onlyparticipationandgraduationrates(inthefollowingparagraphs),butalsothequalityof

contentsandskillsachievedbystudentsandpupilsduringtheireducationalcareers.Education


10

resultsinAustriaarestillinthemiddleoftherangecomparedtoothercountries,but

weaknessesinsomebasicskills(likereading)wereconfirmedbytheirdeteriorationinthelast

2015OECDProgrammeforInternationalStudentAssessment(PISA)test,collectedon15years

oldpupilsatthebeginningofuppersecondaryeducation.In2015Austrianpupilsgainedamean

scoreof497pointsinnumeracyand484inliteracy(EUaveragewererespectively491and

492).Onaveragegirlsoutperformedboysby2points.However,thecoefficientsofvariation

were0.19and0.21,inlinewiththeEuropeanaverageandstablebetween2003and2015,

pointingoutpersistingdifferencesaccordingtogenderandsocialbackgroundineducational

achievement.Parents’socioeconomicstatusandtheireventualmigrantbackgroundcontinueto

haveamajorinfluenceontheirchildren’seducationresults.In2015,firstgenerationimmigrant

studentsare3timesmorelikelythannativebornstudentstoleaveschoolearlybefore

completinguppersecondaryeducation(EuropeanCommission,2017).

Lookingatskillsofyoungpeopleaged20-30(PIAACdata),theadvantageofyoungAustrian

adultswithrespecttotheirEuropeanpeersincreases:in2012themeanscoreofAustriansin

numeracywas286againsttheEUaverageof262;inliteracythemeanscorewas284againstthe

EUaverageof272.However,inboththedomainsthevariationamongrespondentwaslower

thanEUaverage(respectively0.16and0.15against0.20and0.18),pointingoutthecoexistence

ofagoodlevelofskillattainmenttogetherwitharelativelyevenskilldistributionamongyoung

people.

Participationinchildcareandearlyeducationisrelevantindevelopingcognitiveabilitiesand

bufferingtheinfluenceofthefamiliarbackground.Thishasimpactonopportunitiesin

educationandonthelabourmarketlaterinlife.InAustria,theparticipationofchildrenin

childcareandpre-schooleducationisincreasing:in2012,90.9%of4-years-oldswerein

education(82.5%in2005),buttheratewasstillslightlylowerthantheEuropeanaverage

(91.9%in2012forEU27).Withrespecttothenationalaverage,intheregionofViennatherate

islower(86.5%in2015),whileparticipationismuchhigherinUpperAustria(89.5%),butboth

theregionsshowaslightlydecreasingtrendinthelast2-3years.

Lookingatthefollowingstagesoftheeducationsystem,participationinupper-secondaryand

post-secondarynon-tertiaryeducation(ISCED3-4)iscomparativelyquitehighespeciallyin

UpperAustria,asitisconnectedtotheregionalstructureofthelabourmarketandtothejob

demandexpressedbyastrongindustrialproduction.In2012theparticipationrateof

individuals15-24wasequalto42.9%,4pointsabovetheEU27average.InVienna,the

percentageofstudentsinupper-secondaryeducationandpost-secondarynon-tertiary

educationonthepopulationdroppedfrom44.7%in2005to39.8%in2012.InUpperAustria

thesameindicatorremainedquitestable(45.9%in2012).Moreover,youngpeopleinUpper

Austriatendtoenrollmoreinvocationalprogrammes(76.2%ofallthepupilsinupper

secondaryeducation),whileinViennaonly58.4%ofpupilsenrollinvocationalprogrammes.


11

Asfortertiaryeducation,participationinAustriaisstronglyincreasinginthelasttenyears.At

thenationallevel,therateofstudentsintertiaryeducationaspercentageofthepopulationof

20-24yearsold,jumpedfrom46.6%in2005to70.8%in2012(theEU27averageis64.2%).In

theViennaregionthesamerateincreasedto151.4%in2012,duetothefactthattheUniversity

ofViennaattractsmanyAustrianandinternationalstudents.InUpperAustria,theparticipation

ismuchlowerbutitisalsoincreasing:in2012,studentsintertiaryeducationcovered40.4%of

thepopulationaged20-24years,18.5percentagepointsmorethanin2005.

Finally,bylookingatlifelonglearningeducationatalaterage,afterhavingusuallycompleted

initialeducation,youngAustriansstillshowrelevantcommitmentintraining:allinall,24.6%of

youngpeopleaged25-34statedthattheyparticipatedinsomeformsofeducationandtraining

activitiesin2016(theEU28averageis17.4%),25.7%forwomenand23.6%formen.

Goodeducationandskillsareimportantrequisitesforfindingajob.InAustria,84.5%ofadults

aged25-64hadcompletedatleastuppersecondaryeducation(ISCED3-8)in2015,wellabove

theEU27averageof76.5%.Thisistrueespeciallyformales,as88%ofmenhavesuccessfully

completedhigh-schoolcomparedwith80%ofwomen.Lookingateducationattainmentof

youngpeople,i.e.atthelevelandtypeofthequalificationsobtained,themaintrendinAustriais

theupgradingofthequalificationofyouthpotentialworkforce:thedata(Figure3)showadrop

intheshareoflow-educated(from16.5%in2005to13.2%in2016)andupper-secondary

educated(from63.1to44.8%),andasteadyincreaseoftertiaryeducated(from20.4%to42%).

Thedropinparticipationinuppersecondaryeducationandthejumpinparticipationintertiary

educationafter2013ismainlyrelatedtoachangeintheclassificationofAustrianqualifications,

accordingtotheISCED2011standards:indetail,qualificationsattainedafter4and5yearsin

BHSorvocationalcolleges,havebeenclassifiedasshort-cycletertiaryeducation2,thus

accountingforthestrongshiftsinparticipationrates.

2 For information on the application of ISCED 2011 standards at the Austrian education system, see:

http://www.bildungssystem.at/en/footer-boxen/isced/international-standard-classification-of-education/


12

Figure3:Educationalattainment(30-34,%)andparticipationineducationandtraining(25-34,

%),Austria,2005-2015

Source:EurostatEducationandtrainingdatabase,LFSmicrodata

Thedatashowrelevantdifferencesattheregionallevelandsomesignsofarecentdeclinein

educationalattainments.Overall,thepercentageoflow-educatedyoungadultsof30-34years

old(ISCED0-2)isdecreasinginthelasttenyears,butthiscomestogetherwithanincreaseafter

2014(from11.6%to13.2%in2016,theEU28averageis15.3%),reachingaworseningpeakof

17.3%in2016inVienna,6.4percentagepointshigherthaninUpperAustria.Coherently,the

rateofearlyschoolleavers(thepercentageofthepopulationaged18to24havingattainedat

mostlowersecondaryeducationandnotbeinginvolvedinfurthereducationortraining)slightly

increased7.8%in2015(Figure4).Thetrendtowardsashrinkingshareofloweducatedis

commonbothformalesandfemales,butseemstointerruptafter2014.Moreover,a

characteristicoftheAustriancontextthatdidnotemergedbydataonparticipation,isthe

educationaldisadvantageofwomen,whichisshrinkingbutstillexisting:in2005theshareof

low-educatedwomenwas16.5%against11.2%ofmen,whiletheEUaveragewasrespectively

21.6%against23.9%;in2016theshareoflow-educatedwomenwas13.2%against10.8%of

men,whiletheEUaveragewasrespectively15.3%against19%.


13

Secondaryeducationattainment(ISCED3-4)forthoseaged30-34ishigherinAustriathanEU27

average(50.2%and44%respectively),andhigherformen,52.7%,thanforwomen,47.6%.

However,lookingatuppersecondaryvocationaleducationattainmentthedifferenceisstriking:

47.2%against39.5%3.Hereitisworthtonoticethatvocationalprogrammesatuppersecondary

levelaremoreeffectiveinbridgingthetransitionstothelabourmarketthangeneral

programmes.ThisisstronglyconfirmedbythedataregardingAustria,asthedifferencein

unemploymentratesbetweenVETandgeneralsecondaryeducatediswiderthantheaverages

ofotherEUcountries(OECD,2016a).Tertiaryeducationattainment(ISCED5-8)provide

considerableearningadvantagesforbothgenderslaterinthelabourmarket,butmengraduates

especiallyinthefieldofengineering,manufacturingandconstructionformen,whilewomen

mainlyinteachertrainingandeducationsciences.

Allinall,thepercentageofhighereducatedaged30-34was38.7%in2015,veryclosetothe

EU27average(38.8%).FollowingtheEuropeantrend,womenaremoretertiaryeducatedthan

men(40%against37.5%),butthedivideiscloserthantheEUaverage(43.4%against34%).A

relevantshareofgraduatesinhighereducationattainashort-cycletertiarydegreeasa

maximumqualification,whiletheshareofBachelorgraduatesiscomparativelylow.Thisisdue

tothediffusionofvocationalcolleges,ontheonehand,andtothefactthatBachelor

programmeswereintroducedonlyrecentlyintheAustrianeducationsystem,ontheother

(OECD,2016a).

Dataoneducationalattainmentcoverrelevantregionalvariations.Aswesaw,inUpperAustria

youngpeopleheavilyparticipateespeciallyinuppersecondaryeducation(ISCED3-4),whilethe

rateofhighereducationstudentsisquitelow.WithrespecttoVienna,inUpperAustria

vocationaleducationandthedualapprenticeshipsystemplayamoreprominentrolein

structuringthetransitionfromschooltowork.Coherently,havinganupper-secondarynon-

tertiarydegreeasmaximumqualificationisthemostcommonsituationamongyoungpeople

aged30-34inUpperAustria(57.6%in2015),especiallyamongmen(59.9%against57,6%of

women).Secondaryeducationisquitecomprehensiveamongyoungadults,asonly7.8%ofthe

population30-34in2014wasmadeupbylow-educatedyouth.Ontheotherhand,only33.1%of

thoseaged30-34hadaHEdegreein2015,andwomentendtobemoreeducatedthanmen

(34.6%against30.4%).

IntheViennaregion,duetotertiarizationanddevelopmentintheservicesectorsofthe

economy,upper-secondarynon-tertiarydegreeasmaximumqualificationgoesdownto37.2%,

beingmorecommonforwomen(37.9%).HighereducationiswaymorewidespreadinVienna,

withnogenderdifference(48.8%formalesandfemales).Thisiscoherentwiththedataon

participation,confirmingthestrengthofHEintheViennaregion.

3 Onthecontrary,lookingatgeneraluppersecondaryeducationasmaximumattainment,Austrianwomenhavearate8.1%against5.5%ofmen.


14

ThelinkbetweeneducationandthelabourmarketstillappearstobestrongerinAustriaif

comparedtoEurope,evenifslightlydeterioratingafter2012(Figure4):onlyalimitedshareof

youngpeopleisexcludedbothfromworkingandtrainingactivities,goingtogetherwiththe

aforementionedonaverageorabove-averageattainmentrates.TheAustrianNEETrate,

measuringthepercentageofyoungpeopleaged15-24outofeducationandnotemployed,was

7.5%in2015,increasingafter2012.IntheEU28theratewas12%butitisconstantly

decreasing,sothatthegapwithAustriaisreducinginthelast3years.However,therateof

youngpeopleoutofeducationandworkishigherintheViennaregion(11.1%in2015),while

extremelylowinUpperAustria(5.9%in2015).

Figure4:NEETrate(15-24,%)andearlyschoolleavingrate(18-24,%),Austria,UpperAustria

andVienna,2005-2015

Source:EurostatEducationandtrainingdatabase,LFSmicrodata

1.4 Labourmarket

Austriaremainsanattractivedestinationforforeignworkersandisexperiencingacontinuous

inflowfromEUandnon-EUcountriesalike.This,togetherwiththelongerworkinglivesofelder

workers(duetorestrictionsonearlyretirement)andincreasingfemalelabourmarket

participation,ishelpingtoincreasethelaboursupplyandpotentialgrowth.Employmenthas

beenincreasing,buttheeconomycannotfullyabsorbthegrowthinthelabourforce.Thishasled

torecentincreasesinunemployment,especiallyforthelowskilled,evenifitremainslowin


15

comparativeperspective.Thegaininemploymentsincethecrisishasmainlybeendrivenby

part-timejobsratherthanfull-timework.Workisthusdistributedamongmoreemployees.As

wesaw,thisislimitingunemploymenttosomeextentbutalsoresultinginstagnatinglabour

productivityperemployee(EuropeanCommission,2017).TheAustrianlabourmarketdisplays,

accordingtoOECDdata,anintermediatedegreeofemploymentprotection.Therelativeindexes

measuringthestrictnessofregulationonindividualandcollectivedismissalsforregular

contractsremainedstableinthelastyears,beingupto2,37,lessthancountrieslikeGermany,

ItalyorPortugal,butmorethanFinland,SpainandUnitedKingdom.

In2015Austriainvestedinlabourmarketpoliciesanamountofresourceswhichwasequalto

2.26%ofitsGDP.Expenditureincreasedduetothefirstimpactofthecrisisin2008-2009,then

decreasedandstartedrisingagaininthelast3years.ThemainfocusofAustrianLMPsis

training(measuresthataimtoimprovetheemployabilityofLMPtarget,covering0.46%of

GDP),whicharerelativelyhighcomparedtotheEUaverage.Expenditureonlabourmarket

servicesslightlyincreasedaswellinthelasttenyear(0.18%in2015,stilllowerthanthelastEU

averageavailable:0.21%in2011).Othermeasureslabelledasactive,namelyemployment

incentives,supportedemployment,directjobcreationaswellasstart-upincentives,arenotthe

focusofAustrianlabourmarketpolicies.

Lookingatcompensatoryinterventions,theexpenditureforunemploymentbenefitsandout-of-

workincomemaintenanceandsupportdeclineduntil2008,beingbelowEUaverage,but

increasedafterwardsto1.38%ofGDPin2015,afterafirstpeakin2009duetotheeconomic

crisis.ExpenditureforearlyretirementaresignificantlyhigherthantheEUaverage,although

theydecreasedfrom0.24%(2006)to0.15%in2011(theEUaverageexpenditurewas0.05%in

thesameyear),andto0.12%in2015.

Regardingparticipationinthelabourmarket,duringthetimespan2005-2015theoverall

economicactivityratefor15-65yearsoldwasslightlybutconstantlyabovetheEU-28average,

increasingfrom72.4%to75.5%.Thismeansthatin20153individualsoutof4wereworkingor

activelysearchingforajob.In2015,57.4%oftheAustrianyouth(aged15to24)wereanactive

partofthelabourmarket,60.7%formalesand54.1%forfemales.Thisratedidnotchange

substantiallyinthelasttenyears,anditishighabovetheEU27-averageof41.7,whichshowed

insteadadecreaseof2.7percentagepointsafter2008.AttheNUTS2level,theAustrianlabour

marketischaracterizedbyacleardisparitybetweenViennaandUpperAustria.InUpperAustria

theactivityrateofthoseaged15-24isveryhigh(62.9%in2015),asyoungpeopletendtospend

lesstimeineducation(mainlyvocational),thusenteringearlierthelabourmarket.Intheregion

ofViennatheactivityrateislowerthanthecountryaverage(51.2%in2015),duetothe

increasingrelevanceanddiffusionofhighereducation.

TheoccupationalstructureoftheAustrianlabourmarketappearstobemorequalifiedthanthe

EUaverage,inlinewithdataoninnovation,productivityandR&D.Almost30%oftheworking


16

populationin2015wasemployedinhighskilledwhitecollaroccupations(ISCO1,2,3),while

22%waspartofthehighskilledbluecollargroup(ISCO6,7).TheEU28averagesforthesame

occupationswere,respectively,27%and19%.Ontheothersideofskillsdistribution,33%ofthe

Austrianworkingpopulationwasworkinginlowskilledwhitecollaroccupations(ISCO4&5)

andtheremaining16%wasemployedinelementaryoccupations,makingupthelowskilled

bluecollargroup(ISCO8,9).TheEU28averagesforthesameoccupationswere,respectively,

33%and21%.WhatisespeciallyvisibleintheregionofVienna,isthesignificantriseofjobs

withahighqualificationprofile.Therehasbeenatrendtowardsahigherrequestforhigh-

qualifiedactivities,whiletheshareofjobsfocusingonmanualactivitiesisshrinking.Moreover,

Vienna’sjobmarketbenefitsfromthefactthatthecity,asthecapitalofAustria,offersarelative

highamountofservicejobsinthepublicoreducationalsector.Ontheotherhand,opportunities

foryoungpeopleinthedualapprenticeshipsystemformedium-lowqualifiedjobsarequite

limited.ThemainchallengefortheVienneselabourmarketinthefuturewillbetoprovide

sufficientjobsforitsgrowingpopulation.AlsothejobdemandinUpperAustriashowsan

upgradingtrend,evenifitismorefocusedonindustrialproductionthatcanrelyonadeveloped

apprenticeshipsystem.Despitedifferencesinthestructureofeconomyandeducation,itis

forecastedagrowinggapbetweendemandandsupplyofhighskilledlabourinthenextyearsfor

bothregions(Eichmann&Nocker,2015).

OverthelastdecadetheoverallAustrianemploymentrateofthepopulationaged20-64

increased(from71.6%in2005to74.3%in2015).Moreindetail,thispositivetrendwasstrong

beforethecrisis,itstoppedin2008-2009andthenstabilizedafterwards.Asacontrast,theEU-

28employmentratedecreasedbetween2009and2013,whenitstartedrisingagain.However,

intheregionofViennathedatashowadecreaseafter2013,astheemploymentratefellfrom

69.3%to67.7%.InUpper-Austria77.7%ofthepopulationwereemployedin2015,whichis

3.4%abovetheAustrianaverage.Generallyspeaking,onehastonotethatthemaleemployment

ratefollowsaverysimilarpatterntotheAustrianaverage,whilethefemaleemploymentrate

graduallybutcontinuouslyincreased(from64%in2005to70.2%in2015)anddidnotstagnate

ordeclineduringthistimeperiod.Nevertheless,therewasstillagapof8.4%in2015(70.2%

against78.4%formales).Thisismainlyexplainedwiththeincreaseoffemaleemploymentin

non-standardjobs:iftheratioofmalepart-timeworkhasnearlydoubledfrom6.6%(2006)to

11.8%(2016),thefemaleratioofpart-timeworkjumpedupto47.7%in2016.Therefore,we

canconcludethattheAustrianlabourmarketisstillaffectedbyrelevantgendergapsinearnings

aswellasintypeofemployment,aswomenatalllevelsofeducationalattainmentearnlessthan

manandaremoreemployedinnon-standardemployment(fixedtermandparttime)(OECD,

2015).

Theoverallunemploymentrate(aged20to64)stronglydecreasedintheearly2000s,touching

3.8%in2008,wellbelowtheEU-27averageof6.7%.Duetothefirstimpactoftheeconomic


17

crisesitroseby1.2%in2009,thendecreasedtill2011(4.3%).Sincethenithasbeenconstantly

movingup(5.6%in2015).InVienna,wheretheunemploymentistraditionallyhigher,itroseto

10.4%in2015(involvingmoremen,12%,thanwomen,8.6%),abovetheEUaverageof9.2%.

Ontheotherhand,inUpperAustriaunemploymentislowerandroughlystable(3.9%in2015).

InAustria,thepercentageoftheunemployedthathavebeensearchingforajobforayearor

longeriscurrently29.2%.ItishigherandstronglyincreasinginVienna(from29.3%in2009to

36.2%in2015,butstillsignificantlylowerthantheEUaverageof48.1%),andlowerand

decreasinginUpperAustria(20.3%in2015).Amongyoungpeopleaged15-29long-term

unemploymentisquiterare:1.6%inAustriaand3.5%intheregionofVienna(4.8%among

men),comparedto5.8%intheEU27.Long-termunemploymentisparticularlyrelevantasitcan

haveanegativeeffectonfeelingsofwell-beingandresultinalossofskills,furtherreducing

employability.

Lookingattheyouthpopulation(Figure5),theemploymentrate15-24decreasedinthelast

fiveyearsbutit‘sstillmuchhigherthantheEUaverage(51.3%against33.1%in2015),

especiallyinUpperAustria(57.3%),whileinViennaisequalto42%.Moreover,ifatthenational

levelandinUpperAustriayoungmenaremoreemployedthanyoungwomen(54%against

48.7%inAustria,61.6%against52.8%inUpperAustria),inViennayoungwomenareslightly

advantaged(42.5%against41.4%in2015).Accordingly,theunemploymentrateforthoseaged

15-24ismuchlowerthantheEUaverage(10.6%against20.4%in2015),beingslightlyhigher

formales(11.1%)thanfemales(10%).However,after2011itiscontinuouslyincreasing,

comingclosertothelevelsof2009.Onceagain,thesituationisworstinVienna,whereitpeaked

upto19.4%in2012andisequalto18%in2015:youngmalesinViennaappeartobe

particularlyatrisk,astheirunemploymentrateis21.9%,abovetheEU27averageof21%after

2012.Conversely,afterapeakof18%in2012,theshareofyoungwomenunemployedhasfallen

downinthelast3years.

Ontheotherhand,UpperAustriaconfirmstobeamorefavorablecontextalsointermsofyouth

unemploymentwithrespecttotheoverallAustriansituation,astheshareof15-24yearsold

activelysearchingforajobwasequalto9%in2015,9.5%formenand8.5%forwomen.The

youthunemploymentratio,measuringtheshareofunemployedyoungpeopleamongthewhole

youthpopulation,alsosupportsourviewrelatedtothecomparativelygoodconditionsofthe

youngpopulationintheAustrianlabourmarket.TheAustrianshareofyouthunemployedonthe

overallunemployedpopulationislowerthantheEU27average:6.1%for15-24and7.4%for20-

29in2015against8.4%for15-24and11.8%for20-29.Nevertheless,whiletheaverage

Europeantrendisimprovingafter2012-2013(itwasequalto9.9%in2013),theAustrianratio

wasequalto5.3%in2011.ThisconfirmshowinAustriatheyouthlabourmarketconditions,

evenifstillcomparativelybetterthanmanyEuropeancountries,havebeenslightlydeteriorating

inthelast3-5years.


18

Figure5:youthemploymentandunemploymentrates(leftaxe,15-24,%),youthunemployment

ratioofyoungpeople15-24(rightaxe),EU27,Austria,UpperAustriaandVienna,2005-2015

Source:EurostatLabourmarketdatabase,LFSmicrodata

1.5 Redistributionandsocialinclusion

TheAustrianoverallnetexpenditureinsocialprotectionrosefrom24.5%to26.9%ofGDPin

thetimespan2007-2014,thestrongestincreasetookplacebetween2008and2009(from25%

to27%),asanimmediateresponsetotheimpactoftheeconomiccrisis.Expenditureonsocial

protectionisprovidedtohouseholdsandindividualsaffectedbyaspecificsetofsocialrisksand

needs.InthecaseofAustria,resourcesspentforsocialprotectionbenefitsinordertoprotect

peopleinneedareequalto11,312europerinhabitant:thisvalueiswellaboveEUaverageof

7,655europerinhabitant,showingtheextensiveamountofresourcesdeployedbytheAustrian

welfarestate.Themainshareisspentforpensionsandretirement(oldagerisk),whichisalso

theindicatorshowingthemostcontinuousandstrongestgrowthbetween2005and2014,from

9.07%to10.66%ofnationalGDP.Relevantincreaseswerealsoregisteredinthefieldofhealth

care(from6.58%to7.13%),socialprotectionbenefitstocounteractunemployment(from

1.32%to1.59%)andsocialexclusion(from0.36%to0.46%).Expenditurefordisability

increasedonlyslightly(from1.83%to1.86%),whiletherewasaslightdeclineintheamountof

resourcesdestinedforhousing(from0.13%to0.12%),familyandchildren(from2.80%to

2.77%),survivors(from1.63%to1.54%).


19

Thedisposableincomeforhouseholdsistheamountofmoneythatahouseholdearnseachyear

aftertaxesandtransfers,representingthemoneyavailabletoahouseholdforspendingon

goodsorservices.InAustriaitishigherthantheEUaverage,showinganincreasingtrendfrom

2005to2013,from18,000to20,700inPPS(itwas16,800forUKand20,300forGermanyin

2013),withastagnationin2008-2010becauseoftheimpactoftheeconomiccrisis.Itwas

slightlylowerinVienna(20,300),whileitwasequaltothecountryaverageforUpperAustria.

Lookingatincomedistribution,Austriatakesalower-than-averagepositioninEuropeinterms

ofincomeinequality,evenifitfollowsthegeneralEuropeantrendofincreasinginequalities.In

thetimespan2005-2015theGinicoefficientofequivaliseddisposableincome(Figure6),

showingtheconcentrationofincome,wentfrom45%to47.6%againstEU27valuesof,

respectively,49.7%and51.9%.Socialredistributionandsocialbenefits,andonlyslightlythe

taxessystem,areeffectiveinreducingmarketincomeinequality:theGinicoefficientaftersocial

transfersdropsdownto27.2%in2015,accountingfora43%reductionofincomeinequalities

(EUaverageis40.3%).However,ifinequalityofincomeislow,inequalityofwealthisby

contrasthigh(ECB,2016).In2012,therichest10%ofAustrianhouseholdsowned62%of

overallhouseholdwealth.Astheshareofrentersiscomparativelyhigh,wealthintheformof

homes,themajorassettypeforprivatehouseholds,ismoreconcentrated(OECD,2016b).

Figure6:GINIindexbeforeandaftertransfers(leftaxe,0:100),netdisposableincomeinhousehold

inPPS(Europerinhabitant,rightaxe),EU27,Austria,UpperAustriaandVienna,2005-2015

Source:EurostatLivingconditionsandwelfaredatabase,EU-SILCmicrodata


20

Socialwelfarestandardsarestillhighoverall,astheproportionofthepopulationatriskof

povertyorsocialexclusionisoneofthelowestamongEUMemberStates,butsomegroupsmust

facegreaterrisk,inparticularolderwomenandchildrenofforeign-bornparents.Theriskof

povertyandsocialexclusionwasequalto17.4%in2005andjumpedto20.6%in2008,showing

afterwardsaslowdecreasetoarateof18.9%in2015,lowerthantheEU27averageof23.7%.

Manyotherindicatorsrepresentingthelivingandmaterialconditionofthepopulation,focusing

onrisksrelatedtopovertyandsocialexclusion,havebeenclearlyaffectedbythecrisis,showing

asimilarpattern:aslowimprovementbefore2007,anegativepeakin2008-2009andthena

dropandstabilizationafterwards,evenifonahigherlevelwithrespecttothepre-crisis.Values

tendtoremain,however,comparativelylowinEUperspective.Thisistruefortheriskof

poverty(from12.6%in2005to15.2%in2008,thendownto13.9%in2015,againstaEU27

averageof17.3%);fortheriskofpovertyorsocialexclusion(from17.4%in2005to20.6%in

2008,decliningto18.3%in2015,itwas20%forGermanyand23.5%forUK);forthesevere

materialdeprivationrate(from3.5%in2005to5.9%in2008,thendownto4.6%in2015,

againstaEU27averageof8%);aswellasfortheriskofpovertysufferedbyemployedpeople

(from6.7%in2005to8.6%in2008,thendownto7.9%in2015,againstaEU27averageof

9.5%).Adifferenttrendisinsteadrelatedtothepercentageofpeoplelivinginhouseholdswitha

verylowworkintensity:thisindicatorfluctuatedbetween7.3%in2005andamaximumof9.1

%in2014(consideringthetotalpopulationagedlessthan60),goingdownto8.1%the

followingyear,wellbelowtheEUaverageof10.6%.Allinall,thedatapointoutthatmaterial

conditionsoflivinginAustriaaregenerallybetterthaninmanyotherEUcountries,but

deterioratedaftertheeconomiccrisis,bothattheindividualandatthehouseholds’level,and

startedtorecoverwithfluctuationsafter2008-2009.

ConcerningthepublicsphereandcivicparticipationinAustria,resultsfromrecentsurveys

showapersistingsenseofcommunity:93%ofpeoplebelievethattheyknowsomeonethey

couldrelyonintimeofneed,higherthantheOECDaverageof88%(OECD,2016a).However,

dataonvoterturnoutinnationalelections,ameasureofcitizens'participationinthepolitical

process,expressacleartrendofdecline,commontomanyotherEUcountries.Thepercentage

wasequalto78.5%in2006,butparticipationdecreasedto74.9%in2013,evenifitisstill

higherthantheEuropeanaverage.AsimilardeclineisalsoshownbyturnoutdatainEU

parliamentaryelection.Alsotrustinpublicinstitutions,essentialforpublicsupport,isquitelow

inAustria:only43%ofthepopulationreporthavingconfidenceinthenationalgovernment,in

linewiththeOECDaverage.However,trustinthenationalgovernmentishigheramongyoung

peopleunder30(50%,seeOECD,2016b).


21

1.6 Healthandwell-being

MostEUcountrieshaveenjoyedlargegainsinlifeexpectancyoverthepastdecades,thanksto

improvementsinlivingconditions,publichealthinterventionsandprogressinmedicalcare.

Austria’shealthcaresystemischaracterizedbyalargeandcostlyhospitalsectorand

underutilizedoutpatientcare(EuropeanCommission,2017).Ingeneraltheaccessibilityand

qualityofhealthcareprovidedaregoodincomparativeperspective.Beinganageingsociety,

however,accesschallengesashealthcarecostsareexpectedtoincreasemarkedlyinfuture.

From2011to2014totalhealthexpenditureinAustriaincreasedbymorethan10%,touching

33,794millioneuroin2014,equalto2,587europerinhabitant(EUaverageis2,235europer

inhabitant).Theavailablebedsinhospitalsin2014were768.71perhundredthousand

inhabitants,withtheregionofViennabeingslightlyabovetheaverage(800bedsperhundred

thousandinhabitants)andUpperAustriabeingslightlybelow(700beds).Itisstrikingthe

increaseinlong-termcarebeds,thatrosefrom35.8perhundredthousandinhabitantsto55.9in

thetimespan2005-2015,mostlyresultingfromtheregionofVienna(from67to163.35in

2014).Accordingly,lookingatthehealthpersonneldata,thevaluesofmedicaldoctorsand

nursesandmidwivesperhundredthousandinhabitantsarehigherandincreasinginVienna

(respectively689and975),withrespecttoboththenationalaverage(504and816)andto

UpperAustria(407and825).

In2015,70%ofpeopleinAustriareportedtobeingoodhealth,slightlyaboveEUaverageof

67%.Theratiobetweenpeoplewhohaveagoodandverygoodperceptionoftheirhealthand

thosewhohaveabadperceptionisalsoquitefavorableandhighincomparativeperspective,

being9.9ascomparedtotheEUaverageof8.7.Notsurprisingly,youngpeopleinAustriaaged

15-29tendtohaveabetterself-perceptionoftheirhealththantheoverallpopulation,as92.5%

ofthemperceivetheirownhealthasgoodorverygood,againabovetheEUaverageof90.8%.

Youngfemalereportedtobeingoodorverygoodhealthmoreoftenthanyoungmen

(respectively93.6%and91.4%ofrespondents).Theratiobetweenthosewhohaveagoodand

badperceptionoftheirownhealthisaccordinglyhigh,beingequalto77.1(EUaverageis69.8).

Despitethesubjectivenatureoftheindicator,answershavebeenfoundtobeagoodpredictorof

people'sfuturehealthcareuse(OECD,2016a).Moreover,lookingattheEurostatindicatorof

healthylifeyears(HLY),thatmeasuresthenumberofremainingyearsthatapersonofspecific

ageisexpectedtolivewithouthealthproblems,wecangainmoreinsightsonAustrians’health

status.InAustria,amaleisexpectedtolive57.6yearswithouthealthproblems(72.9%oftotal

lifeexpectancy)andafemale57.8(68.8%oftotallifeexpectancy).Itisimportanttostressthat

thebothvaluesarebelowEUaverage(respectively61.4and61.8years).Healthconditions

appearnottobedistributedevenly:thegapinreportedgoodhealthbetweenthetopandbottom

20%oftheincomedistributionisespeciallylargeinAustria.


22

Subjectivewell-beingcanbemeasuredintermsoflifesatisfaction,lookingatthepresenceof

positiveornegativeexperiencesandfeelings.Suchmeasures,whilesubjective,areauseful

complementtoobjectivedatatocomparethequalityoflifeacrosscountries.Ingeneral,

Austriansarecomparativelyquitesatisfiedwiththeirlives.Whenaskedtoratetheirgeneral

satisfactionwithlifeonascalefrom0to10,Austriansgaveita7.8grade,higherthantheEU28

averageof7.1,andthepercentageofhighlysatisfiedwiththeirlifewas37.9%,stronglyabove

theEUaverageof21.7%.InVienna,lifesatisfactionwasratedat7.7in2016,butlabour

satisfactionwassignificantlybelowthenationalaverage(7.1against7.7),somehowreflecting

theproblematiclabour-relatedissuesthatwereportedinsection1.4.YoungAustriansaged16-

24and25-34expresshighlevelofsatisfactioninmanylifedomains(Figure7).Thedifference

withothercountriesisparticularlywideregardingthelivingenvironment(60%and52%of

highsatisfactionforthoseaged16-24and25-34,withrespectto30and27%inEU28),andthe

presenceofrecreationalandgreenareas(59%and51%ofhighsatisfactionwithrespectto28%

and25%inEU28).Theseresultsarerelatedtoeducationattainment:satisfactionismuchlower

forlow-educated,roughlyequaltothenational-averageforuppersecondaryeducated,much

higherfortertiaryeducated.

Figure7:Highsatisfactioninvariouslifedomains(25-34,%),EU28andAustria,2013


Goingbeyondsubjectiveperception,welookatsomeotherindicatorsrelatedtothepersonal

well-being,rangingfromsecuritytoalcoholconsumptionandsmoking,inordertogainamore


23

nuancedpictureofwell-beinginAustria.Thenumberofreportedcrimesisshrinkinginthelast

tenyears,eveniftheoverallnumberofcrimesincreasedfrom2015to2016from518thousands

to537thousands,whiletheviolentcrimesslightlydecreasedfrom2,387to2,363.Thehomicide

rate(thenumberofmurdersper100000inhabitants)isaquitereliablemeasureofacountry's

safetylevelbecause,unlikeothercrimes,murdersareusuallyalwaysreportedtothepolice.

Accordingtothelatestdata,Austria'shomiciderateis0.4,muchlowerthantheOECDaverageof

4.1(OECD,2016b).However,Austriahasthehighestpercapitaconsumptionofalcoholinthe

OECD.At12.2litersperperson,consumptionissignificantlyhigherthantheOECDaverageof8.9

litters,andabovecountriessuchasFrance(11.5)andIreland(11).Austriaisalsotheonly

countrywheretheshareofthepopulationwhosmokedailyremainedstableat24%since2000,

whileontheOECDaverageitfellinthelastyears.

2. EmergingissuesAustriaischaracterizedbyastrongfederalism.Thisimpliesthatinmanypolicyareas,federal

statesshowdifferencesthatarenotexpressedbyaggregateddataatnationallevelandgo

beyondthecommonfederalinstitutionalarchitecture.Inthepaperweshowedthatthetwo

functionalregionsofViennaandUpperAustriaarecharacterizedbycommonalitiesand

differences,asfarascontextuallivingconditionsofyoungadultsareconcerned.Usuallythe

indicatorsconsideredshowthatthesituationofyoungAustrianandtheirperceptionsarequite

positiveinEuropeancomparativeperspective.However,thisgoestogetherwithsomesignsof

deteriorationintermsofgrowingyouthunemployment,persistinggenderdifferences,

worseningskillsachievementandstronginfluenceofparentalbackgroundineducation,high

wealthinequalities.Inaddition,thecreationofpredominantlylow-paidandpart-timejobsover

recentyearshasaggravatedthesegmentationofthelabourmarket.

DataconfirmtheleadingroleofViennainthecountry.Thecapitalattractsstrongflowsof

migrationandhasexperiencedastronggrowthintheservicesectors,especiallyinhighskilled

jobs.Thisisconnectedwiththerelevanceoftertiaryeducationinitsregionalskillformation

system.However,Viennacombinessomecontradictions:thegrowingjobmarketgoestogether

withincreasingunemploymentandNEETrates,especiallyforlowskilled,andscarce

apprenticeshipopportunitiesforyoungpeople.UpperAustriaischaracterizedbyastronger

industrialsectorand,accordingly,vocationaleducationandapprenticeshipplayamajorrolein

theeducationsystem.Themoderateincreaseofthepopulationdidnotincreasedsofarthe

pressureontheyouthlabourmarketasithappenedintheregionofVienna.


24

3. ReferencesBliemW.,PetanovitschA.,SchmidK.(2016).DualvocationaleducationandtraininginAustria,

Germany,LiechtensteinandSwitzerland,IBW.

ECB(2016).TheHouseholdFinanceandConsumptionSurvey:resultsfromthesecondwave,

HouseholdFinanceandConsumptionNetwork,StatisticsPaperSeries,No.18,EuropeanCentral

Bank,FrankfurtamMain.

EichmannH.,NockerM.(2015).DieZukunftderBeschäftigunginWien–Trendanalysenauf

Branchenebene.Forschungs-undBeratungsstelleArbeitswelt(FORBA),Wien:

https://www.wien.gv.at/wirtschaft/standort/pdf/beschaeftigung-trendanalysen-

EuropeanCommission(2017).CountryReportAustria2017,Brussels.

LassniggL.(2011).The‘duality’ofVETinAustria:institutionalcompetitionbetweenschooland

apprenticeship.JournalofVocationalEducation&Training,63(3),417-438.

OECD(2017a).Countrystatisticalprofile:Austria2017,Paris.

OECD(2017b).OECDEconomicOutlook2017.Economicforecast,summary:Austria,Paris.

OECD(2016a).EducationataGlance:OECDIndicators.Countrynote:Austria,Paris.

OECD(2016b).SocietyataGlance2016.ASpotlightonYouth.HowdoesAustriacompare?Paris.

OECD(2015).EmploymentOutlook2015.HowdoesAustriacompare?Paris.

StadtWien(2015).StatistischesJahrbuchderStadtWien–2015:

https://www.wien.gv.at/statistik/publikationen/jahrbuch.html


Work Package 4


Bulgaria –

National Briefing Paper with national and regional

data sets

Valentina Milenkova, Stanimir Kabaivanov, Kaloyan Haralampiev,

Georgi Apostolov and Siyka Kovacheva

SOUTH-WEST UNIVERSITY NEOFIT RILSKI (SWU); UNIVERSITY OF PLOVDIV (PU)

Date: 30/09/2017

Work Package 4 – Quantitative Analysis of Young Adults’ Data

Deliverable 4.1


2

TableofContents

ExecutiveSummary........................................................................................................................................................................3

Introduction.......................................................................................................................................................................................4

Qualitydataassessment...............................................................................................................................................................4

DescriptionofthetwoFunctionalRegions..........................................................................................................................5

FunctionalRegionPlovdiv.................................................................................................................................................5

FunctionalRegionofBlagoevgrad..................................................................................................................................6

Demographicstructure.................................................................................................................................................................7

Thestructureoftheeconomy..................................................................................................................................................11

Educationandtrainingsystem................................................................................................................................................15

Labourmarket................................................................................................................................................................................21

Redistributionandsocialinclusion.......................................................................................................................................24

Healthandwell-beingconditions...........................................................................................................................................26

Finalremarks..................................................................................................................................................................................28

References........................................................................................................................................................................................29

Figures

Figure1.Naturalchangeofpopulation(‰).................................................................................................................8Figure2.PercentageofBulgarianpopulationlivinginanalyzedregions....................................................................9Figure3.Proportionofpopulationaged20-24...........................................................................................................10Figure4.Fertilityrate(right)andinfantmortalityrate(left)....................................................................................10Figure5.GDPatcurrentmarketprices,Europerinhabitantin%ofEuropeanaverage.........................................12Figure6.RealGDPpercapitagrowthrate...................................................................................................................13Figure7.Economicsectors,valueadded(%ofGDP)..................................................................................................14Figure8.PopulationattainmentbyISCEDlevels,25-64yearsoverthecorrespondentagegroup........................16Figure9.Youngadults’educationattainmentbyISCEDlevels,30-34yearsoverthecorrespondentagegroup..16Figure10.Youngadults’educationattainmentbyISCEDlevel3-4,30-34yearsoverthecorrespondentagegroup.........................................................................................................................................................................................17

Figure11.Tertiaryeducationaccessofthepopulationaged20-24yearsoverthecorrespondentagegroup......18Figure12.EarlySchoolLeavers18-24years,ESL(leftaxis)andpopulationneitherinEmploymentnorinEducation15-24years,NEET(rightaxis)....................................................................................................................19Figure13.PISAandPIAACcompetences,Europeanaverage=1.................................................................................20Figure14.Participationrateineducationandtraining–24-34agegroup(last4weeks)......................................21Figure15.Youthemploymentrate(age15-24)...........................................................................................................22Figure16.Longtermyouthemploymentrate(age15-29)........................................................................................23Figure17.ExpenditureinsocialprotectioninPPSperinhabitantas%ofEU19.....................................................24Figure18.GINIindexbeforeandaftertaxes(leftaxis)anddisposableincome(rightaxis)....................................25Figure19.Populationatriskofpovertyorsocialexclusion,%(POV)andseverematerialdeprivationpopulation,%(SMD)..........................................................................................................................................................................26Figure20.Highsatisfactioninvariouslifedomains,populationaged25-34,EU28andBulgaria,2013................27


3

ExecutiveSummary

Thequantitativecharacteristicsdescribinglivingconditions,education,structureoftheeconomyand

labormarket inBulgarian conditionsarevery important forunderstanding the transitionsof young

adultsfromeducationtoemploymentandtheopportunitiesforlifelonglearning.

Ontheonehand,inthenationalcontext,therearehighsharesofpeoplewithhighereducation,both

for thewhole population and for the 30-34 age group. It is also indicative that in 2014 two thirds

(66.5%) of the 20-24 age group are students. This percentage is an indication that education is

perceivedasavalue,andthisisalsoaresultoftheactivepolicyofuniversitiestowardsyoungadultsin

the country. The proportion of people aged between 30 and 34 with upper secondary education

(ISCED3-4)ishigherthanintheUK,andiscomparabletoGermany.

On theotherhand,when itcomes toadulteducation, thevaluesarevery low.Theshareof learners

(24-34)ismuchlowerthantheEU27average.Thismeansthataftercompletingcertaindegree,people

stoptheireffortsandambitionstocontinuetheireducation,whichrequiresmoreactiveinvolvement

ofthetrainingorganizationsinformalandnon-formaleducationandlifelonglearning.

It can also be said that there is a difference in education characteristics between the two regions

regarding different age groups. Apart from education, almost all other proportions describing the

BulgarianwayoflifearelowerthantheEUaverage:

- Socialprotectionexpenditurepercapitaincreasedfrom2005to2014,butremainsmuchlower

thanthatofotherEUcountries.

- TheHouseholds’incomein2013ismuchlowerthaninotherEUcountries.

- The share of people at risk of poverty and social exclusion in Bulgaria is decreasing in the

period2006-2015,andfrom2008to2015itisrelativelystablebetween40%and50%.These

values describeBulgaria as the poorest European countrywith low standard andpoor living

conditions.

- Theoverallsatisfactionforthoseaged18-30yearsinBulgaria(-1.161)ismuchlowerthanthe

averageforES28(-0.014)asmen(-1.211)aremoresatisfiedthanwomen(-1.109).

The situation in the country is characterized by a process of slow economic stabilization, income

growth,povertyreduction,increasingyouthemployment,growthindisposablehouseholdincomeand

higheducationalattainment,butthereisstilla lottobedonetoreachtheaveragevaluesdescribing

thequantitativecharacteristicsofthequalityoflifeintheEUcountries.


4

Introduction

This national briefing paper provides a short overview of the living conditions of young adults in

Bulgaria and in the two functional regions selected for theYOUNG_ADULLLTproject, the regionsof

Blagoevgrad(South-West)andPlovdiv(South-Central). Thedatawerecollatedatnationalandlocal

level (NUTs2) according to six dimensions of contextual living conditions: the demographic

characteristicsofthepopulation,thestructureoftheeconomy,theinputsandoutputsoftheeducation

andtrainingsystem,thelabourmarket,themateriallivingconditionsandtheparticipationofcitizens

in the political and civic life and, finally, the health conditions and individualwell-being.Datawere

extractedfromEurostatandfromdifferentsurveyssuchastheEU-LFS,EU-SILC,PISAandPIAAC.The

main corpus of data proceeding from international and harmonized data was successively

complementedbydatacollatedat the local level,madeavailableby theNationalStatistical Institute

and by the official websites of various Bulgarian Institutions (Ministry of Education and Science,

Ministry of labour and Social policy, Chambers of commerce). The data ranges between 2005 and

2015, but for some indicators the datawere not available for 2015 and for this reasonwe refer to

2014asthelatestyearwithdataavailable.

Qualitydataassessment

StatisticalinformationusedinthisstudyistakenfrompubliclyavailabledatabasessuchasEUROSTAT,

ESSPROS, PISA, OECD and National Statistical Institute (NSI) in Bulgaria. Although these sources

provide a large number of time series and a lot of information on methods used to gather the

information,thereareseveralobservationstobemaderegardingcomparabilityandcompatibilityof

thedata.

DuetotheunificationofvariablesandstatisticalproceduresitiscurrentlypossibletouseEUROSTAT

asaprimarysourcewhenassessingandcomparinglivingconditionsacrossthecountries-membersin

the European Union. However, when a comparative analysis has to be made on a lower than the

nationallevel,itisnecessarytokeepinmindthatNUTS2(andtoalesserextentNUTS3)aretheonly

reliableforcomparisonlocallevelsthatcanbeusedwhensearchingfordata.Eventhenitispossible

tocomeupwithproblemssuchasdatagapsortimeseriesofdifferent lengths.Inaddition, it isalso

possible to have some local databases (in our caseNSI) updatedwithmore recent information and

variablevalues,whicharestillmissinginEUROSTAT.Inthispaper,wehavekeptouranalysislimited

tothevariablesthatwerecommonlyagreedandareavailableinEUROSTAT.

Whenever it was necessary to provide information on sub-regions or comparison of regions with

regard to the most recent information, we have used the same variables as those available in

EUROSTAT butwith latest values obtained fromNSI. This has been duly noted in the footnotes or

sourcesoftherespectivefiguresortables.TheNUTS2dataallowsoundstatisticalcomparisonsbutwe


5

should keep in mind that they do not fully coincide with the chosen functional regions for the

fieldworkintheproject,themaindiversionbeingthattheSouth-WestincludesthecapitalSofiawhere

thesituationalongmostoftheusedindicatorsismuchbetterthaninBlagoevgradFunctionalRegion,

whilePlovdivFunctionalRegionhasabettersituationthantherestareasintheSouth-Centralregion.

NSIdatahasalsobeenusedwhennecessarytocheckfordifferencesinsideaspecifiedNUTS2region

(e.g.forNUTS3andLAUdata)asitoffersmorerecentinformation.Withregardtoeconomicdata,local

sourceshavebeenabletoprovideusefuldetailsonthepurchasingpowerinformationthatreflectthe

differences in the standard of living in big cities and the rest of the rest (more rural area) of the

respectiveregions.

DescriptionofthetwoFunctionalRegions

The traditional administrative-territorial division in the country is two-level – it consists of 28

administrativedistrictsand265municipalities.In2000Bulgariawasdividedinto6planningregions–

North-West, North Central, North-East, South-West, South-Central and South-East which were

grouped into two territorial units according to the agreements with Eurostat (NUTS) in 2005. The

municipalities in the country are very different in their economic development, the demographic

characteristics and the social status of the population. Overcoming these economic and social

differencesisthemaingoaloftheregionalpolicy.

The two functional regions (FR) are Plovdiv and Blagoevgrad. The Plovdiv FR corresponds to the

municipalityofPlovdiv.TheBlagoevgradFRcorresponds to theBlagoevgraddistrict in thenational

administrative-territorial division. The two FRs have a comparable population size: 341625

inhabitants for Plovdiv and 312831 for Blagoevgrad. The two regions have several specific

characteristics: Plovdiv FR has a central location in the country while Blagoevgrad FR is a border

region (withMacedonia andGreece); Plovdiv FR is an urban territorywith higher concentration of

servicesandindustryinitseconomy;BlagoevgradFRismixedwithruralandurbanareasandhasa

highershareofservicesector intheeconomy.Bothregionsare interestingtobestudied intermsof

theimplementationofLLLpoliciesduetotheirdifferenteconomiesandlabormarketdevelopments,

populationandeducationalstructures.

FunctionalRegionPlovdiv

- Plovdiv FR is unique in terms of administrative-territorial characteristics, e.g. Plovdiv

MunicipalityisoneofthethreemunicipalitiesinBulgariawhichcomprisesonlythemaincity.

- TheFRhasamulti-sectoreconomyprovidingaround7%ofthenationalsalesrevenueofgoods

andservices(www.pd.government.bg).Theindustrialproductiongives62%oftherevenue.Thereisa

trend in revenue growth in services. The main economic sectors which shape the industry are

production of food, beverage and tobacco products (around 28% of the gross sales revenue),


6

productionof ferrousmetals(14%);metalcasting,metalworking,andmachineryproduction(11%);

productionof chemicals and chemical products (9%);productionof cellulose, paper, polygraphand

publishing goods (8%), (www.pd.government.bg). The local economy generates output of over 6

billion EUR annually, of which about 3.1 billion EUR in manufacturing, 690 million EUR in

construction, 400 million EUR in transport and logistics, and 310 million EUR in IT and business

services.

- The region has a well-developed logistics network that has a big potential to attract local

entrepreneursandforeigninvestors,anditappearsasanimportantcharacteristiconthesupplyside

ofthelabormarket:ahighwayconnectionwithCentralandWesternEurope;well-developedrailway

network with a connection to the nearest sea port; an intersection of Pan-European transport

corridors(IV,VIIIandX);acargoandpassengerairport(upcomingconcession);afreetradezoneand

acustomsterminal.ThePlovdivInternationalFair,spreadonaterritoryof352000m2,makesthecity

is an international, intellectual, trade and investment center, organizingmany trade fair events and

thematicexhibitionsonnationalandinternationalscale.

- Plovdivhasawell-developededucationalsystem,whichcouldserveasasourcepool to feed

the necessities of unemployed young people, and to insure them with modern and qualitative

knowledge.Thereare9universities,with39260students,and78primary,secondaryandvocational

schools with 8351 pupils. In 2014, there were 8657 university graduates, 5592 high school

graduates, of which 2825 graduated from vocational high schools, and 2767 general high school

graduates(www.nsi.bg).

FunctionalRegionofBlagoevgrad

- BlagoevgradFRisthesixthlargestdistrict inthecountrycovering14municipalitiesand280

settlements (http://www.bl.government.bg/en/population). It has a relatively good demographic

structure. The urban population in the district is 39% and there is a high percentage of people

employedinservices.

- TheFRischaracterizedbydiversifiedeconomicbranchstructure:foodandtobaccoprocessing

industries, tourism, transportandcommunications, textile industry, timberand furniture industries,

ironprocessingandmachineryindustry,constructionmaterialsindustry,aswellaspharmaceuticals,

plastics,paperandshoesproduction.Withitsrailwaylineandroadconnection,thedistrictformsthe

heart of the land-based trading route between northern Greece, Bulgaria and Romania

(http://www.bl.government.bg/en/economy). The developed labor market is an important

prerequisitefortheprofessionaldevelopmentofyoungadultsintheirlifecourse.Industryoccupiesa

significantplaceintheeconomicactivitiesoftheregion.Itsbranchesform25.7%intotalproductsin

Blagoevgrad FR.More than 39% of all employed people in the region are engaged in the industry.

Thereareseveralleadingindustrialbranchesinthearea.Foodindustryconstitutes31%ofthewhole


7

FRindustryanditscompanies formthepredominantemploymentarea.Textile industry,whichisof

particularimportancefortheeconomyoftheregioninrecentyears.Activeplayers,attheendof2014,

dealingwiththeproductionofclothingindustryare739or27.8%ofthetotalregionalindustry.Most

ofthemaresmallandmicrobusinesses.Typicalofthissectoristheparticipationofforeigninvestors

(Greek, German, and French) that created new owned or joint ventures in the field. Wood and

furnitureproduction formanother important segmentof the regional industry.Thedevelopmentof

theindustryisbasedontheuseoflocalrawmaterialsandhasaperspective.Tourismintheregionisa

major sector of the economy. Agriculture is also developed. The specialization of region crop

productioninthecountryisdeterminedbytheproductionoftobacco.

- BlagoevgradFR is a significant, economic, educational and cultural center of theRepublic of

Bulgaria. The large number of young adults in the district is a good basis for the development and

implementation of LLL practices in formal and non-formal education. There are a total of 133

educationalinstitutionsthatinclude106generalschools,3specialschools,1artsschool,18vocational

highschools,2postgraduatecollegesand2universities.

Allofthesecharacteristicsofthepopulationandthesystemsofeducation,economyandcultureinthe

twoFRs suggest awide rangeof diversity in the approaches towards young adults and thepolicies

required for their inclusion in LLL. Both regions demonstrate efforts to establish effective cohesion

betweeneducation,scienceandbusiness.

Demographicstructure

InordertounderstandproperlythedemographicstructureandprocessesinBulgaria,itisnecessary

firsttounderlineafewimportantpoints:

• Bulgaria is a medium sized European country (a bit over 7million inhabitants as of 2016)

whichisexperiencinganegativepopulationgrowthsince1989.

• Figure1demonstratesnotonlythenegativepopulationgrowthinthecountryandinthetwo

regions but also the trend in its development over time. For thiswe are using the 2-period

movingaverageindicator(2perMov.Avg.)anditsvaluesarepresentedonseparatelinesfor

thecountryandtheregions.


8

Figure1.Naturalchangeofpopulation(‰)

Source:EUROSTAT,NSI

Although both South-West and South-Central regions have experienced negative natural changes in

population,theeffectissmallercomparedtotheoverallcountrychange.Thisispartlyduetothefact

thattheeconomicdevelopmentoftheseregionsovertimehasattractedmorepeopleandinparticular

youngpeople,whichmakesthembetteroffcomparedtootherregionsofBulgariawherepopulationis

older (thus in the rest of the country themortality rate is higher and the birth rate is lower). The

South-Westregionhadacruderateofnaturalpopulationchangeof-4in2015,comparedto-5.7for

South-Centralregionand-6.2forBulgaria.Thatmeansthatthedecileinnaturalpopulationgrowthin

theSouth-WestregionissmallerthanthedeclineintheSouth-CentralregionwhichIturnissmaller

thanfortherestofthecountry.Thedecreaseinpopulationduetonaturalcausesinthetworegionsis

partiallycompensatedby internalmigrationandby theabilityof theregionalauthorities toprovide

bettermedicalservices(whichinturnarerelatedtotheeconomicdevelopmentoftheregions).Asa

result, it is evident that the percentage of Bulgarian population living in South-West region has

increasedsteadily from27.6%in2005to29.79%in2015.Thesameindicator for theSouth-Central

regionhasshownaverysmall(butstable)decreasefrom20.15%in2005to20.08%in2015.


9

Figure2.PercentageofBulgarianpopulationlivinginanalyzedregions

Source:EUROSTAT,NSI

• LikemanyotherEuropeancountries,Bulgariahasanagingpopulation.Whatmakestheeffects

of this trend so serious is that combined with outmigration processes and the necessity to

catch up with the more developed European countries aging and high mortality rates are

turningintoamajorhurdleforthefutureeconomicdevelopmentofthecountry.

Aginghasresultedinanincreaseofthemedianpopulationagefrom41.2in2005to43.6in2015.This

changeismoresignificantfortheSouth-Centralregionwherethemeanagehasincreasedfrom41in

2005to44.3tenyearslater,whileintheSouth-Westthechangeissobig–from39.8to41.6.

It shouldbenotedagain that these effects aredistortedby including the capital city in the regional

division which also results in a higher population density in South-West (106 people per sq. km)

compared to South-Central (66 people per sq. km) and a larger share of young population (5.8 in

South-Westcomparedto5inSouth-Centraland5.2onaverage).


10

Figure3.Proportionofpopulationaged20-24

Source:EUROSTAT

Thedemographiccomparisonbetweenthetworegionswillnotbefullenoughifwedidnotunderline

thatSouth-Centralregionhasahigherfertilityrate(1.59comparedwith1.36)butthisisalsofollowed

byahigherinfantmortalityrate(7.9comparedtoonly3.6forSouth-Westregion).

Figure4.Fertilityrate(right)andinfantmortalityrate(left)

Source:EUROSTAT,NSI


11

• Emigrationabroadaffectsnotonlythenationaleconomy,butalsoplaysanimportantrolefor

theregionaldevelopment,becausetheeconomicdisproportionsamongtheregions(reflecting

relative development of different regions as well as relative development within the same

region–asstressedinsection1)resultinasignificantinternalmigrationaswell

WhilecruderatesofnetmigrationremainnegativeforBulgaria(-0.6in2015),theSouth-Westregion

has been able to attractmore people for the last yearwith rates from+5.4 in 2005down to 2.2 in

2015. The South-Central region on the other hand suffers from negative crude rates of migration,

which despite from falling from -4 in 2005 down to -1 in 2015 still represent a challenge for the

economicdevelopmentof the region.Regardingmortality rates it shouldbenoted thateven though

South-Western region is close to the nation-average this indicator differs across cities inside the

region,beinglowerinthecapitalSofia.

With69.3%oftheyoungpeoplelivingwiththeirparentsby2013,Bulgariaissimilartocountrieslike

Spain (69.6%), Croatia (79.1%) and Portugal (71.6%) and this share is higher than the average

percentageintheEU(55.4%measuredforEU27asof2013).Thispercentagehasbeenstableforthe

last fewyears and isdue toboth economic and social factors.Oneof the factors commonlyused to

explain this has been the economic crisis of 2008 and the long recovery period. Howeve,r the

percentageofyoungpeoplelivingwiththeirparentsinBulgariahasnotchangedsignificantlywiththe

economic cycle which indicates that besides the low pay and relatively high rents there are also

significant social factors such as cultural traditions, strong family links and a shared view between

parents and children to keep the former as long as possible inside a well-known “comfort zone”

(KovachevaandKabaivanov,2014;MitevandKovacheva,2014).TheEUROSTATdataalsoshowsthat

menaremore likelytostay longerwiththeirparentscomparedtowomen,which isoftenrelatedto

internalmigrationasinsmallercitiesandvillagesitiseasierformentofindajobandtheyhaveless

incentivestorelocate.

Thestructureoftheeconomy

WhendiscussingthestructureofBulgarianeconomy,weneedtopointoutseveralimportantfactsthat

accountformanyofthedifferencesdiscussedinthistext:

• Firstofall,Bulgariastillneedstocatchupwith itseconomicdevelopment, thustheabsolute

valuesoftheGDPpercapitaaresignificantlylowerthantheEU28averagevalues.

Intermsofabsolutevalues,theGDPpercapitainBulgaria(currentprices)isgrowingatratesofwell

above4%forthelastyear,howeveritisstillabout47%oftheEUaveragevalue.Theeconomiccrisis


12

of2008hasalsohadanegativeimpactonBulgaria,andalthoughthisimpacthasnotbeenasstrongas

inothercountriesinEurope,thefinaloutcomecanbeseenintheslowrecoveryandlowgrowthrates

in2010-2014.

• Despite the fact that GDP in Bulgaria has grown faster than in most of the well-developed

countriesforthelastfewyears,thisgrowthisfarfrombeingsufficienttomovequicklytothe

EUaveragevaluesforgrossoutputandincome.

Figure6showsthattheeconomiccrisisof2008hitBulgarianeconomyabitlatercomparedtotherest

oftheEU(withthedeclineinrealGDPdetectedin2009)andresultedinalongerperiodofrecovery.

Thismeansthatregardlessofthepositivegrowthin2010,thecountryisstillfarfromgettingbackthe

samemomentumithadpriortothecrisis.

• Thereis(andhasbeenforalongtime)asignificantdifferenceintheeconomicdevelopmentof

different regions that has to be accounted for when explaining not only economic but also

demographicandsocialprocessesdevelopinginBulgaria.

ThisdifferenceisclearlyvisibleonFigure5,withBlagoevgrad(South-West)regionhaving76%ofthe

averageGDPpercapita inEU,whilePlovdiv(South-Central)regionhasonly33%oftheEUaverage.

Considering the last ten years, Blagoevgrad (South-West) region has always had about twice the

relativeGDPpercapitalevel,comparedtoPlovdiv(South-Central)regionanditisstillso,regardlessof

thefactthatthegrowthratesofthelatterhavebeenslightlyhigherforthepastthreeyears.

Figure5.GDPatcurrentmarketprices,Europerinhabitantin%ofEuropeanaverage

Source:EUROSTAT,Generalandregionalstatistics


13

There are several reasons for the economic differences across the examined regions, the most

importantperhapsbeingthattheSouth-WestregionincludesalsothecapitalcityofSofia.Itishardnot

tooverestimatetheimportanceofSofiaforthedevelopmentoftheregionasforexampleitaccounts

formorethan50%oftheforeigninvestmentspercapitaforthewholeregion(2015data)andifwe

includealsoSofiaareawewillendupwithwellover80%.

Figure6.RealGDPpercapitagrowthrate

Source:EUROSTAT,Generalandregionalstatistics

The spatial concentration of economic and administrative activity that is so strikingly evident for

South-WestregionandSofiaisalsotakingplace(althoughthescalesmaydiffer)inotherpartsofthe

country.Therefore, it is essentialwhencomparing the regions to take intoaccount thateach region

has typically one large city attractingmostof theForeignDirect Investments (FDI), highlyqualified

employeesandineffectmostofthegovernmentandpublicattention.

Ifwehavetosumup,thedifferencesbetweentheexaminedregionsarequiteimportantandtheyalso

haveahighimpactontheirprospectsofeconomicdevelopment.AnotablefactisthatPlovdiv(South-

Central) region has 12 times less spending in R&D compared to Blagoevgrad (South-West) region,

whichon its turnhasalmost3 times thecountry-averageR&Dspending).Thespatial concentration

explains the short-term prospects of widening the gap in the economic development inside the

regions.


14

Figure7.Economicsectors,valueadded(%ofGDP)

Source:EUROSTAT,NationalStatisticalInstitute

Thevalue-addedcontributionofthemaineconomicsectors,showninFigure7,revealsthatthereare

alsodifferencesacrossregions,withSouth-WestregionbeingclosesttotheEU28sectordistribution.

Itshouldbenotedthatthedifferencesinsectorcontributiontotheaddedvaluearenotnecessarilyan

indicator of problems as theymay rather point out a specialization of the region. In particular for

South-Westregion,Sofiaagainplaysavery importantroleas itseconomy ismainlyconcentrated in

theservicesector,thusincreasingtheshareoftheservicesectorforthewholeregion.

The percentage of researchers is low for both regions being analyzed, and has stayed virtually the

sameoverthe last fiveyears,withasmall increase intheSouth-Westregion.TheR&Dexpenditures

havealreadybeendiscussed,andtheyalsohighlightthefactthatthereisasignificantconcentrationof

R&Dspending inSouth-West region(andSofia inparticular).Thisconclusionholds forbothprivate

sectorandgovernmentexpendituresforR&D(wheretheratioofspendingforSouth-WestandSouth-

Central region is about 18:1, and despite that R&D expenses for South-Central have increased at a

fasterpaceforthelastyearthegapistoolargetobeclosedinshortterm).

Labor productivity in Bulgaria is constantly increasing, though it is still only 43.7% of the EU 28

average (asof2015). InSouth-Central regionover50%of theemployeeswork formicroandsmall


15

companies,while inSouth-Westregionoverhalfof theemployeeswork inmediumand largersized

companies.

Table1.Employmentdatabycompanysize

Companies <9employees 10-49

employees

50-249

employees

>250

employees

Bulgaria 30.56% 20.87% 20.27% 28.3%

South-West 27.37% 20.94% 20% 31.69%

South-Central 32.78% 24.4% 23.45% 19.37%

Source:NationalStatisticalInstitute(NSI)

Educationandtrainingsystem

The Bulgarian education and training system is comprehensive and partially decentralized at the

regionallevel.Theshareofgovernmentspendingoneducationin2014is4.1%ofnationalGDPandis

relativelystablefortheperiod2001-2014,fluctuatingaroundtheaverageof3.7%.Thisfigureplaces

BulgariabelowtheEUaverageof4.9%andamongthebottom10EUMemberStates.Schooleducation

is compulsory for children from 7 to 16 years of age. Secondary education (ISCED Level 3) can be

divided into comprehensive education (comprehensive and specialized schools) and vocational

training.Generalsecondaryeducationcanbeobtainedatcomprehensiveschools(courseduration3-4

years)andatspecializedschools(courseduration4-5years).Theadmissioninthespecializedschools

is upon completion of grades 7 or 8 and after exams depending on the profile of the school (with

emphasiseitheronforeignlanguage,oronscienceand/ormathematics,oronhumanities,orsports,

orartsetc.).

Secondaryeducationcanbeobtainedalsoatvocational-technicalschoolsaftercompletionofgrade8

and4yearsoftrainingoraftercompletionofgrade7and5yearsoftraining.Vocationalschoolswitha

three-year curriculum also provide secondary education. All students successfully completing

secondary education can access university after passing a general entry examination organized by

eachpublicuniversity.TheeducationalstructureoftheBulgarianpopulationisrelativelyclosetothe

educationalstructureofGermanyandtheUK. In2005,27.5%of thoseagedbetween25and65had

lowersecondaryeducation(uptoISCED2),whereasin2014thisratedecreasedto18.9%,equivalent

toadecreaseof8,6percentagepointsfor10years.ThisdecreaseisgreaterthaninGermanyandthe

UK.


16

Figure8.PopulationattainmentbyISCEDlevels,25-64yearsoverthecorrespondentagegroup

Source:LFS,EUROSTAT

Thepercentageofpeopleaged25-64withtertiaryeducation(atleastISCED5)increasedfrom21.6%

in2005to27.0%in2014.TheseratesarecomparabletoGermanyvaluesbutarelowerthanUKand

theEUaverage(37.9%)values.However,therearesignificantdifferencesbetweenstatisticalregions-

the proportion of people aged 25-65 in the South-West region is higher than in the South-Central

Region.IntheSouth-Westregion,thegrowthisfrom31.5%in2005to37.5%in2014.

In the South-Central region, the increase is from15.6% in 2005 to 21.4% in 2014. The difference

betweenthetwostatisticalregionsremainsrelativelyconstant -15.9percentagepoints in2005and

16.1percentagepointsin2014.

Figure9.Youngadults’educationattainmentbyISCEDlevels,30-34yearsoverthe

correspondentagegroup

Source:LFS,EUROSTAT

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Blagoevgrad(SouthWest)

Plovdiv(SouthCentral)

Bulgaria Germany UnitedKingdom

2005

ISCED0-2 ISCED3-4 ISCED5-8

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Blagoevgrad(SouthWest)

Plovdiv(SouthCentral)

Bulgaria Germany UnitedKingdom

2014


0

5

10

15

20

25

30

35

40

45

50

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

ISCED0-2

Blagoevgrad(SouthWest) Plovdiv(SouthCentral) Bulgaria Germany UnitedKingdom

0

5

10

15

20

25

30

35

40

45

50

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

ISCED5-8



17

Whenwe look at young adults, Bulgaria has a very high tertiary education attainment. The rate of

people aged 30-34 that have higher education in Bulgaria is comparable to that in Germany, but is

lowerthanintheUKandtheEUaverage(38.7%).Thisrateincreasedfrom24.9%in2005to30.9%in

2014. However, between 2005 and 2010, the proportion of people aged 30 to 34 with tertiary

educationintheSouth-WestregioniscomparabletothatoftheUK.Between2010and2012,thisrate

isdecreasing,andthen,in2014,itisagainapproachingthevalueintheUK.Thechangeisfrom35.0%

in2005 to43.0%in2014.Therateofpeopleagedbetween30and34withhighereducation in the

South-Central Region is the lowest and between 2005 and 2011 fluctuates at levels below 20%.

Growthhasbeenobservedover the last fouryears,with therate in2011being16.7%andrising to

23.2%in2014.However,thishighestshareintheSouth-CentralRegionislowerthanthelowestvalue

forBulgariaasawholeandfortheSouth-Westregion.

Figure10.Youngadults’educationattainmentbyISCEDlevel3-4,30-34yearsoverthe


Source:EUROSTAT

The proportion of people aged between 30 and 34with upper secondary education (ISCED 3-4) is

higherthanintheUK,butcomparabletoGermany.Thevaluesinthetwostatisticalregionsarevery

close to each other and are close to the average for the country. Dynamics show cyclical ups and

downs.

Thepercentageofpeopleagedbetween30and34withlowerthansecondaryeducationinBulgariais

higher than in the UK and Germany. It was 22.4% in 2005 and is relatively stable over the whole

0

10

20

30

40

50

60

70

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

ISCED3-4



18

period,with20.5%in2014.However,thetwostatisticalregionsarecompletelyopposite-theratesin

the South-West region are the lowest, even lower than the rates of theUK andGermany,while the

ratesintheSouth-Centralregionarethehighest.

Insummaryitcanbesaidthatthereisadifferencebetweenthetworegionsontheonepole,withthe

largestrateofpeopleagedbetween30and34withtertiaryeducation,andthesmallestrateofpeople

ofthesameagewitheducationbelowsecondaryistheSouth-Westregion.Ontheotherpole,withthe

smallestshareof30-34year-oldswithhighereducation,andthelargestshareofpeopleofthesame

agewithlowersecondaryeducation,istheSouth-CentralRegion.In2012theshareoffour-year-olds

attendingpre-schoolchildcarefacilitiesis79.5%,whichismuchlowerthaninGermany(95.8%)and

GreatBritain(98.0%).

Figure11.Tertiaryeducationaccessofthepopulationaged20-24yearsoverthe


Source:EUROSTAT

ThehighereducationsysteminBulgariacomprisesvariousformsofprogramsandcurriculauponthe

completionofthesecondarylevel.Bulgariantertiaryeducationalstructureisstep-by-stepadaptingto

the challenges of the European Higher Education area and there is positive evidence for that, e.g.

endorsingofNationalqualificationnetwork,developingRegistersforthehighereducationinstitutions

andtheirranking,etc.InBulgaria,therateofstudentsinthe20-24agegroupsisslightlyhigherthanin

Germanyand theUK. In2005, fewer thanhalf (48.3%)of thosebetween theagesof20and24are

students,whereasin2014twothirds(66.5%)ofthe20-24agegrouparestudents.

0

10

20

30

40

50

60

70

80

90

100

2005 2006 2007 2008 2009 2010 2011 2012



19

The dynamics in the South-West and South- Central regions is parallel to the overall dynamics for

Bulgaria. In the South-West region, the rate of students increased from69.8% in 2005 to 90.1% in

2013andin2014to80.8%.IntheSouth-CentralRegion,therateofstudentsincreasedfrom26.7%in

2005to52.2%in2014.Thedifferencebetweenthetwostatisticalregionsisrelativelyconstantforthe

period 2005-2013, fluctuating around 40 percentage points, while in 2014 it is reduced to 28.6

percentagepoints.IntheSouth-CentralRegionweseeanincreaseinthenumberofstudentsgrowing

everyyear,andthisgrowthprocessistheresultoftheactivepolicyofuniversitiesintheregionaimed

atattractingyoungadultsandtheirretention in localuniversities.Reducingtheshareofstudents in

theSouth-Westregion isduetoseveralreasons thatoperate inacomplexway:1)Targetinga large

percentage of young people in universities outside the country - mainly in Germany, Austria,

Netherlands,UnitedKingdom;Theseuniversitiesareperceivedasmoreprestigiousandpreferred,and

thisreducesthepercentageofuniversitystudents intheregion.2)Migrationofyoungpeopleoutof

thecountry.3)Theunderstandingthataftercompletingsecondaryeducation,itisgoodtogainlabor

experienceandresources;So,theeducationcareerinahighereducationinstitutionispostponedfor

severalyearsintime.

In Bulgaria the rate of early school leavers in 2016 is 13.8%. The share of early school leavers is

changinginparallelwiththeEU28andisalwayshigherthanit.InBulgaria,thechangeisfrom22.1%

in2005to13.8%in2016.TherateofearlyschoolleaversintheSouth-Westregionismuchlowerthan

thatintheSouth-Centralregion,whichiscomparabletothatofBulgariaasawhole.

Figure12.EarlySchoolLeavers18-24years,ESL(leftaxis)andpopulationneitherin

EmploymentnorinEducation15-24years,NEET(rightaxis)

0

5

10

15

20

25

0

5

10

15

20

25

30

35

40

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Blagoevgrad(SouthWest)ESL Plovdiv(SouthCentral)ESL BulgariaESLEU28ESL SouthWestNEET SouthCentralNEETBulgariaNEET EU27NEET


20

Source:EUROSTAT

The rateof thepeoplebetween15and24whoneither studynorwork isdecreased from21.5% in

2012 to 18.2% in 2016. This change is parallel to the change in the EU27, but the percentage for

BulgariaishigherthanintheEU27.However,theratesintheSouth-WestregionareclosetotheEU27

rates,whiletheratesintheSouth-CentralregionareclosetotheratesofBulgariaasawhole.

Figure13.PISAandPIAACcompetences,Europeanaverage=1

Source:PISA

According toPISA'sresults, theaverageof15-year-oldBulgarianstudents is lower than theaverage

forEurope,andovertheyears theyareapproachingbutataveryslowpace. In2006theresultsof

Bulgarianstudentsare84%oftheaverageforEurope,whilein2015theyare90%oftheaveragefor

Europe.Atthesametime,theresultsofBulgarian15-year-oldstudentsaremoreinhomogeneousthan

theaverageforEurope.In2006thecoefficientofvariationforBulgariawas1.24timeshigherthanthe

averageforEurope.By2012,BulgariaismovingclosertotheaverageforEurope,butin2014Bulgaria

is againmoving away from the European average – The coefficient of variation for Bulgaria is 1.16

timeshigherthantheaverageforEurope.

0,00

0,20

0,40

0,60

0,80

1,00

1,20

1,40

pisa2006,age15

pisa2009,age15

pisa2012,age15

pisa2015,age15

pisa2006,age15

pisa2009,age15

pisa2012,age15

pisa2015,age15

Meannumeracy Coeffitientofvariationnumeracy


21

Figure14.Participationrateineducationandtraining–24-34agegroup(last4weeks)

Source:EUROSTAT

Regardingadultparticipation ineducationandtraining, inBulgariapeoplewhohaveparticipated in

adulteducationinthelastfourweeksbeforebeinginterviewedare7,4%.Thisrateofyoungadultsin

age group between 24 - 34 years ismuch lower than the EU27 average. This share increases from

4.2% in 2005 to 7.4% in 2016 for Bulgaria. The low participation is due to several reasons: 1) the

enterprises andorganizationsdonot invest funds for training their employeesandworkers.2)The

people's incomes are lowand they cannot afford to target training. 3) Insufficiently activepolicy of

organizationsintheformalandnon-formaleducationsystemtowardsadults.

Labourmarket

Youth employment rates in Bulgaria are well below the EU-27 value, as shown on Figure 15 with

South-West region being above country-average of 20.3% in 2015. However, these values are just

slightly higher than youth employment in Spain and Croatia, while being close to the youth

employment rate in Portugal. The employment of male youths in 2015 is higher for both regions

(25.3%comparedto19.3%forfemalesinSouth-Westand23.6comparedto16.1%inSouth-Central)

aswellasforBulgariaingeneral(24%comparedto16.5%forfemales).

0,0

2,0

4,0

6,0

8,0

10,0

12,0

14,0

16,0

18,0

20,0

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

EU27 Bulgaria Germany


22

Longtermunemploymentrates,shownonFigure16, indicatetheeffectsoftheeconomiccrisisfrom

2008on theyouthemployment.Theyalsodemonstrateone interestingcharacteristicof thestudied

regions – South-West (in particular Sofia) respondedmuch faster to the crisis, while South-Central

regionwasthefirstonetoreachthepeakinunemploymentandmovetorecovery.

Figure15.Youthemploymentrate(age15-24)

Source:EUROSTAT

Thegenderstructureoftheunemploymenthasalsobeensubjecttoachangewithbothratesformales

and females going down after the initial surge due to the crisis in 2008. By the end of 2015 the

percentageofunemployedmalesaged15-24is21.2%andisalmostidenticaltheshareofunemployed

femalesinthesameagegroup-22.3%.Bothregionsthatwehaveonfocusfollowthesamepattern,

butwith importantdifferences in theabsolutenumberofunemploymentrates– forexampleby the

end of 2015, the share of unemployed youngmales in South-West is 14.9% compared to 23.2% in

South-Centralregion.


23

Figure16.Longtermyouthemploymentrate(age15-29)

Source:EUROSTAT

Thesefactsonceagainconfirmthatthereisasignificantdifferenceacrossthestudiedregionsandit

affects not only their prospects for economic development but is also an important force driving

internalmigration.Itisstillnecessarytostressthatwithanoverallyouthunemploymentratioof5.6%

(closertoAustriawith6%andUKwith8.6%,ratherthantoSpanwith16.8%orCroatiawith14%)

Bulgariaisofferingquitegoodemploymentopportunitiesforyoungpeople.

Looking at the qualification structure of Bulgarianworkforce in the labormarket it is important to

notethatbytheendof2015theshareofhighlyskilledwhite-collaremployeesismuchlowerthanthe

EU-27average(19%comparedto27%),whiletheshareoflowskilledblue-collaremployeesishigher

(28% compared to 21%). Taking into account that we have almost identical percentages of low

qualifiedwhite collar and high qualified blue-collar employees as the EU-27 average, this indicates

thatBulgarianlabormarketisingenerallessqualified.


24

Redistributionandsocialinclusion

InBulgaria,netsocialprotectionexpenditureincreasesfrom13.4%ofGDPin2007to18.5%ofGDPin

2014.InBulgaria,thecostofsocialprotectionpercapitainPPPin2014isEUR2544,whichis29.0%

of theEUaverage19and is32.2%of theEUaverage28.This rate increases from2005 to2014,but

remainsmuchlowerthantheotherEUcountries.

Figure17.ExpenditureinsocialprotectioninPPSperinhabitantas%ofEU19

Source:ESSPROS,EUROSTAT

The disposable household income in Bulgaria in 2013 is much lower than in other EU countries -

34.0%ofGermanyand41.1%ofUK.Thedisposablehouseholdincomerisesfrom4200Euroin2005

to 6900Euro in 2013. The disposable household income in the South-West region in 2013 is 1200

Euro higher than the average for Bulgaria, while the disposable household income in the South -

CentralRegionis300Euroslowerthantheaverageforthecountry.

In2015,theGinicoefficientfortheequivalentdisposableincomebeforesocialtransfersforBulgariais

very similar to that for the EU27 - 51.9% for the EU27 and 51.6% respectively for Bulgaria,which

shows a relative equal degree of inequality. However, after social transfers, Gini coefficient for

BulgariaishigherthanfortheEU27-31.0%fortheEU27and37.0%respectivelyforBulgariain2015.

0

0,2

0,4

0,6

0,8

1

1,2

1,4

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Bulgaria Germany Italy Finland UnitedKingdom


25

Thismeans that social transfers reduce inequality, but this decrease is less pronounced inBulgaria

thanintheEU27.GinicoefficientsforbothBulgariaandtheEU27arerelativelystableovertheperiod

2006-2016.

Figure18.GINIindexbeforeandaftertaxes(leftaxis)anddisposableincome(rightaxis)

Source:EUROSTAT

TherateofpeopleatriskofpovertyandsocialexclusioninBulgariaisdecreasingintheperiod2006-

2015andisrelativelystablebetween2008and2015between40%and50%.

ThepercentageofpeopleatriskofpovertyandsocialexclusionintheSouth-Westregionislowerthan

in the South-Central Region and Bulgaria as a whole. The change in the two statistical regions is

parallel and parallel to the change in Bulgaria as a whole. In the period 2009-2015, the difference

betweenthetwostatisticalregionsisrelativelystableandfluctuatesaround17percentagepoints.

Similarconclusionscanbedrawnfor therateofpeople livingwithseverematerialdeprivation.The

rate of these people in Bulgaria is decreasing and three periods can be highlighted – in the period

2006-2007theratesfluctuatedaround58%,intheperiod2008-2013theratesfluctuatedaround43%

and in the period 2014-2015 the rates fluctuated around 34%. Again, the rate of people living in

severematerialdeprivationintheSouth-WestregionislowerthanintheSouth-CentralRegionand

Bulgariaasawhole.

€0

€1 000

€2 000

€3 000

€4 000

€5 000

€6 000

€7 000

€8 000

€9 000

0,0

10,0

20,0

30,0

40,0

50,0

60,0

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

EU27GINIbefore BulgariaGINIbeforeEU27GINIafter BulgariaGINIafterBulgariadisposableincome SouthWestdisposableincomeSouthCentraldisposableincome


26

Figure19.Populationatriskofpovertyorsocialexclusion,%(POV)andseverematerial

deprivationpopulation,%(SMD)

Source:EU-SILC,EUROSTAT

Healthandwell-beingconditions

Healthandwell-beingconditionsaredifficulttoassess.Therehavebeenmanydatagapsandthereis

notenoughinformationattheregionallevelandwerefertothegeneralstateofhealthandwell-being

inthissection.

In2014theaveragelifeexpectancyingoodhealthinBulgariais66yearsforwomenand62yearsfor

men. These rates are higher than in Germany and are comparable to those in the UK. The rate of

peoplewhoappreciatetheirhealthasgoodorverygoodinBulgariain2015is65.6%,whichisslightly

lowerthantheEU27average(67.0%).However, thisraterisesrapidly from2006to2010,andthen

beginstoslowdown.

Overall,bothmenandwomen inBulgariaagedbetween25and35aremoredissatisfiedby the ten

indicatorsformenandwomenintheEU28.Thegreatestdiscrepancyisintraveltimeindicators

0

10

20

30

40

50

60

70

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

BulgariaPOV SouthWestPOV SouthCentralPOVBulgariaSMD SouthWestSMD SouthCentralSMD


27

(-21.2% formenand -18.6% forwomen), "personal ties" (-20.5% formenand -23.0% forwomen),

"Livingenvironment"(-17.7%formenand-17.4%forwomen)and"leisureandgreenareas"(-14.8%

formenand-16.8%forwomen).

Totalsatisfactionforthe18-30agegroupinBulgaria(-1,161)ismuchlowerthantheEU28average(-

0,014),whilemen(-1,211)are lesssatisfiedthanwomen(-1,109). At thesametime, theresults for

BulgariaaremoreinhomogeneousthantheresultsfortheEU28.

Figure20.Highsatisfactioninvariouslifedomains,populationaged25-34,EU28andBulgaria,

2013


In2015thenumberofbedsinhospitalsinBulgariais713per1000people,whileintheSouth-West

regionitis688andintheSouth-Centralregionis763.Overall,thetrendinBulgariaistoincreasethe

numberofbedsinhospitalsper1000people.AnupwardtrendisalsoobservedintheSouth-Central

region,whileintheSouth-Westregiontherearecyclicalperiodsofincreaseanddownwardperiods.

In2015 thenumberofnurses andmidwivesper1000people inBulgaria is485, in theSouth-West

regionis500andintheSouth-Centralregionis453.Overall,thetrendinBulgariaisontheincrease,

againsuchanincreaseisobservedintheSouth-Centralregion,whileintheSouth-Westregionthereis

acyclicalalternationofperiodsofincreaseandperiodsofdecrease.

051015202530354045

Financialsituation

Accommodation

Jobsatisfaction

Commutingtime

Timeuse

Overalllifesatisfaction

Recreationalandgreenareas

Livingenvironment

Personalrelationships

Meaningoflife

EU28men Bulgariamen EU28women Bulgariawomen


28

Thenumberofdoctorsper1000people inBulgariahas increasedfrom364in2005to399in2014.

GrowthisalsoseenintheSouth-Centralregion-from317in2005to374in2014.IntheSouth-West

region,however,from2005to2010therewasadecreasefrom419to391,andthenanincreaseand

in2014thefigurereached418,i.e.,reachesthe2005value.

Finalremarks

Tosumupthisoverviewofthe livingconditionsforyouthinthetworegionsinBulgaria,weshould

stressthefollowingpoints:

At the national level andwithin the functional regions there is a process of economic stabilization,

income growth, poverty reduction, increasing youth employment, growth in disposable household

income,andanincreaseintheshareofpeoplewithhighereducation.Whilethistrendhasapositive

impact on the living situation of young adults in the country, still the country lags far behind the

conditions for youth development in the other EU member states. The Bulgarian economy,

productivity, employment and incomes remain low when compared to the average values on the

Europeanlevel.BulgariastillneedstocatchupinitseconomicdevelopmentwiththerestofEurope,as

the absolute value of the GDP per capita is significantly lower than the EU 28 average values. It

remainsatabout47%oftheEUaverage.The laborproductivity inBulgaria isconstantly increasing,

thoughitisstillonly43.7%oftheEU28average(asof2015).Theshareofgovernmentspendingon

education in 2013 is 4.1% of the national GDP and is relatively stable for the period 2001-2013.In

addition,theratesofparticipationoftheBulgarianpopulationintheformsoflifelonglearningarealso

low.

There are important differences between the two regions in Bulgaria. For example, in the South-

Centralregionover50%oftheemployeesworkformicroandsmallcompanies,whileinSouth-West

region over 50% of the employees work in medium and larger sized companies. Concerning the

unemployment rates, the South-West region has somewhat more favorable conditions for youth

transitionsfromeducationtoemployment.ThustherateofunemployedyoungmalesinSouth-Westis

14.9% compared to 23.2% in South-Central region. Regarding education, the South-West region is

withthelargestshareofpeopleagedbetween30and34withcompletedtertiaryeducation,andthe

smallestshareofpeopleinthesameagerangewithlessthaneducation.TheSouth-CentralRegionis

withthesmallestshareof30-34year-oldswithhighereducation,andthelargestshareofpeoplewith

lower secondary education. In addition, the percentage of people at risk of poverty and social

exclusionintheSouth-WestregionislowerthanintheSouth-CentralRegionandBulgariaasawhole.

TheanalysisofthelivingconditionsofyoungadultsinBulgariarevealsseveralriskfactorsthatplace

young people in vulnerable situations. In education it is the young Roma who are particularly


29

disadvantagedwhoareatariskofearlyschoolleavingbecauseofpoverty,culturalpracticesofearly

marriages and the existence of segregated schools (Milenkova and Hristova, 2017). While young

peoplefromotherminoritiesandthemajoritypopulationalsofacetheriskofdroppingoutbeforethe

obligatoryschoolleavingage,fortheRomathisoftenmeansnotonlyalackofanyqualifications,but

alsoremainingilliterate–aboutonefifthoftheRomayouth.(NSI,Census2011).Onthelabormarket

underprivilegedarethelong-termunemployedandthoseworkingintheinformaleconomybutmost

atriskaretheNEETs-withthosenotineducation,trainingandemploymentwhoareover20%inthe

South-Centralregion.YoungpeoplewithdisabilitiesandfromRomaethnicityareoverrepresentedin

thisgroup.Thoseareriskofseverematerialdeprivationinthetotalpopulationvarybetween25%in

theSouth-Westto40%intheSouth-Centralregion.Again,inthisgroupmostaffectedarefamilieswith

manychildren,singlemothersandtheRomayouth.

Inconclusion,thedatashowthatthelivingconditionsforyoungadultsincludingthestateofeducation

arebetter intheSouth-Westregionthan intheSouth-Centralregion.However,weconsiderthatthe

differencesbetweenBulgaria and themoredeveloped countries in theEUaremore significant, and

theyneedtobeaccountedforwhentryingtoexplainyoungpeople’sdecisionsasthesediscrepancies

areoftenthemajorreasonforthestillongoingmassyouthemigrationoutofthecountry.

References

EUROSTAT(2017).EuropeanUnionstatisticaloffice,http://ec.europa.eu/eurostat/TheEuropeanUnionLabourForceSurvey(EU-LFS),EUROSTATKovacheva,S.andS.Kabaivanov(2014)‘Youngpeopleinsearchofawork-familybalance',in

Deliyanni,V.(Ed.)ChanginglandscapesforchildhoodandyouthinEurope,Cambridge:CambridgeUniversityPress,61-85.

Milenkova,V.,S.Hristova,(2017)“Isthereanylightinthetunnel?OntheDrawbacksofRomaEducationalIntegrationinBulgaria”.EuropeanQuarterlyofPoliticalAttitudesandMentalities,6(1):1-16.https://docs.google.com/viewer?a=v&pid=sites&srcid=

ZnNwdWIudW5pYnVjLnJvfGV1cm9wZWFuLXF1YXJ0ZXJseS1vZi1wb2xpdGljYWwtYXR0aXR1ZGVzLWFuZ

C1tZW50YWxpdGllc3xneDo3MWExZjllNzVjMDdhM2YMitev,P.-E.andS.Kovacheva(2014)YoungPeopleinEuropeanBulgaria.ASociologicalPortrait

2014.Sofia:FreidrichEbertFoundation.NationalStatisticalInstitute(2017),http://www.nsi.bg/enOECD(2017),https://data.oecd.org/TheEuropeanUnionStatisticsonIncomeandLivingConditions(EU-SILC),EUROSTATOECD,PIAAC,http://www.oecd.org/skills/piaac/OECD,PISA,http://www.oecd.org/pisa/UNESCO,http://data.uis.unesco.org/


Work Package 4


Croatia -

National Briefing Paper with national and regional data sets

University of Zagreb, Faculty of Teacher Education (UNIZG) Vlatka Domović, Dejana Bouillet & Monika Pažur

15/06/2017

Project Coordinator: Prof. Dr. Marcelo Parreira do Amaral (University of Münster) Project no.: 693167 Project acronym: YOUNG_ADULLLT Project duration: 01/03/2016 to 28/02/2019 (36 months) Type of document: Deliverable 4.1. Delivery date: Month 19 Dissemination level: Public


2

Tableofcontents

ExecutiveSummary........................................................................................................................................................41. Qualitydataassessment.......................................................................................................................................52. Demographicstructure........................................................................................................................................63. Generalstateoftheeconomy.........................................................................................................................114. EducationinCroatia...........................................................................................................................................135. YouthandtheLabourMarket.........................................................................................................................206. Redistributionandsocialinclusion..............................................................................................................247. Healthandwell-beingconditions.................................................................................................................29References.......................................................................................................................................................................33

Listoffigures

Section3DemographicstructureFigure1StatisticalregionsLevel2(NUTSII),2013,p.7Figure2:Comparisonofpopulationregardingageaccordingtothecensusin2001andin2011,p.8Figure3:Migration,olddependencyandfertilityrates,populationchangeinCroatia,ContinentalCroatia,AdriaticCroatia,2005-2015,p.9Section4GeneralstateoftheeconomyFigure4:GDPineuroperinhabitantsPPSandlabourproductivity(rightax,EU=100),Croatia,ContinentalCroatia,AdriaticCroatia,2006-2015,p.11Section5EducationinCroatiaFigure5:Trendsinenrolmentsinacademicvs.professionalhighereducation,p.17Figure6:NEETratesforgroupage15-29inCroatiaandEU28,p.18Figure7:Positioninrelationtostrongest(outerring)andweakestperformers(centre),p.19Section6YouthandtheLabourMarketFigure8:Youthemploymentandunemploymentrates,youthunemploymentratioofyoungpeople15-24(rightex),EU27,Croatia,AdriaticCroatiaandContinentalCroatia,p.21


3

Figure9:TermofunemploymentofunemployedyoungadultsinOsijek-BaranjaandIstriaRegion,p.23Section7RedistributionandsocialinclusionFigure10:Socialprotectionbenefits(%oftheGDP),p.24Figure11:At-risk-of-povertyratebyNUTS2andNUTS3(%),p.25Figure12:Youngpeopleatrisk-of-povertyorexclusionrateandseverematerialdeprivationrate(age16-29,%),p.26Figure13:Giniindexofequaliseddisposableincome,p.27Figure14:MaterialDeprivationRate,p.28Section8Healthandwell-beingconditionsFigure15:Medicaldoctors:Healthpersonnel(perhundredthousandinhabitants,p.30Figure16:Prevalenceoftheratioofpersonswithadisabilityinthetotalpopulationofregions,p.31Figure17:Averageratingofsatisfactionbydifferentlifedomain(age:16yearsandover,2013),p.32


4

ExecutiveSummary

ThisNationalBriefingPaperprovidesashortoverviewofthelivingconditionsofyoungpeopleinCroatia.SpecialattentionisgiventothelivingconditionsofyoungpeopleintwoCroatianfunctionalregions(IstriaCountyandOsijek-BaranjaCounty).

Basedontheobtaineddata,itispossibletoconcludethatyoungpeopleinCroatialiveinconditionsthatarelessfavourableincomparisonwiththeEU28average.Thisconclusionconcernsyouthinbothfunctionalregions,eventhoughtheIstriaCountyismoredevelopedthantheOsijek-BaranjaCounty.

Themaindemographiccharacteristicisadeclineoftherateofnaturalpopulation(includingincreasingtheaverageageofthepopulationandlowfertilityrate).CroatianeconomicconditionsaresignificantlyundertheEU28average(theCroatianGDPissignificantlylowerthantheEU28average,andtheCroatianlabourproductivityissignificantlyundertheEU28andEuroareacountriesaverage).ComparingCroatiawithotherEUcountries,theshareofyouthlivingwiththeirparentsisveryhigh.ThemainstrengthsoftheCroatianeducationsystemareaverylowearlyschoolleavingrateandthehighproportionofsecondaryvocationalschoolgraduatesenteringhighereducation.Themainweaknessesarelowresultsininternationalstudiesofnumeracy,literacyandreadingskillsofyouth,aswellasextremelylowparticipationinearlychildhoodeducationandcareandinadulteducation.Theeconomicactivityrateofyouth(age15-24)hasdecreasedinthelasttenyears.CroatiaisoneofthethreeEU28countrieswiththehighestyouthunemployment.ThekeyissuesfacedbyyoungpeoplewhenenteringthelabourmarketinCroatiaarethelackofpreviousworkexperienceandmismatchbetweentheirqualificationsandtheskilldemand.Moreover,economicactiveyouthinthelabourmarketshowsagreatgendergap.CharacteristicsoftheCroatiansocialwelfaresystemshowthatthesocialprotectionexpendituresinthenationalGDPisbehindtheexpendituresintheGDPofEU28average,whilethematerialdeprivationrateismultipletimeshigher.However,thelivingconditionsforyoungpeopleinCroatiaandtheGiniindexhaveatendencytobesimilartotheEuropeanaverage.ThebestaspectofhealthcareinCroatiaisthebroadnessthatencompassesthepopulationwithfreehealthcareincludingpersonsintheregularsystemofeducationandpersonswithlowincome.However,CroatianpeoplearelesssatisfiedthantheaverageEuropeancitizensinthefieldofsatisfactionwithfinancialsituation,overalllife,recreationalandgreenareasandlivingenvironment.Moreover,theavailabilityofhealthservicesisnotuniforminallregionsofCroatiaanditissignificantlyweakerinrelationtootherEUcountries.


5

AllanalyseddatashowthatthelivingconditionsofyoungpeoplearebetterinIstriathaninthefunctionalregionOsijek-Baranja.

Introduction

This national briefing paper provides a short overview of the living conditions of young people inCroatiaand,morespecifically, intheNUTS2regions-ContinentalCroatiaandAdriaticCroatia. Datahas been collected at national (NUTS 0) and regional (NUTS 2) level according to six dimensions ofcontextuallivingconditionsagreeduponintheWP4guidelines.

Eurostatonlinedatabasesataggregatednationalandregionallevelareusedasmainsources.Thismaincorpusofdataiscomplementedbydatacollectedatthelocallevel,comingfromdifferentsourcesandmadeavailablebyCroatianBureauofStatistics,byofficialwebsitesofvariousCroatianInstitutions(forexample:Ministryofscienceandeducation,CroatianInstituteofPublicHealth,MinistryofHealthoftheRepublicofCroatia),regionaldevelopmentalstrategiesaswellasscientificpapers.ContextuallivingconditionsofyoungpeopleinCroatiaareanalysedbylookingatthe:

• demographiccharacteristicsofthepopulationanditssubgroups;• structureoftheeconomy;• inputsandoutputsoftheeducationsystem;• labourmarketsituation;• materiallivingconditionsofyoungpeople;• participationofyoungpeopleinthepoliticalandciviclife;• healthconditionsandindividualwell-being.

1. Qualitydataassessment

Asitismentionedabove,datahavebeencollectedatnational(NUTS0)andregional(NUTS2)level.Wheneverpossible,theresultsrepresentingthelivingconditionsofyoungpeopleintheselectedfunctionalregions(IstriaCountyandOsijek-BaranjaCounty)aregiven.

Eurostatprovidesavastamountofdatathatcanbeusedtocomparativelyassesslivingconditionsofyoungpeopleindifferentdomainsandinvariouscountries/regions.However,dataavailabilityattheregional/locallevelislimitedatNUTS2levelandextremelylimitedatNUTS3level.

Thisrestrainsthecomparabilityamongregionstoalimitedrangeofindicators.Moreover,harmonizeddataarehardtocomplementwithlocaldata,oftensufferingfromafragmentedlandscape


6

ofsources,astheyarecollectedformoreorlessspecificpurposesandusuallynotwiththeobjectiveofinteractionwithotherdatasources.

AsfortheavailabledatapublishedbyEurostat,datacoverseveralfieldsandarecomplementedwithmetadataandinformationabouttimeseries.However,accessibilityofdatamaybeaproblematicissue,asdatabasesonEurostatarenotcompletelycombinedandflexiblesothatthecollectionisattimesdifficult:asanexample,thesameinformationontwodifferentagegroupsmaybeavailableonlylookingattwodifferentdatabasesindifferentsectionsofthewebsite(theNEETratefor15-24isavailableamonglabourmarketstatisticswhiletheNEETrate15-29isavailableamongyouthstatistics).Ofcourse,thecomplexityandvarietyofthedatapublishedmakesuchcomprehensiveintegrationdifficulttoachieve.

DuetothefactthatCroatiabecamememberoftheEuropeanUnionintheyear2013,theCroatiannationaldataatEurostatareavailablefromtheyear2007orlater.ThatiswhythecomparativenationalandEuropeandata,ingeneral,covertheperiodfrom2007to2015.

2. Demographicstructure

TheRepublicofCroatiacovers56,539sqkmofcontinentalsurface(includingAdriaticIslands)and31,421sqkmoftheAdriaticSeaalongthecoast.AccordingtothePopulationCensustakenin2011,thepopulationsizeis4,284,889inhabitants(Population,HouseholdandApartmentCensus,2011).ItcanbesaidthatCroatiaisaCentralEuropean,aPannonian,aDanube-basin,aPeralpineandaMediterraneancountry.ThebordercountriesareSlovenia,Hungary,BosniaandHercegovina,SerbiaandMontenegro,andItaly(seaborder).Duetoitsgeographicandtrafficposition,culturalandeconomicinfluencesarisingfromwidersurroundings,naturalandgeographicfeatures,Croatiaappearsexceptionallyheterogeneous.TheContinentalPannonianandPeri-Pannonianareacovers53.7%ofthewholestateterritory,whilethecoastalareacovers31.4%.Theremaining14.9%ofthestateterritorycomprisesanarrowmountainareaofLikaandGorskiKotar.

AccordingtotheNationalclassificationofterritorialunits,asof1January2013theRepublicofCroatiahasbeendividedintotwostatisticalregions–ContinentalCroatiaandAdriaticCroatia1(Figure1).ThisclassificationhasbeensetupaccordingtoEUROSTATcriteria.

Eventhoughitisonlyastatisticaldivision,thatiswithoutelementsofmanagementcharacteroradivisionofnon-administrativetype,therecentdivisionoftheRepublicofCroatiaintotwo

1 Official Gazette No 96 2012 year


7

statisticalregions–ContinentalandAdriaticCroatia,hasopenedupaseriesofquestionsinasenseoffinancialandadministrativeefficiencyoflocalandregionalself-government(Bošnjak&Tolušić,2012).

Figure1:StatisticalregionsLevel2(NUTSII),2013(green=ContinentalCroatia,blue=AdriaticCroatia)

Source:CroatianBureauofStatistics

Namely,ContinentalCroatiaincludes13countiesandtheCityofZagrebasthelargesteconomic

centrewhichcomprisesalmostafourthofthepopulationofCroatia.Theregionhasalmost3millioninhabitants.Ontheotherhand,AdriaticCroatiaincludes7countieswith1,469,000inhabitants.TheareaofContinentalCroatiais31,846squarekilometres,whereasthatofAdriaticCroatiais24,696squarekilometres(CroatianBureauofStatistics,2016).ThefunctionalregionofIstriaCountyispartofAdriaticCroatia.TheareaofIstriaCountyis2,813squarekilometres,andthenumberofinhabitantsin2015was208,055(StatisticalYearbookoftheRepublicofCroatia,2016).Theotherobservedfunctionalregion–theOsijek-BaranjaCountyispartofContinentalCroatia,withanareaof4,155squarekilometresand305,032inhabitants(StatisticalYearbookoftheRepublicofCroatia,2016).


8

ThenumberofinhabitantsinCroatiashowsasteadydecline.Duetotheprocessofdepopulationandpopulationageing,Croatiahasbeenfacingnumerousdemographicchallengesforanumberofyears.Accordingtothe2011censustheRepublicofCroatiahad4,284,889inhabitants,whichrepresentsadeclineof3.4%comparedtothepreviouscensusin2001.InAdriaticCroatiathisdeclinewassomewhatlowerthaninContinentalCroatia,Namely,thepopulationofAdriaticCroatiadecreasedby1.06%,whereasinContinentalCroatiathedecreasewasashighas4.57%.Intheyearsafterthelastcensus,thepopulationhascontinuedtodecline.Accordingtodatafrommid-2014,thetotalpopulationwasby0.4%lowerthanin2013.Ifcomparingthetwoselectedfunctionalregions,ithastobenotedthatanincreaseinthepopulationwasobservedinIstriaCounty,whereasOsijek-BaranjaCountywastheonewiththehighestpopulationdeclinein2014(RegionalDevelopmentStrategyoftheRepublicofCroatiafortheperioduntil2020,2016).Intheperiodfrom2001to2011inIstriaCountytherewasamildincreaseinthetotalpopulation(by1,711inhabitants,orby0.83%).Thispopulationincreaseisnottheconsequenceofnaturalgrowth,whichhasshownanegativetrend,butisprimarilytheresultofapositiveexternalmigrationbalance,whichhasshownarisingtrendinthelastfewyears.Figure2:Comparisonofpopulationregardingageaccordingtothecensusin2001andin2011

Source:CroatianBureauofStatistics


9

Thebalanceofexternalmigration,i.e.betweenthenumberofpersonswhoemigratedfromandthosewhoimmigratedtoIstriaCounty,showsapositivegrowthtrend,withasignificantincreasein2014.Parallelwithanincreaseinthebalanceofexternalmigrations,anegativenaturalgrowthcouldbeobserved,withatendencyofmildincreaseofgrowth.In2011,naturalgrowthwasaccordingtoavailabledata-392,andin2013itwas-362,whichwastosomeextentcompensatedbythepositiveexternalmigrationtrends.ThedemographicstructureofthepopulationinIstriaregardingageshowssignsofdemographicerosion,whichhasanegativeinfluenceontheworkpotentialofthepopulation.Personsofmatureage(50-59yearsofage)makethemostnumerouspopulationgroupofIstria,whereastheaverageageis43.TheageingindexofIstriaCountyis136.8andishigherthanthenationalaverage(whichis115.0).ThismeansthatthepopulationofIstriabelongstothetypeofpopulationinthestageofdeepdemographicoldage(StrategyofDevelopmentofHumanPotentialsofIstriaCounty2016–2020).

Figure3:Migration,olddependencyandfertilityrates(rightax),populationchange(rightax),Croatia,

ContinentalCroatia,AdriaticCroatia,2005-2015Source:EUROSTAT

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TherateofnaturalpopulationdeclineandtheproblemofdemographicageingintheRepublicofCroatiaisworrying(e.g.in2014itwas-2.7‰,andin2015-4.0‰).Croatianpopulationisamongthefifteenoldestworldpopulations,withtheshareofolderpersonsinthepopulationconstantlyrising.In2005,16,700morepeoplediedthantherewereborn(37,500born,54,200died,accordingtoEurostat).Theaverageageofthepopulationisconstantlyincreasing.In1961itwas32.5years;in1971itwas34.1;intheyear1981itwas35.4andin1991itwas37.5,in2001itwas39.3andin2011itreached41.7years.Theageingindex(calculatedasthenumberofpersonsolderthan60perhundredpersonsaged0-19)was115.0in2011andisaquarterhigherthaninthepreviouscensus(2001–90.7),theageingindexcalculatedfromthenumberofpersonsaged65yearsandolderinrelationtothegroup0-14yearsis116.3,whereasin2001itwas91.9.Thus,inCroatiathenumberofolderpersonsissignificantlyhigherthanthenumberofyoungerpersons.Populationageingisalsovisibleintheold-agedependencyrate(ratiobetweenpopulationaged65andovertopopulation15–64),thatrosefrom26%in2005to28.3in20015.Acomparisonofchildbase(0–4)andpersons75andolderisverysignificantforunderstandingthestatesandprocessesinthecompositionaccordingtoage.In2001thoseagegroupswerealmostequalintheirnumber,andin2011therewere62%moreolderpeoplethanchildren.BasedontrendsandprojectionsasignificantdeclineinthepopulationofCroatiacanbeexpectedinthedecadestofollow.Accordingtoaprojectionconductedbymeansofthecohort-componentmethodforclosedpopulation(notincludingmigration),in2031Croatiawillhave3,680,750inhabitants.Thus,inthirtyyears’time(2001istheinitialyearoftheprojection)thenumberofinhabitantswillhavediminishedby756,710or17.1%.Inotherwords,duetobiological(natural)depopulation,i.e,ahighermortalitythanbirth(themigrationhasnotbeenincluded),onaveragetheRepublicofCroatiawillhavelost25,220inhabitantsperyear(accordingto:NejašmićandToskić,2013).

ThefertilityrateinCroatiaislowanddoesnotshowsignificantchanges(from2005to2015itis1.5).Infantmortalityinthefirstyearafterbirthis4.1deathsperthousandin2015.InCroatialifeexpectancyin2014was77.9years,withtheexpectedlifedurationinAdriaticCroatiabeing79.3years,whichishigherthanthenationalaverage,andinContinentalCroatiaitis77.2years.Moreover,lifeexpectancyissignificantlylowerformen(74.7years)thanforwomen(81years),(datafor2014).

In2013,amongyoungpeople,79.1%ofthoseaged20–29livedwiththeirparents.Thispercentagehasshownacertainstability,fluctuatingbetween74.4to79.9%intheperiodfrom2010to2013.ComparingCroatiawithotherEUcountries,theshareofyouthlivingwiththeirparentsisveryhigh.However,theaveragevaluesdonotrevealexistingstronggenderdifferences.Thepercentageof


11

youngmaleslivingwithparentsis86.1against72.1forfemales.Thereasonsforyoungpeoplelivingwiththeirparentsarevarious:theimpossibilityofsecuringaccommodation,unemploymentorjobinsecurity,culturalfamilypatterns,etc.

ThereisnodoubtthatCroatiafacedwithunfavourabledemographictrends:namely,between1953and2011theshareofyouth(agedbetween15and29)inthetotalpopulationdecreasedfrom27.7%to20.6%.Thisisoneofthereasonforwhichyoutharebecominganincreasinglyimportantsocialresource(Ilišinetal.,2013).

3. Generalstateoftheeconomy

GDPmeasures(Figure4)forCroatiaingeneral,aswellasfortwoNUTS2regions,showthateconomicconditionsaresignificantlyundertheEU28average.Figure4:GDPineuroperinhabitantsPPSandlabourproductivity(rightax,EU=100),Croatia,ContinentalCroatia,AdriaticCroatia,2006-2015

Source:EUROSTAT

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AfterapositivegrowthofGDPintheyears2006–2008(from14,400to16,500),theeconomiccrisisthatstartedin2008,hascausedadropandstagnationoflowGDPinthenext6years(from2009-2014).In2015,theGDPincreasedtothestatefrom2008(GDP2015=16,700).However,evenwithavisibleeconomicgrowthin2015,theCroatianGDPisstill42%lowerthantheEU28average.

DataforAdriaticandContinentalCroatiaindicatethesametrendchangeoftheGDPduringtheobservedperiod,wheretheGDPforContinentalCroatiaiscontinuouslygreaterthantheCroatianaverageandoftheaverageforAdriaticCroatia.Still,thisdatashouldbeinterpretedwithcaution.Thenationalclassificationofareaunitsfrom2012,dividedCroatiaintotwostatisticalregions(ContinentalandAdriaticCroatia)2.ContinentalCroatiaincludes13countiesandtheCityofZagrebastheeconomicallystrongestcenterwith3millioninhabitants.Inthatway,theBDPforContinentalCroatiaisalmostartificiallydoubled(BošnjakandTolušić,2012).Datapresentedinthiswayarecontradictorytothefindingsinfunctionalregions,andthereforetheOsijek-BaranjaCountyalthoughpartofContinentalCroatia,had,in2014,aGDPperresident8,045EUR.Ontheotherhand,IstriaCountyaspartofAdriaticCroatiaisoneofthemostdevelopedCroatiancountiesandwithitsGDPsignificantlydeviatesfromthedata(GDPperresidentin2014was12,724EUR).

DataaboutlabourproductivityshowsthatCroatiaissignificantlyunder(around40-50%)theEU28andEuroareacountriesaverage.

Croatiahashad146,766activebusinesseconomiesin2014accordingtoEurostat,andinthesameyearEU28averagewas26,307,386.But,itissignificantthatestimatedpercentageofactivebusinesseswithnoemployeesinCroatiais15,whileEUaverageis57%.In2014,around99,500(69%)ofactivebusinesseconomiesinCroatiahadfrom1-4employees,andasmallpercentageofthemhad5-9employees(9%)or10andmoreemployees(8%).TheEurostatdataaboutactivebusinesseconomiesforCroatiaisavailablesinceyear2012,andinthoseyears’numberoftotalactivebusinesseconomieshasincreasedfrom147,798in2012to146,766in2015.

NinemembersoftheEU28,amongwhichisCroatia,allocatelessthan1%oftheirBDPforresearchanddevelopment.In2014,Croatiaspent0.79%oftheBDPforR&D.AnamountofinvestmentinR&Dhasdecreasedin2014thanin2004for1.5%of2004amount.In2015,theamountinvestedinR&Dincreasedfor8,7%ofanamountin2014.However,thatisstilllessthan1%oftheBDPinCroatia(0.85%BDP).TocomparethosenumberswithEU28average,thesituationisfollowing:inyear2015totalinvestmentinR&DinCroatiaexpressedinEuroperinhabitantwas88.7,andEU28averagewas

2 Official Gazette NN 96/2012


13

587.7.Thereareonly3countriesinEU28whoseinvestmentinEuroperinhabitantislowerthaninCroatia:Bulgaria(60.1),Romania(39.4)andLatvia(76.7).FromtheamountofinvestmentinR&D,thebusinesssectorinvested51.2%,thegovernmentalsectorinvested24.5%,andtheremainingamountiscoveredbythehighereducationsector(23%)andprivatenon-profitsector(around1%).Thepercentageofresearchersemployedinallsectorsoftheeconomyisverylow(0.6%ofallemployment).Moreprecisely,in2014thenumberofresearchersemployedinallsectorswas10,726.Mostresearchersareemployedinthehighereducationsector(around7,000)andinthebusinessenterprisesector(1,100).InAdriaticCroatiain2015,therewere0.27%researchers(ofallemployees)employedinallsectors.InContinentalCroatia,thatpercentagewasonlyalittlebithigher(0.45%).

TheshareofpeopleemployedinthepublicsectorisslowlygrowinginCroatia,forexamplefrom2008(5.8%)to2014(7.1%).Thesamemovementispresentinemploymentineducation,thatintheyear2008was5.4%,andin2014,thatpercentagehasgrownto7.6.Finally,peopleemployedinthehealthsectorandinsocialworkmakearound6.8%oftotalemploymentofCroatia.

Inbrief,itispossibletoconcludethatCroatia’simmediateeconomicchallengesincluderestoringmacroeconomicstabilityandmodernizingpublicservices,thejudiciary,andthegovernanceofstate-ownedenterprises,tobettersupporttheneedsofpeopleandfirms.

4. EducationinCroatia

TheproportionofgeneralgovernmentexpenditurespentoneducationinCroatiawasgenerallystablebetween2007(10.5%)and2013(10.7%)butitfellsignificantlyto9.8%in2014.AlthoughgeneralgovernmentexpenditureoneducationasaproportionofGDProsefrom4.7%ofGDPin2007to5.1%in2013,italsofellin2014backto4.7%.ThisfigureplacesCroatiabelowtheEUaverageof4.9%andamongthebottom10EUMemberStates.Inrealterms,between2007and2013therehasbeenonlyasmallincreaseof1.4%inabsoluteexpenditureoneducation,howevertherehasbeenadropof7.8%between2013and2014–thesecondhighestdropintheEU.Alargeproportionofgovernmentexpenditureonschoolsgoesonstaffsalaries.(EducationandTrainingMonitor2016–Croatia).

DespitetheInternationalStandardClassificationofEducation(2011),(dividingthebasicsystemofeducationintopre-primary,primary,lowersecondary,anduppersecondary),theCroatianpre-tertiaryeducationstickstotheoldschemewhichremainedunchangedformorethanfiftyyears.Themaindifferenceincomparisonwithothercountriesisashorterprimaryeducation(ISCEDlevel1).Theoveralleducationalsystemisdividedintothefollowingsegments:pre-schooleducation,elementaryschooleducation,secondaryschooleducation,highereducationandadulteducation.In


14

Table1thekeyindicatorsabouttheCroatianeducationsystem(year2012and2015)arepresentedandcomparedwiththeEUaverage.

Table1:KeyindicatorsofCroatianeducationsystemcompared,source:EducationandTrainingMonitor2016–Countryanalysis Croatia EUaverage

2012 2015 2012 2015ET2020benchmarks

Earlyleaversfromeducationandtraining(age18-24)

Total 5.1% 2.8% 12.7% 11.0%

Tertiaryeducationalattainment

Total 23.1% 30.9% 36.0% 38.7%

Earlychildhoodeducationandcare(ECEC)(fromage4tostartingageofcompulsoryeducation)

71.0% 72.4% 93.2% 94.3%

Proportionof15year-oldswithunderachievementin:

Reading 18.7% : 17.8% :

Maths 29.9% : 22.1% : Science 17.3% : 16.6% :Employmentrateofrecentgraduatesbyeducationalattainment(age20-34havinglefteducation1-3yearsbeforereferenceyear)

ISCED3-8(total) 60.2% 62.6% 75.9% 76.9%

Adultparticipationinlifelonglearning(age25-64)

ISCED0-8(total) 3.3% 3.1% 9.2% 10.7%

Othercontextualindicators

Educationinvestment PublicexpenditureoneducationasapercentageofGDP

4.9% 4.7% 5.0% 4.9%

Tertiaryeducationalattainment(age30-34)

Native-born 23.2% 31.7% 36.7% 39.4%

Foreign-born 21.7% 23.6% 33.8% 36.4%Employmentrateofrecentgraduatesbyeducationalattainment(age20-34havinglefteducation1-3yearsbeforereferenceyear)

ISCED3-4 54.2% 45.0% 69.7% 70.8%

ISCED5-8 65.9% 76.2% 81.5% 81.9%Learningmobility Inboundgraduates

mobility(bachelor)0.2% 0.2% 5.5% 5.9%

Inboundgraduatesmobility(master)

0.5% 0.5% 13.6% 13.9%

Eventhoughpre-schooleducationinCroatiaisnotcompulsory,itrepresentsthebeginningpart

oftheeducationalsystem.Pre-schooleducationcanstartwhenthechildbecomessixmonthsold,but,intheexistingpractice,childrenenterpre-schoolinstitutionswhentheyareoneyearold.The


15

participationrateinearlychildhoodeducationandcare(fromage4tothestartingageofcompulsoryeducation)hassteadilyincreasedoverthelastdecadebutisstilloneofthelowestintheEU,at72.4%comparedtotheEUaverageof94.3%in2014.

ElementaryschooleducationinCroatiaisprovidedthroughthenetworkofpublicandprivateelementaryschools.Elementaryschooling,lastingeightyears,isthecompulsorypartofeducationintheRepublicofCroatiaforchildrenbetweentheagesofsevenandfifteen,andcorrespondstotheISCEDlevels1and2.In2014/15therewereapproximately850elementaryschoolswith321,000pupils,and31,800teachers(CroatianBureauofStatistics).Inthe2014/15schoolyear,therewere707secondaryschoolsinCroatia.

Oneindicatorofthequalityofdevelopmentofpupilcompetencesattheendofcompulsoryeducationaretheresultsininternationalcomparativeresearch.CroatiahasbeenparticipatingintheOECDProgrammeforInternationalStudentAssessment–PISAsince2006.TheCroatianPISAresults,incomparisonwithotherEUcountries,areunsatisfactory.Forexample,in2012,29.9%ofstudentsinCroatiafailedtoachievebasicskillsinmathematicscomparedtotheEU-25averageof22.1%(OECD2013).Inreadingandscience,CroatiawasaroundtheEUaverage(OECD2013).

Afterthecompletionofcompulsoryelementaryschoolmorethan95%ofstudentscontinuetheireducationinsecondaryschools(correspondingtotheISCED3level)althoughsecondaryeducationisnotcompulsory.Intheschoolyear2014/15therewere707secondaryschoolsinCroatia,with175,512studentsand26,138teachers(CroatianBureauofStatistics).

Themaincharacteristicofsecondaryeducationisstreaminginthreedirections:academic(gymnasium),vocationalschoolsandartschools.Whileacademic(gymnasium)andartschoolsarefour-yearsecondaryschools,therearetwotypesofvocationalschools,thefour-yearandthethree-yearvocationalschools.Roughly,70%ofthesecondaryschoolpopulationattendvocationalschools,ofwhomabout44%areinthefour-yearprogrammesandtheremaining26%areinthethree-yearprogrammes(Domović&VizekVidović,2015).Thelevelofparticipationinvocationaleducationandtraining(VET)atuppersecondarylevelinCroatiaisoneofthehighestintheEU—71.3%,comparedtotheEUaverageof48.3%in2015.However,theemploymentrateforrecentuppersecondarygraduates(peopleaged20–34wholeftuppersecondaryeducationbetweenoneandthreeyearsbeforethereferenceyear)46.1%in2014,issignificantlybelowtheEUaverageof73%andisthethirdlowestpercentageinEuropeafterItalyandGreece.TheemploymentgapbetweenyouthwithuppersecondaryandtertiaryeducationismoresignificantthaninotherEUcountries,especially1-3yearsaftergainingaqualification.ArelativelysmallproportionofVETgraduatesfindtheirfirstemployment


16

intheoccupationthattheytrainedfor.Onaverage,between37%and47%managetodoso,whereassomesectorsstandoutaslesschallengingforfindingmatchingemployment,suchastheretailsector,hospitalityandtourismandwoodprocessing(EducationandTrainingMonitor2016–Croatia,p.7).

OneofthestrengthsoftheCroatianeducationalsystemisthelowestearlyschoolleavingrateinEU(2.8%)in2015,comparedtotheEUaverageof11%.

ItshouldbenotedthatthedepopulationtrendinCroatiahasasignificantimpactonthecontinuousdecreaseofthenumberofpupilsandstudentsinCroatia.Inprimaryschools,attheendofthe2014/2015schoolyeartheoverallnumberofstudentswas1.3%lowerandinsecondaryschools2%lowerthantheyearbefore.Thetrendtowardsshrinkingstudentpopulationscontinuedintheschoolyear2015/2016when1%fewerprimaryand4.5%fewersecondarystudentsenrolled.Thenumberofstudentsenteringhighereducationalsoexperiencedasignificantdropin2014/2015when,afteraperiodoffairlyconstantexpansion,3,000fewerpeopleenrolledinhighereducationthaninthepreviousyear(NationalStatisticsOffice,2015).

TertiaryeducationinCroatiaisbasedonthebinarysystemanditcanbeacquiredattheuniversityandprofessionalhighereducationinstitutions.Mostofthetotalnumberofstudentsstudyatpublichighereducationinstitutions(Figure5).Higherprofessionalschoolsandpolytechnicsofferinghighereducationarenotapartoftheuniversitysystem.TheyofferspecialistprofessionalprogrammesandrelevantdiplomasbutdonotprovideprogrammesleadingdirectlytoPh.D.


17

Figure5:Trendsinenrolmentsinacademicvs.professionalhighereducation

Source:EducationandTrainingMonitor,2016–CountryAnalysis

TertiaryeducationalattainmentinCroatiahasformanyyearsbeenonagenerallyupward

trend.Theproportionof30-34-year-oldswithtertiaryeducationinCroatiain2015returnedto30.9%afterasurgeto32.2%in2014.ComparedtotheEUaverageof38.7%,thisisarelativelylowpercentage,butitisapproachingCroatia'sEurope2020targetof35%.MorethantheirpeersinotherEUcountries,studentsinCroatiamainlychoosetostudysocialsciencesandhumanities.Thisisespeciallythecaseforeconomics,businessandlawdegrees,whicharestudiedby41%inCroatiacomparedto34%intheEU.Inthepast5years,therehasbeenaslowbutsteadyincreaseintheproportionofstudentsstudyinginuniversities(Figure5)asopposedtopolytechnicsorschoolsofprofessionalhighereducation.Therehasalsobeenasteadyincreaseintheproportionofstudentspursuingacademicdegreesandaslowdropintheproportionofthosepursuingprofessionaldegrees(EducationandTrainingMonitor2016–Countryanalysis).

TheemploymentratesoftertiarygraduatesinCroatiahavenotrecoveredtothepre-crisislevels.In2008,86.3%oftertiaryeducatedgraduatesfoundemploymentwithin1-3yearsofgraduation

0%

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18

whilein2015thisnumberwasstillaslowas76.2%.ThisfigureputsCroatiaamongthesixworstperformersintheEU,afterGreece,Italy,Spain,CyprusandPortugal.

ParticipationinadulteducationinCroatiaislowcomparedtootherEUcountries.Forexample,in2015,only3.1%ofCroatianadultsparticipatedineducationandtraining,comparedtotheEUaverageof10.7%(EducationandTrainingMonitor2015–Countryanalysis).TheCroatianNEETrate,measuringthepercentageofyoungpeopleaged15-29outofeducationandnotemployed,wasincreasingsince2008to2014(from13%in2008to21.8%in2014).In2016,theNEETratehasslightlydecreased(19,5%)comparedtopreviousyears.However,theNEETrateinCroatiaisconstantlymuchhighercomparedtotheEU28average(14,20%in2016).Figure6:NEETratesforgroupage15-29inCroatiaandEU28

Source:EUROSTAT

TheFigure7sumsupthestrongpointsandweakpointsoftheCroatiansystemofeducationincomparisonwiththeEuropeanaverageandEuropeangoalsfor2020.

0.0

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Croa2a EU28


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Figure7:Positioninrelationtostrongest(outerring)andweakestperformers(centre)Source:EducationandTrainingMonitor2016

Table2showsdataontheavailableeducationalinstitutionsinCroatiaandthetwocounties,includingthestructureofpopulationaged20-29accordingtothelevelofeducation.Table2:Schoolsin2015/2016schoolyearandpopulationaged20-29accordingtohighestlevelofcompletededucation,source:CroatianBureauofStatistics,2016Schoolsin2015/2016schoolyear

CroatiaIstriaCounty

Osijek-Baranja

County

Primaryschools 2,125 105 187Uppersecondaryschools 751 44 52Facultiesandhighschools 104 2 13Populationaged20-29accordingtohighestlevelofcompletededucation

Totalpopulation(20-29,2011)550,724

(100%)26.569(100%) 40.762(100%)

Noschooling 2,352(0.43%) 61(0.23%) 168(0.41%)1-3gradesofbasiceducation 586(0.11%) 22(0.08%) 58(0.14%)4-7gradesofbasiceducation 2,502(0.45%) 103(0.39%) 273(0.67%)


20

Elementaryeducation 27,831(5.05%) 1,499(5.64%) 2,486(6.10%)

Secondaryeducation 415,729(75.49%)

20,356(76.61%) 31,776(77.95%)

Highereducation 1010,385(18.41%) 4,521(17.2%) 5,991(14.70%)

DatapresentedinTable2leadtotheconclusionthatIstriaCounty,despitethesignificantly

lowernumberofeducationalinstitutions,standsoutintermsofafavorableeducationalstructureofyouthwhichisreflectedinthebelow-averagerepresentationofpersonswithalowlevelofeducation.Ontheotherhand,inOsijek-BaranjaCountyweencounteranabove-averageproportionofyouthwhohavenotcompletedsecondaryeducationandasmallproportionofhighlyeducatedpersons,despitetherelativelyfavorablenumberofavailableinstitutionsofhighereducation.

5. YouthandtheLabourMarket

In2015,Croatiainvestedinlabourmarketpoliciesanamountofresourceswhichwasequaltoonly0.6%ofitsGDP.Asmuchas49%ofthatamountwasdirectedintoLMPmeasures.ThemainfocusofCroatianLMPmeasuresistraining(60%),andapproximatelythesameamountgoestotheemploymentincentives(15%)anddirectjobcreation(16%).Around7%ofCroatiansinvestmentinLMPmeasuresgoestostart-upinitiatives.

RegardingparticipationintheCroatianlabourmarket,theoveralleconomicactivityratefrompeopleage15-65hasshownaslowgrowthinthelasttenyears,from63.3%in2005to66.9%inyear2015.ThatisbelowtheEU27average(72.6%).Ontheotherhand,theeconomicactivityrateofyouth(age15-24)hasdecreasedinthelasttenyears,from38.1%in2005to33.2%in2015,thatis8.3percentagepointslowerthantheEU27average.Economicactiveyouthinthelabourmarketshowsagreatgendergap,with28%activefemales,and38%activemales.Theemploymentrateshowstheproportionoftheworkingagepopulationthatisinemployment.InCroatia,theoverallemploymentrate–forpersonsaged20-64was60.5%in2015,thelowestamongallEU-28MemberStatesand9.6%belowtheEU-27average(Figure8).Overallemploymentofpersonsaged20-64inAdriaticCroatiais59.5%andinContinentalCroatia61%.AccordingtoastatisticalportraitofCroatiaintheEuropeanUnion(CroatianBureauforStatistics,2013),theCroatianemploymentrateforthepopulationaged20-64hadincreasedto62.9%by2008,butduringthefinancial,economicandpublicdebtcrisis,itdecreasedeachyearfrom2009to2012.OneoftheEurope2020targetsisthat,by2020,75%ofpersonsaged20-64intheEUshouldbeinemployment;forCroatiathetargetis59%.Thegendergap


21

intheCroatianemploymentratewas9.4percentagepoints,withtherateofmalesat65.2%in2015andthatforfemalesat55.8%.In2012,thegendergapwas8.9%,whichshowsthatthegapincreasedthroughthelastthreeyears.ThegapissignificantlysmallerinAdriaticCroatia(6.9%)thaninContinentalCroatia(11%).Theemploymentofyouthinthe15-24agegroupin2015was19%,thatis,14.1percentagepointsbelowtheEU27average.Again,theemploymentisalittlebithigherinContinentalCroatia(19.3%)thaninAdriaticCroatia(18.3%).Thegapbetweenmalesandfemales(6.6%)existeveninthisagegroup,anditisagainlowerinAdriaticCroatia(5.3%),thaninContinentalCroatia(7.2%).Figure8:Youthemploymentandunemploymentrates,youthunemploymentratioofyoungpeople15-24(rightex),EU27,Croatia,AdriaticCroatiaandContinentalCroatia

Source:EUROSTAT

Thegeneralbusinesscyclehasasignificantimpactonunemploymentlevels,andtheimpactof

thefinancial,economicandpublicdebtcrisiscanbeseenintherecentdevelopmentsofunemploymentstatisticsinmostEUMemberStates.TheunemploymentrateinCroatiarosefromapre-crisislowof8.4%in2008to15.9%by2012,whileintheEU27itrosefrom7.1%to10.5%overthesameperiod.In

0

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40

60

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015EU27unemploymentCroa2aunemploymentJadranskaHrvatskaunemploymentKon2nentalnaHrvatskaunemployment


22

2015theunemploymentrateinCroatiawas15.6%,whichis6.2%higherthantheEU28average(9.4%).UnemploymentisalittlebithigherinAdriaticCroatia(16.3%)thaninContinentalCroatia(15.3%).Thisinformationis,onceagain,contradictorywithinformationabouttheunemploymentrateinthetwofunctionalregions–Osijek-BaranjaCountyandIstriaCounty.Intheyear2015,theunemploymentrateintheOsijek-Baranjafunctionalregionwas28.3%,thatis,13%higherthantheunemploymentrateinitsNUTS2region,ContinentalCroatia(15.3%).Inthesameyear,inIstriafunctionalregiontheunemploymentratewasonly6.1%,whichisremarkablyundertheaverageofCroatia(for9.5%),aswellasIstriaNUTS2region,AdriaticCroatia(for10.2%).Thegendergapinunemploymentofpeopleage20-64issignificantlylowerthaninemployment(just1.3%).Evenhere,thegendergapishigherinContinentalCroatia(1.7%)thaninAdriaticCroatia(0.4%).

CroatiaisoneofthethreeEU28membercountrieswiththehighestyouthunemployment(groupage15-24).Withahigh43%,Croatiais22.6percentagepointsawayfromtheEU28average.YouthunemploymentishighinbothContinental(42.2%)andAdriaticCroatia(44.7%).Again,femaleyouth,age15-24aremoreunemployedthantheirmalepeers(for2.9%).AccordingtothestatisticsoftheCroatianEmploymentService,from24,549unemployedpeopleinOsijek-BaranjaCounty,23.3%areyoungadults,age20-29,and3%areyouthage15-19.IntheIstriafunctionalregion,atthemomentthereare2,949unemployedpersons,outofwhich20%areyoungadults(age20-29),and2%belongtotheagegroup15-19.Theyouth(agegroup15-24)unemploymentratioinCroatiawas14%,whichisveryhighaccordingtotheEU27average(8.4%)in2015.Oftheoverallunemployedpopulation,theratioofyoungadults(age20-29)was17.9%in2015.

IncomparingallthosepercentageswiththeEU27orEU28average,itisobviousthatCroatiaisacountrywithhighunemploymentratesofallpopulation,butalsoofyoungadults.Thereis15.3%ofthoseunemployedyoungpeople(age15-29)thathavebeenunemployedforoneyearormore.ThatpercentageissameinCroatia,aswellasinbothNUTS2functionalregions.Thepercentageoflong-termunemployedofCroatia’sentireunemployedpopulationisashighas63.1%,thatisthehighestpercentageofallEU28membercountries.InContinentalCroatiathispercentageis63.7%,andinAdriaticCroatia61.9%.BylookingmoredeeplyintotheOsijek-Baranjafunctionalregion,14.9%unemployedpersonsareunemployedfrom6-12months,14%areunemployedfrom1-2years,andahighpercentageof17.3%ofpeopleareunemployedfor5andmoreyears.IntheIstriafunctionalregion,50%ofthoseunemployedareunemployedforonly6months,18%areunemployedfrom6-12months,from1-2yearsunemployedis10%ofallunemployed,and13%areunemployedformorethan5years.Thedistributionofthetermofunemploymentofunemployedyoungadults(age20-29)inthe


23

Osijek-BaranjaandIstriaRegion(Figure9)indicatesthatyoungadultsintheOsijek-Baranjafunctionalregionaremoreatriskoflong-termunemployment.Inthatcounty,20%ofyoungonly6.2%.Thepercentageofunemployedpersonsfromtheagegroup20-29,thatareunemployedformorethan3yearsis8.7%inOsijek-BaranjaCounty,and4.8%inIstriaCounty.

Figure9:Distributionoftermofunemploymentofunemployedyoungadults(age20-29)inOsijek-BaranjaandIstriaRegion

Source:CroatianBureauofStatistics,2016

ThekeyissuesfacedbyyoungpeoplewhenenteringthelabourmarketinCroatiaarelackof

previousworkexperienceandmismatchbetweentheirqualificationsandtheskilldemand.Theseproblemsareinparticularevidentincasesofindividualswithlowereducationalattainment,youngmothersandRomapopulation.Long-termunemploymentandlargedifferencesinregionalyouthunemploymentratesarealsorecognized.About17%ofallregisteredyouthunemployedarewithoutpriorworkingexperience,about34%oflong-termunemployedyoungpeoplehavenohighschooleducation,and28%haveathree-yearcourseofvocationaleducation,andonly13%arehighlyeducated(NationalYouthProgramme2014-2017).

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0-6months 6-12months 1-3years 3-5years morethen5years

Termofunemployment,age20-29

Osijek-BaranjaCounty IstriaCounty


24

6. Redistributionandsocialinclusion

Socialprotectionincludesallinterventionsofpublicorprivatebodiesaimedatalleviatingthefinancialburdenofhouseholdsandindividualsfromadefinedseriesofrisksandneeds,providedthatthereisnosimultaneousreciprocalorindividualcounterperformance(aninterventionthatseekssomethingofidenticalvalueinreturnfromthebeneficiaryofsocialprotection).Croatiamaintainsacomprehensiveandcomplexsystemofsocialprotection.Thesystemservesmultipleobjectivesandincludessupporttowarveteransandtheirfamilies,populationpolicymeasures,socialassistancetolow-incomegroups,andalargenumberofothersocialassistanceprograms.Theadministrationofsocialbenefitsishighlyfragmented,withinsufficientcoordinationamongthedifferentlevelsofgovernmentprovidingtheseservices(Jafarov&Gunnarsson,2008).

AkeysocialpolicyissueinCroatiaishowtoreducethegovernment-spending-to-GDPratio,withoutunduesacrificesinquality,eventhoughCroatiaspendsmuchlessonsocialprotectionthantheEuropeanUnionaverage(Figure10).ComparingdataontheshareofsocialprotectionexpendituresinthenationalGDPwiththeshareofsuchexpendituresintheGDPofEUmembercountries,theRepublicofCroatiaranks18th,laggingby8.6percentagepointsbehindtheaverageoftheEU-28.Figure10:Socialprotectionbenefits(%oftheGDP)

24.8

27.5 27.4 27.2 27.6 27.8 27.6

18

20.2 20.3 20.2 20.7 21.5 21.2

0

5

10

15

20

25

30

2007 2008 2009 2010 2011 2012 2013 2014 2015

EU(28) Croa2a


25

Source:EUROSTAT:Tablesbyfunctions,aggregatedbenefitsandgroupedschemes

AccordingtotheSocialwelfareAct3,TheGovernmentofCroatiaisthemainsourceofthesocialbenefitsofpersonsthatareatriskofpoverty,liveinseverematerialdeprivationorliveinhouseholdswithalowworkintensity.Thesocialinsuranceandsocialassistancecomponentofsocialwelfarepolicyitselfconsistsofthreecomponents.Therearecashtransfers,benefitsinkindandfoster-careorresidentialcareforvulnerablegroups(Bejaković&McAluey,1999).Inhabitantsinbothfunctionalregionshavetherighttothesamesocialbenefits,butdifferencesarisefromthenumberofpeoplewhoareinneedofsocialprotection(Figure11).

Figure11:At-risk-of-povertyratebyNUTS2andNUTS3(%)

Source:CroatianBureauofStatistics,Census2011

ThedatapresentedinFigure11showthatOsijek-BaranjaCountyischaracterisedwitha

significantlyhigherrateofpeopleatriskofsocialexclusionthanitisthecasewithIstriaCounty.

3OfficialGazette,157/13;152/14;99/15;52/16

20

17.4

28

11.9

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Con2nentalCroa2a

Adria2cCroa2a

Osijek-BaranjaCounty

IstriaCounty


26

Althoughthepercentageofpersonswhoshouldreceivesocialassistanceis28%,only5%ofthepopulationexercisethisright.InIstriaCounty,0.7%ofthepopulationreceivefinancialhelp,andeverytwelfthpersonisatriskofpoverty(Annualstatisticalreportonappliedrightsofsocialwelfare,legalprotectionofchildren,youth,marriage,familiesandpersonsdeprivedoflegalcapacity,andprotectionof

physicallyandmentallyhandicappedpersonsintheRepublicofCroatia).Thus,inbothfunctionalregionsthereisanimbalancebetweentheneedtoimprovelivingconditionsforpartofthepopulationandthepossibilitiesforthewelfaresystemtocontributetoitadequately.

Unfortunately,thedataonsocialprovisionsinCroatiaarenotkeptaccordingtobeneficiary’sage.However,dataaboutyoungpeopleatriskofpovertyorexclusionrateintheEuropeanUnionandinCroatiashowthatlivingconditionsforyoungpeopleinCroatiahaveatendencytobesimilartotheEuropeanaverage(Figure12).HavinginmindthatthisaverageistheresultofmanydifferentEuropeancountries(thelowestrateofsocialexclusionisaround10%),itispossibletoconcludethatCroatiabelongstothecountrieswithahigherlevelofyouthatriskofsocialexclusion.

Figure12:Youngpeopleatrisk-of-povertyorexclusionrateandseverematerialdeprivationrate(age16-29,%)

Source:EUROSTAT

25.8 26.628.1 28.1

29.631.6

29.427.4

9.5 9.711.1 10.8

14.9 15.8 15.112.5

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35

2010 2011 2012 2013

EU(28)-Risk-of-povertyrate

Croa2a-Risk-of-povertyrate

EU(28)-Severematerialdepriva2onrate

Croa2a-Severematerialdepriva2onrate


27

Itiswellknownthatyoungpeoplearegenerallyinanunfavourablesocioeconomicpositionin

comparisontootheragegroups.Thatmeansthatyouthdonotownproperty(realestate,savingsandstocks),theyhavedifficultiesinfindingemploymentandobtaininghousing,andaredependentontheirparents’support.Transitionalprocessesincreasethedegreeofuncertaintyforyoungpersonswho,havingcompletedtheireducation,havenoclearperspectivesontheopportunitiesforemployment,professionaldevelopmentandleadingindependentandproductivelives.TheGiniindexmeasurestheextenttowhichthedistributionofincome(or,insomecases,consumptionexpenditure)amongindividualsorhouseholdswithinaneconomydeviatesfromaperfectlyequaldistribution.ThusaGiniindexof0representsperfectequality,whileanindexof100impliesperfectinequality.TheGiniindexinCroatiahasnotsignificantlychangedinthelastsixyearsandisequaltotheGiniindexoftheEU28average(Figure13).Nevertheless,itcanbeobservedthattheGiniindexinCroatiahasatendencyofmilddecline,whereastheaverageGiniindexinthe28EUstatesshowsamildincrease.

Figure13:Giniindexofequaliseddisposableincome

Source:EUSILCsurvey,EUROSTAT

30.5

30.8

30.5 30.5

30.931

31.6

31.2

30.9 30.9

30.2

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30

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30.6

30.8

31

31.2

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31.8

2009 2010 2011 2012 2013 2014 2015 2016

EU(28) Croa2a


28

DespitethefactthatdataaboutexposuretopovertyandmaterialdeprivationofyouthinCroatiaarecomparabletotheaveragedatafortheEuropeanUnion,thematerialdeprivationrateforthetotalpopulationisnotinfavourofCroatia.DatashowthatthisratioinrelationtotheEU(28)ismultipletimeshigher,whichpointstoasignificantlyunfavourablelivingconditionsforyoungpeopleinCroatia(Figure14).

Figure14:MaterialDeprivationRate

Source:EUSILCsurvey,EUROSTAT

Finally,thequantitativeanalysisinthefieldofredistributionandsocialinclusionofyoung

adultsinCroatiashowsthatsomeeffortshouldbeinvestedinimprovingthequality,rangeandfrequencyofsocialstatistics.Suchinformationisrequiredforsocialplanning,fortheformulationofappropriatepoliciesconcerningyoungpeople.Thiscanbededucedfromtheunavailabilityofdataaboutsocialpolicies,whichareinCroatia,andsointhetwofunctionalregions,directedtoyoungpeople,andfromthedifficultiesincomparingdataformdifferentsources.

Nevertheless,itisevidentthatyouthinCroatiadonotgetsufficientsocialsupportintheprocessoftransitionfromchildhoodtoadulthood,whichcanbeseenfromthenumberofpersons

17.8 18.519.7 19.5 18.5

17

32.234.7 35.6

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receivingsocialsupportinthetwofunctionalregions.Ithasbeenestablishedthattherateofmaterialdeprivationforthetotalpopulationishigherinrelationtothegroupofyouthaged16-29,afactwhichisparticularlydisturbing.

7. Healthandwell-beingconditions

TheConstitutionoftheRepublicofCroatiaguaranteeseveryonetherighttohealthcareinaccordancewithlaw,andthatrightisexercisedthroughthehealthcaresystem,whichfallswithintheresponsibilityoftheMinistryofHealth.ThehealthcaresystemincludeshealthcareserviceofinteresttotheRepublicofCroatia,whichisbeingperformedasapublicservicebasedonprofessionalmedicaldoctrineandwiththeuseofmedicaltechnologyintheprovisionofhealthcare(NationalHealthCareStrategy,2012).ThehealthcareofthepopulationoftheRepublicofCroatiaisimplementedaccordingtotheprinciplesofuniversality,continuity,availability,acomprehensiveapproachintheprimaryhealthcare,andspecialisedapproachinspecialist-consiliaryandhospitalhealthcare.ThebasiclegalframeworkofthehealthcaresysteminCroatiaconsistsofthreekeyacts:TheHealthCareAct,theMandatoryHealthInsuranceActandthePatient’sRightsProtectionAct.Eventhoughthehealthcareisinprinciplefreeofcharge,thepatientsmustpayfromtheirownpocketstotheprivatelyownedhealthcareserviceproviders.ItincludespatientswhodonothaveacontractualrelationshipwiththeCroatianInstituteforHealthInsuranceandpatientswhodonothaveadditionalhealthinsurance.However,themainsourceofthehealthprotectionofallthepopulationisthenationalbudget.

CroatiaisamongthecountriesinEuropewiththehighestmortalityratesofcerebrovasculardiseases,trachea,bronchusandlungcancerinmen,anddiabetes.Thetrendofincreasingmortalityofwomenbysometypesofneoplasmsisespeciallydisturbing,aswellasthemortalityratecausedbydiabetes,whichisamongthehighestinEurope(NationalHealthCareStrategy,2012).

InCroatia,onaveragethereare1.4hospitalsper100,000inhabitants.Manysignificantdifferencesareobservedinthequalityofhealthserviceandprotectionwithrespecttocounties.Therearesignificantdifferencesinthecoveragebyprimaryhealthofficers,doctors,andthenumberofteamsofgeneralpractitionersandinthenumberofhospitalbedsper1,000inhabitants.(RegionalDevelopmentStrategyoftheRepublicofCroatia–2020,2016),butinthetwofunctionalCroatianregionstheyarenotparticularlyapparent.Although,overtime,thereisanobservedincreaseinthenumberofmedicalstaffinCroatia,theirrepresentationincomparisontoEUcountriesiscontinuouslylower(Figure15).Moreover,significantnumbersofCroatianhealthprofessionalsconsidermovingto


30

otherEUcountries,becauseofthesignificantlylowerearningsandcareeropportunitiesforhealthcareworkersinCroatia.

Figure15:Medicaldoctors:Healthpersonnel(perhundredthousandinhabitants)

Source:EUROSTAT

Itiswellknownthatinthepathologyofyoungpersons,anincreasinglysignificantplaceis

beingoccupiedbydisordersanddiseasesconnectedwithcertainkindsofbehaviour,habitsandlifestyles.Croatianresearchersofyouth(Ilišinetal.,2013;Bouillet,2017)indicateaworryingleveloftolerancetowardsalcoholuseinCroatiansociety,andofshortcomingsinpreparednessofyoungpeopleforresponsiblesexualbehaviour.

Oneoftheindicatorsofthenation’sstateofhealthistheportionofpersonswithadisabilityintheentirepopulation.AccordingtotheCroatianRegistryofPersonswithDisability(2017),thereare511,850personswithdisabilityinCroatia,whichisabout12%ofthetotalpopulation.Themostcommonconditionscausingdisabilityareimpairmentsofthelocomotorsystem,mentaldisorders,impairmentsofotherorgansandbodysystemsandimpairmentsofthecentralnervoussystem.Inthe

346.44350.49

354.58 355.52

299.18303.35

314.02319.15

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EU(28) Croa2a


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majorityoftheanalysedagegroups,morepersonswithaphysicaldisabilityarerecordedinOsijek-BaranjaCountyincomparisontoIstriaCounty,andwiththeincreaseinagethereisanincreaseinthenumberofpersonswithphysicaldisability(Figure16).Figure16:Prevalenceoftheratioofpersonswithadisabilityinthetotalpopulationoffunctionalregions

Source:CroatianInstituteofPublicHealth,2017

Thedeterminationofhealthasastateofcompletephysical,mentalandsocialwell-beingis

relatedtotheresearchofsubjectiveevaluationsofhealth.Suchresearchconfirmsthattheevaluationsofsubjectivewell-beingare,forthemajoritypart,linkedwiththepersonalevaluationofhealth(Miljković,2013),wherewell-beingcontributestothesubjectiveexperienceofminorrepresentationofphysicalsymptomsandbetterevaluationofhealth,whilepositivefeelingslessentheriskofillness(Marčinko,2013).Atthesametime,researchsuggeststhateverypersontriestofindawaytoevaluatetheirhealthconditioninapositivelightandthatsubjectiveevaluationofhealthcanbeinterpretedasapredictorofthephysician’sevaluation,althoughthetwoevaluationscanbeindiscrepancy(Tucak&Nekić,2006).

6.4

3.54.8

14.9

10.5

3.5

9.6

23.3

11.9

4.4

9.3

30.3

0

5

10

15

20

25

30

35

Total 0-19 20-64 65+

IstriaCounty Osijek-BaranjaCounty Croa2a


32

TheaverageratingofsatisfactionbydifferentlifedomainsinCroatiaisnotsignificantlydifferentincomparisonwiththeEuropeanUnionaverageinthefieldofjobsatisfaction,commutingtime,timeuse,personalrelationshipsandmeaningoflife.Thedifferencesarehigherinthefieldofsatisfactionwithfinancialsituation,overalllife,recreationalandgreenareasandlivingenvironment(Figure17).Inthesefields,CroatianpeoplearelesssatisfiedthantheaverageEuropeancitizen.ItispossibletoconcludethatcitizensinCroatiaarerelativelycontentwiththeprivateaspectsoflifewhiletheirdissatisfactionisexpressedinrelationtothesocialconditionsinwhichtheyareliving.Figure17:Averageratingofsatisfactionbydifferentlifedomain(rating:0-10,age:16yearsandover,2013)

Source:EUROSTAT,EU-SILCmicrodata

Overall,thebestaspectofhealthcareinCroatiaisthebroadnesswhichencompassesthe

populationwithfreehealthcareincludingpersonsintheregularsystemofeducationandpersonswithlowincome.However,theavailabilityofhealthservicesisnotuniforminallregionsofCroatiaanditissignificantlyweakerinrelationtootherEUcountries.SmalleravailabilityofhealthcareisaccompaniedwiththerelativelypoorhealthimageofCroatiancitizens.

6

7.57.1 7.4

6.77.1 7.1 7.3

7.87.4

4.6

6.9 7 7.26.6 6.3

5.86.3

7.3 7

0

1

2

3

4

5

6

7

8

9

EU(28) Croa2a


33

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3-4,73-82.


1

Work Package 4


Finland – National Briefing Paper with national and regional

data sets

Heikki Silvennoinen Anna L. Eskola Tero Järvinen Risto Rinne

Jenni Tikkanen

Centre for Research on Lifelong Learning and Education CELE University of Turku

12.09.2017 Work Package 4 – Quantitative Analysis of Young Adults’ Data Deliverable 4.1


2

TableofContentsExecutiveSummary.........................................................................................................................................................4Introduction........................................................................................................................................................................5Qualitydataassessment...............................................................................................................................................61. Findings........................................................................................................................................................................71.1 Demographicstructure.................................................................................................................................71.2 Generalstateoftheeconomy..................................................................................................................121.3 Educationandtrainingsystem...............................................................................................................141.4 Labourmarket................................................................................................................................................211.5 Redistributionandsocialinclusion......................................................................................................251.6 Healthandwell-being.................................................................................................................................27

2. Concludingremarks...........................................................................................................................................293. References...............................................................................................................................................................31

TableofFiguresFigure1.DescriptionofNUTSlevelsandtheirrelationstoeachotherinFinland................................6

Figure2.Theshareof20-24yearoldand25-29yearoldpopulationinFinland,Southwest

FinlandandNorth&EastFinland(%)..............................................................................................................8

Figure3.Populationincreasebymonth2014-2017...........................................................................................8

Figure4.Cruderateofnetmigrationplusstatisticaladjustmentyears2005-2015,Finland...........9

Figure5.LEFT:Olddependencyratio1stvariant(population65andovertopopulation15-64

years)(%)RIGHT:Young-agedependencyratio1stvariant(populationaged0-14to

population15-64years)(%)..............................................................................................................................10

Figure6.Numberofchildrenandyouthwithforeignoriginbyagegroup(0-4years,5-14years,

15-24years)(leftaxis),andpercentageofchildrenandyouth(0-24years)withforeign

originofthewholeagegroup(rightaxis)inFinlandin1990-2014.................................................11

Figure7.Theshareofpersonsagedunder15inthepopulationinFinland,in1940to2065(%)

.........................................................................................................................................................................................12

Figure8.GDPatcurrentmarketprices,Europerinhabitant.......................................................................13

Figure9.GDPatcurrentmarketprices,Europerinhabitantinpercentage(%)ofEU28(=100),

2006-2015..................................................................................................................................................................14

Figure10.TheshareofISCED5-8leveleducationofpopulationaged15yearsormorebygender

inFinland,FRSouthwestFinland,andFRKainuu,2007-2015(%)..................................................15

Figure11.Youngadults’(30-34yearolds)educationalattainmentbyISCEDlevelsinFinland,FR

SouthwestFinland,andFRKainuu,2005-2015.........................................................................................15


3

Figure12.Theshareoflowperformers(belowtestlevel2)andhighperformers(testlevels5

and6)inmathematicsofthe15yearolds:OECDaverageandFinland,inyears2003,2012

and2015(%)............................................................................................................................................................17

Figure13.PupilshavingleftcomprehensiveschoolwithoutaleavingcertificateinFinland,

2000-2016(%).........................................................................................................................................................18

Figure14.Discontinuationofeducationinuppersecondarygeneral,vocational,universityof

appliedsciences,anduniversityeducationinacademicyearsinFinland,from2005/2006to

2014/2015(%)........................................................................................................................................................19

Figure15.YoungpeopleneitherinemploymentnorineducationandtraininginEU27,Finland,

SouthFinland,andNorth&EastFinland,2012-2016(%)...................................................................20

Figure16.Youngpeoplenotineducationoremployment(NEET)byagegroupandgenderin

Finland,2008-2015................................................................................................................................................21

Figure17.Sharesofemployedstudentsagedatleast18ofallstudentsinFinland,2008–2015

(%).................................................................................................................................................................................22

Figure18.ThedevelopmentofnumberofpeopleinlabourforceinFinland,FRSouthwest

Finland,andFRKainuu,1991-2016(year1991=100)...........................................................................23

Figure19.EmploymentratesinFinland,FRSouthwestFinland,andFRKainuu,2005-2016(%)

.........................................................................................................................................................................................24

Figure20.UnemploymentrateinFinland,inFRSouthwestFinland,andFRKainuu1991-2016

(%).................................................................................................................................................................................25

Figure21.Thenumberoflong-termunemployed20-29yearoldsinFinland,2006-2016............26

Figure22.GINIIndexbeforeandaftertransfers,disposableincomeinthehouseholdsinPPS

(rightaxis),inEU27,Finland,SouthFinland,andNorth&EastFinland,in2005-2015..........27

Figure23.Peopleatriskofpovertyandsocialexclusion,inEU27,Finland,SouthFinland,and

North&EastFinland(plusSpainandtheU.K.),in2005-2015(%)..................................................28

Figure24.Rateofyouth(20-29years)livingwiththeirparentsbygender,EU27andFinland(%)

.........................................................................................................................................................................................29

Figure25.Highsatisfactioninvariouslifedomainsofpopulationaged25-34bygender,EU28

andFinland.................................................................................................................................................................30


4

ExecutiveSummary

TheFinnisheducationsystem,especiallythecomprehensiveschool,ischaracteristically

intertwinedwiththeScandinaviannotionofwelfarestate,whichentailsstrongemphasison

equaleducationalopportunities.AsoneofthekeyelementsoftheScandinavianwelfaremodel,

thecomprehensiveschoolsystemisidentifiedbyuniversal,non-selective,andfreebasic

educationprovidedbythepublicsector.PISAresultsfromtheearly2000’sonhaveshownthat

notonlyistheaveragelevelinreading,mathematics,andscienceshighinFinland,butalsothe

shareoflowachieversiscomparativelysmall.TheotherimportantsignisthattheFinnish

schoolsystemhasbeensuccessfulincompensatingforthepoorsocioeconomicbackgroundof

pupils.Also,thebetweenschoolvariationinlearningoutcomesisoneofthesmallestinthe

OECDworld.Theschoolsystemhasprovedtobehomogeneousinquality.Youngpeoplehave

relativelygoodeducationalopportunitiesattheuppersecondaryandtertiarylevel.However,

thereareabout10percentineachagecohortyoungpeoplewhodonotcontinueineducationor

trainingafterbasiceducation.Theirsituationisgettingworsewhilethecompetitioninthe

labourmarketgetstighter.Theotherphenomenonisthedecreasinglevelofaveragelearning

outcomestestedinPISA,TIMSS,andPIRLS.Theshareoflowperformershasbeengrowing.

Finnisheconomyhassufferedtwoseverecrisessincethe1980’s,firstintheearly1990’s

andthenasaneffectoftheglobalfinancialcrisisfrom2008onwards,whichhavehaddrastic

effectsonyouthemployment.Afterthefinancialcrisis,unemploymentforyoungpeoplehas

increased,moreheavilyformalesthanforfemales.Long-termunemploymentof20-29yearold

maleswasseventimeshigherandfemaleseighttimeshigherin2016thanin2008.Uncertain

employmentprospectshavealsodiscouragingeffectsoneducationalmotivationespeciallyof

youngpeopleinthelowendoftheachievementcurve.Incertainregionsofthecountrygettinga

jobwithoutworkexperienceandvocationaltrainingispracticallynon-existent.Thenumberof

NEETyounghasbeenslightlyincreasingduringthepastdecadeorso.Actually,youngadults

livinginthetwofunctionalregions,FRSouthwestFinlandandFRKainuu,liveinquitedifferent

realitieswhatcomestotheirfutureprospects.Peopleborninnorthernandeasternpartsofthe

countrytendtomovetosoutherncitiesaftercompletingcompulsoryoruppersecondary

education.TheoverallemploymentinFRKainuuhasdecreasedquitedramaticallywithinthe

pastdecades:thenumberofemployedinFRKainuuisonlyabout70percentofthelevelitwas

inthebeginningofthe1990’s.However,Finnishyoungpeopleareclearlymoresatisfiedwith

severalareasoftheirlifethantheirpeersinEuropeonaverage.Especiallylargedifferences

betweenFinnishyouthandEuropeanaverageareinaccommodation,jobsatisfaction,and

overalllifesatisfaction.

BeingatriskofpovertyandsocialexclusionislowerinFinlandthanitisinEU27

countriesonaverage.About17%ofthepopulationhasbeenatriskofpovertyorexclusion


5

between2005and2015.Thegapbetweendifferentpartsofthecountryhasbeengrowing

duringthepastdecade.Theriskofpovertyandsocialexclusionhasgrownbiggerespeciallyin

northernandeasternregionsofFinland.

ThenumberofchildrenborninFinlandwillbelowerthaneversincethelastfamine

years1866-68,althoughthesizeofthepopulationhasmorethandoubled.Accordingtothe

projection,theshareofpersonsagedunder15inthepopulationwoulddecreaseto14percent

by2060.Theshareofpeoplewithforeignbackgroundhasbeenverylowcomparedtoother

Europeancountries.Hostilitytowardspeoplewithforeignbackgroundhasincreasedduring

recentyearsamongnativepopulation.Thesedevelopmentswillhavesevereconsequencesfor

thedependenceratiointhefuture.

Introduction

TheFinnisheducationsystem,especiallythecomprehensiveschool,ischaracteristically

intertwinedwiththeScandinaviannotionofwelfarestate,whichentailsstrongemphasison

equaleducationalopportunities.AsoneofthekeyelementsoftheScandinavianwelfaremodel,

thecomprehensiveschoolsystemisidentifiedbyuniversal,non-selective,andfreebasic

educationprovidedbythepublicsectorandofadequatelygoodqualityinordertopreventthe

demandsforprivateschools.Togetherwiththehealthandsocialsecuritysystems,the

comprehensiveeducationformsavirtuouscirclethathascumulativepositiveeffects.Universal

educationsystemprovidesequaleducationalopportunitiesthatleadtogreatersolidarityand

universalsocialcapital,socialtrustwhichconfirmsthelegitimacyofuniversalmodels.

(Kalalahti,Silvennoinen,Varjo&Rinne2015).Thesystemhasprovedtobeproductiveinseveral

respects:Finnishyoungpeoplehaveoutstandingresultsininternationalassessmenton

learning,andqualitydifferencesbetweenschoolsarethesmallestinEurope(OECD2013;OECD

2016a).

However,thelivingconditionsandopportunitystructuresforyoungpeoplearequite

differentindifferentpartsofFinland.ThecapitalcityHelsinkiwithitsmetropolitanareoffer

muchbetteropportunitiesforeducationandemploymentthanmoreremoteareasineastern

andnorthernpartsofthecountry.OurfunctionalregionsSouthwestFinlandandKainuuare

locatedintheoppositepartsofFinlandandtheyaredefinedbyquitedifferentprospectsfor

youngpeople.Thegeneraltrendsincethe1960s’hasbeentheconcentrationofpopulationin

thesouthernpartsofthecountry(includingFRSouthwestFinland),whereasthenorthernand

easternparts(includingFRKainuu)arebecomingmoreandmoresparselypopulated.


6

Qualitydataassessment

Inthisreport,thebasicstatisticsarepresentedatNUTS2-level(‘largerareas’SouthFinlandand

North&EastFinland).However,crucialinformationatNUTS3levelisaddedsothatthe

functionalregionsSouthwestFinland(partofNUTS2area‘SouthFinland’)andKainuu(partof

NUTS2area‘North&EastFinland’)willbedescribedmoreproperly.Therearesubstantial

differencesbetweenNUTS3levelregionsincludedinthesameNUTS2levelareas.Thisconcerns

alsoourtwofunctionalregions(FR),SouthwestFinlandandKainuu.

Figure1.DescriptionofNUTSlevelsandtheirrelationstoeachotherinFinland

NUTS1 Code NUTS2 Code NUTS3 Code

MainlandFinland FI1 WestFinland FI19 CentralFinland FI193

SouthernOstrobothnia FI194

Ostrobothnia FI195

Satakunta FI196

Pirkanmaa FI197

Helsinki-Uusimaa

FI1B Helsinki-Uusimaa FI1B1

SouthFinland FI1C SouthwestFinland FI1C1

Kanta-Häme FI1C2

Päijät-Häme FI1C3

Kymenlaakso FI1C4

SouthKarelia FI1C5

North & EastFinland

FI1D Etelä-Savo FI1D1

Pohjois-Savo FI1D2

NorthKarelia FI1D3

Kainuu FI1D4

CentralOstrobothnia FI1D5

NorthernOstrobothnia FI1D6

Lapland FI1D7

Åland

FI2 Åland FI20 Åland FI200

AscanbeseeninFigure1,geographicallytheareaof‘North&EastFinland’,ofwhichtheFR

Kainuuisarathersmallregion,coversmorethanhalfofFinland.StatisticsonNUTS2area‘North

Southwest Finland

Kainuu


7

&EastFinland’donotrepresentproperlythesituationinFRKainuu.ThesameistruewithFR

SouthwestFinlandandNUTS2areaSouthFinland,withinwhichthereareinmanyrespects

quitedifferentregionsfromEasternFinland(e.g.,NUTS3regionsKymenlaaksoandSouth

Karelia).SuitabilityofNUTS2levelstatisticsindicatingtherealitiesatNUTS3level-atthelevel

ofourfunctionalregions,thatis–isdisputable.ThatiswhywetrytopresentstatisticsatNUTS3

level,fromFRSouthwestFinlandandFRKainuu,wheneveritispossible.Roughly,the

differencesbetweenFRSouthwestFinlandandFRKainuuareingeneralwiderthanNUTS2

areasSouthFinlandandNorth&EastFinland.

StatisticsFinlandcontinuouslycollectsahugeamountandvarietyofdataonpopulation,

economy,education,labourmarket,housing,etc.butstatisticsonlyonquitegenerallevelare

availablefreeofcharge.MostoftherelevantdataonNUTS3levelareaccessibleonlyforextra

costs.

Themostseriousweaknessconcerningthisbriefingpaperistheunsystematicnatureof

availabledataonlivingconditionsofagegroupsinNUTS3regions–i.e.thetwofunctional

regionsofourstudy.Somerelevantdataaregatheredbyadministrativebodiesinthetwo

functionalregions(mostlypopulation,economyandemployment),buttheylackasystematic

approachondatacollecting.

1. Findings


AccordingtoStatisticsFinland'smostrecentdata,Finland'spopulationwas5,506,312attheend

ofMay2017.Theshareof20-29yearoldsisabout12.5percentofthewholepopulation.The

percentageofyoungpeopleaged20-24inSouthFinlandislowerthanthecountryaverage,and

thepercentageofyoungaged25-29islowerthanthecountryaverageinbothexaminedareas,

SouthFinlandandNorth&EastFinland(Figure2).Inmanyregionsinnorthernandeastern

Finland,anumberofpeopleaged25-29havealreadymovedawayfromtheirchildhoodhometo

otherpartsofthecountry.

ThesedaysthebirthrateisverylowinFinland.Populationincreasedby3,015persons

duringJanuary-May2017.Thereasonfortheincreasewasmigrationgainfromabroad,since

immigrationexceededemigrationby5,684.Thenumberofbirthswas2,669lowerthanthatof

deaths(Figure3).


8

Figure2.Theshareof20-24yearoldand25-29yearoldpopulationinFinland,SouthwestFinlandandNorth&EastFinland(%)

Figure3.Populationincreasebymonth2014-2017

Source: Population Statistics, Statistics Finland DuringJanuary-May2017,20,510childrenwereborn,whichis1,613fewerthaninthe

correspondingperiodin2016.Thenumberofdeathswas23,179,whichis130lowerthanayear

earlier.AccordingtothepreliminarystatisticsforMay2017,10,908personsimmigratedto

Finlandfromabroadand5,224personsemigratedfromFinland.Thenumberofimmigrantswas

612lowerandthenumberofemigrants1,393lowerthaninthecorrespondingperiodofthe

previousyear.Intotal,2,604oftheimmigrantsand3,471oftheemigrantswereFinnishcitizens.

(PopulationStatistics,StatisticsFinland.)

Therateofnetmigrationhasbeenaboutthreepercentyearlyinthepastdecadein

Finland(Figure4).North&EastFinlandhasbeenlosingpopulationalmosteveryyearfrom

2005to2015.FrommanyregionsinNorth&EastFinlandpeopleareconstantlymovingoutto

5.2

5.4

5.6

5.8

6.0

6.2

6.4

6.6

FinlandSouthFinlandNorth&EastFinland

5.2

5.4

5.6

5.8

6.0

6.2

6.4

6.6

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016


ExcessofBirths

PopulationIncrease

NetMigration


9

thesouthernpartsofFinland,anddespitesomeimmigration,northernandeasternFinlandis

losingpopulation,especiallyyoungadultsandtheworkingagepopulation.

Figure4.Cruderateofnetmigrationplusstatisticaladjustmentyears2005-2015,Finland

Theworseningofthedependencyratioisduetotheageingofthepopulation.Theshare

ofchildren(aged0-14years)hasbeenquitesteadyandrelativetothesizeoftheworkingage

population.However,thesizeoftheelderlypopulationisgrowingfastandoldagedependency

ratiohasrisenfrom24%to32%betweenyears2005and2016.(Figure5.)InSouthFinlandas

wellasinNorth&EastFinlandtheoldagedependencyratioishigherthatthecountryaverage.

InSouthFinlandareatheratiowasnearly38%in2016,havingthusgrownmorethan10

percentagepointsintenyears’time.

AscanbeseeninFigure5,youngagedependencyratioishigherinNorth&EastFinland

thanonaverageinFinland.AtNUTS2level,theyoungagedependencyratioshavebeenquite

steadyduringtheyears2005-2016.

ThemeanageofwomenatbirthofthefirstchildisinFinlandaboutthesameasin

EuropeanUnion(28countries),28.8yearsin2015.InFinland,themeanagehasrisenalmostby

oneyearintheperiodoftenyears.InfantmortalityrateinFinlandisthelowestamongtheYA

countries:1.7in2015.Fertilityratewas1.64in2015whichisabithigherthanEU28average

(1.58in2014).FertilityrateishigherinNorth&EastFinland(1.92in2014)thaninSouth

Finland(1.66in2014)orinFinlandonaverage.LikeinEuropegenerally,inthelongrunfertility

rateshavegonedownwards.

-3.00

-2.00

-1.00

-

1.00

2.00

3.00

4.00

1 2 3 4 5 6 7 8 9 10 11

Finland SouthFinland North&EastFinland


10

Figure5.LEFT:Olddependencyratio1stvariant(population65andovertopopulation15-64years)(%)RIGHT:Young-agedependencyratio1stvariant(populationaged0-14topopulation15-64years)(%)

Actually,inyear2017,thenumberofchildrenborninFinlandwillbelowerthanever

sincethelastfamineyears1866-68,althoughthesizeofthepopulationhasmorethandoubled.

Thisdevelopmentwillhavesevereconsequencesforthedependenceratiointhefuture.The

shareofpeoplewithforeignbackgroundasbeenverylowcomparedtootherEuropean

countries.Inthissense,Finlandhasbeenanisolatedcountry.

In2014,therewereabout97000childrenandyoungpeople(agedunder25years)with

mothertongueotherthanFinnishorSwedish(Figure6).Theshareofforeignoriginintheage

group0-24yearoldswas6.3%.(StatisticsFinland.)Thebiggestpopulationswithforeign

originsareEstoniansandRussians,whichisquitenaturalasEstoniaandRussiaarethe

neighboringcountriesofFinland.

AccordingtoStatisticsFinland'slatestpopulationprojection,therewouldbe882,000

personsagedunder15inFinlandin2030.Thenumberofpersonsagedunder15haslastbeen

thislowin1894.Atthebeginningofthe1980s,oneinfiveFinnswereagedunder15.According

totheprojection,theshareofpersonsagedunder15inthepopulationwoulddecreaseto14per

centby2060.Themainreasonforthedecliningshareofyoungpeopleisalowbirthrate.

20.0

22.0

24.0

26.0

28.0

30.0

32.0

34.0

36.0

38.0

40.0FinlandSouthFinlandNorth&EastFinland

20.0

25.0

30.0

35.0

40.0

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016



11

Figure6.Numberofchildrenandyouthwithforeignoriginbyagegroup(0-4years,5-14years,15-24years)(leftaxis),andpercentageofchildrenandyouth(0-24years)withforeignoriginofthewholeagegroup(rightaxis)inFinlandin1990-2014

Source:Väestöliitto.

Thenumberofthepopulationofworkingage(aged15to64)washighestin2009,when

therewere3.55millionsuchpersonsinFinland.During2010to2014,thenumberofworking-

agepeoplehasfallenby69,000persons.Accordingtothepopulationprojectionof2015,the

numberofworking-agepeoplewoulddecreasefromthecurrent3.48millionto3.41million,or

by75,000persons,by2030.Afterthis,thenumberofworking-agepeoplewouldrecover

slightly,andby2045theywouldnumber3.46million.Then,thenumberofworking-agepeople

wouldagainstartdecliningand,accordingtotheprojection,theywouldnumber3.40millionin

2060.Theproportionofpeopleofworkingageinthepopulationwilldiminishfromthepresent

64%to59%by2030andto57%by2060.

Theso-calledself-sufficiencyforecastdescribesasituationwheretherewouldbeno

immigrationandemigrationatallandonlythebirthrateandmortalitywouldinfluencetheage

structure.Accordingtotheself-sufficiencyforecast,thenumberofworkingagepeoplewouldgo

downbytheyear2030by300,000personsandbytheyear2050by550,000persons(Figure

7).

0-4y

5-14y

15-24y

Numberofchildrenandyouthwithforeignorigin

year


12

Figure7.Theshareofpersonsagedunder15inthepopulationinFinland,in1940to2065(%)

Source:PopulationStatistics,StatisticsFinland

Theproportionofpersonsaged65oroverinthepopulationisestimatedtorisefromthe

present19.9to26percentby2030andto29percentby2060.Thedemographicdependency

ratio,thatis,thenumberofchildrenandpensionersperonehundredpersonsofworkingage,

willgoupinthenearfuture.Attheendof2014,thedemographicdependencyratiowas57.1.

Accordingtotheprojection,thelimitof60dependentswouldbereachedin2017andthatof70

dependentsby2032.In2060,thedemographicdependencyratiowouldbe76.(Statistics

Finland.)

TosummarizethefindingsondemographicchangesinFinland,andasithasbeenshown

above,younggenerationshavebeenshrinkinginsizeforsometimenowandthenumberof

elderlypeopleisgrowingfast.Youngpeopleborninperipheralregionsofthecountry(likeFR

Kainuu)tendtomovetometropolitanareaandotherregionsinsouthernFinland.Finnishfamily

policyhasfailedbadlyinraisingthefertilityrateandthenumberofchildren.Dependencyratio

isgettinghigher.Atthesametimehostilitytowardspeoplewithforeignbackgroundhas

increasedamongnativepopulation.

1.2 Generalstateoftheeconomy

Finnisheconomyhassufferedtwoseverecrisessincethe1980’s,firstintheearly1990’sand

thenasaneffectoftheglobalfinancialcrisisfrom2008onwards.Figure8reflectsthedamage

the2008globalfinancialcrisismadeonFinnisheconomy.Notonlydidgrossdomesticproduct


13

(GDP)fallduetothecrisis,butalsolabourproductivityrelativetoEUaveragedecreased

substantially.TheFinnisheconomysufferedfromthecrisisformuchlongerthandidmanyother

Westerncountries.In2016therefinallyweresomesignsofrecoverytobeseen,e.g.,GDPgrew

1.9percentrelativetoyear2015.

Figure8.GDPatcurrentmarketprices,Europerinhabitant

AsispresentedinFigure8,thefallofGDPpercapitafrom2008to2009wasmuch

steeperinFinlandthanitwasinEU28.AfterthecrisistheGDPpercapitagapbetweenEU28and

North&EastFinlandgotwider.BeforethecrisisGDPpercapitawashigherinSouthFinland

thaninEU28,butafter2010SouthFinlandhasbeenlaggingbehindEU28andthegaphaseven

grownin2015(seeFigure9).Althoughwedonothaveappropriatedataathand,itishighly

likelythatthefigureforFRSouthwestFinlandwouldlookmorepositivethanthesefiguresfor

NUTS2areSouthFinland.ProbablytheGDPpercapitainFRSouthwestFinlandwouldbehigher

thanFinlandonaverage.

100102104106108110112114116118120

20,00022,00024,00026,00028,00030,00032,00034,00036,00038,00040,000

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

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Finland SouthFinland

North&EastFinland


14

Figure9.GDPatcurrentmarketprices,Europerinhabitantinpercentage(%)ofEU28(=100),2006-2015

Tosummarizethefindingsonthestateofeconomy,itneedstobeemphasizedthat

duringthepast25yearstheeconomyofFinlandhassufferedtwodeepeconomicdepressions,

firstintheearly1990sandthenaftertheglobalfinancialcrisisafter2008.Thecriseshithardon

Finnisheconomyandhadsevereconsequencesonthegrossdomesticproduct(GDP)andlabour

productivityofthecountry,whichbothdecreasedsubstantially.Theconsequencesofthese

crisesmaterialized,e.g.,inshrinkingemploymentandincreasingunemployment.Buttheyalso

havehadahugeimpactonthementalityandsubjectivefutureprospectsofFinnishpeople.

1.3 Educationandtrainingsystem

InFinland,educationisverymuchagenderrelatedphenomenon.Thefieldsofeducationaswell

asoccupationsinworkinglifearestronglysegregatedbygender.Inschool,girlsclearly

outperfomboysinreadingandlanguages.ThemostrecentPISAassessmentshowsthatgirlsdo

betterinmathematicsandsciencesaswell(OECD2016a).Girls’bettersuccessinschoolisalso

reflectedlateroninlifebythefactthatwomenhavehighereducationalattainmentlevelthan

men:34%ofthefemalepopulationhascompletedISCED5-8levelofeducation,whereasonly

26%ofmenhaveattainedtherespectivelevelofeducation(Figure10).Theshareisaboutthe

sameinFRSouthwestFinlandasitisinFinlandonaverage.However,populationinFRKainuu

hasaremarkablylowerrateofISCED5-8educationalattainment.InKainuu27%ofwomenand

20%ofmenhaveISCED5-8leveleducation.

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Figure10.TheshareofISCED5-8leveleducationofpopulationaged15yearsormorebygenderinFinland,FRSouthwestFinland,andFRKainuu,2007-2015(%)

Youngpeoplenaturallyhaveahighereducationallevelthanthepopulationingeneral.

About85percentofthepopulationaged30-34yearshavecompletedsomepostcompulsory

education(Figure11).

Figure11.Youngadults’(30-34yearolds)educationalattainmentbyISCEDlevelsinFinland,FRSouthwestFinland,andFRKainuu,2005-2015

About40percenthavecompletedISCED5leveleducationorhigher.Thechangepatternwithin

tenyearstime,from2005to2015,lookmuchthesameinSouthwestandinFinlandonaverage.

ThereisasmalldifferenceintherelativeproportionsbetweenISCED3-4andISCED5-8levels

sothatonFRSouthwestFinlandyoungadultswithISCED3-4levelhaveincreasedtheirshareat

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16

theexpenceofyoungadultswithISCED5orhigher.Theshareof30-34yearoldswithonlybasic

leveleducation(ISCED0-2)hasincreasedinFRSouthwestFinlandandinFinlandonaverage.

TherearecleardifferencesbetweenFRSouthwestFinlandandFRKainuu:inKainuutheshare

youngadultshavingonlyISCED0-2leveleducationhasdecreasedintenyearstimeandwas

about10percentin2015.InFRSouthestFinlandtheshareofrespectivegrouphasincreased

sinceyear2008.MostyoungadultsinFRKainuuattainISCED3-4leveleducation,andthat

percentagehasincresedquiterapidly.ThegrowingpercentageofISCED3-4levelpeoplehas

comeattheexpenseofhigherlevelattainment(ISCED5orhigher).

PISAresultsfromtheearly2000’sonhaveshownthatnotonlyistheaveragelevelin

reading,mathematics,andscienceshighinFinland,butalsotheshareoflowachieversis

comparativelysmall.Thisisaveryimportantsignofanequalitarianandeffectiveschoolsystem.

TheotherimportantsignisthattheFinnishschoolsystemhasbeensuccessfulincompensating

forthepoorsocioeconomicbackgroundofpupils.Theeffectofsocialclassonlearningoutcomes

hasbeenproventobeweakerinFinlandthaninmostcountriesparticipatinginPISA.Also,the

betweenschoolvariationinlearningoutcomesisoneofthesmallestintheOECDworld.The

schoolsystemhasprovedtobehomogeneousinquality.

However,accordingtorecentdevelopmentsinPISAassessments,allthesepositive

resultsoftheFinnishschoolsystemhavebeendeteriorating.Theeffectofsocioeconomicand

culturalbackgroundonlearningoutcomeshasgottenstronger.

Theaverageproficiencylevelsinliteracy,mathematics,andscienceshasweakened

substantially,andtheproportionofpupilswithlowlevelofskillshasgrownsignificantly.Ascan

beseeninFigure12,theshareoflowperformersinmathematicshasgrownonaveragein

OECDcountries(from21.6%to22.9%fromyear2003toyear2015),butinFinlandthe

proportionhasdoubledintwelveyears,from6.8%to13.6%.Thepercentageoflowperformers

inFinlandisstillwellbelowOECDaveragebutthechangeisremarkableandhascausedalotof

discussiononthecausesbehindthesedevelopments.


17

Figure12.Theshareoflowperformers(belowtestlevel2)andhighperformers(testlevels5and6)inmathematicsofthe15yearolds:OECDaverageandFinland,inyears2003,2012and2015(%)

Besidesthegrowingproportionoflowperformerstherehasalsobeenasignificant

declineintheproportionofhighperformersinreading,mathematics,andsciencesinFinland.

ThesametrendcanbeseenintheOECDaverageaswell,but,again,inFinlandthechangehas

beenbiggerthaninanyothercountry.Forexampleinmathematics,theproportionofhigh

performershashalvedintwelveyears’time,from23.4%to11.7%.


18

PISAresultsreflecttheundesireddevelopmentthatmoreandmorepupilsarehaving

difficultiesinobtainingdecentlevelofmathematicalandreadingskillsinschools.Lateronthey

willhavedifficultiesinattachingtolabourmarketandgettingadecentjob.

Despitegrowingdifficultiesincopingwiththecompetitioninschoolandeducation

system,droppingoutofcomprehensiveschoolhasbeenveryrareinFinland.Almostallstudents

completetheircompulsoryeducationandgetacertificate.However,theshareofpupilsleaving

schoolwithoutaleavingcertificatefromcomprehensiveschoolhasbeenincreasingsince2008

(Figure13).Atotalof409studentshaddiscontinuedstudiesinonewayoranotherin

comprehensiveschoolduringthe2015/2016academicyear.Thenumberofthosewhohad

completelydroppedoutfromcompulsoryeducationinthespringtermwas94andthoseover

theageofcompulsoryeducationhavingleftschoolwithoutaleavingcertificatefrom

comprehensiveschoolwas315.Morethanone-halfofschooldrop-outswereboys.Thenumber

ofboysamongthosewhohadcompletelydroppedoutfromcompulsoryeducationwas53,and

185amongthosehavingleftcomprehensiveschoolwithoutaleavingcertificate.(Statistics

Finland.) Figure13.PupilshavingleftcomprehensiveschoolwithoutaleavingcertificateinFinland,2000-2016(%)

Source:StatisticsFinland Droppingoutofeducationhasbeenconsideredabigproblemespeciallyinsecondary

levelvocationaleducation.Inall,5.1percentofstudentsattendingeducationleadingtoa

qualificationordegreediscontinuedtheirstudiesanddidnotresumetheminanyeducation

leadingtoaqualificationordegreeduringthe2014/2015academicyear(Figure14).Compared

tothepast10yearperiod,discontinuationhasdecreasedinuppersecondarygeneraland


19

vocationaleducation,anduniversitiesofappliedsciencesandremainedrelativelyunchangedin

universityeducation.(ThesedataderivefromStatisticsFinland’sEducationStatistics.Students

whohavechangedtheirsectorsofeducation,e.g.,studentswhohaveswitchedfromupper

secondarygeneralschooltovocationaleducation,arenotcalculatedasdiscontinuedstudents.)

Mendiscontinuedcompletelytheireducationleadingtoaqualificationordegreeinthe

academicyear2014/2015moreoftenthanwomeninallsectorsofeducation.Mendiscontinued

theiruniversityofappliedscienceseducationmostcommonlyandwomentheirvocational

education.Womendiscontinuedtheirstudiesintheirownsectorsofeducationmoreoftenthan

menonlyinvocationaleducation.(StatisticsFinland.)

Figure14.Discontinuationofeducationinuppersecondarygeneral,vocational,universityofappliedsciences,anduniversityeducationinacademicyearsinFinland,from2005/2006to2014/2015(%)

Source:StatisticsFinland ThetrendinthepercentageofNEETyounghasbeendownwardsinEuropesince2012.

AtthesametimethepercentageofNEETyounghasbeenincreasinginFinland.However,year

2016thereseemstobeaturningpointforthegrowingNEETfiguresinFinland(Figure15).The

shareofNEETyouthofallyoungpeoplediminishedabitinbothNUTS2areasinFinlandaswell

asinFinlandonaverage.TheshareofNEETyouthisbiggerinNorth&EastFinlandthanin

SouthFinlandorinFinlandonaverage.HoweveratNUTS2levelthedifferencesbetweenareas

arerathersmall,lessthanonepercentagepoint.

vocationaleducation

unversityofappliedsc.

unversityeducation

uppersecondarygeneral


20

Figure15.YoungpeopleneitherinemploymentnorineducationandtraininginEU27,Finland,SouthFinland,andNorth&EastFinland,2012-2016(%)

ThereisalsorecentresearchonthesocalledNEETgroupmadeinFinlandwith

interestingstatisticsbyagegroupandgender.Youngpeoplenotinemployment,educationor

trainingorconscriptshasincreasedafter2010fortheyoungcohortsexceptthoseagedfrom15

to19(Figure16).TheNEETratefor20to24year-oldmaleshasincreasedespecially

significantly.Theeducationalattainmentofyoungmalesisnotasgoodasforfemales,which

explainsthedifferenceforitspart.ThepercentageofNEETwomenaged20-24hasalmost

doubledbetween2008and2015,fromninepercenttoabout16.5percent.Atthesametime

percentageofNEETmenaged25-29hasincreasedfrom15percentto20percent.

8.0

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EU27 Finland SouthFinland North&EastFinland


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Figure16.Youngpeoplenotineducationoremployment(NEET)byagegroupandgenderinFinland,2008-2015

Source:Alatalo,Mähönen&Räisänen2017. TheageofgraduationfromuniversitiesiscomparativelyhighinFinland.Onecrucial

reasonbehindlongstudytimesandlategraduationisthatitisverycommonforstudentsto

workwhilestudying.In2015,slightlylessthanone-halfofstudentswereemployedduringtheir

studies(Figure17).Since2004,thesharehasbeenhighestin2008whennearlysixoutoften

studentswereemployedduringtheirstudies.Workingwasmostcommoninconnectionwith

universityanduniversityofappliedsciencesstudies.Fifty-fivepercentofuniversitystudents

and54percentofuniversityofappliedsciencesstudentshadanemploymentcontractwhile

studying.Closetoone-halfofthestudentsattendinguppersecondaryvocationaleducationwere

15-19

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22

employedduringtheirstudies.In2015,theshareofemployedstudentsinuniversityeducation

decreasedthemost,byaroundonepercentagepointfromtheyearbefore.(StatisticsFinland.)

Figure17.Sharesofemployedstudentsagedatleast18ofallstudentsinFinland,2008–2015(%)

Source:StatisticsFinland Womenworkedwhilestudyingmorefrequentlythanmen:53percentofwomenand46

percentofmenhadanemploymentcontractwhilestudying.Theproportionofemployed

womeninuppersecondarygeneraleducationandinuniversityofappliedscienceseducation

wastenpercentagepointshigherthanthatofmen.Thirtypercentofwomeninuppersecondary

generaleducationwereworkingalongsidestudiesand56percentofwomeninuniversityof

appliedscienceseducation.Fifty-onepercentofwomeninuppersecondaryvocational

educationworked,whichwassevenpercentagepointsmorethanformen.Employmentduring

studiesgrewclearlytheolderthestudentswere.While22percentofstudentsaged18were

working,theshareofemployedstudentsagedatleast25wasnearlytriple.Of21-year-old

students,39percentandof24-year-oldstudents,49percenthadanemploymentcontract.

Amongstudentsaged25orover,61percentwereemployedduringtheirstudies.(Statistics

Finland.)

Tosummarizethefindingsonlearningandeducation,wecansaythatdespitetherecent

downturninlearningoutcomesinPISAassessments,onaverageFinnish15-year-oldsarevery

goodinmathematics,literacy,andsciences.However,theincreasingpercentageoflowachievers

isanationalconcerninFinnisheducationpolicy.Shareofpupilshavingleftcomprehensive

schoolwithoutaleavingcertificateisverylowinFinland,butithasbeenincreasingsince2008.

Itismostlikelythatmoreyoungpeoplewithpooreducationalqualificationsandpoorskillswill


23

enterlabourmarketinthefuture.Loweducationalattainment(belowISCED5)ismoretypical

tomalethanfemale,andmorecommoninFRKainuuthanFRSouthwestFinland.From2012to

2015,thestatisticaltrendinthepercentageofNEETyoungwasdownwardsinEuropebut

upwardsinFinland.Probably,thenumberofvulnerableyouth(especiallyboys)willincreasein

Finland.

1.4 Labourmarket

The1990’sstartedinFinlandwitharapidlydeepeningeconomicdepression.Theaverage

unemploymentrateincreasedupto20percent,andemploymentratewiththenumberofpeople

inlabourforcedecreased(seeFigure18).Duringthewholeofthe1990’sthenumberofpeople

inlabourforcecontinuedtostayatalowerlevelthanattheturnofthedecade.FRSouthwest

FinlandrecoveredearlierthanFinlandonaverage,nottotalkaboutFRKainuuwherethesizeof

thelabourforcehasbeendecreasingforthewholeperiodexaminedintheFigure18.Year2016

seemstohavewitnessedanewdramaticdownturninlabourforceinFRKainuu.Theglobal

financialcrisisin2008hitespeciallyhardFRSouthwestFinlandwherethenumberofpeoplein

labourforcedovedramatically.

Figure18.ThedevelopmentofnumberofpeopleinlabourforceinFinland,FRSouthwestFinland,andFRKainuu,1991-2016(year1991=100)

Duetorelativelyhighstructuralunemploymentandincreasingshareofelderlypeople

(inretirement)intheFinnishpopulationtheemploymentratehasbeenestimatedtobe

unbearablylow.Beforethe2008crisisemploymentratewasrisingforseveralyears.Butafter

70.0

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2008withincreasingunemploymentanddiscouragedworkersleavinglabourmarketaltogether

theemploymentraterapidlygottoalowerlevelandhasnotrecovered.EmploymentinFR

SouthwestFinlandhasbeenatahigherlevelthaninFinlandonaverage(Figure19).

RespectivelyemploymentrateinFRKainuuhasbeenmuchlowerthantheFinnishaverage.

Figure19.EmploymentratesinFinland,FRSouthwestFinland,andFRKainuu,2005-2016(%)

ThepresentFinnishgovernmenthassetthetargetathavingtheemploymentrateat72

percentin2019.Therehavebeenvariousmeasurestaken,but72%employmentratewillbe

beyondreachintwoyears’time.Year2017hasbeenthefirstpositiveyearinFinnisheconomy

sincethedownturnin2008.Thus,recoveringfromtheworldwidefinancialcrisisof2008took

abouttenyearsinFinland.Andstilltheeconomicfutureisfullofuncertainties.

In1991unemploymentbeguntorisedrastically.Theworstyearswere1993-1995when

theunemploymentratewasatthehighestlevelithadeverbeeninthehistoryofFinland.After

thattheunemploymentbegunasteadyfalltilltheyear2008afterwhichtheunemploymentrate

beguntoriseagain.ForFRKainuutheyear2014wasthepeakinunemploymentratewithabout

17percentoflabourforcebeingoutofwork(Figure20).InFRSouthwestFinland,

unemploymentratehasusuallybeenatalowerlevelthaninFinlandonaverage.However,in

2013unemploymentrateinFRSouthwestFinlandroseabovethecountryaverage.

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25

Figure20.UnemploymentrateinFinland,inFRSouthwestFinland,andFRKainuu1991-2016(%)

Justrecentlytherewasadescriptiveanalysisofstatisticalnaturepublishedwhich

discussesworkinglifeandbeingoutsideofitforyoungpeopleandyoungadults.Thetarget

groupsoftheanalysisareyoungpeopleaged15-24andforsomeparts,youngadultsuptothe

ageof34.Theissuesdiscussedareemploymentandjobtenure,theoccupationalandbranch

leveldevelopmentsinthelabourmarket,workingconditions,occupationsofjob-seekers,

unemploymentandthoseoutsideofemploymentandeducationortraining,allfocusedonyoung

people.Accordingtotheanalyses,participationintheworkinglifehaschangedinmanyrespects

inthe2000sforyoungpeopleandyoungadults.Afterthefinancialcrisis2008,employment

rateshavedecreased,withtheexceptionoftheyoungestcohorts.Malesagedfrom20to24have

adecreasingtrendintheemploymentrate,unlikefemales.Employedyoungwomenparticipate

moreoftenineducationcomparedtoemployedyoungmen.Theaveragejobtenureforyoung

peopleisusuallylow;theemphasisofFinnishyoungpeople´sjobsisintheshortduration,also

ininternationalcomparison.

Whatiscrucial,isthatitismoredifficultthanbeforeforyoungpeopleandyoungadults

togetintoasalariedprofessionalposition.Thelabourmarketpositionofyoungadultshas

worsenedasawholeduringtheprolongedrecessionperiodincomparisontooldercohorts.The

shareof25-34-year-oldmeninthepositionsofworkersanddependentclericalworkersis

increasing.Theshareofthesecohortshasdecreasedinthefieldofinformationand

communication,andincreasedinmining,construction,financeandinsuranceaswellasin

electrical,gasandheatingservices.Accordingtoacademicstudies,thedeterioratinglabour

marketpositionsarealsovisibleintermsofincome.Job-seekersagedbetween20and24are

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oftenunclassifiedintermsofoccupation.Thehighestshareofoccupationsarefoundin

construction,repairandmanufacturingwork,whilealsoserviceandsalesoccupationsarefound

forover20percentofthejobseekersinthecohort.Forthefiveyearsoldercohort,theshareof

expertoccupationsishigher.

Afterthefinancialcrisis,unemploymentforyoungpeoplehasincreased,moreheavily

formalesthanforfemales.Youthunemploymenthasalreadyturneddownwardsthisyear,but

long-termunemploymentisstillrising(Figure21).

Figure21.Thenumberoflong-termunemployed20-29yearoldsinFinlandbygender,2006-2016

Source:Alatalo,Mähönen&Räisänen2017.

TosummarizethefindingsonlabourmarketsituationinFinland,weconcludethatdifferences

inemploymentratesbetweenregionsandagegroupsarelarge.Averageemploymentrateis

muchhigherinFRSouthewestFinandthanFRKainuu,andrespectively,unemploymentrateis

higherinFRKainuuthaninFRSouthwestFinland.Thelabourmarketpositionofyoungadults

hasworsenedasawholeduringtheprolongedrecessionperiodincomparisontooldercohorts.

TheaveragejobtenureforyoungpeopleinFinlandisusuallyshortinduration,alsowhen

comparedinternationally.Itismoredifficultthanbeforeforyoungadultstogetintoasalaried

professionalposition.Youngpeoplehaveahardtimeinplanningtheirfutureespeciallyin

economicallyregressiveregions.

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27


Ininternationalcomparisons,Finlandhashadrelativelynarrowincomedifferences.

SocioeconomicandculturalinequalitieshavebeensmallerthaninmostEuropeancountries.The

culturalgapbetweensocialclassesisnotnearlyaswideas,e.g.,inGreatBritainorFrance.One

ofthereasonistheculturalhomogeneityofthepopulation,butalsoimplementedpolicieshave

certainlyhadanimpactonthesizeoftheclassdifferences.However,OECDstatistics(OECD

2015;2016b)showthatincomedifferencesinFinlandhavegrownsincethebeginningofthe

1990’s(Silvennoinen,Kalalahti&Varjo2016),and,ascanbeseeninFigure22,theregional

differencesindisposableincomearesignificantinFinland–whenrememberingthatcomparing

NUTS2levelareashidealotofregionalandlocaldifferencesandinequalities.Disposableincome

hasincreasedinbothNUTS2areasbuttherelativedifferencebetweentheareashasremained

almostunchanged.

Figure22.GINIIndexbeforeandaftertransfers(leftaxis),disposableincomeinthehouseholdsinPPS(rightaxis),inEU27,Finland,SouthFinland,andNorth&EastFinland,in2005-2015

TheGINIindexbeforeandaftertransfersarelowerinFinlandthaninEU27countrieson

average.Itseemsfromfigure21thatmechanismoftransfershasbeeneffectiveinFinland:GINI

indexbeforetransfersincreasedfrom44.9%in2009to47.4%in2015.Atthesametime,GINI

indexaftertransfersdecreasedslightlyfrom25.9%to25.2%.

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BeingatriskofpovertyandsocialexclusionislowerinFinlandthanitisinEU27countrieson

averagebutitiscertainlynotnon-existent,althoughtheriskismuchlowerthan,e.g.,intheU.K.,

nottotalkaboutSpain.About17%ofthepopulationhasbeenatriskofpovertyorexclusion

between2005and2015.Thereissomevariationbetweentheyearsduringthatperiod,butwith

alongtermexaminationtherateisquitesteady(Figure23).Thegapbetweendifferentpartsof

thecountryhasbeengrowingduringthepastdecade.Theriskofpovertyandsocialexclusion

hasgrownbiggerespeciallyinnorthernandeasternregionsofFinland.

Figure23.Peopleatriskofpovertyandsocialexclusion,inEU27,Finland,SouthFinland,andNorth&EastFinland(plusSpainandtheU.K.),in2005-2015(%)

Itisagreedthattheproportionofpeopleatriskofpovertyandsocialexclusionis

substantialinFinland,andespeciallyinnorthernandeasternregionsofthecountry.However,

severematerialdeprivationrateisatasubstantiallylowerlevelthaninothercountries

participatinginYoungAdullltresearch.Theratehasbeen2-3percentinbothNUTS2levelareas

andinFinlandonaverage.

Insummary,incomedifferences,aswellasriskofpoverty,aresmallerinFinlandthanin

mostEuropeancountries.GINIIndexhasincreasedsincetheyearoffinancialcrisis2008.

However,mechanismoftransfersseemstohavebeeneffectiveinFinland,sincealthoughGINI

indexbeforetransfershasincreasedandGINIindexaftertransfershasdecreasedslightly.

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1.6 Healthandwell-being

AccordingtoPISA2015studyFinnish15yearoldsareamongthemostsatisfiedyouthinthe

OECDworld(OECD2016a).NearlyhalfofFinnishpupils(45%)saytheyareverysatisfiedwith

theirlifewhereastheOECDaverageis34%.Among49participatingcountriesonlytheyouthin

DominicanRepublic,Mexico,CostaRica,andCroatiafeltweremoresatisfiedwiththeirlifethan

Finnishyoungpeople.

Figure24.Rateofyouth(20-29years)livingwiththeirparentsbygender,EU27andFinland(%)

OnefeatureincomingtoageinFinlandisthatyoungpeoplemoveawayfromtheir

childhoodhomeatarelativelyearlyage.InsomeEuropeancountriesyoungleavetheir

childhoodhomeaslateasattheageof30.Thiswouldbeconsideredassomesortofpersonal

failureinFinland.Finnishyouththinkthathavinganownapartment(rentedorowned)isa

crucialstepingainingindependenceasapersonandacitizen.Intheagegroup20-29,only10

percentofFinnishwomenlivewiththeirparents(Figure24).Thathasnotchangedinthepast

tenyearsorso.OftherespectivegroupofFinnishmenabout25percentlivewiththeirparents.

Thepercentagehasbeenslightlydecreasingsince2006.Thedevelopmentisquitetheopposite

comparedtotheirEU27peersofwhich63%livedwiththeirparentsin2013.Thedifferencein

percentagepointsbetweengendersisaboutsameinFinlandandinEU27.Theshareofyoung

menlivingwiththeirparentsisabout15percentagepointshigherthanamongyoungwomen.

Finnishyoungpeopleareclearlymoresatisfiedwithseveralareasoftheirlifethantheir

peersinEuropeonaverage,ascanbeseeninFigure25.

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Figure25.Highsatisfactioninvariouslifedomainsofpopulationaged25-34bygender,EU28andFinland

EspeciallylargedifferencesbetweenFinnishyouthandEuropeanaveragearein

accommodation,jobsatisfaction,andoveralllifesatisfaction(Figure25).Areaswiththelowest

levelofsatisfactionarethesameinFinlandastheEuropeanaverage:timeuseandfinancial

situation.ItseemsthatinFinlandyoungwomenaremoresatisfiedthanyoungmen.Especially

thesenseonmeaningoflifemakesadifferencebetweengendersinFinland.

Tosummarizethefindingsinhealthandwell-beingitsufficestosaythatFinnishyoung

peoplearerelativelysatisfiedwiththeirlifeinmostareasoflife.However,inmanyrespects

youngwomentendtobemoresatisfiedthantheirmalecounterparts.Onfeaturetypicalto

Finlandisthatyoungcohortsleavetheirchildhoodhometoliveontheirownatarelativelyearly

age.Thisprobablyincreasestheirfeltautonomyandindependenceandaffecttheirwell-beingas

well.

2. Concludingremarks

TheschoolsysteminFinlandhasprovedtobehomogeneousinquality.Differencesbetween

schoolsaregrowingbutstillrelativelysmall.Youngpeoplehaverelativelygoodeducational

0

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EU28males Finmales EU28females Finfemales


31

opportunitiesattheuppersecondaryandtertiarylevel.However,thereareabout10percentin

eachagecohortyoungpeoplewhodonotcontinueineducationortrainingafterbasic

education.Theirsituationisgettingworsewhilethecompetitioninthelabourmarketgets

tighter.AnewdevelopmentinFinnishschoolsystemisthesteadilydecreasinglevelofaverage

learningoutcomestestedinPISA,TIMSS,andPIRLS.Duringthepastdecade,theshareofhigh

performershasbeendecreasingandlowperformershasbeengrowing.Lowperformancein

compulsoryschoolhasfarreachingconsequencesonyoungperson’sabilitytoclimbinthe

hierarchiesofeducationsystemandlabourmarket.

Finnisheconomyhassufferedtwoseverecrisessincethe1980’s,firstintheearly1990’s

andthenasaneffectoftheglobalfinancialcrisisfrom2008onwards,whichhavehaddrastic

effectsonyouthemployment.Long-termunemploymentof20-29yearoldmaleswasseven

timeshigherandfemaleseighttimeshigherin2016thanin2008.Uncertainemployment

prospectshavealsodiscouragingeffectsoneducationalmotivationespeciallyforlowachieving

young.Incertainregionsofthecountry,includingFRKainuu,gettingajobwithoutwork

experienceandvocationaltrainingispracticallynon-existent.ThenumberofNEETyounghas

beenslightlyincreasingduringthepastdecadeorso.Actually,youngadultslivinginthetwo

functionalregions(FR),FRSouthwestFinlandandFRKainuu,liveinquitedifferentrealities

whatcomestotheirfutureprospects.Peopleborninnorthernandeasternpartsofthecountry

tendtomovetosoutherncitiesaftercompletingcompulsoryoruppersecondaryeducation.The

overallemploymentinFRKainuuhasdecreasedquitedramaticallywithinthepastdecades:the

numberofemployedinFRKainuuisonlyabout70percentofthelevelitwasinthebeginningof

the1990’s.However,Finnishyoungpeopleareclearlymoresatisfiedwithseveralareasoftheir

lifethantheirpeersinEuropeonaverage.EspeciallylargedifferencesbetweenFinnishyouth

andEuropeanaverageareinaccommodation,jobsatisfaction,andoveralllifesatisfaction.

BeingatriskofpovertyandsocialexclusionislowerinFinlandthanitisinEU27countrieson

average.About17%ofthepopulationhasbeenatriskofpovertyorexclusionbetween2005

and2015.Thegapbetweendifferentpartsofthecountryhasbeengrowingduringthepast

decade.Theriskofpovertyandsocialexclusionhasgrownbiggerespeciallyinnorthernand

easternregionsofFinland.

ThenumberofchildrenborninFinlandwillbelowerthaneversincethelastfamine

years1866-68,althoughthesizeofthepopulationhasmorethandoubled.Accordingtothe

projection,theshareofpersonsagedunder15inthepopulationwoulddecreaseto14percent

by2060.Theshareofpeoplewithforeignbackgroundhasbeenverylowcomparedtoother

Europeancountries.Hostilitytowardspeoplewithforeignbackgroundhasincreasedduring

recentyearsamongnativepopulation.Thesedevelopmentswillhavesevereconsequencesfor

thedependenceratiointhefuture.


32

Inthisreport,thebasicstatisticshavebeenpresentedatNUTS2-level(‘largerareas’

SouthFinlandandNorth&EastFinland).Relatedtothebasicproblematicsandtheapproachof

YoungAdulllt-projectthisisaproblem.TherearesubstantialdifferencesbetweenNUTS3level

regionsincludedinthesameNUTS2levelareas.Thisconcernsalsoourtwofunctionalregions,

especiallyFRKainuu.SuitabilityofNUTS2levelstatisticsindicatingtherealitiesatNUTS3

level-atthelevelofourfunctionalregions–isdisputable.StatisticsonNUTS2area‘North&

EastFinland’donotrepresentproperlythesituationinFRKainuu.However,crucialinformation

atNUTS3level,wheneveravailable,hasbeenaddedsothatthefunctionalregionsSouthwest

Finland(partofNUTS2area‘SouthFinland’)andKainuu(partofNUTS2area‘North&East

Finland’)wouldbedescribedmoreproperly.

3. References

Alatalo,J.,Mähönen,E.&Räisänen,H.2017.Nuortenjanuortenaikuistentyöelämäjasen

ulkopuolisuus.TEM-analyyseja76/2017.Helsinki:MinistryofEconomicAffairsand

Employment.

Kalalahti,M.,Silvennoinen,H.,Varjo,J.&Rinne,R.2015.Educationforall?UrbanParental

AttitudesTowardsUniversalismandSelectivismintheFinnishComprehensiveSchoolSystem.

InP.Seppänen,A.Carrasco,M.Kalalahti,R.Rinne&H.Simola(eds)ContrastingDynamicsin

EducationPoliticsofExtremes:SchoolChoiceinChileandFinland.London:SensePublisher,

205–224.

OECD2013.PISA2012Results:ExcellenceThroughEquity:GivingEveryStudenttheChanceto

Succeed(VolumeII).Paris:OECDPublishing.

OECD.2015.InItTogether:WhyLessInequalityBenefitsAll.Paris:OECDPublishing.

OECD.2016a.PISA2015Results(VolumeI):ExcellenceandEquityinEducation.Paris:OECD

Publishing.

OECD.2026b.IncomeDistributionDatabase(IDD).http://www.oecd.org/social/income-

distribution-database.htm.

Silvennoinen,H.Kalalahti,M.&Varjo,J.2016.Globalisaatio,markkinaliberalismija

koulutuspolitiikanmuutos.[Globalisation,MarketLiberalismandEducationPolicyChange.In


33

Finnish].InH.Silvennoinen,M.Kalalahti&J.Varjo(eds)Koulutuksentasa-arvonmuuttuvat

merkitykset.Kasvatussosiologianvuosikirja1.Kasvatusalantutkimuksia73,11-34.

StatisticsFinland.PopulationStatistics.http://www.stat.fi/til/vrm_en.html.

Väestöliitto.

http://www.vaestoliitto.fi/tieto_ja_tutkimus/vaestontutkimuslaitos/tilastoja/syntyvyys/syntyn

eiden-maara/

Work Package 4


Germany National Report

University of Münster (WWU) & University of Education Freiburg (PHFR)

Sarah Schaufler & Marcelo Parreira do Amaral in cooperation with Thomas Verlage and Uwe H. Bittlingmayer

Project Coordinator: Prof. Dr. Marcelo Parreira do Amaral (University of Münster)

Project no.: 693167

Project acronym: YOUNG_ADULLLT

Project duration: 01/03/2016 to 28/02/2019 (36 months)

Type of document: National Report

Delivery date: Month 19

Dissemination level: Public

ExecutiveSummary

LifeLongLearning(LLL)policiesacrossEuropehavebeenrepeatedlydescribedashighlyfrag-

mentedandoftenconflictingintheirobjectivesinrelationtotheirtargetgroupsandmeansof

implementation. Although aiming to improve economic growth and social inclusion for young

adults, theymightproduceunintended effectswhen they arenotwell suited to thehighlydi-

versetargetgroups.InparticularregardingthehighfragmentationofLLLpoliciesdifferentef-

fectsindifferentcontextscanbeobserved,whichraisesthequestionastotheirfitnessofthese

policiestothetargetedgroups.

TheprojectYOUNG_ADULLLTaimsat identifyingnecessaryparametersforfuturedeci-

sion-makingsupportsystemsbyunderstandingLLLpoliciesforyoungadultsintheirinterplay

between economy, society, labourmarket and education and training systems at regional and

local levels, including discussing issues of fragmentation and discrepancies affecting young

adults’lifecourse.Thus,theobjectivesoftheprojectare:

1. TounderstandtherelationshipandcomplementarityofLLLpoliciesintermsoforienta-tionsandobjectives to theirspecific targetgroups including(intendedandunintendedeffects);

2. Toenquires intopolicies’ fitandpotentials fromtheperspectiveoftheyoungadultstoexplorehiddenresourcesofyoungadultsbuildingtheirlifeprojects;

3. ToresearchLLLpoliciesintheirembeddingandinteractionintheregionaleconomy,thelabourmarketandindividuallifeprojectsofyoungadultstoidentifybestpractices.

InthecontextoftheoverallobjectiveofYOUNG_ADULLLT,thissub-study(WP4)focusesonthe

analysisonhowtheregionalcontextshapestheyoungadults’livingconditions.AsLLLpolicies

becomeeffectiveattheregional/locallevel,thesub-studyaimstoprovideinsightsintothedif-

ferentlocalcontextsLLLpoliciesareembeddedinandhowtheseregionalsettingsunderstudy

providedifferentlivingconditionsforyoungadults.Thus,eachregionalcontextcanprovide(or

preclude)specificopportunitiesforyoungadults’lives,leavinguntappedtheplentifulresources

forindividualgrowthandsocialinclusion.Theaimistopayparticularattentiontothestructural

characteristicsof theregions, suchas the infrastructure,educationandworkopportunities, to

describethedifferentsocialrealitiesofyoungpeopleandhowthoserealitiesareconstructedin

statisticaldatacollection.Thisallowsustounderstandhowthecontextcanmediateandinflu-

enceLLLpoliciesineachregion.

The livingconditionsaremostadequatelyanalysedbymeansofquantitativedata.Thus,WP4

contributestothemulti-methodapproachinYOUNG_ADULLLTandfirst, informsabouttheliv-

ingconditionsofyoungadultsandsecond,providescontextualdataforembeddingthequalita-

2

tivedatacollectionapproachesinthequalitativeanalysisofyoungadults(WP5)andtheanalysis

oftheskillsupplyanddemandonthelabourmarket(WP6).

ThisnationalBriefingPaper,first,providesanoverviewofthelivingconditionsofyoungadults,

second, explains how relevant statistical sources describe their realities, and, third, identifies

gapsforfurtherdatacollectionforthetwoFunctionalRegionsofGermanyinthisstudy,Rhein-

MainandBremen,bydisentanglingvariousriskprofilesfromthecontexttheyareembeddedin.

In order todescribe andunderstand the local living conditions of young adults aswell as the

limitationsandconstraintsofthegivennational/localstatisticaldatainbothFR,fourmaintasks

wereperformed:

1. Identifyingandcollectingof localdata forcomplementingandenrichingthenationaldatasetsprovidedbyinternationaldatasources.

2. Analysing the living conditionsof young adults and their implicationsby identifyinglocalriskprofilesalongthefollowingdimensions:theeconomic,demographic,educa-tion and training, labour market, social inclusion and participation, and health andwell-being.

3. Assessingthequalityoftheavailablestatisticaldata(availability,classificationofthetargetgroup,etc.)byaddressingcontextspecificdatagaps.

4. Reportandassesstheparticularitiesandconditionsoftheregions,whichcanexacer-bateriskforyoungadultsforbuildingtheirlifeprojects.

In this study, the research object has been conceptualised along the living conditions of

youngadultsintheirregionalsettings(chapter2).Youngadultsareaheterogeneousgroupre-

garding theirsocialrealities, lifeprojectsandperspectivesandthusaredifferentlyaffectedby

structuraldevelopmentsasdifferentregionsprovidedifferingsocio-economicopportunitiesand

limitations.Thisrequiresustodistinguishbetweenheterogeneouscontextstheyareembedded

in,suchasthedemographiccharacteristicsofthepopulation,thestructureoftheeconomy,the

inputsandoutputsoftheeducationandtrainingsystem,thelabourmarket,thematerialliving

conditions and civic participation as citizens in political and social life and, finally, the health

conditionsandindividualwell-being.

Basedonthisconceptualisationthelivingconditionsaredescribedasfollowed:

• First,thelivingconditionsdescriberegionalvariationsofstructuralandsocio-economic

conditions, as the resources on sitemay vary and can enhance risks for young adults

buildingtheir lifeprojects. Indoingso,wedescribe localriskprofilesaccordingtothe

particularitiesandconditionsoftheregions,whichcanproduceand/orenhancevulner-

able situations for young adults. In particular since being a young adult itself implies

vulnerablelifephaseaspivotaldecisionsarebeingmade.

3

• Second,datagapsinlocalstatisticalsourcesareassessed,asthedatacollectionforthe

regionalcontextvaries.Comparativesurveysarewidelyusedintheprocessofdescrib-

ing,coordinatingand implementingLLLpolicies foryoungadults,however,oftencon-

structtheirtargetgroupalongtheirindividualdeficitsnotalongstructuraldeficits.

TheresultsofthisBriefingPaperarebasedonsecondaryanalysisusingstatisticaldatacollated

fromnationaladministrativesourcesandcomparativesurveyscompiledbyinternationalorgan-

isationssuchastheEUandtheOECDsuchasEU-SILC,Eurostat.Thedataprovidedbyinterna-

tionalsurveyischallenging,astheregionaldataclassificationdoesnotalwayscovertheselected

twoFunctionalRegionsRhein-MainandBremen.Asthedataisaggregatedalongterritorialad-

ministrative responsibilities, the so-called Nomenclature des Unités Territoriales Statistiques

(NUTS),itdiffersfromtheprojects’adoptedconceptoffunctionalregion.Inordertoavoidover-

lapsofthedataunitswithotherregionsnotincludedinourconceptualization,onlythesmallest

NUTS2levelperFunctionalRegionwasused.Asthoseunitsarealotsmallerthanthetwore-

gions,wetakelossofdataintoaccount,however,theyrepresenttheirmetropolitancore.

The living conditionsof youngpeople (chapter 3)are described along the following six di-

mensions:(1)demographiccharacteristicsofthepopulationanditssubgroups;(2)structureof

theeconomy, (3) inputsandoutputsof theeducationsystem; (4) labourmarketsituation; (5)

redistributionandsocialinclusion,and(6)healthconditionsandindividualwell-being.

Themainresultsareasfollowed:

• Demographic structures: Overall, the German society is undergoing demographic

changesduetoanagingsocietyandan inflowofmigrants.However, thegrowthof the

tworegionsdiffersimmensely,astheFRRhein-Mainisconstantlygrowingduetowork-

erinflow,whereasthepopulationinFRBremenisshrinking.Therealsoseemstobean

interlinkagebetween labourmarketpossibilitiesandfamilyplanning:While inFRBre-

menyoungadults aremore likely tobe responsible at a youngage for children, inter-

rupting training andwork in early career stages, in theFRFrankfurt, especially in the

metropolitancore,youngpeoplearemorepronetopostponinglifeprojectsoffamilyand

ownchildren.Thedatashowsthattoday’syoungadultsgrowupunderdifferentcircum-

stancesanddealwithdifferentlimitations(highlivingcosts,uncertaincareerpath,pro-

longededucationaltrajectories,etc.),whichhindersthemfrommovingoutoftheirpar-

ents’homeandachievingfinanciallyindependentlives.Specifically,youngadultsunder

25–whoarerecipientsofwelfarebenefits(HarzIV)–arefurtherpreventedfromgain-

ingautonomybythelegalregulationsofsocialprogramsandlabourmarketpolicies.

• Structureoftheeconomy:Wealthandeconomicproductivityisunevenlydistributedin

the researched locales:While the core of both regions is ratherwealthy, its periphery

4

hardlyprofitsfromtheeconomicturnover.Atthesametime,thehighlivingcostsinthe

coreareashinderyoungadults fromlivingandworkinthemoreprofitablecoreareas.

Asaresult,amismatchofeconomicopportunitiesandfinanciallimitationsarises,espe-

ciallyconcerningyoungadultslivinginFRRhein-Main.Simultaneously,theregionsface

structuralchangescreatingrisksforcareerpaths,particularlyaffectingyoungadults in

FRBremen.While traditionallydominantsectorsareon thedecline (suchas logistics),

other low-wage sectorsaregrowing,which could lead toa rethinkingof youngadults’

careerchoices:insteadofinvestingtimeinalow-paidapprenticeshipwithprospectsofa

low-paidjobintheservicesectoritcouldleadthemdirectlyintothelabourmarket.

• Educationsystem:TheGermaneducationsystemischaracterisedbyatightcouplingof

certificatesandoccupationalbiographies.Withtheincreasingtrendtowardsacademisa-

tion,youngadultsfaceaprolongationofformaleducation.However,thisfollowsapecu-

liarinstitutionalfragmentationduetothemulti-tieredschoolsystemwhichcaterstola-

bourmarketswithsubstantiallydifferentneeds(forinstanceasindicatedbyaprevalent

discourseaboutanallegedskilledworkshortage(Fachkräftemangel):Although40%in

theFRRhein-Mainand30%intheFRBremenhaveanAbitur,whichqualifiesthemfor

the university, they are trained as Fachkräfte leading to a competitionwith graduates

from other school tracks. The opportunities for education, and thus occupation, are

largelydeterminedbytheregioninwhichtheyoungadultsgrowup:Growingupinthe

neighbouringpartsofFrankfurtamMainasforinstancethecityofOffenbachorAschaf-

fenburg(theBavarianpartof theFR)or intheruralareasofFRBremenexponentially

increases the odds of achieving at most the lower secondary education certificate

(Hauptschule).Youngadultslivingthereareespeciallyatriskofexclusion,asthisschool

track is continuously reduced in Germany thus also diminishing their chances in the

transitionintothelabourmarket.

• Labour market: Although youth unemployment rates are under the EU average, for

youngadultslivingintheFRBrementheriskishigherthanintheFRRhein-Main.Par-

ticular regionaldifferences in contrasting labourmarketspromoteand foster theneed

for specific jobs as consequence of the regional structural changes. Especially the FR

Bremenhasahighlydynamicandcontrastinglabourmarket,howeverstilloffersalarge

numberofjobsinproductionplants.Asaresult,thelabourmarketsarehighlypolarised,

with focus on high and low skilled workers constantly reducing the medium skilled

workers. In contrast, theFRRhein-Mainoffers abroadervarietyof jobs in finance, air

transportation, service and media, however, attract workers all over Germany and

worldwidewhocompetewith thepotentialworkersonsite.ParticularlyasbothFunc-

5

tional Regions attract high skilledworker in the core spreading the remaining skilled

jobsinitsperipherycausingprecarioussituationsforNEETsandearlyschoolleavers.

• Redistributionandsocialinclusion:Beingatriskofsocialexclusionandpovertyvaries

remarkablywithinandacrossbothFunctionalRegions.Livinginthecoreofbothregions

enhancestheriskofreceivingbenefits for longterm-unemployment.However, therisk

varieswiththeregions.Forexample,thechancesforachildreceivingsocialtransfers–

anoften-usedpoverty indicator–in thecitiesBremerhaven,Delmenhorst (FRBremen)

orOffenbach(FRRhein-Main)arethreetimeshigherthaninthecitiesCloppenburg,Os-

terholz(FRBremen),thecityofFulda(FRRhein-Main).Thus,theregionitselfseemsto

beastrongpredictorofpoverty,forcingyoungadultstobemobile.

• Healthandwell-beingconditions:Theabove-mentionedpovertyriskprofilesaresimi-

larintermsofhealth,asgrowingupinpoorfamiliesleadstoadecreasedhealthstatus.

Thisriskrisesforyoungadultslivinginmoreruralareas,astheaccesstohealthcareis

limited.Asdetailedlocaldataismissing,weconcludedbasedondataonpovertyandun-

employment,thatthehealthriskisalsohighinthecitiesofBremerhavenandWilhelms-

haven(bothFRBremen)andWormsandOffenbach(bothFRRhein-Main).

Theassessmentofthedataquality(chapter4)providesanoverviewofthepossibilitiesand

limitationsof theavailabledata fordescribing the livingconditionsofyoungadults.Statistical

dataisoftenabaseforpoliciesprocessesconcerningyoungadults.Therefore,theimplementa-

tionandmatchingofLLLpolicesisalsoaquestionoftheinformationonwhichpolicy-makingis

based.Inordertoachievethisobjectivetwomaintaskswereperformed:

1. Descriptionofdatagapsatnationalandlocallevelwhicharecontextspecific,and

2. Assessingthelimitationsandconstraintsoftheanalysisinrelationtothecontextspecific

ofthefunctionalregionandourtargetgroup.

Inshort,mostdatabanks(e.g.,EUROSTAT,INKAR,DESTATIS)donotcollectandanalysedataon

theindicatorsusedinourresearchatNUTS2level,whichwouldprovideforamoretailoredand

customizedinformationsource.Forthisreason,ithasbeendifficulttoaccessdatadescribingthe

targetgroupathand;also,dataonyoungpeoples’attitudestowardslabourandpolitical life is

largelymissing on a local level. Finally, available indicators reduce young adults’ information

sourcestoeducationandemployment.

Asaresult,youngadultsaremainlyinvisibleinwithinthestatisticaldatasetsasanindependent

agegroup.Therefore,thequestionarises,howcurrentLLLpoliciesarefittingintoyoungadults’

socialrealitiesasthestatisticalbasisofinformationisnottailoredalongtheneededinformation.

ThechapteronEmergingissues(chapter5)dealswithspecificissuesthatcameupduringthe

analysisandarerelevantforthecontextoftheprojectandprovidesconcludingremarks:

6

1. Wecanobserveadivergencebetweenthedataqualityandavailabilityonnationaland in-

ternationallevel,especiallyregardinglocaldata,theageofthetargetgroupaswellashealth

indicators.

2. Althoughtheroleofthefamilyisrelevantfortheyoungadultslivingconditionsandsteered

bytheGermanwelfaresystem(principleofsubsidiarity),theircontributionisratherinvisi-

bleinthedatasets.

Inconclusion,statisticaldataavailableonthelivingconditionsofGermanyoungadultsismainly

collectedatnationallevelandusuallyrestrictedtoeducationandemploymentindicators,gloss-

ingoverothercrucialaspectsof their life courses.Against thisbackground,basedon thedata

reviewed the German context can be described as an employment-centred transition regime

whereyoungadults’autonomyischaracterisedbya low levelofstatesupportbuthigh family

support.Therefore,youngadults’citizenshipcanbedescribedasa‘monitoredcitizenship’,with

the overall aim to expedite their transition intowork along highly institutionalised education

andtrainingsystems.

Contents1. Introduction....................................................................................................................................................................................8

2. Methodologyanddescriptionofthedatacollectedatlocallevel.........................................................................10

3. Findings..........................................................................................................................................................................................15

3.1 Demographicstructure.................................................................................................................................................15

3.2 StateoftheEconomy.....................................................................................................................................................20

3.3 Educationsystem............................................................................................................................................................24

3.4 Labourmarket..................................................................................................................................................................30

3.5 Redistributionandsocialinclusion.........................................................................................................................34

3.6 Healthandwell-beingconditions.............................................................................................................................38

4. Qualitydataassessment..........................................................................................................................................................41

5. Emergingissues..........................................................................................................................................................................44

6. References.....................................................................................................................................................................................46

ListofFigures

Figure1FunctionalRegionsinGermany...................................................................................................................................12Figure2DifferentFormsofRegions.............................................................................................................................................13Figure3Cruderateofnetmigration(1per1000),fertilityrateandolddependencyratefrom2005to2015,NUTS2Level..............................................................................................................................................................................17Figure4Rateofyoungadults(20-29)livingwiththeirparentsbygenderfrom2006to2013;nationalLevel............................................................................................................................................................................................................18Figure5GDPineuroperinhabitantsPPSandlabourproductivity(rightax,EU=100),Germany,BremenandDarmstadt,NUTS2-Level,2006-2015................................................................................................................................21Figure6Shareofstudentsintertiaryeducation(20-24)from2005to2012,NUTS2,%...................................26Figure7ComparisonoftheISCED(0-8)educationlevels(25-64)of2005and2014,NUTS2level,%......27Figure8Tertiaryeducationattainment(ISCED5-8)(30-34)from2005to2014NUTS2Level,%...............28Figure9NEETrate(15-24)andearlyschoolleavingrate(18-24),from2005-2015NUTS2-Level,%........29Figure10:youthemploymentandunemploymentratesforyoungpeople(15-24),EU-27,Germany,BremenandDarmstadtonNUTS2-Level,2005-2015.........................................................................................................31Figure11:GINIindexbeforeandaftertransfers,disposableincomeinthehouseholdsinPPS(rightax),EU-27,Germany,NUTS2LevelBremenandDarmstadt,2005-2015............................................................................36Figure12Highsatisfactioninvariouslifedomains,age25-34,EU-28andGermany,2013...............................40

ListofTables

Table1OverviewonthedatacollationforthetwoFunctionalRegionsRhein-MainandBremen..................14Table2SizeofenterprisesinGermanyandEU-27from2010to2014,%.................................................................22

8

1. Introduction

LifeLongLearning(LLL)policieshavedifferentandoften-competingobjectivesaffectingyoung

adults’lifecourses.AsLLLpoliciesunfoldonthenationallevel,however,playoutdifferentlyin

localcontexts,theyprovidedistinctopportunitiesorconstraintsinyoungadults’livesaffecting

their social realities. Local contexts are important as they shape their living conditions, hence

varyandaresociallyconstructed(cf.Bartlett&Vavrus,2017,p.14):First,regionalsettingsvary,

asstructuralcharacteristics(e.g.infrastructure,educationalandworkingopportunitiesetc.)are

notevenlydistributedwithinonecountry. Second, regional settingsare constructedalong the

“social interactions,politicalprocesses, andeconomicdevelopments” (ibid.) shaping the living

conditions ina specificway.Thus,describing thestructural settingshighlights towhatextend

andhowtheselivingconditionsofyoungadultsareintercededandinfluencedbyLLLpolicies.

InthecontextoftheoverallobjectiveofYOUNG_ADULLLT,thissub-study(WP4)focuses

onthequantitativeanalysisofregionalcontextshapingtheyoungadults’livingconditionsinthe

interplaywithLLLpoliciesatmacro,mesoandlocallevel,whichsupportorhindergrowthand

social inclusion.AsLLLpoliciesbecomeeffectiveattheregional/local level,thesub-studypro-

videsinsightintothedifferentlocalcontextsLLLpoliciesareembeddedin.First,bydescribing

thedifferentlivingconditionsforyoungadultsintheFunctionalRegions(FR)understudyand,

second,byassessinghowthespecificitiesofnationaldatacollectionitselfcreatesadescription

of young adults living conditions (Functional Regions, cf. Kotthoff et al. 2017; Weiler et al.

2017a).Thisallowstoassessthepolicies’fitandpotentialsintheregionalcontextsbydescrib-

ingthetensionbetweenthesocialrealitiesandtheofficialdescriptionofyoungadults.

Inordertodoso,thisBriefingPaperidentifieslocalriskprofilesdescribingthestructur-

al implications on young adults living conditions as different regions have different risks for

theiryoungadultsliving,learningandworkingthere,andthus,cancreatevulnerablesituations

forthem.Growingupinaspecificregioncanbemake-or-breakforyoungadultsincreatingtheir

lifecourseassomeregionsmakeiteasiertocreate‘successful’lifeprojectsthanothersdo.The

analysisofregionalriskprofileshastwoaims:First, toanalysethesocio-economicparticulari-

tiesofthelivingconditionsintheregions,whichcanexacerbateriskforyoungadultsbuilding

their lifeprojects.Second, thespecificitiesofdatacollection,ascomparativesurveysonstruc-

turaldataiswidelyusedasaninformationsystemforLLLpoliciesthemselves.Asstatisticsare

usedtosteerprocessesofdefinition,coordinationandimplementationofLLLpoliciesforyoung

adults,thedataitselfprovidesa ‘data-lens’onyoungadultsshapingthepolicyprocesses,yet–

notnecessarilymatchingtheirsocialrealities.Anassessmentofdatabasesisprovidedtoidentify

datagapsthatshouldandcouldbefilledinordertoinformLLLpolicies,astheirimplementation

isnotonlyaquestionofpolicycoordinationandmatchingofthedifferentcontextsandinterests,

butratheraquestionoftheassessmentoftheinformationonwhichpolicy-makingisbasedon.

9

Againstthisbackground,thesub-studyprovidesaquantitativeanalysisofyoungadults’

socialandlivingconditions(WP4)whichfocusesontheregional/localsocio-economicparticu-

laritiesoftheregionsunderstudy.Thesewerereviewedandmappedintheprevioussub-study

(WP3)(cf.Kotthoffetal.,2017)andthisnationalBriefingPaperprovidesashortoverviewofthe

livingconditionsofyoungadultsinGermanyanditstwoselectedregions,Rhein-MainandBre-

men(cf.Bittlingmayeretal.,2016a).Thequantitativeanalysis identifiesriskprofilesofyoung

adultsintheirspecificcontextandgathersinformationforembeddingthedataconductedinthe

qualitativeanalysiswithyoungadults(WP5)andtheanalysisoftheskillsupplyanddemandon

thelabourmarket(WP6).Theanalysisfollowsthreeapproaches:First,thissub-studyconducts

deskresearchonregionalriskprofilesasasecondaryanalysisofquantitativedataatnational

and local level. Second, analysing the regional living conditions of young adults by identifying

localriskprofiles.Third,assessingthequalityoftheavailablestatisticaldata(availability,classi-

ficationofthetargetgroup,etc.)byaddressingcontextspecificdatagaps.Theanalysisuseddif-

ferentdatasourcesonnational(e.g.Eurostat)andlocallevel(e.g.GermanMicrocensus).

This national Briefing Paper is divided into three parts: First, a short overviewon the

methodsoflocaldatacollectionincludingadescriptionofmismatchesofthedataclassification

used in common international databases with the German regional conceptualisation of the

FunctionalRegions.Second,ananalysisofthelivingconditionsalongthefollowingdimensions:

theeconomic,demographic,educationandtraining,labourmarket,socialinclusionandpartici-

pationaswellashealthandwell-being.Inouranalysis,weareabletoidentifyseveralanddif-

ferentriskfactorsforyoungadults,whicharecloselylinkedto:

• first,theavailablepersonalresourcesintermsofthesocialbackground,thesocialposi-

tion,thepersonallabourmarketandeducationalstatus,and

• second, regional dimensions like the housing situation and the status of the regional

apartmentmarket, theaccesstohealthcare, theregionalshareofpovertyorthesitua-

tionoftheregionallabourmarket.

TheGermancaseingeneralandthetwoFunctionalRegionsBremenandRhein-Maininparticu-

larclearlyshowthatthesedimensionsareinfluencedbysocialpolicy.Furthermore,theavaila-

bledatarevealsthat,dependingontheindicator,astableshareof10-30%ofthepopulationis

notwellsociallyintegratedanddependentonsocialtransfers.

Subsequently to the findings, thedataassessmentalongtheavailability,representation

andqualityofthedataisdescribed.Finally,thereportconcludeswithemergingissues.

Thefollowingsub-chapterprovidesanoverviewonthedatagatheringprocess.

10

2. Methodologyanddescriptionofthedatacollectedatlocallevel

Basedontheoveralltheoreticalperspectivesoftheproject(cf.Weileretal.,2017a)theresearch

objecthasbeenconceptualisedalongthelivingconditionsofyoungadultsintheirregionalset-

tings.Asyoungadultsareheterogeneousgroupsregardingtheirlivingconditions,suchassocio-

economicstratification,theirlifeprojectsandperspectives(cf.Weileretal.,2016)theyaredif-

ferently affected by structural developments. Each setting can provide (or preclude) specific

opportunities foryoungadults’ lives, asLLLpolicies fitdifferently in the local contexts,which

canrevealhiddenresourcesorhindranceforindividualgrowthandsocialinclusion.Therefore,

growingupinaspecificregioncanbemake-or-breakforyoungadults,especiallyastheyhave

differentneeds, in creating their life courseas someregionsmake it easier to create their life

projectsthanothersdo.Againstthisbackground,theanalysisofthesocio-economiclivingcondi-

tionsallowstoassesstheparticularitiesandconditionsoftheregions,whichcanexacerbaterisk

foryoungadultsbuildingtheirlifeprojects.

Thephaseofbeingayoungadultisakeyperiodoftransitionaspivotaldecisionsarebe-

ingmade.Somemightpursuefurthereducationandtrainingorstarttheirworkingcareers,en-

gagewithsociety,develophealthhabitsandcreatetheirlivecourse(cf.Wutzkowsky&Weiler,

2016).However,beinginbetweenyouthandadulthoodcanalsoincreasevulnerabilityandrisk:

Poverty,migration,lackofjobopportunities,accesstohealthcareetc.,canproduceand/oren-

hancevulnerablesituationsforyoungadults,especiallybytheregionalcontext(cf.Weileretal.,

2016).Astheresourcesonsitemayvarysodoestheriskforyoungadultslivinginthoseregions.

Forinstance,alackofworkingopportunitiesinspiteofanextensiveformaleducationcanlead

tolong-termunemployment,thusenhancingvulnerablesituationsandcanevencauseexclusion

ofparticipating in thesociety.ThisaffectsyoungadultsalreadyconstructedbyLLLpoliciesas

being in vulnerable positions even more, as they differ from a notion of a standardized life

course.ThetargetgroupsofLLLpoliciesaremainlydescribedalongtheirdeficits,forinstancein

needforfinancialsupport,havinglefteducationtooearlyorfacinginequalities(cf.Bittlingmayer

etal.,2016b;Wutzkowsky&Weiler,2016).Asaresult,beingatriskcanputyoungadults ina

disadvantageincreatingtheir lifecourseandbeingconstructedaspotentiallybeingatrisk,can

exacerbate inequalities and hinder social inclusion. LLL polices canmake a difference for the

young adults by levelling out structural riskswhen they take the construction of their target

groupsintoaccountandpayattentiontothepoliciesfitwiththeregionalpossibilitiesandlimi-

tations.Thus,thisBriefingPaperofregionalriskprofilesinformsfuturepolicydecision-making.

Departingfromthisconceptualisation,thereportprovidesregionalriskprofilesofyoung

adultsalongsocial,regional,genderandethnicbasedinequalitiescreatinglifeopportunitiesor

obstaclesandmanifesting ineducationalandschool-to-work transitions.Thismeans todistin-

guishbetweendifferentcontextstheyareembeddedinsuchasthedemography,thestructureof

theeconomy, the inputsandoutputsof theeducationand training system, the labourmarket,

11

thematerial livingconditionsandcivicparticipation inpoliticalandsocial lifeand, finally, the

health conditions and individual well-being. As this transition is steered by LLL policies, the

skillsandformal/non-formalqualificationsofyoungadultsintheselectedregionalcontextsare

central,especiallytheeffectsofeducationalattainmentqualificationinrelationtotheentrance

tothelabourmarket.

TherisksprofilesareinformedbystatisticaldatawhicharealsowidelyusedinLLLpoli-

cies processes as part of thedescription, coordination and implementationof LLLpolicies for

youngadults.Thisleadstothequestionwhichkindofdataisavailableandhowdoesitconstruct

thetargetgroupaspotentiallybeingatrisk,suchasearlyschool leavers(ESL)andyoungper-

sons‘NotinEducation,EmploymentorTraining’(NEET).TheimplementationofLLLpoliciesis

notonlyaquestionofpolicycoordinationandmatchingofthedifferentcontextsandinterests,

butratheraquestionofassessingtheinformationonwhichthepolicy-makingisbasedon.1Chal-

lengesarise,asthestatisticaldataisnotalwaysavailabletoprovidetherequiredinformationor,

theavailabledataiscomparableacrosstheEU,yethasregionalgaps.Thiscancausedifficulties

forpolicy-makingprocesses,asitisnotalwaysclearwhatdatacouldtellaboutthelivingcondi-

tions.Therefore,wealsocriticallyanalyse theperspectiveon thedatagatheringprocess(data

availability,protection,etc.),dataoperationalisation(agegroups,targetgroups,etc.)aswellas

overlappinglevelofgovernance(researchunit,administrativeunit,etc.)asa(re)constructionof

youngadultslivingconditions.Foradetailedassessmentofthequalityofdatapleaseseechap-

ter4.

Forthesecondaryanalysisofregionalriskprofiles,acoresetofdata(Eurostat,UNESCO,

OECDetc.)wasprovided.However, thesedatabasesaggregate thedata in regionalunitsalong

territorial administrative responsibilities, the so-called Nomenclature des unités territoriales

statistiques(NUTS),aimingtoprovidecomparabledatabasedonhierarchicalstructures,which

differsfromtheprojectsconceptregionalunits(cf.Parreiraetal.,2017b,p.10ff.).Thisischal-

lenginginthecaseofthetwoGermanFRsastheprovidedregionaldataclassificationdoesnot

fitourcase(seeFig.1below):EitherwehavetoassembleeachFRalongseveralNUTSunitsor,

we only use the smallestNUTS 2,which is a lot smaller than our FRs.The former implies an

overlap with other regions not included in our conceptualization, which sustainably distorts

datavaluesandwouldgeneratedifferentriskprofiles.Choosingasmallerunittakeslossofdata

intoaccount,however,itrepresentstheFRs’core:fortheFRBrementheNUTS2levelunit‘Bre-

men’ (including thecityofBremenandBremerhaven)andrespectively for theFRRhein-Main

theunit‘Darmstadt’wasused(includingthecitiesDarmstadt,Frankfurta.M.,Offenbacha.M.and

Wiesbadenandtheirsurroundings).

1InYOUNG_ADULLLT,twosub-studiesfocusonthecoordinationandmatchingofthecontextandtheinterests.First,aqualitativesub-study(WP5)withperspectiveontheyoungadults’perceptionandexpectationsandsecond,acom-parativeanalysis(WP6)withperspectiveonthepolicycoordinationoflocalactors(cf.Weileretal.,2017b).

12

Figure1FunctionalRegionsinGermany

13

Source:Ownelaboration

AsthedatacollectedwithEurostat,UNESCOandOECDisavailablemostlyonNUTS2andrarely

onNUTS3,thedataisrepresentedinadministrativeunitsandthushaslimiteduseforthede-

scribingthetwoFRs.Thedifferentconceptualisationofregionseithercollectdataalongpoliti-

cal,social,andeconomicalunits(FunctionalRegion)oralong jurisdictionalrights(administra-

tiveunit)(seeFigure2below).

Figure2DifferentFormsofRegions

Source:translatedfromEckey,Schwengler&Türck(2007,p.7)

However,toensurethecomparabilityintheproject,thefiguresintheBriefingPaperweredraft-

edonNUTS2basis,andthencomplementedwithlocaldataonthedistrictlevel.Thus,thelocal

datareconstructsthelandscapeofourresearchunitandrepresentseachFunctionalRegionsas

closeaspossible to the local level alongdistricts and cities (seeTable1below).Thedifferent

dataunitsarelabelledasfollowedinthesubsequentdataanalysis:Whenthedatareferstothe

NUTS 2 level, we use the label ‘NUTS 2 level Bremen’ respectively ‘NUTS 2 level Darmstadt’;

14

when the data is collected along the local district level and represents the spatial unit of our

FunctionalRegions,weusethelabel‘FRBremen’respectively‘FRRhein-Main.

Onthenationallevel,themainsourceforthelocaldatacollectionareregisters.Especial-

lytheinteractiveonline-atlasoftheFederalInstituteforResearchonBuilding,UrbanAffairsand

Spatial Development (INKAR, Online-Atlas des Bundesinstituts für Bau-, Stadt- und

Raumforschung)2wasused,asitnotonlycollectsdatafromothernationalregistersinGermany,

butalsoprovidesdatathatencompassesmetropolitancitiesaswellasmunicipalitydistricts.

Table 1Overviewon the data collation for the two FunctionalRegionsRhein-Main andBremen

Administrativecitiesanddistricts

FRRhein-Main FRBremen

Cities Frankfurta.M. BremenOffenbacha.M. BremerhavenWiesbaden DelmenhorstDarmstadt OldenburgMainz WilhelmshavenWorms Aschaffenburg

Districts Bergstraße AmmerlandDarmstadt-Dieburg CloppenburgGroß-Gerau CuxhavenHochtaunuskreis DiepholzMain-Kinzig-Kreis FrieslandMain-Taunus-Kreis OldenburgOdenwaldkreis OsnabrückOffenbach OsterholzRheingau-Taunus-Kreis VechtaWetteraukreis VerdenGießen WesermarschLimburg-Weilburg VogelsbergkreisFuldaAlzey-WormsMainz-BingenAschaffenburgMiltenberg

Besidesthespatialrestrictionoftheresearchunits,dataforadditionalindicatorshadtobegath-

ered inorder todescribe theGermancontext, as risk ismainlyunderstoodasa financial risk,

suchaspoverty,itsinterrelationtoalackofskills,suchasliteracy(cf.AutorengruppeBildungs-

berichterstattung,2016,p.6,p.17)orasahealthrisk(cf.RobertKoch-Institut,2016).However,

additionalsourcesofriskareimportantaswell:Forexample,duetothesovereigntyoftheLän-

2Availableunder:http://www.inkar.de/Default[lastaccess:10July2017]

15

der in Germany3, the educational system is characterised by different school tracks providing

differentopportunitiesforthetransitionintowork.Inturn,findingworkishighlylinkedtothe

qualificationgained in theeducational systemas the labourmarket couplesqualificationwith

occupation,stressingtherelevanceofcertificationsoverskills.Therefore,thedescriptionofre-

gionalriskprofileshastofocusontheregionalembodimentofinstitutionsasdifferentregions

providedifferenteducationalsystemsandlabourmarketopportunities(cf.Weileretal.,2017b).

Both,thedatacollectiononnationalandregionallevelconformstoethicalstandardsand

dataprotectionregulations.Thetargetgroupforthedatacollectionareyoungadultsintheage

of 18 to29, howeverdifferent age rangeswere consideredwhen suitable as thedata sources

complybothwithnationalandEuropeanlegislation.Therefore,datacollectionbelowandover

theagerangeof18and29complieswithStandardsofEthicalConduct(cf.ParreiradoAmaralet

al.,2017a).

Thefollowingsub-chapterprovidesthefindingsthelivingconditionsofyoungadultsinthetwo

FunctionalRegions.

3. Findings

Thefollowingsub-chaptersdescribethecontextuallivingconditionsofyoungpeopleinthetwo

FunctionalRegionsRhein-Main andBremenalong the followingdimensions: (1) demographic

characteristicsofthepopulationanditssubgroups;(2)structureoftheeconomy,(3)inputsand

outputsoftheeducationsystem;(4)labourmarketsituation;(5)redistributionandsocialinclu-

sion,and(6)healthconditionsandindividualwell-being.


GermanyisthefourthlargestcountryintheEUwith357,000km2.BothFRsvarygeographically

and structurally, with the FR Rhein-Main being the larger region, both geographically and in

termsofpopulationdensity,spreadingacrossseveralmainlocationsandcities.Whilethesmall-

er FR Bremen covers an area of 3.8% of Germany (13.750,97 km2)with 3.3% of the German

population (approx. 2.7million inhabitants), the FR Rhein-Main covers a larger area of 4.1%

(14.755,3km2)with6.5%of theGermanpopulation(approx.5.3million inhabitants)(Statisti-

scheÄmterdesBundesundderLänder,Deutschland,2017;Zensus,2011).Thecontrastingpop-

ulationstructureisreflectedbythepopulationdensity:whileintheFRBremen1.413,16livein

eachkm2,theamountalmostdoublesfortheFRRhein-Mainwith2.440,96inhabitantsperkm2.

However,thepopulationinRhein-Mainisspreadinitscoreoverfivecitieswithatotalof716,96

3InGermany,thepolicyisorganizeddifferentlyinthe16federalstatesresultingindifferentjurisdictions,struc-tures,andlegislationsaffectingeducationandtraining,welfareandsetsdifferentframeworksforpolicymaking(cf.Parreiraetal.,2017b,p.36f.).

16

km2–Offenbacha.M.,Frankfurta.M.,Mainz,DarmstadtandWiesbaden–whileinFRBrementhe

populationismainlylocatedinthethreecitiesBremen,BremerhavenandDelmenhorst,cover-

ingtogetheranareaof482,2km2(INKAR,2017).4ThedifferenceswithinBremencorresponds

totheexpecteddifferencebetweenurbanandruralareasinGermany–asmallcorewithsparse-

lypopulatedagricultural surroundings–while in theFRRhein-Main the core is formedby its

tightlykniturbanmetropolitanareawithanintensivesocialmobility.

Currentpopulationdevelopmentshowsanoverallpopulationdecreaseofanoldergrow-

ingsociety,whichdemographicallybenefitsfromthemigrantinflow(seeFig.3below).InGer-

many,thepopulationdecreasedfrom2005to2014from82.5millionto80.8millioninhabitants,

adevelopmentmirroredintheFRBremen,howevernotintheFRRhein-Main.WhileDarmstadt5

iscontinuouslyexpandingastheirinhabitantsaregrowingfrom3.77to3.82million,Bremen6is

shrinkingfrom663thousandto657thousandinhabitants(NUTS2Level).Itseemsthattheur-

banmetropolitan area is growing faster by attractingmore inhabitants than themore urban-

ruralareaofFRBremen.

Inthelastyears,migrationhasbecomeanimportantaspectofthedevelopmentofthepopula-

tion,affectingbothFunctionalRegionsevenly,asthecruderateofnetmigrationincreasedfrom

1per1,000 inhabitants in2005 to4.9% in2009, and in2015 to14.3% (seeFig. below).One

reasonforthisdevelopmentistheinflowfromcrisisregions,inGermanythesocalled,“refugee

crisis”. Migrants live mostly in the metropolitan cities, notably Frankfurt a.M. with 20.1%,133,530 of all its inhabitants, opposed to an overall smaller share in FRBremenwith 82,910

migrants;however, theystillconstitute15.4%of itsoverallpopulation(StatistischeÄmterdes

Bundes und der Länder, Deutschland, 2017; Zensus, 2011). The naturalization ratesmirror a

similar,yetratherunevendistributedinflowasFRRhein-Mainfacesahigherinflow(in2015:FR

Rhein-Main11,545personsandFRBremen3,529persons).However,thisaffectsthemetropoli-

tancoreFrankfurta.M.with22%toalesserextentthanthecityofBremenwith43.5%(ibid.).7

Thiscouldbedue to thehigh livingcosts inFrankfurta.M.,as theaveragerentingprice is14

EUR/m2, one of the highest inGermany, especially compared to the city of Bremenwith 9,06

EUR/m2andtheGermanaverage(7,97EUR/m2).8

4 The population in the 5 largest cities in the FR Rhein-Main area distributed as followed: Offenbach am Main:5.499,50;FrankfurtamMain:4.961,90;Mainz:4.206,20;Darmstadt:3.556,30;Wiesbaden:3.437,70.Thepopulationinthe3largestcitiesintheFRBremendistributesasfollowed:Bremen:2.878,30;Bremerhaven:2.499,60;Delmen-horst:2.486,20)(INKAR2017).

5Theadministrativeunit ‘Darmstadt’ includesthecitiesDarmstadt,Frankfurta.M.,OffenbachamMain,Wiesbadenanditssurroundingareas.

6IncludingthecityofBremenandBremerhaven.

7 For both regions, themain immigration region is Europe, followed by Asia: In 2015, in the FR Bremen 54.29%(1,916)fromEuropeand30.32%(1,070)becamenaturalized,whileintheFRRhein-Main56.65%(6,540)fromEu-ropeand24.99%(2,885)fromAsiabecamenaturalized(ibid.).

8ForBremen:https://www.wohnungsboerse.net/mietspiegel-Bremen/3193ForFrankfurta.M.:https://www.wohnungsboerse.net/mietspiegel-Frankfurt/3242[lastaccess:20Aug.2017].

17

Figure3Cruderateofnetmigration(1per1000),fertilityrateandolddependencyratefrom2005to2015,NUTS2Level

Source:EurostatDemographyandmigrationdatabase

The high living costs also restrict young people from creating a financially and socially a-self

determinedlifeasthehighcostspreventthemfromcompetingonthehousingmarket.Instead,

therateofyoungadultslivingwiththeirparentsrapidlyincreasedoverthelastdecade.In2013,

this rate was 50.1% (20-29 years), which is under the European average (55.4%), however,

highly stable over time (2005: 45.9%; see Fig. 4 below). The data shows that today’s young

adults grow up under different circumstances and deal with different limitations (high living

costs,uncertaincareerpath,prolongededucational trajectories,etc.),whichhinder them from

moving out of their parents’ home and achieving financially independent lives. Specifically,

youngadultsunder25–whoarerecipientsofwelfarebenefits(HarzIV)–arefurtherprevented

fromgainingautonomybythe legalregulationsofsocialprogramsandlabourmarketpolicies.

Since 2005, young people are hindered frommoving out of their parents’ home without the

agreementoftheJobcenteriftheyortheirparentsreceivewelfarebenefits(cf.SGBII-§22Abs.

5).Thechangedhouseholdstructuresreflectgenderdifferences,asmoreyoungmalesareliving

withtheirparentsasopposedtoyoungfemales.Overahalfofthemalegenerationbetween20

and29is livingathome(2006:57.2%;2013:60.1%)opposedtowomen(2006:32.8%;2013:

39.4%) (EUSILC). Therefore, demographic changes and the risk of social exclusion are closely

interlinkedtosocialandlabourmarketpolicies.

-0.5

0

0.5

1

1.5

2

2.5

3

-5

0

5

10

15

20

25

30

35

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Bremenfer4lity Darmstadtfer4lity Germanyfer4lity

Germanymigra4on Bremenmigra4on Darmstadtmigra4on

GermanyOlddependency

18

Figure4Rateofyoungadults(20-29)livingwiththeirparentsbygenderfrom2006to2013;nationalLevel

Source:EU-SILCmicrodata

While thenumbersofmigrantsareontherise, the fertilityrate isonlymoderately increasing,

both inGermanyandthe tworegions:While inGermany, from2005to2014, the fertilityrate

increasedfrom1.34to1.47.ItroseintheFRBremenfrom1.47to1.57andintheFRRhein-Main

from1.38to1.47(INKAR,2017),however,stillundertheEU-28averagefrom1.51to1.57(Eu-

rostat). As career choices and founding a family are main biographical decisions for women

(Keddi&Pfeil,1999,p.13)thedifferentopportunitiesfortheircompatibilitybetweenruraland

urban areas becomes obvious. It seems, that the cities rather attract workforce than people

planning families, as the fertility rate is stable on a low value in large cities, such asBremen,

BremerhavenFrankfurta.M.andDarmstadt,however,risesinmoreruralareas,suchasthedis-

trictVerdenintheFRBremen(from1.52to1.73,INKAR,2017).However,thereseemstobean

interlinkagebetweenthestructures,opportunitiesforeducationandworkandthefamilyplan-

ningprocess,aslivinginbigcitiesseemstohaveaneffectonwomentopostponethislifedeci-

sionasthisprovidesdifferentopportunities.Theaverageageofwomenhavingtheirfirstchildis

increasinglypostponingfromtheageof28.7in2005totheageof29.5in2015–adevelopment

slightlyabovetheEU-28averageof28.9in2015(UNIDEMO).9WhileinFRFrankfurtpostponing

motherhood is prominent,most likely due to a prolonging of formal education, in FRBremen

earlymotherhoodunder the age of 20 is observable – the agewheremostly transitions from

9 The data sets for the EU 28 countries are only available from 2013 to 2015. Available under:https://data.europa.eu/euodp/en/data/dataset/aahacCLN1mWh03eaNJSMjA[latestaccess:26Sept.2017].

30

35

40

45

50

55

60

65

2006 2007 2008 2009 2010 2011 2012 2013

EuropeanUnion(27countries) Germany Germanfemale Germanmale

19

education intowork takeplace (cf.Goebel,1996,p.144ff.).For instance, inFrankfurta.M. the

motherhoodfromage40to45rosebetween1995-2014from7.4%to17.6%–surpassingthe

Germanaver-ageof4.4%respectively10.9%.Incontrast,duringthe lastdecadeBremerhaven

hadanaverage21.8%ofyoungmothers,doublingtheGermanaverageof10.5%(INKAR,2017).

In the case of Bremen, this could reveal a risk profile that is shaped by socioeconomic disad-

vantagesandloweducationalexpectationsintheirfutureandalowprospectiveonjobopportu-

nitiesasearlymotherhoodcanbeusedasasubstituteforlackofotheropportunities(cf.Wittel-

Fischer,2000,p.111).

Despitethismoderateriseofthefertilityrates,aswellastheriseoflatemotherhood,the

German population is ageing: from 2005 to 2016, the old-dependency rate10 increased from

27.8%to32%andthe lifeexpectancyrosebetween2005to2014from79,4to81,2years–a

developmentmirrored in the twoFunctionalRegions.11However,at thesametimetheyoung-

agedependencyisgoingdowninGermany,from21.6%to20.2%,adevelopmentalsomirrored

bybothFRs.Thus,Germanyfacesdemographicchangesasthepopulationisgettingincreasingly

older,howeverisoverallgrowingthroughanincreasingmigrantinflow.

Regarding a comprehensive perspective on risk factors caused by the demographic

structure,thesituationisambivalentforyoungadults.Ontheonehand,thereareundoubtedly

recentdevelopmentsthatcausestressfulsituationsforyoungadultslikethehighrentsinurban

areasthatcomealongwithaforcedprolongationtolivewiththeparentsortheuncertaintiesof

careerplanningleadingtoapostponementinfamilybuilding.Ontheotherhand,recentpublic

discoursesrenewtheclaim forbetteradulteducationbecauseof the forecasted lackofskilled

workers in thenear futureasaconsequenceofashrinkingpopulation.However, thisambiva-

lence materializes differently in our two regions. While the population of Frankfurt a.M. in-

creased,duetoworkerinflow,thepopulationinBremendecreasedanditsinhabitantspostpone

theirlifeprojectsofhavingownchildren–whichcontainsinitselfmedicalrisks(e.g.stillbirth,

miscarriage,andectopicpregnancy;cf.Stein&Susser,2000).Thelifecourseopportunitiesde-

scribed along the demographic structure shows interlinkages to the economy, which is de-

scribedinthefollowingchapter.

10Theoldold-dependencyrateistheratiobetweenpopulationaged65andovertopopulation15-64(DefinitionbyEurostat).

11FortheadministrativeunitonNUTS2Level ‘Darmstadt’,representingthecoreoftheFRRhein-Main,anincreasefrom26.0%to29.6%canbeobserved,whilethetwounits‘Bremen’and‘Weser-Ems’,representingFRBremen,Raisefrom29.9%to32.2%respectivelyfrom26.7%to30.4%(Eurostat).

20

3.2 StateoftheEconomy

InGermanyandbothFRsthestateoftheeconomyisovertheEU-28average;however,thedis-

tributionoftheproductivityandwealthishighlyfragmented(see.Fig.5below).Particularlythe

FRBremenisfacingstructuralchangesduetothere-anddeindustrialisationelevatingthedif-

ferencebetweenitsruralandurbanareas.Itsmaineconomicdriveristhelogisticssectordueto

itsseveralharbours.However,theshipbuildingsectorfacesseverechangesasaconsequenceof

the automation in the harbour industry using progressive systems for operating processes

whichminimize the need ofworkforce. As a result, the number ofwarpings are reduced, alt-

houghsimultaneouslytheexportandimport-orientedtradeandindustries, for instanceitscar

manufacturers, are expanding. Additionally, its more rural areas gain their economic profit

mainly in theagricultural sector.Thus,FRBremen is facedwithachangingprofileof itsmain

industrieswithachangeddemandofworkers(cf.Weileretal.,2017b,p.49f.).Thesefragmenta-

tionsaremirroredbythedistributionsofthehighgrossdomesticproductpercapita(GDP)as

thelabourforceisconcentratedinthecoreoftheregionprofitingfromtheeconomicproductivi-

ty.However,theamountvariesdependingiflocaldataisusedordataonNUTS2level.Bremen’s

GDPonNUTS2levelisapprox.2,500EURabovethenationalaverage(seeFig.5below),while

usingregionaldatarevealstheFRisbelownationalaverage–althoughitslightlyraised inre-

centyears(2006:24,320EURto2014:29,690EUR).Thus, thewealth isunevenlydistributed,

providingfinancialriskforthoselivingandworkinginmoreruralareas.

In contrast, FRRhein-Main, andespecially its corearoundFrankfurt a.M., isoneof the

wealthiestregions inGermany–andmost likely inEurope(cf.Bittlingmayeretal.,2016a). Its

uniqueeconomicdensityonservicesandindustry,duetoitsfinancialdistrict,airport,tradefair

andmedia sector, attracts the settling from large national and international companies. This

resultsinaneconomicallygrowingurbanterritory,howevermainlyinitscorenotinitsperiph-

ery.TheeconomicperformanceoftheFRRhein-Mainisremarkablewith38,830EUR,as itex-

ceedsthenationalaverage(GDP35,900EUR/capita)andletalonethecityofFrankfurta.M.is

with91,300 EUR up to 330%of the EU-28 average (27,600EUR/ capita). The region around

Darmstadt (NUTS 2 level), including the cities Frankfurt a.M., Darmstadt andWiesbaden, are

withcontinuouslyapprox.10,000EURupto130%abovenationalaverage–wideningtheeco-

nomicdisparitiestoitsperipheralregions.Incontrast,thecityofBremenhaswith47,300EUR

thehighestamountintheFRBremen,exceedingtheGermanaverageof130%–however,thisis

notevenhalfoftheamountofthecityofFrankfurta.M.(Euostat,INKAR,2017).12

12AsthedataprovidedbyEurostatusesdifferentresearchunits,whicharesmallerthanourFRs,thedatawascom-pletedbylocaldata,whichshowsoverallthesametrend,howevertheabsolutenumbersvarypositivelyforGermanywith1000EURperinhabitant.ForthiscompletioncalculationfromINKAR(2017)wereusedwhichanalyseGDPinEuroperinhabitantatcurrentmarketpricesusingEurostatRegioDatenbankaswellastheworkinggroup»RegionalAccounts«.

21

As a result, these data reveal both, fragmentations between the Functional Regions as

wellaswithinthem:TheeconomicdifferencebetweenbothFRsrevealseconomicdisadvantages

basedontheregionalsettings,mostlikelyresultingfromlabourproductivityinspecificsectors.

Onlyaspecificproportionof labourforcegainsfromthematerialwealthbylivinginaspecific

areaandworkinginaspecificfield.ThematerialwealthofbothFRsisconcentratedinitscore

citiesandwidens thegap to itsperipheral regions, leaving thosebehindwhocannotafford to

liveortoworktheinthesecities(cf.sub-chapters3.1&3.4).

Figure5GDPineuroperinhabitantsPPSandlabourproductivity(rightax,EU=100),Germany,BremenandDarmstadt,NUTS2-Level,2006-2015

Source:EurostatEconomyandfinancedatabase

Although the economic prosperity of both regions is above the EU-28 level, theywere evenly

negativlyaffectedbythefinancialcrisis in2008/2009asboth, theGDPper inhabitantandthe

gross value added rate (GVA), decreased and recovered after 2010: The GDP dropped from

30.600EURto28.700EUR(see.Fig.5)andtheGVAdecreased56.4%to54%(FRBremenfrom

50.3%to48.2%;FRRhein-Mainfrom61.6%to58.6%;cf.INKAR,2017).Thelabourproductivity

measurestheamountofGDPproducedbyanhouroflabourandahighamountmeans,thatthe

economyisabletoproducemoregoodsandservicesforthesameamountofwork;thiswasthe

caseinGermanybeforethefinancialcrisiswithitspeakin2007(127.3%,i.e.,27.3%higherthan

the EU-28 average, counted 100%) and levelling off between 2010 (124.9%) and 2015

(126.1%). The recovery of the labour productivity can also indicate a shift of the labour for-

mationperse,forexampleasautomatedprocessesofworkorspecializationoftheworkforce–

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20,000

25,000

30,000

35,000

40,000

45,000

50,000

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Germanlabourproduc4vity(EU=100) EU28GDP

GermanyGDP BremenGDP

DarmstadtGDP

22

especiallyastheGDPisstillgrowinginthesametimespan.Asaresult,theworkforce–especial-

lyyoungadults–eitherarereplacedbynewtechnologiesorareforcedtocompetewithhigher

specializedworkersonthelabourmarket.

Theeconomicstrengthaffectsthetworegionsdifferently,astheshareoftheGDPisnot

closely linked to a specific structure of economic sectors. Especially the rural and agriculture

areas in the FR Bremen, have little economic strength, as this sector contributes remarkably

little to the overall GDP (0.76% compare to 1.8%EU-28 average). Its strength rather derives

from the contributions to the second (industry) and third (services) sectors,which hardly di-

verges from the EU-average (share of industry on GDP for Germany: 29.4%, EU-28 average:

26.46%,WorldBank).However,thesesectorsare,asmentionedabove,locatedinspecificareas

ofeachregionpromotingdisparitiesduetolimitedaccess.

Table2SizeofenterprisesinGermanyandEU-27from2010to2014,%

Sizeofenterprises Total From0to9

personsem-

ployed

From10to

49persons

employed

From50to

249persons

employed

250persons

employedor

more

EU-27in2010 21,801,180 92.45% 6.22% 1.02% 0.19%

Germany2010 n.a.13 89.68% 8.12% 1.88% 0.31%

FRBremen2010 n.a. 88.05% 9.68% 1.98% 0.28%

FRRhein-Main2010 n.a. 90.78% 7.26% 1.66% 0.28%

Germany2012 2,189,737 82.31% 14.68% 2.53% 0.49%

FRBremen2012 n.a. 87.55% 10.02% 2.12% 0.30%

FRRhein-Main2012 n.a. 90.31% 7.65% 1.72% 0.30%

Germany2014 2,497,694 83.57% 13,74% 2.24% 0.44%

Source:EurostatEconomyandfinancedatabase&INKAR2017,owncalculations

ComparedtotheotherEUcountries,theeconomiccrisishadashort-termimpactontheGerman

economyasboththerealestatepricesandthedisposableincomeforhouseholdswasrelatively

stable(cf.sub-chapter3.5).However,astheGermaneconomicstrengthmainlyfromitsexport,

theoverallglobalcrisishadsevereeffectsonitseconomicstrengthderivingfromtheexportof

consumergoods(e.gcars,investments)(cf.Roos,2009,p.392f.).Itseconomicstrengthismainly

producedbyenterpriseswithmorethan250employees(2010EU-27:0.19%,Germany:0.31%)

–allinallaboveEUaverage(seetable2above).Theyproduce68.2%oftheturnoverand52.9%

oftheGVAopposedtoaturnoverof6%bymicro-enterprises,12%oftheGVA(cf.Söllner,2016,

p.3).Asbothregionshavethesameshareoflargeenterprises,theireconomicdifferencesmost

likelyderivefromtheregionaldifferencesalongthesectors.However,duetoalackofregional

data, we can only assume those difference, for instance in the sector of manufacturing

13Nodataavailable.

23

(4,112,399 empl./ 1,614,474 EUR) opposed to transportation and storage (1,084,732 empl./

181,210EUR)(StatistischesBundesamtDestatis,2017).14

Correspondingly,thenumberofmicro-enterprisesissignificantlylowerthantheEU-27

average,evendecreasingsince2010–adevelopmentnotnecessarilymirroredbythetwoFRs:

theyaremoresuccessfullyimplementedintheouterrimoftheFRRhein-Main,whileintheFR

Bremensmalltomedium-sizedcompaniesaremoreprominent(INKAR,2017).15Itseems,that

the“SmallBusinessAct”passed in2008 fosters thegrowthofsmallbusiness in thoseregions.

Nonetheless,Germany’seconomicstrengthderives from itsexportsectorby largercompanies

participatinginforeigntradesize(cf.Söllner,2016,p.4).However,thesmallerenterprisespro-

ducealowereconomicstrengthandprovidelesserjobopportunities.In2014inGermany,only

20%ofallemployeesworkedformicro-enterprisescomparedto39%hiredbylargeenterprises

(cf.StatistischesBundesamt,2016).16

Astheproportionspersectorvary,theregionsprovidedifferentpossibilitiestobehired.

Whilethepublic-sectorisdeclining(2008:7.3%,2014:7.1%),thenumberofemployeesinthe

tertiary sectoraswell as educational andhealth sectorare increasing. Since theunificationof

Germany,thenumberofpublicservantswasreducedbyonethird(bpb,2013),adevelopment

mirroredbybothFRsmarkingastructuralchangeconcerningthegovernmentasemployer.In

bothregionstheemploymentratedeclinedbetween0.7%and1.1%between2008-2014(NUTS

2level,Eurostat).Thus,headingintoacareerinthepublicsectorcandevelopintoacareerrisk.

Thisrevealsgenderproblems,asthepublicsectorhasoneofthesmallestgenderpaygapof8%

withratherhighwages(19.24EUR/hour).On thecontrary, theeducationalandhealthsector

provide vacancies, however with different wage opportunities (Education: 20.08 EUR/ hour;

Human health and socialwork: 16.87 EUR/ hour).17 Both sectors are fostered by a change in

social policies focusing on early childhood education. Since 2005 the staffing conditions have

changedby implementing theTagesbetreuungsausbaugesetz (TAG,day care expansion act) re-

spectivelyKinderförderungsgesetz(KiföG,lawforthesupportofchildren),guaranteeingthelegal

14Availableunder:https://www.destatis.de/EN/FactsFigures/EconomicSectors/Service/Tables/SiD_01_EnterprisesPersonsTurnoverCapitalformation.html[lastaccess:20July2017].

15ThedataprovidedbyEurostatislimited,bothinitsavailabilityasinitsrepresentation.Eurostatonlyprovidesdatafor theEU-27 for2010, and forGermany for2012and2014.Therefore, thedata is complementedwithdata fromINKAR.However,thedatarepresentationvaries,asEurostatdistinguishesbetweencompanysizesfrom10to19and20to49;classificationthatissummedupintheGermandatagatheringprocess,mostlikelytotheGermandefinitionof theMittelstandweresmallandmedium-sizedcompanies,most-oftenfamilyowned,gain importancefortheGer-maneconomy.Therefore,theprovidedEurostatdatawassummedupinordertobecomparabletotheGermandatarepresentation.

16Availableunder:https://www.destatis.de/EN/FactsFigures/NationalEconomyEnvironment/EnterprisesCrafts/SmallMediumSizedEnterprises/Current.html[latestaccess:26Sept.2017].

17Availableunder:https://www.destatis.de/EN/FactsFigures/NationalEconomyEnvironment/EarningsLabourCosts/EarningsEarningsDifferences/Tables/GPG_ByEnterprise.html[lastaccess:20July2017].

24

claimonadaycareplaceaftertheageofoneyear.EspeciallyinBrementhissegmenthasgrown

morethanonethirdinsevenyears,from6.7%to8.8%markingadramaticshiftintheregional

labourmarket(2008-2014,).Onthecontrary,thehealthandsocialworksectorisincreasingin

Darmstadt(2008:9.2%;2014:10.7%;NUTS2level,Eurostat).

Theeconomicconditionsofthetworegionsprovidedifferentrisksforyoungpeople,as

thewealthandeconomicproductivityisunevenlydistributed:Whilethecoreofbothregionsis

rather wealthy, its periphery hardly profits from economic prosperity as especially the large

enterprisesareinthecoreoftheseareas.Atthesametime,thehighlivingcostsinthecoreareas

precludeitsinhabitantslivingandworkinginthehighlyprofitablecoreareas,producingamis-

matchofeconomicopportunitiesandfinanciallimitations.Gainingaprofitablejobopportunity

meansspendingmostofthewageforthelivingcostsorcommuting(seesub-chapter3.1).Thus,

autonomyandfinancial independenceseemstobeatstakeforyoungadultsstarting intotheir

careers. Simultaneously, the regions face structural changes providing risks for career paths:

ThreeoftheprominentsectorsintheFRBremen,agriculture,watertransportandlogistics,are

onadecline,however,ratherlowwagessectors(e.g.health,socialwork)provideastable,orin

thecaseofFRRhein-Main,increasingjobmarket.Thedecouplingbetweentheoveralldevelop-

mentofwealthinGermanyandthestagnationofwagesinindustriesispartoftheexplanation

whysignificantlymoreyoungadultsstaylongerwiththeirfamilies(cf.sub-chapter3.4).These

conditionscanleadtoarethinkingofyoungadultsinmakingtheirfinanciallivingdecision:in-

steadofinvestingtimeinalow-paidapprenticeshipwithprospectsofalow-paidprofessionin

theservicesector, itcouldleadthemdirectlyintothelabourmarket.Thiscancauselong-term

consequencesforthemontheoccupationallabourmarket(seesub-chapter3.4below).

The following chapter describes the education system context for young adults promoting or

hinderingopportunitiesintheirlifecourse.

3.3 Educationsystem

Theeducationsystemasacontextofyoungadults’livingconditions,describesthepositionsand

settings inwhichtheyareembedded inviewof theaccess,attainment,outputsandpoliciesof

educationandthuspavesthewayintothelabourmarket(Checchietal.,2014;Allmendinger&

Leibfried,2003;Pawson&Tilley,1997).Onecharacteristicof theGermaneducationsystemis

thefocusonqualifications,ratherthanonskillsoron-the-job-traininginfirms,withatightcou-

plingofcertificatestothelabourmarket(cf.Weileretal.,2017b,p.12).Thishighlightsthefor-

mationintheschoolsystemanditsoutputintheformofqualificationsprovidingopportunities

orobstacles forthe labourmarkettransitionastheregionsrequiredifferentspecificqualifica-

tions:highandlowqualifiedworkersinthemoreindustrialBremenopposedtoahighvarietyof

workersinthemoreservice-orientatedareaaroundFrankfurt(cf.chapter3.4below).

25

ThestrongGerman federalpoliticalsystem is importantas theeducationsystem isor-

ganisedunderthesovereigntyofthefederalstates,particularlyaffectingthetworegionsasthey

are spread over five different federal systemswith heterogeneous policies, access and output

rates.18Theverticalisationandstratificationoftheschoolsystemsleadstodifferenthighlyseg-

mentedtracksandahighstandardisationoftheeducationalandtrainingsystem(cf.Parreirado

Amaraletal.,2017b,p.11f.)Thisstructureisalsoinfluencedbytheamountofeducationalex-

penditure(Biggartetal.,2015).Withinthelast15years, theexpensesontheGermanysystemincreasedfrom4.3%to4.94%ofthenationalGDP(UNESCO),withapprox.60%inprimaryand

secondary(ISCED0–4)education(AutorengruppeBildungsberichterstattung,2016,p.38).This

riseisnotsurprising,asGermanycanbecharacterisedasasocial-conservativestatewithmod-

eratetohighpublicfunding.Additionally,themedia-stirred‘PISA-shock’discussionsinGermany

ledtoseveralreformschangingtheeducationalsystem(cf.ParreiradoAmaraletal.,2017b,p.

11; Bittlingmayer et al., 2016c; Grek, 2009, p. 29ff.), especially regarding the early education

system.Thepoliciesaimtoprovidechildcareundertheageofthree(cf.sub-chapter3.2);there-

fore,by200584.6%ofthe4-years-oldwereineducationnationwide(by2012:95.8%)andin

Bremen93.1%.19

Theearlytrackingleadstoearlydecisionsunderhighuncertaintyasthedifferenthighly

segmented tracks offer different opportunities of qualifications for young adults. LikeAustria,

theGermaneducationsystemhasafirstdivisionattheageof10atthebeginningoflowersec-

ondaryeducation.Afterthat,pupilscantransitionintothreegeneralschooltracks:Hauptschule,

Realschule, andGymnasium. For studentswith special needs there is a separated and in itself

highly fragmented school track (Sonder- or Förderschulen;~4%of each cohort) (cf. Powell&

Pfahl,2012).Besidesthecharacteristicofaverticaldifferentiation,thesystemhasatraditionof

separating between academic and vocational education (cf. Bittlingmayer et al., 2016a, p. 5f.),

both attainedbypupils in almost equal shares in upper secondary education: in 2015, 53.2%

wereenrolledinthegeneralprogramand46.8%inthevocationalprogram(Eurostat).

Theseuppersecondaryschoollevelsplayanimportantroleinthetransitionfromschool

to labourmarket as theyprovidedifferentqualificationoptions,paving theway intodifferent

careers. Especially the Gymnasium provides the general higher education entrance certificate

(Abitur),whichenablesstudentstoenteruniversity.Since1995,thenumberofgraduateswith

anAbiturhasincreasedabout9.15%to33.4%in2014,mirroredinbothFRs,howevertoadif-

ferentextent:WhiletheFRRhein-Main iscontinuouslyaboveGermanaverage(1995:25.63%,

2014:38.58%),theFRBremenincreasesitsnumberataslowerpace,remainingunderthena-

18Duetothefederalstatessystem,theschoolforsupplystructureisheterogeneousandvarieswithaminimumofthreeuptosixdifferentschoolforms.TheFRRhein-Mainoverlaps3federalstatesallhaveeach6differentschoolforms,whileFRBremenoverlapstwofederalstateswith3respectively5differentschoolforms(cf.AutorengruppeBildungsberichterstattung,2016,p.74).19ThedatareferstoBremenonNUTS2Level.NodataisavailableforDarmstadt.

26

tional average (1995: 22.28%, 2014: 28.5%).However, theGymnasium is not the onlyway of

reachingtheAbiturasthestructureoftheuppersecondarysystemischangingnationwideoffer-

ingnewintegratedschooltrackseithersubstituteorintegrateHaupt-andRealschuleaswellas

toopennewpathstotheAbitur(AutorengruppeBildungsberichterstattung,2016,p.73).

TheHauptschule in particular has been the target of reforms, leading to its steady decline of

around 10% since 1995, both nationwide as well as in the two regions, due to demographic

changes and the increased importance of theAbitur as a prerequisite for entering the labour

market.IntheFRBremen,theschoolhasthehighestattainmentlevelsinitsverynorthernand

rural district Friesland (over 20%)while in the FR Rhein-Main the highest attainment levels

over20%are in its regional corewith the cityofOffenbach, the closeneighbour toFrankfurt

a.M., and the Bavarian part of the FR (INKAR, 2017). This change has led to a creaming out-

process20andattendingaHauptschuleismeanwhilelinkedwithstigmatisationandstereotypes

(Solga&Wagner,2001;Kraemer&Bittlingmayer,2001;Ditton,2013).Itmarksariskfactorof

itsownasthetransitionfromthelowersecondaryschoolsystemintothedualsystemsofVET

hasbecomemarginal,mostlyduetolabourmarketdemands(cf.Weileretal.,2017b).

Figure6Shareofstudentsintertiaryeducation(20-24)from2005to2012,NUTS2,%

Source:EurostatEducationandtrainingdatabase

20The‘creaming-out-process’describesthetransitionoftop-performingstudentsintohighereducationinstitutions,leavingthosebehindfromsocio-economicunstablefamilies.Asaresult,theeducationopportunitiesonlyimproveforacertaingroupofstudents,however,creatingeducational limitations for thealready financiallydisadvantagedstu-dents.

20

30

40

50

60

70

80

90

2005 2006 2007 2008 2009 2010 2011 2012

Germany Bremen Darmstadt

27

The VET consists of three systems: the dual system (Duales System), the school-based

trainingsystemwithoutanin-firmtraininginvocationalschools(Schulberufssystem)andatran-

sitionssystem(Übergangssystem),whichdoesnotleadtoaqualificationtoenterintoaprofes-

sionbutratherimprovestheopportunitiestoentertheothertwoVETschoolsystems(cf.Kohl-

rausch, 2012). This leads to a postponement of their entrance into the labourmarket,with a

stable share of approx. 28% NEETs since 2000 (Autorengruppe Bildungsberichterstattung,

2016,p.103ff.).Incontrast,asteadilyincreasingnumberof20%ofstudentswithanAbituren-

ters thedualSystem(ibid.,p.105)competing in theVETsystemwithstudents fromtheother

schooltracks.

Thedevelopmentoftertiaryeducation(20-24years)isdynamic,astheshareofstudents

rosebetween2005and2012(seeFig.7),alsomirroredbyDarmstadt.Onthecontrary,inBre-menthenumbersdecline,however,theattainmentlevelwashighertobeginwith(NUTS2level,

Eurostat). Comparedwith local data,we can observe that the number of students enrolled in

universitiesinbothregionshasfairlyremainedonthesamestableleveloverthelast20years

(cf.INKAR,2017).

Figure7ComparisonoftheISCED(0-8)educationlevels(25-64)of2005and2014,NUTS2level,%


Contrary to tertiaryeducation, theparticipationrate inadulteducation israther low. In2005,

16.7%oftheGermans(age25to34)participatedinadulteducationortraining,slightlyincreas-

ing until 2016 (18.8%), still being above EU average (EU-27 in 2005: 15.8%; 2016: 17.7%).

16.958.5 24.6

13.159.8 27.1

25.852.7

21.5 19.554

26.5

18.2 53.827.9

15.2 52.832

ISCED0-2 ISCED3-4 ISCED5-8 ISCED0-2 ISCED3-4 ISCED5-8

2005 2014


28

However,slightdifferencesbetweenthegenderscanbeobserved:While20.2%of themale in

thispeergroupparticipateineducationortraining,just17.3%ofthefemaleparticipated.How-

ever, these differences seem to be limited to adult education and training, as the educational

level generally rose in Germany, equally attended by both genders. While the share of low-

educatedstudents(ISCED0-2)decreasedfrom16.9%to13.1%,wenoticeastaticsituationwith

regardtotheamountofpeoplewithupper-secondaryeducation(ISCED3-4:in2005:58.5%;in

2014:59.8%).However, theshareof thehighly-educatedpeoplerose in this timeperiod from

24.6to27.1%.

Incontrast,thesecondaryeducationattainmentbetweentheagesof30-34(ISCED3-4),slightly

decreased between2005 and2014 from58.5% to 56%, equally for both genders (men: from

58%to55.9%;women:from59%to56.2%),howeverincreasedforthesameagegroupinthe

tertiaryeducationattainment(ISCED5-8)from26.1%to31.4%(seeFigures7&8below).Both

regionsareincreasinglyadjustingintheirtertiaryeducationattainment,prolongingtheformal

educationopportunitiesfortheiryoungadults.Especiallywomenprofitfromthisdevelopment

astheysteadilyincreasetheirattainmentlevelsfrom24.1%to30.8%comparedto28%to32%

ofmen(Eurostat).

Figure8Tertiaryeducationattainment(ISCED5-8)(30-34)from2005to2014NUTS2Level,%


Besides the structure and the expenses, the quality assessment of the education system also

plays an important role, forwhich especiallyPISA is a commonlyuseddenominator. In2015,

10

15

20

25

30

35

40

45

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014


29

Germanpupilsgainedameanscoreof505 innumeracyand491 in literacy(EUaveragewere

respectively491and492).However,thegroupofyoungadults(20-29)isnotablyaboveEUav-

erage:In2012,youngpeoplehadameanscoreinliteracyof290(EU:272)andinnumeracyof

288(EU:262)(Eurostat),wellaboveEUaverageinthemeasuredcompetencelevels.

Those that are neither in employment nor in education and training (NEETs) are per-

ceivedasbelongingtoaparticularlyvulnerabletargetgroup(cf.chapter2).InGermany,therate

ofyoungNEETS(15to24years) iscomparably lowtotheEU-27(seeFig.9below).However,

theratesvary locally: InBremen, theshareofNEETswasslightlyaboveGermanaveragewith

9.4%in2016opposed toaslightly increase inDarmstadt from6.4%to7.3%(cf.LSF,NUTS2

level).Comparedtotheeducationalattainmentlevels,itseemsthatBremenimprovedtherates

of tertiary education, however, has fluctuating rates ofNEETs. In contrast, theFRRhein-Main

alreadyhashightertiaryattainmentlevelsandseeminglystableratesofNEETs.

Figure9NEETrate(15-24)andearlyschoolleavingrate(18-24),from2005-2015NUTS

2-Level,%

Source:LSFmicrodata

In sum andwith a view to the risk profiles of young adults, the German education system is

characterised by a tight coupling of certificates and building occupational biographies. This is

discussedunder the label ‘academisation’asan increasingnumberof studentscontinues their

formaleducationafteruppersecondaryschool,bothinGermanyasawholeaswellasinthetwo

regions.Firstly,theratesofstudentsgainingtheschoolleavingcertificate(Abitur)forentering

highereducationissteadilyontherise.Secondly,therestructuringoftheGermanschoolsystem

0

2

4

6

8

10

12

14

16

18

20

BremenESL DarmstadtESL GermanyESL

EU28ESL Bremen,NEET Darmstadt,NEET

EU27NEET Germany,NEET

30

has led to a reduction of lower secondary school tracks (Hauptschule), however hardly to an

integration of Schools for Special Needs Education (Sonderschulen or Förderschulen or

Förderzentren)intothegeneralschooltracks.Thirdly,ahighnumberofstudentsisenrolledin

thetransitionsystem(Übergangssystem),waitingtoentertheVETsystem,competing,however,

withthestudentsfromhigherschooltracks.Theprolongingofformaleducationiscloselylinked

totheoccupationallabourmarket,ascertificatesareapreconditionforanoccupation(seesub-

chapter 3.4 below). In this sense, being at risk is paved and reinforced by the school system

youngadultsattend,bothforthesubsequentchancesbeingincludedinthe labourmarketand

forfacingstigmatisation.

The obstacles they face are hardly levelled out by LLLpolicies or theVET systemand

thus, enhance the risk of facing fragmented occupational biographies.Firstly, the overarching

significance of educational certificates for the employers and the comparatively little signifi-

canceofadulteducationandfurthertrainingexacerbatesthecreationofastableandpredictable

life course for studentsbelowhigher formaleducation.Thesegroupsbuild thecoreof the so-

called “functional illiterates” inGermany,which isoneof themost important target groupsof

LLL-policies (Grotlüschen, 2012; Bilger, 2012; Riekmann & Buddeberg, 2016). Secondly, even

successfully finishing dual vocational education and training can lead into occupational risk-

careersasjobswhicharehighindemandcanleadtoasurplusofworkers.Themainavailable

andcontinuouslyexpandingqualificationsleadtojobsthatareinthelowwagessector,suchas

hairdresser,motorcarmechanic (besides thebig enterprisesof the famousGerman car indus-

try), butcher, or nurse, with nearly no chances of advancement (cf. MAIS, 2017; Lohnspiegel,

2017).Thus,thediscoursesonthelackofskilledworkersseemsneithertobefilledbystudents

ofhighereducationnorbyapprenticeships,asthematchingofthecertificatesandtheneedsof

thelabourmarketaretightlyknit.Asaresult,thelowpermeabilityoftheinstitutionalarrange-

mentsoftheGermaneducationsystemhardlyenhancestheequalityofopportunitiesforyoung

adultsatrisk.

Thefollowingchapterdescribesthestructureoftheyouthandlabourmarketforyoungadults

promotingorhinderingopportunitiesintheirlifecourse.

3.4 Labourmarket

The differentways inwhich young people can participate in labourmarkets affects their life

opportunitiesandsocial identities (cf.Höfer&Straus,2001,p.91f.). In theGermandiscourse,

‘beinginwork’isnotnecessarilyequatedwithhavingajob,ratheranoccupationshapingthelife

course:Whileajobdescribesatemporarylimitedactivityallowingahighflexibility,anoccupa-

tionaimstoprovidelong-term,systematicallytrainedandqualifiedactivity,shapingone’siden-

tity(“Berufsträger”Straus&Höfer,1998,p.280).Thus,inGermany,thequalificationsgainedin

31

theeducationsystemsareapreconditionforanoccupation.Inthissense,thestratificationofthe

educationalsystemismirroredbytheoccupationalsystemcausingalowpermeability(cf.Shavit

&Müller,1998).

Againstthisbackdrop,thefragmentedyetdistinctlabourmarketstructuresandoppor-

tunities(cf.sub-chapter3.2)ofthetworegionsaffectyoungpeople.Theopportunitiesarehighly

coupledtotheeducationsystem:the‘wrong’certificatecanleadintounemployment,nocertifi-

catesurelywill.Thesystemdoesnotintenda‘switch’betweenoccupations,whichisaccompa-

niedbypresumedlossofproductivity(cf.Kambourov&Manovskii,2009).Asaresult,theDual

System,beingthemostimportantstrainoftheVETsystem,providesemployerswithanotionof

whattoexpectfromacertaintypeoftraining(Hall&Soskice,2001)andisapreconditionforits

occupational labourmarket (cf. ParreiradoAmaral et al., 2017b, p. 15). Therefore, the rather

low unemployment rate, especially compared to other EU-27 countries (see Fig. 10 below),

couldleadintolong-termunemploymentorprecariousworkingsituations.Withinthepastten

years, the ratesdecreased remarkably (2005:11.2%;2015:4.6%,age20 to64).Although the

rates foryoungpeople (15-24)wereslightlyhigher tobeginwith (2005:15.5%) thenumbers

havebeenreducedbyhalf(2015:7.2%).Thereductionoftheratesisalsomirroredbythetwo

FRs: inBremen, from16.8% to5.6%and inDarmstadt from8% to4.1% (NUTS2 level, LSF).

Complimentarily, theemploymentrates (age20-64)arehigh,both inGermanyand in the two

regionsandremainedunaffectedbythefinancialcrisisin2008and2009(LSF).

Figure10:youthemploymentandunemploymentratesforyoungpeople(15-24),EU-27,Germany,BremenandDarmstadtonNUTS2-Level,2005-2015

Source:EurostatLabourmarketdatabase,LFSmicrodata

0

10

20

30

40

50

60

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

EU27unemployment GermanyunemploymentBremenunemployment DarmstadtunemploymentEU27employment GermanyemploymentBremenemployment Darmstadtemployment

32

Althoughtheunemploymentratesaredecreasingforbothgenders,theunemploymentratesof

womenarelowerasopposedtomen(e.g.inGermany2015,males:5.0%,females:4.2%).How-

ever, thedatacoversahighnumberofundetectedcases, forexamplehousewivesandpersons

willingtoworkbutunregisteredassearchingforwork(cf.Hahnetal.,1995;Beck,2008).Inthe

national statistical data gathering process, these groups are considered inactive and thus not

includedinthestatistics.Theunemploymentratecancoverriskofprecariouslivingconditions,

aspausingfromemploymentcausesareducedpaymentinpensionschemes.Especiallywomen

areaffectedbyold-agepoverty,astheirfragmentationofthelifecoursethroughpausesishighly

encouragedbytheGermangovernment,forinstanceforchildcare,beingahousewifeorhavinga

part-timejob(cf.StatistischesBundesamt,2016,p.38f;cf.ParreiradoAmaraletal.,2017b,p.17,

sub-chapter3.5).Opposed towomen in theretirementage, thecurrentgenerationofworking

women(18-64) is facing theseprecarious livingconditions later in lifeas theyalready face fi-

nancialstrainsduetounemployment,part-timeemploymentandlowincomeresultinginmate-

rialdeprivation (ibid.).This especially effects theFRBremen, as thegenderdifferences in the

employmentrateshaveonlybegundiminishingsince2014,whileDarmstadtalreadyhasasta-

bleemploymentrateforbothgendersofover40%(NUTS2level,LFS).Thiscouldleadtolimited

possibilitiesforpartakinginthelabourmarket,forinstanceifacarisnecessaryforcommuting

oramovetoanothercityistooexpensiveyetapreconditionforajob.

Againstthisbackground,theyouthunemploymentratesvisualizetheinternalheteroge-

neitywithintheregionsasthemoretightlykniturbanareasofFRRhein-Mainhavelowerrates

thantheFRBremen.WhileinDarmstadt(onNUTS2Level)theunemploymentratesareshrink-

ing(2005:12.1%2015:to7.0%)inBrementheratesareratherhigh(2005:19.3%).Especially

thecitiesofBremerhaven(2014:13.6%)andWilhelmshaven(9.7%)havehighrates,evenmore

obviousincontrasttothehighestrateswithinthecitiesofFRRhein-Main(Worms:8.6%,Offen-

bach:8.2%)(INKAR,2017).Itseems,theunemploymentratesinFRBremenfluctuate,whileFR

Rhein-Mainslowlybutsteadilyreduceditsrates.Althoughthelong-term-unemploymentandthe

youthunemploymentratio21showsaverypositivetrendinthelasttenyearsitrevealsastable

shareofvulnerableyoungadultsmostlikelyheadingintoadultunemploymentbetween3,1%in

theageof15to29(long-term,unemployment;2008)and4,8%intheageof20to29(Eurostat).

Theexclusionofyoungpeoplefromthelabourmarketcausesvariousdebilitatingeffects.

Thefinancialstrainsresultinanoveralldecreaseoflifetimeearningsenhancingtheriskofpov-

erty(cf.StatistischesBundesamt,2016,p.40f).Earlyunemploymentcanhave long-termnega-

tive“scarringeffects”(Øivind&HolmReiso,2011,p.3)bymissingearlycareerexperienceand

beingperceived,or ‘scarred’,witha lackof individualskillsorproductivityasopposedtoper-

ceivestructuralobstacleshinderingthemtoparticipateinthelabourmarket.Asaresult,access21Theyouthunemploymentratiomeasurestheshareofunemployedyoungpeopleamongthewholeyouthpopulation(either15to24-year-oldpersonsor20to29-year-oldpersons).

33

tounemploymentcanbedecisiveforsubsequentlong-termsuccessastheymostlikelyfaceun-

employmentagain(ibid.).Especially theFRBremen isconfrontedwith theeffectsofearlyun-

employment,bothon the individual level (e.g. stigmatisation,health issues, lackofmotivation,

etc.)andstructurallevel(e.g.highercostssocialwelfaresystem,lossoflabourmarketproduc-

tivity).

Itisassumedthattherearefourcontributingfactorstothedifferencesintheyouthunemploy-

ment/employmentrates:

1. Theinterlinkageofsocialandlabourmarketpolicieslinkingunemploymentbenefits

andsocialwelfare.

2. Weakerlegalemploymentprotectionforyoungworkers.

3. Longerformaleducationpostponingtheentranceintothelabourmarket.

4. Regionaldifferencesincontrastinglabourmarketsleavingthosebehindwithamis-

matchoftrainingandjobopportunities.

First,since2005theso-called“Hartz-laws”22wereimplemented,reformingtheunemployment

benefitsbylinkingthemtowelfarebenefitsasanoverallstrategyoflabourmarketpolicies.Due

to thisreformofactivation(workfarepolicy), receivingbenefitspayment for long-termunem-

ploymentisboundtoacontractwithpubliclaw:thebeneficiariesofthepaymentareobligedto

agreetoimprovetheirjobsituationinacceptinganykindofjob–arefusalcanotherwiseleadto

reduction/ complete suspensionof thebenefits. This interlinkage also explains theoverall re-

ductionof expenditures in labourmarket policies as they arepartially substitutedwith social

policies (cf. Lessenich, 2009; Gerdes & Bittlingmayer, 2012). In 2005, Germany spent slightly

morethan3%oftheGDPforlabourmarketpolicies–thehighestvalueacrossallthecountries

analysedinYOUNG_ADULLLTand50%abovetheEUaverage(EU-28:2.0%ofGDP).However,

thisexpendituredecreasedaround50%withinthefollowing10years(2015:1.5%ofGDP).

Second,thelegalemploymentprotectionisweaker,particularlyforyoungworkers.With

theEmploymentPromotionActfrom1985companieshavethepossibilitytoextendfixed-term

contractingfornewentrantstothelabourmarket(cf.Buchholz&Kurz,2008,p.54;cf.Parreira

doAmaraletal.,2017b,p.13).Thisleadstoa‘yo-yo-effect’withphasesofemploymentandun-

employment,promotingafragmentedlifecoursewiththeconstantsearchforthenextemploy-

mentbypassinguncertainty.Thus, labourmarketpolicies contribute toa fragmentationof life

courses–regardlessofskillsets,certificationorlabourmarketsector.

22TheHartz-lawstrytoredefinetherolebetweenstateandsubjectandlimitcivilrightsofunemployedpersonsandestablishalabourpolicyofactivation,i.e.thatunemployedpersonsneedtoprovepermanentlythattheyarewillingtowork,acceptingforinstanceworseworkingconditions,timecontractsandsoon(cf.Lessenich,2009;Dörre,inpress).AsoneconsequenceoftheHartz-IV-law,theamountanddurationofunemploymentbenefitswereshortenedtooneyearand60to67%ofthepreviousnetsalary,regardlesstheageandworkhistory.TherearemanysimilaritiestotheBritishWorkforcepolicyunderToniBlair(cf.Dixon,1999,2000).

34

Third,theparticipationinhighereducationisconstantlyincreasingwhichleadstoapostpone-

mentof theentrance intothe labourmarket(seesub-chapter3.3).Andfourth,regionaldiffer-

ences in contrasting labourmarketspromote and foster theneed for specific jobs as a conse-

quenceoftheregionalstructuralchanges(cf.sub-chapter3.2)leavingthosebehindwithamis-

matchoftrainingandjobopportunities(ParreiradoAmaraletal.,2017b,p.24f.).Especiallythe

FR Bremen has a highly dynamic and contrasting labourmarket, however still offers a large

amountofjobsinproductionplants.Asaresult,thelabourmarketishighlypolarized,withfocus

onhighandlowskilledworkerconstantlyreducingthemediumskilledworkers(cf.Autoretal.,

2003).Incontrast,theFRRhein-Mainoffersabroadervarietyofjobs(e.g.finance,media),how-

everwithaworldwidejobcompetitionwhocompetewiththepotentialworkersonsite.Inthis

sense, theGerman labourmarket creates an interlinkageof life course and careerpathwhich

leadsintoahighprecarityforthosechoosingorforcedtochooseanon-matchingvocation.Par-

ticularlyasbothregionsattracthighskilledworkersinthecorespreadingtheremainingskilled

jobsinitsperipherycausingprecarioussituationsforNEETsandearlyschoolleavers.

Despite theoverallpositiveeconomic situation inGermanyandemployment rates, the

problemsfor–acomparativelysmalleramount–ofyoungadultsaremoreorlessthesamelike

in the other EU-countries. In terms of the interplay between youth and labourmarket, to be

youngisariskfactorofitsowngiventhesignificantagedifferencesinalltherelevantindicators

mentionedabove(e.g.unemploymentrateetc.).However,thereisarelativelynewriskfactorfor

young adults, particularly forGermany: a successfully acquired vocational certificate doesnot

prevent unsecure occupational biographies. Since the 1980’s, the wages in twelve traditional

industriesareinthelow-paysector(MAIS,2016).Thus,receivingtrainingandworkinginthose

industries is a risk in itself.Weassume thatnot vocational trainingper se lowers the risk for

youngadults,butrathervocationaltraininginspecificareas,bothavailableandwithareasona-

blecompensation.Thisisparticularlyachallengeforyoungadultslivinginurbanareaslikethe

citiesFrankfurta.M.orBremenwithhighrentsonahighlycompetedapartmentmarket.

Thefollowingchapterdescribesthemateriallivingconditionsforyoungadultsalongtheredis-

tributionandsocialinclusioninthetwoFunctionalRegions.


Ineverycountry,certaingroupsfacebarrierspreventingthemfromparticipatinginthesocial,

economic and political sphere of society. However, social participation is even more difficult

under conditions of poverty as it can lead to social exclusion and, as a consequence prevents

citizensfromcreatinganautonomouslife(Eurofund,2015,p.5).Thus, fromasocial-economic

perspective,socialinclusionandredistributionofwealtharecloselylinked,asthematerialliving

conditionsareacrucialminimumrequirementtoavoidpoverty.Thewelfarestateisagovern-

35

mentalconceptofprotectingitscitizensbypromotingsocial,economicsecurityandsocialrights

byensuringtheredistributionofwealth(cf.Esping-Andersen,2014,p.140).

InGermany,thewelfarestateisratherconservativeasitoperatesalongtheprincipleof

subsidiarity,however,onlyafterthefamilies’possibilitiesforsupportareexhausted.Thebene-

fits system is constructed along former contributions to the system that have been made

throughemployment.Thisperpetuatesgenderdifferences,aswomenareencouragedtosupport

thefamilyopposedtojointhelabourmarket(cf.ParreiradoAmaraletal.,2017,p.17;cf.sub-

chapter 3.4).Here, regional differences canbe observed as the legislations unfolds differently

amongst and within the regions. First, the possible wealth is dispersed differently. Although

thoselivinginthecorearemorelikelytoparticipateinthewealthoftheregionastheperiphery,

thoselivingintheFRRhein-Mainaremorelikelytofaceadivergenceofrichandpoor(cf.sub-

chapter3.1).Second,thebenefitssystemshavedifferentshort-andlong-termtargetgroups,as

in theFRBremen theyouthunemployment rate ishigher than inFRRhein-Main. In the long-

term,thiscontainstheriskoffuturephasesofunemploymentleadingtorecurrentlypaymentof

benefitsandsubsequently reducedpayment into the social system(taxes, insurances,pension

etc.).Thisperpetuateswomenevenmore,asthedoublepressureofmakingalivingandstarting

a family cancauseseveralpauses fromemploymentandhasnegativeeffectson theirpension

plan,however,ishighlyencouragedbythestate(cf.sub-chapter3.4).

Against thisbackgroundof theprincipleof subsidiarity thehighexpendituresof social

protectionhavetobeenread.TheGermanoverallnetexpenditureinsocialprotectionrosefrom

24.8%to26.6%oftheoverallGDPbetween2007-2014.Thisrathermoderaterisewashowever

influencedbythe financialcrisis,as thestrongest increasetookplacebetween2008and2009

(from25%to28%ofGDP).23InGermany,thespendingisratherhigh:in2014,thegovernment

spent10.324,72EUR/ inhabitant,being130%wellaboveEU-28averageof7.904,73EUR/ in-

habitant(Eurostat;ESSPROS).InlinewiththeGermanwelfarestate,anditsstate-basedhealth

care insurance providing accessible health care (cf. sub-chapter 3.6), themain share of social

protectionisspenthere(2005:7.9%;2014:9.7%).Duetothestrongnotionofthefamilysup-

portsystembeforegovernmentalbenefits,thereisonlyaslightriseintheexpendituresonfami-

lyandchildren(from3.0%to3.1%)andsocialexclusion(from0.1%to0.2%)–however,con-

tinuouslyunder theEU-27averageof0.5%andthe lowestofallparticipatingcountries in the

project.Onthecontrary,thespendingforpensionandretirement(9.6%to9.0%)aswellasso-

cialprotectionbenefitstocounteractunemployment(from2.0%to1.1%)decreased.Thus,fami-

ly,socialinclusionandpensionsarenotontheforefrontoftheexpenditureofsocialprotection,

althoughGermanyfacesdemographicchangesofanageingsociety(cf.sub-chapter3.1).

23According toESPROSS, expenditureon social protection is provided tohouseholds and individuals affectedby aspecific setof social risksandneeds.Availableunder:http://measuring-progress.eu/social-protection-expenditure-current-function-gross-and-net-espross[latestaccess:14Aug.2017].

36

Thedisposable incomeforhouseholdsdescribesthematerialconditionsoftheregions,

astheamountofmoneyearnedeachyearaftertaxesandtransfers,andthus,representingthe

money available for spending on goods or services. In Germany, it is relatively stable and

amongst thehighest intheEU.However,duetotheeconomiccrisis, theamountstagnatedbe-

tween2008-2009(seeFig.below).LivingandworkinginthecoreoftheFunctionalRegionshas

apositiveimpactonthewealthofitsinhabitants,although,notallinhabitant’sprofitfromit,due

toGermanysincreasingincomeinequality(Darmstadt:21,600PPS,Bremen:19,700PSS,NUTS

2-Level). Since 2006, it surpasses the EU-27 average consistently (Germany: 56.4%; EU-27:

51.9% in 2015), following the general trend of widening the gap between rich and poor (cf.

OECD,2011;Piketty,2014).Inthetimespan2005-2015theGinicoefficient24ofequivaliseddis-

posable income (Fig. 11 below),which shows the concentration of incomewent from45% to

56.4%,surpassingtheEUaverage(EU-27:2005:49.7%;2015:51.9%).Also,householdwealthis

muchmoreunequallydistributedthanincome.In2012,therichest10%ofGermanhouseholds

owned59.2%ofoverallhouseholdwealth, the fourthhighestshareof17countriesstudiedby

OECD.(cf.OECD,2016,p.102f.).

Figure11:GINIindexbeforeandaftertransfers,disposableincomeinthehouseholdsinPPS(rightax),EU-27,Germany,NUTS2LevelBremenandDarmstadt,2005-2015


24TheGinicoefficientmeasurestheextenttowhichadistributiondeviatesfromaperfectlyequaldistribution.Inthiscase,GINIisappliedtoequaliseddisposableincomewithinacountry.Ingeneral,itrangesfrom0to100,howeveritcouldalsobeexpressedon1-pointscale.Acoefficientof0expressesperfectequalitywhereeveryonehasthesameincome,whileacoefficientof100expressesfullinequalitywhereonlyonepersonhasalltheincome.

0

5,000

10,000

15,000

20,000

25,000

0

10

20

30

40

50

60

70

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

EU27GINIbefore GermanyGINIbefore

EU27GINIaSer GermanyGINIaSer

Germanydisposableincome Bremendisposableincome

Darmstadtdisposableincome

37

The risk of poverty and social exclusion is under the EU-27 average and one of the lowest

amongst the projects countries (only Finland and Austria are lower). However, its increase

seemsnotaneffectof the financial crisis,butoccurredbefore it.The riskmainly increased in

2005from18.4%to20.2%in2006andremainedonthatstablelevelthroughoutthecrisis,even

recoveringshortlyafterthecrisisin2010(19.7%)(Eurostat;EU-SILC).25Thus,theseveremate-

rial deprivation rate, the inability to pay for basic living supplies26,was affected by the crisis

(2005:4.6%,2009:5.4%).

These developments can particularly be a risk for receiving long-term unemployment

welfarebenefits,duetothecouplingsocialandlabourmarketpolicies(cf.sub-chapter3.4).The

socalled‘Hartz-IV-law’referstotheUnemploymentBenefitII,whichallpeople“capableofwork

andeligibleforbenefitscanreceive”(BundesagenturfürArbeit,2017).Thesecanbeforpersons

whoareunemployed longer thanoneyear (or in special casesoneandahalf year)orpeople

who enter the labourmarket after school/VETwithout successfully getting a job.On average,

personsbeingonunemploymentbenefitsreceive399EUR/month,plus440EUR forhousing,

withslightlydifferentdistributionsperregion(StatistikderBundesagenturfürArbeit,2017).

To sumup this subchapter in terms of risk profiles: Germany has undoubtedly a very

strongeconomyandastabledemocracybutontheotherhand,aconstantshareofpeoplede-

pendsonsocialwelfare.Germanyfailedinthelasttenyearstoreducethisratesubstantially;on

thecontrary,theincomeinequalityincreasedsignificantlyaswellasthenumberofpeoplewho

areworking on a low-income base. Being at risk varies remarkably along the regional differ-

ences,especiallywithintheFunctionalRegions.Forinstance,in2014,forachildthechancesof

receivingsocialtransfers–anoften-usedpovertyindicator–arethreetimeshigherinthecities

Bremerhaven(37.2%,FRBremen)orOffenbach(34.8%,FRRhein-Main) than in thecitiesOs-

terholz(9.3%,FRBremen)orthecityofFulda(9%,FRRhein-Main). TheriskforthoseinBrem-erhavenorOffenbachisevenfive-tosixtimeshigherthanintheBavarianpartofFRRhein-Main

Aschaffenburgwith6.1%(INKAR,2017).Thus,theregionitselfseemstobeastrongpredictorofpoverty,forcingyoungadultstobemobile.However,iftheyareforcedtostayindisadvantaged

districtslikeBremerhavenorOffenbachforseveralreasons–forinstance,asthequalifications

areonlyacceptedlocallyortheyareresponsibleforthehealthcareoftheirparents–thenthe

neighbourhoodturnsdirectlyintoariskfactorfortheirbiographiesaswellasfortheirpartici-

pationinLLL-policies.

25ThereisnodataavailableonNUTS2LevelforGermanregions.

26Severematerialdeprivationrateisdefinedastheenforcedinabilitytopayforatleastfourbasicitemssuchas:1.topaytheirrent,mortgageorutilitybills;2.tokeeptheirhomeadequatelywarm;3.tofaceunexpectedexpenses;4.toeatmeatorproteinsregularly;5.togoonholiday;6.atelevisionset;7.awashingmachine;8.acar;9.atelephone.

38

Thefollowingchapterdescribesthehealthandwell-beingconditionsofyoungadultsalongthe

redistributionandsocialinclusioninthetwoFunctionalRegions.

3.6 Healthandwell-beingconditions

InGermany,localdataonhealthishardlyavailable.Mostofthedataishighlyaggregatedonthe

national level,however,rarelyonthe levelof federalstatesoronregional level,ascentralized

healthdatacollectionhardlyexists.Thus,datafrominternationalsurveys,asinEurostat,aggre-

gatestheGermanhealthdataonacomparativelyhighlevel.Asaresult,thissub-chapterdiffers

fromtheothersregardingtheillustrationoftheindicatorsaswerefermoretodataonthena-

tionallevelcomparedtothefivesubchaptersabove.

Againstthebackgroundofasteadilygrowinglifeexpectancy(cf.sub-chapter3.1),public

health interventions and medical care improved. During the last decade, the total health ex-

penditure in Germany increased steadily touching 321 billion EUR in 2014 – the highest ex-

penditureamongstEUmemberstates–whichequals3.973EURperinhabitant(EU-28average:

2.235EUR/perinhabitant).Yetinrelativeterms,othercountrieshavesimilarratiosofcurrent

healthcareexpendituretoGDPof11%asGermany(Eurostat).However,duringthelast20years

governmentalhealthcarereformshavebeenimplementedinGermanyaimingtoreducethegov-

ernmentalexpensesinhealthcarefavouringacompulsorycontributoryhealthinsurancesystem.

Thisleadtotheintroductionofahealthcareinsuranceaswellastheintroductionofeconomic

principles(e.g.regulationsbyoutcomesinthehealthsector).In2014,thehealthexpendituresin

Germanywere 6.6%of government schemes – one of the lowest of the EU-28 –while 78.0%

werecoveredbycompulsorycontributoryhealthinsuranceschemesandsavingaccounts–the

highestwithin theEU (260compared to3.059PPSper inhabitant) (Eurostat).Asa result, the

accesstoahealthcareisgranted,however,thestandardandqualityofhealthcarecanvaryon

thewealthoftheinhabitants.

Thesechangedhealthpolicieshadstrongeffectsonthefieldofhealthandmedicalcare

aswellashealthcareaccessinGermany.Theintroductionofastate-basedhealthcareinsurance

ledtoanincreasingnumberofpeopleprofitingfromthisinsurance,simplybecauseoftheageing

society. In theFRBremen, thenumberofofficiallyregisteredcarerecipients increasedsignifi-

cantlyfrom6,089in2009to6,476in2013,whichhasenormousconsequencesforthefederal

expendituresinhealthcare(FHB,2015).Furthermore,ofthenineparticipatingcountriesinthe

project,Germanyhasthehighestnumberofavailablebeds inhospital inthe lastdecade.They

facedonly amoderate reduction in the last tenyears (2005:846,7beds/100,000 inhabitants;

2015:822,8beds/100,000inhabitants,Eurostat).27Theavailablehealthcarestaffmirrorsthese

developments.However,theimprovementoftheratioofmedicaldoctors(2005:339,5/100,000

27Dataforthelong-termcurativebedsper100.000inhabitantsisnotavailableviaEurostat.

39

inhabitants, 2015: 410,8/100,000 inhabitants) aswell as nurses andmidwifes during the last

decade (2005:1.137,3/100.000 inhabitants,2015:1.342,2/100.000 inhabitants) ismost likely

not a consequence of an improvement of the health care system, but rather through a stablequota of medical students (Eurostat). These quotas are highly regulated in Germany by the

states(Bremenhasa largeMedicalFacultyat theUniversityofBremen)andanegativedemo-

graphictrendinGermany.

Thesechanges in thestructureandaccess to thehealthcaresystemmaybe thereason

whyGermanshavea lowerperceptionof theirhealth than theEU-27average.Whenasked in

2015, "How is your health in general?" 64.6% of people in Germany reported to be in good

health, slightly under EU-27 average of 67%.However, the ratio between peoplewho have a

goodandverygoodperceptionof theirhealthand thosewhohaveabadperception is rather

highwith9.3%and in comparativeperspectiveover theEU-27averageof8.7% (cf. Eurostat;

EU-SILC).Notsurprisingly,youngpeopleinGermany,aged16-29,haveabetterself-perception

oftheirhealththantheoverallpopulation,asin201589.1%ofthemperceivedtheirownhealth

asgoodorverygoodyetslightlyundertheEU-27averageof90.8%(ibid.).Thisperceptioncould

alsomirrortheactualhealthstatusinGermany,astherateofhealthylifeyears(HLY)isunder

theEUaverage,measuring thenumberof remaining years that a personof specific age is ex-

pectedtolivewithoutanysevereormoderatehealthproblems.GermanmalesarebelowtheEU-

27averageandhavetheshortestamountofhealthyyearsofallprojectcountries.Onaverage,

theyareexpectedtolive56.4healthyyears,whichamountsfor71.7%oftheirlifespan(in2012:

EU-27: 80.3%, Germany: 74.2%). In addition, females are below EU level (in 2012: EU-27:

75.5%,Germany:70.8%)andamongstthe lowest intheprojectwith56.5healthyyearswhich

estimatesfora67.6%healthylifespan(cf.Eurostat).28

Thesubjectivewell-beingcanbemeasuredintermsoflifesatisfaction(seeFig.below).

Thisallowstodescribeaself-positioningperspectiveonhealthandwell-beingofyoungadults

asanuncoveringoftheirperception.Ingeneral,Germansarequitesatisfiedwiththeirlives.Ona

scale from 0 to 10. Germany rated general satisfactionwith lifewith a 7.3 grade (EU-28: 7.1

grade) and 25%were highly satisfied (EU-28 average: 21.7%). Accordingly, young Germans

(16-24)arehighlysatisfiedaswell,forinstance33%withtheirjob,especiallytheirpeersonthe

EU-28averagewith29.3%(cf.Eurostat;EU-SILC).Notsurprisingly,theseresultsarerelatedto

educationalattainmentandlabourstatus:satisfactionismuchlowerforlow-educated,roughly

equaltothenational-averageforuppersecondaryeducated,muchhigherfortertiaryeducated

aswellasthoseineducationandtrainingcomparedtothosebeingunemployed(ibid.).

Thiscloselinkbetweenthesubjectivehealthstatusandtheindividualpositionintheso-

cialstructureontheonehandandeducationalcertificatesontheotherhandleadstothetopicof

28NodataontheEUlevelfor2014wasavailableviaEurostat.

40

health inequalities which has beenwidely discussed in Germany for fifteen years (cf. Mielck,

2005; Richter & Hurrelmann, 2006; Hackauf & Jungbauer-Gans, 2008; Bauer et al., 2008).

MeanwhilethereisnodoubtthathealthinequalitiesexistinGermanyandthattheypartlyincrease

forallagegroups(Kroll,2010;Lampert,2016).

Figure12Highsatisfactioninvariouslifedomains,age25-34,EU-28andGermany,2013


Healthrelevantriskprofilesforyoungadultsareverysimilartotherisksofbeingpoor,unem-

ployedanddependentonsocialtransfers.Recentstudieshaveshownthatchildrengrowingup

inpoorfamiliesaremore likelytohavepoordental,aremoreoftenaffectedbymental illness,

particularlydepressivesymptoms,andhaveapooreropinionoftheiroverallhealthstatus.Simi-

larpatternscanbeobservedforthecontinuinglifecourseandaccumulateindifferentlifeexpec-

tanciesbetweenthetop20%incomegroupsascomparedtothe20%bottomincomegroupof

nearlytenyearsforbothgender(Kroll&Lampert,2014).Furthermore,healthinequalitieshave

anotherindependentregionaldimension.Inruralareastheaccesstohealthcareandspecialized

healthandmedicalservices,forinstanceintermsofpsychiatricorophthalmologiccare,isprob-

lematic(cf.Bittlingmayeretal.,2009;Bauer,2009).Ontheonehand,healthcareaccessinurban

areasismuchbetter.Ontheotherhand,thegapbetweenrichandpoorpeopleinurbanareasis

muchhigherandleadstonotabledifferencesinlifeexpectancieswithinonetown–nearlysix-

teenyearsofwealthyandpoorquarterswithinU.S.-cities(Wilkinson,2005,pp.14ff.).Butrisks

0

10

20

30

40

50

60Financialsitua4on

Accommoda4on

Jobsa4sfac4on

Commu4ng4me

Timeuse

Overalllifesa4sfac4on

Recrea4onalandgreenareas

Livingenvironment

Personalrela4onships

Meaningoflife

EU28males Germanymales EU28females Germanyfemales

41

forbadhealth,ashortenedlifeexpectancyortheriskofmentalillnessofyoungadultsaremost

ofallthedirectconsequenceofbadlivingconditions,however,notjustariskfactorthatstands

alone(cf.Hoffmannetal.,2014;Borrelletal.,2014).

Foramorelocalorregionalhealthrelatedriskprofile,wecanassumethatthesamevariables

andrelationshipsareverylikelytrue.IntheFunctionalRegionsBremenandRhein-Main,there

is very likely a concentrationofbadhealth statusof youngadults, ofmental illnesses, obesity

a.d.o.inthepoorneighbourhoods,followingthelogicofahighconcentrationofunemployment

andbadhousingconditions.Asdetailedlocaldataismissing,weassume,startingfromthedata

onpovertyandunemployment,thatthehealthriskisalsohighinthecitiesofBremerhavenand

Wilhelmshaven (both FR Bremen) andWorms and Offenbach (both FR Rhein-Main) (cf. sub-

chapter3.4).

Thefollowingchapterprovidesthedataassessmentoftheavailablestatisticaldata.

4. Qualitydataassessment

The data quality assessment provides an overview on the possibilities and limitations of the

availabledatafordescribingthelivingconditionsofyoungadults’inthetwoFunctionalRegions

Rhein-MainandBremen.Statisticaldataiswidelyusedinpoliciesprocessestoinformandsteer

thedefinition,coordinationandimplementationofpolicyforyoungadults.Thus,assessingthe

data allows us to understand the perspective, or the ‘data-lens’, shaping LLL policies. As LLL

policiesunfolddifferentlywithinthedifferentcontexts,theimplementationofLLLpoliciesisnot

onlyaquestionof theprocessofpolicy coordinationandmatching,but alsoaquestionof the

informationonwhichpolicy-makingisbasedon.Itsobjectiveistodescribetheavailability,rep-

resentationandqualityofthedataanddatasourcesonthelocal/regionallevel.Inordertodo

so, firstly,contextspecificdatagapsatnationaland local levelweredescribed inordertosec-

ondly,assesseslimitationsandconstraintsoftheanalysis.

Theprocessofgatheringlocal/regionaldatainGermanyischallenging.Thevastmajori-

tyofavailabledatadoesnotfocuseitherontheproject’sagegroup(18-29-year-old)ordoesnot

correspond to the project’s research unit of the Functional Regions. Governmental funded re-

search,suchasthe‘Bildungsbericht’(federalreportoneducation)orthe‘Berufsbildungsbericht

2017’(federalreportonvocationaleducation)of theBundesministeriumfürBildungundFor-

schung,ispublicavailable,however,thestudiesrarelyfocusontheregionallevel.Theymainly

collectandanalysedatainlargerunits,especiallythecomparisonofEastversusWestGermany

andthefederallevel(‘Länder’),focusingmainlyonthereunificationanditsaftermathwiththe

developmentofEastcomparedtoWestGermany.Thisapproachofdatacollectionmirrors the

traditionalpath-dependenciesofGermanysadministrationunits:regionalvariationsbelowthe

federal level are the responsibilityof the federalunits (‘Ländersache’), and therefore it seems

42

thatlargerstudiesfocusonratherbroaderadministrativelevels.Undoubtedly,wecanalsofind

studiesusing smallerunits, however, the representativeness is limited.This challengeunfolds

differentlyontheFunctionalRegionsBremenandRhein-Mainasdescribedinthemethodologi-

calapproach(cf.chapter2).Asaresult,thesystematicintroductionoftheregionallevelingov-

ernmentalfundedresearchhasstilltobemade.

Although the governmental reportsmainly focus on larger research units, the govern-

mental statistical registers provide a broad variety of data on smaller research units, such as

districtsandcities(cf.chapter2).Forthelocaldatacollection,thegovernmentalstatisticalregis-

terswereusedforseveralreasons:

1. regardingthechosenindicatorstheregisterscomecloseenoughtotheregional/local

level,

2. theyofferlongitudinaldatasets,and,

3. theinformationisspecificenoughinordertopermitinterpretation.

Thedatainformationsystemsoftheregistersallowaquickandto-the-pointdatagathering,thus

providingabroadvarietyofspatialcustomizingoftheindicatorsonanoperationallevelasop-

posedtoediteddatareportsbyvariousfederaland/orregional/localagenciesmainlyfocusing

onthenationallevel.Theregistersmergedatafromofficialstatisticsandensureboth,dataac-

cessibilityandrepresentativeness.Asmainsources,thefollowingregisterswereused:

• RegionalDatabaseGermany(RegionaldatenbankDeutschland)29,

• thestatisticalstateofficeBremen(StatistischesLandesamtBremen)30,and.

• theinteractiveonline-atlasoftheFederalInstituteforResearchonBuilding,Ur-

ban Affairs and Spatial Development (INKAR, der interaktive Online-Atlas des

BundesinstitutsfürBau-,Stadt-undRaumforschung)31.

Inordertodoso,mainlytheinteractiveonline-atlasINKARwasusedasitprovidedmostofthe

requireddatadrawingfromdifferentofficialregisters.AlthoughtheRegionalDatabaseGermany

–andthestatisticalstateofficeBremenprovidedetailedstatisticaldatafromvariousofficialsta-

tisticsintheformofstandardtables,theamountofdataislimited.Both,ontheindicatorlevelas

wellasonthedepthof theregionalcategory, the informationsystemshardlyallowa tailoring

and customizing for theneeded research scope. For this reason, it hasbeendifficult to access

datadescribingthetargetgroupathand:

1. Difficultaccessofdatadescribingthetargetgroup:Althoughallthreestatisticalregisters

offeravastamountofdemographicdataandinformationontheeducationalsystemas29Availableunder:https://www.regionalstatistik.de/genesis/online/data;jsessionid=E45863A21A7DB10816FA15E40C669472.reg1?operation=statistikenVerzeichnisNextStep&levelindex=0&levelid=1498395022977&index=1&structurelevel=3[lastaccess:23June2017]

30Availableunder:http://www.statistik.bremen.de/datenangebote-8409[lastaccess:23June2017]

31Availableunder:http://www.inkar.de/Default[lastaccess:10July2017]

43

wellasthelabourmarketsystem,thedatacanhardlybecustomizedaccordingtotheage

ofourtargetgroup.Therefore,datacollectionforcommonindicatorsinGermanyseems

notsomuchaproblemofdataavailability,howevermoreatechnicalissueonthepossi-

bilityfortailoredandcustomizeddataaccessandrepresentation.

2. Indicatorsonyoungpeoples’attitudesarelargelymissingonlocallevel:Datatowardsla-

bourandpoliticallifearelargelymissingonlocallevel.Thisdataisavailableonthena-

tionalaswellasonthelevelofthefederalstates.Here,additionaldataalongtheageof

ourtargetgroupclosertothelocallevelisneededinordertoprovideacollatedpicture

ofthelivingconditionsofyoungadults.

3. Availableindicatorsreduceyoungadultsininformationsourcestoeducationandemploy-

ment:Theavailable indicatorsonyoungadult focusmainlyon theunemployment rate

andeducationalattainmentlevel, thecitizens’economiccontributiontosocietyaccord-

ing to their labourproductivity(GDP;GAV),unemploymentrates,accessandoutputof

theeducationalsystem.Thus,thecontextualinformationisreducedtotheparticipation

tothelabourmarket.

Asaresult,youngadultsaremainlyinvisiblethestatisticaldatasets.Thedatagatheringprocess

oflocaldataisconfrontedwithaclassificationproblemoftheofficialregistersthattailoryoung

adultsnotasan independent targetgroup.Thus, fromaCulturalPoliticalEconomy(CPE)per-

spective, theyoungadultsthemselvesareagapinthedatasets(cf.Weileretal.,2017a).They

are age-wise either groupedwithminors or adolescence, diminishing their position as in be-

tween.Althoughthisagegroupfacecrucialdevelopmentaltaskspertainingcareerbuilding,fam-

ilygainingindependenceandtakingonresponsibility(Weileretal.,2016).Mostofthedatasets

clustertheyoungadultsintotwoagegroups:intheagerangeeitherof15-25or18-25-year-old.

Forexample,INKAR(2017)includestheagegroup‘youngunemployedpeople’,comprisingthe

agegroupbetween15and25.Onlyforthedemographicindicator‘inhabitants’thedataisalso

systematized along the age group of 25-30. However, above the age of 25, young adults are

groupedwith adults. Theseprocesses of classificationmerge the young adultswith older citi-

zens,most likelymore established in terms of career, family planning and personal develop-

ment. Therefore, the classification of young adults produces different degrees of visibility, or

ratherinvisibility.

The invisibility/visibilityof youngadultspertainswhetherornot theyare considered

importantinpolicymakingprocesses.Thishasahighinfluenceonfuturedecision-makingpro-

cesses (cf.Bowker&Star,2000)andcan, ifdeveloped intostandards, representcertainsocial

choiceswhich impose ethical and political implications, especially affecting thosewho are se-

lected–orinthiscasenotselected(cf.Lampland&Star,2009).Thisbecomesevenmorepromi-

nentasmost indicatorsarenot separatelyavailablealong thedifferentagegroups,but rather

alongthe institutions, theyareembedded in.Forexample,regardingthedimensioneducation,

44

wefindabroadvarietyofdifferentdatasets,suchasparticipationrate intheeducationaland

vocationaltraininginstitutions,however,notexplicitlysystematizedalongtheagegroup.Here,

the different age groups are covered by a notion of standardized age-trajectories in passing

throughinstitutionalpathways.

Againstthisbackgroundofdatamismatchesontheageandregionallevel,thestatistical

dataonyoungadultsaremissingcrucialinformationinordertoinformLLLpolicies.First,local

structuraldataonyoungadultsispotentiallyavailable,howevernotrepresentedalongourage

group.Forfurtherdataanalysis,itwouldbehelpfulifthestatisticalregisterswouldallowatai-

lored and customized data collection. Second, more subjective indicators on a local level are

needed inorder todescribe theyoungadults livingconditionsbeyondeducation, trainingand

development.Indoingso,otherimportantfactorsforsocialinclusionandparticipationcouldbe

considered.Therefore,thequestionarises,howcurrentLLLpoliciesarefittingintoyoungadults’

socialrealitiesasthestatisticalbasisofinformationisnottailoredalongtheneededinformation.

Thegatheringofmoreinformationisonlypartiallytheanswer,suchassubjectiveindicatorson

jobsatisfaction,butmoreaquestionofdatarepresentation.

Thefollowingchapterprovidesconcludingremarksandemergingissues.

5. Emergingissues

InthissectionoftheBriefingPaperwewanttopointoutspecificissuesthatcameupduringthe

analysisandare relevant for thecontextof theproject.The first issue reflects thedataquality

andquantityandtherelationshipbetweennationalandEuropeandata(cf.chapter4).Thereare

bigdatagapsindifferentdimensionsonNUTS2andNUTS3-levelthatshouldbeaddressedin

thecomingyears.Thebiggestgapsareinthesubjectofhealtheventhoughtherehavebeenre-

searchersinthefieldofPublicHealthcomplainaboutthepoordataqualityandquantityforthe

past20years(cf.Prüss-Üstünetal.,2006).TheRobertKoch-Institute,whichisresponsiblefor

nationalhealthmonitoring,doesnotpublishhealthdataonaregionallevelduetotheirstand-

ardsinnecessarycasenumbers.Inrecentyears,theGermangovernmentestablishedandwid-

enedanationalhealthmonitoring(Gesundheitsberichterstattung)butaccordingtoamemberof

theRobertKoch-Institute,thesedataarenotcollectedanddesignedwithrespecttotheNUTS-

Level.OnlyinBavaria,thesituationisslightlybetter(cf.BLGL,2017).Butalsointherealmsof

socialpolicyand labourmarketpolicyrelevantdataatNUTS2-levelaremissing.Additionally,

thedatarepresentationontheregionalaswellasagelevelofourtargetgroupischallenging,as

thedata is potentially available, however, thedata output of the registers is not customisable

alongtheresearchinterest.Asaresult,theregistersaggregationofyoungadultsdiffersfromthe

projectsscope,whichcancausedatadistortion.

45

Asecondbigissueistheroleofthefamilyasaveryimportantresourceforyoungadults.

Ontheonehand,familiesareinsomedimensionsimplicitlypictured,forinstanceregardingthe

ratioofyoungadultsliving–voluntarilyorinvoluntarily–togetherwiththeirparentsorregard-

ingearlypregnancies.Ontheotherhand,thefamilysupportismoreorlessinvisibleinthedata.

Weassumethatmostoftheriskfactorsforyoungadultsarebufferedbythefamilysupport,for

instance regarding childcare foryoungmothersormaterial support forunemployedsonsand

daughters. The importance of the family support system highlights the notion of the German

conservative welfare state along the principle of subsidiarity (cf. Parreira do Amaral et al.,

2017b,p.17;cf.sub-chapter3.5).However,itseems,thatthecontributionofthefamilyforthe

youngadults’lifecourseisnotmirroredbythedata,butrathertheyoungadults’contributionto

thesocietythrougheducationandemployment.

Inconclusion,statisticaldataavailableonthelivingconditionsofGermanyoungadultsis

mainlycollectedatnationallevelandusuallyrestrictedtoeducationandemploymentindicators,

glossingoverothercrucialaspectsoftheirlifecourses.Thedatalargelyinformsonthedifferent

school tracks, thetrainingopportunities, theunemployment/employmentratesandthesocial

securitysystem.Againstthisbackground,basedonthedatareviewedtheGermancontextcanbe

describedasanemployment-centredtransitionregimewhereyoungadults’autonomyischarac-

terisedbyalowlevelofstatesupportbuthighfamilysupport(ParreiradoAmaralet.al.,2017b,

p. 22;Walther & Pohl, 2005;Walther, 2006). Therefore, young adults’ citizenship can be de-

scribedasa ‘monitoredcitizenship’,withtheoverallaimtoexpeditetheirtransitionintowork

alonghighly institutionalisededucationand training systems (Chevalier2016,p.14ff.; cf. Par-

reiradoAmaraletal.,2017b,p.21).

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Weiler,A.,Schaufler,S.,ParreiradoAmaral,M.,GanterdeOtero,J.P.&Wutzkowsky,F.(2017a).LaunchingandRe-searchDesign.StateoftheArtReport.YOUNG_ADULLLTWorkingPaper.Münster:WestfälischeWil-helms-UniversitätMünster.

Weiler,A.,GanterdeOtero,J.P.,ParreiradoAmaral,M.incollaborationwithBoutiuc-Kaiser,A.,Schaufler,S.,Verlage,T.(2017b).ComparativeAnalysisSkillsSupplyandDemand.NationalReport:Germany.YOUNG_ADULLLTWorkingPapers.Münster:WestfälischeWilhelms-UniversitätMünster.

Wilkinson,R.(2005).Theimpactofinequality.Howtomakesicksocietieshealthier.NewYork,London.

Wittel-Fischer,B.(2000).DieungestillteSehnsuchtnachSchwangerschaftundMutterschaft?EinvergessenesThemainderSexualpädagogik.In.BundeszentralefürgesundheitlicheAufklärung(eds.).DokumentationderFachtagungzurSexualpädagogischenMädchenarbeit.19.-21.Juni2000,pp.110-113.

Wutzkowsky,F.&Weiler,A.(2016).Vulnerability.YOUNG_ADULLLTGlossaryEntry.Münster:WestfälischeWilhelms-UniversitätMünster.Availableunder:http://www.young-adulllt.eu/glossary/listview.php?we_objectID=218&pid=187[latestaccess:22Sept.2017].


1

Work Package 4


National Report Italy

University of Genoa (UNIGE)

Mauro Palumbo, Anna Siri, Mauro Migliavacca

Project Coordinator: Prof. Dr. Marcelo Parreira do Amaral (University of Münster)

Project no.: 693167

Project acronym: YOUNG_ADULLLT

Project duration: 01/03/2016 to 28/02/2019 (36 months)

Type of document: National Report

Delivery date: Month 19

Dissemination level: Public


2

TableofcontentsExecutivesummary................................................................................................................................................................................3Introduction..............................................................................................................................................................................................5Descriptionofthedatacollatedandqualitydataassessment............................................................................................51. Demographicstructure..............................................................................................................................................................62. Structureoftheeconomy..........................................................................................................................................................83. Education........................................................................................................................................................................................114. Labourmarket..............................................................................................................................................................................185. Redistributionandsocialinclusion.....................................................................................................................................246. Healthandwell-being...............................................................................................................................................................267. Conclusions....................................................................................................................................................................................28References................................................................................................................................................................................................30

Figures

Figure1-Cruderateofnetmigration(1per1000)................................................................................................................7Figure2-Earlyschoolleversatnationalandregionallevels(percent)......................................................................12Figure3-ThereareclearimprovementsinschoolresultsbuttheyarestillbelowtheOECDaverage.........14Figure4-Highereducationparticipationandincentivestoinvestarelow...............................................................15Figure5-Thelevelofskillsmismatchishigh..........................................................................................................................16Figure6-NEETsatnationalandfunctionalregion’slevels(percent)..........................................................................18Figure7-PeopleatriskofpovertyorsocialexclusionbyNUTS2regions,2012-2015......................................26Figure8-Italy’swell-being.............................................................................................................................................................27

TablesTable1-Economicsectors,shareofeconomicsectorsinGDPvalueadded(percentofGDP)............................9Table2-Labourproductivityperhourworked(ESA2010).Percentagechangeonpreviousperiod...........10Table3-GDPatcurrentmarketprices,EuroperinhabitantinpercentofEuropeanaverage..........................10Table4-Netsocialprotectionbenefits.......................................................................................................................................24


3

Executivesummary

Themainfindingsofthein-depthreviewcontainedinthiscountryreportareasfollows:

- Demographicstructures

From a demographic point of view, Italy is one of the oldest countries with the lowest

replacement rate. This makes the demographic stability and the same system of social

security more and more dependent on migrations, which, however, are today one of the

most serious problems for the Country. The old dependecy ratio confirms a worst

demographic dynamic in Liguria in comparison with Lombardy. Regarding the life

expectancyindicator,inLombardy(83.9onaverage),theindicatorshowsabettersituation

thaninLiguria(82,8onaverage),anywayhigherthanthegreatpartofItalianregions.

- Structureoftheeconomy

Productivity growth remains weak, slowing the correction of Italy’s macroeconomic

imbalances. It has been a problem for years. Making the labor market more flexible and

reducingtheindirectcostshavebeenconsideredapivotalpartofawiderstrategyaimedat

reducing high structural Italian unemployment. The focus on these two aspects, however,

hasovershadowedanother importantbutscantily investigated issue: themissingeffectsof

the innovation on productivity growth, as Italian industries preferred financiarization to

innovation.HighpublicdebtremainsamajorsourceofvulnerabilityforItaly,alsobecause

thespreadwithGermanBund(around1,6percent)makedebtheavier, itsreductionmore

difficult and investments for industries more expensive. Despite recent gains, the

competitiveness gap remains. The depreciation of the euro supported the stabilisation of

Italy’s export performance in recent years, togetherwith contained increases in producer

pricesandunitlabourcosts.

LombardyandLiguriaremainintheEUaveragewithregardstotheGDP,butwhilethefirst

oneisfirmlyaboveItalianandEUaverage,thesecondismuchclosertotheaverage.

- Educationsystem

Education reform is ongoing but tertiary education remains largely underfunded and

participationinadultlearningandapprenticeshipsislow.The2015reform,ifproperlyand

swiftly implemented, is expected to improve school outcomes. In particular, strengthened

apprenticeships and work-based learning aim to raise the labour-market relevance of

education. However, participation in adult learning remains a persistent concern, in

particularforthoseneedingitmost.Inspiteofrecentpartialmeasures,thehighereducation

systemsuffersfromsignificantunderinvestment.�


4

Italylacksofshortdegrees(EQF5)makestheaveragerateofyoungwithtertiaryeducation

levellowerthanEUaverage(andfarfromtheLisboa2020target),butinthesametimethe

absence of technical short degrees causes the overqualification ofworkforce, because the

rateofdegrees thatdon’tuseenough theirqualification in the joc ishigh(more inLiguria

thaninLombardy),andtherateofhighlyeducatedyoungsthatmigratesisgrowing.

Ligurianstudentsperform less thanpeers inLombardy,but the resultsare lower thanEU

average.

- Youthandlabourmarket

Despitethegradualimprovementofthelabourmarket,long-termandyouthunemployment

remainhigh.Theimplementationoftheactivelabourmarketpoliciesreform,includingthe

reinforcement of public employment services, is still at an early stage. Also in the public

debate, mismatch prevails over the lack capacity of productive context to absorb skilled

workers.Inthelast15years,profitshaverisenandwageshavefallen,butcompaniesdidnot

devotetheirhighestprofitstogreaterinvestments.Inaddition,duetothehighpublicdebt,

despitearecentmodestreduction,thetaxburdenonproductionfactorsremainsamongthe

highestintheEU.InvestmentinItalysufferedasharperfallthaninmostMemberStates.The

declinewasbroad-based,butparticularlystronginnon-residentialinvestmentandservices.

Thepotentialoffemalelabourmarketparticipationremainslargelyunderutilised.Accessto

affordablechildcareremainslimitedwithwideregionaldisparities,paternityleaveisamong

the lowest in EU and the effectiveness of cash allowances for childcare has not been

assessed. Young people and women are confirmed theless protectedand needystrataof

society,evenifthefemaleemploymenthasdevelopedovertime(if lessthanthestrongEU

countries).�

The structureof the economyexplains a largepart of thedifferent internal outcomes. For

examples,aboutourfunctionalregions,thedatashowsthatinLiguriatheriskofpovertyand

socialexclusionishigherthaninLombardy.

- Redistributionandsocialinclusion

Significant barriers to competition remain in important sectors, including professional

services, local public services, concessions and the transport sector. The public sector is

beingreformedtotacklelongstandinginefficiencies.

Newsocialpolicieshavebeenputforwardtorespondtotherisingpovertyrate.Itisunclear

whether the financial resources will be sufficient to address Italy’s poverty challenge.

Activationpoliciesarenotyetwidespreadenough.Therateofpeopleatriskofpovertyor

socialexclusioniswellabovetheEUaverage,andisparticularlyhighforchildren,temporary

workersandindividualswithamigrantbackground.


5

- Healthandwell-beingconditions

TheshareofprivatehealthexpenditureinItalywas24.5percentofthetotalin2015,equal

to Estonia and Finland. Health public expenditure in Italy was below other important

Europeancountries.IngenerallivingconditionsinLombardyarebetter,andthisevaluation

emergesbothfromobjectivedata,bothfromperceptionsofcitizens.Wemustconsiderthat

Liguria is the regionwith the oldest population, as said heavily affected by economic and

demographiccrisis,causedseriousdisturbanceineducationalandsocialsectors.Lessyoung

peopleinanageingcontextwithfeweropportunitiesandagreaterpartofpopulationatrisk

of social exclusion contribute also to lower levels of subjective well-being and lower

expectationsforthefuture.

To summarise, the current problems of the Italian economic and social context (low

productivity,highpublicdebt,inefficienciesinsomesectors,poorinnovation,populationageing,

overcrowdedsocialpolicycosts,oftenpassive)donotfavortheconditionofYoungAdults,who

toa largeextent continue to live in the family (78%ofpeopleaged20-29,vsaEUaverageof

55,4%).Inatimeofcrisissuchasthis,familiesarethemainsafetyvalve,reducingtheautonomy

ofyoungpeople.

IntroductionThenationalbriefingpaperoffersanoverviewof the livingconditionsofyoungadults in Italy

and,morespecifically, in the two functionalregionsselected for theYOUNG_ADULLLTproject,

theFunctionalRegionsofGenoaandofMilan.

Thelivingconditionsareexploredbyobservingthekeysetofindicatorsthatwasprovidedfor

the 6 dimensions: the demographic characteristics of the population, the structure of the

economy, the inputsandoutputsof theeducationand trainingsystem, the labourmarket, the

reditributionandsocialinclusionand,finally,thehealthconditionsandindividualwell-being.

Thedatawerenotallavailablefor2016andforthisreasonweoftenreferto2014or2015as

thelastdataaccessible.

DescriptionofthedatacollatedandqualitydataassessmentAhugeamountofharmonizedandcomparativedatahasbeencollectedbyOECDandEUROSTAT

sincetheyprovidemetadataandcompletedtimeseries.Mostoftheinformationareprovidedat

nationallevelandnotalldimensionshaveafairnumberofindicatorsatNUTS2andNUTS3level.

Moreover, the analysis of our two Functional Regionswith these data sets is a hard task for


6

mainlytworeasons:a) theavailabledatadonotcoverall the indicatorsof thesixdimensions,

andb)theunitsofNUTS2and3donotmatchourFunctionalRegions.

Theeducationalandlabourmarketdatacollatedatnationalandlocallevelwereextractedalso

fromdifferentsurveyssuchas theEU-LFS,EU-SILC,PISAandPIAAC.Themaincorpusofdata

proceeding from international and harmonized data was successively complemented by data

collatedatthelocallevel,madeavailablebytheALMALAUREAdatasetandbyINVALSIsurveys,

aswellasbyofficialwebsitesofseveralItalianInstitutions(Ministers,regionalgovernmentand

Chambersoftrade).

Thedatarangesbetween2005and2015,butforsomeindicatorsespeciallyatnationallevelit

wascollectedmorerecentdata.Duetolimitedavailabilityofdataattheregional/locallevel,and

thehigh levelof the fragmentationofsources, thepossibilityofcomparison is limited insome

cases.

1. DemographicstructureItaly, with its 302,073 square kilometres, has 60,589,445 inhabitants according to the

calculations current as of December 31, 2016. The distribution of the population is widely

uneven.Inthelastyears,theItalianpopulationrecordedanegativevariationmainlyattributable

tothenaturaldynamicsandthemigrationslowdown.Thenaturalpopulationdifference(births

minus deaths) in the most recent year was negative by almost -142 thousand units. As the

balancewaspositiveforforeignnationals(almost+63thousandunits),fortheItalianonesthe

declinewasevenmoresignificant(-204,675units).

ThedeclineinthenumberofbirthsthatstartedintheSixtiesisstillgoingon.

Thedeathswereover615,000,almost32,000lessthanin2015.Thedecreasein2016wasdue

toahighlevelofmortalityregisteredinthepreviousyear.ThetwoFRsshowdifferentlevelsof

demographic decrease: in Genoa Functional Region the crude rate of natural change of

population in 2015 was -8.0 for thousand inhabitants, in Milan FR of -1.2; crude rate of net

migrationwas-1.3inGFRand+4.8inMFR.

In2016,theinternationalmigratorymovementdeterminedapositivebalanceofapproximately

144,000units,astablevaluecomparedtopreviousyears.Theattractivenessofthenorthernand

centralregionstowhichwereaddressedmostmigrationflows(bothinternalandfromforeign

countries)wasconfirmed.

Inthelastyears,migrationbecomesanimportantaspectofthedevelopmentofthepopulation,

affectingbothFunctionalRegionsevenly.

ThecruderateofnetmigrationdecreasedinLombardyuntil2008(-0.7),jumpedin2013to32.4


7

percent(butonlyduetostatisticflow,andin2015decreasedto4.8.InLiguria,thecruderateof

netmigrationfluctuateduntil2012andthenroseupto26.3 in2013,andcollapsedinthe last

years(in2015-2.4percent).

Figure1-Cruderateofnetmigration(1per1000)

Source:Eurostat

From2005to2010thetotalfertilityrateinItalyincreasesfrom1.34to1.46andthentherate

began todecrease.Thenumbers in thehere focused in functional regionsareverynear these

average,butGFRshowsawortssituationthanMFR. In2015, thenumbersare1,33 inLiguria,

and1,46inLombardy.ThisseemstobeaEuropeanphenomenonaswell,astheEU-28average

increasesfrom1.51to1.62until2010,andinthelastyearstheratestartedaslowdecline(1,58

in2014).Themeanageatchildbearing-31.7yearsin2016-wasstabletothepreviousyear.

The old-dependency rate (ratio between population aged 65 and over to population 15-64)

increasedinItalyfrom29.4percentto34.3percentinthetimespan2005-2016.InLombardy,in

thesameperiodtherateroseupfrom28.5percentto34.2percent,whileinLiguriafrom42.2

percent to 46.8 percent. This indicator confirms a worst demographic dynamic in Liguria in

comparisonwithLombardy.

Life expectancy estimates for2016evidencedanewgrowthof the indicator forboth genders

(80.6 males, 85.1 females), after the exceptional decrease recorded between 2014 (reported

excessdeaths)and2015(males:+0.3comparedto2014,+0.5comparedto2015;females:+0.1

comparedto2014,+0.5comparedto2015).InLombardy(83.9onaverage),theindicatorshows

abettersituationthaninLiguria(82,8onaverage),anywayhigherthanthegreatpartofItalian

regions.

(10)

-

10

20

30

40

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015Italy Genova Milano


8

Therateofyoungadultlivingwiththeirparentsrapidlyincreasedoverthelastdecade.In2013,

therateofyoungadults(20–29years)wholivewiththeirparentswas78percent,whichexceed

23 points the European average (55.4 percent), however in 2006 the rate was still at 72,8

percent(EU-2753.1percent).Weassumethatthisincreaseislinkedwiththereformsofsocial

programsandlabormarketsince2015.Livingathomewiththeirparentsisratherayoungmale

(83.4percentin2013)thanayoungfemaleissue(72.5percent).

2. StructureoftheeconomyTheItalianeconomyishistoricallycharacterizedbyadifferentterritorialdevelopment,usually

represented in three specific geographical areas: the developed industrial North, a less-

developedandwelfare-dependentagriculturalSouth,withhighunemployment,andtheCenter

area,moredominatedbysmallandmedium-sizefirms.Italyhasmovedslowlyonimplementing

needed structural reforms, such as the reduction of the public-sector costs, and increasing

employment opportunities for young workers, particularly women. The data of the different

economicsectors,putinevidencetheroleplayedbytheservicesector(accordingtoEuropean

trends)and,atthesametime,theroleplayedbytheagriculturesector,that,despitethereduced

impact,inItalyrepresentaninterestingareaofdevelopfornewentrepreneurshipactivities.


9

Table1-Economicsectors,shareofeconomicsectorsinGDPvalueadded(percentofGDP)

Agriculture 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 EU 28 1.8 1.7 1.7 1.64 1.49 1.62 1.68 1.68 1.74 1.65 1.6 Italy 2.25 2.17 2.1 2.07 1.98 1.97 2.1 2.19 2.33 2.16 2.25

Industry 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 EU 28 26.46 26.73 26.62 26.14 24.61 24.96 25.03 24.75 24.49 24.37 24.50 Italy 25.83 26.15 26.49 26.13 24.27 24.37 24.21 23.87 23.7 23.38 23.53

Services 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 EU 28 71.74 71.57 71.69 72.22 73.9 73.42 73.28 73.57 73.77 73.98 73.9 Italy 71.92 71.68 71.41 71.8 73.75 73.66 73.69 73.94 73.97 74.46 74.22 Source:Eurostat

The last international financial crisis worsened the economic conditions in Italy, with

unemployment rising from 6.2 percent in 2007 to 12.4 percent in 2015. In the longer-term

Italy’s low fertility rate and quota-driven immigration policies will increasingly strain its

economy.Ariseinexportsandinvestmentdrivenbytheglobaleconomicrecoverynevertheless

helpedtheeconomygrow.

The general framework of the productive structure of the Italian economy is marked by the

persisting financial crisiswhich causedadramatic fall in thenumberof enterprises.Although

thenumberofenterprisesper1,000inhabitantsdecreased,theiraveragesizeremainedstablein

2014atabout4employeesbyenterprise;micro-enterprisesthereforestillplayanon-negligible

roleintheentireproductivesystem.

TheItalianproductivesystemischaracterizedbyalargedegreeoffragmentation,togetherwith

a relative specialisation seen in themicro-enterprise service segment, accounting for over 30

percentofemployment.RegionsintheNorth-westareahadthehighestlevelsofwageadjusted

labourproductivity,while values lower than thenational averagewere recorded in the South

andIslandsarea.Thelowestvalueswererecordedintheconstructionsector.

TheItaliansocioeconomicbackgroundexpertisesomerelevantchangesinthelasttwentyyears.

Although the main indicators of inequality exhibit a stable trend until the explosion of the

currentcrisis,inthesameperiodmajorchangestakingplaceinternallyinItaliansocialstructure

anddynamicshavelargelyredrawnthemapofsocialrisks.InItaly,theeffectsofthecrisis(the

recent economic crisis and early ’90 crisis) was aggravated by a particularly slow economic

growththatconcernedproductivityandwageincreases,aswellaspeople’sstandardsof living

(Crouch1999,RanciandMigliavacca2015).Thelabourproductivitygrewinthemanufacturing

sector by less than 1 percent per year between1996 and2007 anddecreased after 2001. As


10

regardswages,whilstinthe1970sand1980stheaveragegrowthhadbeen2.5percentperyear,

betweentheearliest’90andthefirstdecadeofthe2000thegrosspayofdependentlabourgrew

atarateof0.6percent–aslowdownwhichmeantthatwagescoulddonomorethankeepup

withtheinflationrate.

Table2-Labourproductivityperhourworked(ESA2010).Percentagechangeonpreviousperiod 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016EU28 1.1 1.7 1 -0.4 -1.4 3.1 1.4 0.9 1 0.6 1.2 0.6Italy 0.6 0 -0.1 -0.7 -2.2 2.2 0.5 -0.3 0.9 0.2 -0.2 -0.8Source:Eurostat There was also an evident downturn in the standard of living: in the period 1995-2012, per

capitaGDPgrowthatmarketpriceswas lower in Italy than in themainEuropeancountries –

especiallyafter2001–which increased thedistancebetween Italyand itsprincipalEuropean

partners.Atthesametimebetween2006and2015thepercapitaGDPgrowthatmarketprices

decreased, while a positive variation was registered inmany European countries. Italy’s real

GDP growth recovered only modestly in 2014 and 2015 (0.1 percent and 0.7 percent

respectively), while growth in the rest of the euro area was significantly more dynamic (1.4

percentand2.3percentrespectively).This trendshowsthedifficultiesof the Italianeconomy,

difficultiessimilartotheotherssouthernEuropeancountries(especiallySpain).

AshighlightedbyEuropeanCommission in the last country report Italy2017, theunit labour

costdynamicsslowedsignificantlyinrecentyearsdespitenegativelabourproductivitygrowth.

Since 2010, nominal unit labour costs have slowed down in Italy and in 2014-2016 they

increased by less than 0.4 percent per year on average (as compared to 2.3 percent in 1999-

2013).Thesedevelopmentshelped to reduce slightly the cost competitivenessproblemof the

Italianeconomy in recentyears.Labourproductivitywasnegativealsodue tohistorically low

investmentlevels,whichturnedcapitaldeepeningnegative.

Table3-GDPatcurrentmarketprices,EuroperinhabitantinpercentofEU-28average

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Δ2015-2005

EuropeanUnion(28countries) 100 100 100 100 100 100 100 100 100 100

Italy 108 107 107 106 104 104 102 99 97 96 -12Liguria 118 119 120 119 114 114 112 108 108 107 -11

Lombardy 138 137 140 138 138 137 134 129 128 127 -11Source:Eurostat

Theeconomicstructureof the territorial systemof theMetropolitanAreaofMilanselectedas

oneoftheFunctionalRegionsforYAprojectisquitecomplexduetothehighnumberofsectors


11

and of supply chains for each sector. In the recent years, this area has been characterized by

differentvulnerabilityaspects(morespecifically,territorialdisparity,inequalitiesingenderand

education, social and spatial marginality) which nowadays are stressed due to the economic

crisiseffects.Ithasalsobeenaffectedbyade-industrializationprocess.TheMetropolitanCityof

Milanhasover296,000activeenterprises,themajorityofwhichoperateinthetertiarysector,

particularly in services, where there are over 146,000 units (49.6 percent of the total) and

1,032,000employees(55percent).Themanufacturingsectorcovers18.8percentofemployees,

with10.5percentoftheenterprises.Itisasystemingoodhealth,which,despitetheeconomic

recession,hasseenan increase in thenumberofenterprisesof3.4percent in the last5years,

withanoverallpositiveannualchangeandparticularlyinMilan(4.6percent).

TheMetropolitanAreaofGenoaselectedasthesecondFunctionalRegionischaracterizedbya

dynamicandspecializedport especiallywith regard to container traffic and itsnodalposition

with logistic trans-European and Mediterranean corridors. The Port of Genoa features an

uninterrupted22-kilometre coastline, and covers a total surface areaof6million sqmof land

and14.5millionsqmofseawater.

Accordingtothedata,LombardyandLiguriaremainintheEUaveragewithregardstotheGDP,

butwhilethefirstoneisfirmlyaboveItalianandEUaverage,thesecondismuchclosertothe

average.

3. EducationExpenditureoneducationandtrainingallowstoassesspoliciesimplementedforthegrowthand

optimizationofhumancapital.BothasaproportionofGDP(4.1percent)andasaproportionof

totalgeneralgovernmentexpenditure(7.9percent), theexpenditureoneducation in Italywas

among the lowest in the EU in 2014. Europe Strategy 2020 set some objectives for the

populationeducationlevels,whichourcountryhaspartiallyreachedin2016.

Students inTertiaryeducationrate ishigher inLombardy than inLiguria (61,7percentvs.56

percent) and this phenomenon is relevant because, in thepast, in Liguria families invested in

tertiary educationmore than other regions (Bini & Palumbo, 1990); Lombardy shows also a

higher percentage of pupils enrolled in vocational secondary education than Liguria (61,7

percentvs.54,3),asanadditionalproofoflabourmarketorientedchoicesoffamilies.Anyway,

thepercentageofpeopleaged30-34yearswithhighleveleducation(ISCED5-8)isstillhigherin

LiguriathaninLombardy(in201431.3percentvs25.9).

Theearlyschoolleavingratehasbeenonadownwardtrendsince2008.Thepercentageofearly

school leavers in 2016decreased to 13.8 percent (14.7 percent in 2015), thus surpassing the


12

nationaltargetof16percentsetfor2020.However,therateremainsabovetheEUaverage(11

percent in 2015). It is interesting to note in this context that in Lombardy the ESL rate goes

downveryfast,whileinLiguriaincreasesforatimeforfallinginthelastyears,maybeduetothe

impact of foreigners. In fact, the gap is particularly high among foreign-born students,with a

rate of 31.3 percent compared to the EU average of 19 percent in 2015. Integrating students

withanimmigrantbackgroundisarelativelyrecentissueinItaly,butit isgainingimportance.

The proportion of foreign pupils in state schools reached 9.5 percent in 2015/2016, ranging

from 6.3 percent in upper secondary education to 11.4 percent in early childhood education.

There isalso in thesameyearasignificantgendergap,with therate forboysat17.5percent,

comparedto11.8percent forgirls,andawideningof thenorth-southdivideover the last five

years.

Figure2-Earlyschoolleversatnationalandregionallevels(percent)

Source:Eurostat

According to the 2015 school reform, one of the possible actions to tackling inequalities and

promotinginclusionisimprovingmigrantstudents’proficiencyinItalian.

Therehavebeenconsistentsignsofimprovementinthequalityofeducation.Scoresinreading,

mathand sciencesamong15-yearoldshave increased substantially and faster than theOECD

average, as measured by the OECD Programme for International Student Assessment (PISA).

However,averagelevelsofcompetencesproficiencyarestilllow.

0

5

10

15

20

25

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

EU28ESL ItalyESL LiguriaESL LombardiaESL


13


14

Figure 3 - There are clear improvements in school results but they are still below the

OECDaverage

Source:OECDPISA2006,2009,2012,2015

Inscienceliteracy,themaintopicofPISA2015,15-year-oldsinItalyscore481pointscompared

toanaverageof493pointsinOECDcountries.Boysperformbetterthangirlswithastatistically

significantdifferenceof17points (OECDaverage:3.5pointshigher forboys).Onaverage,15-

year-olds score 490 points in mathematics compared to an average of 490 points in OECD

countries.Boysperformbetter thangirlswithastatistically significantdifferenceof20points

(OECD average: 8 points higher for boys). In Italy, the average performance in reading of 15-

year-oldsis485points,comparedtoanaverageof493pointsinOECDcountries.Girlsperform

betterthanboyswithastatisticallysignificantdifferenceof16points(OECDaverage:27points

higherforgirls).

In thePisa2015 survey, there is no longerdata fromall regions,which canbe seen from the

INVALSIreport2016.From2012totodaytheresultsareworseandnotleast:Lombardylost16

reading points (521-505), nine points inmathematics (517-508),more than twenty points in

three years in science (529-503), but today it is still at the level of Switzerland and Ireland,

halfway between Singapore (556 points). Ligurian students perform less than peers in

Lombardy, but the results are lower than EU average. It is alsointeresting to note that since

thePISAtestsbeganin2000,LombardyperformsbetterthanLiguria.

Therearealsosignificantdifferencesinbasicskillsproficiency,asmeasuredbyProgrammefor


15

InternationalAssessmentofAdultCompetencies(PIAAC).

Figure4-Highereducationparticipationandincentivestoinvestarelow

Source:Eurostat

InItaly,workers’skillsoftendonotmatchemployers’needs.TheSurveyofAdultSkills(PIAAC),

thatmeasures the key cognitive skills for adults to fully participate in society, shows that 12

percentofItalianworkersareover-skilledinliteracyastheyarenotabletofullyusetheirskills

andabilitiesinthejob;while8percentareunder-skilledastheylacktheskillsnormallyneeded

for their job. Both measures are above OECD averages which are 10 percent and 4 percent,

respectively.Under-skillingisespeciallyhighinItaly,reflectingthelowlevelsofskills.Reducing

skill mismatches is crucial to raising productivity, job satisfaction andwell-being. Illustrative

evidencesuggeststhatItalycouldboostitsleveloflabourproductivityby10percentifitwereto


16

reduceitslevelofmismatchwithineachindustrytothatcorrespondingtoOECDbestpractices

(AdaletMcGowanandAndrews,2015).

Figure5-Thelevelofskillsmismatchishigh

Source:Eurostat

Overcomingskillmismatches,underorover-skilling,requirespoliciestofosterlabourmobility

andmaketheeducationandtrainingsystemmoreresponsivetolabourmarketneeds.

In 2015, 26.2 percent of people aged 30-34 achieved a tertiary qualification, in linewith the

objectivesetforItaly,butratherfarfromthe40percentsetforEurope.

InboundgraduatemobilityremainsratherlowatMaster'slevel,butisontheriseatBachelor’s

level (4percentofbachelorgraduates came fromabroad in2014, compared to2.9percent in

2013).

The number of Italian citizenswith a tertiary education degree leaving the country has been

rapidly increasing since 2010. This has not been compensated by inflows of equally well

qualifiedItalians(orforeigners)returningtothecountry(ISTAT,variousyears).Theincreasing

emigration reflects better job opportunities and conditions abroad. Survey data show that

comparedwiththeirpeersworkinginItaly,youngItaliangraduatesworkingabroadearnhigher

andmore rapidly increasing salaries, workmore frequently under open-ended contracts and

considertheirformalqualificationmoreappropriatefortheirjob(ConsorzioInteruniversitario

AlmaLaurea2016).Italianswithadoctoraldegreeworkingabroadreporthavingbothbetterjob

opportunities and significantly higher earnings. Thismay explainwhy highly qualified Italian

workershave very little inclination to return to their home country (Biondo et al. 2012). The


17

emigration of highly qualified Italianworkers therefore does not qualify as ‘brain circulation’

(i.e. when people temporarily go abroad to study or work, but then go back to their home

country), neither a ‘brain exchange’. Many Italian workers leave the country, but few highly

qualifiedindividualsfromothercountrieschooseItalyasadestination.

TheproportionofforeigncitizenslivinginItalyaged25to64withatertiaryeducationdegreeis

muchlowerthanthatofItaliancitizens(11.5percentcomparedto17.5percentin2014).Inthe

EU,asawhole theproportionsofhighlyqualifiedEUcitizensandnon-EUcitizensaresimilar

(29.4 percent and 28.1 percent respectively). The resulting ‘brain drain’ can thus cause a

permanentnetlossofhighlyqualifiedhumancapital,whichwouldharmItaly’scompetitiveness

(EuropeanCommission2016).

Evenlifelonglearning,whichisconsideredtobeanimportantrequirementtobeintegratedinto

thelabourmarket,in2016involved8.3percentofpeopleaged25-64.

The shareof30-34-year-oldswith tertiaryeducation, too, isdifferent across regions: in2016,

the indicator for almost all regions of the Centre and North was above the national average,

whilefortheSouthandIslandsareaitwas5.5percentagepointslower.

Finally,youngpeopleaged15-29whoarenotineducation,employmentortrainingwereover

2,2million(24.3percentoftherelativepopulation),withahigherincidenceamongwomenthan

men.In2016,however,theaggregateshowsaslightdecreaseforthesecondconsecutiveyear.

Thephenomenonseemstohavebegunatrendreversal,aftertheexponentialgrowthdynamic

that has been in place since the beginning of the economic crisis. Compared to themaximum

values reached in 2013 in Liguria and in 2014 in Lombardy, the NEETs are down slightly in

2016.

In2016,15 to24-year-oldNEETsresidents inLiguriawere19,019and their incidenceon the

populationofthesameagewas14.7percent,downfrom15.9percentin2015and17.1percent

in 2013. Among the Italian regions, Liguria is ranked 13th with regard at NEET rate, with a

percentageweightof5.2pointslowerthantheItalianaverage(19.9percent)and0.9pointsthan

theNorthwestItaly(15.6percent).Regardingtheneighboringregions,onlyEmiliaRomagnais

in a better situationwith thepercent rate ofNEETat 12.1percent, followedbyTuscany14.9

percent,Lombardy15percentandPiedmont17.5percent.


18

Figure6-NEETsatnationalandfunctionalregion’slevels(percent)

Source:EUROSTAT

ThepresenceofNEETincreasesbyobservingthe15-29-year-old.TheLigurianNEETsof15-29

yearsin2016were34,859,withanincidenceonthepopulationofthesameageof17.6percent

(16thamongtheItalianregions),6.7percentagepointsbelowtheItalianaverage(24.3percent),

and0.2percentagepointshigherthantheNorth-Westaverage(17.8percent).Ligurialastyear

hadarateofNEETbetween15and29yearshigherthantheneighboringregions.Thisyearisin

an intermediateposition:LiguriaexceedsEmiliaRomagna(15.6percent)andLombardy(16.9

percent),butisexceededbyTuscanyat18percent,andbyPiedmontto20percent.TheNEETs

residentinLiguriaaged18-29are33,425,withanincidenceof20.8percentofthepopulationof

thesameage(16thamongtheItalianregions),8percentagepointsbelowthenationalaverage

(which affects 28,8 percent), and 0.3 points below the North-West average (21.1 percent).

Liguria is also in amiddlepositionwith regard to this age group: it is aboveEmiliaRomagna

(18.7percent)andLombardy(20.1percent),butitisbelowTuscanyat21.5percent,andfrom

Piedmontto23.6percent.

Inconclusion,consideringthetrendofNEETsinthetwoareasinvolvedintheYAproject,Liguria

andLombardyhasmanysimilaritiesand in2016 thepercentage in the tworegionswasquite

thesame.

4. LabourmarketThe Italian labour market recorded slight positive growth between 1999 and 2008, with

0

5

10

15

20

25

2012 2013 2014 2015 2016EU27NEET LombardiaNEET LiguriaNEET ItalyNEET


19

absoluteemploymentandtheemploymentraterisingslowlybutconstantly.In2009,however,

thisupwardtrendreversed.Whilein2008some22.7millionpeoplewereemployed,thisfigure

haddropped to21.8millionby2014.Theemployment rate alsodropped in thisperiod, from

58.6percentin2008downto55.7percentin2014.

Employmentgrowthstartedtorecoverin2014whentheeconomywasstillstagnating,andthis

trendcontinuedin2015and2016.MostrecentdatashowthatItalyreachedthepre-crisislevel.

A look at the rates of employment according to gender and age reveals structural

underemployment among young adults, older persons and women. The poverty risk has

increasedaccordingly.

Afterthepositiveeconomicsignsatthebeginningofthe2015,theItalianeconomylookssetto

return to growth last year. In the second quarter of 2016, against the backdrop of a general

stoppage in economic growth internationally, the Italian economy came to a standstill. GDP

remainedunchangedcompared to thepreviousquarter, and increased0.8percent inyear-on-

year terms. In this context, the absorption of work by the production system continued to

increase:thetotalhoursworkedroseby0.5percentonthepreviousquarterandby2.1percent

year-on-year. The quarter-on-quarter rise affected both industrial production (+0.4percent)

andservices(+0.6percent).

Thenumberofinactivepeoplecontinuedtodeclineatafasterpace,bothquarter-on-quarterand

year-on-year (in absolute and percentage terms), especially with regard to the number of

discouraged people1. After the economic stability, the unemployment rate fell slightly (-0.1

points)incomparisontothepreviousquarter,andwasdown0.6pointsonthesamequarterof

2015,withthenumberofunemployedpersonsfallingyear-on-yearby109,000.

Thechangesintheemployedpopulationimplysignificantchangesinthesituationofpeoplein

thelabourmarket;transitionstopermanentemploymentincreased,particularlyfortemporary

employees and staff. Moreover, the flow from unemployment into employment increased,

particularly for employees. The increased move from unemployment to employment mainly

affectedmen, youngpeople aged25-34, residents in theNorth and secondary school diploma

holders.

Inthesecondquarterof2016therewasanupwardtrendinemployment:anincreasingtrendin

the‘newentrants’expectedbyenterprisescombinedwithadescendingtrendinthenumberof

1Discouragedworkersare persons not in the labour force who believe that there is no work available due to various reasons and who desire to work (OECD, http://www.oecd.org/els/emp/LFSNOTES_SOURCES.pdf).Discouragedworkersdonot includethosewhohavedroppedoutofthelaborforceforotherreasons.Thesearepeoplewhohavegone back to school to better their chances of gettingwork.Manywomen leave theworkforce because they'vegotten pregnant.Otherpeoplecan'tworkbecausethey'vebecomedisabled.Althoughtheymayindeedalsofeeldiscouraged, theyaren'tcountedasdiscouragedworkers.


20

jobseekers.Growinglabourdemandmustthereforemeetreducedlaboursupply;inotherwords,

a virtuous circle has begun which, if it continues, could speed up and intensify the fall in

unemployment. In Lombardy Region, in the second quarter of 2016 there was year-on-year

growth in employment (the number of employed persons was 4,367,000), male employment

rose and female employment decreased. The employment rate of theworking age population

(15-64years)inthefirstquarterof2016stoodat65.8percent.

ThenumberofjobseekersinLombardyin2015fellby3.8percentcomparedto2014.According

to ISTAT, theunemployment rate in the secondquarterof2016was6.9percent compared to

7.8percentinthepreviousquarter.Overall,therewere322,000unemployedpeople.

The first quarter of 2016 showed a decrease of 11percent of hirings comparedwith the first

quarterof2015andrelatedequallytomenandwomen.Alleconomicsectorsrecordedafallin

the number of hirings; agriculture showed the least pronounced fall (1percent), compared to

the construction sector (-19.5percent), industry (-11percent), and tradeand services (-10.8

percent).

As regards employment contract types, overall there was a 6percent increase in agency

contracts between the first quarter of 2016 and the first quarter of 2015 and a decrease in

permanent contracts (-23.5percent), apprenticeships (-9.5 percent), fixed-term contracts (-

4.7percent)andproject-basedcontracts(-32.6percent).

In Lombardy, the difficulties in filling vacancies are attributable equally to the poor skills of

candidates and the lack of availability of the professional profiles sought. On the other hand,

vacanciesarefilledmoreeasilyinpublicutilitiesandinleisureservices.

At a sectoral level, recruitment difficulties are more frequent in IT services and telecoms

(28percentofthetotal),advancedservicestoenterprises(23percent),electricalandelectronic

industries (22percent), metalworking industries (21percent), and textile and clothing

industries(20percent).

Themainsectorsrequiringthegreatestspecificworkexperienceare:construction(74percent),

media and communication (68percent), healthcare and social work (68percent), IT and

telecoms(67percent),andtextileandclothingindustries(66percent).

In 2015, in Lombardy, the recruitment of highly-skilled workers (specialists: 8percent,

technicians:16percent,andasmallnumberofmanagers)cameto32,750,or25percentoftotal

hirings. The hiring of medium-skilled workers, of which 12percent were office workers and

31percent service and trade occupations, was 57,890, or 44percent of total hirings. The

remaining 42,390 planned recruitments were in low-skilled occupations, accounting for

32percentofthetotal.Theyincludedlabourers(21percent)andgenericunskilledoccupations

(11percent).


21

Theoccupationsingreatestdemandwere:skilledworkersintrade,hotelsandrestaurants/bars

(cooks,waiters,bartendersandsimilar),unskilledoccupations in tradeandservices, technical

professionsinorganisational,administrative,financialandtradeactivities,secretariesandoffice

workers,andtechnicalprofessionsinscience,engineeringandproduction.

In2015 inLiguria, theoverallemploymentratewas62.4percent,up1.7percentcompared to

2014,whichwas lower than the average for the NorthWest, but 6.1percent higher than the

national average. Among the employed, men have the largest share (55.1percent), despite

decreasing by 24000 workers compared to 2008 (before the crisis) (-6.6percent); female

employment between 2008 and 2015 remained stable, although the percentage of women

amongtotalpeopleinworkrosefrom43.2percentin2008to44.9percentin2015.

InLiguriain2015,71.6percentofpeopleinworkwereemployees,while28.4percentwereself-

employed.

ThebreakdownofpeopleinworkbyagegroupsshowsthatinLiguriathesituationisespecially

critical for young people: only 3.3percent of people inwork are aged 15-24 years, compared

with 4.1percent of the national figure; 25-34 years-old account for 15.7percent of the

workforceinLiguriaagainst18.2percentatnationallevel.

As to gender differences, in Liguria the greatest gap between men and women in terms of

percentagepointsisfoundintheagegroup25-34years,whereemployedmenare15.1percent

and women 2.6percent of the total by gender, and in the over-65s, withmen outnumbering

womenby2.1percentagepoints.

Breakdown of employment by activity sector shows no significant changes vis-à-vis

2008: services account for almost 80percent of total employment, followed by industry at

20percent. Within industry, the manufacturing sector accounted for 12.7percent of total

employmentin2015.

In2015, according todataobtained fromcompulsory reporting, themostwidelyused typeof

contractcontinuedtobe fixed-termcontracts(44.6percent), followedbypermanentcontracts

(30percent).Comparedto2014,flexibleworkdroppedtothirdplace(16.1percent),withagap

of about14percentagepoints from fixed-term contracts.Between2014 and2015permanent

contracts increased by 65.5percent,while non-standard employment fell by 11.5percent and

apprenticeshipsby19.6percent.

Breakdown by type of occupation shows that 33.2percent of employment was in skilled

occupations in trade and services, followed by unskilled occupations (20.6percent). Office

workers,intellectualprofessions,craftworkers,skilledmanualworkersandfarmersaccounted

foraround11percentofemployment.


22

Compared to 2008, the largest increaseswere in intellectual, scientific and highly specialised

professions(+34.7percent),followedbyskilledworkersintradeandservices(+16.9percent),

which show that in years of crisis people with very specific professional skills and highly

intellectualskillscouldbemoreattractive for the labourmarket.Conversely, therehasbeena

significant drop in legislators, managers and businesspeople (-46.6percent) and technical

occupations(-41percent).

TheunemploymentrateinLiguriaincreasedfrom5.4percentto9.2percentbetween2008and

2015,althoughit fell from10.8percentto9.2percentbetween2014and2015.Withregardto

thegendercomponent,femaleunemploymentinparticulardecreasedinLiguria(-17.1percent,

correspondingto6000people),whilemencontinuetobethelargestcomponent(53.2percent)

ofthoseseekingemployment.

Inspiteoftheimprovementinthefemaleunemploymentrate,therelativerate,whichwasdown

on the previous year, was nonetheless higher than themale unemployment rate (9.5percent

comparedto8.9percent).

The rise in unemployment mainly concerns workers who lost a previous job and first time

jobseekers(whomadeup21percentofunemployedpeopleinLiguriain2015and27.2percent

ofthenationalaverage).

Between2014and2015thegrowthinemploymentwassolelyduetothegoodperformanceof

services (+14000 jobs, corresponding to +3percent), while industry lost a thousand jobs (-

0.8percent), mainly due to the decline of employment in manufacturing (-5000 jobs,

correspondingto-6.6percent).

InLiguriaon1January2015therewere114984non-EUnationalslegallyresident,representing

7.2percentofthetotalregionalpopulation.

AccordingtotheISTATdata(RCFL-ContinuousLabourForceSurveyannualaverage2015),the

employment rate (15-64 years) of non-EU foreign nationals was 58percent; around 4

percentage points lower than the overall regional rate (62.4percent). Among EU nationals,

however,theemploymentratewas69.4percent.Therewere50645employednon-EUnationals

(aged15andover),ofwhom51.5percentweremen.

Theunemploymentrate(aged15andover)ofnon-EUforeignnationalswas20.1percent,more

thandoubletheoverallregionalfigure(9.2percent).

Employedforeignnationals(aged15andover)tendedtobeyoungerthanItalians:64percentof

non-EUworkerswereunder theageof44year(among Italians the figure falls to44percent);

themajorityofemployedforeignnationalswereintheagegroup30-44.


23

Companies in Liguria showed a largely stable trend compared to 2015,with a growth rate of

0.10percent.Therewere163,418businessesregisteredasattheendof2015,andthebalance

betweenregistrationsandclosureswaspositive,standingat163.

In terms of changes in registration, taking into account joint changes in registrations and

closures, the sectors struggling most appeared to be construction, trade, transport and

warehousing,andaccommodationandfoodservices,whilerental,travelagenciesandbusiness

supportservices,realestateactivitiesandmanufacturingshowedapositivetrend.

Morecriticalisthesituationofcraftbusinessesatalllevels:national,regional(NorthWest)and

Liguria.Growthratesincreased,withtheexceptionofLiguria,comparedto2014,butwerestill

innegativeterritory.TheNorthWestfell from-1.15percentto-1.08percent,while inLiguria

the figure fell from0.66percent in2014to -0.93percent in2015andwasnegative inall four

provinces.

AlthoughtheoveralltrendforcompaniesinLiguriaappearedtoshowresilienceratherthanfull

recovery,itisimportanttorecallthattorevivetheeconomy,thedifficultsituationinwhichcraft

businesseshavebeenstruggling foryearscannotbe ignored,giventhatcraftbusinessesmake

upasignificantproportionofthelocaleconomy(27.5percent).

The employment situation for the best qualified deserves attention: the employment rate of

graduatesofdifferenttypesattheUniversityofGenoa(LiguriaRegion)in2015,oneyearafter

graduation,was58.9percentandmorethanhalf(55percent)saidtheymadelittleornouseat

alloftheskillstheygainedduringtheiruniversityeducation,andprobablyalsocarriedouttasks

forwhichauniversitydegreewasnotrequired.Also,oneyearaftergraduation,theemployment

rateofgraduateswithmaster’sdegreesandsinglecycledegrees(76.6percentand62.7percent

respectively) was significantly higher than that of graduates having only a bachelor’s degree

(48.9percent). The academic disciplines with higher unemployment rates include

geology/biology,architectureandsocialandpoliticalsciences; thedisciplineswith thehighest

employmentratesaremedicineandhealth,engineering,teachingandscience.

Inparticular,oneyearafterobtainingabachelor’sdegree,theunemploymentratedeclaredby

respondentswashigherforthosehavingadegreeinsocialandpoliticalsciences(30.7percent),

geology/biology (30percent), law (29.3percent) and architecture (26.3percent). Conversely,

the unemployment rate was lower for psychology-related subjects (4.3percent), the sciences

(7percent)andphysicaleducation(10.5percent).

One year after obtaining a master’s degree, there was a higher unemployment rate in

geology/biology-related subjects (43.1percent), physical education (25.1percent) and

architecture(21.3percent);meanwhile,theemploymentratewashigherinthefieldofmedicine

andhealthcare(92.9percent),engineering(89.6percent)andteaching(86.2percent).


24

Based on the average 2015 data, this trend was more pronounced in Liguria than in Italy,

although it was noteworthy that female graduates conversely had a higher rate of

unemployment thanmenwith similar qualifications. In Liguria, the situationwas the reverse

withregardtohighschooldiplomas,withthefemaleunemploymentrateat7.9percentandthe

malerateat8.9percent.

5. RedistributionandsocialinclusionThe Italian welfare state is considered by the literature on comparative welfare state as

‘familistic’ welfare systems, in the consideration of the key role that the family plays in the

overarchingarchitectureofthewelfaresystem,actingasthemainproviderofcareandwelfare

forchildrenanddependent individuals.At thesametime,wecandefine the Italianwelfarean

unbalancedsystemifweconsiderthesubdivisionofexpenditurebyfunctions.Currenttrendsof

thesocialexpenditurehighlightingtheinertiaoftheItalianwelfarestate.Startingfromearly’90

the Italian public spending on social protection increased, according to the main European

countries,butthisdatait’snotenoughtodescribetheItaliancase.

Table4-Netsocialprotectionbenefits

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

EU (27 countries) 25.1 24.8 24.2 24.9 27.5 27.5 27.3 27.6 27.8 27.6Italy 24.4 24.6 24.5 25.5 27.5 27.6 27.4 28.0 28.7 28.8

Source:Eurostat Asmatterof fact, ifweput the focuson thespecificityof thepublicspendingwecandiscover

someinterestingevidences.Ifthegrowthinthevolumeofsocialexpenditurehasbeenmatched

bymarked fixity in the subdivision of expenditure by functions, the data shows that the only

dynamicelementisexpenditureonold-ageandsurvivorpensions.Consideringthetotalamount

ofsocialsecurityspending(includedthepensions)inoverallsocialprotectionexpenditure,Italy

spendsmorethantheotherEuropeancountries.

ThesocialandeconomicchangeshappenedinItalyinthelastdecades,havenotbeenmatched

byanalogouschangesinthewelfaresystem.Thewelfaresystemstructurehasremainedlargely

unchanged,withfewsignificantexceptions:thereformofthepensionssystem(startedbetween

1992and1995fromthe“Amato”and“Dini”reformsuntil2011withthe“Fornero”reform);the

reformsandthechangesinthelabourmarketregulation(in1997(“Treu”Reform),2001(“Biagi”

Reform)and2014(thejob’sact)andin2017thefirststepoftheminimumincomepolicy,(REI

reddito minimo di inclusione). The amount of expenditure on social protection in Italy has


25

grownatarategreaterthanthatofGDP.In2014isnear7percent,lowerthanEUaverage,for

health care, but higher for old age (11.50 percent) and lower for other social problems, like

disability,housingandsoon.Duringthelasttwentyyears,therehasbeennoreconfigurationof

theItalianwelfarestateabletoincludethenewsocialriskswithintheexistingsocialprotection

system.

If anything, observation of the redistributive effects exerted by thewelfare system shows the

reverse:theevolutionofItalianwelfarehascontributedtoanincreaseinsocialimbalancesand

inequalities.Withoutsignificantchanges in thewelfarestatesystem, thewelfarebenefitshave

beendistributedmainlytotheadvantageoftheinsidersinsteadoftheoutsiders.Theoutcomeof

these dynamics has been that the dualism, between insiders and outsiders, historically

characteristicofItaly’swelfaresystem,likethoseoftheothersouthernEuropeancountries,has

been increased by the joint effect of the absence of the structural welfare system’s reform

(Ferrera1996,RanciandMigliavacca2015).

ItalyisamongonethemainEuropeancountrieswiththehighestlevelsofincomeinequalityas

thedata shows this.Gini coefficient after social transfer is, in2015,32.4,higher thanEU (18)

average,31.0.Thelevelofthepeopleatriskofpovertyorsocialexclusionislargerandislineas

theworstsituationoftheothersouthernEuropeancountries.

Theshareofthepopulationat-risk-of-poverty-or-social-exclusion(AROPE)stabilisedcloseto29

percent in2015,oneof thehighest rates in theEU. In addition, thereare substantial regional

disparities,withverylargedifferencesinAROPEratesbetweennorthernandsouthernregions.

The structure of the economy explains a large part of the different internal outcomes. For

examples, aboutour functional regions, thedata shows that inLiguria the riskofpovertyand

social exclusion is higher than in Lombardy. In fact, the ratio in Liguria grewby18.9 percent

from 2005 to 2015 rising 25.8 percent (EU27 23.7 percent; Italy 28.7 percent), while in

Lombardy by 29.4 percent at the same period considered rising 17.6 percent. People in

conditionofseveredeprivationwasin201511.6percentinLiguria(similartothenationaldata)

adonly6.4percentinLombardy.Also,peoplelivinginhouseholdswithverylowworkdensityis

higherinLiguriathaninLombardy(8.7percentvs.5.3).

Nevertheless,inboththeRegionshouseholds’incomeishigherthanaverage(in2013Lombardy

19.770euros,inLiguria18.500,vsanationalaverageof16.100euros;in2014,averageincome

perinhabitantwas20.200inLombardy,19.200inLiguriaand16.600atthenationallevel).


26

Figure7-PeopleatriskofpovertyorsocialexclusionbyNUTS2regions,2012-2015

Source: EU-SILC

6. Healthandwell-beingFor more than a decade the European health system has undertaken reforms aimed at

rationalizingresourcesandlimitingspending,howeverpublicfundingisstillthemainoptionfor

healthservices.

TheshareofprivatehealthexpenditureinItalywas24.5percentofthetotal in2015,equalto

Estonia and Finland. Health public expenditure in Italywas below other important European

countries;against2,431USDperinhabitantatpurchasingpowerparity,spentinItalyin2014,

theUnitedKingdomandFrancespentover3,000andGermany4,000perinhabitant.

Asforhospitalbedsupply,ItalywasstillbelowEU28averagein2014(3.4against5.2bedsper

thousand inhabitants). Liguria and Lombardy have similar indicators referring to

beds/thousandinhabitants(3.4vs.3.7),butinLiguriathereisagreateravailabilityoflong-term

curativebeds(12.5per100,000inhabitants,vs.8.7)andagreaterpresenceofmedicaldoctors


27

(442.1 per 100,000 inhabitants, vs. 358.6) or nursey and midwives (981.2 per 100,000

inhabitants,vs.684.9),wesupposeforthegreaterweightofolderpeople.

In2015,currentpublichealthexpenditurewasabout112billionEuros(1,838Eurosperyear

perinhabitant),equalto6.8percentofGDP.

Per capita public expenditure at a regional level is highly changeable because of differences

existing in the socio-economic conditions and in the management models of regional health

systems.

AwidegappersistedbetweentheNorthandtheSouthandIslandsareaasforhospitalbeds.

Thehospital systemsofLombardy,Emilia-RomagnaandToscanawere confirmedaspointsof

attractionforadmissionsofnon-residentpatients.

Where people live has an important impact on their opportunities to livewell. There can be

large differences in average levels ofwell-being in different regionswithin the same country.

How’sLifeinyourRegion?andtheOECDregionalwell-beingweb-toolassessperformanceacross

9dimensionsofwell-beinginthe362OECDlargeregions–21ofwhichareinItaly.

Italy’sperformanceacrossthedifferentwell-beingdimensionsismixed.

The chart below by OECD Better Life Initiative shows areas of well-being strengths and

weaknesses in Italy, based on a ranking of all OECD countries. Longer lines show areas of

relativestrength,whileshorterlinesshowareasofrelativeweakness2.

Figure8-Italy’swell-being

Source:OECDcalculationbasedontheOECDBetterLifeIndex2016database,http://stats.oecd.org/Index.aspx?DataSetCode=BLI.

2Formoredetails,seewww.oecd.org/statistics/Better-Life-Initiative-2016-country-notes-data.xlsx.�


28

In general living conditions in Lombardy are better, and this evaluation emerges both from

objective data, both fromperceptions of citizens.Wemust consider that Liguria is the region

withtheoldestpopulation,assaidheavilyaffectedbyeconomicanddemographiccrisis,caused

serious disturbance in educational and social sectors. Less young people in an ageing context

withfeweropportunitiesandagreaterpartofpopulationatriskofsocialexclusioncontribute

alsotolowerlevelsofsubjectivewell-beingandlowerexpectationsforthefuture.

7. ConclusionsItaly is “convalescing” after a deep and long recession. Structural reforms, accommodative

monetaryandfiscalconditions,andlowcommoditypriceshaveaidedtheeconomytoturnthe

corner. The ambitious structural reform programme, named Jobs Act, and social security

contribution exemptions for new entries have developed the labour market and improved

employment.Yet, therecoveryremainsweakandproductivitycontinues todecline.Returning

the banking system to health will be crucial to revive growth and private investment. More

investmentininfrastructurewillbeessentialtoincreaseproductivity.

Raisingchronicallylowproductivitygrowthwillrequireamoreeffectivepublicadministration,

an improved business environment, increased innovation, stronger competition, and a better

match between the demand and supply of skills. The Good School reform also aims at

strengthening links between school and the labour market by mandating school-to-work

experiencesforallstudentsinthelastthreeyearsofsecondaryschool.Intensiveinvolvementof

thebusinesssectorandotherstakeholderswillbekeytoensuringthecreationofqualityschool-

to-work schemes that will help the development of relevant skills for the labour market. An

assessmentsystemaimedatverifyingthequalityoftrainingcarriedoutintheworkplacement

willneedtobeimplemented.

Literacy scores are low and job-skill mismatch is one of the highest among OECD countries,

depressing earnings and well-being. Many workers are under-skilled in the jobs they hold,

emphasizingmismatchesbetweenworkers’skillsandthoserequiredbyemployers.Linkingthe

education systemand labourmarketpoliciesare crucial to raising realwages, job satisfaction

andlivingstandards.TheJobsActandtheGoodSchoolreformgointherightdirectionandneed

tobefullyimplemented.

Italyhasasmallshareofstudentsinhighereducation.Atthesametime,thedifferencebetween

the earnings of tertiary-educated graduates relative to those of adults with only upper

secondary education is low in Italy compared to the OECD average. Furthermore, the

unemployment rate among tertiary educated adults is among the highest in OECD countries.


29

Hence,labourmarketoutcomesoftertiaryeducatedmaketheinvestmentintertiaryeducation

unattractive,atleaststillatechnical-professionaltrackisnotimplemented.

Educationexpenditure is low,particularly in tertiaryeducation,bothrelative toGDP(Italy1.0

percentofGDP2016;1.6percentOECDaverage)and to thenumberof students (expenditure

per student was 71 percent of the oECD average). More funding will be crucial point to

improving the quality of education. Given limited fiscal room, one alternative could be to

increasetuitionfees,whicharelowcomparedtootherOECDcountries(OECD,2017).

Apprenticeshipsareakeyinstrumenttohelpyoungpeopletogainusefulwork-relevantskills.

However,theyareunderutilised.ThemainchallengeforapprenticeshipsinItalyistheweaklink

betweenwork and education. Themost common apprenticeship, is onlyweakly connected to

formal education and under this type of contract less than one third of apprentices were

enrolledinformaleducationin2013.Inothertypeofcontracts,accesstotraining–asrequired

by law–dependson the initiativeof enterprises. Furthermore, there isnonational system to

controlandmonitorthetrainingprovidedbyfirms.Specificqualitycriterianeedtobesetand

enforcedforcompaniesofferingapprenticeships.

Participation in vocationally-oriented tertiary programmes is low in Italy compared to other

OECD countries. In recent years, Italy has taken several steps to create tertiary education

programmespreparing students for a rapid entry into the labourmarketwith the creationof

hightechnicalinstitutes(IstitutiTecniciSuperiori–ITS).TheexperienceofITShasbeenpositive

as graduating students have high level of employability (INDIRE, 2016). The success of ITS is

attributable to its responsiveness to labour market needs, as they benefit from strong

involvement of the business sector, universities and higher secondary education. The full

potentialofITSremainsuntappedastheyareconcentratedinthemostindustrialisedregionsof

Italyandfemaleparticipationislow.EnrollmentinITSisnegligiblecomparedtoothertertiary

educationalpaths,basicallybecauseitrequiresadditionalfunding.

Italymust construct on the positive experience of ITS and establish a VET system at tertiary

level based on apprenticeships. Professional degrees are going to be introduced in national

tertiary education systemand couldhelp to reduce thedistance between educational outputs

andlabourmarketrequirements.

Thiswouldhelpmatchthetrendofrisingdemandformedium-andhigher-levelqualifications,

which are projected to reach 82.5 percent of the labour force in 2025, against less than 80

percenttoday(CEDEFOP,2015).Establishinganationalbodyinvolvingthebusinesssectorand

other key stakeholders would improve strategic planning and coordination, and ensure the

education-working experiencemix reflects not only student preferences but also local labour

marketneeds.


30

Alltheabove-mentionedissuesshallbevalidforbothourFunctionalRegions,butitisimportant

to note that Lombardy need less interventions in all area descripted by the indicators than

Liguria,asrevealedbythestatisticaldata.

ReferencesAdaletMcGowan,M.andD.Andrews(2015),"SkillMismatchandPublicPolicyinOECDCountries",OECDEconomicsDepartment Working Papers, No. 1210, OECD Publishing, Paris.http://dx.doi.org/10.1787/5js1pzw9lnwk-en.

ASSOLOMBARDA(2016),http://www.assolombarda.it/investing-in-the-territory/data-sheets-by-area/.

BiondoA.E.,MonteleoneS.,SkoniecznyG.,TorrisiB. (2012),Thepropensity toreturn:Theoryandevidence for theItalianbraindrain,EconomicsLetters,115,pp.359-62.

Consorzio Interuniversitario AlmaLaurea (2016), XVIII Indagine Condizione occupazionale dei Laureati,http://www.almalaurea.it

CrouchColin(1999),SocialChangeinWesternEuropeOxford:OxfordUniversityPress.

CRUI (2016), Università e ricerca. Pilastri su cui fondare lo sviluppo economico e sociale del Paese,https://www.crui.it

EuropeanCommission(2017),CountryReportItaly2017,https://ec.europa.eu/info/sites/info/files/2017-european-semester-country-report-italy-en_0.pdf

EUROSTAT(2017).TheEuropeanUnionLabourForceSurvey(EU-LFS),http://ec.europa.eu/eurostat.�

Ferrera,M.(1996):‘The“SouthernModel”ofWelfareinSocialEurope’,JournalofEuropeanSocialPolicy6/1,pp.17–37.GenoaportauthorityAuthority(2016),http://servizi.porto.genova.it.

INDIRE (2016), “Istituti Tecnici Superiori (High Technical Institutes)”, National Institute of Documentation,InnovationandEducationalResearch,www.indire.it/approfondimento/its-istituti-tecnici-superiori.

ISTAT(variousyears),http://www.istat.it/it.

Mandrone,E.(2014),“YouthGuaranteeandtheItalianPES: insights fromISFOLPLUSSurveydata”,CIMRResearchWorkingPaperSeries,WorkingPaper,No.21.

MigliavaccaM., Ranci C. (2015), Everything needs to change, so everything can stay the same’: The Italianwelfarestatefacingnewsocialrisks,inAscoliU.andPavoliniE.,TheItalianwelfarestateinaEuropeanperspective,Bristol,PolicyPress.Pp.21-48.ISBN9781447316886.

Monti,P.andM.Pellizzari(2016),“SkillMismatchandLabourShortages intheItalianLabourMarket”,PolicyBrief,No.02,BocconiUniversity.EmploymentSkillsandProductivity in Italy–AResearchProjectcoordinatedby IGIER-Bocconi,inpartnershipwithJPMorganChaseFoundation.

OECD(2014),TALIS2013Results:AnInternationalPerspectiveonTeachingandLearning,Paris:OECDPublishing

OECD(2016),EducationataGlance2016:OECDIndicators,http://www.oecd-ilibrary.org/education/education-at-a-glance-2016_eag-2016-en

OECD(2017),TheEuropeanUnionStatisticsonIncomeandLivingConditions(EU-SILC),https://data.oecd.org

OECD calculation based on the OECD Better Life Index 2016 database,http://stats.oecd.org/Index.aspx?DataSetCode=BLI

OECDProgrammeforInternationalStudentAssessment(PISA),http://www.oecd.org/pisa

ProgrammeforInternationalAssessmentofAdultCompetencies(PIACC),http://www.oecd.org/skills/piaac


Work Package 4


Portugal –

National Briefing Paper with national and regional data sets

Mariana Rodrigues, Ana Bela Ribeiro and Tiago Neves (University of Porto)

António José Almeida, Natália Alves and Rita Queiroga (University of Lisbon)

Date 2017/09/10 Work Package 4 – Quantitative Analysis of Young Adults’ Data Deliverable 4.1


2

Tableofcontents

ExecutiveSummary............................................................................................................................................................3Introduction...........................................................................................................................................................................5Descriptionofthedatacollatedandqualitydataassessment........................................................................5Findings...................................................................................................................................................................................61. Demographicstructure............................................................................................................................................62. GeneralstateoftheEconomy...............................................................................................................................83. Education....................................................................................................................................................................114. Labourmarket..........................................................................................................................................................155. Redistributionandsocialinclusion.................................................................................................................206. Healthandwell-being...........................................................................................................................................22FinalRemarks....................................................................................................................................................................25References...........................................................................................................................................................................26Listoffigures

FIGURE 1: GDP in euro inhabitants (left axis) and labour productivity (right axis, EU=100),

Portugal,NorteandAlentejo,2006-2015...........................................................................................9

FIGURE2:Populationchangeandmigration(rightaxis),olddependencyandfertilityrates(left

axis),Portugal,NorteandAlentejo,2005-2015..............................................................................7

FIGURE3:Percentageofpopulation(25-64)withISCED0-2,ISCED3-4andISCED5-8,in2005

and2014.........................................................................................................................................................12

FIGURE4:Participation(%)intertiaryeducationofpopulationaged20-24,2005-2012..............14

FIGURE5:Percentageofyoungpeopleaged15-24neitherineducation,employmentortraining

(NEET;leftaxis)andearlyleaversaged18-24(rightaxis),Portugal,AlentejoeNorte,

2012-2016......................................................................................................................................................15

FIGURE6:Employmentrate(20-64)inEU27,Portugal,NorteandAlentejo........................................16

FIGURE 7: Youth employment and unemployment rates, youth unemployment ratio of young

people15-24(rightaxis),EU27,Portugal,NorteandAlentejo,2005-2015.....................17

FIGURE8:Unemploymentrate(20-64)inEU28,Portugal,NorteandAlentejo...................................18

FIGURE9:Long-termunemploymentrate(20-64)inEU27,Portugal,NorteandAlentejo............19

FIGURE10:GINI indexbeforeandafter transfers,disposable income in thehouseholds inPPS

(rightaxis),EU27,Portugal,NorteandAlentejo,2005-2015..................................................21

FIGURE11:Highsatisfactioninvariouslifedomains,age25-34,EU28andPortugal,2013..........24


3

ExecutiveSummary

Thisnationalbriefingpaperprovidesashortoverviewofthelivingconditionsandriskprofiles

of young adults in Portugal and in the functional regions of Vale doAve andAlentejo Litoral,

selected as case studies for the YOUNG_ADULLLT project. The contextual living conditions of

young people are analysed by looking at available indicators at NUTS 0 and NUTS 2 level,

collected by the working package leaders and integratedwith NUT 3 data when available or

provided by the Portuguese National Statistics Institute (INE) and the Database of

Contemporary Portugal (PORDATA), as well as by other institutional sources, along the

followingdimensions:demographicstructureofthepopulationanditssubgroups;generalstate

of the economy; education; labour market; redistribution and social inclusion; health and

individualwell-being.

Two of the main demographic characteristic are the growing ageing of the Portuguese

populationbothatnationalandregionallevels,andthehighpercentageofyoungadultsaged20-

29livingwiththeirparents.Duringthetimespan,andinspiteofthefinancialcrisisandTroika’s

intervention the GDP and the GVA increased at national and regional levels. However, the

performance of the Portuguese economy measured by GDP per inhabitant and labour

productivityisstillconsiderablylowerthantheEU28average.

Between 2005 and 2016, the structure of academic qualifications of the Portuguese

population has improved significantly both nationally and regionally. The rates of school

attainment increased in all age groups, the ratio of early school leavers and the rate ofNEET

declinedsignificantly.However,whencomparedtootherEuropeanpartnercountries,Portugal

stillrevealsthelowestratesofschoolattainmentevenamongtheyoungergenerations.

Inspiteofanimportantskillsupgradingduringthedecade,theoccupationalstructureofthe

Portuguese labour market is less qualified than the EU27 average. The Portuguese youth

employment rate (15-24 years old) is one of the lowest in EU27 and decreased consistently

during the time span 2005-2015, showing important differences at regional level.

Unemployment is mainly a youth problem, particularly after 2011. In 2015, the Portuguese

youthunemploymentratewasmorethanthedoubletherateofpeopleagedbetween20and64

years and higher than the EU28 average. Once again, significant regional differences can be

found. Generally, theNorte labourmarket seems to bemore youth friendly than theAlentejo

one.

In Portugal, resources spent for social protection benefits, provided to households and

individuals affectedbya specific setof social risksandneeds isoneof the lowest inEU27. In

spiteofthefinancialcrisisandthegrowthofunemploymentrate,theexpenditureperinhabitant

didn’t rise significantly and the expenditurewith family and children and social exclusion are

thoseweretheunderfundingismoreseverewhencomparedwithEU27.Theincomeinequality


4

started to increase strongly after 2011, transforming Portugal in one of the most unequal

countriesinEU.

During the time span 2005-2015, self perceived health in Portugal has always been lower

thantheEU27average.PortugalwasalsothecountryparticipatinginYOUNGADULLLTproject

withthelowestself-perceivedhealth.Ingeneral,Portuguesepeopleagedbetween25-34years

arecomparativelylesssatisfiedwiththeirlives.

ThedatashowthatthelivingconditionsofyoungpeopleinPortugalareworsethantheEU28

average. They also reveal some regional differences which point to the fact that the living

conditions are slightly better in Norte, where Vale do Ave is located than in Alentejo where

LitoralAlentejano’syoungpeoplelive.


5

Introduction

Thisbriefingpaperoffersaconciseoverviewof the livingconditionsofyoungpeopleandrisk

profiles in Portugal and, particularly, in Vale do Ave and Litoral Alentejano, the two national

functionalregionsselectedforanalysisbythePortugueseteamoftheYOUNG_ADULLLTproject.

Dataweregatheredatnational(NUTS0)andregional(NUTS2and3)levelwithregardtothe

sixdimensionsagreeduponintheWP4proposal.Thesedimensionsrepresentdifferentaspects

ofthecontextuallivingconditionsofyoungadults’experiences,concretely,theeconomiccontext

and structure of the productive system; demographic characteristics; the access, process and

outputsofeducationandtrainingsystem;theinteractionbetweenlabourmarket,welfarestate

andeducationstructures;themateriallivingconditionsofyoungpeopleandtheirparticipation

ascitizensinthepoliticalandciviclife;andthehealthstatusandindividualwell-being.Thejoint

datasetwaselaboratedmainlybasedontheEUROSTATdatabase;however,othersourceswere

alsoused,suchastheOECD,UNESCO,Eurydice,WorldBank,UNIDEMO,PISA,LFS,ESA,EU-SILC,

ESSPRO,DGEMPL,andSES2014.Themaincorpusofdatawas thencomplementedwithdata

collected at the functional regional level (NUTS 3), which were available or provided by the

Portuguese National Statistics Institute (INE) and the Database of Contemporary Portugal

(PORDATA), as well as by other institutional sources (such as Directorate-General of the

Ministries).Thisreportisbasedonadatacollectionovera10-yearspan,rangingfrom2006to

thelastyearofdataavailable(e.g.,2015).


TheEurostat,OECDandUNESCOdatabasesaggregateahugeamountofdata.Thiscanbeuseful

when comparing different dimensions of the contextual living conditions of young people in

variouscountriesorregions.However,datainallsixdimensionsofanalysisaremainlyavailable

at the national level (NUTS 0). This means that access to data at regional level (NUTS 1) is

somewhat limited, and at local level (NUTS 2) it is actually very limited. These limitations

constituteconstraintsonthecomparabilityofsomeindicatorsbetweenlocalfunctionalregions.

Besides,itisimportanttoacknowledgethatcomplementingtheavailableandharmoniseddata

withlocaldatacanbeadifficultandtime-consumingprocess,mainlyduetoissuesrelatedtothe

heterogeneity and fragmentation of data sources. This can be seen, for instance, in the

inconsistency of the concepts and analytical categories used, aswell as in the available time-

series. Since local data are collected within a particular framework and there is no prior

intentiontobringthemintointeractionwithotherdatasources,thisaffectsthepossibilitiesof


6

contextualised comparison between the different national cases. Just to illustrate, in Portugal,

theexistingdatasourcesgrouptogetherretentionandschoolleavingrates,whiletheEuropean

datasourcesprovide therepetitionrate.For thesereasons, themostsignificantdatasource is

EUROSTAT, since this database provides metadata and completed time-series, even if not

completelyconsistentor flexible.So,acomprehensive integrationandanalysisofmulti-source

data at the different levels of analysis is a hard goal to accomplish; therefore, this research

intends to raise awareness for the need and relevance of contextualised data at regional and

local level inordertobeabletoproducea fullpictureof theriskprofilesderivedof the living

conditionsofyoungpeopleindifferentEuropeanregions.

Findings

1. DemographicstructurePortugalislocatedinSouthernEuropeandisarelativelysmallcountry,coveringatotalareaof

92,200 square kilometres. The area of the Norte region is 21,286 square kilometres, while

Alentejo is 31,605 square kilometres. Thepopulationdecreasedby2.2%over the last decade

(2006-2016), from 10.5 million to 10.3 million inhabitants (with 111 women per every 100

men) in 2016; this corresponds to 2% of the total EU28 population. Norte is much more

populated than Alentejo (3.6 million against 0.72 million people), even if it covers a smaller

territory. The national population density accounts for 113 persons per square kilometre in

2014(less0.88%since2006).ThePortuguesepopulationhasanunequaldistributionacrossthe

country:atregionallevel,theNorteisclearlydenserthanAlentejo(-64%);andatlocallevel,Ave

has an incredibly high population density when compared to Litoral Alentejano (-151.1%)1.

Furthermore,theaveragePortuguesepopulationisageingconsiderably:from2005to2016,the

medianageincreasedfrom39.2to44years.Thesamesituationhappenedattheregionallevel:

from37.6 to43.8 years inNorte and from43.2 to46.7 years inAlentejo. Youngerpopulation

aged 15-24 and 25-29 has decreased in the last years, and now accounts for 5.3% and 5.4%,

respectively,of the total inhabitants in2015.Alsoat theregional level, therewasasignificant

reduction in the proportion of these age groups in the population since 2005, reaching

respectively5.6%oftheyouthaged20-24andaged25-29inNorte,and4.8%and5.6%ofthe

youthaged25-29inAlentejoin2015.

Thenational cruderateofnetmigrationdecreasedsignificantlyafter2010, reaching -3.60

per1,000inhabitants in2012.Onlyafter2014didthesituationbegintochange,withtherate

risingfrom-2.90to-1.00per1,000personsbetween2014and2015.After2008,theeconomic1 Source:https://www.ine.pt/xportal/xmain?xpid=INE&xpgid=ine_indicadores&indOcorrCod=0008337&contexto=bd&selTab=tab2


7

crisis obviously affected thedemographic structure of the country,withmore intensity in the

Norte, since a lot ofpeople left thePortugal andmoved toother countries,more attractive in

terms of employment and remuneration, between 2010 and 2014 (FIGURE 2). In 2015, the

crude rate of net migration started to show signs of change at national and regional level,

probablyduetotheslowdownoftheemigrationprocess.

FIGURE 1: Population change and migration (right axis), old dependency and

fertilityrates(leftaxis),Portugal,NorteandAlentejo,2005-2015

Source:Eurostat

Birthandlifeexpectations inPortugalaregood, like inmostotherEuropeancountries.The

infantmortality,inthefirstyearafterbirth,hasbeendecreasingconstantlysince2005,totalling

2.9deathsper1,000in2016,whileintheEU28itwas3.6.LifeexpectancywasPortugalis81.3

years in2015. In termsofgenderdifferences, the female lifeexpectancy is longer than thatof

males(a6.4yearsdifference).Attheregionallevel,inAlentejo,theaveragelifeexpectancy(80.8

years) is lower than the national average,whilst inNorte it is higher (81.7 years) (data from

2015). When compared to other European partners, Portugal had the lowest fertility rate in

2014 (1.23).From2006 to2014, thenational fertility ratedecreased14.6%.Not surprisingly,

duringthistimespan,thefertilityalsodiminishedatregionallevel:21.1%inNorteand12.2%in

Alentejo. At the same time, the age at which awoman gives birth to her first child has been

increasingcontinuouslysince2005,reachingtheageof29.5yearsin2015(2.2yearsmorethan

10yearsago).Thecombinedeffectofincreasedlifeexpectancyandlowerfertilityisproducing


8

some changes in the living conditions of European countries; this is not only visible in the

populationaging,butalsointheolddependencyrate(theratiobetweenpopulationaged65and

overtopopulationagedamong15and65).Thisindicatorhasbeenrisinguninterruptedlysince

2005,from25.7%to31.8%in2014.Thisriseovertime(2005-2014)oftheolddependencyrate

isalsonotedinbothregions,moreprecisely,28.3%inNorteand7.9%inAlentejo.Contraryto

olddependency, thenational young-agedependency rate has beendeclining in the last years,

from23.9%in2005to21.7%in2016.Between2005and2016,therewasthesametrendatthe

regionallevel,reaching20.1%inNorteand20.7%inAlentejoin2016.

ThepercentageofPortugueseyoungpeopleaged20-29livingwiththeirparentshasgrown

since 2006, amounting to 71.6% in 2013. When comparing Portugal with other European

countries,thepercentageofyoungpeoplewhostill livewiththeirparentsismuchhigherthan

theEU28average(55.4%)andtheNorthernEuropeancountries(e.g.,Finland,UnitedKingdom

orAustria),butquitesimilartootherSouthernEuropeancountries(e.g.,Italy,SpainorCroatia).

Intermsofgenderdifferences,thepercentageofyoungmaleslivingwiththeirparents(76.6%)

ishigherthanthatofyoungfemales(66.6%).However,thepercentageofbothPortugueseyoung

malesandfemales(aged20-29)wholivewiththeirparentsishighertotheaverageoftheEU28

(63%and47.7%,respectively).

2. GeneralstateoftheEconomy

FIGURE 1 presents some aspects of the Portuguese economic landscape, from 2006 to 2015.

Basically, the gross domestic product per inhabitant (GDP) increased from 20,400 to 22,200

euro, however, it remained23.2% lower thanEuropean average (EU28) in2015. In the same

period,attheregionallevel,nevertheless,theGDPinbothNorteandAlentejoregionsincreased

overtime(18,700and20,100euro,respectively),evenin2015itremainedsignificantlybelow

otherEuropeancountries,showingadiscrepancyof54.4%and43.8%fromtheEU28average.

DatadrawnfromthePortugueseNationalStatisticsInstitute(INE)2showthat,atthelocallevel,

therewasanincreaseoftheGDPperinhabitantfrom2006to2013.However,itisimportantto

point out the extraordinarydifference inGDPbetweenboth functional regions, since theGDP

perinhabitantinLitoralAlentejanoisnotonly70%higherthantheoneinAve,butalso32.9%

greaterthanthenationalaveragein2013.Itisrelevanttomentionthatthereareconsiderable

discrepanciesregardingtheGDPperinhabitant,from2006till2013,whencomparingdatafrom

EUROSTATandINE.Justtogiveanexample,in2006,thenationalGDPaverageis15,800euroin

INEand20,400euroinEUROSTAT.

2 Source:https://www.ine.pt/ngt_server/attachfileu.jsp?look_parentBoui=224212953&att_display=n&att_download=y


9

However,overthelastdecade,therateofgrowthofthePortugueseeconomywasnotlinear,

oscillatingacrosstime.Theeconomicandfinancialcrisis,whichemergedin2008,broughtabout

yearsofprofoundchallengesforEurope,particularlySouthernEurope.From2008to2009,the

Portuguese GDP per inhabitant decreased from 21,000 to 20,100 euro. Despite some

improvementsbetween2009and2010,Portugalhasbeenineconomicrecessionfortwoyears,

which can be perceived by the drop in differentmeasures between 2010 and 2012: the GDP

(from20,900to20,000euro);therealgrowthrateofregionalgrossvalue(GVA)(from0%to-

1.9%);andthelabourproductivitymeasuredinGDPperhourworked(from69.7%to67.9%).

Various factors may have contributed to this economic framework: the Troika’s intervention

(2011-2014)isoneofthem,sinceitimposedsevereausteritymeasurestothecountry.

FIGURE 2: GDP in euro inhabitants (left axis) and labour productivity (right axis,

EU=100),Portugal,NorteandAlentejo,2006-2015

Sources:EurostatandPortugalStatistics(microdata)

Since 2013, the Portuguese economy started to show some positive signs of recovery,

expressed,forinstance,intheincreaseofGDPandGVArates.Bothregions,NorteandAlentejo,

havealsopresentedevidenceof improvement in these twoeconomic indicators.Despite these

achievements, thenational labourproductivity ratedecreaseduntil 2015 (-1.7%). In fact, this

indicatorwasconsiderablybelowEU28foralldecade(rangingfrom-32%to-30.2%).

Aswith other countries, the service sector is dominant in thenational economic structure,

representing75.4%oftheGDPin2015,whichisahighervaluecomparedtoalmostanyother


10

partner countries (excluding the United Kingdom). The service sector is followed by the

agriculture sector (2.33%),which is remarkably larger than the average for theEU28.On the

contrary, the shareof the industry sector in thePortugueseGDP is lower than in theEU28 (-

2.25%).Tobemoreprecise,thenationalindustrysectorwasonadownwardtrendfrom2005

until 2014, but in 2015 therewas a very slightly increase in this economic sector.Micro and

small firmsarethebackboneof thenationaleconomicstructure. In2014,companieswith less

than49employeesaccountedfor99,3%ofthetotal,whilemedium-sizedandlargeenterprises

withmore than 49 employees represent only 0,7% of the total. Portugal is a relatively small

countryingeographicalterms.However,therailwaylinesandmotorwayscoverrespectively28

and33kilometresofevery1.000squarekilometres. In2013, therailway linesnetwork in the

Norteregionis4.5%higherthaninAlentejoregion,whichisinaccordancewiththedifferences

indensitypopulationbetweenbothregions.

ThePortuguesebusiness enterprises spendmuch less in research anddevelopment (R&D)

thantheaverageinEU28in2014,measuredinPurchasingPowerStandard(PPS)perinhabitant

atconstant2005prices(moreconcretely,107.7against307.4).However,theinvestmentofthe

businesssectorinR&Dwassignificantlydifferentbetweenbothregionsin2014,amountingto

106.1 PPS per inhabitant in the Norte region and 35.4 in the Alentejo. The averages in both

regions were below the national and European averages in 2015 (107.7 and 307.4 PPS per

inhabitant).AlsotheinvestmentofthePortuguesegovernmentinR&Disremarkablybelowthe

EU28(14.5against60.6PPSper inhabitant).What isparticularly important tohighlight is the

low share of Norte (17.2%) and Alentejo (0.8%) regions in the total of national government

expenditure inR&D in2013.Thepublic investment inR&Dhasbeendecreasing considerably

overthepastfewyearsatthenationallevel(-29.3%),aswellasattheregionallevel:inAlentejo

(since 2008, from 10.8 to 1 PPS per inhabitant), and in Norte (since 2010, from 15 to 7.1).

Additionally,totalexpenditureinR&Daccountedfor1.36%ofPortugueseGDPin2014,whichis

avalue lowerthanEU28(-0.68%).Thepercentageofresearchers inalleconomicsectorsover

theactivepopulation ishighcomparedtoSouthernEuropeanpartners(inPortugal, the figure

was 1.5% in 2013, whereas in Spain it stood at 0.9%, and in Italy at 0.7%). Also in this

innovationindicator,thereareterritorialdifferencessince,contrarytotheNorteregion(1.4%),

Alentejoperformedbelowthenationalaverage(0.5%).

The share of people employed in the Portuguese public sector presents small fluctuations

since2008andamountedto7.2%ofthetotalemploymentin2014,withconsiderableregional

differences (10.5% in Algarve and 4.6% in Norte). Regarding employment in the education

sector,thisindicatorhadbeenincreasingfrom2008until2012(from6.8%to8.3%);however,

inthetwolastyearsitbegandecreasing(8.1%in2014).Inanycase,onlytheUnitedKingdom

hadmoreemploymentineducationin2014,whencomparedtoEuropeanpartners.Intermsof

regionaldiscrepancies,Alentejopresentsahigherpercentage(8.5%)thanNorte(7.7%).Finally,


11

thepercentageofpeopleemployedinthehealthsectorandinsocialworkisconsiderablylower

than in other European partners (16.4% in Finland or 12.5% in Germany in 2014). In this

indicator, Alentejo performed 1.1% above the national average in 2014, and Norte below (-

7.1%).

In2015,70%ofthehouseholdshadaccesstoInternet.Thisvalueisthesecondlowestamong

theEuropeanpartners.Onceagain, therearedifferencesbetweenboth regions:63% inNorte

and54%inAlentejoin2014.

3. Education

ThePortugueseeducationandtrainingsystemiscomprehensiveandcentralisedatthenational

level.Since2009,afterthebeginningofthefinancialcrisis,anduntil2012,thepublicinvestment

ineducationdeclinedfrom5.7%to4.9%oftheGDP.Thegovernment’sexpenditureineducation

began to increase again in 2013, being estimated at 5.3% of the national GDP. Full-time

educationiscompulsoryforallchildrenandyouthsagedbetween6and18(inclusive).

InPortugal, pre-school education for childrenbetween theagesof3 and5 is still optional.

Since 2006, the participation of children in childcare and pre-school has been increasing

continuously:in2012,93.4%thechildrenaged4wereenrolledineducation(9.4%morethanin

2006).Bothregionalaveragesarehigherthanthenationalaveragein2012,moreprecisely,96%

inNorteand99.4%inAlentejo.

Basic education consists of nine years of schooling divided into three sequential cycles of

educationoffour(1stcycle),two(2ndcycle)andthreeyears(3rdcycle).

The division into tracks takes placewhen pupils are 15 years old, at the beginning of the

secondaryeducationsystem,which ismadeupof threepossible tracks,eachthreeyears-long:

the scientific-humanistic track prepares pupils to enter higher education in the sciences,

technologyandhumanities;specializedartstrackspreparepupilstoeitherenteractivelifeorto

follow higher education studies in music and performance arts, audio-visual arts and dance;

vocational education and training, together with professional tracks, prepare pupils to enter

activelife,butalsoallowthepursuitofhighereducationstudies.In2015,afterlowersecondary

education, around 55% of young people entered a scientific-humanistic course, against 45%

whoaccessedavocationalprogramme.

All students who successfully conclude the secondary education can apply to the tertiary

education system (university or polytechnics). This application (for public sector higher

education institutions) is made through a national online platform and based on students’

prioritiesandgrades.Briefly,thepolytechnictertiaryeducationsystemisaimedatprovidinga

more practical training and to be profession-oriented,while the university tertiary education

systemischaracterisedbyastrongertheoreticalbasisandresearch-orientation.


12

From2005to2014,thepercentageofpopulationaged25-65whoattainedlowereducation

(ISCED2)declinedfrom73.7%to56.7%.WhencomparedtootherEuropeanpartnercountries,

Portugalrevealsthe lowestratesofschoolattainment,whichcanbepartiallyexplainedbythe

significantdifferencesinschoolattainmentacrossagegroups.Justtoillustrate,thePortuguese

population aged 56-65 has the lowest average number of schooling years of all European

partners in 2014, more concretely, just 23% of this age group attained upper secondary

education(21%lessthantheaverageforEU21).

In both regional contexts, theparticipationpercentage of students in upper-secondary and

post-secondarynon-tertiary education (ISCED3-4) hasbeen fluctuating; however, it has been

declining from 2009 to 2012, from 40.2% to 37.1% in Norte and from 45.7% to 37.1% in

Alentejo.

Examining tertiary education in Portugal (FIGURE 3), there was an improvement in the

percentageofpeopleaged25-65whoattainedISCED5-8,increasingfrom12.8%to21.7%from

2006until2014.Evenso,Portugalhadoneofthe lowestaverages(21.7%)comparedtoother

Europeancountries(e.g.,34.7%inSpainor27.1%inGermany) in2014,withtheexceptionof

Italy.Intermsofgenderdifferences,womenaremorelikelytoconcludethetertiaryeducation

thanmen,whoreached17.2%in2014(8.7%lessthanwomen).

FIGURE3:Percentageofpopulation(25-64)withISCED0-2,ISCED3-4andISCED5-8,

in2005and2014


13

Source:Eurostat

Duringthesameperiod,atthePortugueseregionallevel,NorteandAlentejohadanincrease

in this indicator in 2015, gaining respectively 6.3% and 4% since 2005. Considering the

Portuguesepopulation aged30-34with ISCED5-8, thepanorama is basically the same as the

one described previously; thus, the percentage has also grown considerably since 2006,

amountingto31.3%in2014,butevensoitislessthaninmostEuropeancountries,exceptItaly

andBulgaria.Alsoherethepercentageofwomenwas15.7%higherthanthatofmen,amounting

to 38.9% in 2014. The percentage of the population aged 30-34 that concluded tertiary

education inbothPortugueseregionshasalso increasedover time,with16.7%more inNorte

and10.1%inAlentejothan in2005,reaching30.3%and24.9%in2014.Although ithadbeen

continuouslygrowingsince2006(FIGURE4),thePortuguesepercentageofpopulationaged20-

24 who attained the tertiary education (ISCED 5-8) is one of the lowest among European

countries (51.2% compared to 95.9% in Austria and 88.3% in Finland in 2012). The same

growth trajectory is seen in both regions, as this indicator increased from40.2% to44.4% in

Alentejoandfrom42.7%to58%inNorte.

Regarding adult participation in education and training, in the Portuguese EUROSTAT

sample, 16.8% of the participants aged 25 to 34 stated that they had received education or

traininginthefourweeksprecedingthesurvey.Thisvalueis0.6%lowerthantheEU21average

in2015.DuringThelastdecade,theindicatorpresentedsomefluctuations;however,from2011

to2016ithasbeendecreasing.Thereisnoevidenceofsignificantdifferencesregardinggender.


14

FIGURE 4: Participation (%) in tertiary education of population aged 20-24, 2005-

2012

Source:Eurostat

Portugal only completed the field test of Programme for the International Assessment of

AdultCompetencies(PIAAC),andassuchdidnotparticipate inthemainstudythattookplace

between2008-2013.So,ourmainsourceofdataistheProgrammeforInternationalAssessment

(PISA). Portugal did not participate in 2003; therefore, we included data between 2006 and

2015. Since 2000, every three years, the Programme for International Student Assessment

(PISA) aims to assess and compare education systems worldwide by testing the skills and

knowledgeof15-year-oldstudentsatthebeginningofuppersecondaryeducation.From2006to

2015,thePortuguese15-years-oldstudentsshowedanincreaseinthemeanscoresinnumeracy

and literacy. In 2006, the national numeracy mean was 466 (with 90.67 points of standard

deviation and 0.19 of coefficient of variation). In 2015, the national average had risen to 492

points (with 95.74 points of standard deviation and 0.19 of coefficient of variation).

Simultaneously, the national literacy average grew from 472 points (with 98.79 points of

standarddeviationand0.21ofcoefficientofvariation)in2006to498points(with91.95points

of standard deviation and 0.18 of coefficient of variation) in 2015. The national average in

numeracyandliteracywasgreater,respectively,1pp.and6pp.thantheEUaveragein2015.

In Portugal, the ratio of early school leavers, more specifically, the percentage of the

population aged 18-24 having attained at most lower secondary education and not being in

further education or training, has been declining in the last decade (FIGURE 5). The national


15

average decreased from 40.9% in 2005 to 14% in 2016, which is a value that nonetheless

remainshigherthantheEU28average(10.7%).Attheregionallevel,bothregionsalsohadan

improvementinthisindicator,droppingfrom38.3%to18.4%inAlentejoandfrom45%to19%

inNorte between2005 and2014. In any case, theywere greater than the national andEU28

average(11.2%)in2014.

FIGURE5:Percentageofyoungpeopleaged15-24neitherineducation,employment

or training (NEET; left axis) and early leavers aged 18-24 (right axis), Portugal,

AlentejoeNorte,2012-2016

Sources:EurostatandLFS(microdata)

Similarly to thisprevious indicator, thepercentageofPortugueseyoungpeopleaged15-24

whoneitherinemploymentnorineducationandtraining(NEET)reducedfrom13.9%in2012

to10.6%in2016(FIGURE5).Thisindicatorhasalsodecreasedinbothregions,from12.4%to

11.1% in Norte and from 15.3% to 10.3% in Alentejo between 2012 and 2016. While the

nationalaverageishigherthantheEU27average(11.5%)in2016,theregionalaverageswere

slightlylower.

4. Labourmarket

The occupational structure of the Portuguese labour market is less qualified than the EU27

average.However,somechangeshavehappenedduringthelastdecade,withanimportantskills


16

upgrading, mainly among the high skilled white-collar occupations. In 2015, 22% of the

Portuguese labour forcewas employed in high skilledwhite collar occupations (ISCO1, 2, 3),

and24%waspartofthehighskilledbluecollargroup(ISCO6,7),whilein2008,theaverages

forthesameoccupationswere,respectively,17%and23%.Onthebottomoftheoccupational

structure,30%ofthePortugueselabourforceisworkinginlowskilledwhite-collaroccupations

(ISCO4,5)andtheremaining24%isworkinginlowskilledblue-collaroccupations(ISCO8,9).

Duringthe lastdecadetheoverallPortugueseemploymentrate foradultsagedbetween20

and64 rose from72.2% in 2005 to 73.1% in 2008 (FIGURE6). Between2008 and2013, the

employment rate decreased 7.1pp. due to both the global financial crisis in 2008 and the

nationalonein2010.Itstartedrisingtheyearafter,reachingthevalueof69.1%in2015.Inspite

of this positive trend in last years, the Portuguese employment rate is still below the value

reachedin2005andtheEU27average in2015(70.1%).Duringthetimespan2005-2015, the

overall employment rates for adults aged between 20 and 64 in Norte and Alentejo regions

followed the same national trends, and were below the Portuguese average. In 2015, the

employmentrateforadultsagedbetween20and64was66.5%inNorteand68.5%inAlentejo.

FIGURE6:Employmentrate(20-64)inEU27,Portugal,Norte,andAlentejo

Source:EUROSTAT

ThePortugueseyouthemploymentrate(15-24yearsold) isoneof the lowest inEU27and

decreasedconsistentlyduringthetimespan2005-2015(FIGURE7).Itwas35.3%in2005and

22.8% in 2015, showing a reduction of 12,5pp.. During the last decade, the gap between the


17

Portuguese youth employment rate and the EU 27 average rose from 0.6pp. to 10.3pp., since

2005to2015.Generallyspeaking,onecansupporttheideathattheeffectsofthefinancialcrisis,

inparticular the riseof theunemployment,havebeenparticularly severe to theyoung labour

force.

Theimpactofthefinancialcrisisattheregionallevelwasevenstrongerthanatthenational

level(FIGURE7).Theyouthemploymentratedecreased16pp.inNorteand14.9pp.inAlentejo

between 2005 and 2015. In spite of this general trend, the two regions have different youth

employment rates. In 2015, the youth employment rate in Nortewas 23.7%, higher than the

nationalaverage,whileinAlentejowas19.4%lower.

FIGURE7:Youthemploymentandunemploymentrates,youthunemploymentratio

ofyoungpeople15-24(rightaxis),EU27,Portugal,NorteandAlentejo,2005-2015

Sources:EurostatandLFS(microdata)

Focusing on unemployment, the overall unemployment rate (aged 20 to 64) began to

increaseevenbeforethefinancialcrisisandstronglyrosetill2013.In2006,itwas7.8%,0.9pp.

lowerthanEU28average(8.7%).In2013,thePortugueseunemploymentratewas16.5%,5.9pp.

higherthanEU28average.Sincethanithasbeenconsistentlymovingdown(12.5%in2015)and

thegapbetweenthePortugueseandtheEU27overallunemploymentrateisgettingsmaller,but

thePortugueserateisstill3.3pp.higherthanEU27average.NorteandAlentejoregionsfollowed

thenationaltrend.Inbothregionstheunemploymentratestartedmovingupin2008till2013

when it reached, respectively, 17.4% and 17.2%. As at the national level, the downward


18

movement began in 2014. In 2015, the Norte average was 2.2pp. higher than the national

average,whiletheAlentejoaveragewas2pp.lower.

FIGURE8:Unemploymentrate(20-64)inEU28,Portugal,Norte,andAlentejo

Source:EUROSTAT

InPortugal,thepercentageoftheunemployedthathavebeensearchingforajobforoneyear

ormore is one of the highest in EU27. In 2015, the overall long-term unemployment rate in

Portugalwas57.4%whileinEU27was48.1%(FIGURE9).Whenlong-termunemploymentrate

is concerned, important territorial differences emerge. During the time span 2005-2015, this

ratehasalwaysbeenhigherinNorteregionthaninAlentejo,whereitwasalwayslowerthanthe

nationalaverage.In2015,thelong-termunemploymentratewas61.6%inNorteand49.6%in

Alentejo.

In Portugal, unemployment is mainly a youth problem, particularly after 2011. The

unemploymentrateamongyoungpeopleaged15-24startedtorisewiththeinternationalcrisis

of 2008 (FIGURE 7). However, it was with the severe austerity measures imposed in the

aftermath of the Portuguese bailout of 2010 that it started coming up very rapidly and

intensively. In 2005 and 2006, the Portuguese youth unemployment was lower than EU 28

average.In2011,ittouched30.3%,whileinEU28was21.8%.Thehighestvaluewasreachedin

2013,when38.1%oftheyoungactivepopulationwasunemployed.


19

FIGURE 9: Long-term unemployment rate (20-64) in EU27, Portugal, Norte and

Alentejo

Source:EUROSTAT

In2015,thePortugueseyouthunemploymentratewas32%,morethanthedoubletherateof

people aged between 20 and 64 years (12.5%), and 12.4pp higher than the EU28 average.

Opposite to what happens with the adult unemployment rate, among young people gender

makesthedifference.Youngwomenaremoreaffectedbytheunemploymentthanyoungman.

Duringthetimespan2005-2015,theyouthfemaleunemploymentratewasalwayshigherthan

the young male’s one. The major difference can be found in 2005: the youth female

unemployment rate was 19.2% and the male unemployment rate was 13.9%. Long-term

unemployment seems to be less severe among unemployed youth (15-29) than among the

unemployedadults.Itstartedmovingupduringthefinancialcrises,reachingthehighestvaluein

2013(12.2%). In2015, thePortuguese long-termunemploymentratewas8.1%,4.3pp.higher

thantheEU27average(FIGURE9).

Lookingatyouthunemployment(15-24)someterritorialdifferencescanbefound(FIGURE

7).During the timespan2005-2015,youthunemployment ratewasalwayshigher inAlentejo

than in Norte. While in Norte this rate followed the national trend and was lower than the

nationalaverage, inAlentejoyouthunemploymenthasalwaysbeenmoresevereandgoteven

worseduringthefinancialcrisis.In2012,thePortugueseyouthunemploymentratewas37.9%,

while inNortewas33%andinAlentejo45%.ThisdatasuggeststhattheNorte labourmarket

seems to be more youth friendly than the Alentejo one or even the national one, probably


20

becauseofregion’seconomicstructurewithahighweightof industry.TheadvantageofNorte

disappearedwhenyouthlongtermunemploymentrate(15-29)isconcerned.Inthiscase,youth

long-termunemploymentratesaresimilar inbothregions,andhigherthannationalandEU27

average. In 2015, when long-term unemployment became less severe, youth long-term

unemploymentratewas9.2%inNorteand9%inAlentejoagainst8.1inPortugaland5.8%in

EU27.

Due to the financial crises, thePortuguese investment in labourmarketpolicies, started to

comingupin2009,whenthetotalamountofresourceswasequalto1.98%ofGDPandreached

itspeakin2013(2.14%ofGDP).Sincethatyear,theexpenditureisconsistentlydecreasing.In

2015,Portugalinvestedinlabourmarketpolicies(LMP)atotalamountof1.54%ofGDP.During

thetimespan,almost2/3ofthetotalamountwasinvestedinout-of-workincomeandsupport.

Active labourmarketmeasures represent a very small share of the overall LMP expenditure.

However,theinvestmentintrainingisrelativelyhighcomparedtotheEU28average.Inspiteof

thedecreasefrom2009till2015,trainingexpenditurevariedbetween0.41%and0.27%ofGDP,

onlyAustriaandFinlandinvestedmoreinthisactivelabourmarket.Thesefiguressupportthe

idea that themost important Portuguese active labourmarket policy to copewith the rise of

unemploymenthasbeentheinvestmentintraining.

5. Redistributionandsocialinclusion

InPortugal,thenetexpenditureinsocialprotectionrosefrom22.4%ofGDPin2007to24.9%in

2014.The strongest increase tookplacebetween2009and2013due to the impactsof global

andnationalfinancialcrisis.However,theriseoftheexpenditureinsocialprotectioninPortugal

is lower than in otherEU countries due to the reduction of the entitlement to social benefits.

This can be seen as a political strategy to control public expenditure within the austerity

framework. InPortugal, resourcesspent forsocialprotectionbenefits,provided tohouseholds

andindividualsaffectedbyaspecificsetofsocialrisksandneedsisoneofthelowestinEU27.In

spiteofthefinancialcrisisandthegrowthofunemploymentrate,theexpenditureperinhabitant

didn’t rise significantly. In 2008, the expenditure per inhabitant in Portugal was 4,779 euro

against6,784euroinEU27,whilein2013itwas,respectively,5,544euroand7,763euro.This

trendshowstheweaknessofthePortugueseWelfareStatethattraditionallyallocatestofamilies

andcivilsocietythegreatestresponsibilityinrespondingtosocialproblems.

The main share of the overall expenditure in social protection is spent for pensions and

retirement.Thesocialprotectionbenefitswitholdagerosecontinuously from9.2%ofGDP in

2005to12.8%ofGDPin2014.Portugalwasoneofthecountrieswherethisexpendituregrew

themost.From2005till2014,theexpenditurewitholdageincreased3.6pp.inPortugalagainst


21

1.4pp.inEU27.Thisgrowthcanbeexplainedbothbyagingandhighriskofpovertyduetothe

low incomeof Portuguese old people. The social protectionbenefitswith survivors also grew

duringthetimespanfrom1.5%to1.9%ofGPD.Ontheoppositeside,duringthetimespan,the

expenditurewithsocialprotectionbenefitsdecreasedinthefieldsofhealthcare(from6.7%to

6.1%) and disability (from 2.2% to 1.9%). Expenditure with family and children and social

exclusion remained stable between 2005 and 2014.However, these social protection benefits

are those were the underfunding is more severe when compared with EU27. In 2014, the

amountofresourcesspentwithbothsocialprotectionbenefitswashalfofEU27average.

Thedisposable incomeforhouseholds istheamountofmoneythatahouseholdearnseach

yearaftertaxesandtransfers,representingthemoneyavailabletoahouseholdforspendingon

goodsorservices. InPortugal, thedisposable incomeforhouseholdsrose from11,300euro in

2005 to12,600euro in2013, remainingoneof the lowest inEU (FIGURE10). In spiteof this

growth,duetothefinancialcrisis,thedisposableincomeforhouseholdsin2013wasidenticalto

the one registered in 2010. Norte and Alentejo region followed the same national trend.

However, in both regions the disposable income for households is lower than the national

average.Comparingbothregions,theincomeishighestinAlentejothaninNorte.

Focusing in income inequality, Portugal followed the general European trend of increasing

inequalities. TheGini coefficient of equivalised disposable incomebefore social transfers rose

from51.2%in2005to64.1%in2015(FIGURE10).

FIGURE 10: GINI index before and after transfers, disposable income in the

householdsinPPS(rightaxis),EU27,Portugal,NorteandAlentejo,2005-2015


22

Sources:EurostatandEU-SILCmicrodata

Thiswasnotalineargrowth.Theinequalitystartedtoincreasestronglyafter2011duetothe

structuraladjustmentpoliciesimposedtoPortugalbytheEuropeanCommission,theEuropean

Central Bank and the International Monetary Fund. The concentration of income rose from

50.3%in2011to64.1%in2015,transformingPortugalinoneofthemostunequalcountriesin

EU. The huge growth of inequality shows that the structural adjustment policies were more

severetowardsthelow-incomefamiliesthantothehighincomeones.Thisinequalityisstrongly

reducedwhenthesocialtransferistakeninaccount.AsshowninFIGURE10,theGinicoefficient

aftersocialtransfersdroppeddownfrom38.1%in2005to33.7%in2010,duetotheincreasein

publicexpenditureinsocialprotection.However,itstartedcomingupto34.5%in2014,maybe

asaconsequenceofthecutandreductiontotheentitlementinmanysocialprotectionbenefits.

The risk of poverty and social exclusion decreased from26.1% in 2005 to 24.4% in 2011.

After 2011, it started to grow, reaching 27.5% in 2014. In 2015, 26.6% of the Portuguese

population was at risk of poverty and social exclusion against 23.7% in the EU27. Severe

material deprivation shows a much more erratic behaviour during the time span. It started

comingupin2006,decreasedbetween2008and2011,andreturnedtogrowreachingthepeak

in2013,when10.9%ofthePortuguesepopulationwasinseverematerialdeprivation.Looking

atbothindicators,itcanbeconcludedthatthegrowthofinequalityinPortugal,asintheother

countriesparticipatinginYOUNGADULLLTproject,hasmainlyincreasedthepercentageofthe

populationatriskofpovertyandsocialexclusion.

Focusing in public sphere and civic participation, recent surveys show that in Portugal

confidence in national government is one of the lowest among OECD countries (23% against

42%)anditisevenlowerwhenyoungpeopleaged15-29yearsisconcerned(OECD,2016).Only

20%declaretotrustthegovernment,against43.6%inOECDarea.Notsurprisingly,theinterest

inpolitics isalso lowandhasbeendeclining. In2005, theparticipation in theelection for the

nationalparliamentwas64.3%, in200959.7%, in201158.1%and in201555.9%.Thevoter

turnoutisevenlowerwhentheelectionforEuropeanparliamentisconcerned,neversurpassing

40%inlastdecade.

6. Healthandwell-being

In2015,lifeexpectancyinPortugalwas80.5years,slightlyhigherthantheOECDaverage(79.6

years) (OECD,2015).Portuguesemaleand femalepopulationexperiencedan improvement in

healthylifeyearsbetween2005and2012.After2013,thehealthylifeyearsdeclinedduetothe

effects of the structural adjustment policies. In 2014, males had 58.3 healthy life years and


23

female55.4years.Duringthetimespan2005-2015,selfperceivedhealthinPortugalhasalways

beenlowerthantheEU27average.In2015,peoplereportinggoodorverygoodselfperceived

healthwas67%inEU27and46.5%inPortugal.Portugalwasalsothecountryparticipatingin

YOUNGADULLLTprojectwiththelowestself-perceivedhealth.Mostprobablybecauseoftheir

youth,thehealthperceptionsamongyoungpeopleaged16-29yearsaremuchhigher,81.3%in

2015,butstilllowerthantheEU27average,90.8%in2015.

Thehealth expenditureper inhabitant rose from1,014 euro in 2005 to 1,165 in 2009 and

decreased since than to 1,012 euro in 2014, when it was less than half of the EU27 average

(2,236euro).Thisamountisslightlylowerthanitwasatthebeginningofthedecadeshowing

thePortuguesegovernment’sdivestmentinhealthandmedicalcareduringthefinancialcrisis.

This divestment also affected thenumber of available beds in hospital,whichdecreased from

353,3 per 100,000 inhabitants in 2005 to 339,5 in 2013. Once again the number of available

bedsislessthanhalftheEU27average(681,4).Oppositetothesetrendsthehealthpersonnel

roseduring the timespan2005-2015. In2005,medicaldoctorsandnursesandmidwivesper

100,000 inhabitantswere780while in2015were1079.Howeverhuge territorialdifferences

emerge when we look at both regions. In Norte, the number of health personnel data per

hundredthousandinhabitantsissimilartonationalaverage(719in2005and1074in2015).In

Alentejo,itwasconsiderablylower(668in2005and815in2015).

Subjectivewell-beingcanbemeasured in termsof lifesatisfaction(FIGURE11). Ingeneral,

Portuguesepeopleagedbetween25-34yearsarecomparativelylesssatisfiedwiththeirlives.


24

FIGURE 11: High satisfaction in various life domains, age 25-34, EU28 and Portugal,

2013

Source:EU-SILCmicrodata

Only16.5%arehighsatisfiedagainst25.3%inEU28.Accordingly,Portuguesearelesssatisfied

withfinancialsituation,recreationandgreenareas,andlivingenvironmentthantheirEuropean

peers.However,theyaremoresatisfiedthanthemwithaccommodation,commutingtime,time

use, and personal relations. There are some differences according to gender, in Portugal.

Portuguese young women are more satisfied with accommodation, job, commuting time and

meaningoflife.

Sameotherindicatorscanbeusedtomeasurewell-being.In2015,Portuguesehomiciderate

was0.9,significantly lowerthantheOECDaverageof4.1. In2014,consumptionofalcoholper

capitawas 9.9 litters in Portugal against 8.9 litters inOECD area and the daily smokerswere

16.8%.


25

FinalRemarks

ConsideringthelimitationsofdataavailabilityatNUTS3andNUTS2,aswellasregardingthe

youthagegroup,itischallengingtofindthekeyaspectstounravelriskprofilesatlocallevel.

Still,thefollowingmainfindingsbringrelevantinformationonthesocialconditionsofyoung

adultsinbothFR.

LikeageneraltendencyinEurope,Portugalisalsowitnessinganageingprocessofits

population,mainlyinAlentejo.Inviewoftheriskprofile,thisfactassociatedwithlow

populationdensityanddispersesettlementinfluencesnegativelythelivingconditionsofthe

youngadultsintheregion,especiallyregardingtheaccesstoeducation.Thesmallnumberof

youngpeoplelivinginAlentejoLitoralhasaneffectonthediversityofeducationalprovisionat

bothuppersecondaryandtertiarylevels.Thefactthatthereisnohighereducationinstitutionin

theregionmakestheaccesstohighereducationmoredifficultandexpensiveandpartially

explainthelowerpercentageofpopulationaged20-24whoattainedthetertiaryeducationin

theregion.

Otherdemographiccharacteristicsarethehighpercentageofyoungadults(20-29)stillliving

withtheirparentsandtheincreasingageatwhichawomangivesbirth.Unemployment,

precariousjobsandlowwageshaveagreatimpactinyoungadults’lifecourseinbothregions

andcancontributetopostponetheirownfamilyproject.

ConsideringotherpartnerEuropeancountries,Portugalhasthelowestrateofschool

attainmentalsoamongtheyoungergenerations.AlongtheconsideredtimespanPortugalhas

shownaconsiderabledecreaseintermsofearlyschoolleavingrate,makingagreateffortto

keepyoungstersatschool,byincreasingthecompulsoryschoolupto12years.Nonetheless,

earlyschoolleavingrateisstillhigherthantheEU28average.ThepercentageofNEETalso

reducedandbothregionsshowaverageslowerthantheEU27.However,thesituationitself

poseschallengesforstatisticaleffects,asitsnumberismostlikelygreaterthantherepresented.

Consideringtheidentificationofriskprofiles,unemploymentinPortugalismainlyayouth

problem,(15-24yearsold)withoneofthehighestratesinEU27,withregionaldifferenceswith

AlentejoshowingahigherratethanNorte.Inaddition,gendermakesadifferenceandyoung

womenaremorerepresented,onthecontrarytoadultunemployment.Youthlong-term

unemploymentinbothregionsishigherthanthenationalandtheEU27average.Figuresshow

qualificationasthemostimportantactivelabourmarketpolicytodealwiththeincreasing

unemploymentrates.

Theexpenditureinsocialprotectionbenefitsperinhabitantdidnotaccompanythegrowthof

theunemploymentratewithintheconsideredtimespan.Tobenotedhowfamiliesandcivil

societytraditionallytakeresponsibilitytoactasthePortuguesewelfarestatedoesnotcome

forthwitharesponse.


26

References

OECD(2017)Countrystatisticalprofile:Portugal2017,Paris.

OECD (2016). Education at a Glance 2016: OECD Indicators. OECD Publishing, Paris.

http://dx.doi.org/10.187/eag-2016-en.

OECD (2016). Society at a Glance 2016. A Spotlight on Youth. How does Portugal

compare?.OECDPublishing,Paris.

OECD(2015).EmploymentOutlook2015.HowdoesPortugalcompare?Paris.


Work Package 4


Scotland –

National Briefing Paper with national and regional data sets in Scotland, Glasgow City-Region and

Aberdeenshire

Kristinn Hermannsson, University of Glasgow

Rosario Scandurra, Universidad de Granada

Date 07/09/2017

Work Package 4 – Quantitative Analysis of Young Adults’ Data

Deliverable 4.1


2

Tableofcontents

1 Introduction............................................................................................................................................................4

2 Qualitydataassessment..................................................................................................................................4

3 Demographicstructure....................................................................................................................................6

4 Thestructureoftheeconomy...................................................................................................................11

5 Education...............................................................................................................................................................14

5.1 Post-compulsoryeducation....................................................................................................................16

5.2 Workbasedlearning..................................................................................................................................17

6 Labourmarket....................................................................................................................................................18

6.1 Qualificationsoftheworkingagepopulation.................................................................................19

7 Redistributionandsocialinclusion.......................................................................................................24

8 Healthandwell-beingconditions...........................................................................................................27

9 Finalremarks......................................................................................................................................................28

10 References..........................................................................................................................................................30


3

Figures

Figure1Populationoffunctionalregions(ONSpopulationestimates,2015)...........................................7

Figure2.Shareofthepopulationaged20-29years.....................................................................................8

Figure3.Cruderateofnetmigrationplusstatisticaladjustment................................................................9

Figure4.Agedependencyratio.On1stvariant(populationaged0-14and65andmoretopop.aged

15-64).............................................................................................................................................................11

Figure5.GDPatcurrentmarketprices,Europerinhabitantin%ofEuropeanaverage(EU28=100)..13

Figure6Employmentbybroadsectorandstudyregion...........................................................................14

Figure7OverviewoftheScottishschoolsystem........................................................................................15

Figure8.Youthemploymentrates,population15-24years.....................................................................19

Figure9Shareofpopulationaged25-64withtertiaryqualificationsbyEurostatcountryin2014(%).

.........................................................................................................................................................................20

Figure10Shareofpopulationaged25-64withtertiaryqualificationsinEurostataffiliatedcountriesin

2014.40highestrankedNUTS-2regions.(%)............................................................................................21

Figure11Highestqualificationsachievedforpopulationaged25-64.Eurostataffiliatedstatesand

Scotlandin2014(%).....................................................................................................................................23

Figure12.ExpenditureinsocialprotectioninPPSperinhabitantas%ofEU19.....................................24

Figure13Disposablehouseholdincome(€,PPPadjusted).......................................................................26

Figure14Disposableincomeofprivatehouseholdsperinhabitant,highestandlowestNUTS2region

withineachcountry.......................................................................................................................................27

Figure15.Highsatisfactioninvariouslifedomains,populationaged18-30,EU28andUK,2013.........28


4

1 Introduction

Thisnationalbriefingpaperprovidesashortoverviewofthelivingconditionsofyoungadults

inScotlandandinthetwofunctionalregionsselectedfortheYOUNG_ADULLLTproject,

GlasgowCityRegionandAberdeenshire.Thedatawerecollatedatnationalandlocallevel

(NUTS2)accordingtosixdimensionsofcontextuallivingconditions:thedemographic

characteristicsofthepopulation,thestructureoftheeconomy,theinputsandoutputsofthe

educationandtrainingsystem,thelabourmarket,themateriallivingconditionsandthe

participationascitizenstothepoliticalandciviclifeand,finally,thehealthconditionsand

individualwell-being.DatawereextractedfromEurostatandfromdifferentsurveyssuchas

theEU-LFS,EU-SILC,PISAandPIAAC.Themaincorpusofdataproceedingfrominternational

andharmonizeddatawassuccessivelycomplementedbydatacollatedatthelocallevel.

ForthecaseofAberdeenCityandAberdeenshire,thechosenfunctionalregioncorresponds

withtheNUTS2regionofNorthEasternScotland.ForthecaseofGlasgowCityRegion,thereis

aclosebutapproximatefitwiththeNUTS2regionSouthWesternScotland.Additionally,

SouthWesternScotlandincludesthemoreruralareaofDumfriesandGalloway,whichspans

theareafromAyrshire,whichistakentorepresentthesouthernlimitofGlasgowCityRegion

andtheEnglishcountyofCumbria.Overall,thiswillacttodilutetheurbanandservice

orientedcharacterofGlasgowCityRegion.However,thisbiasislikelytobemodestasthe

populationofDumfriesandGallowayisonlyaround150,000people,orlessthanatenthof

theoverallpopulationofGlasgowCityRegion.Foramoredetailexpositionofthefunctional

regionsseeLowdenetal(2016)andforamoredetaileddiscussionabouttheuseofavailable

statisticsinthemodellingofGlasgowCityRegionseeHermannsson(2016).

2 Qualitydataassessment

EurostatUNESCOandOECDprovideavastamountofharmonizedandcomparativedatathat

canbeausefulresourceforassessingthelifeconditionsofyoungpeopleindifferentdomains

andinvariouscountries/regions.However,theavailabilityofdataattheregional/locallevel

islimited.Mostofthedataareprovidedatnationallevelandonlytwoofthesixdimensions

(economyanddemography)haveafairamountofindicatorsatNUTs2andNUTs3level.This

restrainsthepossibilityofcomparison.Withinthesurveysavailablethemostrelevantsource

ofinformationistheEU-LFSwhichhaslargesamplesizeatlocallevel.Moreover,

complementingtheinternationaldatawithlocaldataisahardtaskformainlytworeasons:a)

fragmentationandavailabilityofsourcesandb)comparabilitybetweenregionsofthesame

stateandatEuropeanlevelandacross2005and2015.Sincetheobjectiveisverybroad,the


5

dataneededarelikelytobecollectedforspecificpurposesandindifferentway.Forthis

reason,themostaccessibledataareEUROSTATsincetheyprovidemetadataandcompleted

timeseries.

DuetoitsautonomousstatuswithintheUK,availabilityofdataforScotlandistypicallybetter

thanforotherUKregions.Forinstance,theScottishGovernmenthaspublisheddetailed

regionaleconomicaccountssincethe1970's.However,thereremainsignificantgapswhenit

comestoassessingthelivingconditionsofyoungadultsattheleveloffunctionalregion.In

somecasesrelevantinformationisavailable,butataggregatespatialscales.Alternatively

theremaybenodataatall.SocialresearchintheUKoftendrawsonseverallargescalesocial

surveysmaintainedbytheOfficeforNationalStatistics,suchastheLabourForceSurveyand

theAnnualPopulationSurvey.Whilstthesesurveysprovideinformationaboutawiderange

ofvariables,samplessizesareoftentoosmalltodealaccuratelywithsub-populationsand

sub-regions.Furthermore,theUKhasinvestedincohortstudies(e.g.forthosebornin1958,

1970and2000)andhouseholdpanelstudies(BritishHouseholdPanelStudy,Understanding

Society),wheregreatercarehasbeentakentooversamplesub-populationtoallowforamore

detailedbreak-down.Thesedatasetsareusefulforthesocialsciencesingeneral,butwaves

areinfrequentandoftenfocussingonspecificcohortssotheseareunlikelytomeettheneeds

ofpolicymakersforongoingmonitoringofthelivingconditionsofyoungadults.Scotlandhas

investedinadedicatedlongitudinalstudy,GrowingUpinScotland,whichtracksfamily

circumstances,healthandeducationof3cohortsbornin2002/3,2004/5and2010/11.

However,asofyet,thesecohortsaretooyoungtoshedlightonthelivingconditionsofyoung

adultsanditisnotclearforhowlongtheywillbefollowedup.

TheUKhighereducationsectorcollectsdetailedadministrativedataanddepositswiththe

HigherEducationStatisticsAgency(HESA).Thesedatasetcontainthefullpopulationof

studentsandsamplesurveysarecarriedouttofollowupgraduates.Theadministrativeand

surveydatasetsareoftenlinkedtocarryoutanalysisofstudentsandgraduates.However,a

shortcomingofthisdatasetforassessingthelivingconditionsofyoungpeopleingeneralis

thatitomitsthesizableshareofthepopulationthatdoesnotenterhighereducationand

similardataarenotgatheredforthoseinothereducationalroutesoremployment.Skills

DevelopmentScotlandcarriesoutanannualsurveyofschoolleavers,trackingtheiractivities.

However,thesecohortsarenotfollowedupsoitisimpossibletotellhowtheyoungpeople

geton,beyondtheirfirstdestinationafterschool.Onbalance,thereisagapinavailabilityof

dataforyoungpeopleaftertheyleavetheschoolsystem.


6

3 Demographicstructure

Scotlandisacountrythatsince1707hasbeenpartoftheUnitedKingdom.WithintheUnited

KingdomScotlandenjoysconsiderableautonomy.Throughoutithasmaintainedalegal

systemandaneducationalsystemseparatefromtherestoftheUnitedKingdom(henceforth

RUK).TheScottishParliamentwasreinstatedin1999andtheScottishGovernment

(originallyreferredtoastheScottishExecutive)established.TheScottishGovernmenthas

devolvedauthorityfromtheWestminsterParliamentovermostdomesticaffairs,including

health,transport,culture,agriculture,fisheries,ruralpolicyandregionaldevelopment.

However,ithasnocontroloverdefenceorforeignpolicyandonlylimitedfiscalpowers.

Taxationisnotadevolvedmatter.HerMajesty'sRevenue'sandCustoms(HMRC)collectstax

revenuesforthewholeoftheUKandHerMajesty'sTreasury(theministryoffinanceinthe

UKgovernment)distributesanannualblockgranttoScotland(aswellasWalesandN-

Ireland,theothertwodevolvedgovernments)basedontheso-calledBarnettformula,which

takesaccountofpopulationandhistoricalexpenditurelevels.Initiallythefiscalautonomyof

Scotlandwasnotional,butfollowingthe2014independencereferendumadditionalsteps

havebeentakentodevolvefurtherfiscalpowers,suchasstampdutyonpropertytransactions

andairportduties.Similarly,elementsofsocialsecurityarenowbeingdevolved,whereas

historicallythesewerereservedmattersforWestminster1.

Scotlandcoversatotalareaof77,933km2,justunderonefifthofthelandmassofFinlandor

Germany,aquarterofthelandmassofItalyandathirdofthelandmassoftheUK–smaller

thanBulgaria,PortugalorAustriaandlargerthanCroatia.ThepopulationofScotlandis

estimatedtobearound5.5millionpeople.

1ForamoredetaileddiscussionofthefiscalarrangementsinScotlandandrecentandemergingchangestothefiscalframeworkseeEiser(2017).


7

Figure1Populationoffunctionalregions(ONSpopulationestimates,2015)

Figure2showstheshareoftheyouthpopulationaged20-29overthestudyperiod.In2015,

youthpopulationaged20-29accountedfor13.5%oftotalinhabitants,inSouthWest

Scotland.ThisisinlinewithScotlandandtheUKasawhole.TheNUTS2regionofNorth

EasternScotland,however,divergesfromthebroaderaverage,with20-29populationmaking

upjustover15%ofthetotalpopulation.Overall,acrosstheUKandScotlandtheshareofthe

20-29populationisstable.


8

Figure2.Shareofthepopulationaged20-29years

Source:EUROSTAT

Infantmortalityinthefirstyearafterbirthis3.9intheUKwhileintheEU28itwas3.6in

2016withaconstantdecreaseoverthelastdecade(in2005itwas3.7).InScotland,however,

thisstoodat3.2intheSouthWestand2.7intheNorthEast,InbothcasesbelowboththeUK

andEUaverages.Conversely,lifeexpectancyinScotlandisbelowtheUKaverageof81.3

years,at78.6intheSouthWestand80intheNorthEast.Inbothcaseslifeexpectancyhas

beenincreasing,broadlyinlinewithdevelopmentsseenelsewhere.

InthepostwarerapartsofScotlandhaveattimesbethreatenedbyde-population.Thisis

particularlythecaseformoreremotesettlements,buthasalsobeenanissueforurban

centresthathavesufferedfromde-industrialisationsuchastheGlasgowCityRegion.In

conjunctionwithpopulationageingthishasbeenseenasasignificantchallengeandwasseen

asapolicypriorityinthelate1990's.However,followingtheenlargementoftheEUnet

migrationtoScotlandincreased(andastheimmigrantpopulationwasmorefertilethisalso

boostedfertilityrates).Notsurprisingly,netmigrationhasbeenstrongerfortheaffluent

NorthEast,aboveboththeUKandScottishaverages,whilstfortheSouthWestmigrationhas

beenbelowbothUKandScottishaverages,albeitpositive.Foradetaileddiscussionofthe

economicimpactofdemographicchangeinScotlandseeLisenkovaetal(2010).


9

Figure3.Cruderateofnetmigrationplusstatisticaladjustment

Source:EUROSTAT

Whilstmigrationandfertilityhasbeenmovinginapositivedirection,thishasnotbeensufficienttooff-setthepopulationmomentum.DependencyratiosareincreasinginScotlandinlinewithdevelopmentselsewhereinEurope,asdepictedin


10

Figure4.However,Scotland'sdependencyratioissomewhatbelowthatoftheUK.

Furthermore,thereisregionalvariationinthedependencyratios.WhilsttheSouthWestis

closetotheaverageforScotlandataround51%in2015,thedependencyratiofortheNorth

Eastis3percentagepointslowerat48%in2015.


11

Figure4.Agedependencyratio.On1stvariant(populationaged0-14and65andmore

topop.aged15-64)

Source:EUROSTAT

4 ThestructureoftheeconomyWhencomparedtotheEU28(asin


12

Figure5)theGDPpercapitainScotlandhasbeenfallingbehind.Thisisinlinewiththetrend

oftheUKasawhole.ThisrunssomewhatcountertothepopularnarrativeintheUKmedia,

wherepoliticianshavebeenatpainstoemphasisetheeconomicachievementsoftheUK.

However,whilstnominalGDPhasbeenincreasing,thishascoincidedwithpopulationgrowth

sothatGDPpercapitagrowthhasbeenlessimpressive.Furthermore,nominalgrowthhas

coincidedwithasignificantdepreciationofthepoundsterling,therebyreducingitseuro

value.TheSouthWestofScotlandfollowstheUKandScottishtrendsalbeitatalowerlevel.

However,intheNorthEast,GDPpercapitaisatafarhigherlevelandhasgrownoverthe

period(althoughfrom2015theregionaleconomyhasbeenhitbyastrongcontractioninthe

activitiesoftheoilandgassector).


13

Figure5.GDPatcurrentmarketprices,Europerinhabitantin%ofEuropeanaverage

(EU28=100)

Source:EUROSTAT


14

Figure6Employmentbybroadsectorandstudyregion

Source:AnnualPopulationSurvey,ONS.

AscanbeseenfromFigure6approximately80%oftheworkforceinScotlandisemployedin

services.Aboutathirdoftheworkforceareemployedinthepublicsector.Thereisstructural

variationwithinthecountry,withGlasgowCityandGreaterGlasgowleaningmoreheavily

towardsservices(approximately84%)andmorepublicsectoremployment(34-35%).

Aberdeenshireisdistinctinthattheenergysector(mainlyoilandgas)andagricultureand

fishingaredisproportionatelylargeemployerscomparedtoScotlandasawhole.Conversely,

theshareofservicesis65%andthepublicsectoronlyemploys24%oftheworkforce.

5 Education

Scotland's32localauthoritiesareresponsiblefortheprovisionofeducation,inEarly

LearningandChildcare(ELC),primaryandsecondaryeducation.Localauthoritiesmaketheir

owndecisionsabouttheshareoftheirincomespentoneducation(ScottishGovernment,

2015).Approximately85%oflocalauthorityfundingisobtainedviaaScottishGovernment

blockgrantandtheremainderfromlocaltaxation2.Figure7presentsanoverviewofthe

differentstagesoftheScottisheducationsystemandthekeyfeaturesofeachstage.

2 For a further discussion of local authority finances see the chapter by Gibb and Christie in this volume. Asummary of local government funding is provided on the Scottish Government's website:


15

Figure7OverviewoftheScottishschoolsystem

Source:ScottishGovernment(2015),citedinOECD(2015,p.38).

FollowingtheChildrenandYoungPeople(Scotland)Act(2014),all3and4yearoldsare

eligibleforEarlyLearningandChildcare(ELC)of600hoursperannum.Thisamountsto

approximately3hoursadayduringtermtime.Additionally,some2yearoldsareeligible3.

Localauthoritieshaveadutytosecuretheseplaces,whichcanbeprovidedbythelocal

authority,inaprimaryschoolnurseryclassorbyindependentproviders4.

Mostprimaryandsecondaryschoolsarerunbylocalauthoritieswithafewspecialistschools

fundeddirectlybytheScottishGovernment.Overalljustover95%ofstudentsattendpublicly

fundedschools.Mostofthesearesecular.However,forhistoricalreasons15%ofpublicly

fundedschoolsaredenominational(mostlyRomanCatholic).Theindependentschoolsector

inScotlandisrelativelysmall,with100institutionsprovidingeducationforapproximately

30,000studentsorjustover4%oftheoverallstudentpopulation.However,theseinstitutions

areunevenlydistributedspatially,withathirdofstudentsattendinginstitutionsin

http://www.gov.scot/Topics/Government/local-government/17999/CoreRevenueFunding/Revenue-Funding-Streams3Thisincludeschildrenincareandchildrenwhoseparentsareinreceiptofparticularbenefits.Fordetailssee:http://www.gov.scot/Topics/People/Young-People/early-years/parenting-early-learning/childcare4Fordetailssee:https://www.scottishfamilies.gov.uk/NationalCategoryDetail.aspx?ncid=7


16

Edinburgh,afifthattendingschoolsinGlasgowand10%attendingschoolsinAberdeen.In

Edinburgh,1in4secondaryschoolstudentsattendindependentschools.Thisisthehighest

concentrationofindependentschoolsinScotland.IndependentschoolsinScotlandreceiveno

publicsubsidy.However,schoolsthatmeettherequirementsforacharitablestatusreceivea

taxbreak(ScottishGovernment,2015).

SkillsDevelopmentScotlandcarriesoutafollowupsurveyofschool-leaverstodetermine

theirfirstdestination.ThesestatisticsplayacentralroleintheScottishGovernment’spolicy

onyoungpeople.TheScottishGovernmentmonitorstheshareofschoolleaversthatgoto

whatitreferstoaspositivedestinations.Thisbroadlyreferstobeinginwork,educationor

training5.Thisindicatorhasbeenimprovinginrecentyears.Thesedataarepublishedbythe

ScottishGovernment:http://www.gov.scot/Topics/Statistics/Browse/School-

Education/TrendDestinations

5.1 Post-compulsoryeducationTheScottishQualificationsAuthority(SQA)awardsqualificationsinScotland,typicallyto

studentsinsecondaryschoolsandFurtherEducationColleges(FECs),butalsoforworkbased

trainingandotherroutes6.After4yearsofsecondaryschooling(S4),studentscanleave

compulsoryeducationat16orcontinuesecondaryschoolingfora5thand6thyear(S5and

S6).Althoughstudentscanleavewithqualificationsafteryear4most(78.3%)stayonforS5

andthemajority(59.25%)ofS4pupilsstayonforS6(ScottishGovernment,2015,p.8).

TheScottishGovernmentfundsteachingandresearchatFECsandHEIsviatheScottish

FundingCouncil(SFC),whichisanarms-lengthorganisation(formallyaNon-Departmental

PublicBody).TheSFCpublishesanoutcomeagreementforeachHEandFEinstitution,which

setsouthowthefundingwillbeusedtoachievepolicyaimsrelatingtoresearch,lifeoutcomes

andtheeconomy.ForinstancetheSFCusesoutcomeagreementstopromotetheparticipation

ofunder-representedsocioeconomicgroupsbyringfencingapartofstudentplacesforthese

groups7.ScottishUniversitiesreceiveateachinggrantfromtheSFC,butadditionallyreceive

tuitionfees.ScottishdomiciledstudentsstudyinginScotlanddonotpaytuitionfeesasthese

arecoveredbytheStudentAwardsAgencyScotland(SAAS).Thisentitlementisalsoavailable

5 For details of the Scottish Government definition see here: http://www.gov.scot/topics/archive/About-Archive/scotlandperforms/NotesSP/TechnicalNotesSPNI106ForuptodatedetailsofqualificationsseetheSQA'swebsite:http://www.sqa.org.uk/sqa/70972.html7 For a detailed overview of current outcome agreements, see the website of the Scottish Funding Council:http://www.sfc.ac.uk/funding/OutcomeAgreements/OutcomeAgreementsOverview.aspx


17

tostudentsfromtheEuropeanunionoutsidetheUK,whilestudentsfromotherpartsofthe

UKpayfees(fordetailsseeSAAS,n.d.).

TheFEsectorismostlyfundedbytheSFCandreceivesfundinglargelyforteaching.A

significantshareofthosestudyingforHEqualificationsinScotland,dosowithintheFE

sector.TheHEsectorreceivesfundingfromtheSFCbothforteaching,researchandother

activities.FurthermoretheHEsectorreceivessignificantincomefromoutwiththeScottish

Government.SuchastuitionfeesfromexternalstudentsandScottishpost-graduatesand

researchfundingfromUKGovernment,EUandindustrysources.Hermannssonetal(2014)

estimatethatonaverageScottishGovernmentfundingamountsto55%ofthesector's

income.

5.2 WorkbasedlearningApprenticeshipschemesinScotlandaremanagedbySkillsDevelopmentScotland(SDS),a

subsidiaryoftheScottishGovernment.ThemainschemeforworkbasedlearningisModern

Apprenticeship(MA),whichemergedinthe1990s.Thisisavailabletoeveryone16yearsor

older.AnMAcombinesemploymentwithtraining,eitherdirectlyprovidedbytheemployer,

affiliatedfurthereducationcollegesorprivatetrainingproviders.AccordingtoSDS8thereare

37,500individualsworkingasmodernapprenticesinScotland,asofAugust1st,2017.The

numberofthesehasbeengrowinginrecentyears,buttoputthisintoperspective,thereare

approximately140,000ScottishdomiciledstudentsregisteredatuniversitiesinScotland

(basedonHESA2014).

Morerecently,twoadditionalapprenticeshipschemeswereintroducedFoundation

Apprenticeships(FA)andGraduateLevelApprenticeships(GLA).FAsareatwoyearlong

work-basedlearningopportunityforsenior-phasesecondaryschoolpupils.Youngpeople

spendtimeoutofschoolatcollegeorwithalocalemployer,andcompletetheFoundation

Apprenticeshipalongsidetheirschoolqualifications.AnexplicitaimoftheFApolicywasto

addressyouthunemploymentbygivingyoungpeopleanopportunitytogainwork

experience.GLAarearoutetowardscompletingadvancedprofessionalqualificationswhilst

inwork.Theseareopentoemployeesofparticipatingemployersincollaborationwith

universitiesandfurthereducationcolleges.

8 SDS publishes statistics on apprenticeships in Scotland on its website:http://www.skillsdevelopmentscotland.co.uk/publications-statistics/statistics/modern-apprenticeships/?page=1&statisticCategoryId=4&order=date-desc


18

Apprenticeshipsareclassifiedthematicallyalongsectorallines9andareassignedaparticular

leveltocorrespondwiththeScottishQualificationsFramework(SQF)10.Apprenticeshipsin

Scotlandrangefromlevel5tolevel11ontheSQF.ThiscorrespondstoISCEDlevels3to7,i.e.

fromuppersecondarytomasterslevel11.

ApprenticeshipsarefundedbyaUK-wideemployerlevy.Employerspaytheirapprentices

salariesandhavetoabidebyminimumwagerulesbutreceiveinturnacontributiontowards

trainingcosts.Insomecases,employersreceivedadditionaltaxincentivesfortakingon

apprentices.SDSsurveysemployerstodeterminetheneedsforparticularskills,whichin

turndeterminesprioritiesforapprenticeships.Oncethesehavebeendeterminedsubsidy

towardstheapprenticeshipsisallocatedonbasisofcompetitivetendering,inlinewithpublic

procurementprinciples.ForfurtherdetailsofthisprocessseeAuditScotland(2014)All

apprenticeshiptrainingproviders,whethereducationinstitutionsorprivatefirmsaresubject

toinspectionbyEducationScotland,whichcarriesoutinspectionsofschoolsandcollegesin

Scotland.

Theneedforthissubsidyarisestooff-setamarketfailure.Asacomponentoftheapprentices

skillsaretransferable,ratherthanfirmspecific,thereisadisincentiveforindividual

employerstoinvestintrainingduetoafreeriderproblem,whicharisesascompetingfirms

couldpoachtrainedemployeeswithoutbearingtheburdenofthetrainingcost,thereby

potentiallygainingacompetitiveadvantageattheexpenseoffirmsmorededicatedto

training.Ifnotcounteredbyinterventionthiswouldleadtoasub-optimaloutcomewith

underinvestmentinskills(foramoredetaileddiscussionofthispointseeOECD(2016).

6 Labourmarket

Throughaseriesofreformssincethe1980´sthelabourmarketintheUnitedKingdomhas

becomeoneoftheleastregulatedintheEuropeanUnion.Whilst,inlinewithpredictionsof

neoclassicaleconomicsthisflexibilityhasmeanthatrecenteconomicshockshaveledtoonly

moderateriseinunemployment,butafallinrealwages(Blundelletal,2016).Furthermore,

9Foranoverviewsee:http://www.skillsdevelopmentscotland.co.uk/media/41680/sds-framework-grouping-1.pdf10Detailsofthisassignmentcanbeaccessedhere:http://www.skillsdevelopmentscotland.co.uk/media/38809/MA%20Level%20Description.pdf11 For details of how the SQP maps against UNESCO’s ISCED framework see:https://beta.gov.scot/publications/scottish-qualifications-unesco-isced-levels/


19

theconsequencesoftheeconomicdownturnhavetakenmoresubtleforms,forinstancearise

inunderemploymentandprecariousemployment(Furlongetal,2017).

Figure8.Youthemploymentrates,population15-24years

Source:EUROSTAT

AscanbeseeninFigure8youthemploymentratesintheUKarefarhigherthanfortheEU27.

Whilstthisfellduringtheeconomicdownturnithasbeenrecoveringsince2013.Scotlandasa

wholeandSouthWesternScotlandcloselytracktheUKaverageintermsofyouth

employmentrates.However,youthemploymentratesintheNorthEastofScotlandarefar

higherandremainedhighduringtheeconomicdownturn.

6.1 QualificationsoftheworkingagepopulationEurostatcompilesdataonthelevelsofformalqualificationsachievedbythepopulationsof

EuropeanUnion(EU)memberstates,affiliatedcountriesintheEuropeanEconomicArea

(EEA),SwitzerlandandcandidatestatesforaccessiontotheEuropeanUnion.InError!Nota

validbookmarkself-reference.,theshareoftheapproximateworkingagepopulationinScotland

iscomparedtothestatesreturningdatatoEurostat.OnthatbasisScotlandhasthehighest

shareofgraduateworkerswithinEurope.However,ofcourse,comparingScotlandtostate-

wideaveragescanbemisleadingasmanyofthesearelargeandinternallyheterogeneous.


20

Figure9Shareofpopulationaged25-64withtertiaryqualificationsbyEurostatcountryin2014(%).

Source:Eurostat.


21

Figure10Shareofpopulationaged25-64withtertiaryqualificationsinEurostataffiliatedcountriesin2014.40highestrankedNUTS-2regions.(%).

Source:Eurostat.

Aslightlydifferentperspectiveispresentedin


22

Figure10,whichshowstheshareofgraduatesoftheworkingagepopulationforNUTS-2

regions.Tosavespaceonlythe40regionswiththehighestshareoftertiaryeducatedworking

agepopulationareshown(dataisavailablefor314regions).Scotland'sfourNUTS-2regions

areallonthis"Top40"listandindeedtheUKiswidelyrepresentedalongwithmanyof

Europe'scapitalregions.


23

Figure11Highestqualificationsachievedforpopulationaged25-64.EurostataffiliatedstatesandScotlandin2014(%).

Source:Eurostat

ThesedataillustratethatScotlandiswellendowedintermsofhighly-qualifiedworkers.

However,analternativeviewistoexaminetheshareofworkerswithlowqualifications.


24

Figure11showsthehighestqualificationsachievedbytheworkingagepopulationof

EurostataffiliatedstatesincomparisontoScotland.Scotlandisclosetothemedianwithjust

under20%ofthepopulationreportingthehighestqualificationobtainedtobelower

secondaryorless.WithinScotlandthereissubstantialregionalvariationinthisregard.The

populationofNorthEasternScotlandhasthelowestshareofworkerswithlowersecondary

qualificationsorlessat13.7%.Whilethesesharesstandat16.8%,20.5%and22.3%in

EasternScotland,theHighlands&IslandsandSouthWesternScotland,respectively.

7 Redistributionandsocialinclusion

Throughouttheperiodexaminedinthisprojectsocialprotectionspendingwasareserved

matterintheUK,conductedbythecentralgovernmentinLondon.Regionspecificdataisnot

availableforScotlandasawholeorScottishregions,butUK-widedatacanprovideanoverall

comparisonwithotherEUcountries.UKnetexpenditureinsocialprotectionfellfromapeak

of99%oftheEU19averagein2006to89%in2015.



ThisshowsthatwhilstsocialprotectionexpendituresintheUK,whereinlinewithotherEU

countries,ithasbeengraduallyshrinking.Whilsttheliberal-conservativecoalition

60%

70%

80%

90%

100%

110%

120%

130%

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014Germany Spain Italy Finland UnitedKingdom


25

governmentthatcametopowerin2010madeapointofwelfarereformsandimplementeda

fiscalausterityprogramme,thetrendseemstohavesetinearlier.


26

Figure13Disposablehouseholdincome(€,PPPadjusted)

Thedisposableincomeforhouseholdsistheamountofmoneythatahouseholdearnseach

yearaftertaxesandtransfers,representingthemoneyavailabletoahouseholdforspending

ongoodsorservices.TheUKonaverageisonparwithItalyandFinlandintermsof

disposableincomeandcomesinatabout80%ofdisposableincomeinGermanyandAustria

andabout120%ofdisposableincomeinSpain.Disposableincomehasfallenfromapeakof

€18,000in2007toatroughof€16,700in2011.Thesetrendsarereplicatedcloselyata

regionallevelforScotlandasawholeandtheSouthWestofScotland,albeitataloweroflevel

of,€16,100and€15,100,respectively,in2011.TheNorthEastofScotlandisoutofsyncwith

therestofScotlandandtheUK,beingdominatedbytheoilandgaseconomy.There,

disposableincomereachedapeakof€20,100in2008andbottomedoutat€18,900in2010.

ComparingScotlandtoUKaveragemaskssignificantregionalvariationinlivingstandards

withintheUK.TheUKaverageisskewedupwardsbythevastlyhigherdisposableincomeof

greaterLondonandwithScotlandbeingthemostaffluentregionoutsidegreaterLondonthis

truncatesthelowerrangeofobservation.Indeed,theOfficeforNationalStatistics(ONS)

recentlyminedEurostatdatatoproducearegionalcomparisonofGDHIacrosstheEU.This

revealsthattherangeofaverageGDHIacrossregionsintheUKisthewidestfoundwithinthe

EU.ThisanalysisissummarisedinFigure14.


27

Figure14Disposableincomeofprivatehouseholdsperinhabitant,highestandlowestNUTS2regionwithineachcountry.

8 Healthandwell-beingconditions

Healthandwell-beingconditionsareverydifficultdimensionstoassess.Manydatagaps

emergedandthereisneitherenoughinformationatregionallevelnorfortargetedagegroup.

Wewillrefertogeneralconditionofhealthandwell-beinginthissection.TheUKpopulation

hasexperiencedanimprovementinlifeexpectancytogetherwithanincreaseinhealthylife

years.Generallythough,ScotlandhaslaggedtheUKintermsofhealthoutcomesandtherefore

UKaveragesmaynotberepresentative.Inparticular,GreaterGlasgowhassufferedbadhealth

outcomes,whichresearchershavebeenunabletoexplainbasedonavailablecontrolssuchas

incomeorsocialclass.ThisresiduallaginhealthoutcomeshasbeentermedtheGlasgow

effect.

Lookingclosertotheyoungadultpopulation,someinformationaboutlifesatisfactionis

availableforEuropeanmembersstatesintheEU-SILC2013.In2013aspecialad-hocmodule

ofEU-SILCassessedsatisfactionindifferentdomainsoflife.WereportintheFigure15the

percentageofyoungadultsagedbetween18and30whoreportbeinghighlysatisfiedinthe

10domainsassessed.GenerallyUKyoungadultsexperiencedsimilarandsometimeshigher

satisfactioninall10differentdomainscomparedtoEU28.Britonstendtobemoresatisfied

withaccommodation,livingenvironmentandrelationships,butlesssatisfiedwiththe


28

financialsituation,jobsandgreenspaces.However,onbalance,overalllifesatisfactionwas

slightlylowerthanintheEU28.

Figure15.Highsatisfactioninvariouslifedomains,populationaged18-30,EU28and

UK,2013


Thereareveryfewproxiesavailableatregionallevelregardingaccesstohealthservices.

Someofthemarecloselyrelatedtohealthsystemsuchashospitalstaffanddoctorsavailable

inthearea.Ofcoursetheseproxiesrepresentameasureofthecoverageofhealthaccess.

9 Finalremarks

ThisreporthasusedharmoniseddatafromEUROSTATandotherpubliclyavailablesourcesto

analyselivingconditionsinabroadsensefortwofunctionalregionsofScotland:

AberdeenshireandAberdeenCityandGlasgowCityRegion.Theharmonisedindicatorsare

usefulastheyallowastraightforwardcomparisonwithotherEuropeanregions.Naturally,

suchindicatorsshouldnotbeinterpretedinisolation.Whereverpossible,thesehavebeen

relatedtothestructureofScottishinstitutionsandpolicies–inparticularfortherealmof

education.Insomecasesthesehavebeensupplementedwithadditionaldatathatarenot

0.010.020.030.040.050.060.0

SaLsfacLonwithfinancialsituaLon

SaLsfacLonwithaccommodaLon

JobsaLsfacLon

SaLsfacLonwithcommuLngLme

SaLsfacLonwithLmeuse

OveralllifesaLsfacLon

SaLsfacLonwithrecreaLonalandgreen

areas

SaLsfacLonwithlivingenvironment

SaLsfacLonwithpersonalrelaLonships

Meaningoflife

EuropeanUnion(28countries) UnitedKingdom


29

availableacrosstheEU.Thissupplementationwithlocaldatahasbeenuseful.However,itis

perhapsnotthedataassuchthatrepresentsthebottleneckformeaningfuldiscussionor

comparison,butratherlocalcapacitytoengagewithdatasourcetointerpretandcritique.

Thisreporthasbenefittedgreatlyfromtheavailabilityofpriorworkmwhichhassoughtto

engagewithandapplythedatatounderstandtheScottishcontext.Coverageofthisis

undoubtedlylimitedbytheauthors'oversightandfocussesmostlyoneducationandthe

economy.Infutureworkitwouldbeusefultosupplementtheanalysisofharmonisedregional

indicatorswithsystematicreviewsofavailableacademicandpolicyliteratures,relatingtothe

topicbeingexamined.


30

10 ReferencesAuditScotland(2014).Modernapprenticeships.RetrievedfromtheWorldWideWeb:http://www.audit-scotland.gov.uk/report/modern-apprenticeships

Blundell,R.,Green,D.,&Jin,W.(2016).TheUKwagepremiumpuzzle:howdidalargeincreaseinuniversitygraduatesleavetheeducationpremiumunchanged?InstituteforFiscalStudies.WorkingPaperW16/01.

Eiser,D.(2017).AprimerontheScottishParliament’snewfiscalpowers:whatarethey,howwilltheywork,andwhatarethechallenges?FraserofAllanderEconomicCommentary,Vol.41,No.2,pp.1-17.RetrievedfromtheWorldWideWeb:https://www.strath.ac.uk/media/1newwebsite/departmentsubject/strathclydebusinessschool/fraserofallander/A_primer_on_the_Scottish_Parliament%E2%80%99s_new_fiscal_powers.pdf

EUROSTAT(2017).EuropeanUnionstatisticaloffice,http://ec.europa.eu/eurostat/

EUROSTAT(n.d.a)TheEuropeanUnionLabourForceSurvey(EU-LFS),

EUROSTAT(n.d.b)TheEuropeanUnionStatisticsonIncomeandLivingConditions(EU-SILC),EUROSTAT

Furlong,A.,Goodwin,J.,O'Connor,H.,Hadfield,S.,Hall,S.,Lowden,K.andPlugor,R.(2017)YoungPeopleintheLabourMarket:Past,Present,Future.Routledge:London.ISBN9781138798069(InPress)

Hermannsson,K.(2016).Beyondintermediates:Theroleofconsumptionandcommutingintheconstructionoflocalinput–outputtables.SpatialEconomicAnalysis,11(3),315-339.

Hermannsson,K.,Lisenkova,K.,McGregor,P.G.,&Swales,J.K.(2014).‘Policyscepticism’andtheimpactofScottishhighereducationinstitutions(HEIs)ontheirhostregion:accountingforregionalbudgetconstraintsunderdevolution.RegionalStudies,48(2),400-417.

Lisenkova,K.,McGregor,P.G.,Pappas,N.,Swales,J.K.,Turner,K.,&Wright,R.E.(2010).Scotlandthegrey:alinkeddemographic–computablegeneralequilibrium(CGE)analysisoftheimpactofpopulationageinganddecline.RegionalStudies,44(10),1351-1368.

OrganisationforEconomicCo-operationandDevelopment–OECD(2015).ImprovingSchoolsinScotland:AnOECDPerspective.Paris:OECD.RetrievedfromtheWorldWideWeb:http://www.oecd.org/edu/school/improving-schools-in-scotland.htm

OrganisationforEconomicCo-operationandDevelopment–OECD(2016).OECDEvaluationFrameworkforModernApprenticeshipsinScotland.OECDscience,technologyandinnovationpolicypapers,no.35.RetrievedfromtheWorldWideWeb:http://www.oecd-ilibrary.org/science-and-technology/oecd-evaluation-framework-for-modern-apprenticeships-in-scotland_59084781-en

OrganisationforEconomicCo-operationandDevelopment–OECD(2017),https://data.oecd.org/

OrganisationforEconomicCo-operationandDevelopment–OECD(n.d.a),PIAAC,http://www.oecd.org/skills/piaac/


31

OrganisationforEconomicCo-operationandDevelopment–OECD(n.d.b),PISA,http://www.oecd.org/pisa/

OfficeforNationalStatistics–ONS(2016).GrossDisposableHouseholdIncomebyEuropeanRegions.RetrievedfromtheWorldWideWeb:https://www.ons.gov.uk/economy/regionalaccounts/grossdisposablehouseholdincome/bulletins/regionalgrossdisposablehouseholdincomegdhi/2015

SAAS–StudentAwardsAgencyScotland(n.d.).Exceptionsfromthegeneralresidenceconditions.RetrievedfromtheWorldWideWeb:http://www.saas.gov.uk/_forms/residence.pdf

ScottishGovernment(2015).OECD-ScotlandEducationPolicyReview:ABackgroundReportbytheScottishGovernment.RetrievedfromtheWorldWideWeb:http://www.oecd.org/education/school/OECD-Scotland-Education-Policy-Review-Background-report.pdf

UnitedNationsEducational,Scientific,andCulturalOrganization–UNESCO,http://data.uis.unesco.org/


Work Package 4


Spain – National Briefing Paper with national and regional

data sets Name: Rosario Scandurra, Universidad de Granada Xavier Rambla, Universitat Autònoma de Barcelona Date 05/09/2017 Work Package 4 – Quantitative Analysis of Young Adults’ Data Deliverable 4.1


2

TableofContents

ExecutiveSummary............................................................................................................................................................3

Descriptionofthedatacollatedandqualitydataassessment........................................................................3

1.Findings..............................................................................................................................................................................5

1.1. Demographicstructure....................................................................................................................................5

1.2. Thestructureoftheeconomy.......................................................................................................................8

1.3. Education.............................................................................................................................................................11

1.4. Labourmarket...................................................................................................................................................19

1.5. Redistributionandsocialinclusion.........................................................................................................21

1.6. Healthandwell-beingconditions.............................................................................................................26

2.Finalremarks................................................................................................................................................................28

References...........................................................................................................................................................................30

Listoffigures

Figure1.GDPatcurrentmarketprices,Europerinhabitantin%ofEuropeanaverage(EU28=100)............9

Figure2.LabourproductivityEU28=1andrealgrowthvalueadded...........................................................................10

Figure3.Shareofthepopulationaged20-29years................................................................................................................6

Figure4.Cruderateofnetmigrationplusstatisticaladjustment.....................................................................................7

Figure5.Agedependencyratio.On1stvariant(populationaged0-14and65andmoretopop.aged15-

64).................................................................................................................................................................................................................8

Figure6.PopulationattainmentbyISCEDlevels,25-64yearsoverthecorrespondentagegroup.................12

Figure7.Youngadult’seducationattainmentbyISCEDlevels,30-34yearsoverthecorrespondentage

group..........................................................................................................................................................................................................13

Figure8.Tertiaryeducationaccessofthepopulationaged20-24yearsoverthecorrespondentagegroup

.......................................................................................................................................................................................................................14

Figure9.EarlySchoolLeavers18-24years,ESL(leftaxis)andpopulationNeitherinEmploymentNorin

Education15-24years,NEET(rightaxis)..................................................................................................................................15

Figure10.PISAandPIAACcompetences,Europeanaverage=1......................................................................................17

Figure11.Participationrateineducationandtraining(last4weeks)........................................................................18

Figure12.Employment(leftaxis)andunemploymentrate(rightaxis),population20-64years...................20

Figure13.ExpenditureinsocialprotectioninPPSperinhabitantas%ofEU19....................................................21

Figure14.GINIindexbeforeandaftertaxes(leftaxis)anddisposableincome(rightaxis)...............................22

Figure15Riskofpoverty,rentimputedonthebaseofincomeoftheyearbefore.................................................24

Figure16.Populationatriskofpovertyorsocialexclusion,%(POV)andseverematerialdeprivation

population,%(SMD)...........................................................................................................................................................................25

Figure17.Highsatisfactioninvariouslifedomains,populationaged25-34,EU28andSpain,2013............27


3

ExecutiveSummary

Thisnationalbriefingpaperprovidesashortoverviewofthelivingconditionsofyoung

adults in Spain and in the two functional regions selected for the YOUNG_ADULLLT

project, theautonomousregionsofAndalusiaandCatalonia.Thedatawerecollatedat

national and local level (NUTs2) according to six dimensions of contextual living

conditions: the structure of the economy, the demographic characteristics of the

population, the inputs and outputs of the education and training system, the labour

market, thematerial living conditions and theparticipation as citizens to thepolitical

and civic life and, finally, the health conditions and individual well-being. Data were

extracted fromEurostatand fromdifferent surveyssuchas theEU-LFS,EU-SILC,PISA

andPIAAC.Themaincorpusofdataproceedingfrominternationalandharmonizeddata

wassuccessivelycomplementedbydatacollatedatthelocallevel,madeavailablebythe

Instituto de Estadística y Cartografía de Andalucía and by the IDESCAT, as well as by

official websites of various Spanish Institutions (Ministers, regional government and

Chambersof trade).Thedatarangesbetween2005and2015,but forsome indicators

thedatawerenotavailablefor2015andforthisreasonwereferto2014asthelastdata

available.


EurostatUNESCOandOECDprovideavastamountofharmonizedandcomparabledata

thatcanbeausefulresourceforassessingthelifeconditionsofyoungpeopleindifferent

domains and in various countries/regions. However, the availability of data at the

regional/locallevelislimited.Mostofthedataareprovidedatanationallevelandonly

twoofthesixdimensions(economyanddemography)haveafairamountofindicators

at NUTS21 and NUTS3 level. This restrains the possibility of comparison. Within the

surveysavailablethemostrelevantsourceofinformationistheEU-LFSwhichhaslarge

sample size at local level. Moreover, complementing the international datawith local

dataisahardtaskmainlyforfourreasons.

1NUTSstandsforNomenclatureUniteTerritorialStatistique.


4

First, thefragmentationofsources isrelevantbothatSpanish,AndalusianandCatalan

levels. Neither the regional bureau of statistics nor the National Statistics Institute of

Spain (INE2) bring together all the information available at public andofficial sites or

provideacompletelistofsourcesandstudies.Thus,collectingdataimpliesinvestinga

lot of time, even if these data are quite simple and publicly available. Second, the

multiplicityofavailablesourcesmightentailmethodologicaldifficultiesthathamperthe

comparability of the provided data between regions and at European level between

2005and2015.Third,thereisalackofdataatprovincial3andlocallevelintheavailable

sources. Finally, some private institutions in agreement with some public ones (the

ChamberofCommerceofCataloniaand theDepartmentofEducationofCataloniaand

the Catalan Employment Service) are collecting very rich information on skills and

competences of the vocational and training education4. However, these data are not

providedpubliclyand thechannels toaccessing themarenotclearlyestablished.This

hampers the transparency of the administration that is collecting a huge amount of

information,butit isnotusingitneithertobetterinformthecitizenshipnor,asstated

bytheChamberofCommerce,toimprovetheirownpoliticalaction.Moreover,thefact

that this isaprivate institution,whichdevelopsandadministers thesedatasets,poses

ethicalproblemsaswellasbureaucraticdifficultiestoaccessit.

Fromamoregeneralperspective,consideringthehighratesofearlyschoolleaversand

NEETinSpain,itisremarkablethatwedidnotfindalmostanyspecificsourcesneither

atregionalnor local level5aboutthisgroupofpopulationwhich issociallyvulnerable.

ReducingearlyschoolleaversisapriorityforbothAndalusianandCatalangovernment,

nevertheless there is no specific instrument to understand the specificities of these

youngadultsandinformpolicies.

2IstitutoNacionaldeEstadística(INE)www.ine.es3 In Spain there are 50 provinces excluding Ceuta and Melilla. They correspond to NUTS3 in the

EUROSTATclassification.4ForthecaseofCatalonia,twodatasourcesarerelevant:theComprehensiveDataBank(BancIntegraldeDades-BID).ThefirstwascreatedbyanagreementbetweentheChamberofCommerceofCataloniaandtheDepartmentofEducationofCatalonia.Nowadaysitsaimistoprovideinformationnotonlyaboutthe

available companies but also, and more importantly, to track the apprenticeship period gathering the

assessmentsdevelopedbyboththehighschools,thecompaniesandthestudentsthemselvesinrelationto

each training process. In the last years, information about those courses provided by the Employment

Service of Catalonia has also been included. The Graduate Insertion Survey (Estudi sobre Inserció deGraduats) collects information about the degree, quality and the suitability of the placement of thestudentsfromtheVETprovidedbytheHighSchoolsoncetheyhavefinishedtheirstudies.5 Here with regional and local level, we refer respectively to Andalusia and Catalonia andMalaga and

GironaasfunctionalregionoftheYOUNG_ADULLLTproject.


5

Understanding young adult social risk represents a very broad objective. For this

endeavour, the data needed were collected in various studies, in different way and

sometimes for very specific purposes. For this reason, the most accessible data are

EUROSTATsincetheyalreadyprovideharmonizeddata,metadataandcompletedtime

series.However,accessibilityofdataisnotastraightforwardissue,asdatabasesarenot

completely combined and flexible and the collection is at times difficult and time

consuming.Thecomplexityandvarietyofthedatapublishedmakesuchcomprehensive

integrationdifficulttoachieve.

1. Findings

1.1. DemographicstructureSpaincoversatotalareaof505.970squarekilometres.Itisthesecondlargestcountryin

theEU28anditrepresents11%of its totalarea.Spain isdivided into17Autonomous

regions; the biggest one isAndalusiawith an area of 87.597 square kilometres,while

Cataloniacovers32.091km².SpainisthefifthmostpopulatedcountryintheEuropean

Union.Thepopulation increasedgradually reaching46.8million in2012, thenstarted

decreasing(in2015,thepopulationwas0.7%lessthan2012).AndalusiaandCatalonia

are the most populated autonomous regions with respectively 8.3 and 7.4 million

inhabitants. The population density is below 93 individuals per square kilometre in

Spainandithasslightlyincreasedoverthepastdecade.Itisveryunevenlydistributed

both between andwithin regions: Andalusia has 97 individuals per square kilometre,

whileCataloniahas232,morethandoubleoftheSpainaverage.

Youth population aged 20-29 in 2015 accounted for approximately 10.4% of total

inhabitants,makingup11.5%ofthepopulationintheregionofAndalusiaand10.1%in

Catalonia.Thedecreaseoftheshareofyouthpopulationoverthelastdecadeisconstant

andremarkable.


6

Figure1.Shareofthepopulationaged20-29years

Source:EUROSTAT

GenerallivingconditionsinSpainarecomparativelygoodinrelationtootherEuropean

countries.Infantmortalityinthefirstyearafterbirthis2.7whileintheEU28itwas3.6

in 2016 with a constant decrease over the last decade (in 2005 it was 3.7). Life

expectancyinSpainis83.3yearshighercomparedtoEuropeanaverage,buttheoverall

valueistheresultofrelevantgenderdifferences:aSpanishfemalein2014couldexpect

tolive86.2years,whileamalehadalifeexpectancyof80.4years.Territorialdifferences

areremarkable;inAndalusiaitis1.2yearslowerthanSpainaverage,whileinCatalonia

itisabout0.3yearshigher.Infantmortalityinthefirstyearafterbirthislow;ittouched

aminimumof2.7deathsper thousand in2015,being theEU28average3.6.Thishas

decreased from2005of1year.Someterritorialdifferencesemerge.Cataloniahas2.4,

whileAndalusia2.9,andthisdifferencewaslargeroverthelastdecade.

SpainsharesaconditionoflowfertilitywithotheradvancedEUcountries,asthefertility

ratewas 1.32 in 2015. Catalonia and Andalusia had higher fertility rate compared to

Spain (1.39).During thepast decades, fertility has remained constantly lowwhile the

ageatwhichawomanhasherfirstchildincreasedfrom29.4to30.7between2005and

2015(EU28averagein2015was28.9).

Spain is a country of recent immigration, above all from Spanish-speaking countries.

During the middle nineties migration started to grow and reached one of its peaks

10

11

12

13

14

15

16

17

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Spain Catalonia Andalusia


7

before theeconomiccrisis.From2007migrationhasbeen increasinglydiminishingas

the economic crisis reduced the attractiveness of the country. The crude rate of net

migrationwentfromitspeakof17.2in2007to0in2016,meaningparityofmigration

flows,afteralreadyhavingreachednegativesignsyearsbefore.

Currently,policiestargetingyoungadultsarecrucialfortheeffectivesocialinclusionof

theforeign-bornpopulationinthecountry.Significantly,whileforeign-bornindividuals

amountedto10%ofthewholepopulation,in2017thisproportionscored13%among

20-to-24year-oldsand16%among25-to-29year-olds(INE,2017)6.Failingtocaterto

theneedsofthesegenerationsthreatenstoaggravateethniccleavagesinthelongterm.

Figure2.Cruderateofnetmigrationplusstatisticaladjustment

Source:EUROSTAT

The combined effect of living longer and fewer children is transforming the

demographicstructureacross theEuropeancountries.Thedemographicpyramidsare

changinganddependencyratiosareoftenusedtocomparethesizeofsuchgroupsand

6Source:InstitutoNacionaldeEstadística-INE(2017)CifrasdePoblación(CP):Poblaciónresidenteporfecha,sexo,grupodeedadynacionalidad.Retrievedfromhttp://datos.gob.es/es/catalogo/e00121204-cifras-de-poblacion-cp-poblacion-residente-por-fecha-

sexo-grupo-de-edad-y-nacionalidadon28July2017

-15.0

-10.0

-5.0

0.0

5.0

10.0

15.0

20.0

25.0

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Spain Catalonia Andalucia


8

theygenerallyrelatecentralagegroupswithdependent(youngandold).Infigure5,age

dependency ratios are plotted together with other European countries. The level is

lowerforSpainalthoughafastincreaseintheshareofdependentamongthepopulation

is registeredsince2009onwards (the firstvariantof theagedependency ratio raised

from 45 until 51.2 in 2016). The increase in the dependent population is similar,

although inAndalusia is lower compared theboth the Spanish average andCatalonia.

Whencomparingtheoldestshareofthepopulationtocentralages,ageneralincreasein

theshareofthepopulation65andoverisrevealed;thetrendissimilarinAndalusiaand

Catalonia.

Figure3.Agedependencyratio.On1stvariant(populationaged0-14and65and

moretopop.aged15-64)

Source:EUROSTAT

Thepercentageof youngadults livingwithparents is69.6%against the55.4%of the

EU27average(formen74.3and64.8forwomen).Overthelastdecadethisindicatorhas

remainedstable,althoughitreacheditslowestpeakin2010,being65.2%.

1.2. ThestructureoftheeconomyDuringthelastdecade,theSpanisheconomyhasexperienceddifficultiesadaptingtothe

impactoftheeconomiccrisis.From2006to2015,GDPincreasedfrom25.500to25.900

europerinhabitant,butithasdiminishedinrelativetermslosing13%comparedtothe

15

20

25

30

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

Pop.0-14and65+to15-64

Germany SpainCatalonia AndaluciaUnitedKingdom

15

20

25

30

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

Pop.65+to15-64years

GermanySpainCataloniaAndalucia


9

Europeanaverage.Inthesameperiod,theGDPofAndalusiadecreasedbothinabsolute

(2.5%)andrelativeterms(14%comparedtotheEU28),whileitincreasedinCatalonia

(2.6%)butdroppedinrelationtoEU28(-15%).Theimpactoftheeconomiccrisisseems

tohavehittheeconomicoutlook,althoughsomesignsofrecoveryseemtobeemerging

togetherwithgrowingeconomicdisparitieswithinthecountry.

Figure 4. GDP at current market prices, Euro per inhabitant in% of European

average(EU28=100)

Source:EUROSTAT

In Spain, the real growth rateof regional grossvalueadded (GVA) showedanegative

sign in2009 (-3.4%)and it stayednegativeuntil 2013, although it started to recover.

Additionally,labourproductivitymeasuredinGDPperhourworkedstayedbelowEU28

average for almost adecadealthough it reached theparity in2009. It started todrop

againaftertheeconomiccrisis,being97.1%ofEU28in2015.

0

20

40

60

80

100

120

140

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Spain Catalonia Andalucía


10

Figure5.LabourproductivityEU28=1andrealgrowthvalueadded

Source:EUROSTAT

Servicesareprevalent in thestructureof theSpanisheconomy,representing73.8%of

theshareofGDP,This issimilartotheEU28(73.9%),althoughithasaslightlyhigher

share of the agriculture sector overall. The reduction in the industry sector was

remarkable in the last decade since it used to be higher compared to the European

partners. The economic structure of the country ismainlymade up of small firms: in

2014, enterprises with less than 10 employees are equal to 94.8% of the total,

enterpriseswith10-19employeesareequal to2.9%,whilebigenterpriseswithmore

than 50 employees represent less than 0.7% over the total. The infrastructural and

transportationnetwork,whichplaysarelevantrolefortheeconomy,appearstobequite

developed;railwaylinesandmotorwayscoverrespectively32and30kilometresevery

1.000 square kilometreswith important territorial differences partially coherentwith

thepopulationdensitywithintheautonomousregions.

Thepercentageofresearchersinalloftheeconomicsectorsovertheactivepopulation

is low compared to European partners (0.9% in 2013, 1.3% in Germany and 1.4% in

0

0.2

0.4

0.6

0.8

1

1.2

1.4

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

SpainLP(EU28=1) AndaluciaGVA CatalunyaGVA SpainGVA


11

UK),withsometerritorialdifferences; forexample inCatalonia it is1%andAndalusia

0.7%.

The percentage of the GDP in PPS7 in research and development in the government

sector is1.24%inSpain(in theEU28 itwas2.04%).Over the lastdecade it increased

slightlymore than0.1%of theGDP. Territorial differences emerged: in Catalonia this

shareis1.49%,whileinAndalusiaitis1.05%,withaquitesimilarevolutionacrosstime.

Expenditure inresearchanddevelopment inthegovernmentsector isconcentrated in

Catalonia(653millioninPPS,thenationalaverageis392millionin2013andAndalusia

173).ThepatternoftheindicatorhasaUshapewithapeakin2008andaconstantand

slowdecreaseuntil2013.

Theshareofpeopleemployedinthepublicsectorisroughlystableafter2010andequal

to 7.6% of total employment in 2014, with some territorial differences (5.3% in

Cataloniaand9.5%inAndalusia),whileemploymentineducationstartedtodecreasein

2013, and was equal to 6.6% in 2014. Andalusia again shows higher employment in

education(7.2%,comparedtoCatalonia’s6.4%).Finally,peopleemployedinthehealth

sectorandinsocialworkmakeup8.2%oftotalemployment,whichislowercompared

toEuropeanpartners (UK13.3,Germany12.5%).Some territorialdifferencesemerge;

employmentinhealthsectorswas7.8%inAndalusia,whileitwas8.2%inCataloniain

2014.

1.3. EducationTheSpanisheducationandtrainingsystemiscomprehensiveandpartiallydecentralized

attheregionallevel.Thegovernmentexpenditureineducationwas4.3%ofthenational

GDPin2013andthishasremainedalmoststableoverthepasttwodecades.Full-time

education iscompulsoryuntil theageof16,althoughrecent legislationseeksto lower

this to15.Spanishsecondaryeducation is fouryears long,withstudentsat theendof

the third year being able to choose between either Bachillerato (Baccalaureate

equivalent) or Ciclo de Grado Formativo Medio, the latter being geared towards

vocationaltraining.Indeed,therearetwoprogramsofvocationaltraining,ashorterand

a longer program, lasting three and five years, respectively. All students successfully

7PurchasingPowerStandard(PPS)isaspecialcaseofPurchasingPowerParityPPPadjustmentascarried

outbyEurostat.


12

completing secondary education can access university after passing a general entry

examinationorganizedbyeachpublicuniversity.

SpainstilllagsbehinditsEuropeanpartnersintermsofeducationalattainment.Thisis

in part due to a highly unequal distribution of education across the age cohorts. The

population aged 56-65 has one of the lowest average years of schooling of all the

EuropeancountriesaccordingtoPIAAC.In2005morethanhalfofthepopulation(51%)

agedbetween25and65yearsattainedlowersecondaryeducation(ISCED2),whilein

2014 this diminished to 43% representing 18% reduction over the past 10 years.

Nevertheless,therateofreductionislowercomparedtootherEuropeancountries.

Figure6.PopulationattainmentbyISCEDlevels,25-64yearsoverthe


Source:LFS,EUROSTAT

Examining tertiaryeducation,34.7%of thepopulationagedbetween25and64years

haveatleastattainedISCED5withanincreaseof22%from2005.Thestockoftertiary

educated people is lower compared to other European partners and it has strongly

increased. However, there is important variation between regions; 23% in Andalusia

and 30% in Catalonia in 2005. Over the last decade, this has increased to 27.6% in

AndalusiaandinCatalonia37%,increasingthegapbetweenthetworegions.

020406080100

2005


020406080

100

2014



13

Figure7.Youngadult’seducationattainmentbyISCEDlevels,30-34yearsoverthe


Source:LFS,EUROSTAT

When we look at young adults, Spain has a very high tertiary education attainment,

higher than European partners; in 2005 almost 2 out of 5 people aged 30-34 have

attained tertiaryeducation,while in2014 theproportion increasedby roughly6%. In

2005, in Andalusia 31% of the population aged between 30 and 34 had tertiary

education and this remained almost stable over the past decade (the increasewas of

0.9%),while forCataloniatheattainmentwas41.2%andit increasedto47%in2014.

Moreover,womenaremorelikelytoachievetertiaryeducationattainment;102women

over100maleattaineditin2005andthisratioincreasedto111in2014.

Examininglowereducationattainmentofthepopulationaged30-34,Spainhasahigher

proportion of population with less than secondary education compared to European

partners. Itwas38.3%in2005andthisdecreasedreaching33.7%in2014.Thereare

highterritorialvariationsinsecondaryeducationattainment.InAndalusiaalmosthalfof

thepopulationagedbetween30and34attainedsecondaryeducationwhileinCatalonia

itwas a third, in linewith the Spanish average.When comparing thiswith European

partners, Spanish secondary educationattainment is almost thedoubleofUKaverage

and three times of that of Germany. Gender differences are very relevant; secondary

educationattainmentamongwomenwas27.9%whileformenitwas10pointshigher;

thisgaphasbeenmaintainedover thepastdecade.Thisdifferencebetweengender is

notpresentedincountrieslikeGermanyorUK.

101520253035404550

ISCED0-2

Andalucia Catalonia Spain

Germany UK

101520253035404550

ISCED5-8

Andalucia Catalonia Spain

Germany UK


14

Overall, there ishighpolarizationofeducationattainmentandhighvariationbetween

regions. Andalusia and Catalonia represent two extreme cases in Spain and this is

indirectlyrelatedtothesocio-economicattractivenessofthetwoterritories.Finally,itis

worth noticing that traditionally vocational programmes at upper secondary level are

not effective in bridging the transitions to the labour market and this represents an

importantfactorintheeducationattainmentpolarization.

InSpain,thereisnocompulsorypre-primaryschoolsystem,butmanyparentsdecideto

prepare their children for primary school by enrolling them to the so called “escuela

infantil”, which is relevant in developing cognitive and non-cognitive abilities and

buffering the influence of the familiar background.Althoughpre-primary education is

not compulsory in Spain, the participation rate of 4 years-old in education was

traditionally very high and remained high during the past decade with almost a full

coverage,reachingalmosttheentirepopulationof4yearsoldsforwhomenrolmentis

soughtandthere'snotsignificantvariationbetweenregions.In2012theEU-28average

was93.9%whereastheaverageinSpainwasalmost4%higher(97.4%).

Figure8.Tertiaryeducationaccessofthepopulationaged20-24yearsoverthe


Source:EUROSTAT

40

50

60

70

80

90

100

2005 2006 2007 2008 2009 2010 2011 2012

Andalucia Catalonia Germany Spain UnitedKingdom


15

InSpain,theleveloftertiaryeducationaccessishighcomparedtoGermanyortheUK.In

2005, Spain had higher tertiary access compared to Germany; overall 1 over 2

individualsbetween20and24yearswasenrolledinatertiaryeducationprogram.Over

the last decades access to university has increased, following a historical trend that

started4decadesbefore.In20124outof5peopleaccessedtertiaryeducationandthe

territorial differences are very relevant. In Catalonia, 9 out of 10 people attended

university, while, in Andalusia, thiswas approximately the case for 7 out of 10, with

more than 20% difference between the two autonomous regions. This difference is

partially due to the attractiveness of Barcelona both for national and international

students and the substantial presence of academic institutions. Tertiary education

access in Spain is high compared to European partners, possibly as a consequence of

economiccrisisandthereductionofopportunitycostofattendinguniversity.

InSpain,theratioofearlyschoolleavers(ESL)(thepercentageofthepopulationaged

18to24havingattainedatmost lowersecondaryeducationandnotbeinginvolvedin

furthereducationortraining)wasequalto19%in2016,comparedtotheEU28rateof

10.7%. Marked gender differences emerged; the prevalence of early school leavers

amongwomenwas15.1% in2016,while formen itwas22.7%.The trend towards a

decreaseofloweducatedindividualsisalmostidenticalforbothgenders(around60%)

andtherateofreduction increasedafter2009. In the lastdecade,earlyschool leavers

diminished frombeing3outof10 to less than2outof10peoplebetween18and24

years.Importantterritorialdifferencesemergedbothinthelevelofearlyschoolleavers

(inAndalusia 27.7% in 2014,while in Catalonia theywere 22.2%), and in the rate of

reduction over the past decade where Catalonia is similar to Spain average while

Andalusiaisslightlybelow.

SimilarlytoESL,theproportionofyoungpeopleneitherinemploymentnorineducation

andtrainingagedbetween15and24years(NEET)diminishedfrom18.6%(13.1%in

theEU27)in2005,to14.6%in2016(11.5%intheEU27),althoughimportantterritorial

differences emerge, similar to those observed for ESL. Overall, the link between

educationandthelabourmarketisstillnotsmoothandmanyyoungadultsareexcluded

orhavedifficultiesinfindingajob.


16

Figure9.EarlySchoolLeavers18-24years,ESL(leftaxis)andpopulationNeither

inEmploymentNorinEducation15-24years,NEET(rightaxis)

Source:EUROSTAT

The former data depict a particular portrait of polarised educational inequalities.

Between2005and2014 theproportionof30- to-34year-oldswhoachievedatmost

both ISCED 0-2 and ISCED 5-8 exceeded the scores of Germany and the UK. In 2012

about 75% 20- to- 24 year-olds entered tertiary education. In 2016 the rate of early

schoolleaverswas19%,thatis,9percentagepointsabovetheEUaverage.Inaddition,

PISA and PIAAC tests have recently noticed that young adults have not acquired the

samelevelofcompetencesthanthemajorityofcountriesincludedintheseassessments.

Therefore, many young adults appear to follow non-standard educational pathways

insofaras they leaveschoolearlybutafterwardsenrol inotherprogrammes that lead

themtotertiaryeducation.However,theseexperiencesareinsufficientformanyofthem

tolearnthebasicacademiccompetences.

0

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25

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30

35

40

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

AndalusiaESL CataloniaESL SpainESL EU28ESL

Spain,NEET Catalunia,NEET Andalusia,NEET EU27NEET


17

Figure10.PISAandPIAACcompetences,Europeanaverage=1

Source:PISAandPIAAC

In terms of the few data available on the competences of the young population, two

assessmentsofferapartialviewofthelevelanddistributionacrossSpanishpopulation:

PISAandPIAAC.Thisdata isnotrepresentative forthecaseofPIAACatregional level

whichisthemostvalidproxybecauseitassessesspecificallyyoungadults.However,we

includePISAinouranalysisbecauseitprovidesaproxyofcompetencesatthemoment

ofcompletingsecondaryeducation.AccordingtothePISAassessment,Spanish15year

oldstudentsperformslightlybelowtheEuropeanaverage.InPISA2003,theyperform7

points lower innumeracy and13 in literacy compared toEuropean average. In2015,

thisgapdiminishedbyhalfapoint,althoughthestandarddeviationandthecoefficient

of variation for Spain are lower than average (10 points and 0.02 respectively). This

showslowerdispersionoftheoveralldistributionandthispatternissimilaracrossPISA

wavesandliteracydomains.LookingatPIAACadultcompetences,youngadultsaged20-

30score5pointslowertheEuropeanaverageandthisappearstobecoherentwiththe

assessment of PISAon15 years oldpupils. Thedisadvantageof Spanish young adults

0.75

0.8

0.85

0.9

0.95

1

Meannumeracy CoeffofvariaUonnumeracy

pisa2003,age15 pisa2015,age15

piaac2012,age20-30 piaac2012,age20-50


18

compared toEuropeanpeers is similar across the twodomainsassessed inPIAAC (in

numeracy is 7 points lower). If we look at 20-50 years population this gap persist.

However, thedistribution ismoreconcentratedand inboth thedomains thevariation

among respondentswas lower thanEU average (the standard deviationwas 8 points

lower in numeracy and 5 in literacy), pointing out the coexistence of a lower level of

adult competenceswitha relativelyevendistributionamongyoungadults (Valiente&

Scandurra2015).

Figure11.Participationrateineducationandtraining(last4weeks)

Source:EUROSTAT

Regarding adult participation in education and training, In Spain people who have

participatedinadulteducationinthelastfourweeksbeforebeinginterviewedare18%

in2016whichisslightlyaboveEU27average(17.4%).Thepatternoverthelastdecade

has a U shape: it starts above EU27 average, it increases strongly between 2009 and

2013andstartstodecreaseduringthelast4years.

12

13

14

15

16

17

18

19

20

21

22

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

EU27 Germany Spain


19

1.4. LabourmarketSpainoperates amalebreadwinnermodel, although, until the effects of the economic

crisiswerefelt,thereweresignsoffastchange,increasingtheaccessofwomentopaid

employment. The labour market has traditionally suffered from very high

unemployment,butthiswasgraduallyreducedinthe20-yearperiodupto2009.Youth

unemploymenthasbeenespeciallyhighduringtherecentyearsaseconomiccrisishas

loweredtheaccesstothelabourmarketandthetransitionbetweeneducationandthe

first jobbecameespeciallyprecarious.Additionally,employment ismoreconcentrated

in low skilled occupations, while high skilledwhite-collar occupation represents only

19%vs.27%comparedtoEU27ofthepopulationemployedin2015.Thisfeatureofthe

Spanish labourmarket and skills level of the overall population play a central role in

explainingdivergenceinlabourmarketaccessacrossEuropeancountries(Calero&Choi

2017).

Duringthetimespan2006-2015theoveralleconomicemploymentrateforadultsaged

between20and64wasbelowtheEU-28average.Thisgapstartedtoincreasein2008,

andin2015itreached8%difference(Spain62vs.EU2770.1%).Lowemploymentrate

isparticularlyhighinyouthpopulation(peopleagedbetween15and24),beingalmost

halfof theEU27,with important territorialdifferences.Before2007,Spainhadhigher

youth employment rate compared to EU27, but after it decreased dramatically being

17.9%in2015,whichisalmosthalftheproportionofEU27.

Focusing on unemployment rate, Spain registers high unemployment rate (in 2015,

21.7% compared to 9.2 of EU28). There are huge territorial variations with 13%

differencebetweenCataloniaandAndalusia.After2008,unemploymentonaggregatein

SpainincreaseddramaticallycomparedtotheEuropeanpartnersandfrom2013ithas

started to decline very slowly. Unemployment is particularly concentrated on youth,

wherealmosthalfoftheactivepopulationaged15to24yearsisunemployed,whichis

more than double the rate of European partners. Again, huge territorial differences

emerge, in Andalusia youth unemployment being 56.8% and 42.3% in Catalonia. In

addition, the percentage of active population unemployed for more than one year

reached10.4% in 2015 (EU274.5%), increasing dramatically from2008when itwas

2%almostinlinewithEU27.Thisrepresentsanimportanthumantollasthesepeople

arelikelytohavelowerchancetogetemployedandlosetheirwillandabilitytowork.

Again, importantterritorialdifferencesemerge; inAndalusia longtermunemployment


20

in2015was14.8%,whileinCataloniaitwas10.4%.Someauthorshaveshownthatthe

chancestoloseajobwereconcentratedinlowskilledoccupation,whichwerethefirst

toshowjoblosses.Particularlyyouthpopulationemployedinlowvalue-addedactivities

associatedwithrealestateor tourismssectorssuffered themostduring theeconomic

crisis.

Figure12.Employment(leftaxis)andunemploymentrate(rightaxis),population

20-64years

Source:EUROSTAT

In 2014 Spain invested in the overall labourmarket policies an amount of resources

equal to3%of theGDP, similar toFinlandwhich is oneof the countrieswithhighest

investment.Expenditureincreasedduetothefirstimpactofthecrisisin2008-2009and

reached its peak in 2010, then started to decrease. Almost 2.4% out of 3% (80%) is

directed toward out-of-work incomemaintenance, although cut and reduction to the

entitlement have lowered the share of GDP. Active labour market represents a very

smallshareoftheoverallLMP,wheretrainingis0.12%ofGDP,ahalfofGermananda

fourthofAustrianGDPshare.

0

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72

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

EmploymentRateSpain EmploymentRateEU28UnemploymentRateEU28(rightax) UnemploymentRateSpain(rightax)


21

1.5. RedistributionandsocialinclusionSpanishnetexpenditureinsocialprotectionrosefrom19.4%to23.9%inthetimespan

2007-2014,withastrongincreasetakingplacebetween2007and2011inordertocope

to theconsequencesof theeconomiccrisis. InSpain,governmentexpenditure ismore

fundedbycentralgovernmentcomparedtoEU28(47,3%in2015),autonomousregions

accountsfor26,3%,localgovernmentof11,1%andsocialsecurityfunds14,9%.

According toESPROSS, expenditureon socialprotection isprovided tohouseholdand

individuals affected by a specific set of social risks and needs. In the case of Spain,

resourcesspentforsocialprotectionbenefitswereequalto6.079europerinhabitants

in 2014, which means almost 70% of the EU19 average and 76% of the EU28. The

expenditureincreasedinthelastdecade,butthisshareremainedconstantlybelowthat

ofEuropeanpartners.



0

0.2

0.4

0.6

0.8

1

1.2

1.4

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Germany Spain Italy Finland UnitedKingdom


22

ThisshowsthetraditionallowgenerosityoftheSpanishwelfarestate.Themainshareis

spent for pensions and retirement (old age), that is also the indicator showing the

strongest increase (45%) between 2007 and 2014, rising from 6 to 8.8% of national

GDP,belowEuropeanpartners. Spain registeredan increaseof spending in thehealth

care system in the years preceding the economic crisis, but following the crisis its

growth fell rapidly and became negative in real terms in 2010 and 2011. Some

schemeofthewelfarestateremainunder-financedcomparedtoEuropeanpartnerssuch

as health (being 79% of EU-28 expenditure in 2012), family (being 39% of EU-28 in

2012),socialexclusion(51%ofEU28in2012),family(59%ofEU28in2012).

Thedisposable incomeforhouseholds is theamountofmoneythatahouseholdearns

eachyearaftertaxesandtransfers,representingthemoneyavailabletoahouseholdfor

spendingongoodsorservices.InSpainthisislowerthantheEuropeanpartners,being

68% of the average for Germany and 83% of the UK average in 2013, and it has

remainedstableduringtheformer4years.ThedisposableincomeinCataloniawas14%

higherthantheSpanishaverage,whileinAndalusiaitwas21%lower.Forthisindicator

longer series are not available and for this reason it is not possible to compare the

recenttrendwiththepre-economiccrisislevel.

Figure 14. GINI index before and after taxes (left axis) and disposable income

(rightaxis)

Source:EUROSTAT

€10,000

€11,000

€12,000

€13,000

€14,000

€15,000

€16,000

€17,000

0

10

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30

40

50

60

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

EU27GINIbefore SpainGINIbefore EU27GINIa\er

SpainGINIa\er Spaindisposableincome Cataloniadisposableincome

Andalusiadisposableincome


23

IntermsofincomeinequalitySpainissimilartoEuropeanpartners(50.8comparedto

51.9EU27),andit followsthegeneraltrendofwideningthegapbetweentherichand

thepoor.Between2005and2015theGiniindex8,whichisoneofthekeymeasuresfor

inequality, shows that the concentration of incomewent from 46% to 50.8% against

EU27valuesof respectively49.7%and51.9%.However, theredistributivecapacityof

thewelfarestateappearsreduced,astheGiniindexaftersocialtransfersdropsdownto

34.6% in 2015, accounting for a 31.8% reduction of income inequalities (EU average

was 40.3%). In addition, householdwealth appearsmuchmore unequally distributed

than income. In 2012, the richest 10% of Spanish households owned 43% of overall

household wealth, being the median 300.000 US dollars, 50% than the 17 OECD

countries included. In addition, half of the population results in a high level of

indebtednesswhichismainlyconcentratedinrealestateassets(OECD,2016).

Therateofpeopleatriskofpovertyorsocialexclusionstartedtogrowin2008andin

thelastfouryearsithasbeenbetween10%and20%higherthantheEU27.Territorial

differencesbetweenCataloniaandAndalusiaareveryrelevantandinthelasttenyears

theyhavegrown;In2005theshareofpeopleatriskofpovertyinAndalusiawas31%,

whichis78%morecomparedtoCatalonia(30%comparedwithSpainaverage),whilein

2015itreached42.6%,representing118%comparedtoCataloniaand50%morethan

Spanishaverage.From2010territorialdifferencesstartedtoenlargereachingapeakin

2015.

Whenwelookattheseverematerialdeprivationrate9,apartfrom2005,Andalusiahas

experiencedhigherlevelofextremepovertyoverthelastdecade.Spanishaveragewas

4.1%in2006equaltoCatalonia,whileinAndalusiaitwas6.5%.In2015itwas6.4%in

Spain,6.7%inCataloniaand8%inAndalusia,showingageneralincreaseinthecountry,

butlessinequalitywithinregions.EU-SILCdatapointthatoverthelastdecadegrowing

inequality seem to be concentrated not on the extreme poor but on people at risk of

povertyandtheshareofpoorisgrowinglargelyamongregionsinSpain.

8 The Gini coefficient measures the extent to which a distribution deviates from a perfectly equal

distribution. In this case, GINI is applied to equalised disposable incomewithin a country. Generally it

ranges from0 to100,however it could alsobeexpressedon1-point scale.A coefficientof0 expresses

perfectequalitywhereeveryonehasthesameincome,whileacoefficientof100expressesfullinequality

whereonlyonepersonhasalltheincome.9Severematerialdeprivationrateisdefinedastheenforcedinabilitytopayforat leastfourbasicitems

suchas:1. topaytheirrent,mortgageorutilitybills;2. tokeeptheirhomeadequatelywarm;3. to face

unexpected expenses; 4. to eatmeat or proteins regularly; 5. to go on holiday; 6. a television set; 7. a

washingmachine;8.acar;9.atelephone.


24

One of the main drivers is the massive loss of job experienced during the economic

crisis. In fact, the share of people living in households with low work intensity

(population aged 0 to 59 years) experienced a dramatic rise until 2014 for Spain,

representing 17.1%while in 2005 it was 6.9%. The same trend was experienced by

Catalonia andAndalusia. From2005 until 2015 the increase ranged between 4.1% in

Cataloniatoamaximumof14.1%inAndalusia.

Finally,althoughtheregionaldataarelimited,itisinterestingtolookattheratesof

povertyacrossagegroupssincethefinancialcrisis(SeeFigure1510).Infact,the

proportionof16-to-29years-oldwhowereexposedtotheriskofpovertyincreased

from18,1%in2008to29,6%in2016.Theleapexceedsthe150%ofthevaluescoredin

theinitialyear.

Figure15Riskofpoverty,rentimputedonthebaseofincomeoftheyearbefore

Source:INE,2017

10INE,Riesgodepobreza(rentaañoanterioralaentrevista).Retrievedfrom,http://www.ine.es/jaxiT3/Tabla.htm?t=9958on18,July2017.

0

5

10

15

20

25

30

35

2008 2009 2010 2011 2012 2013 2014 2015 2016

Total Lessthan16yrs. 16-29yrs.

30-44yrs. 45-64yrs. 65yrs.andover


25

Figure16.Populationatriskofpovertyorsocialexclusion,%(POV)andsevere

materialdeprivationpopulation,%(SMD)


Concerningthepublicsphereandcivicparticipation inSpain,dataonvoterturnout in

national elections, which is one of the proxy of citizens' participation in the political

process, expresses a clear trend of decline, common tomany other EU countries. The

percentagewasequalto75.3%in2006,butparticipationdecreasedto68.9%in2011,

lower than the European average. A similar decline is also shown by turnout data in

regionalandEUparliamentaryelection.In2010accordingtothequalityofgovernment

index11 the Spanishmeanwas 0.09 in 2010 and 0.13 in 2013, being themean of the

Europeanaverage120.23in2010and0.21in2013.Territorialdifferencesarepresent;

Cataloniascoredonthisscale-0.43and-0.05,whileAndalusiascored-0.15and0.02for

2010 and 2013 respectively. The perceptions about the quality and the trust of

11 The European Quality of Government Index (EQI) is the result novel survey data on corruption and

governanceattheregionallevelwithintheEU,conductedintwowavesin2010and2013.Thedatafocus

onbothperceptionsandexperienceswithpublicsectorcorruption,alongwiththeextenttowhichcitizens

believe various public sector services are impartially allocated and of good quality. The data is

standardizedwithameanofzero,andhigherscoresimplyinghigherqualityofgovernment.12Itreferstoall28Europeanmemberstatesandtwoaccessioncountries(SerbiaandTurkey).

0

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30

35

40

45

50

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

SpainPOV CataluñaPOV AndalucíaPOV

SpainSMD CataluñaSMD AndalucíaSMD


26

Spaniards appear to be very low compared to EU average and this is particularly the

caseofCatalonia.

1.6. Healthandwell-beingconditionsHealthandwell-beingconditionsareverydifficultdimensionstoassess.Manydatagaps

emergedandthereisneitherenoughinformationatregionallevelnorfortargetedage

group.Wewillrefertogeneralconditionofhealthandwell-beinginthissection.Spanish

population has experienced an improvement in life expectancy together with an

increase in healthy life years. In 2015 Spanish bothwomen andmenhad65 years of

healthy life years above theEuropeanpartners likeUK (64.2 forwomenand63.2 for

menorGermanyrespectively56.5and56.4).Totalself-perceivedhealthwasveryhigh:

people reporting very good or good self-perceived health were 72.6%, being 5.6%

higher thanEU27 average.However, the trend of this indicator showedhigh increase

before 2011 and it dropped almost 3% in the last three years. This is caused by an

increasing share of peoplewho report bad self-perceived health as the ratio between

highandlowself-perceivedhealthwentbetween2011and2015from14to12.5while

intheEU27itwas8.96reaching8.7inthelastperiodreported.

Lookingclosertotheyoungadultpopulation,someinformationaboutlifesatisfactionis

available for Europeanmember states in the EU-SILC 2013. In 2013 a special ad-hoc

module of EU-SILC assessed satisfaction in different domains of life.We report in the

Figure17 thepercentageof young adults agedbetween25 and34who report being

highly satisfied in the 10 domains assessed. Generally bothwomen andmen Spanish

young adults experienced lower satisfaction in all 10 different domains compared to

EU28,expectintimeuse(+1.7%)andmeaningoflifedomain(+3.2%).Biggestgapsare

revealed incommuting time (-10.7%), recreationalactivities (-7.5%), satisfactionwith

livingenvironment(-4.3%),accommodation(-3.9%)andjobsatisfaction(-5.1%).

Wealsoreportanoverallfactor13oflifesatisfactionforpeopleagedbetween18and30

years for all the items included except labour market and commuting items. This

populationhas similar overall satisfaction compared to theEU28, being respectively -

0.018 and -0.013. However, women seem to experience less overall satisfaction

compared tomenandtheEU28average; thedispersionof the index isalsohigher for

themcomparedtomen,butlowerthantheEU28.

13 The factor is derived from a principal component analysis. The population aged between 18 and 30

yearsareincluded.ItemsincludedarePW030,PW040,PW120,PW160,PW200,PW210.


27

Figure17.Highsatisfactioninvariouslifedomains,populationaged25-34,EU28

andSpain,2013


Thereareveryfewproxiesavailableatregionallevelregardingaccesstohealthservices.

Some of them are closely related to health system such as hospital staff and doctors

available in the area.Of course theseproxies are ameasureof the coverageof health

access.Theavailabilityofhospitalstaffandresourcesrevealedagapbetweenthetwo

regions Catalonia and Andalusia. In 2015, the availability of total beds14 in hospitals

infrastructure in Spain was 297 beds per 100.000 people while in Catalonia and

Andalusiawasrespectively435and259. Inthe lastdecade, theavailabilityofhospital

bedsdeclined as in otherEuropean countries such asGermany, but thedecreasewas

more important for Spain since it accounted for -11.7% compared to 2005 (Catalonia

registereda-12.5%andAndalusia-16%).Thisrevealsalowerhealthaccessparticularly

if we consider that there was a pre-existing gap between Spain and other European

14Totalhospitalbedsareallhospitalbedswhichareregularlymaintainedandstaffedand immediately

available for the care of admitted patients. The overall account for hospital beds which are regularly

maintainedandstaffedandimmediatelyavailableforthecareofadmittedpatients.Thesearethenbroken

downbetween: Curative care (acute care) beds; Psychiatric care beds; Long-term care beds (excluding

psychiatriccarebeds);Otherhospitalbeds.

0

10

20

30

40

FinancialsituaUon

AccommodaUon

JobsaUsfacUon

CommuUngUme

Timeuse

OveralllifesaUsfacUon

RecreaUonalandgreenareas

Livingenvironment

PersonalrelaUonships

Meaningoflife

EU28men Spainmen EU28women Spainwomen


28

partners and that the overall levelwas increasingly lower (being in2015, almost 2/3

lower than Germany and 1/3 of Finland). Considering the availability of nurses and

midwifes in hospital, Spain registered 514 per 100,000 inhabitants in 2015,which is

lower compared to other European partners. Catalonia has 602 nurses andmidwifes,

while Andalusia 370; this represents respectively 116% and 72% of the national

average.Catalonia faced importantdecrease in2010,while inAndalusia thisdrophas

beenregisteredfrom2012.

Regarding the availability of medical doctors, Spain has a similar share of doctors,

similartoFinlandandlower(-8%)thanGermany.Thesharehasincreasedslightlyover

the past decade, but a slight decrease has been registered from 2011 onwards.

Substantialterritorialdifferencesarepresent,comparedtoSpanishaverage.Andalusia

has29%lesswhileCataloniahas5%moremedicaldoctors.Thisgaphasincreasedover

thelastdecade,whilein2005Andalusiahad5%lessdoctorsandin2015ithad28.3%

lessthantheSpanishaverage.Meanwhile,Cataloniaremainedslightlyabovethemean

(+2%and+5%).

Goingbeyondsubjectiveperception,weshouldlookatsomeotherindicatorsrelatedto

thepersonalwell-being,rangingfromsecuritytoalcoholconsumptionandsmoking,in

ordertohaveabetterpictureofwell-beinginSpain.Wecanrelyonthebetterlifeindex

elaboratedby theOECDwhich collectnational composite index fordifferentdomains.

Oneofthemisthehomiciderate(thenumberofmurdersper100000inhabitants)asa

quite reliablemeasureofa country's safetybecause,unlikeothercrimes,murdersare

usuallyalwaysreportedtothepolice.Accordingtothelatestdata,Spainhasaverylow

share of murders, the seven lowest among EU28 and it decreased compared to the

period2000-08.Cataloniahomicide ratewas0.54 in2016and thisdatahasdropped,

much lower than the OECD average of 4.1. Alcohol consumption has been decreasing

overthelastdecadefrom12.3in2002until9.3litrespercapitaforthepopulationaged

15andover.ThisissimilartoUK(9.4)andFinland(9.1).

2. Finalremarks

Limitationsintheavailabilityofdataproduceascatteredoverviewoftheyoungadults

living conditions. In this sense, the present report raises awareness of two huge

challengesforfurtherresearchandpolicyevaluation.


29

First, limited information constrains the scope of academic debates. The general

accountsofeducationaltrajectoriesuseterritorialaverageratesofenrolmentandearly

school leaving in order to discuss the effects of the legal reformspassed in 1970 and

1990 (Merino, 2013; Felgueroso et al, 2014). This strand of research is problematic

becausethedataconflate individualandcollective trends. Inaddition, itasksresearch

questionsintheveinofmethodologicalnationalism,thatis,invitesspecialiststotakethe

nation-stateasthebasicunitofanalysis.

Second,notonlydatacollationrequiresenormousendeavours,butalsothepartnership

betweentheChamberofCommerceofCataloniaandtheDepartmentofEducationhas

neither been effective. Strikingly, this state of the art contrasts with themost recent

recommendationoftheEuropeanUnionregardingearlyschoolleaving:

“[The Council of the European Union], alongside the EU early school leaving

indicator,[invitesthememberstatesto]exploreopportunitiesfordevelopingor

enhancingnationaldatacollectionsystemswhichregularlygatherawiderange

ofinformationonlearners,especiallythoseatriskandearlyschoolleavers.Such

systems, covering all levels and types of education and training and in full

compliancewithnationallegislationondataprotection,could:

(…)

(d)facilitatetheavailabilityofdataandinformationatdifferentpolicylevelsand

theiruseinsteeringandmonitoringpolicydevelopment;

(e) provide the basis for developing effective guidance and support in schools

withaviewtopreventingearlyschoolleaving,aswellasfollow-upmeasuresfor

youngpeoplewhohavelefteducationandtrainingprematurely”(Councilofthe

EuropeanUnion,2015:7).

Although this briefing paper unfortunately cannot provide details at the levels of

autonomous communities and NUTS3, a brief glance of data for the whole of Spain

inspiresa fewgeneral conclusionson thesocial conditionsofyoungadults. Strikingly,

the point is that many young adults are foreign-born, these cohorts are divided by

polarised educational inequalities, and a growing share of young adults have been

exposed to income poverty since the financial crisis. These trends highlight both the

crucialrelevanceofthepoliciesaddressedtothisage-basedtargetgroupandthehuge

challengesthatthesepolicieshavetoovercome.


30

References Calero,J.,&Choi,Á.(2017).ThedistributionofskillsamongtheEuropeanadult

populationandunemployment:Acomparativeapproach.EuropeanJournalofEducation,52(3),348–364.

CounciloftheEuropeanUnion(2015)Councilconclusionsonreducingearlyschool

leavingandpromotingsuccessinschool-Councilconclusions(23November2015),14441/15EDUC310,SOC690,EMPL449,JEUN112,pp.1-14.Retrievedfrom

http://data.consilium.europa.eu/doc/document/ST-14441-2015-INIT/en/pdf(28July2017)

EUROSTAT(2017).EuropeanUnionstatisticaloffice,http://ec.europa.eu/eurostat/

Felgueroso,F.,Gutiérrez-Domènech,M.,&Jiménez-Martín,S.(2014).DropoutTrendsandEducationalReforms:TheRoleoftheLOGSEinSpain.IZAJournalofLaborPolicy,

3(1),1–24.http://doi.org/10.1186/2193-9004-3-9

INE,Estadistícassobreriesgodepobreza.(EU-SILC),Retrievedfrom,

http://www.ine.es/jaxiT3/Tabla.htm?t=9958on18,July2017.Merino,R.(2013).LassucesivasreformasdelaformaciónprofesionalenEspañaola

paradojaentreintegraciónysegregaciónescolar.ArchivosAnalíticosdePolíticaEducativa,21(66).

OECD(2017),https://data.oecd.org/

OECD,PIAAC,http://www.oecd.org/skills/piaac/OECD,PISA,http://www.oecd.org/pisa/

OscarValiente,&RosarioScandurra.(2015).Educaciópostobligatòriaidesigualtatdecompetènciesentreelsjoves.InÓ.Valiente&Q.Capsada-Munsech(Eds.),Elsreptesen

matèriadecompetènciesdelapoblacióadulta(pp.25–73).Barcelona:FundacióJaume

Bofill.TheEuropeanUnionLabourForceSurvey(EU-LFS),EUROSTAT

TheEuropeanUnionStatisticsonIncomeandLivingConditions(EU-SILC),EUROSTAT

UNESCO,http://data.uis.unesco.org/

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