youth unemployment and inactivity

Youth unemployment and inactivityA comparison of school-to-work transitions and labour market outcomes

in four Nordic countries

Ved Stranden 18DK-1061 Copenhagen Kwww.norden.org

Young people follow highly different trajectories from age 16 up to age 20, a time period which is often argued to be the most critical in terms of their future labour market outcomes. The focus of this report is on investigating the look of these early pathways, as well as on exploring their link to labour market outcomes in adulthood. Results are reported and compared for four Nordic countries: Denmark, Finland, Norway and Sweden.

Youth unemployment and inactivity

TemaN

ord 2015:548

TemaNord 2015:548ISBN 978-92-893-4229-2 (PRINT)ISBN 978-92-893-4230-8 (PDF)ISBN 978-92-893-4231-5 (EPUB)ISSN 0908-6692

TemaN

ord 2015:548

TN2015548 omslag.indd 1 20-07-2015 12:48:57

Youth unemployment

and inactivity

A comparison of school‐to‐work transitions and labour market outcomes in four Nordic countries

KarstenAlbæk,RitaAsplund,ErlingBarth,LenaLindahl,KristinevonSimsonandPekkaVanhala

TemaNord2015:548

YouthunemploymentandinactivityAcomparisonofschool‐to‐worktransitionsandlabourmarketoutcomesinfourNordiccountriesKarstenAlbæk,RitaAsplund,ErlingBarth,LenaLindahl,KristinevonSimsonandPekkaVanhalaISBN978‐92‐893‐4229‐2(PRINT)ISBN978‐92‐893‐4230‐8(PDF)ISBN978‐92‐893‐4231‐5(EPUB)http://dx.doi.org/10.6027/TN2015‐548TemaNord2015:548ISSN0908‐6692©NordicCouncilofMinisters2015Layout:HanneLebechCoverphoto:ImageSelectPrint:Rosendahls‐SchultzGrafiskPrintedinDenmark

ThispublicationhasbeenpublishedwithfinancialsupportbytheNordicCouncilofMinisters.However,thecontentsofthispublicationdonotnecessarilyreflecttheviews,policiesorrecom‐mendationsoftheNordicCouncilofMinisters.

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Contents

Introduction.................................................................................................................................................7 Increasingfocusonschool‐to‐worktransitions....................................................................7 Keyfeaturesofthestudy...............................................................................................................10 Structureandcontentofthepresentreport.........................................................................12

1. Performanceofyoungpeople–aninternationalperspective......................................17 1.1 Settingthestage..................................................................................................................17 1.2 SnapshotofrecentNordiccomparativestudies....................................................20 1.3 TheNordicstorytoldbyinternationalcomparativeindicators.....................21

2. Generaldescriptionofpost‐compulsory‐schoolactivities.............................................37 2.1 Thenationaldatasetsused.............................................................................................37 2.2 Mainactivitiesofyoungpeople–theoverallpattern.........................................41 2.3 Non‐completers–anintroductoryview...................................................................65 2.4 Individualschool‐to‐workprofiles–ageneralpicture......................................76

3. School‐to‐worktrajectories:country‐specificclusterresults.......................................89 3.1 Theclusteranalysismethod–abriefoutline.........................................................89 3.2 Country‐specificclusterresults:allyoungpeople...............................................98 3.3 Country‐specificclusterresults:non‐completers..............................................113

4. School‐to‐worktrajectories:commonNordicclusterresults....................................129 4.1 CommonNordictrajectoriesandclusters:allyoungpeople........................130 4.2 CommonNordictrajectoriesandclusters:non‐completers.........................136

5. Non‐completers’school‐to‐worktrajectories:stylizedclusterresults..................147

6. Labourmarketoutcomesasyoungadults..........................................................................171 6.1 Mainactivitiesbeyondage21–allyoungpeople.............................................171 6.2 Mainactivitiesbeyondage21–youngmenvs.youngwomen....................181 6.3 Mainactivitiesbeyondage21–completersvs.non‐completers................190 6.4 Mainactivitiesbeyondage21–latecompletionvs.non‐completion.......210

7. Labourmarketoutcomesinviewofbackground............................................................223 7.1 Genderandlabourmarketoutcomes.....................................................................223 7.2 Cohortandlabourmarketoutcomes......................................................................227 7.3 Familybackgroundandlabourmarketoutcomes.............................................232 7.4 Earlypathwaysthrougheducationandlabourmarketoutcomes.............241

8. Summaryanddiscussion...........................................................................................................273

References................................................................................................................................................279

Sammanfattning....................................................................................................................................285

Appendix:Descriptionsofnationaldatasetsused..................................................................293 Denmark............................................................................................................................................293 Finland...............................................................................................................................................294 Norway..............................................................................................................................................295 Sweden...............................................................................................................................................296

Introduction

Youthunemploymenthasforseveraldecadesbeenamuchdebatedtopicinboththeacademicandthepoliticalarena.Therecentglobaleconomiccrisis,incombinationwithprofoundchangesinlabourmarketstructures(seee.g.AcemogluandAutor,2011),shiftedyouthunemploymenttothetopofthepoliticalagendaafteralarmingreportsonsurgingyouthunem‐ploymentratesandgrowingrisksofyoungpeoplebecomingeconomicallyand socially marginalised (e.g. Scarpetta et al., 2010; ILO, 2011, 2013;Räisänen,2013).Concomitantly,increasingattentionwaspaidtoso‐calledNEETs, that is, young people not in employment, education or training.Several recent reportshighlight theprevalenceof thisphenomenonandalso provide estimates of the societal costs of early school leaving andNEETs(e.g.Eurofound,2012;BrunelloandDePaola,2014).OtherstudieshighlightthecomplexityofproblemsoftenassociatedwithbeingaNEET.A survey of thePrinceTrust (2010) covering youngpeople aged16–25reportsthatNEETsaresignificantlymorelikelytofeelashamed,rejected,lost, anxious, insecure,downanddepressed, isolatedandunloved.Theyare also disproportionately more likely to say that they had turned todrugsandthattheirlifehadnodirection.

Increasingfocusonschool‐to‐worktransitions

A growing body of evidence identifies early school leaving and schooldropoutasmajorreasonsunderlyingyouthunemploymentandmargin‐alisationfromworkinglifeinaworldwhereanuppersecondarycertifi‐catehas increasinglybecometheminimumrequirement forproperac‐cesstothejobmarket.Thoseleftbehindatthelowestfloor–thelow‐orunskilledschoolleaverslackingworkexperience–arethelosersinthecompetition with the better skilled. Their disproportionate presenceamong those holding temporary jobs, in combination with their highconcentration in cyclically sensitive industries, makes them especiallyvulnerable.Apartfromamuchhigherriskofbecomingunemployed,ascomparedtotheirhigher‐educatedpeers,youngpeoplewithalowedu‐cationalsofaceamuchhigherriskofrepeatedspellsofunemployment

8 Youthunemploymentandinactivity

that,moreover,tendtoprolongovertime.Ultimatelyschoolleaversendupoutsidethelabourforceforshorterorlongerperiodsoftime.

Hence, loweducationalattainment levelsnotonly impede initial in‐sertionintothelabourmarket,butalsorepresentanenduringbarriertoemployment(e.g.OECD,2008a).Indeed,whilethenegativelabourmar‐ket and social outcomes of youthunemployment of amore temporarynaturehavebeenshowntodiminishover time, there isaconsiderablebody of evidence on long‐term unemployment having lasting scarringeffectsonyoungpeopleintermsofbothfutureemploymentandfuturewages. Illustrative examples are a study by Kahn (2010) for the USAshowingthatgraduatingfromcollegeinabadeconomyhaslarge,nega‐tiveandpersistenteffectsonwages,andastudybyBellandBlanchflow‐er(2009) for theUKreportingthatyouthunemploymentraisesunem‐ployment,lowerswages,worsenshealthandlowersjobsatisfactionstill25yearslater.Studiesreportingpermanentemploymentandwageloss‐esarealsofoundforotherEuropeancountries,includingGermany(e.g.Schmillen and Umkehrer, 2013;Möller and Umkehrer, 2014), Norway(e.g.NilsenandHolmReiso,2014)andSweden(e.g.NordströmSkans,2011).Takentogether,theexistingevidenceimpliesthatthelong‐termcostsofearlyexitfromtheeducationsystemhaveincreased.

Whiletheeconomicbusinesscycletendstohave long‐lastingcareerconsequencesforyounglabourmarketentrants,alsotheschoolingdeci‐sion itselfmaybeaffectedby the stateof the labourmarket.Desire toworkmaybeanimportantmotivationforsomeyouthtoendtheiredu‐cation at an earlier stage.According to standardhuman capital theory(Becker, 1964), the economic situation affects the schooling decisionmainlythroughtheopportunitycostofschooling,measuredasforegoneearnings.Aboominglabourmarketimpliesmorejobopeningsandhigh‐erwages,whichinturnincreasetheopportunitycostofschooling.Thismayencouragesomeyouth to takeadvantageof the favourable labourmarketconditionsandleaveschoolonatemporaryorpermanentbasis.Aneconomicdownturn,ontheotherhand,mayinduceyouthtostayinschool and postpone their labourmarket entry, or to return to educa‐tion.Previousresearchonuppersecondaryschoolingsupportsthispre‐diction:Studentsarelesslikelytostayinschoolingoodtimes.Alsoen‐rolmenttendstodecreaseingoodtimes(Clark,2011),withgraduationratesbeingcountercyclical,aswell(ReilingandStrøm,2015).Addition‐ally,thepropensitytointerrupttheeducationanddropoutfromschoolaltogether increases in economic upturns (von Simson, 2014). On thewhole,though,theassociationisnotverystrongandotherfactors,such

Youthunemploymentandinactivity 9

asparentaleducation,aremoreimportantinexplainingschoolingdeci‐sionsthanistheeconomicsituation.

Nonetheless,earlyschoolleavinganddropoutfromuppersecondaryeducation can be seen to typically represent unsuccessful transitionswithintheschoolsystemandfurther intoworking life.Thiscontentionhas,morerecently,broadenedthefocusonunemploymentandmargin‐alisationamongyoungpeopletotheroleofschool‐to‐worktransitions.Indeed, the transition from education to working life has frequentlybeenarguedtobethemostcriticalphase intermsofayoungperson’slabourmarket outcomes later in life.While these transitions evidentlyreflect the family situation and compulsory‐school outcomes, thesemuchresearchedbackgroundfactorscannotofferafullexplanationforyoungpeople’shighlydifferent school‐to‐work‐transitionpatternsand,ultimately,fortheirdifferencesinlabourmarketoutcomesinadulthood.Thetransitionsinthemselvesseemtobeofimportance,aswell.Inotherwords, it seemsreasonable toassumethatyoungpeople’searly schooland labour market experiences upon leaving compulsory school alsoplayarolefortheirlabourmarketoutcomeslaterinlife.

These contentions explain and motivate the focus of our study onfour Nordic countries – Denmark, Finland, Norway and Sweden – themainresultsofwhicharereportedinthisvolume.Moreprecisely, firstwepresentanddiscusstheschool‐to‐worktransitionsofyoungpeopleleavingcompulsoryschool.Nextweusethisinformationtoindicatetheextenttowhichdifferentschool‐to‐work‐transitionpatternsarerelatedtotheprobabilityofyoungpeopleendingupinalternativelabourmar‐ketsituationsinadulthood.Doingso,wealsoincludebasicinformationonfamilybackground,whichallowsustotestwhetherornotearlypost‐compulsory‐schoolexperienceshavea“signalvalueoftheirown”espe‐ciallywhen it comes to young people’s probability of going into riskylabour‐markettracksdominatedbytimespentinNEETactivities,thatis,inunemploymentorentirelyoutsidethelabourforce.Putdifferently,isit evident that, in addition to family background, also early school‐to‐work transitions contain important information concerning the likeli‐hoodofdifferent labourmarketoutcomes later in life?Therestof thischapterprovidesamoredetailedoutlineofourstudyandthestructureofthepresentreport.


Keyfeaturesofthestudy

Thelabourmarketperformanceofyouthiscommonlydescribedbyuseofvariousratherconventional indicatorshighlightingphenomenasuchasearlyschoolleaving,prematuretrainingdropout,youthemploymentand unemployment, and NEET. These indicators share the feature ofprovidinganinstantaneouspictureoftheeducationaloutcomeoroftheposition/statusofyouthinthelabourmarket.Themediatedpicturecan,asaconsequence,bepartlymisleadingas thesestatic indicators fail toseetheobservedoutcome“asacumulativeprocessofdisengagementorwithdrawalthatoccursovertime”(Lyche,2010,p.14).Emergingindica‐tors,providingamoredynamicdescriptionofyouthlabourmarketper‐formance,cancorrectforsomeoftheshortcomingscharacterisingstaticindicatorsbutshare,nonetheless,thecommondrawbackofoversimpli‐fyingthedynamicnatureofyouthschool‐to‐worktrajectories.

Inordertoovercomethisunsatisfactorysituation,growingnumbersofresearchers have used alternative ways to assess comprehensively themultiplepatternsof school‐to‐work transitions that youthareknown tofacewhenmovingfromeducationintoworkinglife.However,thesetran‐sitions fromeducation toworkare far fromeasy tomeasurebecauseofthe“fluidityoftheyouthlabourmarket”(OECD2008b,p.59).Inparticu‐lar, school‐to‐work transitionsareoften long‐lastingprocesses involvingfrequent status changes between education, temporary jobs, unemploy‐mentand inactivity (Müller andGangl, 2003;Wolbers,2007; Saaretal.,2008).Thisalsoexplainswhytransitionsfromeducationtoworkcannotbefullyunderstoodbyanalysingsinglechangesofstatusonly.

More recent research on school‐to‐work transitions is therefore in‐creasinglybasedon longitudinal data allowingyoungpeople to be fol‐lowedaftertheyhavecompletedtheireducationoveralongertimepe‐riod.However,apartfromhigh‐qualitylongitudinaldata,suchadynamicapproach also requires the use of proper statistical methods. Sinceyoung people often shift between education, inactivity, unemploymentandworkbeforegettingastable job,sequenceandclusteranalysishasoftenbeenarguedtobethemostappropriatemethodologicalapproachinthiscontext(e.g.Brzinsky‐Fay,2007).Astrongadvantageofthissoci‐ologicalmethodisthatitallowsentireindividualschool‐to‐worktrajec‐tories, includingnatureof spellsand theirorder, tobe identified, com‐paredandclassifiedintooneofseveraldistincttypesofyouthtrajecto‐ries.Thiscategorisationalsoallowsproperaccount tobemade for thefact thatyouth trajectoriesoftenshowahighdegreeofdiversityespe‐ciallybygenderandeducationalbackground.Accordingly,thisevidence


clearly improves our understanding of young people’s often bumpy,occasionallyunsuccessful,transitionintoemployment.

Asalreadynoted,thisdynamicapproachtoanalysingschool‐to‐worktrajectoriesrequiresaccesstohigh‐qualitylongitudinaldata.Itis,there‐fore,hardlysurprisingthatthiskindofevidenceis,sofar,availableonlyforasmallnumberofcountries,occasionallyforthewholeofEuropeasaveragesusinginformationonalimitednumberofEuropeancountries,as done in Quintini andManfredi (2009). Alsomissing is broad‐basedcomparative information for individual Nordic countries, a knowledgegap that the present report aims to fill. Indeed, this report is, to ourknowledge,thefirstcontributionusingsequenceandclusteranalysistoinvestigate school‐to‐work transitions for full cohorts of young peopleand, moreover, to also undertake cross‐country comparisons of suchtransitionsamongyoungpeoplebasedoncomparativenationaldata.

Inexploringtheeducationalandlabourmarketexperiencesofyoungpeople,wepayparticularattentionto identifyingriskytrajectoriesandconspicuous differences in these respects between youth differing intheireducationalbackground,whilealsodifferentiatingacrossgenders.Additionally,attemptsaremadetoidentifyandquantifypossiblechang‐es in early transition patternswithin countries by comparing key out‐comesforatotalofthreeyouthcohorts:16‐year‐oldsin1993,1998and2003,respectively.Allthreecohortsaretraceduptotheyear2008im‐plyingthattheshortestfollow‐upperiodcovers5yearsandthelongest15 years. Equally important, school‐to‐work‐transition patterns andchangesinthesepatternsarecomparedacrossthefourNordiccountriesunder study to highlightmajor similarities anddissimilarities in “typi‐cal”school‐to‐worktrajectories.

Theanalysisbrieflyoutlinedaboveprovidesdetailedcross‐Nordicin‐formationondistincttypesofschool‐to‐worktrajectories forourthreecohortsof16‐year‐olds,uptoage20.Finally,thisinformationislinkedto the youngpersons’ labourmarket outcomes at threepoints later intime:when they turn 21, 26 and 31. Throughout, these alternative la‐bourmarketactivitiesaregroupedintofivebroadcategories–full‐timestudying, employment, unemployment, disability benefits and “other”(inactivity).Apartfromsimplydescribingtheserelationsbetweenearlyandlaterlabourmarketoutcomes,wealsoundertakestatisticalanalysisby use of so‐calledmultinomial logit techniques, with a view of high‐lighting the relative strength between different early school‐to‐work‐transition patterns and alternative labourmarket outcomes later as ayoung adult. As explained earlier, we thereby also account for familybackgroundinordertoexplorewhetherthelinkobservedbetweenear‐


ly school‐to‐work‐transition patterns and alternative labour marketoutcomes in adulthood remains approximately unchanged, diminishesor eventually disappears when adding parental information. The lastoptionwould,ofcourse,meanthatthedistincttypesofearlyschool‐to‐worktrajectoriesidentifiedmerelyreflectdifferencesintheyoungper‐sons’ family background. Likewise, the first optionwould point to theopposite:nolinkwhatsoeverbetweenearlyschool‐to‐worktrajectoriesand family background. Taken together, all this new evidence for thefourNordiccountriesunderstudyshouldprovidepolicy‐makersvalua‐ble information to guide them in their decisions on actions aimed toenhancethetransitionofyouthfromschoolintoworkinglife.

Structureandcontentofthepresentreport

The report is structured as follows.Thenext chapterprovides a snap‐shotofwhatwidelyusedinternationalindicatorscantellusaboutedu‐cational outcomes, school‐to‐work transitions and labour market per‐formanceof youngpeople in theNordic countries. Simultaneously, theinformation mediated by these mainly static indicators serves as abenchmarkwhenweinthenextchaptersturntopresentingresultsob‐tainedbasedonournationallongitudinaldata.

Chapter2 introduces thenationaldatasetsunderlying theempiricalevidencereportedinthisvolume.Italsodescribesandcomparesacrosscountriesthemainpost‐compulsory‐schoolactivitiesinwhichtheyoungpeople covered by our data have been engaged in, with the emphasisbeingontheirsituationuptoage20.Inotherwords,thischapterpaintsageneralpictureofyoungpeople’sactivitiesoveratimeperiodwhichisoftenarguedtobethemostcriticalintermsoftheirfuturelabourmar‐ket outcomes. The chapter also introduces our preferred definition ofyoungpeoplelackinganuppersecondarycertificate:theseyoungpeoplearecalled“non‐completers”,ascomparedto“completers”,implyingthattheyonlyhavetheircompulsory‐schoolexamstillfiveyearsafterhavingleftprimaryeducation.

In the next chapter, Chapter 3,we present a first set of results ob‐tained by “grouping” the multitude of individual school‐to‐work‐transitionpathways followedbyyoungpeoplewhenaged16 to20, asreported inChapter2,byuseofso‐calledclusteranalysis.Accordingly,thechapterstartswithabriefoutlineanddiscussionofthebasicideaofthe cluster analysis method. Only then we turn to the cluster resultsproduced foreachcountryusing informationon the full youthpopula‐


tion.Forcomparativepurposes,separateresultsarepresentedalsoforthenon‐completers.All theseresultson“typical”earlyschool‐to‐work‐transition patterns are obtained by allowing each national dataset toformtheclustersforthecountryinquestion,forwhichreasonwerefertothemas“country‐specificclusterresults”. Inotherwords,wedonotrestrict the cluster analysis in order to produce as similar clusters aspossibleacrossthefourNordiccountriesunderstudy.

Thecountry‐specificclusterresultsreportedinChapter3areusedaskeyinputsfortheclusteranalysesundertakeninthenexttwochapters,whereweexplicitlyaimatimprovingthecomparabilityofearlyschool‐to‐worktrajectoriesacrossthefourNordiccountriesbyidentifyingwhatwehavelabelled“common”Nordicschool‐to‐worktrajectories(Chapter4) and “stylized” school‐to‐work pathways for the Nordic countries(Chapter5). For the cluster analysisundertaken inChapter4wehaveforeachcountrymadea listof theobservedtrajectories(sequencesofactivities) fromage16uptoage20andthencalculatedthenumberofyoung people following each of these sequences. This country‐specificinformation is thenpooled intoonebigdatatowhichweapplyclusteranalysisinordertoallocateallthesetrajectoriesofNordicyouthacrosstenclusters“common”forthefourNordiccountriesunderstudy.1ThisapproachallowsinterestingpatternscommontotheNordiccountriestobe identified. Also this analysis is undertaken separately for all youngpeopleandnon‐completers.

InChapter5,thefocusisoncomparingasetof“stylized”school‐to‐workpathwaysconstructedforthefourNordiccountriesunderstudy.Inbrief, thebasic idea isto firstselectanumberof“typical”earlyschool‐to‐worktrajectoriesbasedontheresultsobtainedinChapter3,andthenallocatethetrajectoriesofallotheryoungpeopleacrossthese“typical”pathways.Byusing identical “typical”early school‐to‐work trajectoriesas the point of departure for all fourNordic countries,we are able toshedfurtherlightonbothsimilaritiesanddissimilaritiesacrossthefourcountries in relation toyoungpeople’spost‐compulsory‐school experi‐encesuptoage20.However,incontrasttotheanalysesreportedinthepreviouschapters,Chapter5isrestrictedtonon‐completersonly,thatis,

──────────────────────────1Hence,forproducingthecommonNordicclusterresultsreportedinChapter4,wehavenotmergedindi‐vidual‐leveldataforthefourNordiccountriesunderstudy.Instead,wehavemerelycombinedinformationonindividualtrajectoriesshowingsequencesofactivitiesfromage16uptoage20.Wehaveaskedforandalsoreceivedpermissionfromtherespectivestatisticalbureaustoundertakesuchapoolingofcountry‐specificindividualtrajectories.


to those young people who have no degree beyond the compulsory‐schoolexamstillfiveyearsafterleavingbasiceducation.Amainreasonfor this choiceof focus is that thegroupofyoungcompleters ishighlysimilar in the four countries,whereaswe seeboth striking similaritiesand distinct differences between the four Nordic countries when itcomes to non‐completers. By complementing the results produced fornon‐completers in thepreviouschapterswith informationprovidedbythese “stylized” school‐to‐workpathways,weobtain a fullerpictureofthemultitudeofearlypost‐compulsory trajectories followedbyNordicnon‐completers.

AfterChapter5,ourfocusturnsfromexploringyoungpeople’smainactivities and school‐to‐work‐transition patterns over the five yearsfollowinguponcompulsoryeducation(i.e.,fromage16uptoage20)toinvestigatingwhathappens to theseyoungstersafter theyhave turned20. What kind of main activities – studying, employment, unemploy‐ment, disability arrangements or other types of inactivity – are theymostlyengagedinasyoungadults?Canweobservedistinctandratherstabledifferences in this respect acrossgenders, on theonehand, andbetween those differing in their educational background, on the otherhand?Orisitpossiblethattheselateroutcomesare,byandlarge,quitesimilar for youngmenandwomen, aswell as for early and later com‐pletersofanuppersecondarydegreeand,possibly,evenforadultnon‐completers, i.e. those with no exam beyond primary education still inadulthood?Canweidentifyconspicuousvariationsacrosscohortsobvi‐ously related to fluctuations in the economic environment, or is theeventual impact of economic shocks rather outweighed by other pro‐cesses andmechanisms affecting the labourmarket situation of youngpeoplerepresentingdifferentcohorts?Last,butnotleast,canweidenti‐fy clear‐cut similarities ordissimilarities in all these importantdimen‐sionsacrossthefourNordiccountriesunderstudy?Chapter6setsouttoprovideanswerstothesekeyquestions.

WhileChapter6givesadescriptionofyoungpeople’s labourmar‐ket situation in adulthood, Chapter 7 looks into the background ofthese young people in an attempt to identify factors that seem to beespeciallystronglyrelatedtothelabourmarketoutcomesobserveduptoage31.Ourstatisticalanalysisreliesonso‐calledmultinomial logitmodelswhichshowtheprobabilityofbelongingtooneofseveralmu‐tuallyexclusivegroups,givenaparticularsetofbackgroundcharacter‐istics.Inourcase,thesegroupsaremadeupofthefivemaincategoriesof labour market activities used in the previous chapters: full‐timestudent,employed,unemployed,disabilitybeneficiaryoroutsideallof


these activities (“other”). The background factors accounted for inthese multinomial logit models can be divided basically into twogroups: one reflecting family background and the other early school‐to‐work‐transitionpatterns,thatis,trajectoriesfollowedstraightaftercompletion of compulsory education up to age 20. Additionally, weaccountforgenderaswellascohort.Accountingforcohortisrelevantas we base our analysis on the pooled information available for allthree youth cohorts under scrutiny, i.e., those young people whoturned16in1993,1998and2003,respectively.

The lastchapterof thisreport,Chapter8,gathersanddiscussesthemain findings presented in the previous chapters.While each chapterpresentingourresults,thatis,Chapters3to8,containsseveralsectionstitled“Mainfindings”–oneforeachsub‐chapter–thisconcludingchap‐teraimstodraw,basedonourmultifacetedresults,abroaderpictureforthefourNordiccountriesunderstudy.Inotherwords,inthisconcludingchapterwechoose tooverlook themultitudeofmoredetailed findingsreportedanddiscussedintheseparatechaptersandsub‐chapters.Thisdoesbynomeansimplythatthesedetailsaretrivial.Instead,thiswayofpresenting themain resultsofour study is theproductof adeliberatechoice with overall conclusions and remarks given in Chapter 8, withtheme‐specific conclusions drawn together in the sections titled “Mainfindings”,anddetailedcountry‐specificaswellascross‐countryresultsandconclusionsreportedanddiscussedthroughoutthetext.

1. Performance of young people– an internationalperspective

Themainfocusofthischapterisonexploringwhatinternationallywide‐ly‐used indicators can tell us about educational outcomes, school‐to‐worktransitionsandlabourmarketperformanceofyoungpeopleintheNordic countries. Simultaneously, the information mediated by theseoverwhelmingly static indicators serves as an important benchmarkwhen we, starting in the next chapter, turn to presenting results ob‐tainedbasedonournationallongitudinaldatasets.

1.1 Settingthestage

The youth population has been themost affected by the recent globalcrisis.Thereare severalobvious reasonswhyyoungpeoplehavebeenhitsohard(seee.g.OECD,2009,2010a;Scarpettaetal.,2010).School‐leavers are often the first to encounter difficulties: when the labourmarket deteriorates, employers shed workers and also become muchmoreselectiveintheirhiringofnewstaff.Asthosemakingthetransitionfromschooltoworkcompetewithmoreexperiencedworkersfor(few‐er)jobs,theyoftenfacevirtuallyimpossiblebarrierswhentryingtogetafootholdinthelabourmarket.However,thecrisishasposedchalleng‐esalsotothoseyouthwhowerealreadyinthelabourmarketbuthold‐ing temporary jobs and/or working in business‐cycle sensitive indus‐tries; theyhaveoftenbeenamongthe first to lose their jobs.Andwiththelabourmarkethavingbecomemoreselective,theriskofunemploy‐mentforrecententrantsisnotablyhigheramongthoselackingrelevantskillsorexperienceand,conversely,theyalsofaceparticulardifficultiesinfindinganewjob.

The relatively higher vulnerability of youth to unemployment andinactivitywas,ineffect,awidelyrecognisedprobleminmanyEurope‐an countries even before the onset of the economic crisis. Particularattention was thereby paid to the multiple barriers in finding work


facedby low‐skilledyouth, that is, earlyschool‐leavers. Indeed,manyEuropeaneconomieswerealreadybeforethecrisistacklinganumberof labourmarketproblems– judged toaffectadversely the transitionfromschooltoworkofyouthaswellastheirinitiallabourmarketex‐periences–inordertocopewithunacceptablyhighyouthunemploy‐mentandinactivityrates.

The recent economic crisis is commonly seen to have aggravatedmany of these structural problems and, consequently, the situation ofespecially those youth whose labour market prospects were weak al‐readyprior to thecrisis.TheNordic countriesarenoexception to thispattern, as shown in statistics compiled by notably Eurostat, ILO andOECD. In particular, although there were significant pre‐crisis differ‐encesbothinthelevelandevolutionofyouthunemploymentalsoacrosstheNordiccountries,theyarenonethelesscharacterisedbytwodistinctfeatureswhichtheysharewiththerestofEurope.

First,youthfaceaclearlyhigherriskofunemploymentthanadultsalsoinNorthernEurope.However,whiletheyouth/adultunemploymentratio(for2008)fallswithintheinterval2to3formostOECDcountries,itrang‐esbetween3and4insevencountries, threeofwhicharelocatedinthenorthern part of Europe (Denmark, Finland and Norway), and settlesabove 4 in only two countries – Iceland and Sweden (Scarpetta et al.,2010,pp.11–12).Second,allNordiccountrieshaveexperiencedamarkedincreaseinyouthunemploymentsincetherecessionbegan.

Increasingyouthunemployment rates in combinationwithdiscour‐aging estimates of the likely short‐term evolution of youth unemploy‐ment soon triggered, in individual countries, a multitude of actionsaimedatcushioning theeffectsof thecrisisonyouthwhile, simultane‐ously, pushing forward the long‐term agenda of necessary structuralreformsfor tacklingpre‐crisisyouthunemploymentproblems.Amajorchallengehastherebybeentodeviseshort‐termmeasureswhichdonotconflict with but, preferably, complement and support the long‐termreformagendaofpromotingmoreandbetterjobsforyouthinresponsetoprojecteddemographicchanges.

Theshort‐andlong‐termmeasuresplannedandrealisedinindividu‐alcountrieshavebeensurroundedbyamyriadofactivitiesinitiated,notleast,bytheEuropeanCommissionandtheOECD.ThemanyinitiativesoftheEuropeanCommissionwerebroughttoaheadintheEurope2020frameworklaunchedinMarch2010[COM(2010)2020]asacontinuationoftheLisbonprocess.ThisEUstrategyforsmart,sustainableandinclu‐sivegrowthhasastrongyouthdimension,ashaveseveralofitsaccom‐panying flagship initiatives, most notably “Youth on the Move”


[COM(2010)477] and “An Agenda for New Skills and Jobs”[COM(2010)682],butalsotheHorizon2020financialinstrumentaimedat securing Europe’s global competitiveness. Illustrative examples ofrecentactionssupplementingtheYouthontheMoveeducationandem‐ploymentinitiativeincludeanactionplantoreduceearlyschoolleavingin theEU [COM(2011)18, COM(2011)19, SEC(2011)96], and theYouthOpportunities Initiative [COM(2011)933] launched in December 2011,whichcanbedescribedasasetofmeasures,plannedfor2012and2013,to drive down youth unemployment. The Youth Employment Packageadopted inDecember2012canbeseenasakeymilestoneof thisYOI.Mostnotably, thispackageofCommissionproposals to fightyouthun‐employmentrecommendedthatmemberstatesintroduceaYouthGuar‐antee, launch a consultation of European social partners on a QualityFramework for Traineeships, and announce a European Alliance forApprenticeships.TheEUcountriesendorsed theprincipleof theYouthGuaranteeinApril2013.Untiltheendof2014,theEUprovidedanad‐viceserviceonapprenticeshipandtraineeshipschemesinordertosup‐portitsMemberStatestodevelophighqualityapprenticeshipandtrain‐eeshipprograms.

ComplementarytotheYouthontheMoveflagshipinitiativeoftheEu‐rope2020strategyis,interalia,theEUYouthStrategy:CouncilResolutionon the renewed framework forEuropean cooperation in theyouth field(2010–2018)(OJC311,19.12.2009,pp.1–11).AparticularfeatureofthisstrategyisthatanEUYouthReportistobedrawnupattheendofeachthree‐yearcycletoevaluatetheprogressmadetowardstheoverallobjec‐tivesofthestrategy,ontheonehand,andtoserveasabasisforestablish‐ing a set of priorities for the comingwork cycle, on the other. The firstwork‐cycleEUYouthReport[COM(2012)495final]waspublishedinSep‐tember2012andadoptedas a JointCouncil–CommissionReport inNo‐vember 2012. In relation to the EU Youth Strategy, a dashboard of EUYouthIndicatorswasreleasedin2011[SEC(2011)401].KeyinstrumentstosupporttheEUYouthStrategyare,mostnotably,theLifelongLearningandYouthinActionprogramsandtheErasmusforAllprogram.

AmongthemanyrecentinitiativesoftheOECD,twoinparticularde‐servetobementionedhere.ThefirstistheHigh‐LevelPolicyForumonJobs forYouth:AddressingPolicyChallenges inOECDCountries,whichwas organised jointly with the Norwegian Ministry of Labour in lateSeptember2010.Themainissuesandpolicyrecommendationsonhowto tackle youthunemploymentproblemspresented at this Forum, andlaterpublished ina comprehensive report (OECD,2010b), synthesisedthe findingsof thematicreviewsof Jobs forYouthundertakenoverthe


years2006–2009in16membercountries.WhilethereviewforNorway(OECD,2008c)tookplaceagainstthebackgroundofabuoyanteconomy,the corresponding review for Denmark (2010c) was more concernedwithyouthunemploymentinthecontextoftheongoingeconomiccrisis.These thematic reviews did not cover Finland, Iceland or Sweden,though. This High‐Level Policy Forum was preceded, about one weekearlier,byajointILO–IMFconference–alsoarrangedinOslobutinco‐operationwiththeOfficeofthePrimeMinisterofNorway–onTheChal‐lengesofGrowth,EmploymentandSocialCohesion,onefocusofwhichwas youth unemployment (ILO–IMF, 2010). A second key initiative oftheOECDistheso‐calledOECDActionPlanforYouth,launchedin2013asanintegralpartofOECD’sworkonyouth,andthehigh‐levelmeetingsand comprehensive reports related to the implementation of the plan(http://www.oecd.org/employment/action‐plan‐youth.htm).

1.2 SnapshotofrecentNordiccomparativestudies

TheNordicCouncilofMinistershasalsoinrecentyearsinitiatedseveralreports on how the youth unemployment problem is addressed in theNordiccountries.Especiallythefollowingreportsshouldbementionedinthiscontext.AreporteditedbyMarkussen(2010)focusesondropoutinuppersecondaryeducationintheNordiccountries.Inparticular, foreachNordic country it provides an overviewof the structure of uppersecondaryeducation,looksatresearchandresultsondropouts,givesanoverview of implemented measures to reduce dropout and improvethrough‐putofstudentsand,finally,assessespossibleeffectsoftheim‐plementedmeasures. It concludes by pointing to the need for furtherreformstoreducedropoutandimprovelevelsofuppersecondarycom‐pletion. Another report, by Engberg (2014), continues on this topic inthesensethat itdescribesthereformsandotheractionscarriedout intheNordiccountriesconcerningvocationalandapprenticeshiptraining,and also reflects on the challenges characterising these systems, usingdesk studies and interviews with national experts as analytical tools.Still another report of some relevance in this context describes bothexisting and planned measures, as initiated by relevant governmentdepartments, to prevent youth unemployment in the Nordic countries(RamböllManagement Consulting AB, 2010). The report reviews bothshort‐termmeasuresimplementedduringtheeconomiccrisisandlong‐term measures related to future demographic challenges. This report

http://www.oecd.org/employment/action%E2%80%90plan%E2%80%90youth.htm


also relies on desk studies and interviews with national experts andpublicservantswithinthefieldsofeducationandlabourmarkets.

While this kind of comparative analysis of short‐ and long‐termmeasures can provide important information on what is done andplanned–and in relation towhich target group(s) andwithwhichex‐pectedoutcomes inmind– indifferent countries, they can tell little, ifanything, about the genuine impact of themeasures undertaken. Suchinformation can be obtained only bymeans of carefully designed andperformed evaluation studies. However, the international research fo‐cusingonin‐depthevaluationofvariousmodesofmeasuresdirectedatdisadvantagedand/orunemployedyouthisstillsurprisinglyscant.Moreimportant, theevidenceproducedbysuchevaluationshas,sofar,beenratherdiscouragingwhenitcomestobothimpactandeffectiveness[seee.g. the reviewsbyAsplund (2009) andAsplundandKoistinen (2014)and,especially,thereferencestherein].

AlsoworthmentioninginthiscontextisarecentreportbyHalvorsenetal. (2012)on the transitionbetweenschoolandwork forparticularlyvulnerablegroupsofyouth.Itconcludesthatbetween2%and5%oftheyouthcohortsarealready“outsiders”.Thereportsummarisestheexistingknowledgeonvulnerableyouth,discusseschallengesandpolicymeasuresintheNordiccountries,withparticularattentionpaidtoyouth,andsug‐geststhebuildingofaNordicknowledgebankforgoodpractices.

1.3 TheNordicstorytoldbyinternationalcomparativeindicators

Another source highlighting the youth unemployment problem from across‐country perspective contains indicators developed and compiledmainlybyEurostatandOECD,andpublishedonaregularbasis.Excel‐lentexamplesareEurostat’sstatisticalportraitsofyouthinEuropeandtheOECD’sEducationataGlancereports. Inthissub‐chapter,wedrawon some of these statistical sources to provide an overview of recentdevelopmentsintheNordiccountries,alsoincomparisonwiththerestofEuropeandtheOECDarea.

While offering comprehensive information, these sources also havetheir shortcomings. First, the provided information is basically static innatureinthesensethatitgivesasnapshotofthesituationin–typically–aspecificyear,andcomparesthefindingswithcorrespondinginformationfromapreviousyear(giventhatsuchinformationisavailable).According‐ly,thistypeofyear‐specificinformationhighlightstheaveragesituationat


agivenpointintime,butcansaynothingabouttheunderlyingdynamicssuch as the shifts over time of young people between education, work,unemployment and inactivity. Second, indicators aiming to describe atleast somespecificdynamicaspectof this continuous transitionprocesscan usually be derived only for a limited number of countrieswith theNordiccountriesmostlybeingsurprisinglyweaklyrepresented.

Thisistheprevailingsituationalsoinspecificstudies,ofwhichQuin‐tiniandManfredi(2009)isanillustrativeexample.Theyaddressatopi‐calissue–thedynamicnatureofyouthlabourmarketsituationsandkeypathwaysofyouthleavingsecondaryeducation–but,duetodatalimita‐tions, they can only include Denmark and Finland out of the Nordiccountriesandonlyup totheyear2001.Simultaneously, thishighlightsthelackofextensivecross‐countrycomparativeevidenceonthedynam‐icnatureofthelabourmarketsituationofyouthintheNordiccountriesandthekeypathwaysfollowedbyschool‐leavingyouthhavingacquireddifferentlevelsofeducation–notmerelyasecondarydiplomaasintheQuintiniandManfredi(2009)study. Indeed,this isthekindofanalysisthatwewillundertakeinthesubsequentchaptersofthisreport.

Akeychallengewhenaddressingtheissueofyoungpeople’sunem‐ploymentproblemsandrisksofmarginalisationisthattheyouthpopu‐lationisfarfromhomogenous.School‐leaversareequippedwithdiffer‐ent quantities and qualities of formal education. They also differ in amultitude of other dimensions, including school experiences and earlylifetime experiences, notably family background. Their transition fromschool toworkand initial labourmarketexperiencesrevealconsidera‐blevariationbothin lengthandquality.Thisvariationhasbeenshowntopartlyoriginate indifferences in theschool‐leavers’educationalandsocial background (e.g. Markussen, 2010). However, it has also beenmaintainedtolargelyreflectthefunctioningofthelabourmarket,thatis,the labourmarket institutions in force and the labourmarket policiespursuedinarapidlychangingeconomicandsocialenvironment.Indeed,severalreportshaveshownthattheconditionsforyoungpeopletoes‐tablish themselves in the labour market reveal important differencesalsoacrosstheNordiccountries(seee.g.OlofssonandWadensjö,2007;OlofssonandPanican,2008).

Furthermore,whileearlyunemploymentisknowntoaffecttheyouthto a substantial degree, it is also recognized that the short‐ and long‐term consequences of early unemployment differ markedly acrossyoungindividuals.Aspointedoutintheoutset,agrowingbodyoflitera‐ture–withevidenceemergingalsofortheNordiccountries–indicatesthatspellsofunemploymententailtheriskofcreatingpermanentscars


especially for disadvantaged youth who tend to be particularly ill‐preparedfortoday’slabourmarket.

Our subsequent comparisons, based on available international data,clearly illustrate how important it is to distinguishbetween youngpeo‐ple’sdifferentsituationsandcompositesofactivitiesalsowhenundertak‐ing international comparisons. In particular, since young people oftencombine schoolwithpart‐timework, especially in theNordic countries,theresultsobtainedvarysubstantiallywiththewayinwhichthestatusofyouthismeasured.Letusstartbyfirstreflectingonyouthemployment.

1.3.1 Youthemployment

Our national longitudinal datasets cover three full youth cohorts: allyoung people turning 16 in 1993, 1998 or 2003 (see Chapter 2). Wetherefore startby illustrating–usingOECDstatistics– theoverall em‐ployment situation foryoungpeople fiveyears later, that is,whenouryoungpeopleturned21.Bythisage,mostofthemcouldbeexpectedtohavecompletedanuppersecondarydegree.Whatactuallyhappenedtotheyoungpeoplecontainedinourthreeyouthcohortswillbecomeevi‐dentinthenextchapter.

Table1.1presentsOECDemploymentpopulationratiosfortheNor‐diccountriesforfourselectedyears:in1998,2003and2008,aswellasin the last year of available data, 2013. In all these years, Denmarkshows upwith the highest employment population ratio, both for thevery young and for the 20–24 year‐olds, followed byNorway, FinlandandSweden.However,thetablealsorevealsthatDenmarkexperiencedamarkeddeclineinemploymentpopulationratiosupto2003,thatFin‐landsawaclearimprovementinemploymentpopulationratiosbetween2003 and2008, and that the employment population ratios ofNorwe‐gian males deteriorated in 2003 but recovered by 2008, whereas theemployment population ratios of Swedishmales started increasing al‐readyin1998.Inallfourcountries,therewasaremarkabledropintheemploymentpopulationratiosofyoungpeoplebetween2008and2013.Thisdeclinewasnotablystrongerforyoungmenthanforyoungwomen.


Table 1.1: Employment population ratios (%) for Nordic youth in 1998, 2003, 2008 and 2013

1998 2003 2008 2013 2008–2013

15–19 year‐olds %‐points %

Denmark males 57.9 51.4 59.2 41.1 ‐18.1 ‐30.6

Denmark females 60.2 49.5 59.1 47.1 ‐12.0 ‐20.3

Finland males 25.7 24.7 26.6 17.0 ‐9.6 ‐36.1

Finland females 19.9 23.3 27.5 26.6 ‐0.9 ‐3.3

Norway males 42.2 38.4 42.1 33.8 ‐8.3 ‐19.7

Norway females 42.3 43.0 46.1 39.5 ‐6.6 ‐14.3

Sweden males 21.7 25.8 20.3 17.5 ‐2.8 ‐13.8

Sweden females 25.1 32.2 26.0 24.1 ‐1.9 ‐7.3

20–24 year‐olds

Denmark males 75.6 71.9 76.3 63.4 ‐12.9 ‐16.9

Denmark females 71.2 65.4 71.9 62.6 ‐9.3 ‐12.9

Finland males 60.2 61.8 70.1 54.5 ‐15.6 ‐22.3

Finland females 48.7 54.7 62.3 60.5 ‐1.8 ‐2.9

Norway males 74.3 68.8 74.8 67.4 ‐7.4 ‐9.9

Norway females 65.0 65.2 71.5 67.6 ‐3.9 ‐5.5

Sweden males 58.2 63.1 66.8 59.4 ‐7.4 ‐11.1

Sweden females 52.5 57.3 59.8 58.0 ‐1.8 ‐3.0

Note: The employment population ratio measures the employed as a percentage of the population

in the age group.

Source: OECD Labour force statistics. OECDiLibrary.

Figure1.1extendsthepicturebyshowingemploymentpopulationratiosofyouthaged15–24fortheNordiccountriesincomparisonwithselect‐ed large OECD economies (with the information referring to the 1stquarter of 2012). The employment population ratios displayed in thefigure are measured in two different ways: the vertical axis gives theemploymentpopulationratioforallyoungpeople,whereasthehorizon‐tal axis restricts the employment ratio to non‐students only, as youthemploymentratioscanbecriticisedforbeingblurredbypupilsandstu‐dentsworkingpart‐timewhile inschool.Thissettingreveals thatDen‐mark,IcelandandNorwayhavehighyouthemploymentratios,togetherwithGermany,theUKandUSA,alsowhenaccountismadeforpart‐timeworking students. Finland and Sweden, on the other hand,move fromabove the OECD average to below the OECD average when the youthemployment ratio is adjusted with respect to students working on apart‐timebasis.


Figure1.1:Employmentpopulationratios(%)forallyoungpeopleaged15–24(verticalaxis)andseparatelyfornon‐studentsonly(horizontalaxis),2012(1stquarter)

Note: The employment population ratio measures the employed as a percentage of the population

in the age group.

Source: OECD based on national Labour Force Surveys.

1.3.2 Youthunemployment

Unemployment isamuchmorewidespreadphenomenonamongyouththanamongadultsvirtuallyeverywhere.Youngpeoplearealsothefirsttobehitbyrisingunemployment,andtypicallythelasttobenefitfromrecoveringlabourmarkets.Table1.2showsunemploymentrates,meas‐uredas apercentageof the labour force, for the fourNordic countriesunderstudyintheyears1998,2003,2008and2013.Amongyoungpeo‐pleunderage20,Denmarkstandsoutwithacomparativelylowunem‐ployment rate in 1998,whereas Finlandwas still strugglingwith highpost‐recession youth unemployment. The unemployment rate of theveryyounghasbeenincreasinginallfourcountriesfrom1998to2013,exceptforNorwaywhereithasdeclined,butonlyamongyoungwomen.Theunemploymentratesofyoungpeopleaged20–24arealsohigh,butnot as dramatically high as for those aged 15–19. Yet, in both FinlandandSweden,aboutone‐fifthofthemalelabourforceof20–24year‐oldswasunemployedin2013,accordingtoOECDstatistics.


Table 1.2: Unemployment rates (%) for Nordic youth in 1998, 2003, 2008 and 2013

1998 2003 2008 2013 2008–2013

15–19 year‐olds %‐points %

Denmark males 8.0 9.9 7.9 17.9 10.0 126.6

Denmark females 9.3 10.7 10.9 13.9 3.0 27.5

Finland males 24.6 25.9 23.3 34.1 10.8 46.4

Finland females 33.3 31.5 25.4 27.6 2.2 8.7

Norway males 13.2 17.3 13.2 13.3 0.1 0.8

Norway females 13.7 14.8 10.5 11.3 0.8 7.6

Sweden males 21.1 18.6 32.5 39.3 6.8 20.9

Sweden females 20.6 18.3 31.8 34.5 2.7 8.5

20–24 year‐olds

Denmark males 5.7 8.6 7.0 11.8 4.8 68.6

Denmark females 6.4 8.1 6.6 10.3 3.7 56.1

Finland males 18.0 16.7 11.5 19.2 7.7 67.0

Finland females 20.0 16.3 11.4 11.7 0.3 2.6

Norway males 7.0 10.4 4.9 9.2 4.3 87.8

Norway females 7.1 8.3 4.1 5.6 1.5 36.6

Sweden males 16.2 12.6 13.9 20.1 6.2 44.6

Sweden females 14.3 9.9 14.0 17.0 3.0 21.4

Notes: The unemployment rate measures the number of unemployed as a percentage of the labour

force in the age group. Note also that Sweden undertook, in 2007, a harmonisation of the unem‐

ployment definition towards the one used by ILO. This harmonisation seems to be overlooked in the

OECD statistics, implying that the Swedish figures for 1998 and 2003 are not directly comparable

with those for 2008 and onwards. Based on harmonised data, the unemployment rate of 15–19

year‐old males and females was in 2003 27.1% and 23.8%, respectively. These rates notably exceed

those given above. The discrepancy is much lower for 20–24 year‐olds: an unemployment rate of

14.8% for men and 12.5% for women according to harmonised data published by the Swedish

statistical bureau SCB.

Source: OECD Labour market statistics. OECDiLibrary.

The unemployment rates reported in Table 1.2 are commonly used ininternational comparisons of youthunemployment. They are basedonLabourForceSurvey (LFS)dataandmeasured ina traditionalway:byrelatingthenumberofunemployedtothetotallabourforce(employed+unemployed).ThisILO–LFSmeasureofunemploymentisbasedonques‐tions in the LSF asking the interviewees, inter alia,whether theyhavebeen actively looking for a job during the past four weeks. The LFSmeasureofthetotalnumberofunemployedmay,asaconsequence,alsoincludeyoungpeoplewhoareactivelylookingforajobwhilealsobeingenrolledasfull‐timestudents.

Anotherwayofmeasuringunemploymentistorelyonregisteredun‐employment, which merely comprises those who have registered asunemployedjobseekersatanunemploymentoffice(PES).Theextenttowhichregisteredunemploymentincludesfull‐timestudentsdependsontheeligibilityconditionsofyoungpeopleforregisteringasunemployedjobseekers.Table1.3,whichisreproducedfromHalvorsenetal.(2012),shows the percentage share of youth in each age group registered as


unemployedintheyears2000and2005–2009.Wenotethatthediffer‐encebetweenregisteredunemploymentandLFSunemploymentispar‐ticularly large foryoungpeople,especially forSweden.Amajorreasonfor thisdiscrepancy is thatregisteredunemployment is typically loweramongyoungpeoplenoteligibleforunemploymentbenefits.

Table 1.3: Registered unemployment rates (%) for Nordic youth, 2000 and 2005–2009

Age 2000 2005 2006 2007 2008 2009

Denmark

16–19 1.0 0.8 0.7 0.7 1.0

20–24 4.7 3.7 2.7 2.5 4.7

16–64 5.3 4.2 2.9 2.1 3.6

Finland

16–19 3.2 2.5 2.4 2.4 2.7 3.5

20–24 9.4 9.0 8.6 8.1 8.4 10.9

Iceland

16–19 0.7 0.9 0.5 0.4 0.9 3.6

20–24 1.1 2.4 1.4 1.0 2.1 9.9

16–70 1.1 1.7 1.1 0.5 1.4 6.8

Norway

16–19 1.2 1.2 1.0 0.7 0.7 1.0

20–24 3.3 4.5 3.2 2.2 2.0 3.5

16–74 2.7 3.5 2.6 1.9 1.7 2.7

Sweden

16–19 1.5 2.2 1.8 1.6 1.8 2.9

20–24 5.0 5.7 5.9 5.0 4.0 6.0

16–64 4.1 4.2 3.6 2.9 2.8 4.0

Notes: The unemployment rate measures the number of registered unemployed as a percentage of

the population in the age group. Information for the year 2000 is missing for Denmark while infor‐

mation on all age groups combined is not available for Finland.

Source: Halvorsen et al. (2012).

Alsotheinformationonunemploymentcontainedinournationallongi‐tudinal datasets used in the subsequent chapters refers to registeredunemployment.However,itdiffersfromtheinformationunderlyingtheregisteredunemploymentreportedinTable1.3,asourdatasetsarere‐codedtoidentifyallyoungpeopleenrolledineducationasfull‐timestu‐dentsalsowhentheyappearasemployedorunemployedintheoriginaldata(seefurtherChapter2).Indeed,asinthecaseofyouthemployment,thewayfull‐timestudentsaretreatedmakesabigdifferencealsowhencalculatingyouthunemploymentrates.WeillustratethisbygoingbacktotheLFSdatatoshowwhathappenstotherankingoftheNordiccoun‐triesdependingontheunemploymentmeasureused.

Wetherebystartbyshowing,inFigure1.2,thenumberofstudentsasapercentageshareof thepopulation in theagegroup. In theLFSdata,more than 80%of those aged 16–19 report studying to be theirmainactivity.Forthoseaged20–24,thisshareisnotablylower,rangingfrom


40 to almost 60% with Denmark having the highest and Sweden thelowestshareofyoungpeoplereportingstudyingas theirmainactivity.Inviewoftheselargesharesofstudentsinbothyouthpopulations,itisobviousthattheresultsobtaineddependcriticallyonthewaystudentsaretreatedinthecalculations.

Figure1.2:Studentsasashare(%)ofthepopulationintheagegroup,forfourNordiccountries

Note: Students are defined as young people who report studying to be their main activity in the LFS.

The drops in the series in 2005 for Norway and Sweden are most likely due to data issues. Cf. the

notes in Table 1.2.

Source: Own calculations based on LFS quarterly data.

Letusnowreturntounemployment.Figure1.3providesinformationonyouthunemploymentfromthe1stquarterof2012fortheNordiccoun‐triesaswellasforaselectednumberofnon‐Nordiccountries.Thehori‐zontalaxismeasurestheunemploymentrate,thatis,thenumberofun‐employedasapercentageofthelabourforce.Swedencomesoutwithahigher youth unemployment rate than the average for Euro countries(EURO).Sweden,togetherwithFinland,alsorankshigherthanboththeUKandtheUSA.

Theverticalaxis,inturn,measuresyouthunemploymentbymeansofthe unemployment ratio, that is, the number of unemployed as a per‐centage of the whole youth population. While 23% of the Europeanyouthlabourforceisunemployed,theseunemployedyoungpeoplecon‐stitute less than 10% of the youth population. In terms of the unem‐


ployment ratio, however, all Nordic countries except Norway scorehigherthantheaverageforEurocountries.InbothIcelandandSweden,youthunemploymentis, infact,higherthaninItalywhenmeasuredbymeansoftheunemploymentratio.

Figure1.3:Youthunemploymentrates(%)andunemploymentratios(%),theNordiccountriesandselectednon‐Nordiccountries,2012(1stquarter)

Notes: Unemployment rate = unemployed 15–24 year‐olds in relation to the labour force of the age

group. Unemployment ratio = unemployed 15–24 year‐olds in relation to the whole population of

the age group.

Source: OECD as reproduced from Albæk et al. (2014).

However,manyoftheyoungpeoplerecordedasunemployedintheLFSareactuallyattendingschooland,moreover,typicallyonafull‐timeba‐sis.Figure1.4 showswhathappenswhenweremove from thepoolofyoungunemployedthosewhoreportstudyingastheirmainactivity.Thevertical axisofFigure1.4nowshowsunemployedyoungpersonswhoarenotattendingschool.FortheEuroareaasawhole,theyouthunem‐ploymentratiodropsfrom9.3%to7.2%oftheyouthpopulation.FortheNordic countries, the change is even larger. After this correction, allNordic countries rank among thosewith the lowest level of youth un‐employment(amongthenon‐students).

Thecountrieswiththelargestdropbelowthe45‐degreelineaddedtoFigure1.4aretheoneswiththelargestproportionofunemployedyouthwhoarealsostudents.Thepatterndisplayedinthefigurethusarisesfromthefactthattheunemployedyoungpersonswhoarenotatthesametimeattending schoolmake up a smaller proportion in the Nordic countries


comparedtotheothercountriesinthefigure.InallNordiccountries,theproportionofunemployedyoungpeoplewhoarenotalsoinschoolislessthanone‐half,andassmallasone‐thirdinSweden.

The huge difference between youth unemployment ratios includingandexcludingunemployedstudents isalsoevident in thenext twofig‐ureswhich,moreover,separate16–19year‐oldsfrom20–24year‐olds.AcomparisonofFigure1.5awithFigure1.5brevealsastrikingly largedrop in the unemployment ratio for the very young (16–19 year‐olds)whenleavingoutstudentsrecordedasbeingunemployed.

Figure1.4:Youthunemploymentratios(%)withandwithoutstudents,theNordiccountriesandselectednon‐Nordiccountries,2012(1stquarter)

Notes: Unemployment ratio = unemployed 15–24 year‐olds in relation to the whole population of

the age group. Unemployment ratio, non‐students = unemployed 15–24 year‐olds with studying not

being their main activity, in relation to the whole population of the age group. The red line shows

the 45 degree angle.

Source: OECD, as reproduced from Albæk et al. (2014).


Figure1.5a:Youthunemploymentratios(%)forfourNordiccountries,1995–2012

Notes: Unemployment ratio = unemployed in relation to the whole population of the age group. Cf.

the notes in Table 1.2 concerning the unemployment information on Sweden prior to 2005.


Figure1.5b:Youthunemploymentratios(%),excludingstudents,forfourNordiccountries,1995–2012

Notes: Unemployment ratio = unemployed in relation to the whole population of the age group.

Students are defined by self‐reported main activity. Cf. the notes in Table 1.2 concerning the unem‐

ployment information on Sweden prior to 2005.



1.3.3 NEETrates

NEETsrefertoyoungpeoplewhoareNotinEmployment,EducationorTraining. Figure 1.6 gives NEET rates for the last quarter of 2012 for15–24 year‐olds in OECD countries, measured as a percentage of thetotalpopulationintheagegroup.TheNordiccountriesarelocatedrela‐tivelyhighuponthisrankingscale,implyingthattheyarecharacterisedbylowNEETrates.For2012,theshareofyoungpeopleinNEETactivi‐tieswasestimatedtobe5.9%forDenmark,6.7%forNorway,7.2%forSwedenand8.4%forFinland.

Allinall,theinformationprovidedsofarshowsthatthelabourmar‐ketisquiteaccessibleforyoungpeopleintheNordiccountries.Inpar‐ticular, employment rates are relatively high among thosewhodo notattend school and, conversely, unemployment rates are relatively low.Thedescriptiveevidencepresentedabovealso implies that the attach‐menttothelabourmarketisrelativelystrongalsoamongyoungpeopleattending school. This follows from the fact that large sharesof youngpeoplerecordedtobeemployedorunemployedare,actually,pupilsandstudentswith studying as theirmainactivity. Simultaneously, they areanintegralpartofthelabourforce.

Figure1.6:NEETrates(%)for15–24year‐oldsinOECDcountries,assplitbyunemploymentandinactivity,2012(4thquarter)

Notes: NEET rate = young people not in employment, education or training as a percentage of the

population in the age group.

Source: OECD Society at a Glance 2014.


1.3.4 Uppersecondaryeducation–completion,non‐completionanddropout

Finally,wetakeacloserlookatschoolcompletion,non‐completionanddropoutwith the focus being on upper secondary education. The pro‐portion of 30–34 year‐olds holding an upper secondary degree is notparticularlyhighinDenmarkorNorway,asisevidentinFigure1.7.Fin‐land and Sweden, on the other hand, rank quite highwithmore than90%ofthe30–34year‐oldsholdinganuppersecondarydegreein2012.

Ifweexploretheaverageageofuppersecondarygraduation(Figure1.8),Swedencomesoutwiththe lowestaverageageamongtheNordiccountries, or about 18 years‐of‐age. In the otherNordic countries, theaverage graduation age ismuchhigher forboth general programsandespecially for vocational programs. Indeed, the average age of uppersecondarygraduationfromvocationalprogramsis28inbothDenmarkandNorway.ForFinland,itisreportedtobeevenhigher.

Figure1.7:Attainment(%)ofanuppersecondarydegreeamong30–34year‐oldsinOECDcountries,2012

Source: OECD Education at a Glance 2014.


Figure1.8:AverageageofuppersecondarygraduationinOECDcountries,2012

Source: OECD Education at a Glance 2014, Chart A2.2.

Therearenumerouswaystomeasuredropoutornon‐completionratesfromuppersecondaryeducation.Figure1.9illustratestheshareofstu‐dentswho successfully completes after the theoretical duration of theuppersecondaryprogram,ortwoyearsafterthetheoreticaldurationoftheprogram.Thecountriesaresortedaccordingtothesuccessfulcom‐pletionofgirlsinuppersecondaryprograms.AllNordiccountriesrankbelowtheOECDaverage,withSwedenandFinlanddoingslightlybetterthanDenmarkandNorway.


Figure1.9:Uppersecondarycompletionrates(%)inOECDcountries,bygender

Source: Education at a Glance 2014. Chart A2.5.

Table1.4, finally,presentsalternativemeasuresofcompletionrates,asreportedbyEurostatandOECD.WhileFigure1.9gives thecompletionrates among those who attend upper secondary programs, Table 1.4presents completion rates as percentage shares related to the wholeyouthpopulation.

Table 1.4: Completion, early leaving and dropout rates (%) for the Nordic countries

Denmark Finland Iceland Norway Sweden

Upper secondary graduation rates

< 25 year‐olds 2011 79.4 85.0 70.4 77.7 75.4

≥ 25 year‐olds 2011 10.2 11.0 17.4 11.8 0

Total 89.6 96.0 87.8 89.5 75.4

Early school leavers 2007 12.9 9.1 23.2 18.4 8.0

(Eurostat) 2012 9.1 8.9 20.1 14.8 7.5

School dropouts 2009 14.2 9.7 55.2 20.3 7.4

(OECD scoreboard for youth)

Notes: The first lines show expected graduation rates before and after the age of 25 as reported in

the OECD publication Education at a Glance. “Early school leavers” (Eurostat) refer to persons aged

18–24 fulfilling the following two conditions: first, the highest level of education or training attained

is ISCED 0, 1, 2 or 3c short; second, respondents declared not having received any education or

training in the four weeks preceding the survey (numerator). The denominator consists of the total

population of the same age group, excluding no answers to the questions “highest level of educa‐

tion or training attained” and “participation in education and training”. Both the numerators and

the denominators come from the EU LFS (Eurostat). The OECD Scoreboard for youth: share of youth

not in education and without an ISCED 3 degree.


The information contained in Table 1.4 clearly shows that the picturelooksquitedifferentdependingonboththemeasureusedandthetimeofmeasurement.Again,thereasonforthisisthatyouthcareertrajecto‐ries are very heterogeneous, involving bothmultiple states at a givenpoint in time (e.g. combined schooling and employment) and frequenttransitions back and forth between different states (e.g. education–employment–unemployment–education). As we will show in the nextchapter,non‐completionratesdropconsiderablyovertimewithineachcohort,anddonotsettleatacertainleveluntilwellintothethirties.

Anyanalysisofyoungpeople’scareersneedstohandlethisheteroge‐neityinsensibleways.Indeed,onemajorpurposeofthepresentreportisto deepen our understanding of the different trajectories followed byyouthuptoage20,tocomparethepatternsoftrajectoriesacrossthefourNordiccountriesunderstudy,andtolinkthesepatternstolabourmarketoutcomesinadulthood.Simultaneously,manyoftheresultsandpatternsreportedinthesubsequentchapterstouchupontheoverallpicturemedi‐atedbytheinternationalandcross‐Nordiccomparisonspresentedinthischapter.Inparticular,severalofthedistinctcharacteristicsoftheNordiccountries,when compared to non‐Nordic countries,will showup in thesubsequent chapters. This holds true also for many of the pronounceddifferencesbetweentheNordiccountriespointedoutabove.Inouranaly‐sis,weaimatpositioningtheminabroader,moredynamiccontext,withaviewofimprovingourknowledgeontheperformanceofyoungpeopleinschoolandinthelabourmarket.

2. General description of post‐compulsory‐school activities

This chapter introduces thenational datasetsunderlying the empiricalevidencereportedinthisvolume.Italsoprovidesageneraldescriptionofthemainpost‐compulsory‐schoolactivitiesinwhichtheyoungpeoplecoveredbyourdatahavebeenengagedin,withtheemphasisbeingontheirsituationup toage20. Inotherwords, in thischapterwegiveanoverallpictureofyoungpeople’sactivitiesovera timeperiodwhich isoftenarguedtobethemostcriticalintermsoftheirfuturelabourmar‐ketoutcomes.

Additionally,we introduceourpreferreddefinitionofyoungpeoplelackinganuppersecondarycertificate.Moreprecisely,weprefertocallthese young people “non‐completers”, as compared to “completers”,implying that they only have their compulsory‐school exam still fiveyears after having left primary education. As shown in the previouschapter,bothEurostatandOECDlabelsuchyoungpeopleinadifferentway–earlyschoolleaversanddropouts,respectively–andalsodefinethem slightly differently. A major reason for using the term “non‐completers” is that, aswill be highlighted below, large shares of themspend,ineffect,aconsiderableamountoftimeasfull‐timestudentsbutwithout completing an upper secondary degree. Calling them earlyschool leaversorschooldropoutswould, therefore,mediateamislead‐ingpictureoftheiractualsituation.This,inturn,givesusalsoreasontocontrast our non‐completers’ results to the early school leaving anddropoutstatistics reportedbyEurostatandOECD for theNordiccoun‐tries,informationthatwasbrieflyreviewedinChapter1.

2.1 Thenationaldatasetsused

Thissub‐chapterprovidesageneraloutlineofthenationaldatasetsusedin our subsequent analyses of young people in four Nordic countries.MoredetailsonourdataaregiveninAppendix1.


2.1.1 Longitudinaldataforthreecohorts

Thenationaldatasetsunderlyingour resultsare longitudinal innatureand compiled from large administrative registers maintained by thestatisticalbureau intherespectivecountry. Inparticular,eachnationaldatasetcoversthreefullcohortsof16‐year‐olds:thosewhoturned16in1993,in1998andin2003,respectively.Thereasonforchoosingage16as our point of departure is that it represents the typical compulsory‐school‐leavingageintheNordiccountries.Sinceweareabletocoverallyoungpeopleinthesethreecohorts,weneednotworryaboutpotentialselection bias problems due to sampling. Apart from allowing overallcomparisons across cohorts, these three youth cohortsmay also high‐light the role of the surrounding economy, as they have faced highlydifferentbusinesscycleswhenleavingcompulsoryschool.Forinstance,those having left compulsory school in 1993,which represents a deepeconomicrecessionyearinallfourNordiccountriesunderstudy,couldbeexpected tohaveencounteredmuchhigheremploymentbarriersascomparedtothosehavingleftcompulsoryschoolin1998,representingastrongeconomicupturnyear.

Thesethreecohortsof16‐year‐oldsarefollowedonanannualbasisup to the year 2008.Hence, all our results refer to pre‐crisis years. Inpractice,thefollowing‐upperiodisthusofdifferentlengthforthethreecohorts. While the 1993 cohort of 16‐year‐olds can be followed for atotaloffifteenyears,uptoage31,the1998cohortof16‐year‐oldscanbetracedfortenyears,uptoage26,butthe2003cohortof16‐year‐oldsforonlyfiveyears,uptoage21.Thismeansthatwehaveinformationonallthreecohortsuptoage21,ontwocohorts(1993and1998)forages22to26andononecohort(1993)forages27to31.Thisfactshouldbekeptinmindinthosesituationswherewemergetheinformationonallthreecohortsandpresentresultsalsoforagepointsbeyondage21.

2.1.2 Fivemainactivities

When following these 16‐year‐olds on their way in post‐compulsoryeducation and to the labourmarket,wedistinguishbetween fivemainactivities: full‐time student, employed, unemployed, disability benefi‐ciary (“pensioner”) and “other”. Allocating our young people acrossthese fiveactivities isnotstraightforward, though,as the fiveactivitiesarenotnecessarilymutuallyexclusive.Ayoungpersonmaywellswitch,evenrepeatedly,betweenactivitiesduringayear.Inthisrespect,werelyontheirstatusatthetimeofobservationinthedata;say,theyoungper‐son’smainactivityasregisteredforthelastweekoftheyear.However,


eventhentheyoungpersonmightbeengagedinseveralactivitiesatthesametime,e.g.full‐timestudyingandpart‐timeemployment.

Wehavetriedtoaddressthechallengesrelatedtotheallocationofouryoungpeopleacross the fiveactivitycategories in the followingway.Asourpointofdeparturewehavechosenthelabour‐market‐statusindicatorreadilyavailableintheFinnishadministrativeregisters.ThisindicatorisconstructedbyStatisticsFinlandinlinewiththerecommendationsoftheInternational Labour Organization (ILO). In brief, this means that theyoungpersonneedstohaveanemploymentcontractinforcetobecodedas employed; to be registered at public employment services (PES) forbeingcodedasunemployed;toberegisteredasadisabilitybeneficiaryforbeing coded as a “pensioner”; and to be enrolled in education forbeingcodedasastudent.Allyoungpeoplenotappearing inanyofthese largeadministrative registers fall into the dumping category of “other”; i.e.,theiractivityisunknown.Sincetheofficialdatasourcesusedfortheotherthreecountrieslackasimilarindicator,theyoungpeoplecoveredbytheDanish,NorwegianandSwedishdatasetshavebeenallocatedacross thefiveactivitiesinawaythatfollowsascloselyaspossiblethecodingrulesfortheFinnishlabour‐market‐statusindicator.

The ILO hierarchy of these five activities is: employed, unemployed,pensioner,student,other.Hence,alsofull‐timestudentsarecodedasem‐ployed,iftheyhappentohaveanemploymentcontractinforceatthetimeofobservation.Sincethiswayofcodingfull‐timestudentswasfeltashigh‐ly unsatisfactory for our purposes (cf. the discussion in Chapter1), allyoung people studying on a full‐timebasiswere recoded as students incasetheyappearedinsomeotheractivityintheoriginaldata.Thisrecod‐ing was based on administrative school register data. Hence, all youngpeopleenrolledinaneducationalinstitutionatthetimeofobservationareinourdatasetsallocatedintotheactivitylabelled“studying”or“student”.Acomparisonofschool‐to‐work‐transitionpatternsovertheages16to20basedonrecodedandnon‐recodedstudent informationprovidesstrongsupportforourrecodingexerciseintermsofmorerealisticearlytrajecto‐riesofyoungpeople(seee.g.AsplundandVanhala,2013,forFinland,andBarthandvonSimson,2012,forNorway).


Box2.1Mainactivities

Acarefulallocationofyoungpeopleacrossareasonablenumberofrele‐vant activities can be expected to produce important information onpost‐compulsory‐school trajectories,aswellasoncrucialchangesovertime(acrosscohorts) inearlyschool‐to‐worktransitionpatterns.How‐ever, thechangesinactivitiespossiblyobservedovertimearenotnec‐essarily merely due to changing behaviours or preferences of youngpeople.Apartfromchangesinthesurroundingeconomy,theseshiftsinactivitypatternsmayalsobedrivenbyreformsoftheinstitutionalset‐ting.Forinstance,adeclineintheunemployedshareofyoungpeopleofa particular age may be explained by higher preferences for workand/orimprovedemploymentopportunities,butmayalsoreflecttight‐enedconditionsforyoungpeopleofthisagewhenitcomestotheirpos‐sibilitiestoregisterasunemployedand/ortheireligibilityforreceivingunemploymentbenefits.Likewise,adeclineintheshareofyoungpeopleof a certain age on disability benefits is not necessarily the result ofyoungpeoplehavingbecomehealthierbutmore likely theoutcomeoffundamentalchangesinthedisabilitybenefitsystem.Wheneverrelevantinthesubsequentanalyses,wewillbringforwardmajorreformsintheinstitutional settingsof the fourNordic countriesunder study that arelikelytohavecontributedtodistinctchangesobservedinyoungpeople’searlyschool‐to‐worktrajectoriesandlabourmarketoutcomes.

Thefollowingmainactivitiesareidentifiedbasedonournationaldatasets:stud‐

ying,employed,unemployed,disabilitybeneficiaryandaresidualgrouplabelled

“other”,whichmainly consists of young people not found in any of the broad

administrative registers from which our national datasets are compiled. If a

youngpersonappearsinseveralregistersatthesametime,thefollowingpriori‐

tyisgiven:activitiesinthelabourforce(employed/unemployed)overrideactiv‐

ities outside the labour force (disability beneficiary and “other”). There is one

importantexceptiontothisrule, though:thoseyoungpeopleregisteredasfull‐

timestudentsarealwaystreatedinourdatasetsasstudents,evenwhentheyare

intheemploymentortheunemploymentregisterwhilestudying.


2.2 Mainactivitiesofyoungpeople–theoverallpattern

We start our general description of young people’s post‐compulsory‐schoolactivitiesbyshowing theoveralldistributionofour threecoun‐try‐specific youth cohorts across the five main activity categories de‐fined above: full‐time studying, employment, unemployment, disabilitybenefits(“pensioner”)and“other”(outsideeducation, labour forceanddisabilityarrangements).Thisisdoneseparatelyforeachagepointbe‐tween16and20/21andthenfor twomoreagepointsslightly later inlife,atage26andage31.Whileeachcountryfigureisbasedonpooledinformation for all three youth cohorts, the table accompanying eachfigure displays the corresponding activity shares separately by genderandbycohortatoneparticularpointintime,viz.whenouryoungpeopleturned21.

2.2.1 Denmark

Thefirstfigureanditscomplementingtable(Figure2.1aandTable2.1a)highlightthesituationforDenmark.Thefigurerevealsthattheshareofcompulsory‐school‐leaving youth continuing directly in education isextremely high (about 90%) among 16‐year‐old Danes, but declinesthereafter: at a rather slow pace up to age 18 butmuchmore rapidlyoverthenext twoyears,uptoage20.Byage21, theshareof full‐timestudentshasshrunktoabout44%.Inparallel,theshareofyoungpeopleinemploymenthasincreasedtoapproximatelythesamelevel.However,these average shares based on pooled cohort data conceal substantialvariationacrosscohorts,asshowninTable2.1a.Inparticular,theshareof21‐year‐oldsengagedinfull‐timestudieshasgrownremarkably,fromclose to 40% for the 1993 cohort to almost 48% for the 2003 cohort.Simultaneously, the shareof21‐year‐olds inemployment revealsade‐cliningtrendacrosscohorts.


Figure2.1a:Denmark:Averagedistribution(%‐share)ofyoungpeopleacrossmainactivitiesuptoage31,basedonpooledinformationonallthreeyouthcohorts

Note: For definitions of the five main activities, see sub‐chapter 2.1.

Table 2.1a: Denmark: Average distribution (%‐share) of young people across main activities at age 21, based on pooled information on all three youth cohorts (all and by gender) and separately by cohort

Activity All three cohorts pooled By cohort of 16‐year‐olds

All Males Females 1993 1998 2003

Full‐time student 43.7 40.6 47.1 39.5 44.2 47.5

Employed 43.2 46.5 39.7 47.5 41.5 40.5

Unemployed 3.9 4.0 3.8 4.8 5.6 1.4

Pensioner (disability benefits) 0.7 0.8 0.6 0.5 0.7 0.8

Other (inactivity) 8.5 8.2 8.9 7.7 8.1 9.8

Total 100.0 100.0 100.0 100.0 100.0 100.0

%‐share in the pooled dataset 100.0 51.7 48.3 34.4 31.0 34.6


ThesmoothtransitionofDanishyouthfrompost‐compulsoryeducationinto working life displayed in Figure 2.1a is a distinct feature of thecountry’suppersecondaryeducationsystem:almostallstudentsinini‐tial vocational education and training (VET) are in some formof com‐bined school‐ and work‐based learning (see Box 2.2). Simultaneouslythereisbynowstrongevidenceshowingthatgraduatesfromsuchpro‐grams have better employment prospects than graduates from more


“school‐based”upper secondary education systems, especially in timesofeconomicdownturns(e.g.Cedefop,2012).

Theshareoftheunemployedstartstogrowafterage17butremainslow: less than 4% still at age 21. Againwe see considerable variationacross cohorts, though: the unemployment share among 21‐year‐oldsincreasedto5.6%inthe1998cohort,butdroppedto1.4%inthe2003cohort.Theunemploymentshareinthetwooldercohortsiswellinlinewith the LFS shares shown in Figure 1.5a of Chapter 1,while it is notentirelyclearwhythecorrespondingshareforthe2003cohortislowerthanfortheothertwocohorts.

The share of young people outside both education and the labourforceisabout7%amongthe16‐year‐olds,andincreasesonlyslightlyup to age 21 (some 9%),with those on disability arrangements con‐tributingonlymarginallytothisshare.However,alsoforthesegroupsofyoungpeoplewecanobserveclear‐cuttrendsovercohorts:boththeshare of young people on disability benefits and the share of thosebelonging to the dumping category of “other” show a steady upwardtrendacrosscohorts.

Thedistributionof21‐year‐oldmenandwomenacrossthefiveactiv‐itycategoriespointstoastrongpreferenceamongyoungwomentocon‐tinue in full‐time education, and among young men to start working(Table 2.1a). Amain reason for this gender difference is that the VETsystemattractsmoreyoungmenthanwomen,andthatmanystudentsdelay their entry into the VET systemuntil they are in their twenties.When it comes to NEET activities (unemployment, disability arrange‐ments and other inactivity) there are no conspicuous differences be‐tweenthemaleandfemaledistributions.

Theshareofyoungpeopleinemploymentcontinuestogrowrapidlywhenmoving beyond the age of 21 (Figure 2.1a). By age 26 it has in‐creasedto60%andbyage31 to81%,mainlyat theexpenseofenrol‐ment in full‐timestudies: theshareofstudents isdownat10%amongthe31‐year‐olds.Theshareof theunemployed isconspicuously lowatage31,alsowhencomparedtothesituationatyoungerages.Theshareof young people on disability benefits increases slightly after age 21while the share of young people in other inactivity is declining. Theseopposite trendsseem,however, tobemainlyexplainedbyashift fromotherinactivityintodisability;takentogether,theshareofyoungpeopleoutsidebotheducationandthe labour force isapproximatelythesameatage26andage31(about7%).


Box2.2Denmark–abriefoutlineoftherelevantinstitutionalframework

Uppersecondaryschoolsystem

EducationinDenmarkiscompulsoryfromtheageof6andlastsfor9yearsupto

the9thgrade.Theprimaryschoolsystemcomprisesbothavoluntary10thgrade

andavoluntarypre‐schoolyear(beginningattheageof5).TheDanishmunici‐

palitiesadministertheprimaryschoolsystem,whichisregulatedbytheMinistry

ofEducation.

Aftercompletingcompulsoryschoolyoungpersonscanapplyforuppersec‐

ondaryeducation.TherearetwomaintracksintheDanishsecondaryeducation

system:anacademictrackandavocationaltrack.Themainacademictracklasts

threeyears and takesplace in the “Gymnasium”.Mostapplicantsare admitted

but theschool canrejectanapplicant, if it isunlikely that theyoungperson is

abletopasstheexams.AnexamfromtheGymnasiumisnormallyaprerequisite

for admission to universities. The vocational educational track (VET) begins

normallywithabasiccourseofadurationbetween20to25weeks ineithera

technicalcollegeoracommercialcollege.Afterthebasiccoursefollowsthemain

course, which is a “dual” educational program: the main part of the training

takesplaceincompanies,butduringsometimeperiodstheparticipantsattend

courses in colleges. The main course typically takes 3–3½ years, but can be

shorterorlongerdependingontheprogram(from1½upto5years).Thereare

about110differentVETprograms.

ThereisfreeadmissiontothebasicVETprogram,butparticipationinthe

maincourseatacompanydemandsthattheparticipantfindsemploymentata

company.Employmentand training incompanies is regulatedbyapprentice‐

shipcontractsbetweenthecompanyandtheapprentice.Theshareinayouth

cohort that obtained a training contract with an employer was about 45%

during the years under scrutiny in this report (Albæk, 2009). This share is

much larger than inmost European countrieswith the exception of Austria,

GermanyandSwitzerland.

AparticularfeatureoftheDanishVETsystemisthehighageoftheappren‐

tices.According toFigure1.8ofChapter1, theaverageageofgraduation from

the Danish VET system is 28, whereas students in general programs typically

graduatewhentheyare19yearsold.Theageofapprenticeshasincreasedover

alongtimeperiod(Albaek,2005).Lackoftrainingslotsincompaniesisamuch

debated policy issue and various employment subsidies have been in effect

(Albæk,2012).


Box2.2continued

Measures directed towards young people outside education and the

labourmarket

Unemployment benefits: A prerequisite to receive unemployment benefits in

Denmark ismembershipofanunemployment insurance fund.These insurance

fundsareprivateorganisationsinprinciple,butthedifferentprovisionsregulat‐

ingtheiractivitiesareregulatedbythestateandthestatealsoprovidesmostof

thefundingofunemploymentbenefits.Aconditionforreceivingunemployment

benefitswas(until2010)employmentforhalfayearduringthelastthreeyears.

Also eligible forunemploymentbenefits arepersonswhohave finishedhigher

educationoraneducationintheVETsystem(ofatleast18months).Themaxi‐

mumamountofbenefitsis90%ofthepreviouswagebutthereisalsoageneral

maximum, which most unemployed workers receive, except for workers who

receivedlowwagesbeforetheunemploymentspell.

Socialassistance:Whenyoungpeopleturn18,theyareentitledtosocialas‐

sistance, if theyhavenoothermeansof income(parentsaresupposed tosup‐

porttheirchildreneconomicallyuntiltheageof18).Noothermeansincludethat

theyhavenotbeenabletofindajob,thattheyhavenosavingsandthattheydo

not have a spouse, who can support them. The amount of social assistance is

means tested,which for example implies that youngpersonswith children re‐

ceivehighersocialassistance thanyoungpeoplewithoutchildren.Socialassis‐

tance is administeredby themunicipalities. If themunicipality assesses that a

youngpersonisabletowork,thenthepersonhastoregisterasanunemployed

jobseeker.Thisimplies,inturn,thatthepersonissupposedtotakeajoboffered

throughthelabourmarketauthorities.

Active labourmarket policy: There are various programs for young people

whodonotworkandwhoarenotenrolledineducation.Theprogramsinclude

both training programs and programs that aim at giving young people work

experience.Enrolmentintheseprogramsgoesunderthename“activation”.Over

theyears, several reformshavebeenenacted to induceyoungpeopleeither to

participateineducationortakeajob.Amajorreformtookplacein1994,accord‐

ing to which young people under 25 on social assistance have the “right and

duty”toparticipate ineducationofat least18monthsofduration.Areformin

2003extendedthis“rightandduty”toyoungpeopleunder25onunemployment

benefitsprovidedtheyhadbeenunemployedformorethansixmonths.Accord‐

ingtoanotherreform,whichalsotookplacein2003,youngpeopleunder25can,

atamaximum,receivesocialassistancecorrespondingtotheamountthatyoung

peopleparticipatingineducationreceive(theDanishsystemofincomesupport

topersonsparticipatingineducation–Statensuddannelsesstøtte(SU)–isrela‐

tivelygenerous).


Box2.2continued

Disabilitybenefits:Tobeeligiblefordisabilitypension,thepersonhastohave

aphysicalorpsychicalillnessthatreduceshis/herworkabilitypermanently.A

disabilitypensioncanbegrantedfromage18andstopsatretirementage.The

right to receive adisabilitypension is, as a general rule, dependentonDanish

citizenshipandresidenceinDenmark.Eligibilityforafullpensionrequiresthat

thepensionerhasbeenaDanishresidentatleast4/5oftheyearsafterthepen‐

sionerturned15tothetimewhenthepensionisgranted.

There isonlyonedisabilitypensionscheme inDenmark,which is financed

outofgeneralpublicrevenue.Norequirementofpreviousworkexperiencehas

tobefulfilledinordertoobtainadisabilitypensionandneitheristhelevelofthe

pension related to previouswork incomewhich is, in effect, also the case for

publicold‐agepensions.Thisisincontrasttomanyothercountries,wheresome

amount ofwork experience is a prerequisite for receiving a disability pension

and where the level of the pension is related to previous earnings. Disability

pensionsaregrantedbythemunicipalities,whichalsodiffersfrompracticesin

most other countries. Most cases start with an application from persons who

wanttoobtainadisabilitypension,butmunicipalitiescanalsoinitiatecasesfor

personswhoresideinthemunicipality.Thedecisionofthemunicipalitycanbe

appealedtoanappealagency(ankestyrelsen).Asubstantialrevisionofthedisa‐

bility pension system was enacted in 2013. A main provision is that persons

belowtheageof40,asthepointofdeparture,cannotobtaindisabilitypensions.

Inlinewiththe2003reformoftheSwedishdisabilitysystemforyoungpeople,

the Danish reform aims at improving the rehabilitation of young people with

disabilities and at providing them, in the first place,with a so‐called resource

plan(ressourceforløb)foralimitedtimeperiod(uptofiveyears).

Priorto2003,disabilitypensionerswereclassifiedincategoriesaccordingto

theirresidualworkabilityandthelevelofthepensionwasdependentoncatego‐

rization (highest, middle, enhanced ordinary and ordinary disability pension).

Startingin2003thecategorizationwasabandonedfornewentrantstothedisa‐

bilitypensionsystemandonlyonetypeofdisabilitypensionisgranted.Persons

ontheoldschemecanapplytoenterthenewscheme.

A special trait of the Danish system is the so‐called flexible‐job scheme,

whichisalsotargetedtopersonswithpermanentlyreducedworkcapacity.The

schemeconsistsofawagesubsidythatamountstoeither1/2or2/3ofthesala‐

ry.Thewagesubsidyispaidtoemployersthathirethepersonsparticipatingin

theflexible‐jobscheme.Personsinthisschemearenotincludedaspensionersin

ouranalysis.


2.2.2 Finland

NextweturntothecorrespondinginformationforFinland(Figure2.1bandTable2.1b).Alargemajorityofthe16‐year‐oldscontinueineduca‐tioneitherdirectlyaftercompletingcompulsoryschooloroneyearlater,atage17,asclearlyindicatedinthefigurebytheincreaseintheshareoffull‐time students among the 17‐year‐olds. Concomitantly, there is asharp decline in the share of compulsory‐school leavers outside botheducation and the labour market (“other”) when youngsters re‐enterschoolafterhavingspentayearinnon‐educationandnon‐employmentactivities. Then follows rapidly growing numbers of 18‐ and 19‐year‐oldsmoving fromuppersecondaryeducation intoworking life, thoughoccasionally also into unemployment or entirely outside the labourforce. This “two‐step” transition into working life reflects, at least inpart,areformofinitialvocationaleducationturningby2001all2‐yearvocational tracks into 3‐year tracks (seeBox 2.3). Since Figure 2.1b isbasedonpooledinformationonthethreeyouthcohortsunderscrutiny,theshareofyoungpeopleenrolledinfull‐timeeducationis,bynecessity,amixofstudentshavingfollowed2‐yearand3‐yearvocationaltracksinuppersecondaryeducation.

Afterage19,theshareoffull‐timestudentsstartstoincrease,mainlyattheexpenseofworking,andbyage21approximatelyhalf(49%)ofallthese youngFinnswere studyingon a full‐timebasis.Hence, the earlypost‐compulsory‐schooltransitionpatternobservedforFinlandischar‐acterisedbytwoconspicuous“pauses”:adelayedstartinuppersecond‐ary education and a delayed start in tertiary‐level education. We willreturn to these delayed starts in our subsequent analyses. Finally it isworthnoting that thevariationacross cohorts in theshareof full‐timestudentsatage21isminor(±2–3%,Table2.1b).Hence,comparedtothesituationinSwedenandespeciallyinDenmark,theshareofyoungFinnsinfull‐timestudieshasremainedremarkablystableacrosscohorts.


Figure2.1b:Finland:Averagedistribution(%‐share)ofyoungpeopleacrossmainactivitiesuptoage31,basedonpooledinformationonallthreeyouthcohorts


Table 2.1b: Finland: Average distribution (%‐share) of young people across main activities at age 21, based on pooled information on all three youth cohorts (all and by gender) and separately by cohort




Employed 35.6 42.0 28.9 34.6 34.0 38.6

Unemployed 8.6 10.1 7.1 10.9 8.4 6.5



Total 100.0 100.0 100.0 100.0 100.0 100.0



Acomparisonacrosscohortsoflabourmarketactivitiesatage21pointstoimprovedemployment,aswellasunemployment(Table2.1b).Howev‐er, themuchmore favourable situation in this respect for the youngest(2003)cohort isnotnecessarilymerelydue to trulybetter employmentopportunities. Obviously it also reflects intensified active labourmarketpolicies directed towards unemployed young people (cf. Box 2.3). Thisaspect is not explored further in this context, though, aswe throughoutoverlook the quality of the employment relationship, including the factthattheemploymentcontractmayconceala(temporary)subsidisedjob.Theshareof21‐year‐oldsengagedinunknownactivities(“other”)outside


botheducationandthelabourmarkethasremainedstrikinglyunchangedoverthethreecohorts,ashasalsotheshareofdisabilitybeneficiaries.

A comparison across genders at age 21 reveals that themost con‐spicuousdiscrepanciesshowup in thesharesof full‐timestudentsandthe employed: young women continue disproportionally in educationcompared toyoungmen,whereasyoungmenaremuchmore likely tomove intoworking life, a situation also observed for the otherNordiccountries.Nonetheless,theriskofunemploymentseemstobeapproxi‐matelythesame,oneinfive,forbothgenders.Aslightlylargershareofyoung men was on disability benefits at age 21 with, in contrast, theshare of those in other inactivity being notably larger among youngwomenofthisparticularage.

Byage26,theshareoffull‐timestudentshaddeclinedto25%,andbyage 31 only about 13%were enrolled as full‐time students. Concomi‐tantly,theshareinemploymentincreasesrapidly,to60%amongthe26‐year‐oldsand73%amongthe31‐year‐olds.Theshareinunemploymentdeclinesslightly,whereastheshareondisabilitybenefitsshowsaweak‐lygrowingtrend,standingat2%amongthe31‐year‐olds.Theshareofyoungpeopleinthedumpingcategoryof“other”(outsideeducation,thelabourmarket and disability arrangements) seems to remain approxi‐matelyunchangedfromage21onwards,thatis,closeto6%.

Box2.3Finland–abriefoutlineoftherelevantinstitutionalframework


AllchildrenpermanentlyresidentinFinlandmustattendcompulsoryeducation,

which starts in the year of the child’s seventh birthday and finisheswhen the

syllabusofthe9‐yearcomprehensiveschooleducationiscompleted.Afterhav‐

ing received a leaving certificate from comprehensive school education in the

same or in the previous year, a studentmay continue in additional voluntary

basiceducation(10thgrade).

The post‐compulsory upper secondary level comprises general education

and initialvocationaleducationand training (VET).Theentireage cohort is in

principle,and increasinglyalso inpractice,grantedastudyplace inuppersec‐

ondaryeducation.Thegeneraluppersecondaryschoolisbasedoncourseswith

nospecifiedyear‐classes.Thescopeofthesyllabusisthreeyearsbutthestudies

maybe accomplished in two, threeor four years.This “class‐free” systemwas

introduced in the period 1994 to 1996. General upper secondary education is

primarilyfreeofchargeforstudents.Theuppersecondaryschoolendsinama‐

triculation examination which gives general eligibility to further education in

universitiesorpolytechnics.


Box2.3continued

The initialVETqualification takes threeyearsof full‐timestudy,unlessprior

learningcanbecountedtowardsthequalification.Upto2001,itwasalsopossible

tocompleteaninitialVETeducationintwoyears.Avocationalqualificationgives

generaleligibilityforpolytechnicanduniversitystudies.Therearenotuitionfees

in initial VET. Training for initial vocational qualifications is availablemainly in

vocationalinstitutions,butalsointheformofapprenticeshiptraining.Vocational

institutions‐basededucationcomprisesabout fivemonthsofon‐the‐job learning,

whereasmostoftheapprenticeshiptrainingstakesplaceintheworkplace,often

supplementedwithonlyshorttheoreticaleducationatavocationalinstitution.The

apprenticeship training track is annually chosen by some 9% of vocational stu‐

dents.Since1994ithasalsobeenpossibletotakeacompetence‐basedqualifica‐

tion.This system is intended to enableworking‐age adults to gainqualifications

without necessarily attending formal training. Less than 20% of the annually

awardedvocationalqualificationsarecompetence‐basedqualifications.

Studentsinuppersecondaryschoolshave,since1998,hadthepossibilityto

combinegeneralandinitialvocationaleducationandcompleteaso‐calleddou‐

bleexam.Thesetypesofstudiestypicallytakethreetofouryearstocomplete.

Measuresdirectedtowardsyoungpeoplenotineducationoremployment

Unemploymentbenefits:Unemploymentinsurancecoversthreedistincttypesof

benefits:earnings‐basedunemployment insurance,basicunemploymentallow‐

ance, and labourmarket support.Only the labourmarket support requires no

employment history. Accordingly, a notable share of these beneficiaries com‐

prisesyoungpeople.Thisflat‐ratemeans‐testedbenefitwasintroducedin1994

andispaidforanunlimitedperiod.Theeligibilityconditionsforreceivinglabour

marketsupportweretightenedin1995and1996fortheunemployedunder25

years‐of‐agelackingavocationalqualification.

Active labourmarketpolicy (ALMP)measuresandprograms:Thedeep re‐

cession in the early 1990s caused an extremely dramatic increase in unem‐

ployment.Moreover, unemployment decreased only slowly after the start of

economicrecoveryin1994,resulting inhighandpersistentstructuralunem‐

ployment.ThissituationinitiatedbothPESreformsandmeasuresinALMPs.In

particular, Finnish labour market policy was thoroughly reformed in 1998,

followedbyfurtheractionsforthisreformcompletedin2001(Räisänenetal.,

2012). A secondwaveofPES reformswasundertaken in2004–2006.Themain

typesofALMPsareemploymentsubsidiesandlabourmarkettraining.Alsopracti‐

caltrainingprogramsarequiteextensiveinvolume.Thedeepeconomicrecession


Box2.3continued

in the early1990s initiated, inter alia,moreuseof preparatory labourmarket

training,introductionofjob‐searchtraininginlabourmarkettrainingprograms,

explicittargetingofemploymentprogramsatthecorporatesectorinparticular,

andcuts inpublic‐sectoremploymentprograms.Especially since2005, there‐

formsinALMPshavebeendesignedtoprovideandsupporteducation.

Youngpeopleareanintegratedpartofthislabourmarketpolicyframework,

withtherelevantALMPsdependingontheirageandemploymenthistory.Spe‐

cialattentionhastherebybeenpaidtothe“youthsocietyguarantee”introduced

in2005.Itcoveredyoungunemployedpersonsundertheageof25andaimedto

enhancetheplacementoftheseyoungpeopleineducationandthelabourmar‐

ket, to prevent prolonged unemployment, and to support sustainable career

solutions. Job‐search plans were made a key instrument. At the beginning of

2013,thissystemwasreplacedbya“youthguarantee”offeringastudyplaceor

ajob,trainingorrehabilitation,orotherrelevantactivityafterthreemonthsof

unemploymenttothoseaged15to24,aswellasthoseunder30whohavere‐

centlyobtainedavocationaloracademicqualification.Bothguaranteesystems

havebeensubjecttoevaluations(seee.g.AsplundandKoistinen,2014).

Socialassistance:Socialassistanceisalastresortformofincomesecurityin‐

tendedtosecureatleastthenecessaryincomereferredtointheConstitutionof

Finland,aswellastopromotetheindependentcopingof individualsandfami‐

lies.Localauthoritiespaymeans‐testedsocialassistancewhenthe incomeand

resources of a household are insufficient to cover necessary daily expenses.

Since the beginning of 2006, social assistance is divided into three categories:

basic,supplementaryandpreventive.Theaimofpreventivesocialassistanceis

tohelpenableindividualsandfamiliestomanageindependentlyandtoprevent

socialexclusionandlong‐termdependenceonsocialassistance.

Disabilitybenefits:Theyoungpeople recorded tobedisabilitybeneficiaries

in the Finnish dataset receive a disability pension according to the registers

compiledjointlybytheFinnishCentreforPensions(ETK)andtheSocialInsur‐

anceInstitutionofFinland(Kela).Adisabilitypensionmaybegrantedeitherin

the national pension scheme or in the statutory earnings‐related pension

scheme.The liability to takeout insuranceunder theearnings‐relatedpension

legislation starts at the beginning of the month following the person’s 18th

birthday.Thenationalpensionscheme,inturn,coversallpersonsaged16to64

whohavepermanentlyresided inFinlandforat least threeyearsafter turning

16.Exceptionsfromthisrequiredperiodofresidenceareawardedto:(1)those

havingbecomeincapableofworkingbeforetheageof19whileresidentinFin‐

landand(2)thosereceivingadisabilityallowanceforpersonsundertheageof

16when turning 16. In contrast to the earnings‐related pension, the national


2.2.3 Norway

The situation for Norway is highlighted in Figure 2.1c and Table 2.1c.The share of full‐time students evolves up to age 20 in a way that isstrikingly similar to the trend observed for Finland (cf. Figure 2.1babove).But thereasonbehind thedecline in theshareof full‐timestu‐dentsatage18,ascomparedto thesituationatage17, isdifferent forNorway:mostprobablythispatternisduetolargesharesofvocationalstudentsdroppingoutbetweentheir2ndand3rdyearduetoa lackofapprenticeshipplaces;acontentionthatreceivesfurthersupportwhencomparing the shares in education at age 17 and 18 for those havingcompletedandthosenothavingcompletedanuppersecondarydegreebyage21(nodropoutisobservedforthecompleters).

ComparedtothesituationinFinland,however,theshareofcompul‐sory‐school‐leavers continuing in full‐time education starts out from aclearlyhigherlevel,andthissharealsodeclineslesssharplywithage.By

Box2.3continued

fundedbythestateandpaidataflatratewithincometesting.Irrespectiveofthe

schemeunderwhichthedisabilitypensionisawarded,thefollowingapplies.The

illness needs to significantly reduce the person’s work ability. The pension is

awardeduntilfurthernoticeorforaspecifictimeperiod.Thetime‐limitedbene‐

fit(since1996calledacashrehabilitationbenefit)isgrantedifthetreatmentor

rehabilitationcanbeexpectedtoimprove,atleastinpart,theperson’sworking

capacity.Accordinglyacashrehabilitationbenefit isalways tobeaccompanied

byatreatmentorrehabilitationplan.

These parallel pension systems have been subject to a number of reforms

overthepastdecades.Onemajorchangewasmade in2005,resulting ina fur‐

therdifferentiationofthetwosystems.Ofparticularrelevanceinthiscontextisa

reform related to the medical requirements for disability pension eligibility

underthenationalpensionscheme.Inparticular,fromAugust1,1999onwards,

anationaldisabilitypensionwasnolongergrantedtopersonsundertheageof

18 until their prospects for vocational rehabilitation had been clarified. By

April1,2002,thisagelimitwasincreasedto20yearsthuscoveringallpersons

aged16to19,althoughthereareanumberoftheexceptionstothisrule.Inthe

earnings‐relatedpensionscheme,itisrequiredthattheincapacityforworkcan

beestimatedtolastforatleastoneyear.Anoteworthychangeinthisschemeis,

however, that theminimum requirement for previous earningswasmarkedly

reduced in 2005, which resulted in a notable increase in the earnings‐related

pensionbeneficiarycaseload.


age21,everysecondNorwegianisenrolledinfull‐timeeducation.ThisshareissimilartothatobservedforFinlandandclearlyhigherthanthatobservedforDenmarkandSweden.

The share of young Norwegians in employment increases notablyafterage18,andbyage21aboutone‐thirdofthemareworking.Youngpeoplethusseemtostartmovingintoworking lifesomewhat later inNorway than in Denmark and Finland, and their employment sharealso tends to remain at a lower level especially when compared toDenmarkandSweden.Norwayisrathercharacterisedbyanincreasingshareofyoungpeoplemovingoutsidebotheducationand the labourforce(“other”)afterleavingcompulsoryschool.Thisshareisashighas16.5% among the 19‐year‐olds, but shrinks to about 9% by age 21.However,thisisstillasharethatishigherthanforDenmarkandmuchhigher than for Finland and Sweden. In contrast, the share of youngNorwegiansondisabilitybenefitsremainslow:itisslightlylowerthanin Sweden butmarginally higher than in Denmark and Finland. Alsotheshareoftheunemployedshowsonlyaweaklygrowingtrenduptoage21whereitlandsat5.4%.ThisshareisclearlylowerthanforFin‐landandSweden,buthigherthanforDenmark.

Figure2.1c:Norway:Averagedistribution(%‐share)ofyoungpeopleacrossmainactivitiesuptoage31,basedonpooledinformationonallthreeyouthcohorts



Table 2.1c: Norway: Average distribution (%‐share) of young people across main activities at age 21, based on pooled information on all three youth cohorts (all and by gender) and separately by cohort




Employed 34.0 38.7 29.1 33.8 34.3 34.0

Unemployed 5.4 7.1 3.7 4.1 7.1 5.1



Total 100.0 100.0 100.0 100.0 100.0 100.0



AconspicuousfeatureofNorwayisthestabilityoftheaveragedistribu‐tionacrossmainactivitiesoverthethreecohortsunderscrutiny(Table2.1c).Thesharesinfull‐timeeducationandinemploymentaremoreorless the same for all three cohorts. The changes across cohorts in thesharesofyoungNorwegiansshowingupinNEETactivities(unemploy‐ment,disabilitybenefitsandother inactivity)arequitesmall,revealingnoclear‐cuttrendovertime.Ratherthereseemstohaveoccurredocca‐sionaltrade‐offsbetweenunemployment,ontheonehand,anddisabil‐itybenefitsandothertypesofinactivity,ontheotherhand.

The average distribution across main activities of young men andyoungwomenturning21unravelsnosurpriseswhencomparedtotheoverall pictureobtained for theother three countries.Also inNorway,youngwomenhaveastrongerpreferencetocontinueinfull‐timeeduca‐tion as compared to their male peers, many of whom prefer to movefromschoolintoworkinglife.Additionally,alargershareofyoungmenthanofyoungwomenencountersunemploymentatage21.Thehigherunemploymentriskofyoungmenisretainedalsowhenaccountismadefor the gender difference in employment shares. However, when itcomestothetwotypesofinactivity(disabilitybenefitsand“other”),thedistributional shares are onlymarginally different for youngmen andyoungwomen.

The share of young people studying on a full‐time basis declinesdramaticallyafterage21.Byage26itisdowntoabout25%andbyage31 ithasdroppedbelow10%.At thesametime,employmentbecomesthedominatingactivitywith72%ofthe31‐year‐oldsworking.Thecom‐binedshareofyoungpeople inNEETactivities remainsapproximatelyunchanged, although there seems to occur continuous shifts betweenthese threenon‐educationandnon‐employmentstatuses,notably fromunemploymentintoinactivity.


Box2.4Norway–abriefoutlineoftherelevantinstitutionalframework


EducationinNorwayiscompulsoryfromtheageof6untiltheageof16.After

completionofcompulsoryeducation,everyyoungpersonhasastatutoryright

to attend three years of upper secondary education free of charge. This right

must be utilized during a period of five consecutive years (six for some voca‐

tionalcourses),andmustbestartedwithinfiveyearsaftercompletedcompulso‐

ryschool.Enrolmentisalmostuniversal:96–97%ofeachyouthcohortleaving

compulsory school has a direct transition to upper secondary education. This

sharehasbarelychangedsince1993(FalchandNyhus,2009).

When applying for upper secondary education, the youthmay choose be‐

tween two main tracks: academic and vocational studies. Around half of the

studentsopt for theacademictrack,whichprepares for furtherstudies inuni‐

versities and colleges. The rest of the youth start a vocational study program,

which gives qualifications for work in a number of different occupations. A

standard course through an academic study program lasts three years, while

mostofthevocationalprogramsfollowa2+2model:twoyearsofschool‐based

trainingfollowedbytwoyearsofapprenticeshipinacompany.Thereis,howev‐

er,noguaranteeofanapprenticeship‐training‐placeandthesupplyofappren‐

ticeshipsisshowntovarywiththeeconomicsituation(Høst,2008).Youthwho

donotreceiveanofferofanapprenticeshipareentitledtoathirdyearinschool.

Thestatutoryrightofuppersecondaryeducationforyoungpeopleaswellas

the integration of apprenticeships through the 2+2modelwere introduced in

1994,andaresomeofthemaincomponentsofReform94–amajoreducational

reform that reorganized theentireupper secondary school system inNorway.

The reform narrowed down the possible routes towards an upper secondary

degree, and aimed at increasing the throughput of students.While the reform

seems to have been somewhat successful, the non‐completion rates are still

high:around30%ofeachyouthcohortfailstocompletetheireducationwitha

formalcertificationwithinfiveyearsafterenrolment.Thenon‐completionrates

have been remarkably stable since the introduction of Reform94, and are al‐

mosttwiceashighforvocationalstudentsasforacademicstudents.


Box2.4continued


labourmarket

Theyouthguaranteeandactivelabourmarketprograms:Youngpeopleaged16

to21whoeitherdonotapplyfororinterrupttheiruppersecondaryeducation

are under the responsibility of the Follow‐up service. This servicewas estab‐

lishedin1994inanefforttomeetthechallengesrelatedtohighdropoutrates,

andactsasasafetynet.Throughindividualguidance,adviceandpracticalassis‐

tanceyoutharedirected intoactivitieswhichaimat improving theiraccess to

thelabourmarket.InadditiontotheFollow‐upservice,youthwhohaverecently

lefttheeducationsystemandhavenotyetfoundajobareassuredparticipation

in an active labour market program through the Youth Guarantee. The term

guaranteemaybemisleading in this context, as thearrangement isnot legally

bindingbutratherreflectsaclearlystatedpolicyambition.Initially,theguaran‐

teeconcerned16–19year‐oldyouth,butwiththeintensifiedeffortsintheperi‐

od1995to1998toprovideactive labourmarketprogramstheguaranteewas

temporarilyextendedtoalsocover20–24year‐oldlong‐termunemployed.This

extendedyouthguaranteehasbeenevaluatedbyHardoyetal.(2006)whofind

that the guarantee increased theparticipationof20–24year‐olds inprograms

and also improved their transition fromunemployment into employment. The

extendedyouthguaranteewasreintroducedin2009.

Unemploymentbenefits:Theunemployment insuranceschemeinNorwayis

based on previous labour market income. In order to receive unemployment

benefits, onemust register as a jobseeker at the local employment office and

actuallyapplyforwork.Inaddition,onemusthavebeenpaidwagesofat least

1.5timestheNationalInsuranceSchemebasicamount(BA)inthelastcalendar

year,orat least3 timestheBAoverthepast three fullcalendaryears.There‐

placementratewas62.4%in2012,andthebenefitcoversupto6timestheBA.

Young school‐leaversdonot in general qualify forunemploymentbenefits,

astheydonotfulfil the incomerequirements.Theincentivestoregisterasun‐

employedforyoutharethuslow.Themajorityofnon‐/unemployedyouthmay

insteadbeclassifiedasNEETs(NotinEmployment,EducationorTraining).


Box2.4continued

Socialassistance:Youthwhoarenotable to financially support themselves

throughemploymentorothermeansmayreceivesocialassistance.Thebenefit

is temporary, and the aim is to secure financial independence. In order to be

entitled tosocialassistance,allotheroptionsmusthavebeenconsidered.This

includes gainful employment, own savings and other financial rights, such as

unemploymentbenefits.Theamountreceivedismeans‐based,andeachcase is

specificallyandindividuallyassessed.Itispossibletoreceivesocialassistanceas

a supplement toother income, if this income is too low tocoverbasic subsist‐

ence costs. Often there are certain conditions attached to the entitlement of

socialassistance,buttheseconditionsarealwayssetonanindividualbasis.For

instance,non‐employedindividualsmayhavetoregisterasjobseekersorpartic‐

ipateinanactivelabourmarketprograminordertoreceivethebenefit.

Disabilitybenefits: Youthwho have reducedwork capacity of at least 50%

duetophysicalormentalhealthproblemsmaybeeligiblefordisabilitybenefits.

Thegeneralrule isthatafter12monthsonsick leave,onecanapplyforeither

temporaryorpermanentdisabilitybenefits,withareplacementrateofapprox‐

imately 66%.Youngpersonswithnopreviouswork experiencemay receive a

minimumamount according to the guidelines established for the old‐age pen‐

sion.Inaddition,theindividualhastobeatleast18yearsold(16yearsolduntil

1998)inordertoapply.Intheperiodanalysedinthisreport(1993to2008),the

temporarydisabilitybenefitsconsistedofmedicalandvocationalrehabilitation

benefits as well as a time‐limited disability pension (introduced in 2004). In

2010,thethreebenefits(medicalandvocationalrehabilitation,andtime‐limited

disabilitypension)were combined intoone:TheWorkAssessmentAllowance.

Thisallowancehasamaximumdurationoffouryears.

Therehabilitationbenefitsmaybereceivedforamaximumperiodof52con‐

secutiveweeks,whilethetime‐limiteddisabilitybenefithasanuppertimelimitof

fouryears. If thehealthproblemspersistafterthisperiod,thepersonmayapply

forapermanentdisabilitypension.Thepermanentdisabilitymaybeeitherfullor

partial,dependingontheremainingworkcapacityoftheperson.Normally,aper‐

manentdisabilitypensionlastsuntilitisreplacedbyanold‐agepensionattheage

of67,andthereisnore‐testingoftheindividual’sworkcapacity.


2.2.4 Sweden

Finallywe turn our focus to Sweden. As illustrated in Figure 2.1d, thecross‐activitydistributionup to age21of the three Swedishyouth co‐hortsunderscrutinycanbasicallybedescribedasanextremeversionoftheoverallpatternsdisplayed forFinlandandNorway.Moreprecisely,also Swedish 16‐year‐olds typically continue directly in post‐compulsoryeducation,occasionallyafterayearspentoutsidebothedu‐cation and the labourmarket: the share of continuing 16‐year‐olds isalmost 94% and increases to over 95% among the 17‐year‐olds.Mostyoung Swedes stay in upper secondary education for three years (seeBox2.5),afterwhichfollowsaremarkablystrongshiftintoworkinglife:theshareoffull‐timestudentsdropsfromabout93%atage18to37%atage19,whereastheshareofemployedgrowsfrombelow3%to42%.Hence,themagnitudeoftheschool‐to‐worktransitionoccurringatthisage is even stronger than inFinland, resulting in a situationwithonlyabout40%of19‐year‐oldSwedesbeingenrolledinfull‐timeeducation,asharesimilartothatobservedforFinland(despitethetwocountries’quitedifferentsituationsamong16‐to‐18‐year‐olds).ThecorrespondingshareisnotablyhigherinDenmarkandNorway,about50%.

Moreover, the recovery inenrolment ratesbyage21 ismarginal inSweden: only up to some 41% (Table 2.1d). In Finland, on the otherhand,theshareoffull‐timestudentshasbyage21increasedtomuchthesamelevelasinNorway(astudentshareofaboutone‐halfinbothcoun‐tries).Hence,inthisrespectSwedenranksfarbehindFinlandandNor‐wayandisalsooutstrippedbyDenmark.


Figure2.1d:Sweden:Averagedistribution(%‐share)ofyoungpeopleacrossmainactivitiesuptoage31,basedonpooledinformationonallthreeyouthcohorts


Table 2.1d: Sweden: Average distribution (%‐share) of young people across main activities at age 21, based on pooled information on all three youth cohorts (all and by gender) and separately by cohort




Employed 44.9 49.9 39.5 42.6 43.0 47.7

Unemployed 9.2 10.4 7.8 11.8 9.2 6.9



Total 100.0 100.0 100.0 100.0 100.0 100.0



AnotherfeaturethatSwedenshareswithbothFinlandandNorwayisanotable increase at age19 in activities outside education andworkinglife. However, while the NEET activities at this particular age are inNorway dominated by “other” (unknown activities), the overbearingactivity is unemployment for Finnish and even more so for Swedishyoungsters:theshareofyoungSwedeshavingregisteredasunemployedjobseekersisabout13%atage19andalsoatage20.Althoughitdropsto about 9% by age 21, this is still the highest share of young unem‐ployedamongthe fourNordiccountriesunderstudy.Alsotheshareof


young people on disability benefits is relatively high among youngSwedes, whereas the share in the dumping category “other” is muchlowerthanintheotherthreecountries.

However,acomparisonoftheaveragedistributionacrossmainactiv‐ities in the three youth cohorts reveals that many of the peculiaritiesobserved forSweden (inFigure2.1d) stem fromoccasionallyquite re‐markablechangesovercohorts.Table2.1dhighlightsthesecross‐cohortdifferencesatage21.Asisevidentfromthetable,theshareoffull‐timestudentsatage21isthroughoutratherlowcomparedtotheotherthreeNordiccountriesandhasdeclinedfurtherintheyoungest(2003)cohort.Simultaneously, the share in employment has increased over cohortswithalmostone‐halfoftheyoungestcohortworkingbyage21.Howev‐er, these changes in studying and working shares concern only theyoungestcohort,withthesetwosharesbeingmoreorlessthesameforthe1993and1998cohorts.Thecross‐cohortincreaseinemploymentisaccompaniedbyadeclineinunemployment,butalsobyasteadygrowthin the share on disability arrangements or in other types of inactivity.Almostone‐halfofyoungSwedesondisabilitybenefitsareestimatedtobesoseverelydisabledthattheywillneverbeabletotakeanordinaryjob.Moreover,theSwedishSocialInsuranceAgencypredictsthattherewillbeafurtherincreaseoverthenextfewyearsinthenumberofyoungpeoplegoingintodisabilityarrangements.Thisincreaseovertimeinthenumber of youth on disability benefits has receivedmuch attention inthepoliticaldebateinSweden.

As in theotherNordic countries, youngwomen continue in full‐timeeducation toamuch largerextent thandoyoungmen(Table2.1d).Theshareof21‐year‐oldfemalesenrolledinfull‐timeeducationisclosetothatoftheirDanishcounterparts,butnotablylowerthaninFinlandandNor‐way.The shareof21‐year‐oldmales studyingona full‐timebasis is ex‐tremelylow,butcounteractedbyanemploymentsharethatwellexceedsthose observed for the other three countries. While also the share ofworking21‐year‐oldfemalesisrelativelyhighinSweden,itisnonethelessmore in line with what is observed for the other countries and, again,quite close to the corresponding share for Denmark. The differences ingender distributions across main activities are much smaller when itcomestoNEETactivities.Asintheotherthreecountries,theshareamong21‐year‐oldmen on disability benefits is slightly larger (except in Nor‐way)andtheshareinothertypesofinactivityslightlylower,whencom‐paredtothecorrespondingsharesamong21‐year‐oldfemales.

Afterage21,theaveragedistributionofyoungSwedesacrossthefivemain activity categories turns increasingly similar to the distributions


observedfortheotherthreecountries.Inparticular,theshareofyoungSwedes enrolled in full‐time education is down at 23%by age 26 anddropsto9%byage31.ThesesharesareveryclosetothoseobservedforDenmarkandFinland,andespeciallyforNorway.Likewise,theshareofyoungpeopleinemploymenthasincreasedtoabout65%byage26,andtoasmuchas82%byage31.Concomitantly,thereisastrikingdeclineintheshareofyoungpeopleinunemployment.Whiletheshareondisa‐bilitybenefitsincreasesslightlyuptoage31,thereisafurtherdeclineintheshareofyoungpeopleinothertypesofinactivity.

Box2.5Sweden–abriefoutlineoftherelevantinstitutionalframework


EducationinSwedeniscompulsoryfromtheautumntermoftheyearthechild

turns7and lasts fornineyears,until thespring termaftergrade9.All tiersof

schooling are a municipal responsibility regulated by the 1985 Education Act

(Ministry of Education and Research, 2000) and overseen by the Swedish Na‐

tionalAgencyforEducation.Aftercompletedcompulsoryeducation,everyyoung

personhasastatutoryrighttoattendthreeyearsofuppersecondaryeducation

freeofcharge.Uppersecondaryschoolisformallyelective,althoughmostattend

it.Whenapplyingforuppersecondaryeducation,theyouthmaychoosebetween

twomain tracks: academic and vocational studies both ofwhich last for three

years.Aroundtwo‐thirdsofthestudentsoptfortheacademictrack,whichpre‐

paresforfurtherstudiesinuniversitiesandcolleges.Therestoftheyouthstarta

vocational study program, which gives qualifications for work in a number of

different occupations.Women and those living in the larger city areas tend to

chooseacademic tracks toa largerdegreewhilemenand those living inmore

sparselypopulatedareastendtochoosethevocationaltrackstoalargerdegree.

Studentsapplytouppersecondaryschoolbasedontheirgrades fromcom‐

pulsoryschool.Studentsgenerallyattendaschool in theirmunicipalityof resi‐

dence,butifthedesiredtrackisnotofferedtheycaninsteadchoosetoattenda

schoolinanearbymunicipality.

Aneducationalreformin1991introducedamorecomprehensiveuppersec‐

ondaryschoolsysteminSwedenwhichsubstantiallyreducedthedifferencesin

curriculabetweentheacademicandvocationaltracksinuppersecondaryschool.

Thiswasdonebyconsiderablyincreasingtheacademiccontentofallvocational

tracks. The length of these trackswas at the same time extended from two to

three years, giving them the same length as the academic tracks. At the same

time, students graduating from a vocational track attained basic eligibility for

universitystudies.


Box2.5continued

Withthe2011reformofuppersecondaryschool,severalchangeshavebeen

made in vocational education. The largest change was the introduction of ap‐

prenticeshiptraining.Thereformalsoreducedthescheduledtimeforthecom‐

pulsorytheoreticalsubjects.Inaninternationalperspective,theSwedishsystem

forvocationaleducationcanstillbecharacterizedasbeingacademicallyorien‐

tatedboth in termsof large amountsof theory in the school‐basedpart of the

education and the relatively small share ofworkplace‐based learning. The re‐

quiredamountofworkplace‐basedlearningis15weeksduringthethreeyears

oftheprogram,whichislessthaninmostothercountries.


labourmarket

Theyouthguaranteeandactivelabourmarketprograms:Youngpeopleaged16

to24,whohaverecentlylefttheeducationsystemandhavenotyetfoundajob

are assured participation in an active labour market program through the

YouthGuarantee(Jobbgaranti förungdomar).Participation is full timeunless

there are specific circumstances such as illness, disability, parental leave or

someotherreasonacceptedbytheemploymentagency.Theyouthguarantee

wasintroducedin2007.Thepurposeoftheyouthguaranteeistoofferspecific

labourmarket support at an early stage. Examples of support are education,

jobsearchassistanceandpracticaltrainingoraninternship.TheYouthGuar‐

antee replaced the earlier youth guarantee program (Utvecklingsgaranti för

ungdomar),whichwas introduced in 1998 and targeted at unemployed per‐

sonsaged20–24.Theguaranteeincludedanassignmenttosomelabourmar‐

ketprogramwithin100daysofunemployment.

Unemploymentbenefits:Theunemployment insurancescheme inSweden is

based on previous income. To receive income‐related benefits, onemust have

beenamemberofanunemploymentinsurancefundforat leasttwelvemonths

(membershipcondition).Thepersonmustalsohavesatisfiedaworkcondition.

Therequirementisthatonemusthaveworkedatleast80hoursamonthforat

leastsixmonthsduringthelasttwelvemonthsbeforebecomingunemployed.

Youngschool‐leaversdoingeneralnotqualifyforunemploymentbenefits,as

theydonotfulfiltheincomerequirements.Thiscouldbeexpectedtolowertheir

incentives to register as unemployed. However, participation in some youth

labourmarket programs such as job training (Arbetslivsintroduktion) and the

YouthGuarantee(Jobbgarantiförungdomar)qualifiesforpaymentatalowlevel

(utvecklingsersättning).


Box2.5continued

Socialassistance:Youngpeople(18yearsandabove)whoarenotabletofi‐

nanciallysupportthemselvesthroughemploymentorothermeansmayreceive

social assistance. The benefit is temporary, and the aim is to secure financial

independence. Inordertobeentitledtoreceivesocialassistance,allotherop‐

tionsmusthavebeenconsidered.This includesgainfulemployment,ownsav‐

ings and other financial rights, such as unemployment benefits. The right to

socialassistance isnotbasedon the incomeprinciplebuton individualneeds

assessment,thatis,theamountreceivedismeans‐based,andeachcaseisspecif‐

icallyandindividuallyassessed.Thismeansthat it ispossibletoreceivesocial

assistanceasa supplement toother income, if this income is too low tocover

basicsubsistencecosts.Oftentherearecertainconditionsattachedtotheenti‐

tlementofsocialassistance,buttheseconditionsarealwayssetonanindividual

basis.Forinstance,non‐employedindividualsmayhavetoregisterasjobseek‐

ers or participate in an active labourmarket program in order to receive the

benefit.Amongtheadultsocialassistancereceivers,39%werebetween18–29

yearsold(Socialstyrelsen2014).

Disabilitybenefits: In2003, the earlier system for early retirement (förtid‐

spension)wasreplacedbyaktivitetsersättningfor individualsbetween19and

29years‐of‐age.Thepurposeofthereformwastoreducethenumberofyoung

peopleondisabilitybenefitsandfacilitatetheirreturntoworkthroughtargeted

activities.Before2003,thedisabilityinsurancewaspartoftheoldpublicpen‐

sionsystem,andfrom2003,itbecamepartofthesocialinsurancesystem.The

reason for this change was to come up with a financially cohesive insurance

schemethatincludedallbenefitsthatcompensateincomelossesforpeoplewith

reduced work ability. In 2003, the cooperation between the Social insurance

agencyand theEmploymentserviceswasexpanded,primarily inorder to im‐

provetheabilityoflong‐termsicktoreturntowork.

According to current regulations, youth who have reduced work capacity

duetophysicalormentalhealthproblemsmaybeeligiblefordisabilitybenefits.

If the employees are between 19 and 29 years old, theymay receive benefits

(aktivitetsersätting)provided that theirworkcapacity is reducedbyat leasta

quarterforatleastoneyear.Compensationislimitedintimeandgrantedfora

maximumofthreeyearseach.Duringthecompensationperiodthereisaplanto

returntowork.Theplanallowstheemployertobeoneoftheactorswhowill

enableemployeestoreturntowork.Duringthetimethattheemployeereceives

benefits, he or she has the opportunity to participate in activities that have a

positiveimpactonthediseaseconditionorperformance.Theactivityalsoaims

toimproveworkcapacity.


2.2.5 Mainfindings

This sub‐chapterhas givena generalpictureof the average changesoc‐curringinyoungpeople’spost‐compulsory‐schoolactivitiesontheirwaythrough education and to the labourmarket. As discussed abovewhencommentingon thepatternsobserved foreachof the fourNordic coun‐triesunderstudy,theoverallpicturelooksmoreorlessthesame:declin‐ing shares in full‐timeeducationand rapidly growing shares in employ‐mentwhen the young people in our three cohorts grow older. In otherwords,largesharesofyoungpeoplearerapidlyandsuccessfullyintegrat‐ed into the labourmarket.However, in all four countries there are alsonon‐negligible shares of young people experiencing unemployment, en‐counteringhealthproblemsmoving themontodisabilitybenefits,oren‐gaginginothertypesofinactivityoutsidebotheducationandwork.

Despite of sharing this overall pattern, there are also distinct differ‐ences between the four countries, especiallywhen it comes to full‐timestudiesandemployment.Althoughmuchattentionispaidtothesediffer‐ences in theabovecountry‐specificsections, there isnonethelessreasonto recall themost conspicuous divergenceswith the help of Table 2.1e,whichrepeatstheactivitysharesatage21ascalculatedfrompooledin‐formationonallthreeyouthcohorts.Inparticular,wehaveobservedlowshares of 21‐year‐olds enrolled in full‐time education for Denmark andSwedenaccompaniedbyrelativelyhighsharesof21‐year‐oldsinworkinglife.AttheotherextremewehaveFinlandandNorwaywithhighsharesofyoungpeople studyingona full‐timebasis still at age21,whereas theirshare in employment is relatively low. However,when adding up thesetwo “activity” shares, as in Table 2.1e, the differences across countriesalmostdisappear.

Table 2.1e Cross‐country comparison: Distribution (%‐share) of young people across main activities at age 21, based on pooled information on all three youth cohorts

Activity at age 21 All three cohorts merged

Denmark Finland Norway Sweden

Full‐time student 43.7 49.0 50.1 40.2

Employed 43.2 35.6 34.0 44.9

Activity share (full‐time student + employed) 86.9 84.6 84.1 85.1

Unemployed 3.9 8.6 5.4 9.2

Pensioner (disability benefits) 0.7 1.0 1.4 1.6

Other (inactivity) 8.5 5.7 9.1 4.2

NEET share (unemployed + pensioner + other) 13.1 15.3 15.9 15.0

Total 100.0 100.0 100.0 100.0



Whenmovingbeyondtheageof21,however,thesharesofyoungpeopleinfull‐timeeducationandinemploymentturnincreasinglysimilarinthefourcountries.Inotherwords,thecross‐countrydifferencesinstudyingandworkingsharesobservedoverthefiveyearsfollowingcompletionofcompulsoryeducationshrinknotablyinadulthoodbutdonotdisappear,as will also be shown in Chapter 6. This notion points to a relativelystrong influence of especially upper secondary education systems butalsooflabourmarketinstitutionsontheearlyschool‐to‐work‐transitionpatternsofyoungpeopleleavingcompulsoryschooland,ultimately,alsoonlabourmarketoutcomesinadulthood.WereturntothisquestioninChapter6and,especially,inChapter7.

Thecounterparttothecross‐Nordicsimilarity inactivity(education+ employment) shares among21‐year‐olds isNEET sharesof approxi‐mately the samemagnitude (Table2.1e).However, theseNEET sharesare found to conceal occasionally quite notable cross‐country differ‐encesinthedistributionofyoungpeopleintounemployment,disabilitybenefits and other types of inactivity: the dominating NEET activityamong21‐year‐olds isunemployment inFinlandandSwedenbut“oth‐er” (unknown activity) in Denmark and Norway. Hence, while cross‐Nordicdifferencesinuppersecondaryeducationsystemsandinlabourmarket institutions seem to leave the NEET share largely unaffected,educational and institutional particularities do seem to influence thedistributionofyoungpeopleacrossalternativeNEETactivitiesand,asaconsequence,labourmarketoutcomesasayoungadult.AlsothisaspectisinvestigatedinmoredepthinChapters6and7.

2.3 Non‐completers–anintroductoryview

Theprevioussub‐chapterhasshownthat largesharesofyoungpeoplecontinuedirectlyinpost‐compulsoryeducation,completeanuppersec‐ondarydegreeandmoveintotertiary‐leveleducation,oraresuccessful‐ly integrated into the labour market. There are, however, also youngpeoplefacingseriousproblemswhenitcomestopost‐compulsoryedu‐cation and labourmarket integration. A non‐negligible share of youngpeople fails to achieveanupper secondary certificatewithoftendetri‐mental influenceontheir labourmarketprospects. In thissub‐chapter,we take a closer look at this non‐completion phenomenon in the fourNordiccountriesunderstudy.


2.3.1 Non‐completionatage21

Uppersecondaryeducationaimstoprovidestudentswiththebasicskillsandknowledgeneededtosuccessfullyenterthelabourmarket,orhighereducation. It is by now a stylized fact that completing upper secondaryeducationhasapositiveeffectonlateroutcomesintermsofbetterlabourmarketprospects.Accordingly,mostcountriesmakeconsiderableeffortstoimproveuppersecondarygraduationratesforallstudents.

Box2.6Definitionof“non‐completer”

Table2.2presentscountry‐specificsharesofnon‐completersforthethreeyouthcohortsunderscrutiny,withthenon‐completerdefinedasayoungpersonwhohasnotfinisheduppersecondaryeducationbytheageof21(cf.Box2.6).Asisevidentfromthetable,thesenon‐completionsharesarehighly similar for Finland and Sweden, ranging between 14 and 20 percent depending on the youth cohort in question. The non‐completionsharesforthesetwocountriesalsorevealastrikinglysimilartrendovercohorts: a growing share from the 1993 cohort to the 1998 cohort, fol‐lowedby a slight decline for the youngest (2003) cohort. In both coun‐tries, however, the share of 21‐year‐old non‐completers remains at ahigherlevelintheyoungestcohortascomparedtotheoldestcohort.

Table 2.2: Non‐completion rates (%‐shares) at age 21 in four Nordic countries, by cohort

Cohort Denmark Finland Norway Sweden

16‐year‐olds in 1993 34.7 16.0 28.5 14.5

16‐year‐olds in 1998 39.0 19.7 29.1 17.0

16‐year‐olds in 2003 38.3 18.4 31.5 16.5

Thesituationlooksdifferent inDenmarkandNorway.Whilethesetwocountries are characterised by notably higher non‐completion sharesamong21‐year‐olds,whencomparedtoFinlandandSweden,thedevel‐opment of these shares across cohorts reveals more differences thansimilaritiesbetween the twocountries. InNorway, thenon‐completionratewasofmuchthesamemagnitudeinthe1993and1998cohortsbutincreased further in the 2003 cohort. Hence, the share of non‐

In our analysis,we define non‐completion as not having completed upper sec‐

ondary education by the year one turns 21 years‐of‐age. Instead of using the

term“drop‐out”or“earlyschoolleaver”,whichinthiscasewouldbesomewhat

misleading,we prefer to use the term “non‐completer” for thosewho still five

yearsaftercompletedcompulsoryeducationhavenouppersecondarydegree.In

otherwords,theironlyformaleducationbyage21isprimaryeducation.


completersintheyoungestcohortwasalmosttwiceaslargeinNorwayasinSweden.

Thehighestnon‐completionrateamong21‐year‐oldsisobtainedforDenmark. As for the other Nordic countries under study, it increasedbetweentheoldestcohortandthemiddlecohort,butclearlymorethanin theother three countries. In the1998 cohort, only threeout of fivehad completed an upper secondary degree by age 21. The non‐completionratewasonlymarginallylowerintheyoungestcohort.

Due tobroadpoliticalagreement in theNordiccountrieson thede‐sirabilityofinvestingineducationandtrainingthroughoutworkinglife,current policies promote also later educational initiatives, bothwithintheframeworkofthesecondaryeducationsystemandintheadultedu‐cationsystem.Therefore,itisnotuncommonthatindividualswhodropout of school re‐enter, sooner or later, the education system to finishtheiruppersecondaryeducation.Thisisalsoevidentinthenextfigureswhich show, separately for the four countries, the share of non‐completers in our three youth cohorts, from age 19 up to age 31. Thenon‐completion shares at age 21 are, of course, identical to those dis‐playedinTable2.2above.Additionallywepresenttheevolutionofnon‐completionsharesalsobygender.

2.3.2 Non‐completionbeyondage21:Denmark

Figure2.2ashowsthattheremarkablyhighshareofnon‐completersob‐served among 21‐year‐old Danes shrinks rapidly up to age 31 (uppergraph). In the oldest (1993) cohort, it declines fromhaving been about35% at age 21 to 17%by age 31. A similar trend is discernible for themiddle(1998)cohort,exceptthattheshareofnon‐completersstartsoutfrom a higher level and also remains at a higher level: 23%among 26‐year‐olds compared to21% in theoldest cohort.On thewhole, this im‐pliesthatlargesharesofyoungDanesprolongtheirstudiesinuppersec‐ondaryeducationandthatthistendencyhasstrengthenedovercohorts.

A splitbygender (lowergraphofFigure2.2a) reveals, in turn, thatthenon‐completionshareismuchhigheramongyoungmenthanamongyoungwomen.Inotherwords,largersharesofyoungwomencompleteapost‐compulsory degree and, moreover, at a faster pace (i.e. youngerage). Additionally the graph indicates that the gender gap in non‐completionshareshaswidenedover cohorts,mainlydue to increasingsharesofnon‐completersamongyoungmen.Atage26,forinstance,thisgapwas5.5percentagepointsinthe1998cohortcomparedto3.3per‐


centagepointsinthe1993cohort.Evenlargergendergaps,andchangesinthesegaps,areobservedatyoungerages,asillustratedinTable2.3a.

Figure2.2a:Denmark:Non‐completionrates(%‐shares)atdifferentages,bycohort(uppergraph)andbycohortandgender(lowergraph)


Table 2.3a: Denmark: Non‐completion rates (%‐shares) at three ages, by gender and cohort

At age 21 At age 26 At age 31

Cohort Young

men

Young

women

Young

men

Young

women

Young

men

Young

women

16‐year‐olds in 1993 39.2 30.3 22.1 18.8 19.2 14.4

16‐year‐olds in 1998 43.9 34.3 25.3 19.8 n.a n.a

16‐year‐olds in 2003 44.6 32.1 n.a n.a n.a n.a

Note: n.a. = information not available in the data.

2.3.3 Non‐completionbeyondage21:Finland

ThecorrespondinginformationforFinlandisprovidedinFigure2.2b.Byand large, theoverallpatternresemblesthatobservedforDenmark. Inparticular,thenon‐completionshareinthe1998cohortstartsoutfromahigherlevelandalsoremainsatahigherlevel,whencomparedtothesituation of the oldest (1993) cohort. There is, however, one distinctdifferencebetweenFinlandandDenmark: inFinland,theshareofnon‐completersisquitelowalreadyatage21anditdeclinesonlymarginallybeyondthisage. In theoldestcohort, it shrinks from16%atage21 tobelow12%atage26and10%atage31.Likewise,inthemiddle(1998)cohortitisdownatabout13%atage26comparedtoalmost20%atage21. Hence,notmuch seems tohappen toyoungFinns’non‐completionratesbeyondage21,aconclusionalsodrawnbye.g.Myrskylä(2011b).

ThelowergraphofFigure2.2bshowsthatnon‐completionisamoretypicalphenomenonamongyoungmenthanamongyoungwomenalsoinFinland.Moreover,thegendergapinnon‐completionsharesturnsoutto widen remarkably at age 20, but remains thereafter approximatelyunchanged.AndincontrasttothesituationinDenmark,thereseemstobe only marginal changes in the gender non‐completion gap over co‐horts,asisalsoevidentfromTable2.3b.


Figure2.2b:Finland:Non‐completionrates(%‐shares)atdifferentages,bycohort(uppergraph)andbycohortandgender(lowergraph)


Table 2.3b: Finland: Non‐completion rates (%‐shares) at three ages, by gender and cohort


Cohort Young

men

Young

women

Young

men

Young

women

Young

men

Young

women

16‐year‐olds in 1993 18.6 12.9 14.5 8.7 12.8 6.9

16‐year‐olds in 1998 22.4 16.1 16.4 10.1 n.a. n.a.

16‐year‐olds in 2003 21.1 16.5 n.a. n.a. n.a. n.a.


2.3.4 Non‐completionbeyondage21:Norway

As shown in Table 2.2 above, the share of non‐completers among 21‐year‐old Norwegians has remained at a relatively high level over co‐horts, albeit clearly below those observed for Denmark. However, thenon‐completionratedeclinesatasteadypaceafterage21.Intheoldestcohort,itisbyage26downat22%andbyage31at20%(Figure2.2c,uppergraph).Moreover,thenon‐completionratebeyondage21evolvesinmuch the samemanner for the 1998 cohort, implying small, if any,changes across cohorts in this respect. Notably larger changes acrosscohortsareobservedpriortoage21withthedelayincompletionratesattheseyoungeragesshowingasteadygrowthacrosscohorts.

Figure2.2c:Norway:Non‐completionrates(%‐shares)atdifferentages,byco‐hort(uppergraph)andbycohortandgender(lowergraph)


Figure2.2ccontinued

ThelowergraphofFigure2.2cprovidesat leastpartofanexplanationfor the changes in early non‐completion shares observed across thethreeNorwegianyouthcohorts.First,non‐completionratesweremuchhigheramongyoungmenthanamongyoungwomenalreadyintheold‐estcohort,butthisgendergapinnon‐completionsharesdidnotchangemuchwithage:itwasabout7percentagepointsatage19,andofasimi‐larsizealsoatage21andstillsometenyearslater,atage31(cf.Table2.3c). Second, the share of non‐completers among young women haschangedonlymarginallyacrosscohorts.Amongyoungmen,incontrast,weobserveamarkeddelayincompletionrates,especiallybelowage21,adelaythatseemstohavestrengthenedfurtherintheyoungestcohort.This pronounced difference in early non‐completion rates for youngmenbelongingtothethreeyouthcohortsunderscrutinyislikelytoberelated to the fundamental reform of the Norwegian upper secondaryschoolsystemin1994(Reform94),whichlengthenedthestandarddu‐rationofmostvocational courses from three to fouryears (cf.Box2.4


above).Asyoungmenareoverrepresentedinvocationalprograms,thismaywell explain the delay in completion rates observed for boys be‐longingtothe1998and2003cohortsof16‐year‐olds.

Table 2.3c Norway: Non‐completion rates (%‐shares) at three ages, by gender and cohort


Cohort Young

men

Young

women

Young

men

Young

women

Young

men

Young

women

16‐year‐olds in 1993 31 26 24 19 21 15

16‐year‐olds in 1998 33 24 24 17 n.a. n.a.

16‐year‐olds in 2003 36 27 n.a. n.a. n.a. n.a.


2.3.5 Non‐completionbeyondage21:Sweden

The lowestnon‐completion ratesamong21‐year‐oldsareobserved forSweden (cf. Table 2.2 above). Moreover, as in Finland, they do notchangemuchafterage21(Figure2.2d,uppergraph). In theoldestco‐hort,weseeadeclinefrom14.5%atage21to12%atage26and11%atage 31. A similar evolution is discernible in the two younger cohorts,albeitatnon‐completionratesofaslightlyhighermagnitude.

Acomparisonofnon‐completionratesacrossgendersindicatesthatyoungmenfairworsethanyoungwomenalso inSweden(Figure2.2d,lower graph). Moreover, the gender gap in non‐completion rates in‐creasesovertimeintwocrucialrespects.First,whilethegapisabout3percentagepointsatage21,itincreasesto4.5percentagepointsbyage31 in the oldest (1993) cohort. Second, the gender gap in non‐completionratesshowsanincreasingtrendacrosscohorts. Inthemid‐dle(1998)cohort, it isashighas5percentagepointsatage26,whichmeansadoublingcomparedtothesituationatage21(agapof2.5per‐centage points). A still higher gender gap in non‐completion shares atage21isobservedfortheyoungestcohort(cf.Table2.3d).


Figure2.2d:Sweden:Non‐completionrates(%‐shares)atdifferentages,byco‐hort(uppergraph)andbycohortandgender(lowergraph)


Table 2.3d: Sweden: Non‐completion rates (%‐shares) at three ages, by gender and cohort


Cohort Young

men

Young

women

Young

men

Young

women

Young

men

Young

women

16‐year‐olds in 1993 16 13 13 10 13 8.5

16‐year‐olds in 1998 18 15.5 17 12 n.a. n.a.

16‐year‐olds in 2003 18 14.5 n.a. n.a. n.a. n.a.


2.3.6 Mainfindings

Inthissub‐chapter,wehaveexploredtheprevalenceofnon‐completionof an upper secondary degree in our three country‐specific youth co‐horts.Wenotice that the share of non‐completers among21‐year‐oldsvariesconsiderablyacrossthefourNordiccountriesunderstudy.Atthisparticularage,itisremarkablyhighinDenmarkandcomparativelylowinbothFinlandandSweden.NorwayfallsinbetweenbutismuchclosertoDenmarkthantoFinlandorSweden.Afterage21, theshareofnon‐completersstartsdeclining inall fourcountries,anaspect thatwewillreturn to in Chapter 6. However, the cross‐Nordic differences in non‐completion rates do not disappear despite a declining non‐completionratewithage:FinlandandSwedenhavethelowestnon‐completionrates(10–11%)alsoamong the31‐yearolds, compared to17% inDenmarkand20%inNorway.OuranalysisreportedinChapter6showsthatthesedifferencesarenottrivialwhenitcomestothelabourmarketprospectsofyoungadults.

Fromacross‐cohortperspective,thefourNordiccountriessharethefeature of younger cohorts revealing higher shares of non‐completersamongthe21‐year‐olds. Inotherwords, there isaclear trendtowardsdelayedgraduation fromupper secondary schoolamongNordicyouth.Moreover,thisgrowthinnon‐completionratesacrosscohortsislargelyretainedalsobeyondtheageof21.Putdifferently,ahighershareofnon‐completers among 21‐year‐olds typically results in a higher share ofnon‐completersalsoat laterages,say,among26‐year‐olds.However,aconspicuous exception to this pattern observed across cohorts is Nor‐way showing remarkable delays over time in completion rates amongnotably19‐and20‐year‐olds(atrendrestrictedtoyoungmen,though),whereasthecross‐cohortdifferencesinnon‐completionratesareminorbeyondtheageof20.

Wehavealsoshownthatmuchofthesefindingsforthefullcohortscanbeexplainedbynotabledifferencesbetweenyoungmenandyoungwomen in upper secondary completion rates. In all four countries,we


observelowernon‐completionratesforyoungwomen.Thegendergapsin non‐completion rates tend to be rather small up to age 21, though,andhavechangedonlymarginallyoverthethreecohortsunderscrutiny,exceptforNorwaywheretherehasbeenaconspicuousincreaseinnon‐completionratesamong19‐to20‐year‐oldmalesbelongingtoyoungercohorts. In some of the countries, however, this gender gap in non‐completionratesrevealsanincreasingtrendbeyondage21,atrendthat,moreover,seemstohavestrengthenedovercohorts,againmainlyduetoaworsening situationamongyoungmen.Thisholds true forDenmarkandespeciallyforSweden.Fortheothertwocountries,weobserveonlyasmall(Norway)orevennegligible(Finland)changeovercohortsinthegendergapinnon‐completionratesbeyondage21.

Finally,wehavealsoreasontocontrastournon‐completionratestothosereportedelsewhere.TheNorwegianratesarecomparabletothosereportedbyFalchandNyhus (2009)andBratsbergetal. (2010)whilethe Danish rates are comparable to those reported by Jakobsen andLiversage(2010).OurfindingsarealsocomparabletothoseofBäckmanetal. (2011),who compare dropout rates across theNordic countries,measured seven years after the school start. Our shares of non‐completionratesarealso in linewith thedescriptive informationpub‐lishedbyinternationalbodies,notablyEurostatandOECD.Forexample,the high expected upper secondary completion rates reported by theOECD(seeTable1.4ofChapter1)reflectthefactthatasizeablefractionofyoungnon‐completerscontinuesineducationonafull‐timebasis,andeventually completes anupper secondarydegreeonly later on, that is,after age 21. As shown above, delayed completion of upper secondaryeducation is quite common inNorway and especially in Denmark, butmuchlesssoinFinlandandSweden.

2.4 Individualschool‐to‐workprofiles–ageneralpicture

Sofar,wehavedescribedhowtheoveralldistributionacrossmainactiv‐itiesevolveswhencompulsory‐school‐leavingyouthsgrowolder.Whileprovidinginterestinginformationperse,thisgeneralpicturetellsnoth‐ingaboutyoungpeople’s individualexperiencesafter completingcom‐pulsoryschool.Inotherwords,basedonthisaveragepatternwearenotabletolearnhowsingleindividualsshiftbetweenactivitiesontheirwaythroughtheeducationsystemandtothelabourmarket.Nextwethere‐foredrillonestepdowntoexplorewhat the individualschool‐to‐work


transitionslooklike.Thisisdonebyuseofso‐calledsequenceanalysis.Accordingly,westartbyexplainingthebasicideaofsequenceanalysis.

2.4.1 Sequenceanalysis–abriefoutline

Asalreadynoted, theaveragesharesofyoungpeople indifferentmainactivities, as displayed in sub‐chapter 2.2, cannot inform us about theschoolandlabourmarketexperiencesofindividualyoungstersinthesecriticalyearsfollowingthecompletionofcompulsoryschool.Insteadweneed to look into each young person’smain activity in each year and,basedonthisinformation,constructforeachofthemanindividualpost‐compulsory‐schooltrajectory,that is,asequenceofannualmainactivi‐ties. This individual trajectory then shows inwhich activity the youngpersonhasmainlybeenengagedineachyear investigated.Wetherebyobtainasequenceofmainactivities foreachyoungpersoninourdata.For our present purposes, we restrict these individual trajectories tocoverthe5‐yearperiodimmediatelyfollowingcompletionofcompulso‐ryeducation,thatis,fromage16uptoage20.

Thisideaonwhichoursubsequentanalysisisbasedcanbeillustrat‐edbymeansofa simpleexample.Presume that threeofouryouthco‐hortmembers experience, fromage16up to age20, the following se‐quencesofmainactivities:

Sequenceone: 11121

Sequencetwo: 11211

Sequencethree: 12544

Theyoungperson insequenceone isa full‐timestudent (activity1)atages16,17and18,employed(activity2)atage19,andagainafull‐timestudentatage20.Thepersoninsequencetwoisafull‐timestudentatallages except for age18whenemployed.Theperson in sequence three,finally,isafull‐timestudentatage16,employedatage17,intheresidu‐al inactivity category “other” (activity 5) at age 18 and shows up as apensioner(activity4,ondisabilitybenefit)atage19andalsoatage20.

Inreality,thepotentialcombinationsofactivitiesand,hence,thepos‐sible number of individual sequences are evidently enormous and ac‐cordinglydifficulttohandlewithoutthehelpofsomespecifictechniqueforcategorisingthemintoareasonablenumberofgroups(clusters).Wewill return, inChapter3, to thisclusteringof individualsequencesandthepatternsobtainedforourfourNordiccountries.


Here we next present, separately for each country, the individualpost‐compulsory‐school trajectories of eachyoungperson inour threepooled youth cohorts, starting from their main activity at age 16 andendingwiththeirmainactivityintheyeartheyturned20.Additionally,these sequencesofmainactivities obtained for the full cohortswill becontrastedagainstthoseofnon‐completers,thatis,youngpeoplewhoseonlyformaleducationbyage21isprimaryschool.

2.4.2 Denmark:allvs.non‐completers

Figure2.3aillustratestheindividualtrajectoriesof16‐year‐oldDanesuptoage20whenbasedonpooledinformationonallthreeyouthcohortsunderscrutiny.Theuppergraphhighlightsthesituationforallyoungpeopleinthethreecohortswhilethelowergraphdisplaystheindividualtrajectoriesofnon‐completersonly.They‐axisoftheuppergraphrevealsthat,takento‐gether,thethreeDanishyouthcohortscoveratotalof164,879youngpeo‐ple.Accordingly,thegraphgivesthecombinedoutcomeof164,879individ‐ualtrajectories,whenrankedaccordingtothelengthofeachyoungperson’sunbroken record of years in education straight after leaving compulsoryschool: thosewithallyearsbetweenage16andage20spent in full‐timeeducation appear highest up in the graph and those startingwith a yearoutsideeducationlowestdowninthegraph.Putdifferently,eachrowinthegraphrepresentsanindividualtrajectoryand,whenrankingalltheseindi‐vidualsequencesofactivitiesovertheages16to20accordingtothenum‐ber of the youngster’s initial years spent in post‐compulsory school, theoutcomeforthefullcohortsisthesituationillustratedintheuppergraphofFigure 2.3a. Likewise,when restricting the individual trajectories to non‐completersonly,thelowergraphshowsthattheDanishdatacoversatotalof61,844youngpeoplewithonlyabasiceducationstillatage21,andthattheindividualtrajectoriesofthese61,844youngpeopleadduptothesitua‐tionillustratedinthisgraph.


Figure2.3a:Denmark:Individualschool‐to‐worktrajectoriesfromage16uptoage20forallyoungpeople(uppergraph)andseparatelyfornon‐completers(lowergraph)

Notes: Both graphs are based on pooled information on all three youth cohorts under scrutiny. Non‐

completers refer to young people who still five years after completing their compulsory education

(at age 21) have no upper secondary degree. The vertical axis gives the absolute number of individ‐

ual school‐to‐work trajectories and, hence, the absolute number of young persons covered by the

graph. The upper graph illustrates individual school‐to‐work trajectories for a total of 164,879 young

Danes, the lower graph separately for a total of 61,844 young Danish non‐completers.


How to read the two graphs: Each row (line) represents an individual school‐to‐work trajectory,

starting at age 16 and ending at age 20. At each age point, the young person is observed to be

engaged in one of the five main activities identified (and described in sub‐chapter 2.1). Each row

thus indicates how the young person in question shifts between activities or stays in certain activi‐

ties. For example, the young persons located highest up in the two graphs are in all years, from age

16 up to age 20, enrolled as full‐time students, whereas the young persons situated lowest down in

the two graphs show up in the dumping category of “other” (inactivity) in all these post‐compulsory

school years. Hence, in the upper graph covering all young Danes in our three youth cohorts, the

point of departure is exactly the same as in Figure 2.1a: all young persons’ main activity upon leav‐

ing compulsory school at age 16. While Figure 2.1a illustrates the average share of young Danes in

the five main activity categories at each age point (17, 18, 19 and 20), the upper graph in the above

figure traces each young person’s pathway through these activities up to age 20.

TheoverallimpressionmediatedbythetwographscontainedinFigure2.3a is that the situation looks strikingly similar for all young people(upper graph) and non‐completing young people (lower graph) withlargesharesofbothgroupscontinuingdirectlyinpost‐compulsoryedu‐cationandmovingsmoothlyfromschoolintoworkinglife.Anothercon‐spicuous feature is that while many young Danes occasionally spendyearsoutsidetheeducationsystem,theytypicallyre‐enterschoolbeforetheyturn21.

2.4.3 Finland:allvs.non‐completers

Figure2.3bforFinlandisconstructedinthesamewayastheabovefig‐ureforDenmarkandshould,asaconsequence,alsobeinterpretedinthesame fashion. Hence, taken together the three Finnish youth cohortscoveratotalof193,567youngpeoplehavingexperiencedtheindividualtrajectoriesdisplayedintheuppergraphofthefigure.Thelowergraph,inturn,restrictstheseindividualtrajectoriestothoseyoungpeoplewhostill lack an upper secondary certificate when turning 21 (the non‐completers).Asindicatedbythislowergraph,theirtotalnumberinthedatais34,956.


Figure2.3b:Finland:Individualschool‐to‐worktrajectoriesfromage16uptoage20forallyoungpeople(uppergraph)andseparatelyfornon‐completers(lowergraph)






Finns, the lower graph separately for a total of 34,956 young Finnish non‐completers.









school years. Hence, in the upper graph covering all young Finns in our three youth cohorts, the

point of departure is exactly the same as in Figure 2.1b: all young persons’ main activity upon leav‐

ing compulsory school at age 16. While Figure 2.1b illustrates the average share of young Finns in



The upper graph of Figure 2.3b shows that a largemajority of youngFinnscontinueinpost‐compulsoryeducation,mostlydirectly,occasion‐allyafterabreakyearinotheractivitiesdirectlyfollowingcompletionofcompulsoryschool.Post‐compulsoryeducationtypicallyextendsovera3‐yearperiodbeforemovingintoworkinglife.However,largenumbersof young people continue in education also after this 3‐year period,againeitherdirectlyorafterahiatusinotheractivities.

The situation looks quite different for the non‐completers (lowergraph).Whilemost of alsonon‐completers continue in education aftercompleting compulsory school, either directly or after a break year innon‐educationactivities,theirschool‐to‐worktrajectoriesarecharacter‐ised bymuchmore variation from the very beginning.More precisely,weseelotsofyoungnon‐completersleavingpost‐compulsoryeducationalready after one or two years, while there are also large numbers ofthemstayinginfull‐timeeducationforthreeorfouryearsorevendur‐ingallyearsup toage20,butwithoutcompletinganuppersecondarydegree.Whenleavingpost‐compulsoryeducation,theyendupeitherinemployment or in NEET activities. Noteworthy, however, is that thereseemstobeanpronounceddifferencebetweenthemdependingonhowmany years they spent in post‐compulsory education: the fewer theseyears,themorelikelytheyaretoendupinNEETactivities.Conversely,the more years spent in post‐compulsory education, despite non‐completion of an upper secondary degree, themore likely they are tomoveintoworkinglife.Frequentreturnstoschoolareanotherconspic‐uousfeatureofFinnishyouthfacingnotabledifficultiesincompletinganuppersecondaryeducation.Thenon‐completers’graphalsoshowsthatthereisasmallgroupofnon‐completersmovingstraightintodisabilityarrangementsafterleavingcompulsoryschool.

2.4.4 Norway:allvs.non‐completers

ThecorrespondinggraphsforNorwayaredisplayedinFigure2.3c.Theuppergraphhighlightstheindividualschool‐to‐worktrajectoriesforallyoung people in the three Norwegian youth cohorts, 156,164 in total,


whilethelowergraphagainshowstheindividualschool‐to‐worktrajec‐toriesofnon‐completersonly,46,441intotal.

Figure2.3c:Norway:Individualschool‐to‐worktrajectoriesfromage16uptoage20forallyoungpeople(uppergraph)andseparatelyfornon‐completers(lowergraph)







Norwegians, the lower graph separately for a total of 46,441 young Norwegian non‐completers.








school years. Hence, in the upper graph covering all young Norwegians in our three youth cohorts,

the point of departure is exactly the same as in Figure 2.1c: all young persons’ main activity upon

leaving compulsory school at age 16. While Figure 2.1c illustrates the average share of young Nor‐

wegians in the five main activity categories at each age point (17, 18, 19 and 20), the upper graph in

the above figure traces each young person’s pathway through these activities up to age 20.

Theindividualschool‐to‐worktrajectoriesfortheyoungpeoplecoveredbythethreeNorwegianyouthcohorts(uppergraph)formapatternthatishighlysimilartotheoneobservedforFinlandinthesensethatlargenumbers of young people continue directly in post‐compulsory educa‐tion,typicallystayinfull‐timeeducationforthreeyears,thenmoveintootheractivities(mainlyemployment),butoftenreturntoschoolbeforeturning21.Likewise,andasalso inFinland,manyyoungpeoplespendmostoralloftheiryearsfromage16toage20infull‐timeeducation.

Ontheotherhand,wealsoobservelargenumbersofspellsspentininac‐tivity (outside both education and the labour force) among Norwegianyoungpeopleleavingcompulsoryschool.However,thesespellsseemtobestrongly concentrated to young people staying only a few years in post‐compulsory educationor startingpost‐compulsory educationonly after abreak year. This impression is further strengthenedwhen looking at theschool‐to‐worktrajectoriesofthenon‐completers(lowergraph).Moreover,alsore‐entriesintoschoolamongtheseyoungnon‐completersseemoftentoendinnewspellsspentoutsidebotheducationandthelabourmarket.

OtherwisealsothesituationofNorwegiannon‐completersresemblesstronglythatofFinnishnon‐completers:individualschool‐to‐worktrajec‐toriesformingastaircasewiththeprobabilityofnon‐completersofmov‐ing intoworking life increasing, andof endingup inNEETactivitiesde‐creasingwith the number of years spent in post‐compulsory education.Onlyafewyearsoradelayedstartinpost‐compulsoryeducationincrease,soitseems,substantiallytheriskofencounteringhighbarrierstocontin‐ueineducationandtomoveintoworkinglifealreadyatayoungage.

2.4.5 Sweden:allvs.non‐completers

Finally we turn to the individual school‐to‐work trajectories obtainedbasedondataforthethreeSwedishyouthcohorts.Thepatternsformed


bythesetrajectoriesaredisplayedinFigure2.3d,againseparatelyforallyoungpeople(uppergraph)andfornon‐completers(lowergraph).

Figure2.3d:Sweden:Individualschool‐to‐worktrajectoriesfromage16uptoage20forallyoungpeople(uppergraph)andseparatelyfornon‐completers(lowergraph)







Swedes, the lower graph separately for a total of 46,523 young Swedish non‐completers.








school years. Hence, in the upper graph covering all young Swedes in our three youth cohorts, the

point of departure is exactly the same as in Figure 2.1d: all young persons’ main activity upon leav‐

ing compulsory school at age 16. While Figure 2.1d illustrates the average share of young Swedes in



The dominance of full‐time education is overwhelming (upper graph).MostyoungSwedescontinuedirectlyinpost‐compulsoryeducationandstay there for three years. After this follows a year typically spent inworkinglife,lessofteninNEETactivities.Theemploymentspellusuallyextendsoverseveralyears;onlyoccasionallydoesitendwiththeyoungpersonreturningtofull‐timeeducation.Theactivities followinguponayearspentinNEETactivities,afterthreeyearsinuppersecondaryedu‐cation,aremorevariedwithprolongedinactivitybeingequallylikelyasemploymentorreturntoeducation.

As in both Finland and Norway, large shares of young people alsospendall ormost of their timeup to age20 as full‐time students.Theremainderofindividualtrajectoriesseemstomainlyrepresentdifferentcombinationsofspellsspentinterchangeablyinfull‐timeeducationandNEETactivities.However, this impressionmaywellbe false inviewofthe largenumberofyoungpeoplecoveredby the threeSwedishyouthcohorts: 290,257 in total. Accordingly, the upper graph of Figure 2.3dbecomesintheSwedishcaseextremely“compressed”withtheindividu‐al trajectories so densely packed that they easily cover and, therefore,concealeachother.

Since the total number of non‐completers is substantially lower(46,523),thepatternofearlyschool‐to‐worktrajectoriesismucheasierto assess for this group of young people from graphs like the ones inFigure2.3d.Indeed,theimpressionofnon‐negligiblesharesofcompul‐sory‐school‐leaving Swedish youth spending prolonged spells in NEETactivitiesreceivesfurthersupportfromthelowergraphofFigure2.3d.Otherwiseweobserve,asalsoforFinlandandNorway,astaircase‐typepattern among young Swedish non‐completerswith the probability ofgettingajobincreasing,andtheprobabilityofendingupinNEETactivi‐tiesdecreasingwiththenumberofyearsspentinpost‐compulsoryedu‐cation. Another peculiarity that Sweden shares with Finland concerns


youngpeoplereceivingdisabilitybenefits.First,thereisasmallgroupofnon‐completers showing up as disability beneficiaries straight afterleavingcompulsoryeducation.Anothergroupofyoungpeopleappearstostarttheirpost‐compulsory‐schooltrajectoryoutsidebotheducationand the labour force (in “other” inactivity) before eventually movingontodisabilitybenefits.

2.4.6 Mainfindings

In this sub‐chapterwehavedescribedyoungpeople’s school‐to‐worktrajectories,startingfromthecompulsory‐school‐completingageof16and tracing themup toage20.Apart frompresenting thiskindof in‐formationforallyoungpeople inourthreecountry‐specificyouthco‐horts, we have illustrated the corresponding patterns separately fornon‐completers, that is, young people having only a basic educationstillatage21.

The graphs contained in each country‐specific figure clearly revealthat there is considerablevariation in individual trajectories inall fourNordic countries under study, a variation effectively concealed in theaveragedistributionspresentedinsub‐chapter2.2.Simultaneously,thegraphscontainingallyoungpeople illustrate,onceagain, the impactofthecountries’differentlyorganiseduppersecondaryeducationsystems.Inparticular, inDenmark,whereapprenticeshipshavealongtradition,thetransitionfromschooltoworkseemstobemuchsmootherthaninFinland,NorwayandSweden,whereupper secondary education isor‐ganisedinamore“school‐based”manner.

The cross‐country differences are not equally pronounced when itcomestotheindividualschool‐to‐worktrajectoriesofthenon‐completers.Indeed,inallfourcountries,theearlyschool‐to‐worktrajectoriesofnon‐completers are found to form a “staircase” with young people leavingpost‐compulsory‐school–sometemporarily,someonamorepermanentbasis–atamoreorlesssmoothpace.Moreprecisely,forFinland,NorwayandSweden,theindividualtrajectoriesofnon‐completerspointtoastep‐wiselyoccurringbreakinuppersecondaryeducationwith,broadlyspeak‐ing,approximatelyequalnumbersofnon‐completingyoungpeopleleav‐ingafterone, twoor threeyearsof full‐time studies. Fewerof themarelikely to leaveafterhavingbeenenrolledasa full‐timestudentformorethan threeyears.Nonetheless, they fail to completeanupper secondarydegree(byage21).AnothercommonfeatureofFinnish,NorwegianandSwedish non‐completers is that their probability of getting a job uponleaving post‐compulsory education increases and of ending up inNEET


activities decreases with the number of years initially spent in post‐compulsoryeducation.Hence,inallthreecountries,moreyearsinuppersecondaryeducation,evenwithoutcompletingadegree,seemtoberelat‐edtolessriskyschool‐to‐workprofilesuptoage20.InChapters7and8,wereturntotheirsituationafterage20.

Thesituation looksdifferent for theDanishnon‐completers. Inpar‐ticular, youngDanes turningup as non‐completers by age21 typicallyleavepost‐compulsoryeducationalreadyafteroneor twoyears,whiletheymoreseldomdropoutafterthreeormoreyearsinuppersecondaryschooling.Moreover,alsothoseleavingschoolearlyoftenreturnsoontofull‐timeeducationorsucceed ingettinga jobon,so it seems,aratherpermanent basis. Hence, young non‐completers seem to fair better inDenmarkthanintheotherthreecountries.Inthesubsequentchapters,wewillgomoredeeplyintothismatter.

3. School‐to‐work trajectories:country‐specific clusterresults

Inthischapter,wepresentafirstsetofresultsobtainedby“clustering”the multitude of young people’s individual school‐to‐work transitionpathwayswhenaged16 to20, as reported in thepreviouschapter,byuseofso‐calledclusteranalysis.Accordingly,westartwithabriefout‐lineanddiscussionofthebasicideaoftheclusteranalysismethod.Onlythen do we turn to the results obtained for each country. It is worthstressingfromtheoutsetthattheseresultsareobtainedwhenallowingeachnationaldatasettoformtheclustersforthecountryinquestion.Inotherwords,wedonotrestricttheclusteranalysisinordertoproduceas similar clusters as possible across the four Nordic countries understudy. However, the results underlying the country‐specific clustersreportedbelowareusedaskeyinputsfortheclusteranalysisundertak‐eninthenextchapters,whereweexplicitlyaimatproducingandcom‐paringwhatwehavelabelled“common”Nordicschool‐to‐worktrajecto‐ries(Chapter4)and“stylized”school‐to‐workpathways for theNordiccountries(Chapter5).

3.1 Theclusteranalysismethod–abriefoutline

Inthepreviouschapter,weshowedcountry‐specificgraphsillustratingthemultifacetedschool‐to‐worktransitionpathwaysthatyoungpeoplefollowafterleavingcompulsoryschool.Eachindividualtrajectorypaintsasequence(row)ofmainactivitiesbasedoninformationontheyoungperson’seducationaland labourmarketexperiences fromage16uptoage 20. Thesemain activities, whichwere described inmore detail inChapter 2, include five mutually exclusive statuses: full‐time student,employed, unemployed, disability beneficiary (pensioner) and “other”.As previously indicated, this mutual exclusiveness implies that theyoungpersonisforeachyear(age)assignedonlyonemainactivity.Thisexercise then produces for each young person in our data one single


sequence of activities over the ages 16 to 20. Based on all this infor‐mation on individual school‐to‐work trajectories (sequences of mainactivities),wefinallyallocateouryoungpeopleintoanumberofgroups(clusters)usingclusteranalysistechniques.

Butbeforedescribinginmoredetailthebasicideaoftheclusteranaly‐sismethod,thereisalsoreasontobrieflyreflectonwhyitispurposefulorevennecessarytoformsuchclusters.Aswasevidentalreadyintheprevi‐ouschapter,wecantraceouryoungpeoplealsobeyondtheageof20.Forthe youngest cohort (the 2003 cohort of 16‐year‐olds) we have infor‐mationuptoage21, for themiddlecohort(the1998cohortof16‐year‐olds)uptoage26,andfortheoldestcohort(the1993cohortof16‐year‐olds)uptoage31.Thisinformationonmainactivitieslaterinlifewillbefurtherexploredinthesubsequentchapters,notablyinChapters6and7,withthe focusbeingon threespecificagepoints,viz.age21,26and31.Thehypothesisthenisthatthefuturelabourmarketstatusofyoungpeo‐ple(asindicatedbytheirmainactivities)canbeexpectedtoberelatednotonly to childhood and compulsory‐school experiences but also to theireducational and labour market experiences straight after completingcompulsoryschool. Inordertoinvestigatetheprevalenceofsucharela‐tionship, it isnecessarytoclusterallyoungpersonsinareasonablewaybasedontheireducationalandlabourmarketexperienceswhenaged16to20,asmeasuredbytheirearlyschool‐to‐worktrajectories.Forsuchaclusteringtomakesense, the formedgroupsneedtocontainyoungper‐sonswho are highly similarwith respect to their early educational andlabourmarketexperiencesaftercompletingcompulsoryschool.

3.1.1 Step1:Sequences

Indescribingtheclusteranalysismethod,wedepartfromtheoutlineofthesequenceanalysismethodinChapter2andbybuildingontheexam‐pleusedinthatcontext.Inparticular,wepresumethatthreeyouthco‐hortmembers experience, fromage16up to age20, the following se‐quencesofmainactivities:

Sequenceone: 11121 Sequencetwo: 11211 Sequencethree: 12544


Theyoungpersoninsequenceoneisafull‐timestudent(activity1)atallages up to 20, except for age 19when the person spentmost time inworking life (activity 2). The situation is similar for the person repre‐sentingsequencetwo,exceptthattherowoffull‐timeeducationyearsisinterrupted by a spell in employment one year earlier, at age 18. Theperson in sequence three, in contrast, continues in post‐compulsoryeducation for one year only, moves into working life at age 17, with‐drawsfrombotheducationandthelabourmarket(activity5)atage18,andshowsupasapensionerondisabilityarrangements(activity4)atage19andstillatage20.

Needlesstosay,thealternativetrajectories(sequencesofmainactiv‐ities)thatayoungpersonmayfollowarehugeinnumber.Thereasonissimple:fromoneagetothenext–e.g.fromage16toage17–theyoungpersoncaninprinciplemakefivedifferentmoves:stay inthesameac‐tivityormoveintooneoftheotherfourmainactivities.Accordingly,thetotalnumberofpossiblecombinationsofmainactivitiesoverfiveages,from16to20,isnolessthan3.125(5x5x5x5x5=3.125).

Thereal‐lifenumberofalternativetrajectoriesfromage16uptoage20ismuchsmaller,though,asisalsoevidentfromthecountry‐specificgraphspresentedinsub‐chapter2.4above.ForthethreeDanishyouthcohorts under scrutiny we can identify a total of unique 813 post‐compulsory‐school sequences, implying that the different trajectoriesfollowedbythe164,879youngDanesbelongingtothesethreecohortsrepresentaboutone‐fourth(813/3,125)ofallpossiblecombinationsofmain activities over these five age points. The number of actually ob‐served trajectories is 1,322 forFinland, 1,071 forNorwayand767 forSweden.Accordingly,youngDanesandSwedesaremorelikelytofollowhighlysimilarpost‐compulsory‐schooltracksthanareFinnishandNor‐wegianyouth.

However,alsothesenumbersofactuallyobservedtrajectoriesaresohighthatitisimpossibletodescribeandanalyseeachofthemseparate‐ly.Amajoraimoftheclusteranalysismethodistoobtainanoverviewoftransitionpatternsbyreducinglargenumbersofreal‐lifesequencestoasmallernumberofclassificatorycategoriesofsequences.


3.1.2 Step2:Substitutionsanddistancesbetweensequences

Inourexample,wehavethreesequencesandthenextstepwill,conse‐quently,beto formclusters fromthesesequences.Asdescribedabove,theeducationaland labourmarket experiencesof the twopersons fol‐lowingsequenceoneandsequencetwoarealmost identical:both indi‐viduals spend most of their early post‐compulsory years in full‐timeeducation,exceptforatemporarymoveintoworkinglife.Theonlydif‐ferencebetween the twopersons is the timingof thisbreakbeforere‐turningtoeducation.Thetrajectoryfollowedbythethirdpersonisverydifferent: early school leaving and disability arrangements already atage19.Hence, the early educational and labourmarket experiences ofthepersonsfollowingsequencesoneandtwoarehighlydifferenttotheeducationaland labourmarketexperiencesof theperson followingse‐quence three. Put differently, there is a large distance from sequencesoneandtwotosequencethree,butasmalldistancefromsequenceoneto sequence two. Intuitively, sequencesone and two should, therefore,gointooneclusterandsequencethreeintoaseparatecluster.

However,whenallocatinglargenumbersofindividualtrajectoriesin‐toareasonablenumberofclusters,weneedtobeable tomeasure thedistancesbetweensequencesinaneasybutreasonableway.Inourex‐ample, thismeasureshould thenbesmall for thedistancebetweense‐quencesoneandtwo,andlargeforthedistanceofthesetwosequencestosequencethree.Onewayofmeasuringthedistancebetweentwose‐quences is to count thenumberof substitutions required for changingonesequenceintotheothersequence,andthenusethenumberofsub‐stitutions needed as a measure of the distance between the two se‐quences.Box3.1illustratesthisideaforourthreeexamplesequences.


Box3.1Calculatingsubstitutionsanddistancesbetweensequences,anexample

Formeasuringthedistancebetweensequenceoneandsequencetwobelow,we

needtoconvertsequencetwosothatitbecomesidenticaltosequenceone.

Sequenceone: 11121

Sequencetwo: 11211

Sequencethree: 12544

Thetwosequencesdifferfromeachotherintworespects.First,thethirdelement

(activity) in sequence two contains a 2 (employed) while the third element in

sequenceonecontainsa1(full‐timestudent).Hence,weneedtosubstituteactivity

2 in sequence twowith activity 1. Second, the fourth element in sequence two

containsa1whilethefourthelementinsequenceonecontainsa2,whichrequests

asubstitutionofactivity1insequencetwowithactivity2.Thesetwosubstitutions

haveconvertedsequencetwointosequenceone.Asimilarconversionofsequence

twointosequencethreewoulddemandfoursubstitutions.

Next,thethreesequencesinourexamplearegroupedintoclustersaccord‐

ingtothemeasureddistancebetweenthem.Thedistancebetweensequenceone

andsequencetwoistwo,whereasthedistancefromsequencethreetobothof

thesesequencesisfour.Sequencesoneandtwowouldthusgointoonecluster

andsequencethreeintoaseparatecluster.Thisclusteringreflectstheintuitive

notion that there is a largedifferencebetweensequencesoneand two,on the

onehand,andsequencethree,ontheotherhand.

Itmayalsobenotedthatanotherwayofconvertingonesequence intoan‐

other is to delete elements and insert elements. Instead of a substitution, one

elementinasequencecouldbedeletedandanotherelementinserted.Thecosts

oftheseoperationsarecalledInDelcosts(InsertandDelete).Forourpurposes,

there isnogain inapplying insertionsanddeletions,whereasadistinctionbe‐

tweensubstitutions,deletionsand insertionsmightbeveryuseful inotherap‐

plications(e.g.whenthesequencestakeplaceoverdifferenttimeintervals).


The literatureuses thenotion“costs” forconvertingonesequence intoanother.IntheexampleoutlinedinBox3.1,wehavesetthe“cost”ofallsubstitutionsequaltoone.However,thecostofconvertingoneelement(activity)ofasequenceintoanothercouldalsobesettoalargernumber(thanone),ifthedifferencebetweenthetwostatusesisconsideredtobelarge. For example, if it is a common and natural phenomenon thatyoung people move frequently between the statuses “student”, “em‐ployed” and “unemployed”, then the costs of moving between themcouldbeseentobelowand,hence,settoone.Likewise,ifatransitionofyoungpeoplefromtheseactivitiesintothestatusof“pensioner”or“oth‐er”isconsideredtobealesscommonandnaturalphenomenon,thenthecostsofsuchmovescouldbesethigher,say,totwo.Alsomorecomplexsystemshavebeenused in the literaturewitheachmovebetweendif‐ferentstatutesassignedadifferentcost.Inouranalyses,werelyonthedefaultofapplyingunitcostsforallsubstitutionsnecessaryformakingsequencesidentical.Wedidexperimentwithdifferentcostsfordifferenttypesof substitutions,but soonrealised that the results fromapplyingunitcostsaremorestraightforwardtointerpret.

3.1.3 Step3:Formingclustersofsequences

Abovewedescribedhowtocalculatethedistanceorsimilaritybetweensequences. In a final step, thesedistances are used to form clusters ofsequences. In our subsequent analyses,we have applied two differentprocedures: clusters formedbyoptimalmatching2andclusters formedbyreferencesequences.Themainreason forapplyingbothmethods isthattheyhaveadvantagesaswellasdisadvantageswhenitcomestothetypesofanalysesperformedandreportedinthisvolume.Nextwegiveabriefdescriptionofthesetwoclusteringprocedures.SomemoredetailsareprovidedinBox3.2.

──────────────────────────2Itshouldbenotedthattheterm“optimalmatching”isusedin(atleast)threesensesintheliterature.Onesenseisourapplicationofthetermasdescribedinthissub‐chapter,thatis,asamethodforformingclustersbyanalgorithmthatinsuresthatthedistancebetweenthesequenceswithinclustersisassmallaspossibleandthatthedistancebetweenclustersisaslargeaspossible.Anothersenseofthetermincludesalltypesofclusterformationonthebasisofdistancesbetweensequences.Inthissenseoftheterm,clusterformationbyreferencesequencesisasub‐categoryofoptimalmatching.Athirdsenseofthetermincludesboththeformationofdistancesbetweensequencesandtheformationofclustersintothetermofoptimalmatching.Somestudiesusethetermoptimalmatchinginmorethanoneofthesethreesenses.Thecontentofitisnormallyclearfromthecontext,though.


Box3.2Formingclustersbyoptimalmatchingandreferencesequences,anexample

Optimalmatching

This standardmethod for forming clustersof sequencesof activitiesmeans that

sequencesare“matched”witheachothertoformclustersusingan“optimal”pro‐

cedureinthesensethatthedistanceissmallbetweenthesequencescontainedin

sameclusterandlargebetweenthesequencesallocatedintodifferentclusters.

If forming two clusters by optimal matching based on our example with

threesequences,theresultwillbeoneclusterwithsequenceoneandsequence

two and another cluster with sequence three, because the distance between

sequences one and two is smaller than theirdistance to sequence three. Ifwe

extendthenumberofsequencesfromthreetofourwhileretainingthenumber

ofclusters(two),thisadditionalsequencewilleithergointotheclustercontain‐

ing sequences one and two or into the cluster containing sequence three, de‐

pendingonitsdistancetothesequencesinthetwoclusters.

Referencesequences

Thebasic ideawhenformingclustersbyuseofreferencesequences isthatthe

clustersarebuiltaroundpredefinedreferencesequences.

In our examplewith three sequenceswe could pick sequence one and se‐

quencethreetobereferencesequences.Thelastsequence,sequencetwo,isthen

to be allocated to the cluster where the reference sequence has the smallest

distance to sequence two, implying that sequence twowill go into the cluster

withsequenceoneasthereferencesequence.Afourthsequencewouldbeallo‐

catedtotheclusterwithsequenceoneasthereferencesequence,ifthedistance

from this fourth sequence to sequence one is smaller than its distance to se‐

quencethree,andtotheclusterwithsequencethreeasthereferencesequence,

if thedistance from this fourth sequence to sequence three is smaller than its

distance to sequence one. This procedure is, of course, repeatedwhen adding

further sequences: the distance to sequence one and the distance to sequence

three is calculated for all additional sequences and each of them is allocated

either into the cluster defined by sequence one or the cluster defined by se‐

quence three, dependingonwhichoneof the twodistances is smaller. Cluster

formationsonthebasisofmorethantworeferencesequencesareconstructedin

anidenticalway.


Optimalmatchingisarelativelyrecentprocedure3buthas,nonetheless,cometobethestandardmethodusedintheliteratureforformingclus‐ters.Thismethodformsclustersofsequenceswhichareoptimalinthesense that thedistancebetween thesequencesallocated into thesameclusterisassmallaspossible.Inotherwords,thesequencescontainedineachclusterarehighlysimilarwiththedistancebetweenthembeingminimised. Conversely, thedistancebetween sequences going intodif‐ferentclustersismaximised,thatis,aslargeaspossible.

Weuseoptimalmatching forproducingclustersseparately foreachof the fourNordiccountriesunderstudy,andrefertotheseclustersas“country‐specific clusters”. Inparticular, foreachcountryweallowthenationaldatasettoformatotaloftenclusters.Whiletheseclusterscanbeformedinseveralwaysandbyuseofalternativeprocedures,wepre‐fertoapplythecommonprocedureinsocialsciences,viz.theso‐calledNeedleman–Wunschalgorithm(seeBrzinsky‐Fayetal., 2006). Inbrief,thisalgorithmfirstdividesthesequencesintotwoclusters.Thenitsub‐divideseitheroneofthetwoclustersintotwosub‐clusters,givingatotalofthreeclusters.Next,thealgorithmsubdividesoneofthesethreeclus‐ters into two sub‐clusters, giving a total of four clusters, and so forth.The algorithm stopswhen it has reached the pre‐specified (by the re‐searcher)numberofclusters.Thetenclustersproducedforeachcoun‐tryusingnationaldataarepresentedintherestofthischapter.

Thebasic ideaofclusteringbyreferencesequences is that theclus‐tersareformedaroundgivenreferencesequences.Intheliterature,thisprocedure for forming clusters is, therefore, sometimes referred to asformingclustersaround“ideal”sequences,“typical”sequencesor“ideal‐typical” sequences.4 When matching by reference sequences, each se‐quenceisallocatedtotheclusterwherethedistanceofthesequencetothe reference sequence is smallest. In other words, first a number ofreference sequences need to be identified and only then are the other

──────────────────────────3ThefirstalgorithmtoperformoptimalmatchingwasdevelopedbytheRussianmathematicianVladimirLevenshteinanditsfirstscientificapplicationwasinmicrobiology,fortheanalysisofDNAsequences.Se‐quenceanalysisandoptimalmatchingwereintroducedintothesocialsciencesbytheAmericansociologistAndrewAbbot(seeAbbott,1983;AbbottandForrest,1986).Inarecentreviewoftheuseofoptimalmatch‐inginsociology,23applicationsoftheprocedurewerefoundinsociologicalstudies(seeMartinandWiggins,2011,p.386).4Incontributionswherethereferencesequenceisdeductedfromtheoreticalconsiderations,oftenofsocio‐logicalorigin,theterm“ideal”sequenceissometimesused.Someauthorsfirstperformoptimalmatching,thentheytrytofindsequencesthatarerepresentativeortypicalfortheclustersand,finally,theyusetheserepresentativesequencesforfurtheranalysis.Insuchcases,theterm“typical”sequenceissometimesused,seeMartinandWiggins(2011).


sequencesclusteredaroundthesereferencesequencesaccordingtothedistance(similarity)betweenthem.Thisproducesanumberofclusterswhichcontainssequencesthatareassimilaraspossibletothereferencesequence of the cluster. This procedure is, in effect, followed in Chap‐ter5,wherewestartoutbyspecifying16referencesequences.Wethenapplythesesamereferencesequences ineachof the fourNordiccoun‐trieswhenformingclusters,thatis,whenallocatingyoungpeople’searlyschool‐to‐work trajectories across the 16 reference sequences. Henceandincontrasttothecountry‐specificclustersreportedlateroninthischapter,clusteringbyreferencesequencesallowsustoformclustersinthesamewayacrossall fourcountries:aparticularsequenceobservedintwoormoreoftheNordiccountriesis,ineachcountry,allocatedintoexactlythesamereferencesequencecluster.5Thisalso impliesthatweareable to compare themagnitudeofdistinct school‐to‐work trajecto‐riesacrossthefourcountries.

In this context it may also be noted that we have used one moremethod to form cross‐country comparable clusters. In particular, foreach countrywe havemade a list of the sequences identified and thenumber of young people following each of these sequences. Then wehavepooledthiscountry‐specificinformationintoonebigdataandap‐plied optimalmatching to form clusters of sequences. Also this proce‐dureguaranteesthatsequencesobservedinmorethanonecountryareallocated into exactly the same clusters. In this sense, the clustersformedare“common”forthefourNordiccountriesunderstudy.ResultsobtainedfromusingthismethodarereportedinChapter4.

──────────────────────────5WeapplytheStataprogramtodoalltheanalysesreportedinthisvolume.However,Statadoesnotcontainamoduleforclusterformationbyreferencesequences,forwhichreasonwehavewrittenaprogramtoperformthisprocedure.Inmanyapplicationsofclusterformations,theproblemof“ties”arises,thatis,asequencehasthesamedistancetotwoormoreclusters.The“solution”tothisproblemistoallocatethesequencerandomlytooneoftheclusterstowhichthesequencehasthesamedistance.Wehavewrittenourreferencesequenceprogramsothatiftheprogramrandomlyallocatesasequencetooneparticularclusterine.g.Finland,thenthissequenceisrandomlyallocatedtoexactlythesameclusteralsointheotherthreeNordiccountries.


3.2 Country‐specificclusterresults:allyoungpeople

Nextwe turn to the country‐specific clusters obtainedwhen formingclustersbasedonthenationaldatasetsbyuseofoptimalmatching,asdescribed above. More precisely, we use this standard clusteringmethod to group, separately for each country, the large numbers ofindividualschool‐to‐worktrajectoriesdisplayedinFigures2.1ato2.1dof Chapter 2.Accordingly, the country‐specific clusters presentedbe‐low reflect the situation when pooling the information on all threeyouthcohorts.Inotherwords,weuseourfulldatasetswithoutdistin‐guishing between cohorts, gender or completers vs. non‐completerswhen forming these clusters. And, as indicated above, we allocateyoung people’s early school‐to‐work trajectories into a total of tenclusters,whichwefound–afteranumberofexperiments– tobethebestchoice forourpurposes, that is, forunravellingalsorisky transi‐tionprofilesofyoungpeopleleavingcompulsoryschool.

3.2.1 Denmark

ThepatternobtainedforDenmarkwhenallocatingyoungDanesintotenclustersbasedontheirearlyeducationalandlabourmarketexperiences(asmeasuredbytheirsequencesofmainactivities) isdisplayedinFig‐ure3.1andbrokendowninTable3.1.EachofthetengraphscontainedinFigure3.1highlights thesequencesofmainactivities that theyoungpeopleallocated into thatparticularclusterhave followed fromage16uptoage20.Asisalsotobeexpected,eachclusterisclearlydominatedby certain types of school‐to‐work trajectories showing conspicuoussimilaritiesincrucialrespects.Theverticalaxisofeachgraphgivestheabsolutenumberofyoungpersonsinthecluster.Ontopofeachgraph,thereisanumberinbracketedparenthesesandapercentageshare.Thenumberreferstothenumberoftheclustergivenbythealgorithmcreat‐ingthetenclusters(accordingtothesubdivisionproceduredescribedintheprevioussub‐chapter).Thepercentageshare,inturn,showsthesizeofeachclusterasmeasuredbytheshareofyoungpersonscontainedinthecluster.

Thefirstcluster(cluster1) isalsothe largest,containingmorethanthree‐fourths (76.3%) of the young people in the three Danish youthcohortsunderscrutiny.Allofthemarestudentsatage16,afterhavingleftcompulsoryschool,andmostofthemcontinueinfull‐timeeducationalsoatage17andstillatage18,forwhichreasonthisclusterislabelled“studytrack”.Atage19and20,largesharesofthemareemployed.Oth‐


ercharacteristicsoftheclusterarethatitcontainsaslightlylargershareoftheyoungwomen(77%)thanoftheyoungmen(75.6%),andalsoaslightly larger share of young people from the oldest (1993) cohort(78.1%)thanfromthetwoyoungercohorts(about75%).Table3.1alsoshows that the cluster covers about 88% of the young Danes havingcompletedanuppersecondarydegreebyage21,withthecorrespond‐ingsharebeing56%foryoungDaneswithnopost‐compulsorycertifi‐catestillatage21.

Figure3.1:ClusteringofyoungDanes’individualschool‐to‐worktrajectoriesfromage16uptoage20intotengroups,usingclusteranalysisonpooledinformationforallthreeyouthcohorts

Notes: The clustering concerns individual school‐to‐work trajectories of young Danes when aged 16

to 20, as displayed in Figure 2.1a of Chapter 2, using the optimal matching methodology described

in sub‐chapter 3.1. The vertical axis of each graph gives the absolute number of young persons in

the cluster, whereas the percentage share on top of each graph shows the relative share of young

people in the cluster. The total number of young people is 164,879. The number in bracketed pa‐

rentheses on top of each graph refers to the number given by the algorithm creating the ten clus‐

ters by means of the subdivision procedure described sub‐chapter 3.1. For more details on each

cluster, see Table 3.1 below.


Table 3.1: Distribution (%‐share) of young Danes across the ten clusters displayed in Figure 3.1, by gender, cohort and completion/non‐completion of an upper secondary degree by age 21

Cluster:

number – %‐share – label

Gender Cohort of 16‐year‐olds Post‐compulsory

degree by age 21

Male Female 1993 1998 2003 Yes No

[1] – 76.3% study tracks 75.6 77.0 78.1 75.5 75.2 88.4 56.0

[2] – 0.2% pensioner tracks 0.3 0.2 0.0 0.3 0.4 0.0 0.7

[3] – 3.7% early inactivity tracks 3.2 4.2 3.4 3.9 3.7 1.8 6.8

[4] – 2.1% inactivity tracks 1.9 2.4 2.0 2.0 2.3 0.2 5.3

[5] – 4.8% very early inactivity tracks 4.6 5.0 2.1 5.4 6.8 3.8 6.4

[6] – 1.5% study/unemployment tracks 1.4 1.6 1.9 1.3 1.3 0.3 3.6

[7] – 0.5% inactivity/unempl. tracks 0.4 0.5 0.3 0.5 0.6 0.0 1.2

[8] – 0.0% early unemployment tracks 0.0 0.0 0.0 0.0 0.0 0.0 0.1

[9] – 8.7% early employment tracks 9.8 7.6 10.2 8.8 7.2 4.0 16.7

[10] – 2.2% very early employment tracks 2.8 1.5 1.9 2.2 2.4 1.5 3.2

Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0

%‐share in the pooled dataset 51.7 48.3 34.4 31.0 34.6 62.6 37.4

Notes: See Figure 3.1 above.

Thesecondlargestcluster(cluster9)contains8.7%oftheyoungpeopleinthethreeDanishyouthcohorts.Themostconspicuousfeatureoftheseyoungpeopleisthatallofthemareinworkinglifeatage17.Largesharesof them return to education, though,while the rest of them continue inemployment or move outside both education and the labour market(“other”).Cluster10issubstantiallysmaller(2.2%)buthighlysimilar tocluster9 in the sense that all youngpeople contained in the cluster areemployed,althoughalreadyatage16(insteadofage17asincluster9).Mostyoungpeopleincluster10have,however,returnedtoeducationbyage 17, but with a non‐negligible share also continuing inworking life.Table3.1showsthatboththeseclusterscoveralargershareoftheyoungmen thanof the youngwomen.Moreover,while the cluster10 typesoftrajectoriesrevealaweakincreaseovercohorts(from1.9%upto2.4%),theshareofyoungpeoplefollowingthecluster9typesoftrajectorieshasdecreasedover time(from10.2%downto7.2%).Taken together, thesetwo clusters cover slightly more than one‐tenth of the three cohorts’young people, but asmuch as one‐fifth of the young people lacking anupper secondarydegree still at age21. It is alsonoteworthy that about87%ofyoungDanescompletingcompulsoryschoolfollowtrackscharac‐teristicofthethreeclustersdiscussedsofar(clusters1,9and10),allofwhicharedominatedbystudyingandworking.


Figure3.1further indicatesthatcluster3 issimilartocluster9,butwithallyoungpeoplebeingoutsidebotheducationandthelabourforce(inactive)atage17,insteadofbeingemployedasincluster9.Moreover,beyond the ageof 17, these cluster3 youngstersdonot seem tobe inworkinglifetothesameextentasthecluster9youngsters.Thesettingisidenticalwhencontrastingcluster5tocluster10:cluster5issimilartocluster 10, but with all cluster 5 youngsters being inactive at age 16,insteadofbeingemployedasincluster10.Table3.1showsthatcluster3andespeciallycluster5haveincreasedinmagnitudeoverthethreeco‐horts. Taken together, these two clusters comprise 8.5% of the youngpeopleinthethreeDanishyouthcohorts,withbothofthemcoveringaslightlylargershareofyoungwomenthanofyoungmen.Whenaddingthispercentagesharetothatofclusters1,9and10, thesefiveclustersturnouttocoveralmostall(95.7%)youngDanes.

Accordingly, theremaining fiveclustersareverysmall insize,com‐prisinglessthan5%ofDanishyouth.Clusters6and7aresimilarinthesense that nearly all youngpeople contained in these two clusters areunemployed at age 18. A main difference between the two clusters,however, is thatmost cluster 6 youngsters studied at ages 16 and 17whilemost cluster 7 youngsterswere outside both education and thelabourmarketat theseages.Despite thisdifference,however,asignifi‐cantshareofboththecluster6andthecluster7youngstersremainun‐employed also after age 18 with few returning to full‐time education.Instead, these youngsters face a high risk ofwithdrawing from the la‐bourmarket, into inactivity.Takentogether, thesetwoclusterscontain2%ofDanishyouth.Asimilarsharegoesintocluster4,whichcomprisesyoungpeoplewhowereinactivewhenaged17and18.Cluster2,inturn,containsyoungpeoplewhomoveintodisabilityarrangements.Cluster8,finally,containslessthan0.05%ofthethreecohorts’youngpeopleandis,therefore,overlookedinthiscontext.

All inall, amainoutcomeofapplyingoptimalmatching to the indi‐vidualschool‐to‐worktransitionsofDanishyouthisthatanoverwhelm‐ingmajorityfallsintothreespecificclusters:amajorityfollowsstandardstudytracks,asmallgroupleavestheeducationsystemforemploymenteither at age 17 or already at age 16 upon completing compulsoryschool,whereasathirdgroupleavestheeducationsystemforinactivityeither at age 17 or straight after compulsory school. Taken together,theseclusterscoveralmost96%ofDanishyouth.


3.2.2 Finland

The ten clusters obtained fromusing optimalmatching on the Finnishdata covering all three cohorts of 16‐year‐olds are displayed inFigure3.2.As for theotherNordic countries, themost conspicuous featureofthesetenclustersistheoverwhelmingdominanceoftheso‐calledstudytrack (cluster 1): close to 80% of compulsory‐school‐leaving Finnishyouthgointothisparticularcluster,thedominantfeatureofwhichisatleastthreeyearsinuppersecondaryschoolstraightaftercompletionofbasic education.Moreover, as shown in Table 3.2, the share of young‐stersmovingearly intoeducation‐dominatedtrackshas increasedovertheyears,fromabout75%forthe1993cohortto83%forthe2003co‐hort.And,needlesstosay,most(86.5%)youngpeoplehavingcompletedanupper secondarydegreeby age21 appear in this particular clusterwith the corresponding share for non‐completers being substantiallylower(about42%).

The other nine clusters are throughout of substantially smallerimportanceinthesensethattheycontainmuchfeweryoungpeople.Indeed,allofthemhaveasharebelow5%,exceptforcluster9withashare of 9.5%. However, taken together they covermore than one‐fifthoftheyoungpeoplebelongingtothethreeFinnishyouthcohortsunderscrutiny.

Abouthalfoftheseclustersinvolveaconsiderableamountofstudy‐ingonafull‐timebasis(notablyclusters2,4,5,8and9)whiletherestofthem are dominated by non‐study activities (clusters 3, 6, 7 and 10).Anotherwayofcharacterisingthesenineclusters istodepart fromtheyoung person’s main activity straight after completion of compulsoryschool. Then we see that some 3–4% continue directly in post‐compulsoryeducationbutdropoutafteroneortwoyearsandbecomeunemployed(cluster2andpartlycluster7)whileasimilarsharedropsout and start working (a majority of those in cluster 5) or withdrawfrombotheducationandthelabourmarket(cluster8).However,manyoftheseyoungpeopledore‐entereducationbeforetheyturn20,butfarfromallofthem.


Figure3.2:ClusteringofyoungFinns’individualschool‐to‐worktrajectoriesfromage16uptoage20intotengroups,usingclusteranalysisonpooledinformationforallthreeyouthcohorts

Notes: The clustering concerns individual school‐to‐work trajectories of young Finns when aged 16

to 20, as displayed in Figure 2.1b of Chapter 2, using the optimal matching methodology described

in sub‐chapter 3.1. The vertical axis of each graph gives the absolute number of young persons in

the cluster, whereas the percentage share on top of each graph shows the relative share of young

people in the cluster. The total number of young people is 193,567. The number in bracketed pa‐

rentheses on top of each graph refers to the number given by the algorithm creating the ten clus‐

ters by means of the subdivision procedure described sub‐chapter 3.1. For more details on each


Table 3.2: Distribution (%‐share) of young Finns across the ten clusters displayed in Figure 3.2, by gender, cohort and completion vs. non‐completion of an upper secondary degree by age 21

Cluster:



degree by age 21


[1] – 78.5% study tracks 76.7 80.3 74.9 77.8 83.0 86.5 41.9

[2] – 3.1% dropout/unemployment tracks 3.6 2.6 6.5 2.1 0.6 2.1 7.6

[3] – 0.6% disability‐benefit tracks 0.7 0.6 0.5 0.7 0.6 0.0 3.4

[4] – 0.3% disability/delayed‐study tracks 0.3 0.3 0.7 0.2 0.0 0.2 0.8

[5] – 4.2% study/employment tracks 4.2 4.1 5.7 4.1 2.5 3.5 7.3

[6] – 1.0% employment tracks 1.2 0.8 1.7 0.9 0.4 0.6 2.8

[7] – 0.8% study/unemployment tracks 0.9 0.8 1.5 0.6 0.3 0.3 3.1

[8] – 1.0% study‐inactivity‐mix tracks 0.8 1.2 0.1 1.9 1.1 0.5 3.4

[9] – 9.5% inactivity/delayed‐study tracks 10.5 8.5 7.5 10.5 10.7 6.1 25.2

[10] – 1.0% inactivity/employment tracks 1.0 0.9 0.9 1.2 0.8 0.2 4.4

Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0




Stillanothergroupofyoungpeoplespendsthefirstyearaftercompulso‐ry school outside education:working (part of cluster 5), in unemploy‐ment(partofcluster7),ondisabilitybenefits(cluster4)orinotherin‐activity(cluster9).Inotherwords,manyyoungpeopledelaytheirmoveintopost‐compulsoryschoolingforonereasonortheother.Butabreakyearaftercompletionofcompulsoryeducationdoesnotalways inspiretheyoungpersontore‐enterschool:anon‐negligiblesharestayinnon‐educationactivitieswithfew,ifany,schoolingyearsbreakingthistrack(notablyclusters3,6and10).

Allinall,theclusteringofyoungFinns’individualschool‐to‐worktra‐jectoriesup to age20 into a total of ten groups identifiesbasically fourbroad categories of young people: (1) those who continue in post‐compulsoryeducationspendingmostoftheirtimeuptoage20bystudy‐ingonafull‐timebasis;(2)thosewhocontinueinpost‐compulsoryeduca‐tion and drop out after one or two years butwho eventually, albeit farfromalways,re‐entereducationbeforeturning21;(3)thosewhocontin‐ue in post‐compulsory schooling after having spent typically one yearoutside education straight after compulsory school; (4) those who stayoutsidetheeducationsystemafterhavingcompletedcompulsoryschool.

Moreover,acomparisonofyoungmenandwomenrevealsthatthereareonly smalldifferences in theirdistributionsacross the tenclusters (Table3.2). Simultaneously these sharesalso indicatewhichclustersare slightlymorefemaleormaledominated.Thereasonforthisissimple:theFinnishdatacontainsalmostequallymanyyoungwomenasyoungmen(thefemaleshare is 48.7% and the male share accordingly 51.3%). Hence, a lower(higher) female share in Table 3.2 is also an indication of youngwomenbeingslightlyunderrepresented(overrepresented) in thatparticularclus‐ter.Theclearestoverrepresentationofyoungwomenoccurs forcluster8whiletheirclearestunderrepresentationconcernsclusters2and6.

When it comes to the distribution across the ten clusters of youngpeoplebelonging to the three cohortsunder study,Table3.2points toseveral trends. As for themale–female distribution shares, the cohortsharesmay be interpreted as also reflecting the relative share of eachcohortinthetenclustersforthesimplereasonthatthethreecohortsareofapproximatelyequalsize,eachcoveringaboutone‐thirdofthepooleddataset(seeTable3.2).Forafewclusters,wecanobserveanincreasingshareover the threecohorts implying that theyoungest (2003)cohorthasamoredominantrole in thecluster thantheoldest (1993)cohort.Thisholdstrueespeciallyforthestudytrack(cluster1)butalsoforclus‐ters involvingearlyyears spentoutsidebotheducationand the labourmarket(clusters8and9).Alongsidethereareseveralclustersshowinga


declining share over the three cohorts, notably clusters related to em‐ployment(clusters5and6),unemployment(clusters2and7)anddisa‐bilitybenefits(cluster4).Thedecliningtrendsinrelationto(registered)unemployment and disability benefits are most probably explainedmainly by changes in the institutional setting, whereas the decline inemploymentmaybeseenasalogicalconsequenceofagrowingshareofyoung people staying in full‐time education. Only two clusters revealmoreor lessunchangedsharesacross thethreecohorts,bothofwhichinvolveminor,ifany,post‐compulsorystudies(clusters3and10).

Table3.2alsoprovidesinformationonthedistributionofcompletersand non‐completers across the ten clusters, with the non‐completersagain referring to those young people still lacking a post‐compulsorydegree by the time they turn 21. Not surprisingly, the completers aremainly distributed across clusters representing education‐dominatedtrajectories.However, strikingly largenumbersof alsonon‐completersseemtobeheavilyengagedinfull‐timestudies,althoughquiteafewofthemshowupalsoinclusterscontainingratherriskytrajectories.

All in all, young Finns seem to follow quite different post‐compulsory‐school trajectories up to age 20. However, this clusteringexercisealsorevealsdistinctpatternscharacterisingyoungFinns’earlyeducationalandlabourmarketexperiences.Inparticular,aboutnineintencontinue ineducationeither immediatelyaftercompletingcompul‐soryschoolorafterayearspentinnon‐educationactivities,andmostofthem continue in higher education or move successfully into workinglife. The rest of young Finns follow various employment dominatedtracksafter leaving compulsory school, but alsohigh‐risk tracksdomi‐natedbytimespentinNEETactivities.

3.2.3 Norway

The ten Norwegian clusters obtained from pooled information on thethree youth cohorts under scrutiny are displayed in Figure 3.3. Thestudytrack(cluster1)isthebyfarmostdominantclusteralsoforNor‐way,comprising87%ofNorwegianyouthandwithaboutthesamepro‐portion (86%) of youngmen and youngwomen going into the cluster(Table3.3).Theclusterconsistsforthemostpartofyoungpeoplewhostay forat least threeconsecutiveyears inpost‐compulsoryeducation.As is evident fromTable 3.3, the study‐track cluster has gained in im‐portanceover time:while83%of the1993cohortof16‐year‐olds fol‐lowed this track, the sharehadgrown to89% for the2003cohort. In‐deed, this share largely exceeds the corresponding share for Finland


(83%)andevenmoresothatforDenmark(75%)andis, ineffect,veryclosetotheshareobservedforSweden(92%).Asexpected,most(94%)youngpeoplewhohavecompletedtheiruppersecondaryeducationbyage21gointothestudy‐trackcluster.However,thisclustershowsupasahighlydominant trackalsoamongthenon‐completers(youngpeoplewith no upper secondary degree still by age 21): close to 70% of thenon‐completersareinthiscluster.Theshareisstrikinglyhighalsowhencompared to the other Nordic countries: 58% for Sweden, 56% forDenmarkandonly42%forFinland.

The remaining 13% of young Norwegians not following this studytrackaredistributedacrossthreebroadgroupsofearlyschool‐to‐worktrajectories:studytrackswithadelayedstartinpost‐compulsoryeduca‐tion(clusters5,7and9),studytrackswithabreakyearfromeducation(clusters 2 and 3) and tracks containing mainly non‐study activities(clusters 4, 6, 8 and 10). As shown in Table 3.3, all these clusters aredominatedbynon‐completersofuppersecondaryschool,someofthemoverwhelminglyso.

Figure3.3:ClusteringofyoungNorwegians’individualschool‐to‐worktrajecto‐riesfromage16uptoage20intotengroups,usingclusteranalysisonpooledinformationforallthreeyouthcohorts

Notes: The clustering concerns individual school‐to‐work trajectories of young Norwegians when

aged 16 to 20, as displayed in Figure 2.1c of Chapter 2, using the optimal matching methodology

described in sub‐chapter 3.1. The vertical axis of each graph gives the absolute number of young

persons in the cluster, whereas the percentage share on top of each graph shows the relative share


of young people in the cluster. The total number of young people is 156,164. The number in brack‐

eted parentheses on top of each graph refers to the number given by the algorithm creating the ten

clusters by means of the subdivision procedure described sub‐chapter 3.1. For more details on each


Table 3.3: Distribution (%‐share) of young Norwegians across the ten clusters displayed in Figure 3.3, by gender, cohort and completion/non‐completion of an upper secondary degree by age 21

Cluster:



degree by age 21


[1] – 86.6% study tracks 86.8 86.3 82.7 87.6 89.2 94.2 68.6

[2] – 2.3% study/unemployment/study tracks 2.2 2.3 2.8 2.1 1.9 0.7 6.0

[3] – 3.9% study/inactivity/study tracks 3.4 4.4 4.3 3.5 3.9 2.2 7.8

[4] – 0.1% disability tracks 0.1 0.1 0.2 0.1 0.1 0.0 0.3

[5] – 3.6% inactivity/delayed‐study tracks 3.7 3.4 5.0 3.4 2.3 2.1 7.1

[6] – 0.2% unemployment tracks 0.3 0.2 0.5 0.1 0.1 0.0 0.7

[7] – 1.2% unemployment/delayed‐study tracks 1.2 1.1 1.7 0.9 0.9 0.4 3.0


[9] – 0.4% employment/delayed‐study tracks 0.5 0.3 0.3 0.5 0.3 0.2 0.8

[10] – 1.1% inactivity tracks 1.0 1.3 1.7 0.9 0.8 0.2 3.3

Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0


Note: See Figure 3.3 above.

The break‐year tracks (clusters 2 and 3) constitute the second largestgroupoftracksafterthestudytrack,comprisingabout6%ofNorwegianyouth.Theseareyoungpersonswhostartapost‐compulsoryeducationat the age of 16but take a break year from school, filling itwithnon‐studyactivitiesbeforere‐enteringeducation.Incluster2,thisbreakyearisfilledwithlabourmarketactivities–unemploymentoremployment–while in cluster 3, young people tend to spend the break year outsideboth education and the labour market, that is, in unknown activities.Youngwomen aremore likely than youngmen to follow tracks of thecluster3type,whereasthegenderdifferencewithrespecttocluster2isnegligible.Acomparisonacrosscohortsindicatesthattheshareofyoungpeople following the tracks representedby cluster2 and cluster3hasdeclinedovertime.

Athirdgroupconsistsofyoungpeoplewhopostponetheirentryintopost‐compulsoryeducation,so‐calledlatestarters.Fortheyoungstersincluster 5, the activity during this break year is unknown, that is, theycannot be found in any of the large administrative registers onwhichourdatasetsrely.Thisclustercomprises3.6%ofNorwegianyouth,andcontainsaslightlylargershareofyoungmenthanofyoungwomen.For1.2%ofNorwegianyouth,thebreakyearbeforeenteringuppersecond‐aryeducationisfilledwithunemployment(cluster7).Theselate‐startertrackswere,however,morecommonamongyoungpeopleintheoldest


cohort(the1993cohort)thaninthetwoyoungercohorts(the1998and2003cohorts).

The last four tracks (clusters4, 6, 8 and10) comprise a very smallshare of Norwegian youth. A common feature of these clusters is thattheycontainyoungpeoplewhospendmostoftheiryearsfromage16uptoage20outsidetheeducationsystem.Inclusters6and8,theseyoung‐stersareengaged in labourmarketactivities: theyspendmostof theirtimeeitherunemployed(cluster6)oremployed(cluster7).Youngmenaremarginallymorelikelytoenterthesetwoclusters.Clusters4and10,finally,aredominatedbyactivitiesoutsidethelabourforce.Mostoftheyoung people going into cluster 4 are on disability arrangements,whereastheyoungpeopleallocatedintocluster10are,whenaged16to20,inactivitiesnotcoveredbythelargeadministrativeregistersunder‐lying our datasets, that is, their activity is not known. Also these fourclustershavebecomelesscommonovertime.

Three observations stand out from this comparison of ten clusters.First,mostyoungNorwegiansfollowastudytrackfromage16uptoage20. Alsothosewhofailtoachieveanuppersecondarydegreebyage21,spendmostoftheirtimeenrolledasfull‐timestudents.Second,thereareno conspicuous genderdifferences in the allocation of youngmen andyoungwomenacrossthesetenclusters.Althoughyoungmenseemtobeslightlymore likely to be engaged in labourmarket activities at theseages,thegenderdifferenceissmall.Finally,thereisacleartendencyofconvergence over timewith an increasing share of youngNorwegiansfollowing the study track (cluster 1). Conversely, it has become lesscommon todeviate from the study track in the formof late starts andpauseyears.Broadlyspeaking,theearlypost‐compulsory‐schooltrajec‐toriesofyoungNorwegianshavecometolookincreasinglysimilar.

3.2.4 Sweden

TheclusteringofyoungSwedes’post‐compulsory‐schooltrajectoriesuptoage20results inasituationwithanoverwhelmingmajority(almost90%) following standard study tracks (cluster1).Moreprecisely, nineout of ten young Swedes start upper secondary school at age 16 andcontinueinfull‐timeeducationwithoutinterruptions.Thestudytrackisbyfarthemostpreferredtrackofyoungpeoplecompletingtheiruppersecondaryeducationbyage21,atthelatest:95.4%ofSwedishcomplet‐ers followthis track(Table3.4.).However,substantialnumbersofalsonon‐completers – 58.5%– showup in this cluster. An onlymarginallylargershareofyoungwomen thanofyoungmengoes into thecluster.


Moreover,therehasbeenasteadyincreaseacrosscohortsintheshareof young Swedes following early post‐compulsory‐school trajectoriesdominatedbyuninterruptedstudiesonafull‐timebasis.

Apartfromthedominatingstudy‐trackcluster(cluster1),twootherclusterscontainfrequentspellsofstudy‐relatedactivities,viz.cluster2andcluster5.Whilecluster5containsyoungstersdelayingtheirstartinpost‐compulsory educationby spending a year outside both educationandthelabourmarket,theyoungpeoplecontainedincluster2dropout– mostlytemporarily–afteroneortwoyearsinuppersecondaryeduca‐tion.Bothclusterscontainonaverage3.5%ofyoungSwedes,butwithclearly feweryoungsters following these tracks in theyoungest (2003)cohortascomparedtothesituationintheoldest(1993)cohort.

Whenaddingthepercentagesharesofthesetwoclusterstotheshareof cluster1, theoutcome is that these three clusters coverasmuchas96.4% of all young Swedes in the three youth cohorts under scrutiny.Thesameexerciseforcompletersofanuppersecondarydegreebyage21rendersapercentagesharethatiscloseto100%implyingthatfew,ifany,ofthemshowupintheothersevenclusters(Table3.4).Thecorre‐sponding percentage share is strikingly high (about 80%) also for thenon‐completers,indicatingthatfull‐timeeducationisanoverwhelming‐lycommonactivityalsoamongthoseyoungpeoplewhodonotsucceedin completing their upper secondary educationwithin five years aftercompulsoryschool.

Oftheremainingsevenclusters,onlytwo(clusters8and10)containabout1%ofyoungSwedeswhiletherestareevensmaller,eachcover‐ing less than 0.5% of young Swedes. Cluster 8 represents early post‐compulsory‐school trajectories thatmostlyresult insomekindofdisa‐bility arrangements after prolonged spells outside both education andthelabourmarket.Althoughsmallinmagnitude,it isworthnotingthattheshareofyoungpeoplefollowingsuchtrackshasdoubledovertime:from0.7%fortheoldestcohortto1.3%fortheyoungestcohort.Alltra‐jectoriesrepresentedbycluster10startwithprolongedspellsininactiv‐ity thatmight, so it seems, lead the young person into principally anykindofsubsequentactivity:education,employmentorNEETactivities.


Figure3.4:ClusteringofyoungSwedes’individualschool‐to‐worktrajectoriesfromage16uptoage20intotengroups,usingclusteranalysisonpooledinformationforallthreeyouthcohorts

Notes: The clustering concerns individual school‐to‐work trajectories of young Swedes when aged

16 to 20, as displayed in Figure 2.1d of Chapter 2, using the optimal matching methodology de‐

scribed in sub‐chapter 3.1. The vertical axis of each graph gives the absolute number of young

persons in the cluster, whereas the percentage share on top of each graph shows the relative share

of young people in the cluster. The total number of young people is 290,257. The number in brack‐

eted parentheses on top of each graph refers to the number given by the algorithm creating the ten

clusters by means of the subdivision procedure described sub‐chapter 3.1. For more details on each


All in all, the patterns emerging when allocating young Swedes’ post‐compulsory‐school trajectories up to age 20 into ten clusters can besummarised as follows.Most young people follow threemain types oftracks,allofwhichareheavilydominatedbystudyactivities.Addingthesharesofthesethreeclustersresultsinacoverageof96.4%forallyoungpeople,closeto100%forthosecompletinganuppersecondarydegreeby age 21, and about 80% for the non‐completers, that is, those withonlyabasiceducationstillatage21.Moreover,theuninterruptedstudytracks (cluster 1) have gained further in importance across cohortswhiletherehasbeenacorrespondingdeclineinthemore“bumpy”studytracksoftheothertwokeyclusters.Theremainingsevenclustersthuscontainlessthan4%ofallyoungSwedes,anegligibleshareofcomplet‐ers, but about 20%of thenon‐completers. A common feature of thesenon‐completer‐dominatedclustersisthattherehavebeensmall, ifany,


changesacrosscohortsinthesharesofyoungnon‐completersfollowingthese types of post‐compulsory‐school tracks. Finally it may be notedthat youngmen and youngwomen are distributed in a highly similarwayacrossthetenclusters.

Table 3.4: Distribution (%‐share) of young Swedes across the ten clusters displayed in Figure 3.4, by gender, cohort and completion vs. non‐completion of an upper secondary degree by age 21

Cluster:


Gender Cohort of 16‐year olds Post‐compulsory

degree by age 21


[1] – 89.4% Study tracks 88.9 90.1 87.7 88.3 91.9 95.4 58.5

[2] – 3.5% Study/pause‐year/study tracks 3.3 3.8 4.1 3.3 3.4 1.9 12.4

[3] – 0.4% Dropout/employment tracks 0.5 0.3 0.4 0.4 0.3 0.0 2.2

[4] – 0.2% Dropout/inactivity/employment tracks 0.2 0.3 0.2 0.3 0.2 0.0 1.4

[5] – 3.5% Delayed‐start/study tracks 4.0 3.0 4.8 4.9 1.2 2.5 8.7

[6] – 0.2% Inactivity/employment tracks 0.2 0.2 0.2 0.2 0.2 0.0 1.3

[7] – 0.2% Dropout/unemployment tracks 0.2 0.2 0.3 0.2 0.1 0.0 1.4

[8] – 1.0% Pensioner tracks 1.1 0.8 0.7 0.9 1.3 0.0 6.1

[9] – 0.3% Dropout/inactivity/mix‐of‐activities tracks 0.4 0.3 0.3 0.4 0.4 0.1 1.9

[10] – 1.1% Inactivity/mix‐of‐activities tracks 1.3 1.0 1.2 1.2 1.0 0.2 6.1

Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0



3.2.5 Mainfindings

Theclusteringofyoungpeople’spost‐compulsory‐schooltrajectoriesuptoage20 intoa totalof tengroupsreveals interestingsimilarities–aswellasdissimilarities–betweenthefourcountries.Indeed,despitethefact that the cluster analysis is performed separately for each countrywiththeformationofclustersbeingentirelydeterminedbythenationaldataset, a clear commonpatternemergesacross the fourNordic coun‐tries. In particular, the uninterrupted study track is by far the mostprevalent cluster amongNordic youthwhen aged 16 to 20,withmostyoungpeopleinthisclusterspendingatleastthreeconsecutiveyearsineducationstraightaftercompletingcompulsoryschool.

AssummarisedinTable3.5,thestudy‐trackclustercontainscloseto90%ofSwedishyouth,almost87%ofNorwegianyouth,nearly79%ofFinnish youth and about76%ofDanish youth.Moreover, the share ofyoung people going into this particular cluster has increased over co‐horts,exceptinDenmark.Notsurprisingly,alargemajorityoftheyoungpeoplehavingcompletedanuppersecondarydegreebyage21showupin the study‐track cluster. However, also the share of non‐completerscontainedintheclusterisstrikinglyhigh,especiallyinNorway.Finally,aslightlylargershareofyoungwomenthanofyoungmenisallocatedinto


thiscluster,withtheexceptionofNorwaywherethisgenderdifferenceisnegligible.

This general pattern is further strengthened when adding to thestudy‐track cluster other study‐dominated clusters, that is, more non‐standard post‐compulsory‐school tracks followed by especially earlycompleters of an upper secondary degree. An illustrative example ofsuchanalternativetrajectoryisadelayedstartinuppersecondaryedu‐cationdue toabreakyearafter completionof compulsory school.Theoutcome of this exercise is shown in the lower half of Table 3.5. As isevidentinthetable,mostcompletersgointothese(twoorthree)study‐dominatedclusters:thispercentageshareexceeds90%inallfourcoun‐triesandisalmost100%forSweden.Inotherwords,thegroupofyoungcompletersofanuppersecondarydegreeisremarkablyhomogenousinallfourcountries.

Conversely, few, if any, of the completers follow tracks representedbytheremainingclusters.Instead,theseclustersaredominatedbypost‐compulsory‐school trajectories mostly followed by youngsters lackinganuppersecondarydegreestill atage21.Hence,althoughremarkablyhigh shares of these young non‐completers follow study‐dominatedtracks – 80%ormore in Sweden andNorway and66–67% in FinlandandDenmark – large shares of them followalso other types of tracks,manyofwhichcanbeseen torepresenthigh‐risk transitionpathways.Next we, therefore, take a closer look at non‐completers’ post‐compulsory‐schooltrajectoriesuptoage20.

Table 3.5: Summary of study‐dominated clusters for the four Nordic countries under study, by gender, cohort and completion vs. non‐completion of an upper secondary degree by age 21


degree by age 21


Study‐track cluster (cluster 1)

Denmark – 76.3% 75.6 77.0 78.1 75.5 75.2 88.4 56.0

Finland – 78.5% 76.7 80.3 74.9 77.8 83.0 86.5 41.9

Norway – 86.6% 86.8 86.3 82.7 87.6 89.2 94.2 68.6

Sweden – 89.4% 88.9 90.1 87.7 88.3 91.9 95.4 58.5

Combination of major study‐dominated clusters

Denmark – 83.3% (clusters 1, 5 & 10) 83.0 83.5 82.1 83.1 84.4 93.7 65.6

Finland – 88.0% (clusters 1 & 9) 87.2 88.8 82.4 88.3 93.7 92.6 67.1

Norway – 94.1% (clusters 1, 3 & 5) 93.9 94.1 92.0 94.5 95.4 98.5 83.5

Sweden – 96.4% (clusters 1, 2 & 5) 96.2 96.9 96.6 96.5 96.5 99.8 79.6

Note: This table is compiled based on the information presented in the country‐specific tables 3.1 to 3.4.


3.3 Country‐specificclusterresults:non‐completers

Inthissub‐chapterwelookinmoredetailintotheearlyschool‐to‐workexperiencesofyoungpeoplewhodonotsucceedinachievinganuppersecondary degree by the time they turn 21. As shown in the previoussub‐chapter,thenon‐completersdistributeovergroupings(clusters)ofindividual post‐compulsory‐school trajectories in away that differs incrucialrespectsfromcompleters,that is, fromthoseyoungpeoplewhoachieve an upper secondary certificatewithin five years after comple‐tionofcompulsoryschool.Nextwedonot,however,departfromthetenbroad clusters formed for each country in the previous sub‐chapterbasedoneachnationaldataset.Insteadwerepeattheclusteranalysisondata restricted to embracenon‐completers only. By excluding all com‐pletersfromthedata,weexpecttoobtainamorecomprehensivepictureofthepost‐compulsory‐schoolpathwaysfollowedbyyoungstersendingup as young non‐completers and, in so doing, also improve the cross‐countrycomparabilityofnon‐completers’ earlyeducationaland labourmarket experiences.Moreprecisely,weallocate themultitudeonnon‐completers’ early school‐to‐work trajectories displayed in Figures 2.3ato2.3dofChapter2acrossatotaloftenclustersusingoptimalmatching.Again, the reported results are country specific in the sense that eachnationaldatasetisallowedtounrestrictedlyformthesetenclusters.

3.3.1 Denmark

Figure 3.5 contains the ten clusters obtained for the Danish non‐completers (61,884 in total). The study‐track cluster (cluster 1) formsthe largest group covering about one‐half of the non‐completers. Thisoutcomeisnotsurprisinginviewoftheresultspresentedintheprevi‐oussub‐chapter: largesharesofalsonon‐completersspendingmostoftheirtimeuptoage20infull‐timeeducationbutwithoutcompletinganupper secondary degree within five years after leaving compulsoryschool.Table3.6,inturn,showsthataslightlylargershareofyoungmenthanofyoungwomengoesintothisclusterandthatthesizeoftheclus‐terhasremainedrelativelystableovercohorts.


Figure3.5:ClusteringofyoungDanes’individualschool‐to‐worktrajectoriesfromage16uptoage20intotengroups,usingclusteranalysisonpooledinformationfornon‐completersonly

Notes: The clustering concerns individual school‐to‐work trajectories of Danish non‐completers

when aged 16 to 20, as displayed in the lower graph of Figure 2.3a in Chapter 2, using the optimal

matching methodology described in sub‐chapter 3.1. The vertical axis of each graph gives the abso‐

lute number of non‐completers in the cluster, whereas the percentage share on top of each graph

shows the relative share of non‐completers in the cluster. The total number of non‐completers is

61,884. The number in bracketed parentheses on top of each graph refers to the number given by

the algorithm creating the ten clusters by means of the subdivision procedure described sub‐

chapter 3.1. For more details on each cluster, see Table 3.6 below.

Othergroupsofyoungpeoplespendingmuchtimeasfull‐timestudentswithout obtaining an upper secondary degree by age 21 are found incluster8andcluster9.Allyoungsters incluster8areemployedatage16buthavere‐enteredtheschoolsystembyage17,someofthemtem‐porarilyandsomeofthemonamorepermanentbasis.Allyoungstersincluster9are inactiveatage16butmostofthemhavereturnedtofull‐timeeducationbyage17.Table3.6showsthatthedifferenceinthemaleand female shares for these two clusters is marginal. Moreover, theshareofnon‐completers contained in these twoclustershas increasedovertimeandespeciallysoforcluster9,whichcovers6.6%ofthenon‐completersinthe2003cohortcomparedtoonly2%intheoldestcohort.Inotherwords,abreakyearbeforecontinuinginuppersecondaryedu‐cation has become amore prevalent phenomenon amongDanish non‐completers. Together with cluster 1, these study‐dominated clusters


cover58.4%ofthenon‐completers,withthissharebeingclearlyhigherforthe2003cohort(60%)thanforthe1993cohort(56%).Hence,largesharesof thenon‐completersspendsubstantialamountsof time inup‐per secondary education without obtaining a degree. Moreover, thistrendhasstrengthenedovertime.

Table 3.6: Distribution (%‐share) of Danish non‐completers across the ten clusters displayed in Figure 3.5, by gender and cohort

Cluster:


Gender Cohort of 16‐year‐olds

Male Female 1993 1998 2003

[1] – 52.1% study tracks 53.3 50.4 52.7 52.5 51.2

[2] – 25.1% dropout/employment/inactivity tracks 25.0 25.3 29.2 23.5 22.8

[3] – 0.7% dropout/pensioner tracks 0.7 0.7 0.0 0.8 1.1

[4] – 3.8% dropout/unemployment tracks 3.3 4.6 4.3 3.4 3.9

[5] – 0.3% early unemployment tracks 0.2 0.4 0.4 0.3 0.1

[6] – 2.5% dropout/employment/inactivity tracks 2.2 2.9 2.9 2.5 2.1

[7] – 2.4% employment tracks 2.9 1.8 2.6 2.3 2.4

[8] – 1.6% early employment tracks 1.7 1.4 1.2 1.7 1.8

[9] – 4.7% early inactivity tracks 4.6 4.7 2.0 5.2 6.6

[10] – 6.9% inactivity tracks 6.2 8.0 4.8 7.8 8.1

Total 100.0 100.0 100.0 100.0 100.0

%‐share in the non‐completers’ pooled data 58.6 41.4 32.1 32.4 35.5


Twoclusters containearlypost‐compulsory‐school trajectories charac‐terised by unemployment: cluster 4withmost non‐completers havingbeen unemployed at age 18, and cluster 5 containing non‐completershavingexperiencedunemploymentat still earlier ages.A common fea‐tureofthetwoclustersisthatthisearlyunemploymentexperienceoftenresults inthenon‐completercontinuinginunemploymentorinactivity,orswitchingbetweenthesetwoNEETactivities.Slightlylargersharesofyoungwomenthanofyoungmentendtofollowthistypeoftrajectory.Table3.6alsoindicatesthattherehasbeen,atmost,aweakdeclineovertime in the share of non‐completers following unemployment‐dominatedtracksaftercompletionofcompulsoryschool.Takentogeth‐er,cluster4and5coveronaverage4%oftheDanishnon‐completers.

Cluster7,inturn,containsnon‐completerswhostarttheirearlypost‐compulsory‐schoolcareerinemployment.Mostofthemalsocontinueinworkinglife,soitseems,onapermanentbasis.Theclusterismaledom‐inated, stable over time and covers on average 2.4% of Danish non‐completers. Employment isquite adominating statusalso in cluster2,whichcoversnolessthan25%ofthenon‐completers,albeitthisshareisclearly lower among the non‐completers in the 2003 cohort (close to23%)thanamongthenon‐completersinthe1993cohort(29%).


Theearlypost‐compulsory‐schooltrajectoriescontainedincluster6mostly start with the non‐completer dropping out from school intoworkinglifealreadyatage17.However,inmostcasestheemploymentspell turns into inactivity already the following year. For some of thenon‐completersthiswithdrawalintoinactivitycontinues,forothersitisreplaced by employment or full‐time education. This mix‐of‐activitiescluster ismoreprevalentamongyoungwomen thanyoungmen.How‐ever, theshareofnon‐completers following thequiterisky trajectoriescontainedinthisclusterhasdeclinedovertime,standingat2.1%forthenon‐completersofcohort2003.

Also cluster 10 contains high‐risk trajectories,mostly startingwithprolonged spells in inactivity straight after completion of compulsoryschool,withonlyaminorshareoftheseyoungstersreturningtoeduca‐tion.Moreover,theshareofyoungDanesfollowingthistypeoftrajecto‐ryhas increasedsubstantiallyovertime, from4.8%inthe1993cohortto8.1%inthe2003cohort.Anotherfeatureofthisclusteristhatitco‐versa clearlyhigher shareofyoungwomen thanofyoungmen.Whilethe early experience of non‐completers appearing in cluster 3 is quitesimilar, theseyoungstershave typicallybecomedisabilitybeneficiariesalreadybyage18.Cluster3ismarginalinsize,butincreasing.

Allinall,Danishnon‐completersarefoundtobeheavilyconcentratedin clusters dominated by full‐time education or employment, or both.Moreprecisely,about52%ofthemfollowstandardstudytracks.Whenaddingthesharesofnon‐completersfollowingmorenon‐standardedu‐cationtracks,theoutcomeisthataboutthreeoutoffivenon‐completersfollow education‐dominated tracks, but without completing an uppersecondary degree by age 21.When further adding the shares of non‐completersinemployment‐dominatedtracks,weendupatalmost86%.Hence,alargemajorityofDanishnon‐completersfolloweitherstudy‐oremployment‐dominated tracks upon completion of compulsory school.This implies that about 14% of Danish non‐completers are engagedmainlyinNEETactivities.TheNEETshareofnon‐completerswasnota‐blylowerinthe1993cohortthaninthe2003cohort,though.

3.3.2 Finland

Figure3.6presentsthetenclustersobtainedfromusingclusteranalysison young Finns identified as non‐completers in the three cohorts of16‐year‐oldsunderstudy,35,956intotal.AsalreadyshowninTable3.2as well as in Table 3.5 above, a considerable share of also non‐completersspendmuchtimeasfull‐timestudents,despitethefactthat


theydonotsucceedinachievinganuppersecondarydegreewithinfiveyearsaftercompletingcompulsoryschool.Accordingly, it ishardlysur‐prising that several of the clusters displayed in Figure 3.6 reveal con‐spicuousresemblancewiththosepresentedinFigure3.2forthefulldatacontainingbothcompletersandnon‐completers.

Figure3.6:ClusteringofyoungFinns’individualschool‐to‐worktrajectoriesfromage16uptoage20intotengroups,usingclusteranalysisonpooledinformationfornon‐completersonly

Notes: The clustering concerns individual school‐to‐work trajectories of Finnish non‐completers

when aged 16 to 20, as displayed in the lower graph of Figure 2.3b in Chapter 2, using the optimal







As is to be expected,we identify a study‐track cluster also among thenon‐completers, covering a substantial share of them. More precisely,two out of five non‐completers (41.2%) continue directly into post‐compulsory education where they spend several consecutive years asfull‐time students, but without finalising an upper secondary degree.Instead,theyeventuallydropout,mostlytostartworking.

Alsothenexttwoclusters(2and3)resemblestronglythosepresent‐edinFigure3.2.Bothstartwithanearlydropoutfrompost‐compulsory


education,typicallyalreadyafterthefirstyear,andcontinueintheformof either unemployment or employment, occasionally with short re‐entries into the education system. Taken together, these two clusterscoverabout17%ofthenon‐completers.

Clusters4and5alsohavetheircounterpartsinFigure3.2:yearsasdisability beneficiaries straight after completion of compulsory school,eithercontinuingonamoreorlesspermanentbasis(cluster4)oreven‐tually turning into a re‐entry into education (cluster 5). The non‐completers following these types of tracks are rather few in number,though(ashareunder4%).

Alsotheemploymentandunemploymenttracksfollowingstraightaf‐ter completion of compulsory school (clusters 6 and 7) are similar tothose in Figure 3.2, as are also the inactivity‐delayed tracks of post‐compulsoryeducation (cluster9)andemployment(cluster10).Hence,the only conspicuously different cluster for the non‐completers, whencompared to the clusters formed for all young people in Figure 3.2, iscluster8.Theyoungpeoplegoingintothisparticularclusterspendmostof their timeoutsidebotheducationand the labourmarket.Moreover,withashareofcloseto7%itisthefourthlargestclusteramongyoungnon‐completers.

Acomparisonofnon‐completersacrossgendersrevealsconsidera‐bly larger differences in cross‐cluster distributions (Table 3.7) be‐tweenyoungmenandyoungwomenascomparedtothesituationde‐scribedinTable3.2forthefulldataset.Whilelargesharesofbothmaleandfemalenon‐completers followastudytrack(cluster1), this trackis clearly more common among young male non‐completers. At theother extreme we have the inactivity‐dominated track (cluster 8),whichisfarmorecommonamongyoungfemalenon‐completers.ThesefindingsareinlinewithwhathaspreviouslybeenreportedbyAsplundandVanhala(2014)fornon‐completersbelongingtotheyoungestco‐hort, that is, the 2003 cohort of 16‐year‐olds: while there are feweryoung women than young men belonging to the group of non‐completers, the female non‐completers often seem to follow riskiertrajectoriesthantheirmalecounterparts.

Finally,when it comes to thedistribution across the ten clusters ofnon‐completersfromthethreecohortsunderstudy,Table3.7doesnotaddmuchtothetrendsalreadypointedoutinrelationtoTable3.2.Boththestudytrack(cluster1)andtheinactivity/delayed‐studytrack(clus‐ter 9) have gained substantially in popularity also among non‐completers.Thisholdstruealsofortheinactivitytrack(cluster8)which,asnotedearlier, isa trackdistinct tonon‐completersonly.Formostof


theotherclustersweobserveadecliningshareovercohorts,obviouslymainly due to successful changes in the institutional setting. The onlyconspicuous exceptions from this declining trend concern the employ‐ment‐dominated tracks (contained in cluster 6 and 10), the shares ofwhich have remained approximately stable across cohorts. In otherwords,anearlymoveintoworkinglifehasretaineditspopularityamongnon‐completersofanuppersecondarydegree.

Table 3.7: Distribution (%‐share) of Finnish non‐completers across ten clusters as displayed in Figure 3.6, by gender and cohort

Cluster:



Male Female 1993 1998 2003

[1] – 41.2% study tracks 42.9 38.8 35.0 42.1 46.1

[2] – 11.4% dropout/unemployment tracks 10.8 12.2 19.6 8.7 6.8

[3] – 5.9% dropout/employment tracks 5.8 5.9 7.0 6.4 4.2

[4] – 2.5% disability‐benefit (pensioner) tracks 2.5 2.6 2.9 3.1 1.6

[5] – 0.7% disability/delayed‐study tracks 0.7 0.6 1.6 0.4 0.0

[6] – 6.1% employment tracks 6.3 5.9 5.6 7.1 5.3

[7] – 1.5% unemployment tracks 1.5 1.6 3.4 1.0 0.5

[8] – 6.7% inactivity tracks 5.7 8.3 3.6 6.8 9.5

[9] – 20.1% inactivity/delayed‐study tracks 20.1 20.0 18.3 19.8 22.2

[10] – 3.8% inactivity/delayed‐employment tracks 3.5 4.2 3.0 4.6 3.7

Total 100.0 100.0 100.0 100.0 100.0

%‐share in the non‐completers’ pooled data 59.3 40.7 30.1 37.8 32.1


Onthewhole,then,alsoFinnishnon‐completersshowupinlargenum‐bers in post‐compulsory‐school tracks dominated by full‐time educa‐tion:about41%ofthemgointothestudytrack(cluster1),whereasanadditional 21% follow study tracks after a delayed start. Hence,morethan three out of five non‐completers follow education‐dominatedtracks, but without gaining an upper secondary certificate by age 21.When further adding the share of non‐completers following employ‐ment‐dominatedtracks(closeto16%),weactuallycovercloseto78%of all non‐completers. Hence, a substantial share of also Finnish non‐completers followeither study‐ or employment‐dominated trajectoriesafterhaving left compulsoryschool,a share that is about8percentagepoints lower than for Denmark. Conversely, a larger share of FinnishthanofDanishnon‐completers showup inNEETactivities:about22%comparedto14%inDenmark.Acommonfeatureofthetwocountries,however, is that the share of non‐completers following inactivity‐dominated trackshas increasedovercohorts.Thesituation isdifferentwhen it comes tounemployment: the shareof Finnishnon‐completersgoing into unemployment‐dominated tracks has declined remarkably


over time. A major reason for this finding is that the school‐to‐worktransitionofthe1993cohortstartedinthemiddleofadeeprecession.

3.3.3 Norway

AlsoforNorway,theclustersformedforthenon‐completerslookquitesimilartothoseforthefullyouthpopulation,asisevidentfromcompar‐ingFigure3.7toFigure3.3.However,whenrestrictingtheclusteranaly‐sistonon‐completersonly,asinFigure3.7,weseeamoreevendistribu‐tion of young people across the different tracks. Again, the dominantcluster is the standard study track (cluster 1), which contains almost70% of the non‐completers. Young men are more likely than youngwomentopursueastudytrackwithoutcompletinganuppersecondarydegree by age 21. Moreover, the time trend towards convergence oftracks is even stronger for the non‐completers than for the full youthpopulation: while the study track covers close to 59% of the non‐completers in the 1993 cohort, the corresponding share for non‐completersinthe1998and2003cohortsis71and77%,respectively.Inotherwords, thephenomenonof followingstandardstudytrackswith‐out completion of an upper secondary degree by age 21 has becomeincreasinglycommonamongyoungNorwegians.

The other nine clusters, covering almost one‐third of the non‐completers,maybedividedintothreebroadgroups:studytrackswithadelayed start in post‐compulsory education (clusters 6 and 10), earlydropoutfromuppersecondaryeducation(clusters3,4and7)andtracksmainlydominatedbynon‐studyactivities(clusters2,5,8and9).Early‐dropouttracksarefollowedbyarelativelylargeshareofyoungNorwe‐gians:closeto15%ofthenon‐completersshowupinthistypeoftrack.Another large group consists of late starters with delayed entry intopost‐compulsory education (11%), while the non‐study tracks coveronly6%ofthenon‐completers.


Figure3.7:ClusteringofyoungNorwegians’individualschool‐to‐worktrajecto‐riesfromage16uptoage20intotengroups,usingclusteranalysisonpooledinformationfornon‐completersonly

Notes: The clustering concerns individual school‐to‐work trajectories of Norwegian non‐completers

when aged 16 to 20, as displayed in the lower graph of Figure 2.3c in Chapter 2, using the optimal







Theearly‐dropoutclustersdifferfromeachotherwithrespecttotheac‐tivity dominating after school dropout: almost 4%become unemployed(cluster 3) and close to 5%move intoworking life (cluster 7),whereascloseto7%withdrawfrombotheducationandthelabourmarket,thatis,disappear from all large administrative registers (cluster 4). Notablesharesoftheseearlyschool‐dropoutsreturntoeducation,butfarfromall.Moreover, theseearly‐school‐dropout tracksare typicallymorecommonamongyoungwomenthanamongyoungmen.Thisholdstrueespeciallyfortheearly‐dropout/inactivitytracks(cluster4).Althoughthetimetrendacrosscohortsforthesethreeearly‐dropouttracksisnotequallyclear‐cutasforthestandardstudytracks,acomparisonbetweennon‐completersintheoldest(1993)cohortandnon‐completersintheyoungest(2003)co‐hort indicates that the probability of youngNorwegians following thesetypesofearly‐dropouttrackshasdeclinedovertime(Table3.8).


Table 3.8: Distribution (%‐share) of Norwegians non‐completers across ten clusters as displayed in Figure 3.7, by gender and cohort

Cluster:

number ‐ %‐share ‐ label


Male Female 1993 1998 2003

[1] 69.0% study tracks 70.9 66.3 58.6 70.6 76.5

[2] 0.3% disability‐benefit tracks 0.3 0.3 0.4 0.2 0.3

[3] 3.8% early‐dropout/unemployment tracks 3.5 4.2 5.3 3.1 3.2

[4] 6.5% early‐dropout/inactivity tracks 5.6 7.8 7.7 5.9 6.0

[5] 0.8% unemployment tracks 0.7 0.8 1.6 0.4 0.4

[6] 2.7% unemployment/delayed‐study tracks 2.6 2.9 3.9 2.1 2.2

[7] 4.5% early‐dropout/employment tracks 4.6 4.5 4.9 5.7 3.1

[8] 2.3% employment/unemployment tracks 2.4 2.2 2.8 2.7 1.4

[9] 2.1% inactivity tracks 1.6 2.9 3.6 1.8 1.2

[10] 8.0% inactivity/delayed‐study tracks 7.8 8.2 11.2 7.5 5.7

Total 100.0 100.0 100.0 100.0 100.0

%‐share in the non‐completers’ pooled dataset 58.0 42.0 31.4 32.2 36.4


Clusters 6 and 10 represent delayed‐study tracks. These two clusterscontainyoungpeoplewhotakeabreakyearbeforecontinuinginpost‐compulsoryeducation.Cluster10is,ineffect,thesecondlargestclusterafter the study‐track cluster, comprising 8% of the non‐completers.Youngpeopledelayingtheirstartinpost‐compulsoryeducationtypicallyspend their break year outside both education and the labourmarket.However,incontrasttothesituationinbothDenmarkandFinland,theshareofyoungNorwegiansfollowingsuchtrackshasdeclinedmarkedlyover time (Table 3.8). The other delayed‐study‐track cluster, which isnotably smaller in size (2.7%), includes youngsterswho spend a yearmainlyinunemployment–mostlyinsomeformofactivelabourmarketpolicy (ALMP)program–beforecontinuing inpost‐compulsoryeduca‐tion. Also the share of non‐completers following these types of trackshasdeclinedacrosscohorts,though.Largersharesofyoungwomenthanofyoungmentendtofollowdelayed‐studytracks.

The four remaining clusters (2, 5, 8 and 9) contain young peoplespendingmostoftheirtimepursuingnon‐studyactivitiesaftercomplet‐ingcompulsoryschool.Inclusters5and8,theseyoungpeoplearemost‐ly either employed or unemployed: around 2% of the non‐completersspend their post‐compulsory‐school years up to age 20 by switchingbetween employment and unemployment (cluster 8) while a minorshareofthem(0.8%)isforthemostpartunemployed(cluster5).About2%of the non‐completers follow tracks dominatedby time spent out‐sidebotheducationandthelabourmarket,inunknowninactivity(clus‐ter8),andaverysmallshareofthem(0.3%)isreceivinghealth‐relatedbenefits(cluster2).Alltheseclustersweremoreprevalentintheoldest(1993)cohort.


TheoverallpictureemergingforyoungNorwegianshavingachievednopost‐compulsorydegreebyage21isquiteclear‐cut.Inparticular,wecan identify two parallel trends over cohorts. First, there has been astrong tendency of convergence towards standard study tracks alsoamong the non‐completers,whereas a declining share of them followsother types of post‐compulsory‐school tracks, many of which involvehigh‐risk elements. Put differently, a growing share of also non‐completers continue directly in post‐compulsory education and spendmostoralloftheirtimeuptoage20asfull‐timestudents,butwithoutfinishinganuppersecondarydegreewithin fiveyearsaftercompletingcompulsoryschool.Second,agrowingshareofNorwegianyouthisfac‐ingthissituation:theshareofnon‐completershasbeenontherise,from28.5%intheoldest(1993)cohortto31.5%intheyoungest(2003)co‐hort,atrendthatbecameevidentalreadyinChapter2.

3.3.4 Sweden

More than two‐thirds (69.4%) of the Swedish non‐completers followstandard‐type study tracks (cluster 1), implying that they continue di‐rectly in post‐compulsory education for a number of years but fail tocomplete an upper secondary degree by age 21. This is a remarkablyhigh share. Only for Norway do we observe a share of a similar size(69%) while it is substantially lower for Danish and Finnish non‐completers(58and41%,respectively).AsalsointheotherNordiccoun‐tries,youngmenaremorelikelytocontinuestudyingonafull‐timebasiswithout completing an upper secondary degreewithin five years aftercompleting compulsory school, whereas the situation is the oppositeamongyoungwomen,whosefull‐timestudytracksmoreoftenresultinanuppersecondarycertificatebyage21,atthelatest.Additionally,wesee a clear time trend in the share of non‐completers engaged in full‐time studies: 67% for the non‐completers in the oldest (1993) cohortcomparedto72%ofthenon‐completersintheyoungest(2003)cohort(Table 3.9).Hence, larger shares of Swedishnon‐completers spend in‐creasinglymore time in post‐compulsory education, butwithout com‐pleting an upper secondary degree by age 21. Moreover, as shown inChapter2,fewofthesenon‐completersfinaliseanuppersecondaryde‐greeafterage21.


Figure3.8:ClusteringofyoungSwedes’individualschool‐to‐worktrajectoriesfromage16uptoage20intotengroups,usingclusteranalysisonpooledinformationfornon‐completersonly

Notes: The clustering concerns individual school‐to‐work trajectories of Swedish non‐completers

when aged 16 to 20, as displayed in the lower graph of Figure 2.3d in Chapter 2, using the optimal







Table 3.9: Distribution (%‐share) of Swedish non‐completers across ten clusters as displayed in Figure 3.8, by gender and cohort

Cluster:



Male Female 1993 1998 2003

[1] – 69.4 % study tracks 70.1 68.5 67.0 68.8 71.8

[2] – 8.0 % dropout/employment tracks 7.0 9.2 8.0 10.1 6.1

[3] – 5.9 % dropout/mix‐of‐activities tracks 5.4 6.5 7.1 5.5 5.3

[4] – 0.8 % dropout/unemployment tracks 0.8 0.8 1.4 0.7 0.5

[5] – 0.5 % employment‐delayed‐start tracks 0.3 0.7 0.8 0.4 0.3

[6] – 0.8 % employment tracks 1.0 0.5 1.0 0.8 0.7

[7] – 2.0 % inactivity‐delayed‐employment tracks 1.9 2.0 2.4 2.3 1.4

[8] – 6.2 % inactivity tracks 7.6 5.7 7.1 6.0 5.7

[9] – 0.6 % dropout/pensioner tracks 0.6 0.6 0.5 0.6 0.7

[10] – 5.9 % inactivity/pensioner tracks 6.2 5.5 4.7 4.9 7.7

Total 100.0 100.0 100.0 100.0 100.0

%‐share in the non‐completers’ pooled dataset 56.5 43.5 28.2 33.8 38.0



The distribution of the remaining one‐third of non‐completers acrosstheothernineclusters looksquiteuneven inthesensethatsomeclus‐tersembracerelativelylargesharesofnon‐completerswhilethesizeofotherclustersisminor.Thelargestgroupconsistsofclusterscharacter‐isedbyschool‐dropouttracks,notablyclusters2,3and4.Intotal,closeto15%ofSwedishnon‐completersfollowthistypeoftrackuponleavingcompulsoryschool.However,themainactivityaftertheyoungperson’sdropout from school differs considerably between the three clusters.Moreprecisely,cluster2withashareof8%ofthenon‐completerscon‐tains school‐dropoutswhomove intoworking life and also succeed instaying employed. Only occasionally does the working spell turn intounemploymentorinactivity,orendwiththeyoungpersonreturningtoschool.Incluster3withashareof6%,thedropoutoccursalreadyafterone year in post‐compulsory school and results in the young personstayingoutsidebotheducationandthe labourmarket for typicallyoneyear.Amajorityofthemcontinueinnon‐studyactivities,eitherdirectlyor after a temporary return to education, with NEET activities beingmorecommonthanemployment. Incluster4, finally,schooldropout ismostly followed by prolonged spells in unemployment. This cluster,however,comprises less than1%of thenon‐completers.Largersharesofyoungwomenthanofyoungmenfollowthedropouttracksofclusters2 and 3, whereas the gender shares are identical for cluster 4 (Table3.8). A common feature of all three dropout clusters is that their im‐portancehasdeclinedovertime,especiallywhencomparingtheyoung‐est(2003)cohorttotheoldest(1993)cohort.

Another relatively large group of non‐completers follow post‐compulsory tracks starting from non‐study activities, with the youngpersonthenmovingeitherintoworkinglife(clusters5and6)orwith‐drawingfrombotheducationandthelabourmarket(clusters7and8).Otherwise,thesefourclustersdifferquitesubstantiallyfromeachother.Cluster 5, which isminor in size covering only 0.5% of Swedish non‐completers, contains tracks where initial employment turns into re‐entryintotheeducationsystem,albeitoftenalsointounemployment.Incluster6,whichisonlymarginallylargerinsize(0.8%),initialemploy‐ment seems to be more permanent in nature with most of the non‐completers inthisclusterbeingemployedduringallyearsfromage16uptoage20.Alsothetrackscontainedincluster7,covering2%ofSwe‐dishnon‐completers,tendtoturnintoprolongedemploymentspellsbutonlyafteroneortwoearlyyearsspentininactivity.However,comparedto the employment tracks of the non‐completers in cluster 6, the em‐ploymenttracksofcluster7tendtoinvolvemorebreaks,notablyinthe


form of unemployment. Cluster 8, finally, coversmore than 6% of thenon‐completersandcontainstracksstartingwithprolongedspellsout‐sidebotheducationandthelabourmarket.Thelongerthesespells,themorelikelytheyturnintoNEETactivities.Returnstoschooloccuronlyoccasionallyandmostlyforshortperiods.However,alsothesetypesoftracks have become less common among the non‐completers.When itcomes to the distribution of youngmen and youngwomen across thefourclusters,thereisnoclearpatterndiscernible:someofthetracksaremoretypicalamongyoungwomenwhileothersaremoretypicalamongyoungmen.

The last twoclusters (9and10)are closely related todisabilityar‐rangements. Taken together, they cover 6.5% of Swedish non‐completers. However, cluster 9 is small in size (0.6%), covers equalsharesofyoungmenandwomen,andhasincreasedonlymarginallyinsize across cohorts. Most young people covered by disability arrange‐ments follow the tracks contained in cluster 10: disability benefitsstraightaftercompulsoryschoolorafterapost‐compulsory‐schoolperi‐odofmostlythreeyearsspentininactivity,thatis,outsidebotheduca‐tionandthelabourmarket.

Broadly speaking, the Swedish situation of non‐completersmay besummarisedasfollows.Remarkablylargenumbers(closeto70%)con‐tinuedirectlyinpost‐compulsoryeducationandtypicallystaythereforthreeyears,oftenlonger.AdistinctfeatureofSwedishnon‐completers,however, isthatfewofthemmoveintosuchstudytracksafterabreakyear after completion of compulsory school. Also employment‐dominated early‐age tracks are quite common among Swedish non‐completers.Whenaddingthesharesofnon‐completersfollowingtypicalemployment tracks to thesharesof those instandardstudy tracks,weend up covering almost 81% of all non‐completers. This implies thatcloseto20%ofSwedishnon‐completersgoatanearlyage intoNEET‐dominated tracks, with the role of pure unemployment tracks beingmarginal. Instead,theyspendmostoftheiryearsuptoage20,at least,outsidebotheducationandthelabourmarket,inunknowninactivity.

3.3.5 Mainfindings

This country‐specific analysis of non‐completers, that is, young peoplewithnouppersecondarydegreestillatage21,revealsthatNordicnon‐completers havemuch in common, although they alsodiffer in certaincrucialrespects.Next,wetrytosummarisethesesimilaritiesanddissim‐ilaritiesbymeansofTable3.10.


Strikinglylargesharesofnon‐completersinNorwayandSwedenfol‐lowstandardstudytracksstraightaftercompletingcompulsoryschool.However,whenaddingstudytrackscharacterisedbyadelayedstart inpost‐compulsory education, Norway outperforms Sweden, while Den‐mark and Finland move closer to Sweden. As can be concluded fromTable3.10,weidentifysmallsharesofSwedishnon‐completersdelayingtheirstartinpost‐compulsoryeducation,whereasthisisquitecommonin the other threeNordic countries under study and especially in Fin‐land. The time trend across cohorts implies, in turn, that increasinglylarger shares ofNordic non‐completers follow study‐dominated tracksbutwithoutachievinganuppersecondarydegreewithinfiveyearsafterleavingcompulsoryschool.AnothercommonfeatureofthefourNordiccountries is that largersharesofyoungmenthanofyoungwomenfol‐lowstudytrackswithoutcompletinganuppersecondarydegreebyage21.As indicatedearlier, theoppositeholds true forcompleters.Hence,full‐timeeducationwithoutgraduationbyage21isamoretypicalphe‐nomenonamongyoungmenthanamongyoungwomen.

Table 3.10: Summary of non‐completers’ post‐compulsory‐school tracks up to age 20 for the four Nordic countries under study based on the dominating activity, by gender and cohort

All non‐

completers


Male Female 1993 1998 2003

Study‐track cluster (cluster 1)

Denmark 52.1 53.3 50.4 52.7 52.5 51.2

Finland 41.2 42.9 38.8 35.0 42.1 46.1

Norway 69.0 70.9 66.3 58.6 70.6 76.5

Sweden 69.4 70.1 68.5 67.0 68.8 71.8

Major study‐dominated clusters

Denmark (clusters 1, 8 & 9) 58.4 59.6 56.5 55.9 59.4 59.6

Finland (clusters 1, 5 & 9) 62.0 63.7 59.4 54.9 62.3 68.3

Norway (clusters 1, 6 & 10) 79.7 81.3 77.4 73.7 80.2 84.4

Sweden (clusters 1 & 5) 69.9 70.4 69.2 67.8 69.2 72.1

Study‐ and employment clusters

Denmark (clusters 1, 2, 7, 8 & 9) 85.9 87.5 83.6 87.7 85.2 84.8

Finland (clusters 1, 3, 5, 6, 9 & 10) 77.8 79.3 75.4 70.5 80.4 81.5

Norway (clusters 1, 6, 7, 8 & 10) 86.5 88.3 84.1 81.4 88.6 88.9

Sweden (clusters 1, 2, 5, 6 & 7) 80.7 80.3 80.9 79.2 82.4 80.3

NEET‐dominated clusters

Denmark (clusters 3, 4, 5, 6 & 10) 14.2 12.6 16.6 12.4 14.8 15.3

Finland (clusters 2, 4, 7 & 8) 22.1 20.5 24.7 29.5 19.6 18.4

Norway (clusters 2, 3, 4, 5 & 9) 13.5 11.7 16.0 18.6 11.4 11.1

Sweden (clusters 3, 4, 8, 9 & 10) 19.4 20.6 19.1 20.8 17.7 19.9

Notes: This table is compiled based on the information presented in the country‐specific tables 3.6

to 3.9. NEET refers to Not in Employment, Education or Training.


Whenaddingtothesestudy‐tracksharesofnon‐completerstheirsharesin employment‐dominated tracks, Denmark almost closes the gap toNorwaydue toaremarkably largeshareofDanishnon‐completers fol‐lowing employment tracksupon completionof compulsory school. Putdifferently,Finland–closely followedbySweden–comesoutwith thelowestsharesofnon‐completers instudy‐andemployment‐dominatedtracks in all dimensionsunder scrutiny: in total, by gender andby co‐hort.Conversely,FinlandandSwedenhavemuch largersharesofnon‐completers following early tracks dominated by NEET activities. Thehigh share of NEET‐dominated tracks obtained for Finnish non‐completers reflects, in part, widespread unemployment among schooldropouts, starting in the deep recession years of the early 1990s (cf.Table3.7above).

Onthewhole,weobserveconsiderableheterogeneityacrossthefourNordic countries in theNEET trajectories followedbynon‐completers.This also explains the countries’ different trends in NEET shares overcohorts, aswell as the differently signed and sized gender gaps in theshares of non‐completers followingNEET‐dominated tracks. Taken to‐gether, these observations justify our efforts to create both “commonNordic trajectories” and “stylized trajectories” in order to improve thecross‐countrycomparabilityofresultsespeciallywithrespect toyoungnon‐completers. We start out, in the next chapter, from the commonNordicpathways.

4. School‐to‐work trajectories:common Nordic clusterresults

The previous chapter has shown that the trajectories through uppersecondary education are, generally speaking, highly similar for youngpeople in the four Nordic countries under study. Apart from certaincountry‐specific particularities, the following picture emerges: a largemajorityofNordicyouthentersastudytrackaftercompletingcompul‐soryschoolandonlyasmallershareofthemfollowspathwaysdominat‐ed by activities outside both education and employment, i.e. so‐calledNEETactivities.Byandlarge,thisholdstruealsoforthecategoryofnon‐completers,thatis,youngpeoplewhohavenotcompletedanuppersec‐ondaryeducationstillatage21.Moreover,acomparisonacrosscohortsreveals that there has, in all four Nordic countries, been a notable in‐crease in the share of youngpeople following study‐dominated tracks.This convergence over time in early school‐to‐work trajectories is, ineffect, discernible also among the non‐completers. Put differently, in‐creasingsharesofalsonon‐completersspendmost,orall,oftheirtimeuptoage20asfull‐timestudents,butwithoutcompletinganuppersec‐ondarydegreewithinfiveyearsafterleavingcompulsoryschool.

In this chapter,wehaveusedone of the twomethodsdescribed insub‐chapter 3.1 for forming cross‐country comparable clusters of indi‐vidualschool‐to‐worktrajectories.Asexplainedinthatsub‐chapter,wehaveforeachcountrymadealistoftheobservedsequencesofactivitiesfromage16uptoage20andthencalculatedthenumberofyoungpeo‐ple following each of these tracks. Finally, this country‐specific infor‐mationhasbeenpooledintoonebigdatatowhichwehaveappliedop‐timalmatching inorder to form ten clusters of sequences.Thisproce‐durealsoguaranteesthatsequencesobservedinmorethanoneNordiccountryareallocatedinexactlythesamewayacrossthetenclusters.Inthis sense, theclusters formedare truly “common” for the fourNordiccountriesunderstudy.Nextwereportresultsobtainedusingthismeth‐od for the full youth population and separately for the young peopleidentifiedtobenon‐completersstillwhenaged21.


4.1 CommonNordictrajectoriesandclusters:allyoungpeople

WestartourpresentationofresultsforcommonNordictrajectoriesandclustersbyproviding,inTable4.1,ageneralpictureofhowyoungpeo‐plearedistributedacrossthefivemainactivitiesateachagepointfrom16up to20,whenmerging thecountry‐specific information (basedonallthreeyouthcohorts)reportedinsub‐chapter2.2.6Asisevidentfromthe table, and previously seen in Chapter 2, the share of full‐time stu‐dentsundergoesadramaticdeclinewhile the share inworking life in‐creasesrapidlywhenNordicyouthsapproachtheageof20:byage20,theshareinemployment(about40%)isalmostaslargeastheshareinfull‐timeeducation(some42%).Intotal,thesetwosharescovercloseto83%of20‐year‐oldNordicyouth,withtheshareinNEETactivitiesthusbeing about 17%. However, as can be seen from Table 4.1, this NEETshare varies a lot over these early post‐compulsory‐school ages withstrikinglyhighsharesafterthreeyearsinuppersecondaryeducation.

Table 4.1: Distribution (%‐share) of Nordic youth across main activities, by age

Main activity Age Average for age

16 to 20 16 17 18 19 20

Student 90.3 90.1 83.4 43.8 42.2 70.0

Employed 1.6 3.7 8.4 36.3 40.4 18.1

Student or employed 91.9 93.8 91.8 90.1 82.6 88.1

Unemployed 0.6 1.2 3.1 9.3 9.0 4.6

Pensioner (on disability benefits) 0.4 0.5 0.6 1.0 1.2 0.7


NEET activities 8.0 6.3 8.1 20.0 17.4 11.9

Total 100.0 100.0 100.0 100.0 100.0 100.0

Note: The %‐shares are calculated from pooled information on individual post‐compulsory‐school

trajectories up to age 20, as produced separately for each country for all three youth cohorts com‐

bined, and reported in Chapter 2.

Figure4.1,inturn,detailstheaverageinformationgiveninTable4.1byprovidingacumulativegraphofallsequencesofyoungpeople’sactivi‐tiesfromage16uptoage20.Sincethisgraphisbasedonpooledinfor‐

──────────────────────────6Herewerepeat,oncemore,whatwasalreadyunderlinedintheintroductorychapter:forproducingthesecommonNordicresults,wedonotmergeindividual‐leveldataforthefourNordiccountriesunderstudy.Insteadwemerelycombineinformationonindividualtrajectoriesshowingsequencesofactivitiesfromage16uptoage20.Wehaveaskedforandalsoreceivedpermissionfromtherespectivestatisticalbureaustoundertakesuchapoolingofcountry‐specificindividualtrajectories.


mationontheearlyschool‐to‐worktrajectoriesidentifiedforeachcoun‐try, it actually represents a combination of the four country‐specificgraphs for all youngpeople presented in sub‐chapter 2.4. Accordingly,this particular figure shows individual school‐to‐work trajectories ofmore than 800,000 young persons. In viewof this, it is not surprisingthat Figure 4.1 conveys much the same pattern as previously seen inChapter2,with largesharesofNordicyouth followingastudytrackoftypically three or more years in upper secondary education straightafter completing compulsory school, only occasionally after an initialyear innon‐study activities.Upper secondary education is followedbystudiesmostly in tertiary‐leveleducation,or shifts intoworking lifeorNEET activities. Next we take a closer look at these common Nordicschool‐to‐worktrajectories.

Figure4.1:CommonNordicpathways:Individualschool‐to‐worktrajectoriesfromage16uptoage20forallyoungpeopleinthefourNordiccountriesunderstudy,asobtainedfrompooledinformationonallthreeyouthcohortsunderscrutiny

Notes: The graph is obtained by pooling the information on individual post‐compulsory‐school

trajectories up to age 20, as produced separately for each country and reported in Chapter 2. The

vertical axis gives the absolute number of individual school‐to‐work trajectories and, hence, the

absolute number of young persons covered by the graph. The total number of young people cov‐

ered by the graph is 802,867 (164,879 for Denmark, 193,567 for Finland, 156,164 for Norway and

290,257 for Sweden).


Themain typesof trajectories followedbyNordic youthwhenmovingthroughuppersecondaryeducationandintoworkinglifeareillustratedinFigure4.2andbrokendowninTable4.2.About84%ofyoungpeoplein the four Nordic countries follow standard study tracks (cluster 1),thatis,theytypicallyspendatleastthreeconsecutiveyearsinfull‐timeeducationstraightaftercompletingcompulsoryschool.Thesecondlarg‐est group consists of young people who delay their entry into uppersecondaryeducationbyoneyear(cluster5).

Thethirdandfourthlargestgroupsrepresenttrajectorieswheretheyoungpersonspendsapauseyearfromschoolwhenaged17,eitherinworking life(cluster3)or ininactivity(cluster2).However, thispauseyear is far fromalways followedbyareturntoeducation.Manyyoungpeople prolong their spell in employment or in inactivity. For bothgroupsofyoungpeople, therealso seems tobeagrowing riskof theirtrajectories turning increasinglyunstableafter thispauseyear,as indi‐cated by their frequent moves between employment, unemploymentand inactivity.As canbe seen fromcluster10, the fifth largest cluster,theriskofanearlyshiftintoNEETactivitiesistypicallyevenhigherforthose young peoplewho start working straight after completing com‐pulsoryschool.

Eachof theother five clusters covers less than2%ofNordic youthbut,takentogether,theircoveragelandsat3.6%,whichmakesthem,ineffect, the third largest groupafter standard anddelayed study tracks.AllthesefiveclusterscontaintrajectoriesdominatedbyNEETactivities.Thespreadofthesetypesoftracksacrossnolessthanfiveclustersre‐veals,oncemore,theheterogeneityprevailingamongyoungstersfacingnotable problems when trying to continue in or return to post‐compulsoryeducation,andalsowhentryingtomove intoworking life.Inparticular,cluster6showsthatprolongedspellsoutsidebotheduca‐tion and the labourmarket (inunknownactivities) straight after com‐pletionofcompulsoryschoolresultonlyoccasionally intheyoungper‐sonre‐enteringschoolormovingintoworkinglifeonamorepermanentbasis.Clusters7,8and9are,inturn,dominatedbyspellsinunemploy‐ment,withthesespellsincreasinglyinterruptedbynon‐study,insteadofstudy,activitieswhengoingfromcluster7tocluster9.Cluster4,finally,contains trajectories followed by young people with health problemsmovingthemintodifferenttypesofdisabilityarrangements.

Table4.2providessomemoredetailsonthetenclustersdisplayedinFigure4.2.InlinewiththeresultsreportedinChapter3,Swedencomesout with by far the largest group of young people going straight intostandardstudytracks(about91%),followedbyNorway(closeto86%).


Finland and especially Denmark havemore differentiated tracks, withless than 80% of young people showing up in the study‐track cluster(cluster1).ThisdifferencebetweenSwedenandtheotherthreeNordiccountries under study is due to a comparatively small share of youngSwedes inprincipally all theothernine clusters.Mostnotably Swedendivergesfromtheothercountrieswhenitcomestocluster3,whichcon‐tains trajectoriescharacterisedbyabreakspent inworking lifebeforereturningtouppersecondaryeducation:whilethesetypesofearlytra‐jectoriesarequiteuncommonamongSwedishyouth,theyarerelativelyprevalentinDenmark,asarealsopost‐compulsory‐schooltracksdomi‐natedbyemploymentofamorepermanentnature(cluster10).Norwaystrikesoutmainlywithrespecttoarelativelylargeshareofyoungpeo‐plefollowingtrajectoriescharacterisedbyfrequentmovesbetweened‐ucation and unemployment (cluster 7). Finally, the most conspicuousfeatureofFinlandisthehighshareofyoungpeopledelayingtheirentryintouppersecondaryeducation(cluster5).Whenitcomestotheotherclusters,most ofwhich represent inactivity‐dominated trajectories, nocountry comes out as a clear “outlier” when compared to the corre‐spondingshareintheothercountries.

Alsoacomparisonofcross‐cohortdistributionsofyoungpeoplein‐tothetenclustersinvestigatedprovidesfurthersupportfortheobser‐vations made in Chapter 3 based on country‐specific clusters. Moreprecisely, as is evident in Table 4.2, the overwhelming dominance ofstandardstudytracks(cluster1)hasbeengrowingovertime,coveringabout86%ofNordic youthbelonging to the youngest (2003) cohort.This growth in the share of young people following standard studytrackshasoccurredmainlyat theexpenseof employment‐dominatedtracks (clusters 3 and 10): the combined share of these two clustershasdeclined fromabout6%in theoldest (1993)cohort to3% in theyoungest(2003)cohort.


Figure4.2:CommonNordicclusters:Clusteringofyoungpeople’sschool‐to‐worktrajectoriesfromage16uptoage20intotengroups,usingclusteranalysisonpooledinformationforallthreeyouthcohorts,allfourNordiccountriescombined

Notes: The clustering concerns the individual school‐to‐work trajectories displayed in Figure 4.1

above, using the optimal matching methodology described in sub‐chapter 3.1. The vertical axis of

each graph gives the absolute number of young persons in the cluster, whereas the percentage

share on top of each graph shows the relative share of young people in the cluster. The number in

bracketed parentheses on top of each graph refers to the number given by the algorithm creating

the ten clusters by means of the subdivision procedure described sub‐chapter 3.1.

Table 4.2: Distribution (%‐share) of young people across the ten common Nordic clusters dis‐played in Figure 4.2, by country and cohort

Cluster:


Country Cohort of 16‐year‐olds

DK FI NO SW 1993 1998 2003

[1] – 84.3% study tracks 76.0 79.9 85.8 91.3 83.0 83.4 86.4

[2] – 2.3% study/inactivity/study tracks 4.0 0.8 3.5 1.6 2.3 2.3 2.2

[3] – 3.1% study/employment/study tracks 9.0 2.9 1.8 0.6 3.9 3.2 2.3

[4] – 0.5% disability tracks 0.4 0.8 0.1 0.5 0.6 0.6 0.2

[5] – 4.6% inactivity‐delayed‐study tracks 4.1 7.2 3.7 3.7 4.4 5.5 4.0

[6] – 1.6% inactivity/mix‐of‐activities tracks 2.0 2.2 0.8 1.6 1.2 1.5 2.1

[7] – 0.9% study/unemployment/study tracks 0.2 1.3 2.6 0.2 1.5 0.7 0.6

[8] – 0.2% unemployment tracks 0.1 0.3 0.3 0.0 0.3 0.1 0.1

[9] – 0.4% inactivity/unemployment tracks 0.2 0.9 0.7 0.1 0.6 0.4 0.3


Total 100 100 100 100 100 100 100

%‐share in pooled Nordic trajectory‐data 20.6 24.1 19.4 35.9 32.8 32.6 34.7



4.1.1 Mainfindings

In this sub‐chapter,wehave reported themain results obtainedwhenpooling country‐specific information on young people’s early post‐compulsory‐schooltrajectoriesintoonebigdataandperformingclusteranalysisonthisdatatoformtengroups(clusters)oftrajectories,acrosswhichourNordic youth are allocatedbyuseof optimalmatching.Thereportedresults,whichhereconcernallyoungpeoplebelongingtothethreeyouthcohortsunderscrutiny,providestrongsupportforthemostimportantobservationsmadeonthebasisofthecountry‐specificclusterresultspresentedinChapter3.ThisholdstrueformajorsimilaritiesaswellaskeydifferencesbetweenthefourNordiccountriesunderstudy.

Inparticular, large sharesofyoungpeople in the fourNordic coun‐triesfollowstandardstudytracks,implyingthattheycontinueineduca‐tion straight after completing compulsory school and typically stay infull‐time education for at least three years. This pattern is most pro‐nounced forSwedenand least so forDenmark. Inparallel,weobservemuchsmallerbut,nonetheless,conspicuoussharesofyoungpeople(a)droppingoutfrompost‐compulsoryeducationtomoveintoworkinglife;(b) delaying their entry intopost‐compulsoryeducationby spendingabreakyearworking;or (c)moving intoworking lifeonamoreperma‐nentbasis straightafter completingcompulsory school.Theseemploy‐ment‐dominated tracks are strikingly common among young Danes. Acomparison across cohorts reveals, however, that study tracks havegained in popularity among compulsory‐school leavers, mainly at theexpense of employment tracks. Not surprisingly, this trend isweakestforDenmark.

Additionally, we see non‐negligible shares of compulsory‐schoolleavers following trajectories dominated by NEET activities. All thesetrajectories tendto involveahighriskof theyoungpersonbeingmar‐ginalised from economic as well as social life. Moreover, as shown inChapter 3, these NEET‐dominated trajectories are observable mainlyamongthenon‐completers,i.e.youngpeoplehavingonlyacompulsory‐schoolexamstill at age21.Nextwe, therefore, turnour focus to thesenon‐completersusingapan‐Nordicperspective.


4.2 CommonNordictrajectoriesandclusters:non‐completers

Again,westartourpresentationofresultsforcommonNordictrajecto‐riesandclustersbyprovidingageneralpictureofhowyoungpeopleinthefourNordiccountriesaredistributedacrossthefivemainactivitiesateachagepoint from16up to20(Table4.3).However,nowtheem‐phasis is on non‐completers, implying that the subsequent results areobtainedbyexcludingallcompletersfromthepooledNordicdatausedintheprevioussub‐chapter.Inparticular,weformanewsetoftenclus‐ters based only on information about the non‐completers’ early post‐compulsory‐schooltrajectoriesuptoage20. Inthiscontext, it is there‐fore important to recall that the non‐completion rates at age 21 differconsiderablyacross the four countries, as shown inTable2.2ofChap‐ter2.ThismeansthatrelativelylargersharesofyoungDanesandNor‐wegians than of young Finns and Swedes enter this combined Nordicdata on non‐completers’ educational and labour market experienceswhenaged16to20.

Table 4.3: Distribution (%‐share) of young Nordic non‐completers across main activities, by age

Main activity Age Average for age 16

to 20 16 17 18 19 20

Student 75.2 69.4 54.5 37.9 32.4 53.9

Employed 4.0 10.6 18.2 30.0 36.0 19.8

Student or employed 79.2 80.0 72.7 67.9 68.4 73.7

Unemployed 2.1 4.3 9.3 12.1 12.7 8.1

Pensioner(on disability benefits) 1.2 1.2 1.9 3.3 4.2 2.4


NEET activities 20.9 20.1 26.3 32.0 31.6 26.4

Total 100.0 100.0 100.0 100.0 100.0 100.0

Notes: The %‐shares are calculated from pooled information on individual post‐compulsory‐

school trajectories up to age 20, as produced separately for each country’s non‐completers and

reported in Chapter 2.

AsshowninTable4.3,andinlinewithwhatwasobservedinChapter2,large shares of non‐completers continue in education straight aftercompletingcompulsoryschool.Morethanone‐halfofthemarefull‐timestudentsstillatage18,butlessthanone‐thirdtwoyearslater,atage20.Concomitantly,theshareofnon‐completersoutsidebotheducationandworkinglife(inNEETactivities)increasessteadily,from21%atage16to32%atage19,asharethatisapproximatelyunchangedoneyearlat‐er,atage20.This increase is,however,almostentirelyduetogrowingshares of non‐completers in unemployment and on disability arrange‐ments,whiletheirshareininactivity(“other”)changesonlymarginally


duringthesefirstfiveyearsaftercompletionofcompulsoryschool.Sim‐ultaneously,alsotheshareofnon‐completersinworkinglifegrowsrap‐idly, especially after age18.By age20, approximatelyone‐thirdof thenon‐completers are in education, one‐third in employment and one‐thirdinNEETactivities.

Afterthisbrieflookattheaverageage‐specificdistributionsofNordicnon‐completers across the fivemain activities under scrutiny,we turnour focus to the overall shape of these youngsters’ individual post‐compulsory‐schooltrajectoriesuptoage20.ThisinformationisgiveninFigure4.3,whichprovidesacumulativegraphofall sequencesofnon‐completers’ activities between age16 and20.As for thepooled youthpopulations analysed in theprevious sub‐chapter, also this graph is inreality a combination of the four country‐specific graphs for non‐completers presented and discussed in sub‐chapter 2.4.When poolingallthiscountry‐specificinformationonnon‐completers’earlyschool‐to‐worktrajectories,weendupwithindividualschool‐to‐worktrajectoriesofalmost200,000youngNordicnon‐completers.Accordingly,itishard‐ly surprising that Figure 4.3mediates a pattern thatwas observed al‐readybasedonthecountry‐specificresultsofChapter2.

Inparticular,theearlyschool‐to‐worktrajectoriesofnon‐completersdisplayed in Figure 4.3 form a “staircase” with young people leavingpost‐compulsory‐schoolinamoreorlesssmooth“step‐wise”way,main‐lyafterone,twoorthreeyearsinpost‐compulsoryeducation.Fewerofthemare likely to leaveafter fouryears in full‐timeeducation. Insteadthey often continue in post‐compulsory education still at age 20 butwithout having completed an upper secondary degree still by age 21.Somedropoutssoonreturntoeducationwhileothersstayinnon‐studyactivities.Moreover,thissamepatternseemstoholdtruealsoforthosenon‐completerswhodelay their start inpost‐compulsoryeducationbyspendingtypicallyoneyearoutsidebotheducationandthelabourmar‐ket(locatedatthebottomofthegraph).

Figure4.3also indicates that theprobabilityofnon‐completersget‐ting a job upon leaving post‐compulsory education increases, and ofendingupinNEETactivitiesdecreaseswiththenumberofyearsspentinpost‐compulsoryeducationbeforedroppingout.Inotherwords,moreyearsinuppersecondaryeducation,evenwithoutcompletingadegree,seemtoberelatedtolessriskyschool‐to‐workprofilesuptoage20.


Figure4.3:CommonNordicpathways:Individualschool‐to‐worktrajectoriesfromage16uptoage20forallnon‐completersinthefourNordiccountriesunderstudy,asobtainedfrompooledinformationonallthreeyouthcohortsunderscrutiny

Notes: The graph is obtained by pooling the information on non‐completers’ individual post‐

compulsory‐school trajectories up to age 20, as produced separately for each country and reported

in Chapter 2. The vertical axis gives the absolute number of individual school‐to‐work trajectories

and, hence, the absolute number of young non‐completers covered by the graph. The total number

of young people covered by the graph is 189,804 (61,884 for Denmark, 34,956 for Finland, 46,441

for Norway and 46,523 for Sweden). Non‐completers refer to young people who still five years after

completing compulsory education have no upper secondary degree.

Themaintypesofearlypost‐compulsory‐schooltrajectoriesfollowedbyNordicnon‐completersaredisplayedinFigure4.4withmoredetailsoneachofthetenclustersgiveninTable4.4.Alsothenon‐completersareheavily concentrated into the study‐track cluster (cluster 1): almostthree out of five Nordic non‐completers follow a study track straightupon having left compulsory school. Moreover, also among the non‐completersweobserveagrowth intheshare followingstandardstudytracks, implying that increasingly larger shares of the non‐completerscontinue directly in post‐compulsory education for typically three ormoreyears,butwithoutcompletinganuppersecondarydegreewithinfiveyearsaftercompletingcompulsoryschool.

In view of the strong dominance of standard study tracks amongSwedishyouth,itishardlysurprisingthatalsoyoungSwedeswithdiffi‐culties in completing an upper secondary degree continue in large


sharesinpost‐compulsoryeducation.Whiletwo‐thirdsofSwedishnon‐completersshowupinstandardstudytracks,thecorrespondingshareisonly about 43% among Finnish non‐completers, with Denmark andNorway fallingbetween these twoextremes (Table4.4).However, andaspointedoutalsoearlier,itismorecommonamongyoungFinnsthanamong other Nordic youth to delay their entry into post‐compulsoryeducationwith typically one year (cluster 9). These late starters com‐priseasmuchas14.3%oftheFinnishnon‐completerscomparedtoonly5% inDenmark.Whencombining thesharesof these twostudy‐track‐dominated clusters (1 and 9), we cover close to 58% of Finnish non‐completers.Butevenwiththisshare,FinlandstillranksbelowDenmark(62.4%)andfarbelowNorway(71.4%)andSweden(75.9%).

Another common set of non‐completers’ trajectories involves fre‐quentspellsinworkinglife,eitheronatemporaryor,soitseems,amorepermanent basis (clusters 6 and 7). Amajor difference between thesetwoclusters isthatcluster6containsemployment‐dominatedtrajecto‐riesinterruptedmainlybyyearsspentinfull‐timeeducation,whereasincluster7, theseeducationbreaksaremostly replacedby time spent inNEET activities. In view of cluster 7 thus containingmuchmore riskytrajectories,itisconfidenttonotethatitcovers,onaverage,only2.4%ofNordic non‐completers compared to 11% for cluster 6. However, thetimetrendforthesetwoclustersislesssatisfying:whiletherehasbeena decline across cohorts in the share of non‐completers going into thelessriskytrajectoriesofcluster6,thecorrespondingshareforthemoreriskytrajectoriesofcluster7revealsaslightincrease(Table4.4).

Asisonlytobeexpectedbasedonpreviouslypresentedresults,thestudy‐employment‐mixed tracks of cluster 6 aremost commonamongDanishnon‐completers,coveringalmostone‐fifthofthem.Theshareofnon‐completers going into cluster 6 is relatively high also in Finland(almost 12%), but quite low in Norway (5.4%) and Sweden (3.6%).When it comes to themore risky post‐compulsory‐school employmentprofiles contained in cluster 7, the situation looks quite differentwiththehighestshareobservedforFinnishnon‐completers(4.4%),followedby Danish non‐completers (3.1%), but very small shares for Swedish(1.4%)andNorwegian(0.7%)non‐completers.

Relativelylargesharesofnon‐completersdropoutafteroneyearinpost‐compulsory education andmove into NEET activities, either intounemployment(cluster2)or intoactivitiesoutsidebotheducationandthe labourmarket (cluster3).Althoughanon‐negligibleshareof theseearlydropoutsreturntoeducationeitheronatemporaryormoreper‐manentbasis,mostofthemseemtocontinueonbumpytrackswithfre‐


quent shifts between non‐study activities. The dropout‐into‐inactivitytracks of cluster 3 have retained, or even strengthened, their positionacross cohorts with a share of 7.2% in the oldest (1993) cohort and7.7%intheyoungest(2003)cohort.ThesetypesoftrajectoriesaremostcommonamongDanishnon‐completers,butquiteprevalentalsoamongNorwegian(8.7%)andSwedish(6%)non‐completers.Thedropout‐into‐unemploymenttracksofcluster2coveranotablysmallershareofNor‐dic non‐completers (2.2%). Moreover, the prevalence of this type oftrackshasdeclinedover timewithonly1.4%of thenon‐completers intheyoungest(2003)cohortfollowingsuchtracks.WhilethesetracksareofequalimportanceinFinlandandNorway,coveringcloseto5%ofthetwocountries’non‐completers,theyplayamarginalroleamongDanishandSwedishnon‐completers.

Figure4.4:CommonNordicclusters:Clusteringofyoungnon‐completers’school‐to‐worktrajectoriesfromage16uptoage20intotengroups,usingclusteranalysisonpooledinformationforallthreeyouthcohorts,allfourNordiccountriescombined

Notes: The clustering concerns the individual school‐to‐work trajectories of non‐completers dis‐

played in Figure 4.4 above, using the optimal matching methodology described in sub‐chapter 3.1.

The vertical axis of each graph gives the absolute number of young persons in the cluster, whereas

the percentage share on top of each graph shows the relative share of young people in the cluster.

The number in bracketed parentheses on top of each graph refers to the number given by the

algorithm creating the ten clusters by means of the subdivision procedure described sub‐chapter

3.1. Non‐completers refer to young people who still five years after completing compulsory educa‐

tion have no upper secondary degree.


Cluster10,coveringonaveragecloseto3%ofNordicnon‐completers,isrelatedtobothcluster2andcluster3inthesensethatalsothesetracksinvolvefrequentspells inNEETactivities.Amajordifference,however,is that the non‐completers going into cluster 10 do not drop out frompost‐compulsory education but, instead, move into NEET activitiesstraight after completing compulsory school. Another conspicuous dif‐ferenceisthatthetracksofcluster10aremuchmoreseldominterrupt‐edbyspells ineducationoremployment.Onthecontrary,thetrajecto‐riesofcluster10seemtocontainevermoretimespentoutsidenotonlyeducationbutalso the labourmarketwhen theseyoungstersapproachtheageof20.While theshareofnon‐completers followingthis typeoftrack has declined over time, these high‐risk pathways have remainedmore prevalent among Finnish and Norwegian non‐completers thanamongDanishandSwedishnon‐completers.

Cluster8containsyoungstersspendingmost,orall,oftheirfirstfiveyears after completing compulsory school outside both education andthelabourmarket,thatis,inunknownactivities(inactivity).Thesepro‐longedspellsininactivityearlyinlifemay,soitseems,turnintohighlydifferent subsequent activities. In other words, the outcome of theseinitialinactivityspellsisquitemixedwhenlookingatthesituationatage19orage20.Nonetheless,itseemsasifshorterinitialspellsininactivityaremore likely to end ina return to educationor a shift intoworkinglife,whereasprolongedspellsininactivitytendtoinvolveahigherriskof the young person continuing inNEET activities.While cluster 8 co‐vers, on average, 5.4% of Nordic non‐completers, its share is clearlyhigher(over8%)inbothFinlandandSweden.Moreover,acomparisonacross cohorts reveals that it containsamuch larger shareof thenon‐completers in the youngest (2003) cohort as compared to the oldest(1993) cohort (7.3% vs. 4.1%), implying that growing shares of non‐completers disappear for several years from all large administrativeregistersstraightaftercompletingcompulsoryschool.


Table 4.4: Distribution (%‐share) of young non‐completers across the ten common Nordic clusters displayed in Figure 4.4, by country and cohort

Cluster:


Country Cohort of 16‐year‐olds

DK FI NO SW 1993 1998 2003

[1] 58.2% study tracks 57.4 43.3 63.2 65.9 55.4 57.5 61.3

[2] 2.2% study/unemployment/mix tracks 0.3 4.7 4.6 0.8 3.9 1.6 1.4

[3] 7.5% study/inactivity/mix tracks 10.2 3.1 8.7 6.0 7.2 7.4 7.7

[4] 1.5% disability tracks 0.5 2.5 0.3 2.9 1.7 2.0 0.7

[5] 0.4% disability‐delayed‐study tracks 0.0 1.4 0.2 0.3 0.7 0.4 0.0

[6] 10.9% study/employment/study tracks 19.5 11.8 5.4 3.6 12.3 11.4 9.1

[7] 2.4% inactivity/employment tracks 3.1 4.4 0.7 1.4 1.9 2.7 2.4

[8] 5.4% prolonged‐inactivity tracks 3.5 8.9 2.5 8.1 4.1 4.8 7.3

[9] 8.8% inactivity‐delayed‐study tracks 5.0 14.3 8.2 10.0 8.3 9.8 8.2

[10] 2.9% unemployment/inactivity‐mix tracks 0.4 5.6 6.1 1.0 4.4 2.5 1.9

Total 100 100 100 100 100 100 100

%‐share in non‐completers’ pooled Nordic

school‐to‐work‐trajectory data

32.9 19.2 22.9 24.9 31.3 33.8 35.0


Thetwofinalclustersaredominatedbydisabilityarrangements,cover‐ingtogetherabout2%ofNordicnon‐completers.Bothclustersaredom‐inatedbyprolonged spells ondisabilitybenefits straight after comple‐tionofcompulsoryschool.Mostyoungpeopleexperiencingearlyhealthproblemstendtocontinueondisabilitybenefits(cluster4)whileonlyasmall share of them succeed in returning to education, either perma‐nentlyoronlyforayearortwo(cluster5).Theuninterrupteddisabilitytrackscontainedincluster4aremostcommonamongFinnishandSwe‐dish non‐completers, but show a declining trend over time, obviouslymainlydue tostrictereligibilityconditions foryoungpeople.Thedisa‐bility‐delayedstudytracksofcluster5occurmainlyamongFinnishnon‐completers, but these types of trajectories have basically disappearedamongnon‐completersbelongingtoyoungercohorts.

4.2.1 Mainfindings

This analysis of common Nordic trajectories and clusters for non‐completers largelyconfirmthemain findingsconcerningcross‐countrysimilaritiesanddissimilaritiespointedout inChapter3basedonsepa‐rate clustering of non‐completers for the four Nordic countries understudy.Themostdistinct featureofNordicnon‐completers is that largeandincreasingsharesofthemcontinuedirectlyinpost‐compulsoryedu‐cationandspendmost,orall,oftheirtimeuptoage20asfull‐timestu‐dents, but without completing an upper secondary degree by age 21.ThispatternismostprevalentamongSwedishnon‐completersandleastprevalentamongFinnishnon‐completers.Moreover, thisoverall cross‐


country pattern does not change, when adding the shares of non‐completers continuing in post‐compulsory education only after firsthaving spent typically one year in non‐study activities, and mostly inactivitiesnotshowingupinanylargeadministrativeregister.Theshareof non‐completers following these types of inactivity‐delayed studytracks has remained approximately unchanged across cohorts and ishighestamongFinnishnon‐completers.

Compared to these study tracks, the other trajectories play amuchsmaller role, covering notably lower shares of Nordic non‐completers.Broadlyspeaking,wecanidentifytwomajorcategories.Thefirstcatego‐ry contains various types of employment‐dominated trajectories withthe move into working life occurring immediately after compulsoryschool, after early dropout frompost‐compulsory education, or after ayear in inactivity straight after completion of compulsory school. Pro‐longed employment tracks as well as employment‐dominated tracksinvolving frequent returns to education are common especially amongDanishnon‐completersbutalsoamongFinnishnon‐completers.Howev‐er,theshareofsuchtracksamongthenon‐completersrevealsadeclin‐ing trend over time. Early employment tracks coupled with frequentspellsininactivityaremuchlesscommon,butrevealaslowlyincreasingtrend.ThesebumpyemploymenttracksaremostcommonamongFinn‐ishnon‐completers.

Thesecondcategoryconsistsofnon‐completersfollowinghighlydif‐ferentearlypost‐compulsorytrajectories,acommonfeatureofwhichisthat they for themost part represent high‐risk tracks. In otherwords,theyaredominatedbyNEETactivitieswhichfollowuponanearlydrop‐out from post‐compulsory education, or into which the young personmovesstraightaftercompletingcompulsoryschool.Onlyoccasionallydothesetracks involveareturntoeducationeventemporarily.Moreover,theshareofnon‐completersfollowingtracksdominatedbyNEETactivi‐ties has remained practically unchanged over cohorts. A comparisonacrossthefourNordiccountriesimplies, inturn,thattheshareofnon‐completers finding themselves in high‐risk NEET‐dominated tracks ismuchlower inDenmarkthan intheotherthreecountries.Hence,oncemoreweare inclined to conclude thatDanishnon‐completers seem tofair better than Finnish, Norwegian and Swedish non‐completers.Whether this holds true also beyond the age of 20 is an issue thatwereturntoinChapters6and7.

Ontheotherhand, there isreasontorecallalso in thiscontext thattheshareofyoungnon‐completersdiffersconsiderablyacrossthe fourNordic countries under study (see Chapter 2). While the summary in


Table4.4 illustrateswell thesituationamongyoungnon‐completers inthedifferentcountries,itoverlooksthefactthatthesepercentagesharescover,ineffect,highlyvaryingproportionsofthefullyouthpopulationineachcountry. InTable4.5we, therefore, recalculate thedistributionofyoungnon‐completersinTable4.4byrelatingeachpercentagesharetothefullyouthpopulationofthecountryinquestion.

Table 4.5: Distribution of young non‐completers across the ten common Nordic clusters displayed in Figure 4.4, by country, %‐share of the full youth population

Cluster:

number ‐ label

%‐share of the full youth population


[1] study tracks 21.4 7.8 18.8 10.5

[2] study/unemployment/mix tracks 0.1 0.8 1.4 0.1

[3] study/inactivity/mix tracks 3.8 0.6 2.6 1.0

[4] disability tracks 0.2 0.5 0.1 0.5

[5] disability‐delayed‐study tracks 0.0 0.3 0.1 0.0

[6] study/employment/study tracks 7.3 2.1 1.6 0.6

[7] inactivity/employment tracks 1.2 0.8 0.2 0.2

[8] prolonged‐inactivity tracks 1.3 1.6 0.7 1.3

[9] inactivity‐delayed‐study tracks 1.9 2.6 2.4 1.6

[10]unemployment/inactivity‐mix tracks 0.1 1.0 1.8 0.2

Non‐completers’ share in the full youth population 37.3 18.0 29.7 16.0

Notes: The percentage shares displayed in Table 4.4 as recalculated in relation to the full youth

population of each country.

Duetotheprevailingcross‐countrydifferencesinnon‐completionratesamongthe21‐year‐olds,thisrescalingisboundtoproduceapicturethatdiffersfromtheoneemerginginTable4.4.Wenowobservethatthoseyoung non‐completers having followed study‐dominated tracks uponcompletion of compulsory school cover nearly one‐third of theDanishandmorethanone‐fifthoftheNorwegianyouthpopulation.Thecorre‐sponding share for both Finland and Sweden is only about 10%. Fur‐thermore, about 6% of Finnish aswell as Norwegian youths have fol‐lowed one of the four inactivity‐dominated tracks (track [7] to [10]),comparedto,respectively,only3.3and4.5%forSwedenandDenmark.A common feature of the four countries, however, is that disabilitytracksarefollowedbyapproximatelythesameproportionofyouthinallfourcountries.

Allinall,whenrelatingtheproportionofyoungnon‐completershav‐ing followeddifferent tracksuponcompletionof compulsory school tothefullyouthpopulation,theoverallpatternchangesincertainrespects.As noted above, the reason is simple: young non‐completersmake uphighly different shares of the full youth population in the four Nordiccountries under study. Thus, the relatively large share of 21‐year‐oldnon‐completersinDenmarkimpliesthattheproportionofDanishyouth


following standard study tracks or study/employment tracks straightaftercompletingcompulsoryschool–butwithoutcompletinganuppersecondary degree by age 21 – ismuch larger in Denmark than in theotherthreecountries.Thisrescalinginproportiontothefullyouthpop‐ulationalsoshowsthatthesituationinNorwayresemblesmorethatinDenmarkthanthepictureemergingforFinlandandSweden,especiallywhenitcomestoalargeshareofyoungsterscontinuingineducationbutwithoutcompletinganuppersecondarydegreebyage21.WithFinland,inturn,Norwaysharesthefeatureofhavingarelativelylargegroupofyoungsters turning into young non‐completers because they end upoutsidebotheducationandthelabourmarketalreadyatanearlyage.

5. Non‐completers’ school‐to‐work trajectories: stylizedcluster results

In the previous chapter, country‐specific information on individualschool‐to‐work trajectorieswas pooled into one big data. Based on allthisinformationforthefourNordiccountriesunderstudy,tencommonNordicclusterswereformedforallyoungpeopleandseparatelyforthenon‐completers. The results obtained for the common Nordic clusterspresented inChapter4provided further support for thebroadpicturepaintedalreadybythecountry‐specificclusterresultsreportedinChap‐ter 3. Basically two distinct features emerged. First, large shares ofyoungpeople in theNordiccountries followstudy tracksstraightaftercompletingcompulsoryschool,occasionallyonlyafterabreakyearbe‐foreenteringpost‐compulsoryeducation.Therestoftheidentifiedclus‐tersof typicalschool‐to‐worktrajectoriesplayamoremarginalroleasalternativestostandardstudytracksinthesensethattheycovermuchsmaller, but by no means negligible, shares of young people. Second,whilestandardstudytracksareoftenfollowedalsobynon‐completers,thesealternativetypesoftracksplayamuchmoreimportantroleamongyoungpeoplefacingproblemsincompletinganuppersecondarydegree,letalonestartinganuppersecondaryeducation.

While there are striking similarities between the fourNordic coun‐triesinalltheserespects,theyrevealdistinctdifferences,aswell.Inthischapter,wetakeacloserlookatthesedifferences,butalsosimilarities,whenitcomestotheearlypost‐compulsory‐schooltrajectoriesfollowedbyNordicnon‐completers.Thisisdonebyuseofclusteringbyreferencesequences, amethodoutlined in somedetail inChapter3. Inbrief, thebasicideaistochooseanumberofreferencesequencesandclustertheothersequencesaroundthesereferencesequences.Byuseofthesamereference sequences for all fourNordic countries,we are able to shedfurther light on both similarities and dissimilarities across the fourcountriesinrelationtonon‐completers’post‐compulsory‐schoolexperi‐encesuptoage20.


5.1.1 16stylizedpathways

Fortheclusteranalysisreportedinthischapter,weconstructedatotalof16referencesequences.Weprefertocallthesereferencesequences“styl‐ized pathways”, aswe have explicitly aimed at identifying reference se‐quencesfornon‐completers’mainpost‐compulsory‐schoolactivitiesuptoage20whichresembleascloselyaspossiblethe“typical”trajectoriesofnon‐completersdistinguishedbothinthecountry‐specificclusteranalysisofChapter3andinthecommonNordicclusteranalysisofChapter4.Twomain criteriawere usedwhen selecting these stylized pathways. A firstcriterionwas:Forhowlongdotheyoungnon‐completersstayinitiallyinpost‐compulsory education? A second criterion was, logically: What istheirmainactivity if leaving school?Basedondifferent combinationsofthesetwocriteria,weconstructedatotalof16stylizedpathwaysforthenon‐completers. Thereafter,we allocated all non‐completers to the styl‐izedpathwaythatlookedmostsimilartothetrajectorytheyhadactuallyfolloweduponcompletionofcompulsoryschool,uptoage20.Hence,theonlydifferenceinthissetting,whencomparedtotheclusteringundertak‐en inChapters4and5 is thathere, theclustersarepre‐determined(byus)andnotdecidedbytheclusteringmethodused.

Table5.1presentsthe16stylizedpathwaysconstructedbasedonthetwo aforementioned criteria, grouped after the non‐completer’s mainactivityafterleavinguppersecondaryeducation:continueineducation,employment, unemployment, disability arrangements or “other” (i.e.unknowninactivity).Thenumberseriesinthecolumnlabelled“stylizedpathways”showsthepre‐determinedreferencesequencesofmainactiv‐ities from age 16 up to age 20. Each number signifies amain activity,defined in the same way as in the previous chapters, that is, with 1standingfor full‐timestudent,2 forbeingemployed,3 forbeingunem‐ployed,4forreceivingdisabilitybenefits,and5forbeinginthedumpingcategory“other”.Theorderofthesenumbersdenotestheyearinwhichthe activity takes place. For instance, the stylized pathway [11122]meansthattheyoungpersonspendsthefirstthreeyears,fromage16toage 18, in post‐compulsory education. Thereafter, this person movesinto working life and stays employed up to age 20. This employmentspellmay,ofcourse,continuebeyondage20–asmightanyoftheothermain activities. Also in this chapter, however, we stop our tracing ofyoung people’s activities at age 20. Only in the next chapters will weinvestigatewhathappensbeyondtheageof20.

Next we turn to the clusters formed when allocating all non‐completersacross these16stylizedpathways, separately foreachcoun‐try. As already pointed out above, this means that all non‐completers


showup inoneof the16 clustersbuilt around these stylizedpathways,dependingonwhichpathwaycomesclosesttothenon‐completer’sactualpost‐compulsory‐schooltrajectory.WepresenttheseresultsbyfollowingthecategorizationofpathwaysusedinTable5.1.Inotherwords,westartfromthe firstcategorycontainingstylizededucationalpathways, that is,two typical post‐compulsory‐school trajectories dominated by non‐completers spending practically all their time up to age 20 as full‐timestudents(butwithoutobtaininganuppersecondarycertificatebyage21).

Table 5.1: Overview of pre‐determined reference sequences: 16 stylized pathways

Main activity after leaving

education (criterion 2)

Years in post‐compulsory education up to

age 20 (criterion 1)

Stylized pathways

Continue in education all 5 years in education [11111]

delayed start, all 4 years in education [51111]

Employment first 3 years in education [11122]

first 2 years in education [11222]

first (initial) year in education [12222]

no entry into post‐compulsory education [52222]

Unemployment first 3 years in education [11133]



Disability benefits (pensioner) first 3 years in education [11144]



Other (inactivity) first 3 years in education [11155]



no entry into post‐compulsory education [55555]

Notes: 1 = full‐time student, 2 = employed, 3 = unemployed, 4 = disability beneficiary, 5= “other”.

For other explanations of the table, see the text.

5.1.2 Stylizededucationalpathways

Thecountry‐specificgraphscontained inFigure5.1 illustratewhat thetwostylizededucationalpathwaysactually look like in the fourNordiccountries, and also howprevalent they are in each country.As before,theverticalaxisofeachgraphgivestheabsolutenumberofyoungpeo‐plecoveredbythegraph,whereastheinformationontopofeachgraphshowsthestylizedpathwayinquestionandtheshareofeachcountry’snon‐completersgoingintothatparticularcluster.Hence,these%‐sharesofthe16stylizedpathwaysarecountryspecificand,accordingly,sumupto100%foreachcountry.Somemoredetails,bygenderandcohort,areprovidedintheaccompanyingtable(Table5.2).

Figure5.1confirmstheoverallpicturefornon‐completersmediatedby theresultspresented inChapters3and4: largesharesofalsonon‐completers continue, either directly or after a break year, in post‐


compulsory education. In particular, these two sets of country‐specificgraphsamplifythisoverallpicturebyexplicitlyillustratingthesharesofnon‐completersspendingallormostoftheirtime,fromage16uptoage20, as full‐time students. Indeed, these two stylized educational path‐wayscan,ineffect,beseenasextremecasesofthemoregeneralstudy‐trackclustersformedinChapters3and4inthesensethattheyidentifynon‐completersthatarehighlyengagedinpost‐compulsorystudiesbut,nonetheless,failtoachieveanuppersecondarydegreewithinfiveyearsaftercompletingcompulsoryschool.AscanbeseenfromFigure5.1,theshareofthesefull‐time‐studyingnon‐completersishighestinDenmark(35%), closely followedbyNorwayandSweden,and lowest inFinland(closeto22%).Whenaddingtheshareofnon‐completersdelayingtheirentry into post‐compulsory education, the two stylized educationalpathwayscoveralmost40%oftheDanishnon‐completersand35–37%ofthenon‐completersintheotherthreecountries.Again,Finland“clos‐es the gap” to the other three countries due to a comparatively highshareoflatestarters(13.5%).

Figure5.1:Stylizededucationalpathwaysofnon‐completers,bycountry

Notes: The clustering concerns individual school‐to‐work trajectories of non‐completers when aged

16 to 20, using clustering by reference sequences as described in sub‐chapter 3.1. The vertical axis

of each graph gives the absolute number of non‐completers in the cluster, whereas the percentage

share on top of each graph shows the relative share of non‐completers in the cluster, by country.

The country‐specific percentage shares for the 16 stylized pathways thus sum up to 100% for each

country. The number in bracketed parentheses on top of each graph refers to the stylized pathway

in question as described in Table 5.1. For more details, by gender and cohort, see Table 5.2 below.

This full,orclose to full,engagement ineducationover the fiveyearsfollowingupon completion of compulsory school reveals no clear‐cutgendered pattern across the four countries, as is evident from Table5.2.InNorwayandespeciallyinDenmark,youngmenaremorelikely


thanyoungwomentocontinueinpost‐compulsoryeducationformostorallyearsuptoage20,butwithoutcompletinganuppersecondarydegree by age 21. The share in these two countries of education‐engaged non‐completers delaying their entry into full‐time educationis small, covering an approximately equal share of young men andyoungwomen.InFinlandandSweden,ontheotherhand,thesituationis the opposite, except for Swedish late starters. These cross‐countrydifferencesingenderedsharesdonotchangewhenaddingupthenon‐completer sharesof the twostylizededucationalpathways, as showninthelowerhalfofTable5.2.

Thesegender‐specificfindingsareinterestinginviewofthecountryresultsfornon‐completersreportedinChapter3:forallfourcountries,weobservedthatyoungmenaremorelikelytofollownon‐completers’studytracks,whereasyoungwomenaremorelikelytofollowcomplet‐ers’studytracks.However,accordingtoTable5.2,thispatterndoesnotnecessarilyholdtrueforFinlandandSwedenwhenrestrictingthenon‐completers’studytrackstocoveronlythosewithmost,orall,yearsuptoage20spent in full‐timeeducation. Instead, these twocountries ra‐ther reveal a kind of segmentation by gender when it comes to non‐completers’studytracks:femalenon‐completersseemtobemorelikelyto follow “longer” (uninterrupted) study tracks, whereas male non‐completerstendtomoreoftenfollow“shorter”orbumpierstudytracks.Yet,despitethisdifferenceinpost‐compulsory‐schoolengagement,theirsituation at age21 is identical: still five years after compulsory schooltheyonlyhaveanexamfromprimaryeducation.

Table 5.2: Distribution (%‐share) of young non‐completers across the two stylized educational pathways displayed in Figure 5.1, by country, gender and cohort

Years in post‐compulsory

education up to age 20

[stylized pathway]

%‐share

in the

cluster


Male Female 1993 1998 2003

All 5 years in

education

[11111]

Denmark 35.0 39.2 29.9 32.6 38.0 34.5

Finland 21.6 19.7 24.4 20.6 21.0 23.3

Norway 30.3 31.3 28.9 25.2 31.4 33.8

Sweden 29.1 27.9 30.6 31.8 25.2 30.5

Delayed

start, all 4

years in

education

[51111]

Denmark 4.1 3.1 3.4 1.6 4.9 5.8

Finland 13.5 12.4 15.2 10.4 13.8 16.2

Norway 6.2 6.3 6.2 8.9 5.6 4.6

Sweden 7.7 8.0 7.4 12.3 8.8 3.4

Total share =

[11111] +

[51111]

Denmark 39.1 42.3 33.3 34.2 42.9 40.3

Finland 35.1 32.1 39.6 31.0 34.8 39.5

Norway 36.5 37.6 35.1 34.1 37.0 38.4

Sweden 36.8 35.9 38.0 44.1 34.0 33.9



Also the time trend(acrosscohorts) for these twostylizededucationalpathwaysdiffersincertainrespectsfromtheoneobservedinChapters4and 5. More precisely, while the previously reported results point togrowing shares of also non‐completers in study tracks, the patternemergingfromTable5.2ismorediversified.Inparticular,thistrendofincreasinglymorenon‐completersfollowingstudytracksdoesnotseemtohold true forSwedishnon‐completersspendingmost,orall,of theirtime up to age 20 as full‐time students. Instead, their share reveals adeclining trend, especially with respect to delayed entries into post‐compulsory education. Hence, the composition of Swedish non‐completers’ study tracks seems to have undergone a major change intwo,potentiallycloselylinkeddimensions:theshorterandmorebumpypost‐compulsory‐school study tracks appear to have increased at theexpenseoflongerandlessinterruptedstudytracksand,asnotedabove,this tendency seems to have been stronger for young men than foryoungwomen.Indeed,thiscouldwellbeonemajormechanismunderly‐ing the growing gender gap in non‐completion rates discernible forSwedeninFigure2.2dofChapter2.

5.1.3 Stylizedemploymentpathways

Next,weturntothefourstylizedemploymentpathwaysdefinedinTa‐ble 5.1 above.As shown in that table, the only differencebetween thefour pathways is the number of consecutive years spent by the non‐completer in post‐compulsory education before moving into workinglife.Accordingly,thesefourpathwayscanbeexpectedtodetailthegen‐eralpicturemediatedbythebroademploymentclustersunderlyingtheresultsreportedinChapters3and4.

The first set of graphs in Figure 5.2 illustrates the outcome for thefourNordic countriesunder studywhen it comes to the stylizedpath‐waywheretheyoungpersoncontinuesdirectlyinpost‐compulsoryedu‐cation for three consecutive years before moving into working life[11122]. The cross‐country differences in non‐completers’ shareswithrespect to this pathway are rather small, ranging from 10–11% forDenmarkandNorwayto14–15%forFinlandandSweden.Hence,manyyoungpeople leaveuppersecondaryschoolafter threeyears forwork,eventhough theyhavenotsucceeded inachievinganuppersecondarycertificate.Moreover,theroleofthesestudy–employmentpathwayshasincreasedovertimeinallfourcountries,althoughthistrendislessclear‐cutforNorwayandSweden(Table5.3).


ThesecondsetofgraphsinFigure5.2givesthesameinformationforthenextstylizedemploymentpathway:thepersoncontinuesdirectlyinpost‐compulsory education, but only for two years before substitutingeducation with work [11222]. The share of non‐completers allocatedaroundthisstylizedpathwayislower(Finland)ormuchlower(NorwayandSweden),whencomparedtothecorrespondingsharefortheprevi‐ous,more“standard”pathway[11122].OnlyforDenmarkdowegetanoppositeresult.Inallfourcountries,however,therehasbeenadeclinein the share of non‐completers following this type of employment‐interruptededucationpathway.

A slightly (Denmark) or notably lower (Finland, Norway, Sweden)shareof thenon‐completersare clusteredaround the stylizedemploy‐ment pathwaywhere non‐completers spend only one year in full‐timeeducation straight after completing compulsory school before enteringworking life. In all four countries, many of these early employmenttrackstendtobequiteunstable,though.However,alsotheseearlyem‐ployment pathways cover decreasing shares of the non‐completers,whencomparing thesituationacross cohorts.Again thisholds true forallfourNordiccountries.

The fourthand last setofgraphs inFigure5.2concernsemploymentpathwaystypicallystartingwithayearininactivitystraightaftercomplet‐ing compulsory school before entering working life. The share of non‐completersfollowingthistypeoftrackiscomparativelylargeonlyinFin‐land. Moreover, this high share for Finnish non‐completers reveals aweak,ifany,downwardtrendovertime.AmongDanishnon‐completers,thistypeofpathwayisclearlyontherise,withtheirsharehavingrapidlyapproached the level observed for Finland (Table 5.3). In Norway andSweden,thesmallshareofnon‐completersallocatedaroundthisstylizedpathwayhasdeclinedfurtherovertime.


Figure5.2:Stylizedemploymentpathwaysfornon‐completers,bycountry








Allinall,twomaincontentionscanbemadebasedonthesefourstyl‐izedemploymentpathways.First,employmenttracksaremorepreva‐lentamongDanishnon‐completersthanamongnon‐completersintheother three countries: almost 36% of the Danish non‐completers gointo one of the four employment pathways. Second, the role of theseemployment pathways, as measured by the share of non‐completerscovered, increaseswith thenumberofyearsspent in full‐timeeduca‐tion beforemoving intoworking life. Put differently, the fewer yearsnon‐completers initiallyspend inpost‐compulsoryeducation, the lesslikelytheyaretomoveintoemploymentcareersofamorepermanentnature.BothfindingslendfurthersupporttotheconclusionsdrawninChapters3and4.


We conclude this section with a few words on the distribution ofyoung men and women across these four stylized employment path‐ways.BasedonTable5.3, thereseemstobenoobviouspattern inthisrespect, neither within countries nor between countries. The [11122]pathwaycoversalargershareofyoungmenthanofyoungwomen,ex‐ceptinDenmarkwherethesituationistheopposite.The[11222]path‐waycoversalargershareofyoungmenthanofyoungwomen,exceptinDenmarkandSwedenwherethesituationistheopposite.The[12222]pathwaycoversalargershareofyoungmenthanofyoungwomen,ex‐cept in Norway and Sweden where the gendered shares are approxi‐mately of the same size. The [52222] pathway, finally, covers a largershare of young men than of young women, except in Norway wherethesetwosharesare,again,ofmuchthesamesize.

Table 5.3: Distribution (%‐share) of young non‐completers across the four stylized employment pathways displayed in Figure 5.2, by country, gender and cohort

Years in post‐compulsory education

before moving into working life [stylized

pathways]

%‐share

in the

cluster


Male Female 1993 1998 2003

first 3 years in education

[11122]

Denmark 10.2 9.0 9.6 8.6 9.8 12.1

Finland 11.1 13.3 7.8 7.7 11.4 13.8

Norway 14.6 15.1 13.8 11.6 16.8 15.1

Sweden 13.8 14.3 13.2 8.3 18.3 13.9

first 2 years in education

[11222]

Denmark 11.8 12.1 12.4 14.5 10.0 11.0

Finland 8.8 9.9 7.2 9.8 9.7 6.9

Norway 9.4 10.1 8.5 10.3 10.7 7.6

Sweden 7.4 6.8 8.2 6.8 9.2 6.2

first (initial) year in educa‐

tion

[12222]

Denmark 9.7 11.0 9.8 12.0 9.0 8.4

Finland 4.4 4.7 3.8 5.5 4.7 2.9

Norway 2.7 2.7 2.8 3.3 3.3 1.6

Sweden 2.0 1.9 2.1 2.3 2.2 1.6

No entry into post‐

compulsory education

[52222]

Denmark 3.9 3.9 2.8 3.3 3.6 4.7

Finland 6.2 6.8 5.4 5.9 7.3 5.2

Norway 0.9 0.8 1.1 1.4 1.0 0.4

Sweden 2.1 2.5 1.7 2.4 2.3 1.8

Total share =

[11122] + [11222] +

[12222] + [52222]

Denmark 35.6 36.0 34.6 38.4 32.4 36.2

Finland 30.5 34.7 24.2 28.9 33.1 28.8

Norway 27.6 28.7 26.2 26.6 31.8 24.7

Sweden 25.3 25.5 25.2 19.8 32.0 23.5


5.1.4 Stylizedunemploymentpathways

In Table 5.1, we distinguish between three stylized unemploymentpathways,whichdifferfromeachotheronlywithrespecttothenumberof years spent by the youngnon‐completer in post‐compulsory educa‐tion before becoming unemployed (i.e., registering as an unemployedjobseeker).ThefirstsetofgraphsinFigure5.3departsfromthetypical


uppersecondarystudytrackofthreeyears,uponwhichfollowsspellsinunemployment[11133].Thesecondsetofgraphshighlightsasituationwheretheyoungnon‐completerdropsoutfrompost‐compulsoryeduca‐tionalreadyaftertwoyears[11333],whereasthelastsetofgraphsco‐vers a situationwith theyoungnon‐completermoving intounemploy‐mentalreadyafteroneyearinpost‐compulsoryeducation[13333].

InlinewiththeresultsreportedinChapters3and4,thesestylizedun‐employmentpathwaysarerelativelyinfrequentamongyoungNordicnon‐completers:inallfourcountries,eachofthemcovers,atmost,some5%ofthenon‐completers– typicallymuch less.Theonlyexception is Swedenwith a share of close to 12%of thenon‐completersmoving into unem‐ploymentuponleavinguppersecondaryschoolafterthreeyears(withoutadegree).Thecorrespondingshareismuchlowerintheotherthreecoun‐tries,withDenmarkdownat2.1%.Acommon featureof the four coun‐tries,however, is thattheshareofnon‐completersfollowingthistypeofdropout–unemploymenttrajectoryrevealsaweakdeclineacrosscohorts(Table 5.4). Another joint feature is aminor difference in the shares ofyoungmenandyoungwomenfollowingthistypeoftrajectory.

Figure5.3:Stylizedunemploymentpathwaysofnon‐completers,bycountry









Comparedtothe[11133]pathway,Swedenhasanotablylowershareofnon‐completers ending up in unemploymentwhen dropping out frompost‐compulsoryeducationalreadyaftertwoyears.ThisholdstruealsoforNorway,whereasthesetwounemploymentpathwayscoverapprox‐imately equal shares of the non‐completers in bothDenmark and Fin‐land. However, the ranking of the four countries remains unchangedwithSwedenshowingupwiththehighestandDenmarkwiththelowestshare. A distinct feature of this [11333] pathway is that the share ofyoung non‐completers following this type of school‐dropout trajectoryhasdeclinedsubstantiallyovertime.Thisdeclinehasbeenparticularlystrong for Finland. Additionally, Finland is characterised by a clearlyhighershareofyoungmalethanofyoungfemalenon‐completersfollow‐ingthistypeofdropout–unemploymenttrack.However,allthesepeculi‐arities are related to the difficult employment situation of especiallylow‐educated youngsters following upon the deep recession that theFinnisheconomyplungedintointheearly1990s(cf.theFinnishclusterresults fornon‐completers inChapter3).TheyoungerFinnishcohorts,in contrast, face an unemployment situation which is quite similar tothatexperiencedbyotheryoungNordicnon‐completers.

Also the share of non‐completers showing up as unemployedjobseekers already when aged 17, is conspicuously high for Finland(about5%),butvery lowintheother threecountries.Theexplanationis, by and large, the same as in the previous case: widespread unem‐ploymentamonglow‐educatedyoungpeoplestartinginthedeepreces‐sion years of the early 1990s. As is evident in Table 5.4, the share ofFinnish non‐completers moving into unemployment more or lessstraightaftercompulsoryschoolhasshrunkfromabout13%intheold‐est(1993)cohortto1.2%intheyoungest(2003)cohort,asharewhichisverymuchinlinewiththesharesobservedfortheotherthreecoun‐tries.Finally,asfortheothertwostylizedunemploymentpathways,wesee declining shares across cohorts in all four countries andminor, ifany,differencesinthesharesofthetwogenders.


Table 5.4: Distribution (%‐share) of young non‐completers across the three stylized unemploy‐ment pathways displayed in Figure 5.3, by country, gender and cohort

Years in post‐compulsory education

before moving into unemployment

[stylized pathway]

%‐share

in the

cluster


Male Female 1993 1998 2003

First 3 years in education

[11133]

Denmark 2.1 2.0 2.7 2.3 2.4 1.6

Finland 3.5 3.7 3.1 4.2 3.5 2.8

Norway 4.5 4.8 4.1 5.4 4.2 4.1

Sweden 11.6 11.8 11.2 12.6 10.7 11.5


[11333]

Denmark 1.8 1.6 2.3 2.0 1.9 1.6

Finland 3.7 4.2 2.9 7.1 2.6 1.7

Norway 3.0 3.3 2.6 4.7 2.5 2.0

Sweden 4.2 4.1 4.4 6.1 3.4 3.6

First (initial) year in

education

[13333]

Denmark 0.7 0.7 0.9 0.8 0.7 0.5

Finland 5.1 5.4 4.6 12.8 2.2 1.2

Norway 1.9 2.0 1.9 3.5 1.3 1.1

Sweden 0.8 0.8 0.9 1.3 0.6 0.6

Total share =

[11133] + [11333] +

[13333]

Denmark 4.6 4.3 5.9 5.1 5.0 3.7

Finland 12.3 13.3 10.6 24.1 8.3 5.7

Norway 9.4 10.1 8.6 13.6 8.0 7.2

Sweden 16.6 16.7 16.5 20.0 14.7 15.7


Broadly speaking, these stylized unemployment pathways thus coverrelatively small and further declining shares of young Nordic non‐completers.Whilethisistheoutcomeofadecliningtrendobservedforall three pathways, the early dropout trajectories [13333 and 11333]havecontributedmoretothisdeclinethanthemore“standard”[11133]trajectory.Thisfindingislikelytobetheoutcomeofseveraltrends.Thisdecline in the share of young non‐completers following dropout–unemployment trajectories may well reflect a situation where youngpeople truly try to avoid this typeof high‐risk track.However, thede‐clinemayalsosimplyreflectasituationwherethetightenedconditionsfor receivingunemployment benefits havemade youngpeople less in‐clinedtoregisterasunemployedjobseekers(inwhichcasetheygointothe dumping category labelled “other”). The observed decline is alsolikelytoreflectintensifiedyouthunemploymentpolicies,coupledwithafavourable economic development, where low‐educated youngstersregisteringasunemployedhave increasinglybeendirectedeitherbackintoschoolor intovarioustypesofarrangementsequippingthemwithworkpractises(inthe formercasetheyturnupinourdatasetsas full‐time students, in the latter case as employed). Indeed, the time trendsfor thestylizededucationalandemploymentpathwaysexplored in theprevious sections seem to lend further support to this last interpreta‐tion.Themuchhigher sharesof youngnon‐completers coveredby the[11133]pathwaymay,inturn,betakentoindicatethatnon‐completershaving spentmore years in post‐compulsory education before experi‐


encing(registered)unemploymentare,firstandforemost,slightlyolderand,hence,more likelytostart in“ordinary”active labourmarketpro‐gramswhenfacingprolongeddifficultiesinfindingajob.

WithbothFinland,NorwayandSweden fitting into thisoverallpic‐ture,Denmarkisanprofoundexceptionwithsmallandfurtherdecliningshares of young non‐completers moving early into unemployment‐dominated pathways. Even taken together, the three stylized unem‐ploymentpathwayscoverlessthan4%oftheDanishnon‐completersinthe youngest (2003) cohort (Table 5.4). The corresponding share is5.7%forFinland,7.1%forNorwayandashighas15.7%forSweden.

5.1.5 Stylizeddisability‐benefit(pensioner)pathways

The three stylized disability‐benefit pathways describe a situationwhere the young non‐completer moves into disability arrangementsafterthree,twooronlyone,ifany,yearsinpost‐compulsoryeducation[11144, 11444, 14444]. Depending on the system in place, the youngpersoniseitherondisabilitybenefitsofamorepermanentnature,oronso‐calledrehabilitationbenefits,whicharetypicallymeanttobetempo‐rarybutmayalsoprecedemorepermanentdisabilityarrangements.

Figure 5.4 contains these three sets of stylized disability‐benefitpathways, showing the prevalence of each of them in the four Nordiccountries under study. A general observation is that few young non‐completersmoveintothistypeofpost‐compulsory‐schooltrack.Takentogether, the three graphs illustrating the situation forDenmark coveran average of only 1.3% of Danish non‐completers. The three graphsalso reflect the country’s institutional settingwith young people beinggrantedadisabilitypensiononlyfromage18(cf.Chapter2).Inviewofthis,itisnotsurprisingthatamajorityofyoungDanishnon‐completersmove intodisabilitypensionarrangements immediatelywhen fulfillingtheagecondition.Thisisalsothecategoryofyoungdisabilitypension‐ersthatstandsbehindtheobservedincreaseacrosscohortsintheDan‐ishshareofdisability‐pension‐receivingnon‐completers(Table5.5).


Figure5.4:Stylizeddisability‐benefitpathwaysofnon‐completers,bycountry








Also Norway displays an increasing trend in the share of young non‐completersgoingintodisabilityarrangements.AgrowingshareofNor‐wegianyouthreceivingtemporaryorpermanenthealth‐relateddisabil‐itybenefitsis,ineffect,alsoreportedby,forexample,BragstadandBra‐ge(2011),withthisdevelopmentshowntobemainlyduetoasteepriseinyoungdisabilitybeneficiariessuffering fromseverementaldiseases.Otherwise, the situation in Norway looks quite different compared tothat observed for Denmark. In particular, most Norwegian non‐completers following a disability‐benefit track have stayed in post‐compulsoryeducation for threeormoreyearsbefore showingupas adisabilitybeneficiary[11144].Thisisalsothecategoryhavingincreasedover time, especially among non‐completers in the youngest (2003)cohort(Table5.5).Mostprobably,themainreasonforthegrowthinthenumberofyoungdisabilitybeneficiariesbeingconcentratedtothispar‐ticulartrackistheinstitutionalchangesmadeinNorwaywithrespecttoyoungpeoples’possibilities tomove intodisabilityarrangementsatanearlyage(cf.Chapter2).


AnotherpatternemergesforFinlandandSweden.Bothcountriesap‐peartohavecomparativelylargesharesofyoungnon‐completersgoinginto disability arrangements straight after completing compulsoryschool.ThistypeofdisabilitybenefittrackistotallymissinginDenmarkandcoversanegligibleshareofyoungnon‐completersinNorway.How‐ever,theshareofFinnishandSwedishyoungstersfollowingsuchtrajec‐tories has declined remarkably over cohorts, mainly due to profoundchangesinthedisabilitybenefitsystemforyoungpeople(cf.Chapter2).Indeed,thechangehasbeenquitedramaticforSweden:ashareof0.1%intheyoungest(2003)cohortcomparedtoabout4.5%inthetwooldercohorts (Table5.5).Simultaneously, therehasbeenanotable increase,from0.4%to1.9%,intheshareofyoungSwedishnon‐completersmov‐ingintodisabilityarrangementsataslightlyhigherage,viz.aftertheageof 18.While we observe a similar pattern for Finland, the changes insharesacrosscohortshavebeenmuchsmaller.

Table 5.5: Distribution (%‐share) of young non‐completers across the three stylized disability‐benefit pathways displayed in Figure 5.4, by country, gender and cohort

Years in post‐compulsory education before

moving into disability arrangements

[stylized pathway]

%‐share

in the

cluster


Male Female 1993 1998 2003


[11144]

Denmark 0.2 0.2 0.2 0.2 0.2 0.2

Finland 0.5 0.4 0.6 0.4 0.5 0.6

Norway 1.5 1.4 1.6 1.5 1.0 1.8

Sweden 1.0 1.1 1.0 0.4 0.7 1.9


[11444]

Denmark 0.6 0.5 0.5 0.5 0.3 0.7

Finland 0.2 0.2 0.2 0.1 0.3 0.2

Norway 0.3 0.3 0.4 0.3 0.3 0.4

Sweden 0.2 0.3 0.3 0.1 0.2 0.3

First (initial) year in education

[14444]

Denmark 0.5 0.4 0.3 0.3 0.5 0.7

Finland 2.3 2.2 2.3 2.6 2.6 1.5

Norway 0.1 0.1 0.1 0.1 0.1 0.1

Sweden 2.8 3.0 2.6 4.4 4.5 0.1

Total share =

[11144] + [11444] +

[14444]

Denmark 1.3 1.1 1.0 1.0 1.0 1.6

Finland 3.0 2.8 3.1 3.1 3.4 2.3

Norway 1.9 1.8 2.1 1.9 1.4 2.3

Sweden 4.0 4.4 3.9 4.9 5.4 2.3


In sum, for all four Nordic countries we observe relatively few non‐completers entering disability arrangements at an early age. Anothercommonfeatureofthefourcountries isthattheinstitutionalsettinginplace is strongly reflected in the type of disability‐benefit trajectoriesfollowedbyamajorityofthecountry’syoungpeopleshowingup,sooneror later, as disability beneficiaries. Likewise, the institutional changesmade during the time period covered by our three youth cohorts areclearly mirrored by the cross‐cohort changes seen in the relative im‐


portanceofdifferenttypesoftracksendingupinsomeformofdisabilityarrangements.Inparticular,theoverallimpressionisthattheseinstitu‐tional changeshave, firstand foremost,onlydelayed theseyoungsters’possibilities to enter disability arrangements, until they fulfil the new(increased) age condition. Finally, a third common feature of the fourcountriesisthattherearenostrikinggenderdifferencesinthedisabilitypathwaysinanyofthecountries.

5.1.6 Stylizedinactivity(“other”)pathways

Finallyweturnthe focus totheclustersofyoungnon‐completersbuiltaround the four stylized inactivity pathways defined in Table 5.1. Asoften pointed out earlier, the category of other inactivity embraces allyoungpeoplenotappearinginanyofthelargeadministrativeregistersfromwhichourdatasetsarecompiled.Theallocationofnon‐completersacrossthesefourstylizedpathwaysisdisplayedinFigure5.5,separatelyforeachcountry.Again,thesestylizedpathwaysprovide,atbest,amuchmore detailed description of young non‐completers’ early inactivity‐dominatedpathways than themorebroadly defined inactivity clustersofChapters3and4.

In all four countries, we see large shares of young non‐completerscontinuing directly in post‐compulsory education for three or moreyearsbeforedroppingout fromschool(withoutadegree) justtowith‐draw also from the labourmarket, into inactivity. This share of youngnon‐completersisparticularlyhighinNorway(about13%).Thecorre‐spondingshare intheotherthreecountries isonlyabouthalf thissize,butstillsome6to7%.Moreover,thistypeofdropout–inactivitytrajec‐tory covers increasing shares of young non‐completers. The increaseover cohorts has been remarkably strong amongNorwegian and Swe‐dishnon‐completers,withagrowthfrom11to17%inNorwayandfrom3to9%inSweden(Table5.6.).WhileanincreasingtrendisdiscerniblealsoforFinland,itisnotablyweaker(lessthantwopercentagepoints).In Denmark, in contrast, the share of young non‐completers in suchtrackshasdeclinedovertime.


Figure5.5:Stylizedinactivity(“other”)pathwaysofnon‐completers,bycountry








Alsoearlydropoutintoinactivity–alreadyaftertwooronlyoneyearinpost‐compulsoryeducation– turnsout tobe a comparatively commonphenomenon,butmainlyinDenmarkandNorway.Takentogether,thesetwo inactivity pathways cover, in both countries, almost 10% of theyoung non‐completers. Indeed,when further adding the share of non‐completers allocated around the previous [11155] pathway, we cover16%of theDanishnon‐completersandasmuchas23%of theNorwe‐giannon‐completers.However, forbothcountriesweobserveadeclin‐ingtrendinthesharesofyoungnon‐completersfollowingthesetypesofearly‐dropout–inactivity tracks. The corresponding share for Finlandand Sweden is much lower, covering only about 4% of the non‐completers. But in both countries, these shares are increasing ratherthandecreasing.

The situation is reversed with respect to inactivity tracks startingstraightaftercompletionofcompulsoryschool[55555]inthesensethat


theseearlyinactivitytracksarequiteprevalentamongFinnishandSwe‐dish non‐completers. Moreover, both countries have seen a doublingacross cohorts in the share of non‐completers in such tracks: from lessthan5%intheoldest(1993)cohorttonearly11%ormoreintheyoung‐est(2003)cohort.ThecorrespondingshareismuchlowerinDenmarkbutincreasing,whereasitisverylowinNorwayanddecreasing.

Table 5.6: Distribution (%‐share) of young non‐completers across the four stylized inactivity (“other”) pathways displayed in Figure 5.5, by country, gender and cohort

Years in post‐compulsory education before

moving into inactivity (‘other’)

[stylized pathway]

%‐share

in the

cluster


Male Female 1993 1998 2003


[11155]

Denmark 6.3 5.9 8.0 6.7 6.9 5.5

Finland 7.4 7.1 7.8 6.6 7.2 8.3

Norway 13.3 12.3 14.8 10.6 11.9 17.0

Sweden 6.1 6.3 5.9 2.9 5.8 8.8


[11555]

Denmark 4.8 4.0 6.9 6.7 3.8 4.0

Finland 2.2 1.8 2.7 0.8 2.8 2.8

Norway 6.0 5.3 6.8 6.2 5.2 6.5

Sweden 2.4 2.4 2.4 2.4 2.2 2.5

First (initial) year in education

[15555]

Denmark 4.9 3.7 6.9 5.5 4.6 4.6

Finland 1.7 1.3 2.3 0.5 2.4 2.0

Norway 3.5 3.0 4.2 4.4 3.2 2.9

Sweden 1.8 1.7 1.9 1.7 1.6 2.1

No entry into post‐compulsory

education

[55555]

Denmark 3.5 2.7 3.6 2.8 3.4 4.1

Finland 7.9 6.6 9.7 4.9 8.0 10.6

Norway 1.8 1.2 2.2 2.6 1.5 1.0

Sweden 6.9 7.4 6.3 4.3 4.2 11.3

Total share =

[11155] + [11555] +

[15555] + [55555]

Denmark 19.5 16.3 25.4 21.7 18.7 18.2

Finland 19.2 16.8 22.5 12.8 20.4 23.7

Norway 24.6 21.8 28.0 23.8 21.8 27.4

Sweden 17.2 17.8 16.5 11.3 13.8 24.7


All in all, the share of young non‐completers following inactivity‐dominated tracks at an early age is strikingly high in all four countries.Moreover, increasingly larger shares of the non‐completers show up insuchtracks,exceptinDenmark(Table5.6).Thisincreasehasbeenquitemoderate in Norway, but with the initial level being remarkably highwhencomparedtotheotherthreecountries:fromashareof22–23%intheoldercohortstoashareexceeding27%intheyoungest(2003)cohort.The development observed for Finland and Sweden can rather be de‐scribed as explosivewith an increase from 13% to almost 24% amongFinnish non‐completers and from 11% to almost 25% among Swedishnon‐completers. However, a look behind these average shares revealsdistinctdifferencesinthedropout–inactivitytracksactuallydominatingineach countryand the time trendsemerging for these various tracks. In‐deed, it is tempting to explain these differences in country‐specific pat‐


ternswith theunderlying institutional settingand the restrictionsmadeoverthepastdecadesespeciallywithrespecttotheeligibilityconditionsforyoungpeopleconcerningunemploymentanddisabilitybenefits.Final‐ly, itmay be noted that youngwomen tend to bemore likely to followearly inactivity‐dominated tracks, when compared to their male peers.OnlyinSwedendoyoungmenseemtofaceanequallyhighriskoranevenslightlyhigherriskofendingupinsuchtracks.

5.1.7 Mainfindings

Theconstructionofa totalof16stylizedpathwaysand the resultsob‐tained for thesepathwayssharpen further thepicture formedso farofyoungNordicnon‐completers’earlypost‐compulsory‐schoolexperienc‐es,uptoage20.Whiletherearelotsofdistinctdifferencesbetweenthefour Nordic countries in this respect, we can also observe importantsimilarities. All these details, including results by gender and cohort,have been presented and discussed above. In sum, these results showthefollowing.

The two stylized educational pathways confirm the overall picturefor young Nordic non‐completers painted by the results presented inprevious chapters, notably in Chapters 4 and 5. In particular, largesharesofalsonon‐completerscontinue,eitherdirectlyorafterabreakyear, in post‐compulsory education. Indeed, remarkablymany of themspend all ormost of their time, fromage16up to age20, as full‐timestudents,butwithoutcompletinganuppersecondarydegreewithinfiveyearsafterleavingcompulsoryschool.

The four stylizedemploymentpathwaysshow,onceagain, thatem‐ploymenttracksaremoreprevalentamongDanishnon‐completersthanamong non‐completers in the other three countries. Nonetheless, thefour countries share the featureof the roleof theseemploymentpath‐ways, asmeasuredby the shareofnon‐completers covered, increasingwith the number of years spent in full‐time education before movinginto working life (but without having completed an upper secondarydegree). In other words, the earlier the non‐completers leave post‐compulsoryeducation,thelesslikelytheyaretomoveintoemploymentcareersofamorepermanentnature.

Comparedtothestylizededucationalandemploymentpathways,thestylizedunemploymentpathwayscoverrelativelysmallsharesofyoungNordicnon‐completers.This iswell in linewiththeobservationsmadeinthepreviouschapters.Moreover,theshareofyoungnon‐completersinregisteredunemploymenthasdeclinednotablyovertime.Thisdeclin‐


ing trendacross cohorts isdiscernible for all three stylizedunemploy‐ment pathways. It is worth noting, though, that the early‐ dropout–unemployment trajectorieshave contributedmore to thisdecline thanthe more “standard” trajectory characterised by unemployment spellsfollowingupondropoutonlyafterthreeyears inuppersecondaryedu‐cation,withoutcompletionofadegree.Asdiscussedabove,thisoutcomeobviouslymirrorsthecombinedeffectofseveralcircumstances.

WhenitcomestoothertypesofNEETactivities,ourresultsindicatethefollowing.Theinstitutionalsettinginplacestronglyaffectsthetypeofdisability‐benefit trajectories followedbyamajorityof thecountry’syoung people showing up, sooner or later, as disability beneficiaries.Likewise,major institutionalreformsundertakensincetheearly1990sare clearly reflected in the changing relative importance of differenttypesof tracks endingup in some formofdisability arrangements. In‐deed, the overwhelming impression is that these institutional changeshavemerelydelayedyoungnon‐completers’possibilities toenterdisa‐bility arrangements. Obviously, this also explains why we in all fourNordiccountriesobserverelativelyfewnon‐completersenteringdisabil‐ityarrangementsatanearlyage. Inall fourcountries, theNEETactivi‐tiesofnon‐completersaredominatedbywithdrawal frombotheduca‐tionandworkinglifealreadyatanearlyage.Anotherdistinctfeatureisthatrelativelymoreyoungwomenthanyoungmengointothistypeofhigh‐risk track straight or almost straight afterhaving left compulsoryschool.OnlyinSwedendoyoungmenseemtofaceanequallyhighriskoranevenslightlyhigherriskofendingupinsuchtracks.

Anotherway of summarising thesemain findings is to rely on twomorefigureswhichhighlighttheobservedcross‐countrysimilaritiesanddissimilaritiesfromslightlydifferentangles.Thefirstfigure,Figure5.6,summarisesthedistributionofnon‐completersaccordingtothenumberofinitialyears(none,one,two,three,ormorethanthree)spentbythenon‐completers in post‐compulsory education before dropping outwithout having achieved an upper secondary certificate. The secondfigure,Figure5.7,isorganisedinareversedmanner:itdepartsfromthedistributionofyoungnon‐completersacrossthefive“end‐up”activitieswithout account being made for the number of initial years spent inpost‐compulsory education before entering the activity in question.Hence,Figure5.6isbuiltoncriterion1andFigure5.7oncriterion2ofTable5.1.Apart from these two figureshighlightingourmain findingsfor the group of non‐completers as such, we also relate these non‐completer‐specificoutcomestothefullyouthpopulation.Asinthepre‐viouschapter,thisisdoneinordertoprovideafullerpictureoftherela‐


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tive importance of different non‐completer tracks in the four Nordiccountriesunderstudy.

Figure5.6 illustrateswella findingpointedoutearlier in thisreport:large shares of Nordic non‐completers spend most of their post‐compulsory years, up to age20, as full‐time students, butwithout com‐pletinganuppersecondarydegreebyage21.Asshowninthefigure,be‐tween 35% (Finland) and 39% (Denmark) of young non‐completersspendmorethanthreeyearsinuppersecondaryeducationbeforedrop‐ping out temporarily or permanently. Also the share of young non‐completerscontinuingforexactlythreeyearsinuppersecondaryeduca‐tionbeforedroppingoutisrelativelyhigh,especiallyinNorwayandSwe‐den. This implies that about 70%of bothNorwegian and Swedish non‐completersspendthreeormoreyearsinuppersecondaryeducation,butwithout achieving a degree. The corresponding share is notably lower(closeto58%)forDanishandFinnishnon‐completers.Thisismainlydueto Danish and Finnish non‐completers being almost twice as likely asNorwegian and Swedish non‐completers to drop out already after oneyearinpost‐compulsoryeducation.Finnishnon‐completersalsohavethehighest probability of following a non‐starter pathway: about 14% ofFinnish non‐completers do not continue in post‐compulsory education.Thisshareisstrikinglylow(under3%)forNorway.

Figure5.6:Distribution(%‐share)ofnon‐completersacrossstylizedpathwaysbynumberofinitialyearsspentinpost‐compulsoryeducationbeforedroppingout,forthefourNordiccountries

Note: The figure is based on the information provided in Tables 5.2 to 5.6.


TheinformationprovidedinFigure5.6ispresentedinarescaledformatin Table 5.7 in order to illustrate the corresponding situationwhen ac‐count ismade for the fact that thenon‐completion rate among21‐year‐oldsdifferssubstantiallyacrossthefourcountries(seeChapter2).InbothDenmarkandNorway,more thanone‐fifthof theyouthpopulationcon‐tinueinpost‐compulsoryeducationforatleast3yearsbutfail,nonethe‐less,toachieveanuppersecondarydegreebyage21.ThecorrespondingshareforFinlandandSwedenisjustabove10%.Thecross‐countrysitua‐tion ismuchmoresimilarwhen, instead,comparingtheshareofyoung‐stersdroppingoutearlyfrompost‐compulsoryeducation:almost14%ofDanish youth follow early school‐leaving tracks, compared to about 8%forFinlandandNorway,andcloseto6%forSweden.

Table 5.7: Distribution of non‐completers across stylized pathways by number of initial years spent in post‐compulsory education before dropping out, for the four Nordic countries, %‐share of the full youth population

Number of initial years in post‐

compulsory education



> 3 years 14.6 6.3 10.8 5.9

3 years 7.0 4.1 10.1 5.2

2 years 7.1 2.7 5.6 2.3

1 year 5.9 2.4 2.4 1.2

Non‐starter 2.8 2.5 0.8 1.4

Non‐completers’ share in the full

youth population

37.3 18.0 29.7 16.0

Notes: The percentage shares displayed in Figure 5.6 as recalculated in relation to the full youth


Next, we turn from the activity dominating the start of each stylizedpathway to the activity dominating the end years of each pathway. Asshown in Figure 5.7, the stylized post‐compulsory‐school pathwaysdominatedbycontinuousengagementinfull‐timeeducationcovermorethanone‐thirdofthenon‐completersinallfourcountries.Theseyoungpeoplespendmostoftheiryearsfromage16uptoage20as full‐timestudents but fail, nonetheless, to finalise their upper secondary educa‐tion by age 21. The share of young non‐completers spending most oftheirearlypost‐compulsory‐schoolyearsineducationislargestinDen‐mark(39%)andlowestinFinland(32%).

Denmarkalsohasthelargestshareofyoungnon‐completersfollowingpost‐compulsory‐schooltracksmovingthemearlyintoworkinglife(closeto36%),followedbyFinland(30.5%).InNorwayandSweden,youngnon‐completersarelesslikelytoleaveschoolforemployment.Takentogether,these early education‐ and employment‐dominated pathways comprise75% of the Danish non‐completers. The corresponding share of non‐


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completersspendingmostoftheiryearsfromage16uptoage20ineitherschoolorworkis66%forFinland,64%forNorwayand62%forSweden.

Figure5.7:Distribution(%‐share)ofyoungnon‐completersacrossstylizedpathwaysbymainactivityafterleavingpost‐compulsoryeducation,forthefourNordiccountries

Note: The figure is based on the information provided in Tables 5.2 to 5.6.

Swedish non‐completers aremore likely to spend time in (registered)unemploymentafterhavingdroppedout fromuppersecondaryeduca‐tion than are non‐completers in the other three Nordic countries: anaverage of close to 17% of Swedish non‐completers end up in unem‐ploymenttracksbeforeturning21,comparedtoabout12%forFinland,some9%forNorwayandlessthan5%forDenmark.MostSwedishnon‐completers in unemployment tracks have spent three years in uppersecondaryeducationbeforeshowingupasunemployedjobseekers.Therelatively large share of Finnish non‐completers in unemploymenttracksismainlyduetotheweakemploymentprospectsoflow‐educatedyouthwho tried toenter the labourmarket in thehigh‐unemploymentyears of the 1990s. In the two younger Finnish cohorts, the shares ofnon‐completers experiencing early spells inunemploymentare similartothoseofDanishandNorwegiannon‐completers.

Relativelyfewnon‐completersfollowpathwaysshiftingthemalreadyatanearlyageintodisabilityarrangements.Thehighestshare(anaver‐age of 4%) is observed for Sweden.Much larger shares of youngnon‐completers showup in trajectoriesdominatedby (unknown)activitiesoutsidebotheducationandthe labourforce.Thisshare isnotablyhigh


(closeto25%)forNorway.Intheotherthreecountries,itisclearlylow‐erbut still of a remarkable size: about19% forDenmark andFinland,andsome17%forSweden.

Considernextthesamedistribution,nowrelatedtothefullyouthpop‐ulation of each country. After this rescaling,we find that about 13% ofDanish youth shift early into employment tracks,which typicallymeansthattheylackanuppersecondarydegreestillwhenaged21.InNorway,the corresponding share is 8%, in Finland 6% and in Sweden only 4%.DenmarkandNorwayalsocomeoutwithalargershareoftheyouthpop‐ulation(7.3%)followingearlytracksendingwiththeyoungpersonwith‐drawingfrombotheducationandthelabourmarketalreadybeforeturn‐ing21.InFinlandandSweden,suchtracksaremuchlesscommon.Whenrelated to the fullyouthpopulation, thecountry‐specificsharesofyouthendingup,alreadyatanearlyage,inunemploymentordisabilitybecomequitesimilarinsize.Indeed,Finland,NorwayandSwedenhaveaboutthesameshareofyouth(2.4–2.8%)movingearly intoregisteredunemploy‐ment–andnon‐completionofanuppersecondarydegree.TheshareforDanish youth is smaller, 1.7%, but not as different as the comparisonacrossnon‐completerssuggests(inFigure5.7).

Table 5.8: Distribution of young non‐completers across stylized pathways by main activity after leaving post‐compulsory education, for the four Nordic countries, %‐share of the full youth population

Main activity after leaving

post‐compulsory education



Continue in education 14.6 5.8 10.8 5.9

Employment 13.3 6.3 8.2 4.0

Unemployment 1.7 2.4 2.8 2.7

Disability benefits 0.5 0.5 0.6 0.6

Other (inactivity) 7.3 3.0 7.3 2.8

Non‐completers’ share in the

full youth population

37.3 18.0 29.7 16.0

Notes: The percentage shares displayed in Figure 5.7 as recalculated in relation to the full youth


Hence, themainimplicationofthe largedifferenceamongthe21‐year‐olds in non‐completion rates between especially Denmark, but alsoNorway,ontheonehand,andFinlandandSweden,ontheotherhand,isthat a notably larger share of Danish and Norwegian youth continuestraightinpost‐compulsoryeducationfortypicallythreeormoreyears,butwithoutcompletinganuppersecondarydegreebyage21,or leaveschoolforworkbeforehavinggraduated.Thesedifferencesarelikelytobebasicallyduetotheinstitutionalsetting,inparticulartheorganisationof vocational training. The shares of early dropouts going into typicalNEETpathsaremoresimilaracrossthefourcountries.

6. Labour market outcomes asyoung adults

Ouranalyseshaveso far focusedonexploringyoungpeople’smainac‐tivities and school‐to‐work‐transition patterns over the five years fol‐lowinguponcompletionofcompulsoryschool,thatis,fromage16uptoage20.A logicalnextstepistoask:Whathappenstotheseyoungstersaftertheyhaveturned20?Whatkindofmainactivities–studying,em‐ployment, unemployment, disability arrangements or other types ofinactivity–aretheymostlyengagedinasyoungadults?Canweobservedistinct and rather stable differences in this respect across gendersand/orbetweenthosedifferingintheireducationalbackground?Orisitpossible that these later outcomes are, by and large, quite similar foryoungmen andwomen, aswell as for early and later completers of apost‐compulsory educational degree and, possibly, even for non‐completers, i.e.thosewithnoexambeyondprimaryeducationstillasayoungadult?Last,butnotleast,canweidentifyclear‐cutsimilaritiesordissimilaritiesinalltheseimportantdimensionsacrossthefourNordiccountriesunderstudy?Thischaptersetsouttoprovideanswerstothesekeyquestions.

6.1 Mainactivitiesbeyondage21–allyoungpeople

We start by recalling theoverall patternof labourmarket outcomes foryoungadultsbasedonpooled informationonour threecountry‐specificyouthcohorts(16‐year‐oldsin1993,1998and2003).Inotherwords,wefirst re‐report inwhichmainactivities theyoungpeoplecoveredbyournationaldatasetsareengagedatthreedifferentages–21,26and31.Butinsteadofrepeatingthecountry‐specificgraphscontainedinFigures2.1ato2.1dofChapter2,wenowpresentthesameinformationfromaslightlydifferentangle.Thenwerefinethisdescriptiveinformationinanattempttounravel towhatextent theeconomicsituation ispossibly reflected inthelabourmarketoutcomesofouryouthcohortsunderscrutiny.


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Student Employed Unemployed Pensioner Other

6.1.1 Reproducingthegeneralpicturefromadifferentangle

In particular, Figure 6.1 contains three graphs with the first graphprovidinginformationontheallocationofeachcountry’syoungpeopleacrossourfivemainactivitycategories–studying,employment,unem‐ployment,disabilityarrangementsandothertypesof inactivity–whentheyturned21.Thenext(middle)graphgivesthecorrespondinginfor‐mationfiveyearslater,atage26.Thebottomgraph,finally,displaysthesituation ten years later, at age 31. Each graph then highlights cross‐Nordic similaritiesanddissimilarities inyoungpeople’sactivity sharesattheseparticularages.Atop‐downcomparisonofthethreeage‐specificdistributionssheds,inturn,lightonthechangesinactivityshareswithincountries when moving from age 21 to age 31. Indeed, this line‐of‐comparison is identical to the information provided in the country‐specificFigures2.1ato2.1dofChapter2.

Figure6.1:Distribution(%‐share)ofyoungpeopleacrossmainactivitiesatage21,26and31,respectively,basedonpooledinformationonallthreeyouthco‐horts,bycountry


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Note: For definitions of the five main activity groups, see Chapter 2.

SinceFigure6.1containsthesamebasicinformationatages21,26and31asFigures2.1ato2.1d,albeitinadifferentmode,weherecommentonlybrieflyonthepatternsdisplayedinthefigure.First,theoverallpic‐turelooksmuchthesameacrossthefourNordiccountriesunderstudy:rapidly declining shares in full‐time education and growing shares inemploymentwhenyoungpeoplegrowolder.Thisis, ineffect,themostconspicuouschangeinactivitysharesoccurringbeyondage21.

Second,inallfourcountriestherearenon‐negligiblesharesofyoungpeopleexperiencingunemployment,healthproblemsmovingthemontodisabilitybenefits,orotherformsofinactivityexcludingthemfromboth


education and working life. Although also these NEET shares changeovertime,thechangesarerathersmallinmagnitudewithnosystematicpatterndiscernibleacrossthefourcountries.

Third,thesituationatage21looksmoreorlessthesameinallfourcountrieswhenaddingupyoungpeople’sshares in full‐timeeducationandemployment,ontheonehand,andinNEETactivities,ontheotherhand. Moreover, this overall pattern is only marginally different fiveyearslater,atage26.Whilethedistributionofyoungpeopleacrossmainactivities appears to revealmore distinct cross‐country differences byage31,whencomparedtothesituationfiveortenyearsearlier,weneedtorecallthattheoutcomeatage31isbasedoninformationononesin‐glecohort,viz.theoldestcohortrepresentingyoungpeoplewhoturned16in1993.

6.1.2 Cohorteffectsoftheeconomicsituation

Nextwerefinethedescriptive informationprovidedinFigure6.1.Thisexercisedepartsfromthefactthatwehaveinformationonlaterlabourmarketoutcomesfortwoofourthreeyouthcohortsunderscrutiny:the1998 cohort of 16‐year‐olds can be followed up to age 26 (in 2008)while the 1993 cohort of 16‐year‐olds can be traced up to age 31 (in2008). Amainmotivation for looking somewhat closer into these twocohorts is that they started their school‐to‐work transition inverydif‐ferenteconomiccontexts.Asreferredtointheoutset,weknowfromtheliterature that the prevailing economic situation tends to have far‐reaching career consequences for young labour market entrants. Ac‐cordingly,wemightexpectthelabourmarketexperiencesinadulthoodtobedifferentforthesetwocohorts.

In Figure 6.1, the distribution across activities of our young peoplewhen aged 26 shows the average outcome for the 1993 and 1998 co‐horts. In contrast, andas alreadyunderlinedabove, thedistributionof31‐year‐oldsreflectsthesituationfortheoldest(1993)cohortonly.Bysplittingthe informationprovided inthe figure forage26,wemayun‐dertake two additional comparisons potentially shedding light on thefollowingquestions:Does thedistributionacrossmainactivitiesatage26 lookdifferent for the “economic‐bust” cohortof1993and the “eco‐nomic‐boom” cohort of 1998?Does the situation changemarkedly be‐tweenage26andage31fortheeconomic‐bustcohortof1993,ordoesitremain approximately unchanged? These two comparisons are under‐taken inFigures6.2and6.3. Since theeconomic recession in theearly


1990shitallfourNordiccountriesunderstudy,wewouldexpectcross‐cohortdifferencestoshowupforallfourcountries.

AccordingtoFigure6.2,theshareofyoungpeopleengagedineitherfull‐time education or employment is, by age 26, slightly higher in the1998 “economic‐boom” cohort than in the 1993 cohort. However, thisholdstrueforDenmarkandFinlandonly.InDenmark,thishigher“activ‐ity”shareof the1998cohort isdueto full‐timestudyingstillatage26beingmorecommoninthe1998cohort,whereastheshare inworkinglifeisofthesamemagnitudeinthetwocohorts.InFinland,ontheotherhand,the1998cohortisbyage26moreengagedinbothfull‐timestud‐iesandemploymentthanwasthe1993cohortwhenaged26.

ThesituationlooksdifferentforNorwayandSweden.Forbothcoun‐tries,weobserveasmalldeclineacrossthetwocohortsintheshareoffull‐timestudentsandaslightincreaseintheshareinemployment.ForSweden,thesetwoopposite‐signedchangesareofmuchthesamemag‐nitude,forwhichreasonweseeprincipallynodifferenceacrossthetwocohorts in the total share of 26‐year‐olds in either education or em‐ployment. For Norway, in contrast, the drop in the share of full‐timestudentsmorethanoutweighstheconcomitantincreaseintheshareofemployed.Thisresultsinan“activity”shareamong26‐year‐oldNorwe‐giansthatislowerinthe1998cohortthaninthe1993cohort.

Figure6.2 further indicates that theshareof26‐year‐olds in (regis‐tered)unemploymentwasclearly lower inthe1998cohort.Thisholdstrue for all four countries and is,most likely, due to a favourable eco‐nomicsituationincombinationwithincreasedvolumesofactivelabourmarketpolicies.Simultaneously,however, theshareof26‐year‐oldsondisabilitybenefitsor inothertypesof inactivityappearstobeofmuchthe same size in the two cohorts (Finland) or even larger in the 1998economic‐boom cohort (notably in Norway, but also in Denmark andSweden).Allinall,Figure6.2seemstosuggestthattheprevailingbusi‐nesscyclehas,atmost,beenreflectedinyoungpeople’sactivitieswhenit comes to studying and working, including unemployment, whereaswithdrawal from both education and the labourmarket is mainly theresultofotherprocessesandmechanisms.


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Figure6.2:Distribution(%‐share)ofyoungpeopleacrossmainactivitiesatage26,bycountry:comparisonofthe“economic‐bust”cohortof1993withthe“eco‐nomic‐boom”cohortof1998


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Figure6.3,finally,showsthattheoveralllabourmarketoutcomeofthe1993“economic‐bust”cohortimprovedoverthe5‐yearperiodfromage26uptoage31.InSweden,morethaneightoutoften(82%)oftheco‐hort’syoungpeoplewereworkingatage31withanadditional9%stillbeingenrolledineducation.Hence,91%oftheSwedesbelongingtothiscohort were either studying or working when aged 31 (compared tocloseto89%whenaged26).Inotherwords,thesituationoftheSwedish1993cohorthad,byage31, turnedvery similar to thesituationof theDanish 1993 cohort in terms of both employment and education. Also


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theFinnish1993cohorthadbyage31experiencedanotableimprove‐mentinitsemploymentsituationwhich,nonetheless,remainednotablyweaker(73%)thanfortheDanishandSwedish1993cohorts.However,thisloweremploymentlevelisnotnecessarilyentirelyduetheeconomicrecession and the high unemployment levels of the 1990s: as has be‐comeevidentalsointhepreviouschapters,Finlandisthroughoutchar‐acterised by a lower share of employed, when compared to the otherthreeNordiccountriesunderstudy.

Figure6.3:Distribution(%‐share)ofyoungpeopleacrossmainactivitiesatage26and31,respectively,bycountry:the“economic‐bust”cohortof1993


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Inparallelwithimprovingemploymentuptoage31,the1993cohortofDenmark,FinlandandSwedenexperiencedadeclineintheshareofun‐employedjobseekers.Butsimultaneouslyallthreecountriesalsosawanincreasingshareofthecohort’syoungpeoplemovingoutsidebothedu‐cationandthelabourmarket,whencomparingthesituationatage26tothatprevailing fiveyears later,atage31.This increase is, for themostpart,explainedbyahighersharereceivingdisabilitybenefits.

Aslightlydifferentpatternemergesfor theNorwegian1993cohort.While the shareof the cohort’s youngpeoplemoving intoworking life


increasedbetweenage26and31alsoinNorway,thisgrowthcouldnotcompensate for theconcomitantdrop in thesharestillenrolled in full‐time education. As a consequence, the cohort’s “activity” (education +employment)sharewasmarginallyloweratage31thanatage26.Sim‐ultaneously,theshareofthecohort’syoungpeoplemovingoutsidebotheducationandthelabourforceincreasedquitemarkedly,fromabout9%atage26toalmost14%atage31.Moreover,onlyaminorpartofthisincreaseisexplainedbyagrowingnumberofthecohort’syoungadultsmoving into disability arrangements. Instead, the main explanationseemstobethattheywithdrawintoothertypesofinactivitynotcoveredby the large administrative registers fromwhich ournational datasetsarecompiled.

6.1.3 Mainfindings

In this sub‐chapter, we have addressed two interconnected questions:Doesthedistributionacrossmainactivitiesatage26lookdifferent forthe“economic‐bust”cohortof1993andthe“economic‐boom”cohortof1998?Doesthelabourmarketsituationchangebetweenage26andage31fortheeconomic‐bustcohortof1993,ordoesitremainapproximate‐lyunchanged?

Ourdescriptiveanalysisbasedon information for the full youthco‐hortscannotprovideclear‐cutanswers to thesequestions in thesensethatweseenosystematiccross‐countrytrendsinactivitysharesatage26fortheeconomic‐bustandeconomic‐boomcohorts.Inparticular,theshareinemploymentbyage26isslightlyhigherinthe1998cohortthanin the 1993 cohort for Finland,Norway and Sweden, but not forDen‐mark.Theshareenrolledinfull‐timeeducationstillatage26ishigherintheDanishandFinnish1998cohorts,whereas theoppositeholds truefor Norway and Sweden. Adding up the shares in education and em‐ploymentrevealsnoconspicuousdifferencesbetweenthe twocohorts,either.Instead,weseeaslightincreaseinthis“activity”shareacrosstheDanishandFinnishcohorts,nochangeacrosstheSwedishcohortsandadecline across the Norwegian cohorts.While the share in (registered)unemploymentatage26is,indeed,lowerinthe1998cohortinallfourcountries,thischangeseemstohaveoccurredattheexpenseofamuchhigher(Norway)orslightlyhigher(DenmarkandSweden)shareof26‐year‐olds in the 1998 cohort standing outside both education and thelabourforce.ForNorway,theresultsfurtherindicatethatthisconspicu‐ousincreaseintheshareofyoungpeoplewithdrawingfrombotheduca‐


tion and the labour force has been fednot only by a flow fromunem‐ploymentbutalsofromfull‐timeeducation.

Thecountry‐specificpatternsaremoresimilarwhencomparing thelabourmarketsituationofthe1993cohortof16‐year‐oldsattwopointslaterinlife,viz.atage26andage31.Inallfourcountries,weobserveanimprovement in the cohort’s labour market situation between age 26and31 in termsofmoreemploymentand lessunemployment. Finally,whiletheshareoutsidebotheducationandthe labourforcerevealsanupwardtrendinallfourcountries,thischangeuptoage31hasgeneral‐lybeenquitemodest,exceptfortheNorwegian1993cohort.

However,theseweaksignsofthedeepeconomicrecessionoftheear‐ly 1990s having had an impact on the labourmarket outcomes of the1993cohortof16‐year‐oldsdonotmeanthattheirsituationwasunaf‐fected by the difficult employment situation that prevailed for severalyearsalsoafter thestartof theeconomicrecovery.Firstand foremost,weneedtorecallthatourdatameasuresregisteredunemployment.Asshown and discussed at length in Chapter 1, this measure is likely tounderestimate the prevalence of unemployment among young people:many of them do not fulfil the conditions for signing on, or then theymaychoosenottoregisterifnotbeingeligibleforreceivingunemploy‐mentbenefits.However,itmightalsobethattheeconomiccrisisaffect‐ed specific groups of young persons, instead of influencing all youngpeople about to enter the labourmarket. In Finland, for instance, therecessionstartedinmale‐dominatedexportindustries,whichresultedinsurgingmaleunemploymentratesandwidespreaddestructionofespe‐ciallylow‐skilledjobsoftenoccupiedbylow‐educatedyoungsters.Next,we therefore deepen our analysis in two respects: first, by comparingthesituationofyoungmenandwomen,andsecond,bycontrastingtheoutcomesofcompletersandnon‐completersofanuppersecondaryde‐greebyage21.

6.2 Mainactivitiesbeyondage21–youngmenvs.youngwomen

Next,wecomparethelabourmarketoutcomesinadulthoodacrossgen‐ders:Arethelabourmarketexperiencesofyoungmenandyoungwom‐endistinctlydifferentatage21,26and/or31?Canweidentifyastrong‐erimpactoneithergenderoftheeconomiccrisisintheearly1990s?


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6.2.1 Labourmarketoutcomesbygenderatthreespecificagepoints

Alogicalwaytostartthismale–femalecomparisonistosplittheinfor‐mationprovidedinFigure6.1bygender.ThisisdoneinFigure6.4withthestructureofthefigurenowemphasising,firstandforemost,within‐countrydifferencesratherthanbetween‐countrydifferences.

Figure6.4:Distribution(%‐share)ofyoungpeopleacrossmainactivitiesatage21,26and31,respectively,basedonpooledinformationonallthreeyouthco‐horts,bygenderandcountry


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The first graph of Figure 6.4 highlights the situation forDenmark.WeseebasicallynodistinctdifferencesacrossgendersamongyoungDanes,irrespectiveofwhetherwecomparetheirsituationatage21,age26orage31.Theonlydivergenceintheirdistributionsacrossmainactivitiesconcernsthehighershareofyoungwomencontinuinginfull‐timeedu‐cation and a correspondingly higher share among youngmenmovingintoworkinglife,adifferencepointedoutalreadyinpreviouschapters.However,alsothiscross‐genderdifferenceseemstohavealmostdisap‐pearedbyage31.


Intheotherthreecountries,thereareclearlymoredifferencesinthedistribution across activities between young men and young women.Whilemuchlargersharesofyoungwomenareinfull‐timeeducationatage21,thisdifferenceacrossgendersdiminishessteadilyovertime,butit does not come close to vanishing as in Denmark. Likewise, also thegendergapinemploymentsharesobservedatage21shrinksovertime,but still by age 31working ismore common amongmen than amongwomen.Nonetheless,takentogether,largersharesofyoungwomenthanofyoungmenareineithereducationorwork.ThisholdstrueatallthreeagepointsforNorwayandSweden,butonlyatage21forFinland.Atage26,aswellasatage31, theshareofFinnishwomeneitherworkingorstudyingislowerthanforFinnishmen.

Thesegenderdifferencesineducationandemploymentsharesare,ofcourse,mirroredbycorrespondingdifferencesacrossgendersinrelationtoNEETactivities.However,inthisrespectitismuchhardertofindcom‐mon patterns for Finland, Norway and Sweden. In particular, while allthree countries are characterised by a lower share in unemploymentamongyoungwomenthanamongyoungmenaged21, thisgapprevailsuptoage31inFinland,disappearsbyage31inNorway,andisreversedbyage31inSweden.Asimilarpatternis,ineffect,discernibleacrossgen‐ders,agesandcountriesforthoseondisabilitybenefits.Forothertypesofinactivity,weobserveforFinlandalargershareforyoungwomenthanforyoung men with, moreover, the inactivity share among young Finnishwomenincreasingrapidlywithage.Theinactivityshareislargeandgrow‐ingwithagealsoinNorwaybut,incontrasttoFinland,thisseemstoholdtrueforbothgenders.ForSweden,ontheotherhand,theinactivityshareshrinkswithageforbothgenders,moreforyoungwomenthanforyoungmen. By age 31, a clearly larger share of Swedishmen than of Swedishwomenbelongstothedumpingcategoryof“other”inactivity.

6.2.2 Gender‐specificcohorteffectsoftheeconomicsituation

Asasecondstepinourcross‐gendercomparisons,werepeatthesplitbycohortofthedistributiveinformationprovidedforage26inanattempttounravelwhetherornot theeconomicsituationat the timeof labourmarketentryhaseventuallyaffectedyoungmenandyoungwomendif‐ferentlywhenitcomestotheirdistributionsovermainactivitycatego‐ries.TheresultsofthisexercisearedisplayedinFigure6.5.


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Figure6.5:Distribution(%‐share)ofyoungpeopleacrossmainactivitiesatage26,bygenderandcountry;comparisonofthe“economic‐bust”cohortof1993withthe“economic‐boom”cohortof1998


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Sweden



Intheprevioussub‐chapterfocusingonallyoungpeople,wenotedthattheshareofyoungpeople ineithereducationoremployment is some‐whathigheratage26inthe1998“economic‐boom”cohort,butonlyinDenmarkandFinland.ForDenmark, thishigher“activity” (education+employment) sharewas found to be due to a larger share of full‐timestudentsinthe1998cohort,whereastheshareinworkinglifeappearedtobeofthesamemagnitudeinthetwocohorts.AsisevidentinFigure6.5, this overall pattern shows up for both genders. For Finland, wefoundaslightlyhighershareinbotheducationandemploymentamong26‐year‐olds belonging to the1998 cohort. Also thesepatterns are re‐


peatedforbothgenders.ForSweden,weidentifiedopposite‐signedbutbalancedchangesineducationalandemploymentsharesacrossthetwocohorts,resultinginapproximatelysimilar“activity”sharesforthe1993and1998cohorts.Thispatternisdiscernibleforbothgenders.ForNor‐way,finally,wesawasimilarbutmoreunbalancedtrendacrossthetwocohorts. In particular, the increase in the share of employed was notenough to compensate for the concomitant decline in the share of 26‐year‐oldsenrolledinfull‐timestudies,whichshowedupasalower“ac‐tivity”shareinthe1998cohortthaninthe1993cohort.Again,thesamepatternholdstrueforbothgenders.

Common to all four countrieswas a share of 26‐year‐olds in (regis‐tered)unemploymentthatwaslowerinthe1998cohort.Alsointhisre‐spectweobservethesamepatternforyoungmenandyoungwomen.Thecohort‐specific shares of 26‐year‐olds on disability benefits or in othertypesof inactivitywere foundtorevealmuchmorecross‐countryvaria‐tion:forFinland,theinactivityshareinthetwocohortswasnotedtobeofmuch the same size, but forDenmark, Sweden andnotably forNorway,theshareofyoungpeopleoutsidebotheducationandthelabourmarketwas found to be larger in the 1998 than in the 1993 cohort. Again, thesamecross‐cohortpatternisdiscernibleforbothgenders.Hence,thedif‐ferences between the “economic‐boom” and the “economic‐bust” cohortin thedistributionofyoungpeopleacrossmainactivitiespointedout intheprevious sub‐chapter donot showupdifferently among youngmenand young women; the same pattern emerges irrespective of gender.Moreover,thisholdstrueforallfourcountries.

Finally, we take a gendered perspective on the distribution acrossmain activities of the 1993 “economic‐bust” cohort at two age points:whenaged26and31,respectively.Here,themainquestioniswhetherornotthelabourmarketoutcomesofmalesbelongingtothisparticularcohortpossiblyevolveddifferentlyovertheseyears,whencomparedtotheexperiencesoftheirfemalecounterparts.Forthispurpose,wesplitthe information given in Figure 6.3 above to indicate the situation ofyoungmenvs.youngwomenbelonging to the1993cohortof16‐year‐olds.ThiscomparisonisundertakeninFigure6.6.

For Denmark, Finland and Sweden we found, based on Figure 6.3,that theoverall labourmarketoutcomeof this “economic‐bust” cohortimprovedoverthe5‐yearperiodfromage26uptoage31. Inall threecountries,aboutnineoutoftenofthecohort’syoungpeoplewereeitherstudyingorworkingatage31.Moreover,inallthreecountries,theshareofyoungpeopleregisteredasunemployedjobseekersdeclineduptoage31,whereastheshareoutsidebotheducationandthelabourforcewas


0%10%20%30%40%50%60%70%80%90%

100%

Men at 26 Men at 31 Women at 26 Women at 31

Denmark


0%10%20%30%40%50%60%70%80%90%

100%


Finland


marginally higher. Again,much the same overall pattern is discerniblefor bothmen andwomen: a decline in the share enrolled in full‐timestudies accompaniedbya strong increase in the share in employment,less unemployment but slightlymore inactivity. For both genders, thisincrease in the inactivity sharebyage31 seems tobemainlydue toagrowinginflowintodisabilityarrangements.

Figure6.6:Distribution(%‐share)ofyoungpeopleacrossmainactivitiesatage26and31,respectively,bygenderandcountry,theeconomic‐bustcohortof1993


0%10%20%30%40%50%60%70%80%90%100%


Norway


0%10%20%30%40%50%60%70%80%90%

100%


Sweden



Figure6.3mediatedaslightlydifferentpatternfortheNorwegian1993cohort of 16‐year‐olds: despite a growth in the share of employed be‐tweenage26andage31also inNorway, this increasecouldnot com‐pensate for the concomitant drop in the share of full‐time students,whichresultedinan“activity”shareofthe1993cohortthatwaslowerat age31 than at age26.Moreover,while the share in unemploymentdeclined,theshareofthecohort’syoungpeoplewithdrawingfrombotheducationandthelabourmarkethadincreasedmarkedlybyage31.Asis evident from Figure 6.6, this overall pattern is strikingly similar formenandwomen.


6.2.3 Mainfindings

In Chapter 2, wemade a first comparison between genders also withrespecttotheirdistributionacrossmainactivitiesatage21.Inthissub‐chapter,we have expanded this comparison to two age points later inlife:fiveyearslater,atage26,andtenyearslater,atage31.Doingso,weobserve basically no differences across genders among young Danes,irrespectiveofwhetherwecomparetheirlabourmarketsituationatage21,age26orage31.Indeed,alsothehighershareofyoungwomencon‐tinuing in post‐compulsory education and the correspondingly highershare among youngmenmoving already at a relatively early age intoworkinglifearedifferencesthatseemtohavedisappearedbyage31.

We find much more differences in the gender distributions acrossmain activities for the other three countries. The gender gap in theshares of full‐time students and the employed narrows steadily overtimebutisdiscerniblealsoatage31withenrolmentinfull‐timeeduca‐tionstillbeingmorecommonamongyoungwomenandworkingbeingmorecommonamongyoungmen.However,simultaneouslyweobservelargersharesofyoungmenthanofyoungwomenoutsideeducationandwork.Thisholdstrueatallthreeagepoints(21,26,31)forNorwayandSweden,butonlyatage21 forFinland.Atbothage26andage31, theshare of Finnish women neither working nor studying on a full‐timebasisismuchhigherthanforFinnishmen.

Attemptswerealsomadeto identifypossibledifferences in thedis‐tributionofyoungmenandyoungwomenacrossmainactivitiesduetochangesintheeconomicenvironment.Thesimpleexercisesundertakeninthisrespectdonotprovidesupportforchangesinthebusinesscycleshowingup differently among youngmen and youngwomen. In otherwords, to the extent that changing business cycles are reflected in theoverall distribution of young people across main activities, men andwomenseemtobeaffectedinmuchthesameway.Thisfindingemergesforallfourcountriesunderstudy.

6.3 Mainactivitiesbeyondage21–completersvs.non‐completers

Asafinalstepinthisdescriptiveanalysisofthelabourmarketoutcomesof our three youth cohortswhen young adults,we turn the focus to acomparisonofupper‐secondary‐schoolcompletersandnon‐completers.Again,completersrefertothoseyoungpeopleinourthreeyouthcohortswhosucceededinfinalisingtheiruppersecondaryeducationwithinfive


yearsafter leavingcompulsoryschool.Thegroupofnon‐completers, inturn,comprisestheremainingyoungpeople, that is, thosewithstillnopost‐compulsorydegreewhenreaching21years‐of‐age.Thisdefinitionisvalidthroughoutthissub‐chapter.Inthenextsub‐chapter(6.4),how‐ever,wewillusealessstrictdefinitioninthesensethatweallowforthefactthatatleastsomeofthesenon‐completersdocompletetheiruppersecondaryeducation,butonlylateron,aftertheageof21(cf.Chapter2).

We start by comparing the distribution of completers and non‐completersacrossour fivemainactivitycategorieswhenaged21.Thiscomparisonoflabourmarketoutcomesisthenrepeatedfiveyearslater,atage26and,finally,tenyearslater,atage31.Weconcludebyreturn‐ingtothequestionoftheroleplayedbytheeconomicsituationforlaterlabourmarketoutcomes,withthe focusnowbeingonacomparisonofcompletersandnon‐completers.

6.3.1 Situationfiveyearslater,atage21

Figure6.7 illustrates towhatextent completers (uppergraph)andnon‐completers (lower graph) are engaged in differentmain activitieswhenaged21,thatis,fiveyearsafterleavingcompulsoryschool.Fromthefig‐ure it is evident that the distribution acrossmain activities varies a lotwhencomparing thosehavingcompleted to thosenothavingcompletedan upper secondary degree by age 21.Moreover, this holds true for allfourNordiccountriesunderstudy.Inseveralrespects,therearealsodis‐tinct cross‐country differences among both completers and non‐completers,aspointedoutalreadyinChapter2.

Broadlyspeaking,about90%ofthecompletersareeithercontinuingin education or working when aged 21, with this share being slightlyhigherinDenmarkandmarginallylowerinFinland.Thecorrespondingsituation for 21‐year‐old non‐completers looks very different with ashare ineither full‐timeeducationoremploymentwellbelow70% forFinland, Norway and Sweden. Only in Denmark is this share clearlyhigher (78%). From awithin‐country perspective, these differences incombined education and employment shares imply that the “activity”gap between 21‐year‐old completers and non‐completers is compara‐tively large for Sweden (26%‐points), closely followedbyNorway andFinland,withDenmarkcomingoutwiththesmallestbutstillquitenota‐blegap(15%‐points)(Table6.1).


0%10%20%30%40%50%60%70%80%90%100%


Completers


The shareof full‐time students isby farhighest (60%)amongNor‐wegian completers while the share of completers in employment ishighest–andofasimilarsize(about46%)– inDenmarkandSweden.Conversely, the shareofDanish andSwedish completers continuing ineducationwhenaged21iscomparativelylow,asistheshareof21‐year‐oldNorwegiancompletershavingenteredworkinglife.Adistinctlydif‐ferentcross‐countrypatternemergesforthenon‐completers.Inparticu‐lar,thehighestshareof21‐year‐oldnon‐completersengagedinfull‐timestudiesisobservedforDenmark(40%comparedtolessthan30%intheotherthreecountries).Thesituationismoreorlesstheoppositewhenitcomes to thenon‐completers’employmentshare:nowNorwayhas thelargest(closeto43%)andDenmarkthelowest(below38%)share.

Figure6.7:Mainactivitiesatage21forcompletersandnon‐completersofanuppersecondaryeducation,basedonpooledinformationonallthreeyouthcohortsunderstudy,bycountry


0%10%20%30%40%50%60%70%80%90%100%


Non‐completers


Notes: Completers are defined as young people having completed an upper secondary education by

age 21. Conversely, non‐completers are defined as those having reached 21 years‐of‐age without

finishing an upper secondary degree. The number of completers is 103,203 for Denmark, 158,611

for Finland, 109,723 for Norway and 243,763 for Sweden, whereas the number of non‐completers is

61,676 for Denmark, 34,956 for Finland, 46,441 for Norway and 46,494 for Sweden. For definitions

of the five main activity groups, see Chapter 2.

These highly different cross‐country patterns when it comes to bothcompleters’ and non‐completers’ shares in education and employmentwhenaged21alsoexplainthehugevariationobservedacrossthe fourcountries when contrasting the “activity” (education + employment)share of completers to that of non‐completers. As shown in Table 6.1,mostofthis“activity”gaporiginates inadramaticcross‐countryvaria‐tion in thegapbetweencompleters’andnon‐completers’enrolment ineducation: the difference in the share of 21‐year‐old completers andnon‐completerscontinuingineducationisconspicuouslylargeforNor‐way (an almost 35%‐point lower share for the non‐completers) com‐paredtoagapof less than6%‐points forDenmark.Thecorrespondinggapinemploymentsharesistypicallymuchsmaller(about9%‐pointsinDenmarkand7%‐points inSweden)orevenreversed. Indeed, theem‐ploymentshare ishigher for21‐year‐oldnon‐completers thanfortheircompleterpeers inFinland (about4%‐pointshigher) andespecially inNorway(about12%‐pointshigher).


Table 6.1: Main activities at age 21: completers (%‐share) vs. non‐completers (%‐point gap)

Main activity Denmark Finland Norway Sweden

%‐

share

%‐point

gap

%‐

share

%‐point

gap

%‐

share

%‐point

gap

%‐

share

%‐point

gap

Student 45.9 ‐5.8 53.5 ‐24.6 60.4 ‐34.6 43.2 ‐18.8

Employed 46.6 ‐9.1 34.9 +4.1 30.3 +12.4 46.0 ‐7.1

Student + employed 92.5 ‐14.9 88.4 ‐20.5 90.7 ‐22.2 89.2 ‐25.9

Unemployed 2.3 +4.3 7.8 +4.5 2.6 +9.4 7.0 +13.5

Disability benefit (pensioner) 0.0 +1.8 0.3 +3.8 0.2 +3.9 0.2 +8.3

Other (inactivity) 5.2 +8.9 3.5 +12.3 6.5 +8.9 3.5 +4.3

NEET activities 7.5 +15.0 11.6 +20.6 9.3 +22.2 10.7 +26.1

Total 100.0 100.0 100.0 100.0

Notes: These calculations are based on the distributions displayed in Figure 6.7. The %‐shares in

the table show the distribution of completers across main activities when aged 21 (these shares

are identical to those displayed in the upper graph of Figure 6.7). The %‐point gaps indicate the

difference between non‐completers’ and completers’ shares. A negative sign implies that the

non‐completers’ share is lower: for instance, the share of Danish non‐completers in education is

5.8 %‐points lower (or 40.1%) than the corresponding share for completers (45.9%). Likewise, a

positive sign means that a larger share of the non‐completers than of the completers is in that

particular activity.

The other side of the coin illustrates completers’ and non‐completers’involvement invariousNEETactivities.Theshareofcompletersshow‐ing up in such activities when aged 21 is small in all four countries,whichfollowsdirectlyfrommostofthembeingeitherfull‐timestudentsoremployed.Ofthenon‐completers,ontheotherhand,aboutone‐thirdisneitherstudyingnorworkingbyage21.OnlyinDenmarkisthissharesmaller, underone‐fourth.Moreover, amajority of thenon‐completersinNEETactivitiesbelongstothedumpingcategoryof“other”(inactivi‐ty), that is, theydonotappear inanyof the largeadministrativeregis‐ters fromwhichournationaldatasets are compiled.A conspicuousex‐ception from this pattern is Swedish non‐completers, though, whoseNEET activities are dominated by registered unemployment. Notableshares of the non‐completers are also on disability benefits, a labourmarketoutcomethat isalmosttotallymissingamong21‐year‐oldcom‐pletersinallfourcountries.

Inviewofthesefindings,itishardlysurprisingthatacomparisonbycountryofcompleters’andnon‐completers’NEETactivitieswhenaged21 results in a situationwhere thenon‐completers’ shares throughoutexceedthoseofthecompleters.However,thecross‐countryvariationinalsothesepatterns issubstantial(Table6.1).For instance, theshareofthe unemployed is quite high and of a similar size (about 7%) amongFinnishandSwedishcompletersaged21.Theshareofunemployednon‐completers is, however, even larger (12.3% in Finland and 20.5% inSweden).Thisresultsinaremarkablylargegap(13.5%‐points)inSwe‐


dish completers’ and non‐completers’ unemployment shares, with thecorresponding gap being notably lower (4.5%‐points) for Finland. Asimilarsituationprevails forDenmarkandNorway,wheretheshareof21‐year‐old completers in unemployment is very low (less than 3%)while their non‐completer peers experience either somewhat higherunemployment(Denmark)ormuchhigherunemployment(Norway).Asis evident in Table 6.1, similar examples can be foundwith respect todisabilitybenefits,aswellasothertypesofinactivity.

6.3.2 Situationtenyearslater,atage26

Nextwepickupthesecompletersandnon‐completersatage26.Asnot‐edabove,we therebyretain theclassificationofouryoungpeople intocompleters and non‐completers that prevailed when they turned 21.This exercise results in the country‐specific distributions across mainactivitiesshowninthetwographscontainedinFigure6.8.

Amongthecompleters,employmenthasbyage26takenoverastheoverwhelmingly most common activity, while their share in full‐timeeducationhas shrunk tobetweenone‐third (Denmark) andone‐fourth(Sweden). Taken together, the share of completers either studying orworking is at this age slightlyhigher than fiveyears earlier, at age21,butonlyforDenmarkandSweden.ForFinnishcompleters,the“activity”sharestandsatapproximatelythesamelevelasfiveyearsearlier,obvi‐ouslymainlydue to theconspicuousshareoutsidebotheducationandthelabourmarketobservedamongyoungwomenatage26(andalsoatage31)intheprevioussub‐chapter.ForNorway, incontrast,theshareofcompleterseitherstudyingorworkingisslightlyloweratage26thanat age21.This finding is in linewith theobservationsmadeearlier inthis chapter, viz. a decline in the share of students that exceeds thegrowth in the share in employment, coupled with a concomitant in‐creaseintheshareofyoungpeopleininactivity(cf.Tables6.1and6.2).

Alsotheshareofnon‐completersineithereducationoremploymentishigher at age 26 than at age 21:marginally higher in Denmark (78 vs.79%) and Norway (69 vs. 70%), but notably higher in Sweden (63 vs.71%).Only forFinlanddoweseeadecline innon‐completers’ “activity”shareoverthesefiveyears,justasforFinnishcompletersand,evidently,forthesamemainreason.Inallfourcountries,the“activity”shareofnon‐completerslags,nonetheless,farbehindthatofcompletersstillatage26(Table 6.2). However, the cross‐country variation in this “activity” gapbetweencompletersandnon‐completersismuchsmalleratage26thanatage21.Inparticular,whilethisactivitygapbetweencompletersandnon‐


completershasremainedapproximatelyunchangedfromage21uptoage26inDenmark,ithasnarrowedquitesubstantiallyinSweden(cf.Tables7.1and7.2).Yet,thewayinwhichthegapsbetweencompletersandnon‐completersinstudentandemploymentsharesfeedintothis“activity”gaplookstotallydifferentatage26,whencomparedfiveyearsearlier.Note‐worthyisespeciallythechangeintheemploymentgap:byage26,ithasturnedfrompositivetonegative(FinlandandNorway)orevenmoreneg‐ative (Sweden). At age 26, non‐completers thus typically face aweaker(Norway)ormuchweaker (Finland andSweden) employment situationthancompleters,exceptinDenmark(Table6.2).

Theshareof21‐year‐oldcompletersoutsideeducationandemploymentwasnotedtobelowinallfourcountries.TheshareofcompletersinNEETactivitieshasdeclinedfurtherbyage26.Amongnon‐completersofage21,largeshareswerefoundtobeeitherunemployed,ondisabilitybenefitsorinothertypesofinactivity,withthissharerangingfromabout22%inDen‐markuptoalmost37%inSweden.Thesituationhas,byage26,improvedslightlyamongSwedishnon‐completersbutonlymarginallysoamongDan‐ishandNorwegiannon‐completers.ForFinnishnon‐completers,theNEETshare is basically unchanged and now, in effect, highest among the fourcountries. However, just as the “activity” gap, also the NEET gap is con‐structedinadifferentwayatage26thanage21.Putdifferently,thegapsincompleters’ and non‐completers’ shares in unemployment, disability ar‐rangementsandotherinactivityfeedintothetotalNEETgapinhighlydif‐ferentwaysatage21andatage26(cf.Tables6.1and6.2).

On thewhole, though, the overall cross‐country pattern in relation tocompleters’ andnon‐completers’ distributions acrossmain activitiesdoesnotchangethatmuchwhencomparingthesituationatage26tothesitua‐tionprevailingat age21.Thehighest “activity” share is still observed forDenmark,andthisholdstrueforbothcompletersandnon‐completers.Therankingoftheotherthreecountrieshaschanged,though,withSwedensur‐passingbothFinlandandNorwaywithrespecttobothcompletersandnon‐completers.ThenfollowsNorwayand,finally,comesFinland.Indeed,atage26,Finlandcomesoutwiththelowest“activity”shareand,conversely,thehighestNEETshareamongbothcompletersandnon‐completers.Asnotedabove, this outcome for Finland seems to be due, at least in part, to thegrowingsharebeyondage21ofyoungwomenoutsidebotheducationandthelabourmarket.Additionally,(registered)unemploymentturnsouttobequitewidespreadamongFinnishnon‐completersaged26.However,ashasbeenindicatedinearlierpartsofthisreportandaswillbeshownlateron,this is largely a cohort effect related to theweak employment prospectsfacedbyyounglabourmarketentrantsinthe1990s.


0%10%20%30%40%50%60%70%80%90%

100%


Completers


0%10%20%30%40%50%60%70%80%90%

100%


Non‐completers


Figure6.8:Mainactivitiesatage26forcompletersandnon‐completersofanuppersecondaryeducation,basedonpooledinformationontwo(1993and1998)oftheyouthcohortsunderstudy,bycountry

Notes: Completers are defined as young people having completed an upper secondary education

by age 21. Conversely, non‐completers are defined as those having reached 21 years‐of‐age

without finishing an upper secondary degree. Recall that we are not able to trace the 2003

cohort of 16‐year‐olds up to age 26, only up to age 21. This also affects the total number of

completers and non‐completers in respective country underlying the %‐shares displayed in this

particular figure: now the number of completers is 68,003 for Denmark, 108,935 for Finland,

72,885 for Norway and 154,288 for Sweden, whereas the number of non‐completers is 36,762

for Denmark, 23,728 for Finland, 29,521 for Norway and 28,818 for Sweden. For definitions of

the five main activity groups, see Chapter 2.




%‐

share

%‐point

gap

%‐

share

%‐point

gap

%‐

share

%‐point

gap

%‐

share

%‐point

gap

Student 35.1 ‐17.7 27.0 ‐10.9 29.5 ‐16.9 24.6 ‐8.0

Employed 59.2 +2.7 61.6 ‐10.2 59.4 ‐2.2 67.3 ‐12.5


Unemployed 3.2 +4.9 6.1 +9.2 3.3 +8.5 4.2 +7.8



NEET activities 5.7 +15.0 11.3 +21.1 11.0 +19.3 8.0 +20.6

Total 100.0 100.0 100.0 100.0





non‐completers’ share is lower: for instance, the share of Danish non‐completers in education is

17.7 %‐points lower (or 17.4%) than the corresponding share for completers (35.1%). Likewise, a

positive sign means that the share of the non‐completers is larger than that of the completers in

that particular activity.

6.3.3 Situation15yearslater,atage31

Finallywecomparethelabourmarketoutcomesofcompletersandnon‐completersatage31,thatis,15yearsaftertheseyoungadultsleftcom‐pulsoryeducation.At thisparticularage,about95%of theDanishand94%oftheSwedishcompletersareeitheremployedorenrolledinedu‐cation(Figure6.9,uppergraph), that is,astill largershare thanatage26.InFinland,this“activity”shareis89%,whichcorrespondstoanonlymarginallyhighersharethanfiveyearsearlier.InNorway,ontheotherhand,thissharehasdeclinedslightly,from89%atage26tobelow87%atage31,apatternobservedalsoinearlierpartsofthisreport.

OftheDanishandSwedishcompleters,about85%areinworkinglifewhenaged31,comparedtosome76%ofFinnishandNorwegiancom‐pleters.Hence,thecompleters’employmentsituationhasimprovedfur‐ther by age 31.The share of completers still enrolled as full‐time stu‐dentshasshrunktobelow10%inDenmarkandSwedenandtolessthan11%inNorway.ThehighestshareisfoundforFinland,or13.5%.


0%10%20%30%40%50%60%70%80%90%

100%


Completers


Whiletheemploymentsituationhas, inall fourcountries, improvedalso for thenon‐completersover the5‐yearperiod fromage26 toage31,thegrowthinthenon‐completers’employmentsharehasbeenclear‐lyweaker: up to a share of 73% inDenmark, 65% in Sweden, 62% inNorway and 60% in Finland (lower graph of Figure 6.9). As a conse‐quence, the gap in employment shares between completers and non‐completers is in all four countries larger at age 31 than at age 26 (cf.Table 6.2 and 6.3). Simultaneously, the gap in completers’ and non‐completers’ student shares has turned small (Finland andNorway) ornegligible(DenmarkandSweden).Thisalsoexplainswhythe“activity”gapbetweencompletersandnon‐completersis,ineffect,slightlysmalleratage31thanatage26,exceptforSwedenwhereitisunchangedand,hence, stillhighestamong the four countries (Table6.3).However,de‐spite these various trendsbetweenandwithin countriesup to age31,the overall cross‐country pattern observed for completers and non‐completers at age26 showsup also five years later, at age31: an em‐ployment share and, hence, also an “activity” share of non‐completerslaggingfarbehindthatofcompleters.

Figure6.9:Mainactivitiesatage31forcompletersandnon‐completersofanuppersecondaryeducation,basedoninformationonone(1993)oftheyouthcohortsunderstudy,bycountry


0%10%20%30%40%50%60%70%80%90%

100%


Non‐completers


Notes: Completers are defined as young people having completed an upper secondary education by

age 21. Conversely, non‐completers are defined as those having reached 21 years‐of‐age without

finishing an upper secondary degree. Recall that we are not able to trace the 1998 and 2003 cohorts

of 16‐year‐olds up to age 31. This affects the total number of completers and non‐completers in the

respective country underlying the %‐shares displayed in this particular figure: now the number of

completers is 36,932 for Denmark, 55,088 for Finland, 36,451 for Norway and 77,498 for Sweden,

whereas the number of non‐completers is 19,778 for Denmark, 10,507 for Finland, 14,561 for

Norway and 13,113 for Sweden. For definitions of the five main activity groups, see Chapter 2.

The steady increase up to age 31 in the share of Danish and Swedishcompletersineithereducationoremploymentismirroredbyaconcom‐itantdecreaseintheirshareinNEETactivities.Indeed,theshareof31‐year‐old completers outside both education and work is very low inDenmarkandSweden.InFinland,itisabout11%amongboth26‐year‐oldand31‐year‐oldcompleters,withunemploymentshowingupasanimportant explanation for also 31‐year‐old completers’ comparativelyhigh NEET share. In Norway, in contrast, the share of completers inNEETactivitiesisslightlyhigheratage31(13%)thanatage26(11%).ThisrelativelylargeandincreasingNEETshareamongNorwegiancom‐pletersseemstobemainlydue towithdrawalnotonly fromeducationbut also from the labourmarket: the share of completers in unknowninactivityincreasessteadilyfromage21(6.5%)uptoatage31(closeto10%).Whileasimilartrendisdiscerniblealsoforthosereceivingdisa‐bility benefits, the share of disability beneficiaries among Norwegiancompletersisstillbyage31belowonepercent.




%‐

share

%‐point

gap

%‐

share

%‐point

gap

%‐

share

%‐point

gap

%‐

share

%‐point

gap

Student 9.9 +0.9 13.5 ‐2.9 10.7 ‐3.6 9.0 +0.1

Employed 85.5 ‐12.6 75.5 ‐15.6 76.0 ‐13.8 85.3 ‐20.6


Unemployed 1.6 +1.7 4.8 +7.7 2.8 +6.8 2.1 +5.8



NEET activities 4.6 +11.8 11.0 +18.6 13.4 +17.3 5.8 +20.4

Total 100.0 100.0 100.0 100.0





non‐completers’ share is lower: for instance, the share of Danish non‐completers in employment

is 12.6 %‐points lower (or 72.9%) than the corresponding share for completers (85.5%). Likewise,

a positive sign means that a larger share of the non‐completers than of the completers is in that

particular activity.

DenmarkshowsupwiththelowestNEETshare(16.4%)alsoamong31‐year‐old non‐completers, whereas substantially higher shares emergefor theother threecountries:about26%forSweden, close to30%forFinlandandalmost31%forNorway.Hence,stillbyage31remarkablylarge shares of the non‐completers stand outside both education andemployment.Indeed,theirNEETshareisonlymarginallylowerthanfiveyears earlier, at age 26, and inNorway it reveals an increasing ratherthan decreasing trend. The moderate change in the non‐completers’NEET share in adulthood ismainly explained by two opposite trends:declining shares of non‐completers in unemployment (compared withthesituationatage26)andgrowingsharesof themwithdrawingfromthelabourmarket,especiallyintodisabilityarrangements.Accordinglyitis not surprising that the gap in the share of completers and non‐completersondisabilitybenefitshasincreasedinallfourcountriesfromage26uptoage31,whereasthecorrespondinggapsinunemploymentandinactivityshareshavetypicallydeclinedoverthesefiveyears.

6.3.4 Theinfluenceofeconomicshocks

As a final exercise of this sub‐chapter, we again split the informationprovidedatage26intotwoparts:oneillustratingthedistributionacrossmain activities at this particular age of young people belonging to the“economic‐bust” cohort of 1993, and one providing the same infor‐mation for the “economic‐boom” cohort of 1998. Needless to say, the


focusnowisonacomparisonbycohortofthesituationofcompletersvs.that of non‐completers. The outcome of this exercise is presented inFigure6.10,separatelyforeachofthefourNordiccountriesunderstudy.

The firstgraphofFigure6.10givesthedistributionacrossmainac‐tivities of Danish completers and non‐completers belonging to respec‐tiveyouthcohort.The“activity”(education+employment)shareofthe1998 economic‐boom cohort is slightly higher than for the 1993 eco‐nomic‐bust cohort among both completers and non‐completers. Con‐versely, the 1993 cohort is characterised by a somewhat higherNEETshareirrespectiveofwhetherornottheyoungpersonhascompletedanupper secondary degree by age 21. In this sense, the 1998 economic‐boomcohortseemstohaveexperiencedamorefavourablelabourmar‐ket situation when aged 26. Simultaneously, however, the changesacrossNEETactivitieshavebeenremarkable,andnotnecessarilyalwaystothefavourofthe1998cohort.Inparticular,whiletheshareinregis‐tered unemployment is smaller (completers) or dramatically smaller(non‐completers) in the 1998 cohort,when compared to the 1993 co‐hort,thesituationisreversedwhenitcomestotimespentoutsidebotheducationandthelabourforce:highersharesofyoungpeoplebelongingtothe1998cohortare,whenaged26,eitherondisabilitybenefitsorinother(unknown)typesof inactivity.Moreover, thisholdstrue forbothcompletersandnon‐completers.These findingspoint toa “reshuffling”ofNEETsratherthantoastraightforwardimpactofaneconomicshock.

ThenextgraphprovidesthecorrespondinginformationforFinland.As forDenmark,we seea clear improvementof completers’ andespe‐cially of non‐completers’ engagement in education and employmentacrossthetwocohort,andacorrespondingreductionintheirNEETac‐tivities.But incontrasttoDenmark, thesharesamongbothcompletersandnon‐completersindisabilityarrangementsorothertypesofinactiv‐ityarebasicallythesameinthetwocohorts.Inotherwords,thedeclineinNEET activities across the two cohorts is in Finland almost entirelyexplainedbylessregisteredunemploymentinthe1998economic‐boomcohortthaninthe1993economic‐bustcohort.Thesefindingsarewellinline with the high unemployment levels that prevailed long after thestartoftheeconomicrecoveryin1994.


0%10%20%30%40%50%60%70%80%90%100%

Completers,cohort 1993


Non‐completers,cohort 1993


Denmark


0%10%20%30%40%50%60%70%80%90%100%





Finland


Figure6.10:Distribution(%‐share)ofcompletersandnon‐completersofanuppersecondaryeducationacrossmainactivitiesatage26,bycountry;comparisonofthe“economic‐bust”cohortof1993withthe“economic‐boom”cohortof1998


0%10%20%30%40%50%60%70%80%90%

100%





Norway


0%10%20%30%40%50%60%70%80%90%100%





Sweden


Notes: See Figure 6.7.

The graph displaying the situation for Norwegian completers and non‐completersbelonging toeitheroneof the twocohorts repeatsapatternthathasalreadybeendiscernibleinpreviouspartsofthisreport:adropinthe share of students that is not fully compensated by the concomitantincrease in employment, resulting in an “activity” (education + employ‐ment) share that reveals a declining rather than increasing trend overcohorts(aswellaswithincohortswithage).Simultaneously,weseemoreyoungpeoplemovingoutsideboth education and the labour force.Thistrendshowsupstronglyamongbothcompletersandnon‐completers.


ThelastgraphofFigure6.10illustratesthesituationforSweden.Thecombined education and employment share is slightly higher for com‐pleters belonging to the1998 economic‐boom cohort, but amongnon‐completers it is of approximately of the same size in the two cohorts.Hence,while the completers’NEET share is slightly lower in the1998cohort,itisunchangedacrossthetwocohortsfornon‐completers.AsinDenmarkandNorway,muchmoreseemstohappenwith thecomposi‐tionofNEETs: lowersharesofunemployed jobseekers in the1998co‐hortbutattheexpenseofhighersharesoutsidebotheducationandthelabourforce.Again,thesamepatternshowsupamongbothcompletersandnon‐completers.

Allinall,themostprofounddifferencebetweencompletersandnon‐completers is much weaker employment prospects of non‐completersand, hence, notably higher risks of ending up in NEET activities. Eco‐nomicbusinesscycles,ontheotherhand,seemtoimpactonyoungpeo‐pleinmuchthesamewayirrespectiveoftheireducationalbackground(completionornotofanuppersecondarydegreebyage21).Butwithaninitiallyweaker labourmarket attachment of non‐completers, it is notsurprisingthatalsotheconsequencesofaneconomicshockaretypicallyconceivedtobemoreseriousforlow‐skilledyoungpeople.Apartfromapersistently higher NEET share among non‐completers, another con‐spicuous trend that seems tobe little, if at all, linked to theprevailingeconomic situation is the growing tendency among non‐completers ofmoving intopotentiallymore riskyNEETactivities, that is,withdrawalnotonlyfromeducationbutalsofromthelabourforce,includingregis‐teredunemployment.InNorway,thistrendisforsomereasonconspic‐uouslycommonandincreasingalsoamongcompleters.

6.3.5 Mainfindings

Themain findingis,unsurprisingly, that lowersharesofnon‐completersthanofcompletersareeitherineducationorinemploymentandthatthisgapprevailsuptoage31,atleast.Inotherwords,non‐completersdonotclose up the gap to completers in their “activity” (education + employ‐ment)share.Simultaneously,however,thisgaptocompletersintermsofeducationandemploymentseemstoberelativelysmall,oratleastsmallerthanwouldperhapshavebeenexpectedinviewofthediscussionoflow‐skilledyoungpeoplebeingthelosersintoday’slabourmarkets.

Indeed, the conspicuous “success rates” in terms of studying andworking observed for also non‐completers could be taken to indicatethat, inthelastresort,manyofthemfarereasonablywellinthelabour


marketasyoungadultsdespitealowformaleducation.Thehighestsuc‐cess rates are obtained for Denmark. The difference in non‐completeroutcomesbetweenDenmark,ontheonehand,andFinlandandSweden,ontheotherhand,couldthenbeinterpretedasaresultofnotablecross‐countrydifferences in thecompositionof thegroupofnon‐completers.The so‐called hard core of non‐completers, that is, young peoplewithdisproportionallyweaklabourmarketprospects,tendtodropoutfromeducation at an early age in principally any country. If the number ofnon‐completers increases, thismost likely implies thatalsoyoungpeo‐plewith lessseriousproblemsand,hence,withanobviouslycloser la‐bourmarketattachment,areforsomereasonshiftingintothegroupofnon‐completers. If this is thecase, thentheoverallsizeof thegroupofnon‐completers could also tell us something about the composition ofnon‐completers. For this very reason we would expect the relativelylargeshareof21‐year‐oldDanishnon‐completerstodobetteronaver‐age than the comparatively small sharesof non‐completers among the21‐year‐oldsobservedforFinlandandSweden(cf.Chapter2).

However, this interpretationdoesnot get supportwhen comparingFinland and Sweden to Norway. In this setting, a large cross‐countrydifferenceinnon‐completionratesdoesnotresultinconspicuouslydif‐ferent success rates of the three countries’ non‐completers.Moreover,even in the case of relatively high employment rates also among non‐completers,previousresearchhasshownthatthereisalargeandsignif‐icantly negative wage differential between employed non‐completersandemployedcompleters(seeBratsbergetal.,2010).

Apart from differences in the quality of completers’ and non‐completers’employmentcontracts,adimensionoverlookedinouranal‐yses, thereareworryingaspects also related to the time trend innon‐completers’labourmarketprospects.Inparticular,theresultspresentedin this sub‐chapter point to the employment share of non‐completerslagging increasingly behind that of completers when comparing theirsituationatthreedifferentagepoints(21,26and31).Thisishighlyevi‐dentinTable6.4,whichreproducespartsoftheinformationprovidedinTables6.1to6.3.Simultaneously,thecross‐countryvariationinthegapshaving emerged by age 31 between completers’ and non‐completers’employment shares is particularly pronouncedwhen it comes to Den‐mark and Sweden: in both countries, completers fair equally well intermsofemployment,whereasthegaptothenon‐completers’employ‐mentshareisalmosttwiceaslargeinSweden(20.6%‐points)asitisinDenmark(12.6%‐points).


Table 6.4: Selected main activities at age 21, 26 and 31, respectively: completers (%‐share) vs. non‐completers (%‐point gap)


%‐

share

%‐point

gap

%‐

share

%‐point

gap

%‐

share

%‐point

gap

%‐

share

%‐point

gap

Employed

at age 21 46.6 ‐9.1 34.9 +4.1 30.3 +12.4 46.0 ‐7.1

at age 26 59.2 +2.7 61.6 ‐10.2 59.4 ‐2.2 67.3 ‐12.5

at age 31 85.5 ‐12.6 75.5 ‐15.6 76.0 ‐13.8 85.3 ‐20.6

Disability benefit (pensioner)

at age 21 0.0 +1.8 0.3 +3.8 0.2 +3.9 0.2 +8.3

at age 26 0.1 +2.9 0.6 +5.0 0.5 +5.3 0.6 +8.9

at age 31 0.4 +4.0 1.1 +5.8 0.9 +6.2 1.4 +10.8

Other (inactivity)

at age 21 5.2 +8.9 3.5 +12.3 6.5 +8.9 3.5 +4.3

at age 26 2.4 +7.2 4.6 +6.9 7.2 +5.5 3.2 +3.9

at age 31 2.6 +6.1 5.1 +5.1 9.7 +4.3 2.3 +3.8

Notes: See Tables 6.1 to 6.3.

Thecounterpart to thisdevelopment isasteadilygrowingshareofnon‐completersmovingoutsidebotheducationandthelabourmarket,eitherintodisabilityarrangementsorother(unknown)typesofinactivity.Whiletheshareofdisabilitybeneficiariesincreaseswithagealsoamongyoungcompleters, this share is initiallymuch higher and also increasesmuchfasteramongthenon‐completers,apatternrepeatedforallfourcountries.

Whenitcomestoothertypesofinactivity,thesituationvariessubstan‐tiallyacrosscountries,asalsopointedoutearlier.Forall fourcountries,weobserveanarrowinggap incompleters’andnon‐completers’ “other”inactivityshares(Table6.4).However,inbothDenmarkandSwedenthisisduetoadeclinewithageintheinactivityshareamongbothcompletersand non‐completers, with this trend being stronger for the non‐completers. InFinland andespecially inNorway, on theotherhand,wesee growing numbers of completers withdrawing from both educationand the labour forcewhengoing fromage21up toage31,whereasanoppositetrendisobservableamongnon‐completers.Indeed,theshareinunknowninactivityamong31‐year‐oldNorwegiancompletersisnotonlymuch higher than the corresponding share for completers in the otherthreecountries.ItalsoexceedsbyfartheinactivityshareofbothDanishand Swedish non‐completers aged 31,while it is onlymarginally lowerthantheinactivityshareof31‐year‐oldnon‐completersinFinland.

Moreover, these overall patterns and trends across and within thefourNordiccountriesunderstudy,aswellasacrossandwithinthethreeyouth cohortsunder scrutiny, seem tohavebeenonlymarginally, if atall,affectedbychangesintheeconomicenvironment.Changingbusinesscyclesseemtotypicallyimpactonyoungpeopleinmuchthesameway


irrespectiveoftheiruppersecondarygraduationbackground(complet‐er vs. non‐completer). However,with an initiallymuchweaker labourmarket attachment, the consequencesare inevitablymore far‐reachingforyoungnon‐completersthanfortheircompleterpeers.

Finally, we undertake a rescaling of also these findings by relatingthem to the full youth population of each of the fourNordic countriesunder study. Table 6.5 displays the outcome of this exercise by mainactivityatage21,26and31,respectively,separatelyforcompletersandnon‐completers.

About50%ofbothFinnishandNorwegianyouthareenrolledinfull‐timeeducationwhenaged21,withcompleterscontributingoverwhelm‐inglytothishighshare.Sweden,inturn,comesoutwiththelowestshareofstudentsatthisparticularagemainlyduetoaverysmallshare(under4%) of young non‐completers continuing in education when aged 21.ForDenmark,incontrast,weobserveastrikinglyhighshareof21‐year‐oldnon‐completers still in education. Conversely, Sweden turns out tohave the highest share of 21‐year‐olds in employment, but this holdstrue for completers only. YoungSwedeswithonly an exam fromcom‐pulsory school stillwhen aged 21 are the least likely of youngNordicnon‐completersofbeingineducationoremployment.

Table 6.5: Distribution of young completers and non‐completers by main activity at age 21, 26 and 31, respectively, by country, %‐share of the full youth population

Status at age 21 – %‐share of the full population

Completers Non‐completers

Main activity DK FI NO SW DK FI NO SW

Student 28.8 43.9 42.5 36.3 15.0 5.2 7.7 3.9

Employed 29.2 28.6 21.3 38.6 14.0 7.0 12.7 6.2

Student + employed 58.0 72.5 63.8 74.9 29.0 12.2 20.4 10.1

Unemployed 1.4 6.4 1.8 5.9 2.5 2.2 3.6 3.3

Pensioner 0.0 0.2 0.1 0.2 0.7 0.7 1.2 1.4

Other 3.3 2.9 4.6 2.9 5.3 2.8 4.6 1.2

NEET share 4.7 9.5 6.5 9.0 8.5 5.7 9.4 5.9

In total 62.7 82.0 70.3 84.0 37.3 18.0 29.7 16.0




Student 22.0 22.1 20.7 20.7 15.0 2.9 3.7 2.7

Employed 37.1 50.5 41.8 56.5 14.0 9.3 17.0 8.8

Student + employment 59.1 72.6 62.5 77.2 29.0 12.2 20.7 11.5

Unemployed 2.0 5.0 2.3 3.5 2.5 2.8 3.5 1.9

Pensioner 0.1 0.5 0.4 0.5 0.7 1.0 1.7 1.5

Other 1.5 3.8 5.1 2.7 5.3 2.1 3.8 1.1

NEET share 3.6 9.3 7.8 6.7 8.5 5.9 9.0 4.5

In total 62.7 82.0 70.3 84.0 37.3 18.0 29.7 16.0





Student 6.2 11.1 7.5 7.6 4.0 1.9 2.1 1.5

Employed 53.6 61.9 53.4 71.7 27.2 10.8 18.5 10.4

Student + employed 59.8 73.0 60.9 79.3 31.2 12.7 20.6 11.9

Unemployed 1.0 3.9 2.0 1.8 1.2 2.3 2.9 1.3

Pensioner 0.3 0.9 0.6 1.2 1.6 1.2 2.1 2.0

Other 1.6 4.2 6.8 1.9 3.2 1.8 4.2 1.0

NEET share 2.9 9.0 9.4 4.9 6.0 5.3 9.2 4.3

In total 62.7 82.0 70.3 84.0 37.3 18.0 29.7 16.0

Notes: See Tables 6.1 to 6.3.

Sweden, together with Finland, also stands out with a comparativelyhigh share of 21‐year‐olds registered as unemployed jobseekers, butonly among young completers. Among 21‐year‐old non‐completers,Norwayshowsupwith thehighestunemployment ratio, albeit thedif‐ference to theother threecountries is rather small.However, togetherwithDenmark,Norwayalsohasa relativelyhighshareof21‐year‐oldswhose activity is unknown.Moreover, this high inactivity share showsupamongbothyoungcompletersandyoungnon‐completers.

Byage26,Swedenstillcomesoutwiththehighestemploymentsharein the youth population but, again, only for completers; Swedish non‐completers’ employment situation is weakest among Nordic non‐completers also at age 26. The share of young people enrolled in full‐timeeducationstillwhenaged26has,inturn,convergedacrossthefourcountries and,moreover, among both completers and non‐completers.TheonlyexceptionisDenmark,wheretheshareofnon‐completerscon‐tinuingasfull‐timestudentsisatthesamehighlevelasfiveyearsearli‐er,atage21.

WhenitcomestoNEETactivities,theoverallcross‐countrypatternatage26isverysimilartothesituationobservedatage21.Inparticular,the shareof theunemployedhas remained relativelyhigh inbothFin‐landandSwedenduetounemploymentstillbeingmorecommonamongFinnishandSwedishcompleters,whencomparedtoDanishandNorwe‐gian completers. And also among the 26‐year‐olds, Norway comes outwith the highest share of unemployed jobseekers among the non‐completers.AlsotheshareofyoungNorwegiansoutsidebotheducationandthelabourmarketiscomparativelyhighstillatage26,withthein‐activity share being even higher among completers than among non‐completers.WhiletheinactivitysharehasremainedatahighlevelalsoamongDanishnon‐completers, thesituationhasimprovedamongDan‐ishcompleters.


Byage31,finally,allfourcountrieshavearound10%oftheiryouthsenrolled as full‐time students, with the student share among the non‐completersnowbeingvery low.Theemployment share ishigh amongFinnish and especially among Swedish completers, whereas the em‐ployment situation of the countries’ non‐completers is relativelyweakstillatage31.AreversedsituationisobservedforDenmarkandNorwayin the sense that the employment share is comparatively low amongcompletersbutrelativelyhighamongnon‐completers.

Theshareofyoungpeopleinunemploymenthascomedowninallfourcountriesand,moreover,amongbothcompletersandnon‐completersbutis,nonetheless,stillhighestamongNorwegiannon‐completers.Likewise,Norwayhasthehighestshareofyoungpeopleoutsidebotheducationandthelabourmarketalsoamongthe31‐year‐olds.Indeed,comparedtothesituation at age 26, the inactivity share has increased rather than de‐creasedamongbothcompletersandnon‐completers.

Onthewhole,then,theoverallimpressionfromthisexerciseofrescal‐ing themain activity shares at three age points of completers and non‐completers inrelationto the fullyouthpopulationofeachcountry,doesnotseemtochangethegeneralpicturemediatedsofar.Particularlystrik‐ingisthestabilitywithageintheNEETshareamongthenon‐completers.AnotherconspicuousfeatureofTable6.5isthesimilarityinNEETsharesacrossthefourcountries,asimilaritythatishigherthanexpectedinviewof the large differences observed in school‐to‐work‐transition patternsandcompleting‐ratetime‐profilesbetweenthecountries.

6.4 Mainactivitiesbeyondage21–latecompletionvs.non‐completion

Weendthischapteronlabourmarketoutcomesinadulthoodbyrelax‐ing our “prime” definition of non‐completers. More precisely, we nowallow for the fact that someof thenon‐completers,but far fromall,dofinaliseanuppersecondaryeducation,butonlyaftertheageof21, i.e.,morethanfiveyearsafterhavingleftcompulsoryschool.Asshownear‐lier,notablyinChapter2,latecompletionofuppersecondaryeducationiscommonamongyoungpeopleinDenmarkandNorway.InFinlandandSweden,ontheotherhand,amajorityofyoungpeoplehasfinalisedanuppersecondaryeducationbythetimetheyturn21.

Westart thissub‐chapterbyexploringtowhatextentyoungpeoplewithonlyabasiceducationstillatage21succeedincompletinganup‐per secondary education later in life. Again, this is done for two age


points:bythetimetheyturn26andbythetimetheyturn31.Inthefol‐lowing,theseyoungpeoplearecalled“latecompleters”inordertosepa‐ratethemfrom21‐year‐oldcompleters,thatis,youngorearlycomplet‐ers.Likewise,weuse the term“adultnon‐completer” foryoungpeoplelackinganuppersecondarydegreestillatage26orage31inordertoseparate them from 21‐year‐old non‐completers, that is, young non‐completers. Inanextstep,wecomparethe labourmarketoutcomesofyoung completers, late completers and adult non‐completers at thesesameagepoints.

Thisparticularfocusonlatecompletersimpliesthatmostattentionispaidtoyoungpeopleidentifiedasnon‐completersatage21.Morepre‐cisely, the emphasis is on whether or not these 21‐year‐old non‐completers succeed in achieving anupper secondary certificate by age26orbyage31,andtowhatextent this latecompletioneventuallyaf‐fectstheir labourmarketsituationwhencomparedtoearlycompletersand,especially,toadultnon‐completers.Inotherwords,isearlycomple‐tion the best choice, late completion a second‐best choice and non‐completion still in adulthood the worst alternative in terms of labourmarketoutcomesasayoungadult?Thissettingalsomeansthatallsub‐sequentresultsarebasedon informationononly twooutofour threeyouthcohortsforthesimplereasonthattheyoungestcohort(the2003cohortof16‐year‐olds)cannotbetracedbeyondtheageof21.

6.4.1 Latecompletionofuppersecondaryeducation

There might be reason to first recall the shares of 21‐year‐old non‐completersinthefourNordiccountriesunderstudy.WethereforestartbyreproducingtheinformationprovidedinTable2.2ofChapter2,butnowwith the youngest (2003) cohort of 16‐year‐olds left out. As hasbeenpointedoutearlierinthisreport,non‐completionofanuppersec‐ondary degree is strikingly common among 21‐year‐oldDanes, less soamong21‐year‐oldNorwegiansandquiteinfrequentamong21‐year‐oldFinnsandSwedes.

Table 6.6: Non‐completion rates (%‐shares) at age 21 in four Nordic countries, by cohort

Cohort Denmark Finland Norway Sweden

16‐year‐olds in 1993 34.7 16.0 28.5 14.5

16‐year‐olds in 1998 39.0 19.7 29.1 17.0

Thenexttable(Table6.7)showstowhatextentthese21‐year‐oldnon‐completershavesucceeded in finalisinganuppersecondarydegreeei‐therbyage26orbyage31.InDenmark,morethanone‐halfofthe21‐


year‐oldnon‐completersfromthe1993cohorthadeventuallycomplet‐edanuppersecondarydegreebythetimetheyturned31.Closeto42%of them had actually come around to completing an upper secondaryeducationbyage26.Thishighshareoflatecompletersalsoexplainstherapiddecline beyond age 21 in thenon‐completion sharedisplayed inFigure2.2aofChapter2fortheoldest(1993)Danishcohortof16‐year‐olds. Moreover, this high share of late completers is repeated for theDanish1998cohort(about43%byage26).

Table 6.7: Completion of an upper secondary degree by age 26 and by age 31 among 21‐year‐old non‐completers, by country

Completion by age


Cohort 26 31 26 31 26 31 26 31

16‐year‐olds in 1993 41.6 51.8 25.4 34.7 26.3 36.3 19.3 26.4

16‐year‐olds in 1998 42.9 29.7 29.1 16.7

In the other three countries, the completion rates beyond age 21 aremuchlower.InFinlandandNorway,slightlymorethanone‐thirdoftheyoungpeopleinthe1993cohortidentifiedasnon‐completersstillatage21hadachievedanuppersecondarycertificatebythetimetheyturned31 with the corresponding share being only about 26% for Sweden.Moreover, while the late‐completion rate reveals an increasing trendacrosscohortsinbothFinlandandNorway,ithasratherbeendeclininginSweden.

These cross‐Nordic differences in young non‐completers’ likelihoodofachievinganuppersecondarycertificateonly inadulthoodarequitepronounced. It could be argued that the substantially lower non‐completionratesbeyondage21observedforFinland,NorwayandSwe‐den,whencomparedtoDenmark,arerelatedtothecomparativelyhighshareofnon‐completersamong21‐year‐oldDanes(Table6.6).However,the markedly higher non‐completion share among 21‐year‐old Danescanonlyexplainpartof theseconspicuouscross‐countrydifferences inlate‐completionrates. Inparticular,while the late‐completionratesareverysimilarforFinlandandNorway,theshareofnon‐completersbyage21 ishighlydifferent in thetwocountries.Likewise,while theshareof21‐year‐old non‐completers is of similar size in Finland and Sweden,there are substantial differences between the two countries when itcomes to late‐completion rates. In other words, there is no clear‐cutcross‐countrycorrelationbetween theearly‐and late‐completionratesreportedinTables6.6and6.7.


6.4.2 Latecompleters:comparisonoflabourmarketoutcomesatage26

The completion patterns of post‐compulsory‐school degrees displayedinTables6.6and6.7raiseseveralquestions:Doearlycompleterstendtofairbetterintermsoflabourmarketoutcomesthanlatecompleters?Likewise, do late completers typically fair better than adult non‐completers?Thenextfigureaimstoprovideatleastpartofananswertothesequestionswiththefocusbeingonthesituationprevailingamong26‐year‐olds differing in their completion and non‐completion history.Inordertocleanthepicturefromchangingcohort‐specificdistributionsacrossmainactivitiesaswellasfrombusinesscyclefluctuations,Figure6.11isbasedoninformationforthe1998cohortonly,acohortofyoungpeoplethatcanbetraceduptoage26,butnottoage31.Wereturntothesituationamong31‐year‐oldsinthenextsection.

Figure6.11containsfourcountry‐specificgraphs,eachofwhichdis‐plays three distributions across our five main activity categories. Allthreedistributions refer to the situationprevailing at age26,whereasthe allocation of these 26‐year‐olds across the three distributions de‐pendson their completionandnon‐completionhistorywith respect topost‐compulsory‐school educations. The first (left‐hand‐side) pillar il‐lustrates the distribution across main activities of the 1998 cohort’syoung completerswhen aged 26, that is, of those young people in thecohortwhohadcompletedanuppersecondaryeducationalreadybyage21. Thesecond(middlepillar)showsthecorrespondingdistributionforthe cohort’s late completers, that is, those young people in the cohortwhowereclassifiedasnon‐completerswhenaged21butwhohadsuc‐ceeded in completing anupper secondarydegreeby age26.The third(right‐hand‐side) pillar, finally, displays the distribution across mainactivitiesofthecohort’sadultnon‐completers,thatis,thoseyoungpeo‐pleinthecohortwhostillwhenaged26hadanexamonlyfromcompul‐soryschool.

The first graph of Figure 6.11 illustrates the situation for Danishyoungcompleters, latecompletersandadultnon‐completersbelongingto the 1998 cohort. The differences in main‐activity distributions be‐tweenyoungcompletersandlatecompletersaremarginalatage26.Inboth groups, engagement in either education or employment is theoverwhelmingly most common activity. Hence, the advantage of com‐pletinganuppersecondarydegreebyage21insteadofage26seemstobeminor in Denmark, at least in terms of labourmarket outcomes inadulthood. The situation is entirely different for Danish adult non‐completers:an“activity”(education+employment)shareofabout74%


impliesthatone‐fourthoftheadultnon‐completersisinNEETactivitieswhenaged26,belongingmainlytothedumpingcategoryof“other”(un‐known)inactivity.

The next graph gives the corresponding information for Finland. Itclearly shows that young completers faremuch better than late com‐pleters. In particular, about nine out of ten young completers are en‐gaged in either education or employment by age 26. Among late com‐pleters,thisshareisapproximatelytenpercentagepointslower,orsome80%. Instead, they face a higher risk of showing up as unemployedjobseekers or disability beneficiaries, when compared to young com‐pleters. However, compared to adult non‐completers, these late com‐pletersdoquitewell.The“activity”shareofadultnon‐completersisonlyabout65%.Whiletheyhaveanonlymarginallyhigherriskofbecomingunemployed,whencomparedtolatecompleters,theirriskofendingupineitherdisabilityarrangementsorothertypesofinactivityisconsider‐ablyhigherthanforlatecompleters.Hence,earlycompletion,latecom‐pletionandnon‐completionstillasayoungadultmakesaconsiderabledifferenceinFinland.

A more or less similar overall pattern emerges for Norway exceptthat the main‐activity distributions of young and late completers aremore similar inNorway than in Finland. Indeed, the difference in em‐ployment shares between young and late completers is marginal inNorway,whereas there are largerdifferencesbetween the twogroupswhenitcomestoenrolmentineducationandregisteredunemployment:the share enrolled in education still at age 26 is higher among youngcompleters, whereas the share in registered unemployment is higheramong latecompleters.Aconspicuousfinding,however, is that thedif‐ferenceininactivitysharesamongyoungandlatecompletersisclosetonegligible,implyingthatyoungandlatecompletersareequallylikelytowithdrawoutsidebotheducationand the labourmarket.Thedistribu‐tionacrossmainactivitiesofadultnon‐completers isdistinctly less fa‐vourable and, in effect, remarkably similar to that observed for adultnon‐completersinFinland:an“activity”sharejustabove60%incombi‐nationwithlargesharesbeinginNEETactivitiesalreadyatage26.


0%10%20%30%40%50%60%70%80%90%

100%

Young completersby age 21

Late completersby age 26

Adult non‐completersby age 26

Denmark


0%10%20%30%40%50%60%70%80%90%

100%




Finland


Figure6.11:Main‐activitydistributions(%‐share)byage26ofyoungcomplet‐ersvs.youngnon‐completershavingcompleted(latecompleter)ornothavingcompleted(adultnon‐completer)anuppersecondaryeducationbyage26,basedoninformationforthe1998youthcohort,bycountry


0%10%20%30%40%50%60%70%80%90%100%




Norway


0%10%20%30%40%50%60%70%80%90%100%




Sweden


Notes: For definitions of the five main activity groups, see Chapter 2. Young completers = young

people having completed an upper secondary education already by age 21. Late completers = 21‐

year‐old non‐completers having achieved an upper secondary degree by age 26 (but not yet by age

21). Adult non‐completers = young people with only a basic education still at age 26.

A third kind of pattern is discernible for Sweden (last graph of Figure6.11).Asnotedearlier in thisreport,youngSwedishcompletersfareex‐tremely well: their “activity” (education + employment) share exceeds90%byage26,asharethatlagsonlyslightlybehindthatofyoungDanishcompleters.Latecompleters,incontrast,donotseemtomanagebetterintermsof labourmarketoutcomesthandoadultnon‐completers: thedif‐ferenceinmain‐activitydistributionsisstrikinglysmall.Whilethe“activi‐ty” shareof26‐year‐oldnon‐completers is about68%, it is only slightly


higher for late completers. Hence, when compared to the other threecountries, Swedish late completers fare worst, whereas Swedish adultnon‐completers farebetter thanbothFinnishandNorwegianadultnon‐completers,andonlyslightlyworsethanDanishadultnon‐completers.

6.4.3 Latecompleters:comparisonoflabourmarketoutcomesatage31

Next we compare the labour market outcomes of late completers andadultnon‐completers fiveyears later,atage31(Figure6.12).Morepre‐cisely,weamendthesettingusedinthepreviousfigureandaddonemoredistribution: a pillar showing the distribution across main activities ofyoungnon‐completershavingachievedanupper secondarydegreeonlybyage31(butnotyetbyage26).Inotherwords,Figure6.12displaystheactivity distribution at age 31 for a total of four different categories ofyoungpeople: thosewhohad completed anupper secondarydegree al‐readybyage21(youngcompleter); thosewhohadcompletedanuppersecondarydegreeeitherbyage26(latecompletersby26)orbyage31(latecompleterby31);andthosehavinganexamonlyfromcompulsoryschool still when aged 31 (adult non‐completer). Consequently, all fourdistributions displayed in Figure 6.12 covermerely the 1993 cohort, asthetwoyoungercohortscannotbetraceduptoage31.

The firstgraphofFigure6.12,displaying thesituationatage31 foryoungDanesdiffering in their completionandnon‐completionhistory,revealsseveralinterestingresults.First,thepatternofnoclear‐cutdis‐advantagefromcompletinganuppersecondarydegreeonlybyage26,insteadofage21,isrepeatedalsoforthe1993cohort.Second,comple‐tiononlybyage31seemstohavebeenanevenbetteroption,atleastintermsof labourmarketoutcomes.Third,adultnon‐completion,nowatage 31, results inmuch the same outcome as adult non‐completion atage 26: an “activity” share of about 74% and one‐fourth of adult non‐completers inNEET activities. Finally,when comparing the results foryoungcompletersandlatecompletersbyage26withthosedisplayedinFigure 6.11 for the 1998 cohort, the 1993 cohort seems to have faredslightlyworse in termsofunemployment,which is in linewith the re‐sults reported earlier in this chapter (when comparing the 1993 “eco‐nomic‐bust”cohorttothe1998“economic‐boom”cohort).Theconspic‐uouslygoodlabourmarketperformanceofyoungpeoplehavinggradu‐atedfromuppersecondaryeducationonlybyage31may,ineffect,alsobeanindicationoftheinfluenceofthesedeepeconomicrecessionyears(cf.thediscussionintheintroductorychapter).


0%10%20%30%40%50%60%70%80%90%

100%

Young completerby age 21

Late completerby age 26


Adult non‐completerby age 31

Denmark


0%10%20%30%40%50%60%70%80%90%

100%





Finland


Figure6.12:Mainactivitydistributions(%‐share)byage31ofyoungcompletersvs.youngnon‐completershavingcompletedanuppersecondarydegreebyage26(latecompletersby26)oronlybyage31(latecompletersby31),ornothav‐ingcompletedanuppersecondaryeducationbyage31(adultnon‐completers),basedoninformationonthe1993youthcohort,bycountry


0%10%20%30%40%50%60%70%80%90%

100%





Norway


0%10%20%30%40%50%60%70%80%90%

100%





Sweden


Notes: For definitions of the five main activity groups, see Chapter 2. Young completers = young

people having completed an upper secondary education already by age 21. Late completers by

26 = 21‐year‐old non‐completers having achieved an upper secondary degree by age 26 (but not

yet by age 21). Late completers by 31 = 21‐year‐old non‐completers having achieved an upper

secondary degree by age 31 (but not yet by age 26). Adult non‐completers = young people with

only a basic education.

ThesecondgraphofFigure6.12,showingthecorrespondingresultsforFinland, paints a slightly different picture, despite certain distinct fea‐tureswhichFinlandseemstosharewithDenmark.Inparticular,youngcompletersaremostsuccessfulwithrespecttolabourmarketoutcomes,followedbythosehavingcompletedanuppersecondarydegreeonlybyage 31. The lowest “activity” (education + employment) share is ob‐


tainedforthosehavinggraduatedbyage26which,again,maywellre‐flect the impactof theeconomic recession in theearly1990s.Anothersignoftheinfluenceoftheserecessionyearsisthehighersharesofun‐employedinthe1993thaninthe1998cohort.Adultnon‐completers,ontheotherhand,arealso inFinlanddistributedacrossmainactivities inmuch the sameway as adult non‐completers in the 1998 cohort: bothreachuptoan“activity”levelofonlysome65%.Theshareoftheunem‐ployedisinbothcohortsabout14%,whereasaboutone‐fifthhaswith‐drawnoutsidethelabourmarket.

ThepatternemergingforNorway,asdisplayedinthethirdgraphofFigure6.12,indicatesthatthetwogroupsoflatecompletersofanup‐persecondarydegreefare,byandlarge,equallywellintermsofcom‐binededucationandemployment shares,butworse thanyoung com‐pleters. There is, however, one major difference between the twogroups of late completers: a relatively larger share of unemployedamongthosehavinggraduatedbyage26andarelativelylargersharehavingwithdrawnfrombotheducationandthe labourmarketamongthose having graduated only by age 31. The weakest labour marketsituation isobserved foradultnon‐completers. Indeed, theirdistribu‐tion across main activities is very similar to that of adult non‐completersinthe1998cohortalsoinNorway.

ThelastgraphofFigure6.12exploresthesituationatage31amongyoungSwedesbelongingtothe1993cohort.Ofthefourgroupsofyoungpeoplediffering in theirgraduationhistory,only theyoungcompletersreach an “activity” share of almost 92% when aged 31. This share ismarginally lower than that of young completers in the 1998 cohort,mainlyduetoaslightlyhighershareofunemployed jobseekersamongyoungcompleters in the1993cohort.Theoutcome for theother threegroups of young people is notably weaker with an “activity” share ofabout70%,irrespectiveoflategraduationornograduation.Indeed,themaindifferencebetweenthe threegroupsof latecompletersandadultnon‐completers is not in their combined education and employmentsharebutratherinthecompositionoftheirNEETactivities:thosehav‐ing graduated by age 26 experience, when 31‐year‐old, more unem‐ployment but less disability, with the situation being the opposite forthose having graduated only by age 31 aswell as for those having nopost‐compulsory degree still at age 31. Perhaps most striking is thesteadyincreaseintheshareofdisabilitybeneficiariesandalsoofthosein other types of inactivitywhen going from young completers to latecompleterstoadultnon‐completers.


6.4.4 Mainfindings

This sub‐chapter has focused on exploring whether there are distinctdifferences in terms of labour market outcomes between young com‐pleters,latecompletersandadultnon‐completersofanuppersecondarydegree.Thiscomparisonwasmadeattwoagepoints:amongthoseaged26andamongthoseaged31.

Theresultsobtainedforyoungpeoplewhenaged26indicatethefol‐lowing.WecanidentifybasicallythreepatternscharacterisingthefourNordiccountriesunderstudy.InDenmark,earlyandlatecompletionofan upper secondary degree seems to make no difference in terms oflabourmarketoutcomes.Indeed,thedistributionsacrossmainactivitiesare almost identical for young completers and late completers, withmost of them either studying or working at age 26. Adult non‐completers,on theotherhand,are less likely to continue ineducation.They also face weaker employment possibilities and, consequently, ahigherriskofendingupinNEETactivities.

A second kind of pattern emerges for Finland andNorway. In bothcountries,youngcompletersfarebetterthanlatecompleters,albeitthedifference in labour market outcomes is more pronounced in FinlandthaninNorway.Conversely,thegaptoadultnon‐completersisbroaderin Norway than in Finland. Indeed, the labourmarket situation of 26‐year‐old non‐completers is strikingly similar for these two countries,withalmost40%ofthembeinginNEETactivities.

Sweden,finally,ischaracterisedbyathirdtypeofpattern.Inparticu‐lar,whileyoungcompletersfareextremelywellintermsoflabourmar‐ket outcomes, late completers lag far behind. A conspicuous finding isthat thereareonly small, if any,differences in thedistributionsacrossmain activities for late completers and adult non‐completers. In bothgroups, about 30% are in NEET activitieswhen aged 26. Hence, adultnon‐completersdonotseemtofareworsethanlatecompleters,intermsoflabourmarketoutcomes.Latecompletersseemtobethemajorlosergroupinthissetting.

Taken together, these highly different young‐completer/late‐completer/adult‐non‐completer patterns observed for Denmark, Fin‐land, Norway and Sweden imply that late completers and adult non‐completers encounter highly different labour market situations in thefour countries. Among late completers, Swedish late completers fareworst, whereas Danish late completers manage equally well as youngcompletersintermsoflabourmarketoutcomesbyage26.Therankingofcountrieschangesslightlywhencomparingthepositionofadultnon‐completers:Denmarkshowsupwiththehighest“activity”(education+


employment) share also among adult non‐completers, but now withSwedencomingsecond.Hence,whileadultnon‐completers throughoutfaremuchworsethanyoungcompletersintermsoflabourmarketout‐comes inadulthood it isnotobviousthat latecompletion isalwaysthesecond‐best option. In particular, late completion can definitively beseenasasecond‐bestoptioninFinlandandNorway,butnotnecessarilyin Denmark and Sweden, albeit for different reasons: in Denmark latecompleters fare equallywell as young completers,whereas in Swedenlatecompletersfarenobetterthanadultnon‐completers.

Whenextendingthisexercisewithfivemoreyears,uptoage31,thecross‐country pattern becomesmore dispersed. An additional circum‐stanceaffectingthepatternwithinaswellasbetweencountriesrelatesto theeconomicrecession intheearly1990s,as theresults for the31‐year‐olds concern the 1993 cohort only. This impact shows up in, forinstance, typically higher shares of unemployed among both early andlatecompletersinthe1993cohort,whencomparedtothe1998cohort.Thisfindingtherebyalsolendsfurthersupporttotheconclusiondrawnearlier in this chapter in relation to the impact of economic shocksonyoung completers and non‐completers; i.e., changing business cyclesseem to typically impact onyoungpeople inmuch the sameway irre‐spectiveoftheiruppersecondarygraduationbackground.

Butdespitethemoremixedpicturemediatedbytheresultsobtainedforthe1993cohort,therearealsodistinctcountry‐specificfeaturescom‐montotheresultsproducedforthe1993and1998cohorts,implyingthatmuchthesameoverallpatterncanbeidentifiedforbothcohorts.Inpar‐ticular, early and late completers tend to fare equallywell in Denmark,while late completers fareworse than young completers inFinlandandNorway,andmuchworseinSweden.Moreover,theageoflatecompletiondoesnot seem tomatter thatmuch: the “activity” (education+ employ‐ment)share isapproximatelythesameand,hence,alsotheNEETshare.However, there isconsiderablevariationinthecompositionof latecom‐pleters’NEETactivitiesdependingontheageofgraduation.

Theworstoutcome isobtained foradultnon‐completers,except forSweden in the sense that the labour market outcome of adult non‐completers is highly similar to that of late completers. Moreover, thedistributionacrossmainactivitiesofadultnon‐completersis,inallfourcountries, approximately the same in the 1993 cohort as in the 1998cohort. This indicates that the labour market situation of adult non‐completers looks more or less the same irrespective of cohort andchangingeconomicenvironments.

7. Labour market outcomes inview of background

Inthischapter,welookintothebackgroundofouryoungpeople,withaviewoftryingtoidentifyfactorsthatseemtobeespeciallystronglyre‐lated to the labourmarket outcomesobserved at threepoints in time:whentheseyoungpersonsturned21,26and31.Ourstatisticalanalysisisbasedontheuseofso‐calledmultinomiallogitmodelswhichshowtheprobabilityofbelongingtooneoutofseveralmutuallyexclusivegroups,given a particular set of background characteristics. In our case, thesegroupsaremadeupofthefivecategoriesofmainactivitiesusedintheprevious chapters: full‐time student, employed, unemployed, disabilitybeneficiary or outside all of these activities (“other”). The backgroundfactorsaccountedforinthesemultinomiallogitmodelsdividebasicallyinto twomain groups: one reflecting family background and the otherearly school‐to‐work‐transition patterns, that is, trajectories followedstraight after completion of compulsory education up to age 20. Addi‐tionally, we account for gender as well as cohort. Accounting also forcohort is relevant as we base our analysis on the pooled informationavailable for all three youth cohorts under scrutiny, i.e., those youngpeoplewhobecame16in1993,1998and2003,respectively.

Inthefollowing,wereportourresultsbybackgroundfactor,startingwithabriefnotionontheroleofgenderandcohort.Thereafterweturnto family background and, finally, to early school‐to‐work transitions.Eachsub‐chapterwillalso,whenrelevant,provideashortdescriptionofthebackgroundfactorinquestion.

7.1 Genderandlabourmarketoutcomes

Westartbycomparingtheaverageoutcomeforyoungmenandwomen.More precisely,we compare the overall probability of youngwomen tothatofyoungmenofbeingafull‐timestudent,employed,unemployed,ondisability benefits and in inactivity (“other”) when aged 21, 26 and 31.This information is gathered intoTable7.1 for all fourNordic countriesunderstudy.Itisworthnotingthatthereporteddifferencesintheproba‐


bilityofyoungwomen,whencomparedtoyoungmen,ofshowingup ineitheroneofthefivemainactivitycategoriesunderscrutinyreflectsthesituation after taking into account differences in familybackgroundandearlyschool‐to‐work‐transitionpatterns,inadditiontocohort.

Table 7.1: Young women’s probabilities in terms of labour market outcomes at age 21, 26 and 31, respectively, by country; differences in average probabilities when compared to young men

Labour market outcome Denmark Finland Norway Sweden

Full‐time student age 21 0.079 0.131 0.106 0.124

age 26 0.048 0.013 0.021 0.065

age 31 0.010 0.010 0.027 0.048

Employed age 21 ‐0.084 ‐0.124 ‐0.089 ‐0.107

age 26 ‐0.053 ‐0.053 ‐0.012 ‐0.055

age 31 ‐0.011 ‐0.054 ‐0.022 ‐0.050

Unemployed age 21 0 ‐0.029 ‐0.028 ‐0.021

age 26 0.006 ‐0.020 ‐0.014 0

age 31 0.005 ‐0.015 0 0.004

Disability beneficiary age 21 0 ‐0.001 0.003 0

age 26 0 ‐0.003 0.005 0.005

age 31 0 ‐0.003 0.006 0.013

Other (inactive) age 21 0.008 0.023 0.007 0.004

age 26 0 0.063 0 ‐0.011

age 31 0 0.062 ‐0.009 ‐0.014

Notes: The reported average probabilities are obtained after also accounting for cohort, family

background and early school‐to‐work‐transition patterns. A negative sign implies a weaker probabil‐

ity of young women than of young men of showing up in the labour market situation in question.

Low (high) absolute values indicate a small (large) difference in this respect to young men. All re‐

ported probabilities are significant at the 99% level or more. Statistically insignificant and only

weakly significant probabilities are set at zero. The probabilities are calculated from pooled infor‐

mation on the three youth cohorts under scrutiny. For definitions of the five main activity catego‐

ries, see Chapter 2.

Table 7.1 indicates the following. In all four countries, young womenhave a significantly higher probability of being in full‐time education,when compared to their male peers. All four countries also share thefeatureofanotablenarrowinginthisgendergapwhenmovingtowardsage31,withmostof this change typicallyoccurringbeforeage26, ex‐ceptinDenmark.ThehighestprobabilitygapshowsupforFinlandwith21‐year‐old women having a 13% higher probability than their malepeers of being enrolled in full‐time education. This probability is onlyslightly lower (12.4%) for Sweden, but comparatively low (about 8%)forDenmark.However,whilethisfull‐time‐studyprobabilityinfavourofyoungwomen remains comparatively high in Sweden up to age 31, itnarrowsremarkablyinFinlandand,ineffect,downtothesamelowlevel(1%)asinDenmark.

Conversely, young men have throughout, at all three age points, aclearlyhigherprobabilityofbeinginworkinglife.However,againweseeadecliningtrendwithage intheprobabilitygapbetweenthetwogen‐


ders: a smoothlynarrowinggap inDenmark,butamorestep‐wisede‐clineintheotherthreecountriesinthesensethatmostofalsothisnar‐rowing seems to take place before the age of 26. In view of the highprobability gap obtained for full‐time studying 21‐year‐old Finns, it ishardly surprising that Finland comes outwith the highest gender gapalso in theprobability of 21‐year‐olds being in employment (12.4% infavourofmen), again closely followedby Sweden (close to11% in fa‐vour ofmen). In Denmark and Norway, the corresponding gap is justbelow9%.However,thishigherprobabilityofyoungmenbeinginwork‐ing life has, in all countries, shrunk to about 5%alreadyby age26, inNorwaytoonlyabout1%.

Thedifferencebetweenyoungmenandyoungwomenintheaverageprobabilityofshowingupin(registered)unemploymentissmallornon‐existentatallthreeagepointsinvestigated.Moreover,thisholdstrueforall fourcountries.Eventhelargestdifferencesfallbelow3%(tothefa‐vour of women) and are observed only at the age of 21 and only forthreeoutofthefourcountriesunderstudy.

Alsothedifferencesinaveragegenderprobabilitiesofbeingindisa‐bilityarrangementsaremoreor lessnegligible inall fourcountries. InDenmark, there exist principally no differences between young men’sand young women’s probabilities of being on disability benefits. Thispatternisrepeatedatallthreeagepoints.InFinland,youngwomenhavea marginally lower probability in this respect, and the difference toyoungmenremainsapproximatelyunchangeduptoage31.InNorway,the situation is reversed. Additionally, young women tend to face aweaklyincreasingprobability,whencomparedtoyoungmen,ofendingupasdisabilitybeneficiaries.Thispatternandtrend isevenmorepro‐nouncedforyoungwomeninSweden.

When it comes to the probability of youngmen and youngwomenmovingintoothertypesofinactivity,thedifferencesinprobabilitiesare,again, small or negligible. The only exception is Finland where youngwomenhaveacomparativelyhighprobabilityofwithdrawingfrombotheducation and the labour force, when compared to their male peers.Moreover,thisdifferenceininactivityprobabilitiesismuchhigheratage26, andalsoat age31, thanat age21.Also the results for Swedenareworthcommentingoninthesensethatwhileyoungwomentendtofaceanincreasinglyhigherprobabilityofgoingintodisabilityarrangementswhenapproachingage31,youngmentendinsteadtoincreasinglywith‐drawintoothertypesofinactivity.


7.1.1 Mainfindings

Thelargestdifferencesinyoungmen’sandyoungwomen’saverageprob‐abilitiesofshowingupinalternativelabourmarketsituationswhenaged21,26and31,respectively,relatetofull‐timeeducationandemployment.Inparticular, youngwomen face amuchhigherprobabilityof being en‐rolledinfull‐timeeducation,whereasyoungmenaremuchmorelikelytoenterworkinglife.Whilethesedifferencesineducationandemploymentprobabilitiesprevailacrossallthreeagepointsinvestigated,theydiminishsubstantiallywithageespeciallyuptoage26,withmoreminorchangesoccurringbeyondage26,uptoage31.Thisoverallpatternisdiscerniblein all four countries, implying that there is a notable convergence overtimenotonlyacrossgendersbutalsoacrosscountries.

WhenitcomestoNEETactivities,thedifferencesingenderprobabili‐tiesarenotablysmaller.Alsothispatternemergesforallfourcountries.For Denmark, the differences in gender probabilities are consistentlyminorornon‐existent,suggestingthatyoungmenandyoungwomeninDenmarkareonaverageequallylikelytobecomeunemployed,togoondisability benefits and towithdraw into other types of inactivity. Thisholds,byand large, truealso forNorway,exceptwhen it comes toun‐employment. In this respect,youngmen faceaclearlyhigherrisk thanyoungwomen, although the difference is small and vanisheswith age.Finland stands out with a persistently, albeit only marginally, higherprobabilityofyoungmenbecomingunemployedorofmovingintodisa‐bility arrangements, whereas young women have a strikingly higherprobabilityofwithdrawing intoother typesof inactivity,especiallybe‐yondage21.AreversedpatternappearsforSwedenwithyoungwomenbeingonaveragemorelikelytogoondisabilitybenefitsandyoungmeninto other (unknown) types of inactivity.While these country‐specificpatterns were pointed out already in the previous chapter, they thusseem to be retained also after control for differences in cohort, familybackgroundandearlyschoolandlabourmarketexperiences.


7.2 Cohortandlabourmarketoutcomes

Next,welookbrieflyatdifferencesintheaverageprobabilityforthethreeyouthcohortsunderstudyofbeinginthesesamefivealternativelabourmarketsituationsatage21and26afteralsocontrollingforgender,familybackground and early school‐to‐work‐transition patterns. At age 21,wecanmakecomparisonsacrossall threecohortsaswehaveobservationsforallofthemfiveyearsaftercompletionofcompulsoryschool.Atage26,thiscomparisonboilsdowntotwocohorts(the1993and1998cohortsof16‐year‐olds)forwhichwehaveobservationsuptotenyearsaftercom‐pletionofcompulsoryeducation.Forage31,nocorrespondingcompari‐sonscanbemadeas the informationat thisparticularageconcerns theoldestcohortonly,i.e.the1993cohortof16‐year‐olds.

Again, thedifferences inaverageprobabilitiesreportedhere(inTa‐bles7.2and7.3)are thoseobtainedafteraccounting for the full setofbackgroundfactors.However,incontrasttothesituationforgender,wesee considerable variation in the relation between cohort and labourmarket outcomes depending on whether or not we leave out infor‐mationoneitherfamilybackgroundorearlyschool‐to‐worktransitions.Thisobservationpointstoachangingroleofthesetwobackgroundfac‐torsacrosscohorts.Thislendsfurthersupporttoincludingbothsetsofbackground factors when analysing data containing information onmorethanonecohortandwhen,furthermore,tryingtoexplorewhethertherearedistinctdifferencesbetweencohortsinlabourmarketoutcomeprobabilitiesinadulthood.

7.2.1 Differencesinaveragelabourmarketoutcomeprobabilitiesatage21

FromTable7.2itisevidentthattheaverageprobabilityofbeingineitheroneofthefivealternativelabourmarketsituationswhenaged21revealsremarkable variation across cohortswithin countries, aswell aswithincohorts across countries. The probability of being a full‐time student atage 21 has increased across cohorts in Denmark, stayed unchanged inNorway,and followedaconcave‐type trend inFinlandandSweden.TheDanish result is well in linewith previous observations ofmore youngDanescontinuing ineducationand increasinglyalsodelaying theircom‐pletion of an upper secondary degree (cf. Chapter 2). The Finnish andSwedishresults,inturn,arelikelytoreflectthegrowingtendencyacrosscohortsofyoungpeopledelayingtheirstartinhighereducation.


Table 7.2: 1998 and 2003 cohort probabilities in terms of labour market outcomes at age 21, by country; differences in average probabilities when compared to the 1993 cohort


Full‐time student

cohort 1998 0.030 0.019 0 0.020

cohort 2003 0.066 ‐0.019 0 ‐0.037

Employed

cohort 1998 ‐0.040 0 0 ‐0.012

cohort 2003 ‐0.053 0.059 0.011 0.041

Unemployed

cohort 1998 0.009 ‐0.019 0.034 ‐0.028

cohort 2003 ‐0.033 ‐0.036 0.013 ‐0.051

Disability beneficiary

cohort 1998 ‐0.002 ‐0.002 0 0.003

cohort 2003 ‐0.002 0 0 0.012

Other (inactive)

cohort 1998 0 0 ‐0.038 0.016

cohort 2003 0.022 ‐0.005 ‐0.021 0.034

Notes: The reported average probabilities are obtained after also accounting for gender, family

background and early school‐to‐work‐transition patterns. A negative sign implies a weaker probabil‐

ity of the cohort’s young people of showing up in the labour market situation in question compared

to young people from the 1993 cohort. Low (high) absolute values indicate a small (large) difference

in this respect to the 1993 cohort. All reported probabilities are significant at the 99% level or more.

Insignificant and only weakly significant probabilities are set to zero. The probabilities are calculated

from pooled information on the three youth cohorts under study. For definitions of the five main

activity groups, see Chapter 2.

Theaverageprobabilityof21‐year‐oldsofbeinginworkinglifeismoreorlessthesameforcohorts1993and1998,butsignificantlyhigherforthe2003cohort,notably inFinlandandSweden.ForDenmark,ontheotherhand,weseeasteadydeclineacrosscohortsintheprobabilityof21‐year‐oldsbeing in employment.These findings are the logical counterpart tothecountry‐specifictrendsinstudyingprobabilitiesdiscussedabove.

Inallcountries,exceptNorway,theaverageprobabilityofbeingreg‐isteredasanunemployedjobseekerwhenaged21isclearlylowerintheyoungest (2003) cohort than in the oldest (1993) cohort. For Finlandand Sweden, this holds true also for the 1998 cohort. These differentfindings for the fourNordic countries,despite the fact that all of themexperienced a deep economic recession in the early 1990s,may seemrather surprising. However, the interpretation of these differences inaverage unemployment probabilities across the three cohorts is notnecessarily straightforward, for several reasons. First, unemploymentrefers to registered unemployment and, as pointed out earlier, youngpeoplenoteligibleforunemploymentbenefitsmightchoosenottosignon.Thisbehaviourmaywellhavebecomemorecommonwithtightenedconditions, especially for young people, for receiving unemploymentbenefits. Second, youth unemployment policies have increased both in


volumeandinintensityoverthepastdecadeorso,butinquitedifferentwaysinthefourNordiccountries.

Alsowhenitcomestodisabilitybenefitsandothertypesofinactivity,the cross‐country picture appears quitemixed. In all countries, exceptSweden,weseeminorcross‐cohortdifferencesinyoungpeople’sprob‐abilityofbeingondisabilitybenefitsalreadyatage21.ForSweden,weobserve instead a weakly increasing probability across cohorts of 21‐year‐olds showing up in disability arrangements. A similar trend is, infact,observableforSwedenalsowhenitcomestoothertypesofinactivi‐ty.Also forDenmark, theaverageprobabilityofwithdrawal frombotheducation and the labour forcewhen aged 21 is slightly higher in the2003 cohort than in the older cohorts, whereas the opposite trend isdiscernibleforFinlandandNorway.

7.2.2 Differencesinaveragelabourmarketoutcomeprobabilitiesatage26

Inthenexttable,weexpandthispictureforthe21‐year‐oldswithcorre‐spondingresultsfiveyearslater,atage26.Asnotedabove,thecompari‐son across cohorts at this age is, due to data limitations, restricted toonly two cohorts (cohorts 1993 and 1998). In order to facilitate ourcomparisonofprobabilitiesatage21andage26,Table7.3reproducestheprobabilitiesofthe1998cohortatage21,asreportedinTable7.2.Thisallowsustoeasilycomparethesituationofthe1993cohorttothatofthe1998cohortattwospecificagepoints.

Table 7.3: 1998 cohort probabilities in terms of labour market outcomes at age 21 and 26, respec‐tively, by country; differences in average probabilities when compared to the 1993 cohort


Full‐time student

cohort 1998, age 21 0.030 0.019 0 0.020

cohort 1998, age 26 0.028 0 ‐0.037 ‐0.015

Employed

cohort 1998, age 21 ‐0.040 0 0 ‐0.012

cohort 1998, age 26 0.008 0.031 0.015 0.021

Unemployed

cohort 1998, age 21 0.009 ‐0.019 0.034 ‐0.028

cohort 1998, age 26 ‐0.051 ‐0.020 ‐0.013 ‐0.028


cohort 1998, age 21 ‐0.002 ‐0.002 0 0.003

cohort 1998, age 26 0 0 0.003 0.006

Other (inactive)

cohort 1998, age 21 0 0 ‐0.038 0.016

cohort 1998, age 26 0.015 ‐0.009 0.031 0.016

Notes: See Table 7.2 above.


Theoverall impressionmediatedbyTable7.3 is that there isnoclear‐cut cross‐country pattern discernible in the labour market outcomeprobabilitiesofthetwocohortswhenmovingfromage21toage26.InNorwayandSweden,26‐year‐olds fromthe1998cohortare less likelyto be in education thanwere 26‐year‐olds from the 1993 cohort. Thiscouldbearguedtobeaconsequenceofthedeepeconomicrecessionintheearly1990sspurringyoungpeopletostaylongerineducationduetosluggish employment opportunities. However, this same pattern doesnot emerge forFinland,where theyoungpeople from the twocohortsareinsteadequallylikelytobefull‐timestudentsstillatage26,norforDenmark,wherethehigherprobabilityofthe1998cohortofbeingen‐gagedineducationisofthesamemagnitudeatage26asfiveyearsear‐lier,atage21.

The different economic situations faced by young people from thetwocohortsuponlabourmarketentranceseemtoplayamoredistinctrolewhenitcomestoemploymentprobabilities.AsshowninTable7.3,the average employment probability at age 26 is in all four countriesclearlyhigherforthe1998cohortthanforthe1993cohort,moresoinFinlandandSweden than inDenmarkandNorway.Concomitantly, the1998 cohort’s unemployment risk at this particular age is in all fourcountrieslowerthanforthe1993cohort,especiallyinDenmark.InFin‐landandSweden,thedifferenceinunemploymentprobabilitiesbetweenthetwocohortsis,ineffect,thesameatage26asitwasatage21.

Concerning disability benefits, the differences in probabilities be‐tweenthetwocohortsareminor.Yet,thetrendisincreasingratherthandecreasing.Inparticular,inbothDenmarkandFinland,the1998cohortstartedout,atage21, froma lowerprobability levelthancohort1993,butthisgapwasclosedbyage26.Intheothertwocountries,theproba‐bility of going on disability benefits already at age 21 was the same(Norway)ormarginallyhigher (Sweden),whencompared to the1993cohort.Byage26, thisriskhadincreasedmorerapidly inthe1998co‐hort,albeititwasstillonlymarginallyhigherthanforthe1993cohort.

Finally,with respect toother typesof inactivity cohort1998comesoutwithanotablyhigherriskofbeingoutsidebotheducationand thelabourforceatage26.InNorway,thereisaremarkablechangebetweenage 21 (an almost 4%higher risk for cohort 1993) and age 26 (a 3%lowerriskforcohort1993).InSweden,thishigherriskforcohort1998wasobservablealreadyatage21.Only inFinlandisthis inactivityrisklower at age 26 in the 1998 cohort than in the 1993 cohort, but onlymarginallyso.


7.2.3 Mainfindings

The labourmarket outcome probabilities of young people belonging todifferent cohorts reveal considerable variation both within and acrosscountries, showing no clear‐cut overall patternswhatsoever. A first ob‐servation is that the differences in probabilities between cohorts arethroughoutquitesmallinsize,implyingthattheprobabilityofyoungpeo‐pleendingupindifferentlabourmarketsituationshasnotchangedthatmuchacrosscohortsafteralsocontrolling forcohort‐specificdifferencesinfamilybackgroundandearlyschool‐to‐worktransitions.Asecondob‐servation is that there is typically no clear pattern of changing (or un‐changing)probabilitiesacrosscohortswhengoingfromage21toage26.

Acomparisonacrossthethreecohortsofthelabourmarketoutcomeprobabilitiesofyoungpeoplewhenaged21impliesthattheprobabilityofbeinga full‐timestudentwas lowerforthe2003cohortthanforthe1998 and 1993 cohorts in both Finland and Sweden, obviously due tobreak years having become increasingly common before continuing inhighereducation.Thiscontention issupportedbyworkingbeingmuchmorelikelyamong21‐year‐oldsinthe2003cohortthaninthetwooldercohorts.ForDenmark,thefindingsarerathertheoppositewithincreas‐ingprobabilities across cohorts of being engaged in education andde‐creasingprobabilitiesofbeing in employmentwhenaged21.ForNor‐way, on the other hand, there areminor, if any, differences in cohortprobabilitieswhenitcomestostudyingandworking.

InrelationtovariousNEETactivitiesamong21‐year‐olds,themixofcross‐cohortpatternswithinandbetweencountriesismuchlargerthanfor education and employment probabilities, which is only to be ex‐pectedinviewoftheresultspresentedinpreviouschapters.Themostlyvery smallornon‐existentdifferences inNEETprobabilitiesacross co‐hortsconfirm, inturn, the impressionofstrikinglystableprevalenceofNEETactivitiesamongyoungpeople.Inparticular,theriskofbeingout‐sidebotheducationandthelabourmarket–indisabilityarrangementsorothertypesofinactivity–whenaged21revealsanincreasingratherthan decreasing trend across cohorts. This holds true especially forSweden,butalso forDenmark.Onlywith respect tounemploymentdowe see a clearly lower risk among21‐year‐olds from the2003 cohort,thoughagainwithNorwaybeinganexceptiontothispattern.

A comparison of labour market outcome probabilities at age 26 –nowbasedononlytwocohorts–inducesbasicallythreemainobserva‐tions. First, the probability of being employed at age 26 is in all fourcountries notably higher in the 1998 cohort than in the 1993 cohort.Second, the riskofbeingunemployed is clearly lower.Taken together,


thesetwoobservationsarelikelytomirrortheimpactofthedeepeco‐nomic recession in the early 1990s on young labourmarket entrants.Third,thedifferencesbetweenthetwocohortsintheriskofbeingout‐sidebotheducationandthe labour forceatage26aremostlysmallorminorand,ineffect,verysimilartothoseobservedamongthe21‐year‐olds.Thispointstoratherstableinactivitypatternsacrosscohortsalsoinadulthood.Indeed,alsoatage26theriskofendingupininactivityhasbeenincreasingratherthandecreasingacrosscohort,atendencywhichnowshowsupforallcountriesexceptFinland.

7.3 Familybackgroundandlabourmarketoutcomes

Intergenerational transmission from parents to children has for longbeenanimportantacademicaswellaspolitical issue.Specialattentionhas thereby been paid to the parents’ educational and income levels.Indeed,asshownbye.g.Björklundetal.(2010)andBlackandDevereux(2011)intheircomprehensivereviews,thereisahugebodyofliteratureprovidingsupportforthecontentionthatschoolsuccessand,ultimately,labourmarketoutcomesare closely related to familybackground. It istherefore of interest to include also in this contextmeasures approxi‐matingthefamilybackgroundsituationoftheyoungpeoplebelongingtothethreecohortsinvestigated.

Wemeasure family background by use of a small set of traditionalfamilybackgroundmeasurescommontoallfourNordiccountriesunderstudy.Moreprecisely,we askwhether there is a clear‐cut relationbe‐tween the family situation asmeasured by education and income andthe child’s probability of being a full‐time student, employed, unem‐ployed,disabilitybeneficiaryorinactive(“other”)atage21,26and31,respectively. The parents’ formal educational level is measured bymeansof threecategories:basic, secondaryandhighereducation.Alsothe (gross) income level of parents is split into three categories: low,middle and high wage‐income. While the information on educationallevelisgivenseparatelyforthemotherandthefather,thewage‐incomereferstothehousehold‐level income, i.e. thesumoftheparents’wage‐income.Theparents’educationand incomeconcerntheyearwhenthechildturned16,exceptforFinlandastheFinnishdatacontainsparentaleducationinformationfortheyear2010only.

Whilethisfamilybackgroundinformation(mother’sandfather’sed‐ucation, parentalwage‐income level) is added jointly to our statisticalmodel, we split the presentation of results, starting with the relation


between themother’s educational level and the child’s labourmarketoutcomesat laterages.Apart from familybackground information, themodel also accounts for gender and cohort aswell as early school‐to‐worktransitions.

7.3.1 Theroleofthemother’seducationallevel

Table7.4reportstheextenttowhichtheeducationallevelofthemotherislinked to thechild’s later labourmarketoutcomes. Inparticular, itgivesthedifferencesinprobabilitiesforthechildbeingineitheroneofthefivealternative labourmarket situations at age 21, 26 and 31, respectively,depending on the educational level completed by themotherwhen thechildturned16.Thesedifferencesinprobabilitiesarereportedformoth‐erswithanuppersecondaryorahighereducation.Inotherwords,moth‐erswithnopost‐compulsorydegreeactasthereferencegroup.

Table 7.4: Probabilities in terms of labour market outcomes at age 21, 26 and 31, respectively, of children with a higher educated mother, by country; differences in probabilities when compared to children with a mother lacking a post‐compulsory education

Mother’s highest educational level: secondary‐ or tertiary‐level degree


Labour market outcome sec. ed. tert. ed. sec. ed. tert. ed. sec. ed. tert. ed. sec. ed. tert. ed.

Full‐time student

at age 21 0.039 0.065 0.047 0.156 0.064 0.152 0.045 0.175

at age 26 0.035 0.148 0.023 0.098 0.040 0.130 0.028 0.118

at age 31 0 0.048 0 0.047 0 0.031 0 0.029

Employed

at age 21 ‐0.027 ‐0.063 ‐0.035 ‐0.114 ‐0.041 ‐0.122 ‐0.019 ‐0.136

at age 26 ‐0.023 ‐0.142 ‐0.011 ‐0.065 ‐0.026 ‐0.114 ‐0.012 ‐0.101

at age 31 0 ‐0.049 0 ‐0.038 0 ‐0.026 0.008 ‐0.014

Unemployed

at age 21 ‐0.008 ‐0.011 ‐0.007 ‐0.033 ‐0.011 ‐0.021 ‐0.018 ‐0.038

at age 26 ‐0.005 ‐0.007 ‐0.006 ‐0.020 ‐0.011 ‐0.017 ‐0.011 ‐0.019

at age 31 0 0 0 ‐0.010 ‐0.007 ‐0.012 ‐0.006 ‐0.011


at age 21 0 0 0 0 0 0 ‐ 0.004 ‐0.007

at age 26 0 0 0 0 0 0 ‐0.003 ‐0.006

at age 31 0 0 0 0 0 0 0 ‐0.009

Other (inactive)

at age 21 ‐0.005 0.009 ‐0.005 ‐0.009 ‐0.011 ‐0.010 ‐0.004 0.006

at age 26 ‐0.007 0 ‐0.005 ‐0.011 0 0 0 0.009

at age 31 0 0 0 0 0 0 0 0

Notes: The three educational‐level categories correspond to ISCED 1–2, 3–4 and 5–6, respectively,

with ISCED 1–2 (no post‐compulsory educational degree) being used as the category of reference.

The Norwegian results also include a category for missing educational information which is not

reported here, though. For other notes, see Table 7.2 above.


Table 7.4 presents results concerning the child’s probability of beingengagedineducationlaterinlifethatarewellinlinewiththeempiri‐cal evidence reported in the international literature. In particular,there is a strong linkbetween the child’sprobabilityof continuing ineducationandthemother’seducationallevel.Thisrelationstrengthensatallthreeagepointswiththelevelofthemother’scompleteddegree:comparedtomotherswithnopost‐compulsorydegree,thislinkisno‐tably stronger for mothers with an upper secondary degree andstrongest for high‐educatedmothers.However, the table also revealsthattheroleofthemother’seducationalbackgroundweakenswiththechildgrowingolder:formotherswithanuppersecondarydegree,thelink is broken by age 31while it has turned quiteweak formotherswithatertiary‐leveldegree.Thisoverallpatternisrepeatedforallfourcountries, butwith the strengthof the relationvaryinga lotbetweenthe countries. The cross‐country situation is most similar at age 31,whichagainpointstoconsiderableconvergencewithageintheeduca‐tionalbehaviourofNordicyouth.

Notsurprisingly,thecounterparttothiseducationalpatternisemploy‐mentprobabilitiesof thechild thatarenegatively related to themother’seducational background. In other words, for the probability of the childbeinginemployment– insteadofcontinuingineducation–weobserveareversedpattern:thechild’sprobabilityofhavingenteredworking lifeal‐readybyage21declinesnotablywiththeeducationallevelofthemother,implying that it is highest for children with a mother lacking a post‐compulsory degree. Again, this same pattern is repeated for each of thethreeagepoints investigated,butwith the link to themother’seducationweakening also in the case of employment probabilities when the childgrowsolder.Andagain,thesamepatternemergesforallfourcountries.

Thechild’s riskofendingup inNEETactivities–unemploymentorinactivity, including disability benefits – is, on average, much moreweakly related to the mother’s educational background than is thechild’sprobabilityofstudyingorworking.Thereis,inallfourcountries,anegativebutquiteweak linkbetweenthechild’sriskofexperiencingunemploymentandthemother’seducationalbackground,withthisrela‐tionshipweakeningfurtherwhenthechildgrowsolder.Whenitcomestothechild’sprobabilityofbecomingadisabilitybeneficiary,themoth‐er’seducationalbackgroundplaysnosignificantrole,exceptinSwedenwhere the link seems to exist but in an extremelyweakmode.Also inrelation to thechild’s riskofendingup inother typesof inactivity, thelink to themother’s educational background isminor or non‐existent.Again,thesameoverallpatternshowsupinallfourcountries.


7.3.2 Theroleofthefather’seducationallevel

Next,we turn to the corresponding results for the father’shighest com‐pletededucation.TherelevantprobabilitiesarepresentedinTable7.5.Byand large, the picture looksmuch the same, suggesting that the child’slabourmarketoutcomes later in lifearerelated to themother’sand thefather’s educational background in a highly similarway.Moreover, thisholdstrueforboththesignandthestrengthoftheserelations.Forallfourcountries,weobservestudyingprobabilitiesofthechildthatarepositive‐lyrelatedandworkingprobabilitiesthatarenegativelyrelatedtothefa‐ther’s educational background. This link strengthensmarkedlywith theeducationaldegreecompletedbythefather.Moreover,whilethispatternis repeatedwhen the child turns21, 26 and31, also the relation to thefather’s educational background tends toweaken considerablywith thechildgrowingolder.Likewise, theriskofthechildofendingupinNEETactivitiesisonlyweakly,ifatall,relatedtothefather’seducation.

Table 7.5: Probabilities in terms of labour market outcomes at age 21, 26 and 31, respectively, of children with a higher educated father, by country; differences in probabilities when compared to children with a father lacking a post‐compulsory education

Father’s highest educational level: secondary‐ or tertiary‐level degree


Labour market outcome sec. ed. tert. ed. sec. ed. tert. ed. sec. ed. tert. ed. sec. ed. tert. ed.

Full‐time student

at age 21 0.032 0.098 0.035 0.156 0.059 0.163 0.033 0.180

at age 26 0.018 0.136 0.019 0.103 0.037 0.129 0.022 0.100

at age 31 0 0.031 0 0.037 0.016 0.034 0 0.027

Employed

at age 21 ‐0.025 ‐0.101 ‐0.028 ‐0.116 ‐0.044 ‐0.141 ‐0.023 ‐0.162

at age 26 0 ‐0.140 ‐0.016 ‐0.087 ‐0.024 ‐0.122 ‐0.011 ‐0.098

at age 31 0 ‐0.034 0 ‐0.027 0 ‐0.035 0.009 ‐0.022

Unemployed

at age 21 ‐0.005 ‐0.011 0 ‐0.034 ‐0.009 ‐0.014 ‐0.005 ‐0.022

at age 26 ‐0.007 0 0 ‐0.015 ‐0.006 ‐0.010 ‐0.006 ‐0.009

at age 31 0 0 0 ‐0.010 0 0 ‐0.005 0


at age 21 0 0 0 0 0 0 ‐0.002 ‐0.003

at age 26 0 0 0 0 0 0 ‐0.003 0

at age 31 0 0 0 0 0 0 ‐0.004 0

Other (inactive)

at age 21 0 0.012 ‐0.005 ‐0.008 0 ‐0.008 ‐0.004 0.007

at age 26 0 0 0 0 0 0 0 0.009

at age 31 0 0 0 0 0 0 0 0

Notes: See Table 7.4 above.


7.3.3 Theroleoftheparents’wage‐incomelevel

The thirdand final family‐relatedbackground factor concerns thepar‐ents’totalwageincome.Theprobabilitiesofyoungpeopleofshowingupinalternativelabourmarketactivitiesatage21,26and31,respectively,givenobserveddifferencesinparents’wage‐incomelevelsaredisplayedinTable7.6.Otherbackgroundfactorsaccountedforinthiscontextare,in linewith the overall settingused,mother’s and father’s educationallevels,aswellastheyoungperson’sgender,cohortandearlyschool‐to‐work‐transitionexperiences.

Table 7.6: Probabilities in terms of labour market outcomes at age 21, 26 and 31, respectively, of children with higher wage‐income parents, by country; differences in probabilities when com‐pared to children with parents located in the lowest tertile (one‐third) of the wage‐income scale

Parents’ wage‐income level: 2nd tertile or 3rd tertile


Labour market outcome 2nd

tertile

3rd

tertile

2nd

tertile

3rd

tertile

2nd

tertile

3rd

tertile

2nd

tertile

3rd

tertile

Full‐time student

at age 21 0.016 0.067 0.027 0.074 0.021 0.058 ‐0.011 0.035

at age 26 0 0.038 0 0.046 0 0.027 ‐0.011 0.012

at age 31 0 0 0 0.014 0 0 ‐0.010 ‐0.013

Employed

at age 21 0.009 ‐0.030 0 0 0.011 ‐0.013 0.074 0.060

at age 26 0.024 0 0.030 0 0.026 0 0.067 0.063

at age 31 0.023 0.029 0.026 0.034 0.033 0.023 0.063 0.080

Unemployed

at age 21 ‐0.009 ‐0.021 ‐0.021 ‐0.047 ‐0.012 ‐0.023 ‐0.038 ‐0.066

at age 26 ‐0.013 ‐0.019 ‐0.017 ‐0.035 ‐0.012 ‐0.013 ‐0.027 ‐0.039

at age 31 0 ‐0.009 ‐0.016 ‐0.030 ‐0.008 0 ‐0.019 ‐0.026


at age 21 0 0 0 0 ‐0.004 ‐0.005 ‐0.006 ‐0.012

at age 26 0 0 ‐0.002 ‐0.004 ‐0.005 ‐0.006 ‐0.009 ‐0.016

at age 31 0 ‐0.007 ‐0.004 ‐0.006 0 0 ‐0.016 ‐0.023

Other (inactive)

at age 21 ‐0.016 ‐0.016 ‐0.015 ‐0.018 ‐0.016 ‐0.017 ‐0.018 ‐0.018

at age 26 ‐0.012 ‐0.012 ‐0.015 ‐0.019 ‐0.013 ‐0.009 ‐0.020 ‐0.021

at age 31 ‐0.009 0 ‐0.007 ‐0.011 ‐0.019 0 ‐0.018 0.018

Notes: The three wage‐income categories of parents refer, respectively, to the lowest, middle and

highest one‐third of the wage‐income scale. For other notes, see Table 7.2 above.

AfirstobservationbasedonTable7.6isthatparents’wage‐incomelevelis to a varying degree related to the child’s probability of later in lifebeingeitherstudying,working,inunemployment,ondisabilitybenefitsorinothertypesofinactivity,evenafteraccountingfortheparents’edu‐cationalbackground.Thismeansthatthewage‐incomelevelofparentsplaysanindependentroleforthechild’slaterlabourmarketoutcomes;it doesnotmerely act as aproxy forparents’ educational background.


And vice versa, parents’ educational background is not necessarily asufficientproxyfortheirlabourmarketincomestatus.Hence,thesetwofamily background factors are correlated, but no perfect correlates.Moreover, these two family background indicators are, in this context,occasionally oppositely related to the child’s later labour market out‐comes,asdiscussedbelow.

Children with higher wage‐income parents are, on average, morelikely to be enrolled in full‐time educationwhen aged 21, when com‐paredtochildrenwithlowwage‐incomeparents.Moreover,thispositiverelationstrengthenswiththewage‐incomelevelofparentsand,hence,isstrongestforparentsbelongingtothehighestone‐thirdofthewage‐incomescale.However,thisrelationbetweenthechild’slaterprobabilityofbeingengagedinfull‐timestudiesandtheparents’wage‐incomelevelweakensrapidlywhenthechildgrowsolder:forparentslocatedinthemiddlepartofthewage‐incomescaleithasdisappearedbeforethechildturns 26 and for parents in the highest one‐third of thewage‐incomescaleithasturnedverysmallorinsignificantbythetimethechildturns31. OnlyforSwedendoesthispatternlookdifferent.Inparticular,chil‐dren of parents located in the middle part of the wage‐income scaleshowupwiththelowestprobabilityofbeingengagedinfull‐timestud‐iesatallthreeagepointsinvestigated.Forhigh‐incomeparents,inturn,thelinktothechild’sprobabilityofstudyingonafull‐timebasislaterinlifehas,byage31,turnedfrompositivetonegative.Hence,theprobabil‐ityofstudyingwhenaged31tendstobehighestforchildrenwithlow‐incomeparents.On thewhole, though, thisdivergingpatternobservedforSwedenbuildsonverysmalldifferencesinthechild’sstudyingprob‐abilityacrossthethreeparentalwage‐incomelevels.

Theprobabilityofthechildofbeinginemploymentwhenaged21,26and31isonlyweaklyrelatedtotheparents’wage‐incomelevel.Moreo‐ver,thisrelationistypicallypositiveandincreasingwiththechild’sage(i.e.strongeratage31thanatage21),whichisoppositetotherelationobserved for the mother’s and the father’s educational background.Thesedifferenttypesofrelationsarelogical,though:whiletheparents’educationalbackgroundislikelytomirrorthechild’sprobabilityofsub‐stitutingworkwith studies, theirwage‐income level rather tells aboutthechild’s lateremploymentprospects.Alsowithrespect to thechild’slater employment probabilitywe observe the same overall pattern forDenmark, FinlandandNorway.Again, thepattern is different for Swe‐den:arelativelystrong,albeitstillpositive,relationbetweenthechild’sprobabilityofbeingemployedlaterinlifeandtheparents’wage‐incomelevel. However, this difference appears mainly with respect to low‐


incomeparents,whereas thedifference in the children’s later employ‐ment prospects isminoror negligiblewhen comparingmiddle‐incomeparentstohigh‐incomeparents.

Children with low‐income parents tend to have the highest risk ofexperiencingunemploymentlaterinlife.Thisriskdeclineswiththepar‐ents’ wage‐income level and, hence, is lowest for children with high‐incomeparents.However, the linkbetweenthechild’s likelihoodofex‐periencing unemployment in adulthood and the parents’wage‐incomelevelturnsincreasinglyweakerwhenthechildgrowsolder.It isworthnoting, though, that thisnegativerelationremainsquitestrong inbothFinlandandSweden:childrenwithmiddle‐incomeparentshavestillbyage31analmosttwopercentandchildrenwithhigh‐incomeparentsanalmost three per cent lower probability of being unemployed, whencomparedtochildrenwithlow‐incomeparents.

Thechild’sprobabilityofmovinglaterinlifeintodisabilityarrange‐mentsis,atmost,weaklynegativelyrelatedtotheparents’wage‐incomelevel.Moreover,whensuchalinkexists,ittypicallystrengthensslightlywhenthechildgrowsolder.Inotherwords,theprobabilityofthechildofbeingondisabilitybenefitsis,onaverage,morestronglylinkedtotheparents’wage‐incomewhenthechildis31thanwhenitis21.Thispat‐tern is most pronounced for Sweden with the difference in children’sprobabilityofbeingondisabilitybenefitshavingbyage31increasedto1.6%tothefavourofthosewithmiddle‐incomeparentsandto2.3%tothe favour of those with high‐income parents, when compared to thesituationatage31ofchildrenwithlow‐incomeparents.

Forothertypesofinactivity,theoverallpatternisagainquitediffer‐ent, albeit still highly similar across the four Nordic countries understudy. Inparticular,weobserve aweakbut significantlynegative rela‐tionbetweenthechild’sriskofendingupoutsidebotheducationandthelabourmarket and the parents’wage‐income level.Moreover, this dif‐ferenceinrisksoccursbetweenchildrenwithlow‐incomeandchildrenwithhigher‐incomeparents,whereasthere isbasicallynodifferenceinthis respect between children with middle‐income and high‐incomeparents. Furthermore, this clearly higher risk of children with low‐incomeparentsofmovingintoinactivityremainspracticallyunchangedup to age31. In those few caseswhere thisdifference in risks shrinksand, ultimately, turns to zero, the underlying reason is not a truesmoothingofrisksacrosschildrenwithparents’differingintheirwage‐income levels but rather a statistical property following from too fewchildrenwithhigh‐incomeparents showingup in thisparticular situa‐tionlaterinlife.


7.3.4 Mainfindings

Theseresultsonthelinkbetweenthechild’sprobabilityofshowingupinalternativelabourmarketsituationslaterinlifeandtheparents’edu‐cational and income background show, first and foremost, that eachparental dimension – the mother’s and the father’s educational back‐ground and the parents’ wage‐income level – mostly retains an inde‐pendent and significant relation to the child’s later labourmarket out‐comes also after accounting for other background factors, notably thechild’s early school‐to‐work‐transition experiences. Indeed, an inde‐pendentrelationforeachofthethreeparentaldimensionsshowsup,inmostcases,eventhoughtheyareaccounted for jointly, that is,withallthreeindicatorsincludedatthesametime.Moreover,theparents’edu‐cational background and theirwage‐income level tell slightly differentstories,implyingthataccountingforbothofthemproducesafullerpic‐tureofthelinkbetweenthechild’sfamilybackgroundandlaterlabourmarketoutcomes.

The country‐specific results in relation to the child’s probability ofcontinuingineducationwhenaged21,26and31indicatethefollowing.Theprobability of the child studyingwhenaged21 increaseswith theparents’ educational level and also with their wage‐income level. Thesamepatternappearsfiveyearslater,atage26,andstilltenyearslater,atage31,butwiththelinkturningincreasinglyweaker.

A similarpattern showsupalsowhen it comes to the linkbetweenthe child’s later employment probability and the parents’ educationalandincomestatus.Inparticular,ahighereducationalleveloftheparentsis linkedtoa lowerprobabilityofthechildofmovingintoworking liferather than continuing in education, whereas a higher wage‐incomelevelof theparents tends to improvetheemploymentprospectsof thechildinadulthood.

Thelinkbetweenthechild’sriskofendingupinNEETactivitieslaterinlifeandtheparents’educationalandincomebackgroundis,onaver‐age,notablyweakerandalsomuchmoredispersed,whencomparedtothecorrespondinglinkforthechild’seducationalandemploymentactiv‐ities.Thelinktotheparents’educationalandincomebackgroundforthechild’sriskofexperiencingunemploymentwhenaged21resemblesthatobserved for thechild’seducationalandemploymentprobabilities: thelinkisnegative,strengthenswiththeparents’educationandincome,butweakenswhen the child growsolder.Moreover, the child’s unemploy‐mentriskseemstobemorestronglylinkedtotheparents’incomelevelthantotheireducationallevel,whereastheoppositeholdstypicallytruefor the child’s educational and employment probabilities. In other


words, the child’s risk of experiencing unemployment in adulthood isstrongest for childrenwith low‐income parents, although this relationtendstoweakenwithage.

Alsothechild’sriskofmovingintodisabilityarrangementsorothertypesofinactivitywhenaged21,orbeyond,seemstobemorestronglylinkedtotheparents’wage‐incomelevelthantotheireducationalback‐ground. In the case of disability benefits, the negative link (i.e. lowerprobability) tends to strengthenwith the parents’ educational and in‐come levels: the risk is highest for children with low‐education/low‐income parents and lowest for children with high‐education/high‐income parents. For other types of inactivity, this trend of a steadilystrengtheninglinkdependingonthechild’sfamilybackgroundismostlymissing in the sense that the main difference occurs between low‐education/low‐income parents, on the one hand, and higher‐education/higher‐incomeparents,ontheotherhand.Anotherconspicu‐ousdifferencebetweenthesetwoinactivitycategoriesisthatthechild–parent link strengthens for disability benefits but weakens for other(unknown)typesofinactivitywhenthechildapproachestheageof31.

Finally,itisworthnotingthatourresultsindicatethatthereisnoma‐jordifferencebetween theroleof themother’sand the father’seduca‐tional background: the overall pattern is basically the same when itcomestoboththesignandthestrengthoftheinvestigatedchild–parentlinks.Anothernoteworthyfeatureisthattherearemoreclear‐cutdiffer‐ences in the strength of these links in relation to parents’ educationalbackgroundthaninrelationtotheirwage‐incomelevels.Moreprecisely,therearedistinctdifferencesinthechild’slabourmarketoutcomeprob‐abilities later in lifewhen comparing childrenwith low‐educated par‐entstochildrenwithhighereducatedparents,aswellaswhencompar‐ing children with secondary‐level educated parents to children withtertiary‐level educated parents. In relation to parents’ wage‐incomelevels, in contrast, themain and often only difference occurs betweenchildrenwithlow‐incomeparentsandchildrenwithhigher‐incomepar‐ents. In other words, the differences between children with middle‐incomeandhigh‐incomeparentsareoftenminorornegligible.


7.4 Earlypathwaysthrougheducationandlabourmarketoutcomes

The other major set of background factors included in our statisticalmodel concernswhatwehave labelled “stylized” school‐to‐workpath‐ways for those young people who have achieved no post‐compulsorydegree by the time they turn 21. Several recent studies have exploredtherelationshipbetweennon‐completionofuppersecondaryschoolandlaterlabourmarketoutcomes[e.g.Bäckmanetal.(2011)forScandina‐via, and Bratsberg et al. (2010) and Falch and Nyhus (2011) for Nor‐way]. In this section,we go one step further and investigate this rela‐tionship by means of early school‐to‐work pathways. These stylizedpathways–16intotal–aredefinedanddiscussedinChapter5andwill,therefore,notbesubject toadetailedpresentation in thiscontext.Theresultsreportedbelowrefertothoseobtainedwhenalsoaccountingforgender,cohortandfamilybackground.Asbecameevidentalreadyintheprevious sub‐chapter when discussing the role of family background,theseearlyschool‐to‐worktrajectoriesarecloselyrelatedtotheeduca‐tionand income levelsofparents.Accordinglywehavereason tokeepthis inmind also when exploring the pathway results. However, evenafter accounting for differences in family background, early school‐to‐work‐transition experiences often prove to be closely linked to theyoungperson’s later labourmarketoutcomes. Inotherwords, goodorbadearlypost‐compulsory‐schoolexperiencesmaystrengthenorweak‐entheroleoffamilybackground.

Theextenttowhichdifferentschoolandlabourmarketexperiencesearly in life tend to increaseordecrease youngpeople’s probability ofshowingup inalternative labourmarketsituations is themain topicofthissub‐chapter.Sinceourresultscoverfourcountries, fivealternativelabourmarketoutcomes,threeagepoints(21,26and31)atwhichtheseoutcomesareprojected,andatotalof16stylizedschool‐to‐workpath‐ways,themostefficientwayofreportingthismultidimensionalamountofresultsisnotself‐evident.Alldimensionshavetheirownvalue.How‐ever,asthefocusisonthe16stylizedpathways,theyarealsochosenasourpointofdepartureforthecategorisationoftheresultstobereport‐ed next. In other words, for each stylized pathway we will show theprobabilityofyoungpeoplefollowingthatparticularpathwayofbeingineitheroneofthefivemainactivitycategoriesinvestigatedwhenaged21,26and31,respectively.

Evidently,itisnotpossibleorevenmeaningfultocommentindetailonthismultitudeofresults.Instead,thetextwillmainlyfocusondisen‐


tanglingoverallpatternsand trends,whilecountry‐specific resultsandpeculiarities are easily identified in the separate tables and, therefore,mostly overlooked when commenting on key results. In the section“Mainfindings”concludingthissub‐chapter,anattemptwillbemadetosummarizealltheseresultsfroman“opposite”perspective,viz.fromtheviewofyoungpeoples’probabilitiesofshowingupinthefivealternativelabourmarket situations given the stylized pathway followed straightaftercompletionofcompulsoryschool.

7.4.1 Earlypost‐compulsory‐schoolpathways:continueineducation

AsnotedinChapter5, largesharesoftheyoungstersidentifiedasnon‐completersatage21havecontinuedineducationstraightaftercomplet‐ing compulsory school andhave also stayed as full‐time students overthenext five years, at least.Butdespite thisunbroken recordof studyyears, they have not succeeded in completing an upper secondary de‐greebythetimetheyturn21.Thisholdstruealso foranotherstylizedpathway, the dominant feature of which is a delayed start in post‐compulsoryeducationduetoabreakyearspentoutsidebotheducationand the labourmarket (inunknownactivities), uponwhich follows anunbrokenrecordofyearsenrolledinfull‐timeeducation.Next,welookin more detail into the link between these two education‐dominatedpathways and the probability of young people having followed suchpathways of being in the five different labourmarket situationswhenaged21,26and31,respectively.

We start by reporting the results for the early post‐compulsory‐school trajectoryrepresentinganunbrokenrecordofstudyyears fromage16up to age20 [11111;with1 standing for full‐time student].Asshown in Chapter 5, the share of young non‐completers following thisstylized pathway – or highly similar pathways – is close to 35% forDenmark, about30% forNorway, some29% forSwedenbut less than22% for Finland. Table 7.7a gives the differences in the probability oftheseparticularnon‐completers,whencomparedtocompleters,ofbeinginthefivealternativelabourmarketsituationsatthethreedifferentagepointsinvestigated.


Table 7.7a: “Study‐track” non‐completers’ probabilities in terms of labour market outcomes at age 21, 26 and 31, respectively, by country; differences in probabilities compared to completers


Labour market outcome [11111]

share 34.9%

[11111]

share 21.6%

[11111]

share 30.3%

[11111]

share 29.2%

Full‐time student

age 21 0.296 0 ‐0.044 0

age 26 ‐0.126 ‐0.028 ‐0.093 0

age 31 0 0 0 0.027

Employed

age 21 ‐0.307 ‐0.042 ‐0.034 ‐0.140

age 26 0.057 ‐0.093 0 ‐0.124

age 31 ‐0.107 ‐0.117 ‐0.067 ‐0.139

Unemployed

age 21 0 0 0.045 0.121

age 26 0.032 0.059 0.041 0.064

age 31 0 0.047 0.034 0.043


age 21 0 0.007 0.024 0.011

age 26 0.005 0.019 0.036 0.028

age 31 0.021 0.034 0.038 0.042

Other (inactive)

age 21 0.012 0.055 0.010 0.014

age 26 0.032 0.044 0.019 0.027

age 31 0.068 0.036 0 0.027

Notes: The reported average probabilities are obtained after also accounting for gender, cohort and

family background. A negative sign implies a weaker probability of being in that particular activity,

when compared to completers, that is, those having achieved a post‐compulsory degree by the time

they turn 21. Low (high) absolute values indicate a small (large) difference with respect to complet‐

ers. All reported probabilities are significant at the 99% level or more. Insignificant and only weakly

significant probabilities are set at zero. The probabilities are calculated from pooled information on

the three youth cohorts under study. For definitions of the five main activity groups, see Chapter 2.

For a definition and discussion of the 16 stylized post‐compulsory‐school pathways up to age 20

constructed for the Nordic non‐completers, see Chapter 5. The percentage share for the pathway in

question among the non‐completers, as reported for each country, is taken from Chapter 5. “1”

refers to being a full‐time student.

Thecorrespondingresultsfornon‐completershavingdelayedtheirstartinuppersecondaryeducationbyoneyearaftercompletionofcompulso‐ryschool[51111;with1standingforfull‐timestudentand5forinactivi‐ty(“other”)]areshowninTable7.7b.Whiletheshareofnon‐completersfollowingthistypeofpathwayisnotablylowercomparedtothe“study‐track”non‐completers,itisfarfromnegligible:4.1%forDenmark,6.2%forNorway,7.7%forSwedenandashighas13.5%forFinland.


Table 7.7b “Delayed‐study‐track” non‐completers’ probabilities in terms of labour market outcomes at age 21, 26 and 31, respectively, by country; differences in probabilities compared to completers



share 4.1%

[51111]

share 13.5%

[51111]

share 6.2%

[51111]

share 7.7%

Full‐time student

age 21 0.199 ‐0.027 ‐0.059 0.038

age 26 ‐0.108 ‐0.047 ‐0.138 ‐0.033

age 31 0 0 0 0

Employed

age 21 ‐0.275 ‐0.096 ‐0.078 ‐0.235

age 26 ‐0.022 ‐0.172 0 ‐0.159

age 31 ‐0.111 ‐0.216 ‐0.139 ‐0.180

Unemployed

age 21 0.022 0.014 0.057 0.125

age 26 0.052 0.101 0.063 0.088

age 31 0 0.075 0.051 0.056


age 21 0.003 0.020 0.039 0.053

age 26 0.010 0.052 0.060 0.065

age 31 0 0.075 0.069 0.085

Other (inactive)

age 21 0.051 0.089 0.040 0.019

age 26 0.069 0.066 0.031 0.038

age 31 0.059 0.079 0.032 0.026

Notes: See Table 7.7a above. “1” refers to being a full‐time student, “5” to belonging to the catego‐

ry “other” (inactivity).

The beyond‐age‐20 studying behaviour of study‐track and delayed‐study‐tracknon‐completersisquitesimilar.InbothFinlandandSweden,thesetwonon‐completergroupsappeartohavean,atmost,onlyslightlylowerprobability,whencompared to completers, ofpursuing full‐timestudies also after age 20. In Norway, on the other hand, both non‐completer groups have a much lower probability of being in full‐timeeducationstillatage21,withthisdifferencewithrespecttocompleterswidening furtherup toage26.Moreover, thedelayed‐study‐tracknon‐completersseemtobeinaweakerpositioninthisrespectthanarethestudy‐track non‐completers. For Denmark, there is no clear‐cut age‐relatedtrenddiscernible:non‐completershaveamuchhigherstudyingprobabilityatage21,butamuch lowerstudyingprobabilityatage26,whencomparedtoyoungpeoplehavinggraduatedfromuppersecond‐aryschoolalreadybyage21.Moreover,whileDanishstudy‐tracknon‐completersaremore likely tocontinue ineducationatage21thanaretheirdelayed‐study‐tracknon‐completerpeers,thesituationisreversedatage26.

Hence, this cross‐country picture looks quite messy with an over‐whelming dominance of dissimilarities rather than similarities. Ulti‐mately, this is only to be expected, though, in view of highly different


countryratesofyoungnon‐completers, latecompletersandadultnon‐completers (cf. Chapter 6) in combination with distinct differences inpost‐compulsory education systems. By age 31, however, these differ‐ences across the four Nordic countries in relation to study‐dominatedtrackshavedisappeared.

Themostconspicuouspatternwhenitcomestobeyond‐age‐20em‐ployment probabilities is that completers are much more likely to beemployedatage21 thanarestudy‐tracknon‐completers,with theem‐ploymentprobabilitytypicallybeingevenlowerfordelayed‐study‐tracknon‐completers.Moreover, thispattern is,byand large, repeatedatallthreeagepointsinvestigated.ForFinland,weobserveaclear‐cuttrendinthisrespectwiththeemploymentprobabilityofthesenon‐completergroupsweakeningconsiderablywithage.Asimilarage‐relatedpatternisnotdiscerniblefortheotherthreecountries.

Thecounterparttothesedifferencesinemploymentprobabilitiesisamuch lower unemployment risk among completers than among bothstudy‐track and delayed‐study‐track non‐completers, with the lattergroupofnon‐completersagaindoingworsethantheirstudy‐tracknon‐completerpeers.However,thisdifferencewithrespecttocompletersinunemploymentriskstendstonarrowwithage,apatternthatisdiscern‐ibleinallfourcountriesandmostclearlyforSweden.

Theriskofbecomingadisabilitybeneficiaryisnotablyhigherforde‐layed‐study‐track non‐completers, less so for study‐track non‐completers, when compared to completers. Moreover, this risk is in‐creasing with age, more strongly for delayed‐study‐track non‐completers than for study‐track non‐completers. This overall patternshows up in all four countries. The cross‐country pattern ismore dis‐persed when it comes to other (unknown) types of inactivity. Study‐track and especially delayed‐study‐track non‐completers encounter ahigher risk than completers also in this respect, but the age‐relatedtrendvariesa lotacrossthefourcountries: inDenmarkit is increasingand in Finland decreasingwith age. These differences in risks are, onaverage, smaller inNorwayandSweden than inDenmarkandFinland,revealingnoage‐relatedtrendwhatsoever.

7.4.2 Earlypost‐compulsory‐schoolpathways:moveintoworkinglifeatayoungage

TheanalysisinChapter5ofnon‐completers’stylizedpost‐compulsory‐school trajectories revealed that large shares of them drop out fromuppersecondaryeducationandmoveintoworkinglife,soitseems,on


quite a permanent basis. This dropout pattern is particularly commonamongthosehavingcontinuedinuppersecondaryeducationfortwoorthree years. It is less frequent among young non‐completers havingdroppedoutalreadyafteroneyear,aswellasamongthosewhonevercontinued in education after compulsory school. Moreover, althoughthey tend to spendmost of their timeafter schooldropout in employ‐ment,theiremploymentprofileisofamuchmorebumpynature,whencomparedtothatofnon‐completersdroppingoutonlyaftertwoorthreeyearsinuppersecondaryeducation.

Next we investigate to what extent these employment‐dominatedpost‐compulsory‐schoolpathwaysofnon‐completersarerelatedtotheirprobabilityofendingupinthefivemainlabourmarketsituationsunderscrutiny5,10and15years after completionof compulsoryeducation.Again,thegroupofreferenceiscompleters,that is,thoseyoungpeoplehaving achieved an upper secondary degree by the time they turn 21.We thereby start with the most typical early employment tracks fol‐lowed by non‐completers, viz. tracks characterised by the young non‐completercontinuingdirectly inpost‐compulsoryeducation for twoorthree years before substituting school with work, but without havinggraduated fromupper secondary education [11222and11122;with1standingforfull‐timestudentand2foremployed].

As indicated in Chapter 5, the share of non‐completers followingthesetwotypesofearlyemploymentpathwaysiscloseto24%forNor‐way and only slightly lower for Denmark (22%), Sweden (21%) andFinland(about20%).ThesefourNordiccountriesalsosharethefeatureofthe3‐year‐study–employmenttrackcoveringaclearlylargershareofthenon‐completersthanthe2‐year‐study–employmenttrack,exceptinDenmark where the latter track is slightly more common. Table 7.8apresents thedifferences for the relevantprobabilities,whencomparedtothesituationofcompleters,fornon‐completersleavinguppersecond‐aryeducationforworkafterthreeyearsoffull‐timestudies.Thecorre‐spondinginformationfornon‐completersdroppingoutforemploymentalreadyaftertwoyearsoffull‐timestudiesisgiveninTable7.8b.

Notsurprisingly,youngnon‐completersmovingearlyintoworkinglifeare less likely thancompleters toshowupas full‐timestudentsalsobe‐yondage20. Inall fourcountries, this lower studyingprobability,whencomparedtocompleters,ishighestatage21,considerablyloweratage26and almost non‐existent at age 31. In view of the results presented inChapter2, thistimetrendobviously followsfromincreasingnumbersofcompletersmoving intoworking life rather than fromearlydropouts inworking life returning to full‐timeeducation. Interestingly,both thepat‐


ternandstrengthofthislowerstudyingprobabilityarehighlysimilarfornon‐completersstayingeithertwoorthreeyearsinuppersecondaryedu‐cationbeforedroppingout.Hence,itdoesnotseemtomatterthatmuchwhether the young non‐completer has left upper secondary educationaftertwooronlyafterthreeyearsoffull‐timestudies.

Table 7.8a: “Dropout‐after‐three‐years‐employment‐track” non‐completers’ probabilities in terms of labour market outcomes at age 21, 26 and 31, respectively, by country; differences in probabili‐ties when compared to completers



share 10.3%

[11122]

share 11.1%

[11122]

share 14.6%

[11122]

share 13.8%

Full‐time student

age 21 ‐0.234 ‐0.294 ‐0.406 ‐0.248

age 26 ‐0.119 ‐0.081 ‐0.114 ‐0.089

age 31 0.031 0 ‐0.029 0

Employed

age 21 0.149 0.266 0.290 0.204

age 26 0.033 0.043 0 0.026

age 31 ‐0.095 0 ‐0.067 ‐0.066

Unemployed

age 21 0.028 0 0.058 0.045

age 26 0.033 0.021 0.047 0.041

age 31 0 0 0.041 0.030


age 21 0 ‐0.003 0.011 0

age 26 0.005 0 0.015 0.009

age 31 0.014 0 0.029 0.023

Other (inactive)

age 21 0.055 0.028 0.047 0

age 26 0.043 0 0.031 0.013

age 31 0.039 0 0.026 0.016

Notes: See Table 7.7a above. “1” refers to being a full‐time student, “2” to being employed.

Likewise, it is not surprising to find thatnon‐completersmoving earlyintoworking life tend to have a higher probability of being employedalsoatage21,whencomparedtocompleters.Thisadvantageintermsofemployment prospects vanishes rapidly, though. In all four countries,the employment probability of these non‐completers is at age 26 onlyslightlyhigherthanamongcompletersandbyage31,ithasturnednega‐tive in all countries except Finland. In otherwords, young completerstend to rapidly close the employment gap to non‐completers havingmovedintoworkinglifeatanearlyage.Alreadybyage31,theemploy‐mentprospectsofcompletersareclearlybetter.Again,weseesmall, ifany, differences in these respects between non‐completers having leftupper secondary education after two years compared to those havingdroppedoutonlyafterthreeyears.


Table 7.8b: “Dropout‐after‐two‐years‐employment‐track” non‐completers’ probabilities in terms of labour market outcomes at age 21, 26 and 31, respectively, by country; differences in probabilities when compared to completers



share 11.8%

[11222]

share 8.8%

[11222]

share 9.4%

[11222]

share 7.4%

Full‐time student

age 21 ‐0.205 ‐0.294 ‐0.418 ‐0.224

age 26 ‐0.131 ‐0.105 ‐0.194 ‐0.070

age 31 0 0 ‐0.043 0

Employed

age 21 0.119 0.256 0.293 0.169

age 26 0.037 0.039 0.078 0

age 31 ‐0.080 0 ‐0.053 ‐0.061

Unemployed

age 21 0.030 0 0.063 0.055

age 26 0.040 0.022 0.051 0.036

age 31 0.019 0 0.030 0.026


age 21 0.002 0 0.016 0

age 26 0.008 0 0.027 0.015

age 31 0.013 0 0.031 0.024

Other (inactive)

age 21 0.053 0.030 0.047 0

age 26 0.047 0.042 0.038 0.013

age 31 0.039 0 0.035 0.020

Notes: See Table 7.7a above. “1” refers to being a full‐time student, “2” to being employed.

Theprobabilityoftheseearly‐workingnon‐completersofencounteringunemploymentatage21,orbeyond,isonlyslightlyhighercomparedtothe situation facedby their completer peers.Moreover, this pattern ofrelatively small differences inunemployment risks,when compared tocompleters, holds trueat all threeagepoints investigatedand, indeed,showsupinallfourcountries.Alsointhisrespect,thesituationismuchthe same for young non‐completers moving into employment‐dominated tracksafter threeyearsoralreadyafter twoyears inuppersecondaryeducation.

Thetwotablesalsoindicatethatthesenon‐completershaveanonlyamarginally, if any, higher probability of going into disability arrange‐ments after having turned20,when compared to completers. For Fin‐land, there are no significant differences in this respect between com‐pletersandnon‐completershavingmovedearlyintoworkinglife.Intheother three countries, the difference is small, albeit weakly increasingwithage.Again, thepattern isstrikinglysimilar for thosedroppingouteitheraftertwooronlyafterthreeyearsinuppersecondaryeducation.

Whenitcomestoothertypesof inactivity,thedisadvantageinrela‐tion to completers is clearly stronger, especially inDenmark andNor‐way.However,thishigherriskofnon‐completershavingenteredwork‐


inglifeatayoungageofendingupininactivitydeclineswithage,imply‐ingthatthedifferencewithrespecttocompletersistypicallysmalleratage31thanatage21.

Onthewhole, then,we identifyrelativelysmalldifferences in therisk of showing up inNEET activities between completers and non‐completersmoving, so it seems, quite successfully intoworking lifealready at a young age. This finding is most likely related to theircomparativelygoodemploymentprospects,whencompared tocom‐pleters,alsolaterinlife.Hence,bymeansofaclosetofinisheduppersecondaryeducationcoupledwithearlyengagement inworking life,theyseemtohavebeenabletoachievecompetenciesthatkeepthememployedalsoinadulthood.Moreover,inthisrespectweseenoma‐jor differences between non‐completers dropping out after two oronlyafterthreeyearsinuppersecondaryeducation.

Next we compare the outcome of these two groups of non‐completerstothoseoftheirnon‐completerpeershavingdroppedoutalreadyafteroneornoyearinpost‐compulsoryeducation.Morepre‐cisely,thisfirstpost‐compulsory‐schoolyearistypicallyspenteitherineducation [12222]oroutsidebotheducationand the labourmar‐ket [52222],with1standing for full‐timestudent,2 foremploymentand5for“other”(inactivity).Theresultsforbothofthesegroupsareincluded inTable7.8c for thesimplereasonthat thetwogroupsaresosmall forNorwaythat it isnotpossible toobtainseparateresultsforthematage21.Indeed,alsowhentakentogether,theycoverlessthan4%of theNorwegiannon‐completers.Their combined share isslightly higher in Sweden (about 5%) and highest in Denmark(13.6%) and Finland (10.6%). However, while those dropping outfrom school already after one year represent the dominating track(close to10%)of the two inDenmark, the “non‐starters”makeupalargershare(about6%)inFinland.

As is also to be expected, the studying probability of these non‐completers looks much the same as the studying probability of non‐completersdroppingoutslightlylater.Allfourgroupsofnon‐completerssubstituteschoolwithworkatayoungage,implyingthattheyaremuchless likely thantheircompleterpeers tobeenrolled ineducationespe‐ciallywhen comparing their situation at age21.With increasingnum‐bersofalsocompletersmovingintoworkinglife,thedifferenceinstudy‐ingprobabilitiesbetweencompletersandnon‐completersnarrowsrap‐idlyand,ultimately,disappears.


Table 7.8c: “Drop‐out‐after‐one‐year‐employment‐track” & “Inactivity‐year‐employment‐track” non‐completers’ probabilities in terms of labour market outcomes at age 21, 26 and 31, respec‐tively, by country; differences in probabilities when compared to completers


Labour market

outcome

[12222] [52222] [12222] [52222] [12222] [52222] [12222] [52222]

Share

9.7%

share

3.9%

share

4.4%

share

6.2%

share

2.7%

share

0.9%

share

3.0%

share

2.1%

Full‐time student

at age 21 ‐0.172 ‐0.286 ‐0.288 ‐0.350 ‐0.383 ‐0.383 ‐0.217 ‐0.290

at age 26 ‐0.154 ‐0.174 ‐0.110 ‐0.129 ‐0.215 ‐0.138 ‐0.102 ‐0.094

at age 31 0 0 0 0 ‐0.065 0 0 0

Employed

at age 21 0.099 0.171 0.224 0.271 0.195 0.195 0.146 0.236

at age 26 0.061 0.044 0 0 0.070 0 0 0

at age 31 ‐0.067 ‐0.107 0 0 ‐0.056 ‐0.139 ‐0.080 ‐0.108

Unemployed

at age 21 0.024 0.050 0 0 0.065 0.065 0.047 0

at age 26 0.034 0.043 0.026 0.032 0.066 0.063 0.038 0.041

at age 31 0.013 0 0 0 0.047 0.051 0 0.042


at age 21 0.002 0 0 0 0.024 0.024 0 0.017

at age 26 0.009 0.010 0 0 0.021 0.060 0 0.018

at age 31 0.014 0.021 0 0 0.028 0.069 0 0

Other (inactive)

at age 21 0.047 0.062 0.048 0.058 0.099 0.099 0 0.020

at age 26 0.049 0.078 0.047 0.054 0.059 0.031 0.050 0.031

at age 31 0.033 0.068 0 0 0.046 0.032 0 0

Notes: See Table 7.7a above. “1” refers to being a full‐time student, “2” to being employed and “5” to

belonging to “other” (inactivity). For Norway, the distribution across the five labour market outcomes

of non‐completers following an early post‐compulsory‐school trajectory of [12222] or [52222] is too

skewed at age 21 to allow separate probabilities to be estimated for the two pathways.

Alsowithrespecttotheprobabilityofbeingemployedstillbeyondage20, the overall pattern is highly similar for the four groups of non‐completers following early employment‐dominated tracks. More pre‐cisely, allof them tend tohaveahigherprobabilityofbeingemployedalsoatage21,whencomparedtocompleters.Anothercommonfeatureof these four non‐completer groups is that this advantage in terms ofemploymentprospects vanishes rapidlywithage. In all four countries,theyhavewhenaged26anemploymentprobabilitythatisonlyslightly,ifatall,higherthanforcompleters.Byage31,thisadvantagehasturnedintoadisadvantageinallcountriesexceptFinland.However,despitethiscommonoverallpatterntherearealsodistinctdifferencesbetweenthefourgroupsofearly‐employmentnon‐completers,themostconspicuousbeingthefollowing:youngnon‐completersnothavingcontinuedinpost‐compulsoryeducationhave,whenaged31,notablyweakeremploymentprospects not onlywhen compared to completers but alsowhen com‐pared to their non‐completer peers having continued in post‐compulsory education for at least one year. In Norway, for instance,


thesenon‐starters’employmentprobabilityatage31is14%lowerthanfor completers and about 8% lower than for their dropout non‐completerpeers.

WhenitcomestoNEETactivities,similaroverallpatternsshowagainup for all four non‐completer groups following early employment‐dominated tracks. Broadly speaking, all of them face a higher risk ofendingup inNEETactivities,whencompared to completers.However,as is evident inTable7.8c illustrating theoutcome fornon‐completersenteringworkinglifeafteronlyoneornoyearinpost‐compulsoryedu‐cation, theresultswithrespect toNEETactivitiesareoccasionallysur‐roundedbyuncertainty.ComparedtotheresultsreportedinTables7.8aand 7.8b, this shows up in less clear‐cut age‐related trends.More im‐portant,itisreflectedinaconsiderablenumberofcellscontainingzeros,indicatingnodifference inprobabilitieswhencomparedtocompleters,whenthecorrectinterpretationratheristhatthenumberofcompletersand/ornon‐completersinthatparticularlabourmarketsituationistoosmallforproducingreliable(robust)results.Butalsowiththiswarninginmind,thelabourmarketoutcomeprobabilitiesreportedinthethreetables seem to strongly suggest that young non‐starters in upper sec‐ondaryeducationfaremuchworseasyoungadultsalsowhencomparedtotheirworkingpeershavingdroppedoutearlyfromuppersecondaryeducation.Moreover, thiscontention iswell in linewith theresultsre‐portedinthepreviouschapter.

7.4.3 Earlypost‐compulsory‐schoolpathways:unemploymentexperiencesatayoungage

In our national datasets, “unemployment” covers situations where theyoungpersonisregisteredasanunemployedjobseeker.Thismeansthatwe occasionally observe quite large differences across the four Nordiccountriesinthesharesofyoungpeopleinunemployment,butalsointhecross‐cohorttrendintheseshareswithinsinglecountries.Thisholdstrueforthosebelowtheageof25andevenmoresoforthosebelowtheageof21. Needless tosay,amajorreasonfor theseobservations isdifferencesbetweencountriesandchangeswithincountriesinthepreconditionsforbeing eligible for unemployment benefits in combinationwith potentialdifferencesbetweencountriesandchangeswithincountriesintheregis‐teringbehaviourofparticularlythoseyoungpeoplenoteligibleforreceiv‐ingunemploymentbenefits:Willtheystillregisterasunemployed?

InChapter5,weconstructedforthenon‐completersatotalofthreestylized post‐compulsory‐school trajectories dominated by unemploy‐


mentexperiencesatayoungage.These tracksare identical to theem‐ployment‐dominatedtracksdiscussedaboveinthesensethattheystartwith a varying number of years in post‐compulsory schooling beforedropping out without graduating. However, now a dropout after one,twoor threeyears inpost‐compulsoryschoolingturns intoearlyyearsdominated by unemployment. Next, we present and comment on thelabourmarketoutcomesuptoage31thataremostprobablyrelatedtodropping out from school and experiencing prolonged unemploymentalreadybeforetheageof21.

Again,westartbyfirstpresentingresultsforthemosttypicaltrack:non‐completerswhocontinuedirectlyinpost‐compulsoryeducationbutdropout after three yearsof full‐time studies just to endup in (regis‐tered)unemployment[11133;with1standingforfull‐timestudentand3forunemployment].BasedontheinformationgiveninChapter5,theshareofnon‐completers inour threeyouthcohorts following this typeof unemployment‐dominated pathway is 2.1% for Denmark, 3.5% forFinland,4.5%forNorwayand11.6%forSweden.Table7.9areportsthedifferences for the relevant probabilitieswhen compared to the situa‐tionofcompleters.

Table 7.9a “Dropout‐after‐three‐years‐unemployment‐track” non‐completers’ probabilities in terms of labour market outcomes at age 21, 26 and 31, respectively, by country; differences in probabilities when compared to completers



share 2.1%

[11133]

share 3.5%

[11133]

share 4.5%

[11133]

share 11.6%

Full‐time student

age 21 ‐0.119 ‐0.181 ‐0.295 ‐0.129

age 26 ‐0.124 ‐0.068 ‐0.164 ‐0.048

age 31 0 0 ‐0.049 0

Employed

age 21 ‐0.173 ‐0.068 0.094 ‐0.147

age 26 ‐0.086 ‐0.143 0 ‐0.151

age 31 ‐0.236 ‐0.172 ‐0.111 ‐0.198

Unemployed

age 21 0.141 0.128 0.102 0.225

age 26 0.062 0.113 0.086 0.107

age 31 0.037 0.090 0.069 0.074


age 21 0.015 0 0.028 0.011

age 26 0.049 0 0.041 0.040

age 31 0.066 0 0.041 0.059

Other (inactive)

age 21 0.135 0.118 0.072 0.040

age 26 0.098 0.083 0.060 0.052

age 31 0.081 0 0.050 0.053

Notes: See Table 7.7a above. “1” refers to being a full‐time student, “3” to being unemployed.


The pattern in relation to the probability of showing up as a full‐timestudentatage21,26and/or31is identical tothatobservedforyoungnon‐completerssubstitutingschoolwithwork:amuchlowerprobabilityof being enrolled in full‐time education at age 21,with this differencewithrespecttocompleterstypicallylevellingoutwithage.Dropoutnon‐completerswithearlyunemploymentexperiencesalsotendtoencoun‐ter much lower employment possibilities. These notably weaker em‐ployment prospects are discernible already at age 21. Moreover, theytend toweaken furtherwithage,being considerablyweakerat age31than at age 21. Conversely, their risk of continuing in or returning tounemploymentisobvious.Indeed,theyencounterstillatage31ariskofbecomingunemployedthatishigherthanthatfacedbycompleters,butalso higher than the riskof becomingunemployed characterisingnon‐completershavingsubstitutedschoolwithworkatanearlyage.

WhenitcomestoothertypesofNEETactivities,weobserveinitiallysmallbutincreasingrisksofthesenon‐completersmovingintodisabilityarrangements. This pattern shows up in all countries except Finland.Non‐completers following unemployment tracks after having droppedoutafterthreeyearsinuppersecondaryeducationalsohavearemarka‐bly high risk of being in other (unknown) types of inactivity alreadywhenaged21.Whilethisrisktendstodeclinewithageitis,nonetheless,relativelyhighstillatage31.InDenmark,forinstance,itisalmost12%higherthanforcompletersand,indeed,alsomuchhigherthanfornon‐completershavingdroppedoutfromschoolintoworkinglife.

Droppingoutintounemploymentafterthreeyearsinuppersecond‐aryeducationwithoutgraduationthustendstoresult inarisky labourmarket situation also as a young adult. In particular, the employmentprospectsaremuchweakerandtheriskofendingupinNEETactivitiesmuch higher than for completers, but alsomuch higher than for non‐completerpeershavingsuccessfullyentered the labourmarketdespitedropping out from upper secondary education.Moreover, thisweakersituationtypicallyprevailsstill15yearsaftercompletionofcompulsoryschool. These findings thus lend further support to the internationalliteratureinthisfield.

Next, we compare this outcome for young unemployed non‐completers having dropped out after three years of upper secondaryeducationtothatoftheirunemployedpeershavingdroppedoutalreadyafter two years or after only one year in post‐compulsory education.Table7.9breportstheresultsobtainedfornon‐completerswhocontin‐ued in post‐compulsory education but dropped out after two years offull‐timestudiesjusttoendupinunemployment[11333;with1stand‐


ing for full‐time student and 3 for unemployment]. The share of non‐completersfollowingthistypeofpathwayisofmuchthesamesizeasforthe[11133]pathway,butonlyinDenmarkandFinland.ForNorwayitisslightlylowerandforSwedennotablylower.

Table 7.9b: “Dropout‐after‐two‐years‐unemployment‐track” non‐completers’ probabilities in terms of labour market outcomes at age 21, 26 and 31, respectively, by country; differences in probabilities when compared to completers



share 1.8%

[11333]

share 3.7%

[11333]

share 3.0%

[11333]

share 4.2%

Full‐time student

age 21 ‐0.202 ‐0.197 ‐0.399 ‐0.112

age 26 ‐0.158 ‐0.074 ‐0.218 ‐0.060

age 31 0 0 0 0

Employed

age 21 ‐0.157 ‐0.087 0.150 ‐0.188

age 26 ‐0.136 ‐0.188 0 ‐0.190

age 31 ‐0.214 ‐0.174 ‐0.137 ‐0.224

Unemployed

age 21 0.159 0.128 0.104 0.212

age 26 0.088 0.138 0.089 0.136

age 31 0 0.109 0.072 0.081


age 21 0.037 0 0.029 0.018

age 26 0.076 0 0.040 0.050

age 31 0.039 0.026 0.047 0.073

Other (inactive)

age 21 0.162 0.151 0.115 0.069

age 26 0.130 0.111 0.073 0.064

age 31 0.118 0.062 0.037 0.058

Notes: See Table 7.7a above. “1” refers to being a full‐time student, “3” to being unemployed.

Table 7.9c, finally, reports the probability of ending up in alternativelabourmarketsituationsfornon‐completersstartinganunemploymenttrack record already after one year in post‐compulsory education[13333,with1standingforfull‐timestudent,3forunemployment].Asisevident in the table, the shareofnon‐completers inourdata followingsuch tracks is mostly very low: 0.7% for Denmark, 0.8% for Sweden,1.9%forNorwaybutashighas5.1%forFinland.


Table 7.9c: “Dropout‐after‐one‐year‐unemployment‐track” non‐completers’ probabilities in terms of labour market outcomes at age 21, 26 and 31, respectively, by country; differences in probabili‐ties when compared to completers



share 0.7%

[13333]

share 5.1%

[13333]

share 1.9%

[13333]

share 0.8%

Full‐time student

age 21 ‐0.211 ‐0.167 ‐0.349 ‐0.193

age 26 ‐0.106 ‐0.105 ‐0.174 ‐0.076

age 31 0 0 0 0

Employed

age 21 ‐0.146 ‐0.108 0.091 ‐0.197

age 26 ‐0.178 ‐0.202 0 ‐0.192

age 31 ‐0.181 ‐0.255 ‐0.162 ‐0.259

Unemployed

age 21 0.131 0.109 0.112 0.196

age 26 0.130 0.174 0.095 0.106

age 31 0 0.117 0.082 0.091


age 21 0 0.006 0.029 0.042

age 26 0 0.023 0.041 0.073

age 31 0 0.033 0.050 0.081

Other (inactive)

age 21 0.211 0.160 0.118 0.152

age 26 0.122 0.110 0.101 0.089

age 31 0.090 0.123 0.060 0.091

Notes: See Table 7.7a above. “1” refers to being a full‐time student and “3” to being unemployed.

Byandlarge,thesameoverallpatternisrepeatedforallthreegroupsofnon‐completers with early experiences from (registered) unemploy‐ment. This contention seems to hold true despite the uncertainty evi‐dently surrounding the results reported in Table 7.9c due to smallsharesofnon‐completers followingsuchtracks(except forFinland). Insum, the picturemediated by the three tables indicates the following.Theprobabilityoftheseyoungnon‐completersofbeingenrolledinfull‐timeeducationwhenaged21islow,butthisdifferencewithrespecttocompletersdiminisheswithgraduatedyoungpeoplemovingincreasing‐lyfromeducationintoworkinglife.Allthesenon‐completersgoingearlyinto unemployment also face a much lower probability of being em‐ployedbyage21,andbeyond,with theiremploymentprospectswors‐eningfurtherwithage.

A comparison of the three tables further suggests that the pictureoutlinedabovetendstostrengthenwhengoingfromyoungunemployednon‐completershavingdroppedoutonlyafterthreeyearsinuppersec‐ondaryeducationtothosehavingdroppedoutalreadyafteroneyearinpost‐compulsory education. However, such a pattern appears only inrelation to education and employment probabilities.When it comes totheriskofexperiencingunemploymentalsoinadulthood,therearemi‐


nordifferencesbetweenthesethreegroupsofyoungunemployednon‐completersdifferingintheiryearsinpost‐compulsoryeducationbeforedropout.Indeed,thisseemstoholdtruealsowithrespecttotheriskofmoving on disability benefits, whereas the risk of ending up in other(unknown) typesof inactivity revealsa tendencyof typicallybeing thehigher, the earlier the young non‐completer has dropped out fromschool into unemployment. Finally, while the three tables indicate thedifferenceinprobabilitieswhencomparedtocompleters,acomparisonofTables7.9a‐candTables7.8a‐c suggests thatyoungnon‐completerswithearlyexperiencesfromunemploymentfare,onaverage,worsealsowhencomparedtoyoungnon‐completersskippingschoolforwork.

7.4.4 Earlypost‐compulsory‐schoolpathways:becomingayoungdisabilitybeneficiary

When it comes to young disability beneficiaries, we refer to a recentanalysisofours(Albæketal.,2014)publishedinthefinalreportoftheso‐calledNORWELLproject fundedby theNordicCouncil ofMinisters.Nonetheless, we will use some space also in this context to highlightlabour market outcomes of young adults having experienced healthproblemsatanearlyage.Doingso,weareabletoobtainafullerpictureof the role of all the 16 stylized pathways presented and discussed inChapter5intermsofnon‐completers’labourmarketsituationasyoungadults.Moreover,theAlbæketal.(2014)analysisdidnotcoverSweden,merelyDenmark,FinlandandNorway.

As for the employment and unemployment pathways discussedabove,weconcentrateonearlytracksstartingwithavaryingnumberofyears inpost‐compulsory schoolingbeforeendingwith theyoungper‐sondroppingout,nowtobecomeadisabilitybeneficiary.Thetotalshareof non‐completers in these types of pathways is low relative to thesharesofnon‐completersfollowingtheotherstylizedpathways–closeto1% forDenmark,3% forFinland,about2% forNorwayand4%forSweden–butfarfromnegligibleinabsoluteterms.

The first stylized pathway analysed below turns into a disability‐benefittrackafterthreeyearsinpost‐compulsoryschoolingstraightaftercompletionofbasic education [11144;with1 standing for full‐time stu‐dentand4fordisabilitybeneficiary].Theshareofyoungnon‐completersfollowingsuchpathwaysis0.1%forDenmark,0.5%forFinland,1.5%forNorwayand1%forSweden.Table7.10agivesthedifferencesfortherele‐vantprobabilitieswhencomparedtothesituationofcompleters.


Table 7.10a: “After‐three‐years‐dropout‐disability‐track” non‐completers’ probabilities in terms of labour market outcomes at age 21, 26 and 31, respectively, by country; differences in probabili‐ties when compared to completers



share 0.1%

[11144]

share 0.5%

[11144]

share 1.5%

[11144]

share 1.0%

Full‐time student

age 21 ‐0.427 ‐0.378 ‐0.188 ‐0.172

age 26 ‐0.330 ‐0.152 0 ‐0.107

age 31 ‐0.097 0 0 0

Employed

age 21 ‐0.440 ‐0.287 ‐0.109 ‐0.384

age 26 ‐0.353 ‐0.526 ‐0.160 ‐0.580

age 31 0 ‐0.504 ‐0.182 ‐0.753

Unemployed

age 21 ‐0.025 ‐0.061 ‐0.139 ‐0.038

age 26 ‐0.033 0 0.107 0

age 31 ‐0.016 0 0.072 ‐0.021


age 21 0.945 0.702 ‐0.074 0.612

age 26 0.716 0.599 0.099 0.728

age 31 0 0.501 0.120 0.760

Other (inactive)

age 21 ‐0.052 0 ‐0.084 ‐0.018

age 26 0 0 0 0.026

age 31 ‐0.027 0 0 ‐0.023

Notes: See Table 7.7a above. “1” refers to being a full‐time student, “4” to being a disability benefi‐

ciary. For Norway, the distribution across the five labour market outcomes of non‐completers

following an early post‐compulsory‐school trajectory of [11144], [11444] or [14444] is too skewed

at age 21 to allow separate probabilities to be estimated for these three pathways at this particular

age, which explains the parentheses surrounding the estimated difference in probabilities for alter‐

native labour market outcomes at age 21.

Youngnon‐completersmoving intodisability arrangements afterhavingdroppedout fromthreeyearsof full‐timestudiesatanuppersecondaryschool reveal a low probability of having returned to school by age 21.Theyalsohavealowprobabilityofbeingemployedatthisparticularage,with their employment prospectsweakening furtherwith age. The onlyexceptionisDenmark,butduetothelowshareofnon‐completersinthistypeoftrack,theDanishresultsshouldinthiscontextbeinterpretedwithcaution.Generallynon‐completershavingfollowedthistypeoftrackalsotendtofaceaslightlyhigherriskofbeingunemployed,whencomparedtocompleters,butthispatternvariesalotbetweencountriesandalsowithincountrieswithage.Additionally,theytypicallyhaveahighrisk,alsowhencomparedtootheryoungnon‐completers,ofcontinuingonorreturningtodisabilitybenefitsasyoungadults,whereastheirlikelihoodofendingupinothertypesofinactivityismostlyverylow.

Inthenexttable(Table7.10b),weturnthefocustoyoungdisabilitybeneficiaries having dropped out after two years or already after one


year inpost‐compulsory schooling [11444and14444;with1 standingforfull‐timestudentand4forbeingadisabilitybeneficiary].Theshareof non‐completers following either one of these twopathways is com‐parativelyhighonlyintwocases,bothofwhichcoverimmediateoral‐mostimmediatemovesintodisabilityarrangementsaftercompletionofcompulsory school [the 14444 track]: 2.3% for Finland and 2.8% forSweden,withtherestofsharesstayingbelow0.5%.

Table 7.10b: “Dropout‐after‐two‐years‐disability‐track” and “Dropout‐after‐one‐year‐disability‐track” non‐completers’ probabilities in terms of labour market outcomes at age 21, 26 and 31, respectively, by country; differences in probabilities when compared to completers


Labour market

outcome

[11444] [14444] [11444] [14444] [11444] [14444] [11444] [14444]

share

0.4%

share

0.4%

share

0.2%

share

2.3%

share

0.3%

share

0.1%

share

0.2%

share

2.8%

Full‐time stu‐

dent

at age 21 ‐0.439 ‐0.439 ‐0.346 ‐0.419 ‐0.188 ‐0.188 ‐0.293 ‐0.379

at age 26 ‐0.320 ‐0.330 ‐0.192 ‐0.234 0 0 0 ‐0.196

at age 31 0 0 ‐0.132 ‐0.118 0 0 ‐0.058

Employed

at age 21 ‐0.395 ‐0.407 ‐0.295 ‐0.356 ‐0.109 ‐0.109 ‐0.450 ‐0.459

at age 26 0 ‐0.483 ‐0.556 ‐0.602 ‐0.468 0 ‐0.604 ‐0.626

at age 31 0 0 ‐0.607 ‐0.736 0 0 ‐0.639 ‐0.812

Unemployed

at age 21 ‐0.025 ‐0.025 ‐0.070 ‐0.078 ‐0.139 ‐0.139 ‐0.054 ‐0.070

at age 26 ‐0.033 ‐0.033 0 ‐0.053 0.098 0 0 ‐0.039

at age 31 0 0 ‐0.049 ‐0.038 0 0 ‐0.021 ‐0.016

Disability

beneficiary

at age 21 0.911 0.923 0.720 0.883 ‐0.074 ‐0.074 0.831 0.942

at age 26 0 0.871 0.715 0.925 0.105 0 0.652 0.891

at age 31 0 0 0.839 0.933 0.118 0.118 0.660 0.908

Other (inactive)

at age 21 ‐0.052 ‐0.052 0 ‐0.030 ‐0.084 ‐0.084 ‐0.035 ‐0.034

at age 26 ‐0.025 ‐0.025 0 ‐0.036 0.132 0 0 ‐0.032

at age 31 0 0 ‐0.050 ‐0.041 0 0 0 ‐0.021

Notes: See Table 7.10a above.

Theoverall impressionarising fromcomparing the labourmarketpro‐spectsofthethreegroupsofyoungnon‐completersexperiencinghealthproblems at an early age is that their situation looksmuch the same,despitetheuncertaintyundeniablysurroundingmanyoftheresultsdueto small numbers of observations fulfilling particular combinations ofbackgroundcharacteristics. Inotherwords, itdoesnotseemtomatterhowmanyyearstheyoungpersonhasspentinuppersecondaryeduca‐tionbeforedroppingoutwithoutachievingadegree. Inall threecases,themostlikelyoutcomeisthattheyoungpersoncontinuesinorreturnstodisabilityarrangementsalsoinadulthood.


7.4.5 Earlypost‐compulsory‐schoolpathways:withdrawalatyoungageintoinactivity

The last set of our 16 stylized pathways constructed for the non‐completerscontainsatotaloffourearlypost‐compulsory‐schooltrajec‐toriesdominatedbyyearsspentoutsidebotheducationandthelabourforce,thatis,inactivitiesnotcoveredbyanyofthelargeadministrativeregistersfromwhichourdatasetsarecompiled.These“other”situationsmay,asnotedinpreviouschapters,implyengagementinhighlydifferentactivities which may have a positive influence on the young person’snear‐future choices, but may also involve activities starting a riskypathwayintoadulthood.

The first three pathways are characterised by the young non‐completerhavingcontinueddirectlyineducationaftercompletingcom‐pulsory school. Their main difference lies in the number of years en‐rolledinfull‐timeeducationbeforedroppingout:afterthreeyears,aftertwoyearsor alreadyafteronepost‐compulsoryeducationyear.Takentogether, these three pathways cover 16.3% of the non‐completers inDenmark,11.3%inFinland,22.8%inNorwayand10.3%inSweden.Inotherwords,asubstantialnumberofyoungpeopledropoutfromschooljust to withdraw from taking part in educational or in labourmarketactivities.Thefourthpathway,incontrast,involvesnopost‐compulsoryeducation whatsoever: it starts with the young person withdrawingstraightawayafter leavingcompulsoryschool frombotheducationandthe labourmarket, and continueswith the person staying outside anysuchactivitiesuptoage20,atleast.Theshareofyoungnon‐completersfollowingsuchtracksislowinNorway(1.7%)andDenmark(3.5%)butworryinglyhighinbothFinland(8%)andSweden(7%).

Nextwe look somewhatmore in detail into the labourmarket out‐comesthatthesewithdrawalpathwaysseemtobemoststronglyrelatedto.Wetherebystartwiththepathwayprecededbythreeyearsinpost‐compulsoryeducationbeforedropout [11155;with1standing for full‐timestudentand5for“other”(activities)].Theshareofnon‐completersfollowingthistypeofearlytrajectoryisstrikinglyhighinallfourNordiccountriesunderstudy:6.4%forDenmark,7.4%forFinland,13.3%forNorwayand6.1%forSweden.Theprobabilityofendingup inalterna‐tive labour market situations in adulthood is, therefore, of particularinterest for this comparatively large group of non‐completers. Theseprobabilities,ascomparedtocompleters,aredisplayedinTable7.11a.

Table7.11ashowsthatyoungnon‐completerswithdrawingintoinac‐tivity after having dropped out from upper secondary education afterthreeyearsoffull‐timestudies,areunlikelytohavereturnedtoeduca‐


tionbyage21.Althoughthisdifferenceinstudyingprobabilities,whencomparedtocompleters,shrinkswithage,thisnarrowingis,onceagain,obviously mainly due to completers having left the education systemratherthanthesedropoutshavingreturnedtoeducationbyage26orbyage31. They are alsomuch less likely to be in employment at age21,withtheiremploymentprospectsweakeningratherthanimprovingwithage.Probably,thisalsoexplainstheirtypicallyonlyslightlyhigherrisk,when compared to completers, of being registered as unemployedjobseekersasyoungadults.Moreover,theirriskofmovingintodisabilityarrangements increases with age, especially in Denmark and Sweden.Finally,theyareverylikelytocontinueininactivitystillatage21,withthisriskdecliningonlyslowlywithage.

Table 7.11a: “Dropout‐after‐three‐years‐withdrawal‐track” non‐completers’ probabilities in terms of labour market outcomes at age 21, 26 and 31, respectively, by country; differences in probabili‐ties when compared to completers



share 6.4%

[11155]

share 7.4%

[11155]

share 13.3%

[11155]

share 6.1%

Full‐time student

age 21 ‐0.164 ‐0.248 ‐0.373 ‐0.207

age 26 ‐0.074 ‐0.049 ‐0.083 0

age 31 0.058 0 0 0

Employed

age 21 ‐0.160 ‐0.097 0.149 ‐0.153

age 26 ‐0.132 ‐0.182 ‐0.072 ‐0.192

age 31 ‐0.236 ‐0.184 ‐0.157 ‐0.170

Unemployed

age 21 0.057 0.027 0.068 0.113

age 26 0.059 0.100 0.063 0.053

age 31 0.024 0.074 0.051 0


age 21 0.015 0.014 0.025 0.034

age 26 0.045 0.017 0.032 0.075

age 31 0.073 0.030 0.042 0.103

Other (inactive)

age 21 0.252 0.304 0.132 0.213

age 26 0.103 0.114 0.060 0.086

age 31 0.081 0.085 0.053 0.048

Notes: See Table 7.7a above. “1” refers to being a full‐time student, “5” to being in “other” activities.

Thecorrespondingdifferencesinprobabilities,ascomparedtocomplet‐ers, for those young non‐completers withdrawing into inactivity aftertwoyearsinpost‐compulsoryeducation[11555;with1standingforfull‐timestudentand5for“other”(activities)]arereportedinTable7.11b.The share of non‐completers following this type of track is less than2.5%inbothFinlandandSweden,abouttwiceaslargeforDenmarkand,again,highest(6%)forNorway.


Table 7.11b: “Dropout‐after‐two‐years‐withdrawal‐track” non‐completers’ probabilities in terms of labour market outcomes at age 21, 26 and 31, respectively, by country; differences in probabili‐ties when compared to completers



share 4.9%

[11555]

share 2.2%

[11555]

share 6.0%

[11555]

share 2.4%

Full‐time student

age 21 ‐0.165 ‐0.220 ‐0.341 ‐0.158

age 26 ‐0.122 ‐0.069 ‐0.111 0

age 31 0.051 0 0 0

Employed

age 21 ‐0.232 ‐0.192 0.090 ‐0.262

age 26 ‐0.176 ‐0.281 ‐0.098 ‐0.270

age 31 ‐0.290 ‐0.200 ‐0.163 ‐0.291

Unemployed

age 21 0.078 0 0.077 0.138

age 26 0.073 0.112 0.081 0.064

age 31 0.023 0 0.059 0.071


age 21 0.054 0.022 0.027 0.058

age 26 0.097 0 0.037 0.083

age 31 0.125 0 0.042 0.100

Other (inactive)

age 21 0.266 0.357 0.146 0.224

age 26 0.128 0.211 0.091 0.132

age 31 0.092 0 0.079 0.074


BasedonTable7.11b,thefollowingmaybeconcluded.Alsoyoungnon‐completerswithdrawingintoinactivityalreadyaftertwoyearsinuppersecondaryeducationfaceamuchlowerprobabilityofbeingenrolledineducation at age 21,when compared to completers. Themagnitude ofthis lower studying probability and its age‐related trend are almostidenticaltothoseobservedforyoungnon‐completersdroppingoutfromuppersecondaryeducationonlyafterthreeyears,justtowithdrawintoinactivity.However,when itcomes to theiremploymentprospects, thesituation looks notably weaker. In particular, also when compared totheirnon‐completerpeerswithdrawingonlyafter threeyears inuppersecondary education, their employment prospects are much weakeralready when aged 21, with the trend pointing to a faster weakeningwithage.Alsotheirriskofbecomingunemployedisclearlyhigher.Thesamepatternisrepeatedwhenitcomestotheirriskofcontinuinginorreturningtoinactivity.Moreover,itholdstruealsoinrelationtodisabil‐ity benefits, but only for Denmark. In the other three countries, thesetwogroupsofearlywithdrawingnon‐completershaveanapproximatelyequallyhighrisk,whencomparedtocompleters,ofendingupindisabil‐ity arrangements. All in all, the overall impression is that young non‐completersdroppingoutfromuppersecondaryeducationintoinactivity


fare inmostrespectsworse ifdroppingoutalreadyafter twoyears in‐steadofdroppingoutonlyafterthreeyears.

Theshareofnon‐completershavingdroppedoutfromschoolintoin‐activityalreadyafterhavingcontinuedinpost‐compulsoryeducationforonly one year [15555;with 1 standing for full‐time student and 5 for“other” (activities)] is smaller than for the other two groups of youngwithdrawingnon‐completers investigated so far: less than2% forFin‐landandSwedenand3.5%forNorway.TheonlyexceptionisDenmarkwhere this share is approximately the same (5%) as for the previousgroup of withdrawing non‐completers. These young non‐completers’probabilities in relation to later labour market outcomes, when com‐paredtothesituationofcompleters,aregiveninTable7.11c.

Table 7.11c: “Dropout‐after‐one‐year‐withdrawal‐track” non‐completers’ probabilities in terms of labour market outcomes at age 21, 26 and 31, respectively, by country; differences in probabili‐ties when compared to completers



share 5.0%

[15555]

share 1.7%

[15555]

share 3.5%

[15555]

share 1.8%

Full‐time student

age 21 ‐0.209 ‐0.238 ‐0.372 ‐0.188

age 26 ‐0.123 0 ‐0.158 0

age 31 0 0 0 0

Employed

age 21 ‐0.221 ‐0.143 0.095 ‐0.261

age 26 ‐0.219 ‐0.247 ‐0.074 ‐0.266

age 31 ‐0.326 0 ‐0.195 ‐0.295

Unemployed

age 21 0.075 0.063 0.087 0.107

age 26 0.075 0.126 0.078 0.102

age 31 0 0 0.072 0.064


age 21 0.060 0.039 0.032 0.129

age 26 0.095 0.023 0.040 0.076

age 31 0.131 ‐0.011 0.047 0.120

Other (inactive)

age 21 0.294 0.279 0.158 0.213

age 26 0.171 0.138 0.113 0.128

age 31 0.163 0 0.097 0.074


The broad picture emerging based on Table 7.11c is highly similar tothat obtained for youngwithdrawing non‐completers having been en‐rolledfortwoyearsinuppersecondaryeducationbeforedroppingout.There are, however, a few conspicuous differences. First, in all fourcountries youngwithdrawingnon‐completers dropping out frompost‐compulsoryeducationalreadyafteroneyear,seemtohaveanevenlow‐erprobability of having returned to educationby age21.Anotherdis‐


tinctdifferencecompared toyoungwithdrawingnon‐completersdrop‐pingoutonlyaftertwoyears,isthattheirprobabilityofcontinuinginorreturningtoinactivityisclearlyhigher.ThisholdstrueforNorwayandespeciallyforDenmark,thatis,forthosetwocountrieswheretheshareof non‐completers following this type of inactivity track is highestamongthefourNordiccountries.

Finally,weturntothepathwayindicatingimmediatewithdrawalaf‐ter completion of compulsory education [55555; with 5 standing for“other” (activities)]. The share of non‐completers following this riskytrack already before turning 21 is less than 2% in Norway, 3.5% inDenmark,butashighas7%inSwedenand8%inFinland.Table7.11dgivesthedifferences inprobabilities,whencomparedtocompleters,oftheseyoungnon‐completersof endingup inalternative labourmarketsituationsatage21,26and31,respectively.

Table 7.11d: “Early‐withdrawal‐track” non‐completers’ probabilities in terms of labour market outcomes at age 21, 26 and 31, respectively, by country; differences in probabilities when com‐pared to completers



share 3.5%

[55555]

share 7.9%

[55555]

share 1.7%

[55555]

share 6.9%

Full‐time student

age 21 ‐0.244 ‐0.244 ‐0.426 ‐0.254

age 26 ‐0.138 ‐0.090 ‐0.123 ‐0.100

age 31 0 ‐0.051 0 ‐0.033

Employed

age 21 ‐0.217 ‐0.214 0.275 ‐0.320

age 26 ‐0.254 ‐0.344 ‐0.134 ‐0.278

age 31 ‐0.444 ‐0.343 ‐0.185 ‐0.372

Unemployed

age 21 0.082 0.036 0.072 0.060

age 26 0.074 0.138 0.090 0.040

age 31 0 0.109 0.068 0.046


age 21 0.055 0.097 0 0.409

age 26 0.094 0.068 0.047 0.246

age 31 0.137 0.088 0.046 0.279

Other (inactive)

age 21 0.324 0.324 0.066 0.106

age 26 0.224 0.228 0.120 0.092

age 31 0.237 0.198 0.077 0.079

Notes: See Table 7.7a above. “5” refers to being in “other” activities.

Youngnon‐completerswithdrawingstraightaftercompletingcompulso‐ryschoolhaveavery lowprobabilityofbeingenrolled ineducationatage21:comparedtoyoungcompleters,thisprobabilityis43%lowerinNorway and about 25% lower in the other three countries. Indeed,among the four groups of young non‐completers following inactivity‐


dominated tracks early in life, these immediatewithdrawers are leastlikely tohavere‐enterededucationbyage21.Theyalso typicallyhavethe weakest employment prospects which, moreover, rapidly weakenfurtherwithage:comparedtocompleters,theyhaveinDenmarka44%lowerprobabilityofbeingemployedwhenaged31.Theirriskofbecom‐ingunemployedishigh,butnotnecessarilyhigherthanforthosewith‐drawingnon‐completershavingcontinuedineducationforat leastoneyearbeforedroppingout.

WhenitcomestoothertypesofNEETactivitiesthesituationisdiffer‐ent, though. In particular, among the four groups of withdrawing non‐completers, they have the highest probability of moving into disabilityarrangements, notably in the two countries with the highest share ofyoung non‐completers following this type of track, that is, Finland andSweden.Theyalsohavethehighestprobabilityofcontinuinginorreturn‐ing to inactivity, but only in Denmark and Finland,whereas this risk ismoreinlinewiththatoftheotherthreewithdrawinggroupsinNorwayandSweden.However,despitethesecross‐countrydifferencesincertainrespects,theoverallpicturepointstotheseimmediatewithdrawershav‐ing the worst prospects when it comes to labour market outcomes inadulthood. On the whole, it seems that these prospects tend to be theweaker,theearliertheyoungnon‐completerwithdrawsintoinactivity.

7.4.6 Mainfindings

Thissub‐chapterhas focusedonreportinganddiscussingresultshigh‐lightingthepotentialroleofyoungpeople’searlyeducationalandlabourmarketexperiencesfortheiroutcomesinadulthoodor,moreprecisely,at age 21, 26 and 31, respectively. These early experiences followingupon completion of compulsory school have been approximated bymeansof16stylizedpathwaysconstructedforthenon‐completersandpresentedindetailinChapter5.

With resultsproduced for 16 stylizedpathways at three agepointsand,moreover,separatelyforfourcountries,theoutputfromthisexer‐cise is quite massive. While the detailed country‐specific results havebeendisplayed ina largenumberof tables, the text surrounding thesetables hasmainly focused on identifying common patterns among thefourNordic countries, but also distinct differences. However, althoughtheredoexistdifferencesacross the four countries in certain respects,most of these differences seem to relate to the underlying data.Moreprecisely, since thesharesofnon‐completersgoing intoeachof the16stylizedpathwaysvarysubstantiallyacrossthefourcountries,thenum‐


ber of observations is not always enough for obtaining robust results,especially aswe simultaneously account for differences in gender, co‐hortandfamilybackground.Whenrelevant,suchuncertaintyrelatedtothepresentedresultshasbeenindicatedinthetext.

Theprobabilitiesofnon‐completersbeinginalternativelabourmarketsituations at age 21, 26 and 31, respectively, depending on the post‐compulsory‐schooltrackfolloweduptoage20,arethroughoutcontrastedagainstthesituationofcompleters,thatis,youngpeoplehavinggraduatedfromupper secondary educationby age21.The reporteddifferences inprobabilitiesthusindicatehowmuchmoreorlesslikelyanon‐completeris to showup in a particular labourmarket situation later in life,whencomparedtocompleters.However,comparisonsmayalsobeundertakeninotherdimensionsbasedonalltheseresults.Inparticular,itisalsopos‐sible to compare theoutcomeacrossnon‐completers followingdifferentearlytracks.Whilealsosuchattemptsweremadealreadywhendiscuss‐ingtheresultsdisplayedintheseparatetables,wewillconcludethissub‐chapterwithfourfigureswhichhopefullyshedfurtherlightonourresultsandtheconclusionstobedrawnbasedonthesefindings.

The results presented in the subsequent figures are simplified,though, when compared to the detailed tables presented above: thecountry‐specificprobabilitieshavenowbeenturnedintoNordicaverag‐es with the country‐specific shares of non‐completers going into eachstylized pathway used asweights. This averaging across countries canbejustifiedinviewofthesimilarityinoverallpatterns.Theuseofcoun‐try‐specificpathwaysharesasweightsmeans,inturn,thatmajorresultsfor each non‐completer pathway is given more weight. This choice ismotivatedespeciallyincaseswheresomecountry’snon‐completersareonlyweaklyrepresentedinthepathwayinquestion.Onthewhole,then,thisaveragingexerciseproduces,foreachagepoint,fiveresultsforeachofthe16stylizedpathwaysinvestigated.Forinstance,weobtainforthenon‐completers’study‐trackpathway[11111]fiveprobabilitiesshowingtheaveragedifferencewithrespecttocompletersatage21ofbeing(1)enrolled ineducation; (2)employed; (3)unemployed; (4)ondisabilitybenefits;and(5) inother typesof inactivity.Correspondingresultsareproduced for this particular pathway also at age 26 and at age 31. Ofcourse,thesameexerciseisrepeatedfortheother15stylizedpathways,implying thatwenowhave for eachagepointonly five labourmarketoutcomeprobabilitiesperstylizedpathway.

Westartbypresentingthesefivepathway‐specificpointsforage21.ThisisdoneinFigure7.1,butwiththeearlydisability‐benefittracksleftoutandgatheredintoaseparatefigure(Figure7.4).Thischoiceisguid‐


edbytherelativelyhighprobabilitiesobtainedforthesetracks:includ‐ingthemwiththeotherstylizedpathways,theprobabilitiesofwhichareof a notably smaller magnitude, would produce a highly unbalancedscatterwithmostpointsgathereddenselyinanunreadableway.

Figure7.1clearlyshowsthatnon‐completersfollowingstandardstudytracks[11111]aremostlikelytobeenrolledineducationalsoatage21.Indeed, they have a higher probability of being in education alsowhencompared to 21‐year‐old completers (positively signed difference). Forthosenon‐completershavingspentayearininactivitybeforecontinuingineducation[51111], thecorrespondingdifferencewithrespect tocom‐pletersisminor,albeitstillpositive.Forallothernon‐completers–thatis,thosehavingfollowedothertypesofearlypost‐compulsory‐schoolpath‐ways–theprobabilityofbeingenrolledinfull‐timeeducationwhenaged21isnotablylower(negativelysigneddifference).

Figure7.1:Non‐completers’probabilitiesintermsoflabourmarketoutcomesatage21;differencesinprobabilities,whencomparedtocompleters,for13stylizedpathwaysasaveragedoverthefourNordiccountriesunderstudy

Notes: The figure gives differences in probabilities, when compared to completers, averaged over

the four Nordic countries under study. These averages are calculated based on the country‐specific

probabilities reported in Tables 7.7a to 7.11d, using the country‐specific shares of non‐completers

going into each stylized pathway as weights. The horizontal axis measures these average differences

in probabilities with a positive sign indicating a higher probability and a negative sign a lower prob‐

ability, when compared to completers. The vertical axis represents 13 out of the 16 stylized path‐

ways constructed for Nordic non‐completers, as described in Chapter 5. A corresponding presenta‐

tion for the three stylized disability‐benefit pathways is given in Figure 7.4.


The probability of being employed at age 21 is highest for non‐completershavingsubstitutedschoolwithworkalreadyatanearlyage.Inotherwords,youngnon‐completershavingstartedanearlyand,soitseems, successful employment career appear to experience a clear‐cutemploymentadvantageoverbothcompletersandnon‐completershav‐ing followed other early tracks, still when aged 21. Indeed, non‐completershaving followedothertypesofearly tracksareobservedtohavethe lowestprobabilitynotonlyofbeingenrolledineducationbutalsoofbeingemployed.

Theprobabilityofexperiencingunemploymentwhen21years‐of‐ageispersistentlyhigher fornon‐completers than for completers irrespec‐tiveoftheearlypathwayfollowedbythenon‐completer.Thedifferenceintheriskofshowingupasanunemployedjobseekerisespeciallypro‐nounced for those young non‐completers having early unemploymentexperiences. A similar pattern is observed for young non‐completershavingwithdrawnintoinactivityalreadyatanearlyageinthesensethattheyfacethehighestriskofbeingoutsidebotheducationandthelabourmarketstillwhenaged21.

Allinall,Figure7.1illustrateswellthatthereisastronglinkbetweenyoung people’s early and later school and labourmarket experiences.Moreover,theselinksdonotdisappearwhenalsoaccountingfordiffer‐encesinfamilybackground.Indeed,itisworthemphasisingalsointhiscontext that the differences in probabilities reported in the figure, aswell as in the subsequent figures, are those obtained after taking intoaccount differences in parents’ educational background and wage‐incomelevel.Hence,whiledifferencesinfamilybackgroundcangosomewayinexplainingdifferencesinyoungpeople’slabourmarketoutcomes,thereisstillanindependentroleplayedbytheirearlyschoolandlabourmarketexperiences.

Thenexttwofiguresillustratethecorrespondingsituationatage26(Figure 7.2) and at age 31 (Figure 7.3). The information contained inthesetwofiguresindicatesthatthestronglinkbetweenearlyeducation‐alandlabourmarketexperiencesandtheprobabilityofbeinginalterna‐tive labourmarket situationsobservedat age21, is clearlydiscerniblealsoatage26andstillatage31.




All early non‐completer tracks have, by age 26, resulted in a situationwith theseyoungpeoplehavingamuch lowerprobabilityofbeingen‐rolled as full‐time students, when compared to their peers having al‐readybyage21achievedanuppersecondarydegree.Noteworthy,how‐ever, is that the difference in this probability is somewhat smaller forthose non‐completers having spent at least three early years in post‐compulsoryeducation,butwithouthavingcompletedanuppersecond‐ary education still when aged 21. Non‐completers with an early em‐ployment track aremore likely to be employed than both completersandothernon‐completersstillatage26,butwiththisemploymentad‐vantageovercompletersnowbeingnotablyweaker.Theworstemploy‐mentprospectsarefacedbyyoungpeoplehavingwithdrawnintoinac‐tivityalreadyatanearlyage.

Thesituationatage21indicatedthatyoungnon‐completerstypicallyface a higher probability, when compared to completers, of being inNEET activities, irrespective of the early track followed. This outcomehasnotchangedbyage26.Onthecontrary,itseemstohavesharpenedfurtherwiththeprobabilityofendingupasaNEETbeingthehigherthefeweryearstheyoungpersonhasattendedschool.




Atage31, finally, theoverallpicture looksqualitativelyverysimilar tothatobservedfiveyearsearlier,atage26.Therehaveoccurredcertaininterestingchanges, though.Theemploymentadvantageover complet‐ersofthoseyoungpeoplehavingmovedearlyintoworkinglifehas,byage31,turnednegative.However,thischangeinemploymentprospectsdoesnotnecessarilymeanthattheemploymentsituationoftheseyoungpeoplehasweakened inabsoluteterms. Itrathertells thatmostyoungcompleters of upper secondary school have now finished their furthereducation, entered working life and started a successful career. Thestrongdeclineuptoage31intheshareofyoungpeoplebeingenrolledas full‐time students also explains the minor differences in studentprobabilitiesirrespectiveoftheearlytrackfollowed.Youngpeoplewithearly experiences from NEET activities have, also when aged 31, theweakest labourmarket prospects, albeit thedifferencewith respect tocompletersisnolongeraspronouncedatage31asatage26.

Inourlastsummaryfigure(Figure7.4),weillustratethelabourmar‐ket prospects at age 21, 26 and 31, respectively, of young non‐completershavingfollowedearlytracksdominatedbytimesentondis‐ability benefits. The most conspicuous feature of Figure 7.4 is strongpersistence in young people’s disability situation: early school leaving,


withtheyoungsterbecomingadisabilitybeneficiaryalreadyatayoungage,most likely results in the youngster being a disability beneficiaryalso as a young adult. This persistence, however, should not be inter‐preted asbeingdue to receivingbenefits at an early age, but is ratherexplainedbypersistence of the causebehind the youngperson’s earlymoveintodisabilityarrangements.

Figure7.4:Non‐completers’probabilityofbeingadisabilitybeneficiaryatage21,26and31,respectively;differencesinprobability,whencomparedtocompleters,for3stylizeddisability‐dominatedpathwaysasaveragedoverthefourNordiccountriesunderstudy


All in all, amajor finding is thatweobserve growing persistencewithage among young people having followed early tracks dominated byNEET activities: early unemployment shows up increasingly in unem‐ploymentexperiences inadulthood;earlydisabilityarrangements tendtocontinueinadulthood;andearlyinactivityinvolvesahighriskofcon‐tinuing outside both education and the labourmarket, a process oftenendingwithamoveintodisabilityarrangements.

However, also study‐dominated tracks tend to involve a non‐negligibleriskofthenon‐completerultimatelyendingupinNEETactivi‐tiesinadulthood.InviewoftheresultspresentedinChapter6,thisout‐comeislikelytoconcernespeciallythoseyoungpeoplewhofailtocom‐


pleteanuppersecondarydegreealsobeyondtheageof21,thatis,thosebecomingadultnon‐completers.

Thosewhoappeartodothebestamongthenon‐completersaretheonesmovingearly,withoutgraduatingfromuppersecondaryeducation,but,nonetheless,successfully intoworking life.Anevenbettersolutionalso for theseyoungnon‐completerscould,ofcourse,beanuppersec‐ondarydegreebeforesubstitutingschoolwithwork.Thiswouldrequireattractivegraduationroutesforyouthencounteringseriousproblemsinfinishing theiruppersecondaryeducationwhilehavingastrongdesiretowork.

8. Summary and discussion

Youngpeoplefollowhighlydifferenttrajectoriesfromage16uptoage20,atimeperiodwhichisoftenarguedtobethemostcriticalintermsoftheir future labour market outcomes. In other words, the early post‐compulsory‐schoolpathway theyhappen to follow– forone reasonoranother–islikelytoaffecttheirfutureoptionsandoutcomesinadeci‐siveway.Thefocusofthisreporthasbeenoninvestigatingthe lookoftheseearlypathways,aswellasonexploringtheirlinktolabourmarketoutcomesinadulthood.

Inouranalyses,wehavetracedthreefullcohortsofyouth:thosewhoturned16in1993,1998and2003,respectively.AlltheseyoungpeoplefromfourNordiccountries–Denmark,Finland,NorwayandSweden–havebeen followedup to theyear2008, implying that the longest fol‐low‐upperiodcoversasmanyas15year.

IntheNordiccountries,avastmajorityofcompulsory‐schoolleaverscontinues immediately, occasionally only after a break year, in uppersecondary education and followsup to age20, at least, amore or lessunbroken track of full‐time‐study years. However, there are also largesharesofyoungpeoplegoingintoothertypesofearlypost‐compulsory‐school tracks,manyofwhichinvolveriskyelementssuchasprolongedwithdrawaloutsidebotheducationandthe labourmarket. Inouranal‐yses,wehaveusedso‐calledclusteringtechniquestogroupyoungpeo‐ple into different clusters depending on the early post‐compulsory‐schooltrajectoryfollowed.(Chapter3)

Throughout thereport,adistinction ismadebetweenyoungpeoplehavingcompletedanuppersecondarydegreebythetimetheyturn21(completers),andyoungpeoplewithanexamonlyfromcomprehensiveschool still at age21 (non‐completers).Most of our focus has beenonthecategoryofyoungnon‐completers.Additionally,attentionhasbeenpaidtohighlightingdistinctdifferencesbetweengenders,aswellasbe‐tweenthethreeyouthcohortsunderscrutiny.

Within the Nordic countries, Denmark and Sweden can be seen tohave polar systems of upper secondary schooling, especially when itcomestovocationaltraining.Denmarkhasacomprehensiveapprentice‐ship system with the young person gathering large amounts of workexperienceatemployers,whereasSwedencanbecharacterisedashav‐


ingatypicalschoolsystemalsoafterthereformin2011.Thisdifferenceinuppersecondaryschoolsystemsisclearlyreflectedinyoungcompul‐sory‐school‐leavers’ trajectories up to age 20 and, hence, also in theircompletionratesbyage.InSweden,thetypicalyoungpersoncontinuesfor threeyears inuppersecondaryschooling,with thenon‐completionrateby21being,atmost,17%inthethreeyouthcohortsinvestigated.InDenmark,ontheotherhand, thecorrespondingnon‐completionrate isashighas39%inthe1998cohort(andonlyslightlylowerintheothertwocohorts)butwiththe21‐year‐oldyouthbeing,nonetheless,mostlyeither in school or in employment.The situation inNorway resemblesmorethatofDenmarkthanofSweden,withnon‐completionratesocca‐sionallyreaching32%.Finland,inturn,looksmorelikeSwedenthanlikeDenmarkorNorway,withnon‐completionratesatage21being,atmost,closeto20%.(Chapter2)

Evenwhen restricting the analysis of early post‐compulsory‐schooltrajectories to the group of young non‐completers, a majority is stillfoundtofollowstandardstudytracks,butwithoutcompletinganuppersecondarydegreebyage21.Indeed,whenclusteringyoungNordicnon‐completers into groups common to all four countries, 58% of Finnishnon‐completers follow a standard or delayed upper secondary studytrack,with the corresponding share being about 62% for Danish non‐completers,some71%forNorwegiannon‐completersandcloseto76%forSwedishnon‐completers.Hence,althoughtheseyoungstershavenotsucceededinachievinganuppersecondarydegreestillbyage21, theyhavetypicallyspentmostoftheirearlypost‐compulsory‐schoolyearsasfull‐time students. Moreover, the share of non‐completers followingearlystudytrackshas increased inall fourcountriesover time, that is,whencomparingthesituationacrossthethreeyouthcohortscoveredbyournationaldatasets.Whilelessthan64%oftheNordicnon‐completersfromthe1993cohort followedeitherstandardordelayedstudytracksafterleavingcompulsoryschool,thissharehadincreasedtoalmost70%inthe2003cohort.(Chapter4)

When, as in Chapter 5, we refine our analysis of Nordic non‐completersbygroupingthemaccordingtotheirmainactivityafterthreeorlessyearsinuppersecondaryeducation,full‐timestudiesstillretaintheirpositionasalsonon‐completers’maintypeofactivity:about39%of Danish, close to 37% of Norwegian and Swedish and some 35% ofFinnish non‐completers go into early post‐compulsory‐school trajecto‐riesdominatedbyfull‐timestudyingduringthefiveyearsuptoage20.Another important type of early post‐compulsory‐school trajectory ischaracterised by the non‐completer substituting schoolwithwork be‐


fore graduating from upper secondary school: almost 36% of Danishnon‐completers show up in this type of employment‐dominated earlytrackwith thecorrespondingsharebeingclose to31% forFinland,al‐most28% forNorwayandabout25% forSweden.However,whileweobserve a clear‐cut increase across cohorts in the shareof youngnon‐completersfollowingstandardstudytracks, thereseemstobenocom‐monNordic trend for these school‐dropout‐employment tracks: largershares of Swedish non‐completers from the youngest (2003) cohortfollow such employment tracks, whereas the situation is the oppositeamongDanishnon‐completersbelonging todifferentcohorts.All inall,then, the results indicate, once again, that pathways dominated byschool and work activities are the most prominent ones also amongyoungnon‐completersandthatthisholdstrueforallfourNordiccoun‐triesunderstudy.(Chapter5)

The rest of Nordic non‐completers follow early post‐compulsory‐school‐dropout trajectories ending in so‐calledNEET activities, that is,unemployment or inactivity, including disability arrangements. Unem‐ployment pathways are followed by almost 17% of Swedish non‐completers, about 12%of Finnishnon‐completers, over 9%ofNorwe‐giannon‐completers,but less than5%ofDanishnon‐completers.Disa‐bility benefits are rare among young non‐completers with the sharebeinghighest (some4%) for Sweden and lowest (only 1.3%) forDen‐mark.Incontrast,largesharesofyoungpeoplelackinganuppersecond‐arydegreestillatage21haveahistoryofpost‐compulsory‐schooltra‐jectoriesdominatedbyothertypesofinactivity.Thisshareisparticular‐ly high for Norway covering about one‐fourth of the country’s non‐completerswith,moreover,amajorityofthemhavingdroppedoutonlyafterthreeyearsinuppersecondaryschool.Thecorrespondingshareisjust below20%amongDanish andFinnishnon‐completers, and about17%amongSwedishnon‐completers.(Chapter5)

However,when theshareofyoungnon‐completershaving followedNEET‐dominatedtracksalreadyatanearlyageis,instead,relatedtothefull youth population, these quite large cross‐country differences inNEETsharesbecomemuchsmaller:about10%ofbothDanishandNor‐wegian youths are non‐completers going early into NEET‐dominatedtracks, with the corresponding share being some 6% for Finland andSweden. Hence, the much lower completion rate among 21‐year‐oldsobserved for Denmark and Norway, when compared to Finland andSweden,isnotaboutyoungcompulsory‐schoolleaversgoingintoNEET‐dominatedtracks,butmoreaboutyoungpeoplefollowingstudy‐orem‐


ployment‐dominated trackswithout achieving an upper secondary de‐greebyage21.(Chapter5)

Next,weexploredlabourmarketoutcomesatage21,26and31,re‐spectively.Of completers aged21, about 90%were found to be eitherstudyingorworking.Thishigh“activity”shareamongyoungcompletersis retained, and typically also strengthened, at age 26,withmore than67%ofSwedishcompletersbeinginemploymentcomparedtobetween59and62% in theother threecountries.Byage31, theshareof com‐pletersinemploymenthasincreasedtoover85%inDenmarkandSwe‐den and to about 76% in Finland andNorway,whereas the share stillenrolled in full‐time education was mostly down at about 10%. Con‐versely,theshareofcompletersinNEETactivitiesisinallfourcountriesquite low, ranging fromabout13% inNorway to less than5% inDen‐mark.(Chapter6)

Thesituation looksverydifferent fornon‐completers,albeitastrik‐inglylargeproportionofalsonon‐completersisstudyingorworkinginadulthood. At age 31, this share is close to 84% for Danish non‐completers, compared to about 74% for Swedish non‐completers andsome70%forFinnishandNorwegiannon‐completers.However,amongthenon‐completerswealso find largesharesofunemployed,disabilitybeneficiariesandthosehavingwithdrawnintoothertypesofinactivity.Norway stands out with an extraordinarily large share of non‐completers being outside both education and the labourmarketwhenaged 31, whereas Sweden is characterised by a large share of non‐completers in disability arrangements when young adults. Finland, inturn,hasacomparatively largeshareofnon‐completersshowingupasunemployedjobseekersasyoungadults,whichmainlyreflectsthehighunemploymentlevelinthe1990s.(Chapter6)

Whentheseoutcomesofyoungnon‐completersatthreedifferentagepoints – 21, 26, and 31, respectively – are, instead, related to the fullyouthpopulation,theoverallcross‐countrypicturechanges,onceagain,in certain crucial respects. Most notably, while we observe for bothDenmark and Norway a comparatively high share of non‐completersamongthe21‐year‐olds,manyofthemare,nonetheless,inemploymentwhenyoungadults.Atage31,about27%oftheDanishyouthpopulationinvestigatedcoveremployedyoungpeoplewhowereclassifiedasnon‐completers when aged 21. The corresponding share for Norway isaround19%,butonlysome10%forFinlandandSweden.Thesehighlydifferentsharesreflectwellthecross‐countryvariationinthenumberofyoung people completing an upper secondary degree only beyond age21and,inparticular,thestrikinglydifferentlabourmarketoutcomesof


these latecompleters in the fourcountries. Indeed, inDenmark itdoesnotseemtomatterthatmuchifyoucompleteyoureducationbyage21or26,whereasitmattersalotifyouareanon‐completerstillatage31.InSweden, incontrast, itmattersa lot ifyou fail tocompleteanuppersecondarydegreeinthenormaltime,whereasFinlandandNorwayfallin‐betweenthesetwoextremes.Anotherdistinctfeatureistheconspic‐uously similar share of theNEETpopulation across the four countriesdespite remarkable cross‐country differences not least in the share ofyoung people still lacking an upper secondary degree when aged 21.(Chapter 6) Taken together, these findings suggest that cross‐countrydifferences in school‐to‐work‐transition patterns are not necessarily adecisivedeterminantofthecountries’NEETrates.Accordingly, thedif‐ferent upper secondary education systems in place should rather bejudgedbytheirimplicationsforthedevelopmentofskillsandlong‐termproductivity,aswellasbytheircosts.

Thereisahugebodyof literatureprovidingsupportfortheconten‐tion that school success and, ultimately, labour market outcomes arecloselyrelatedtotheyoungperson’sfamilybackground.Alsoourresultssupportthisbroad‐basedevidence.Itis,therefore,ofinteresttoexplorewhetherthelinkweobservebetweenearlyandlaterschoolandlabourmarketexperiencesis,ultimately,alinkbetweenfamilybackgroundandlater labourmarket outcomes.Our results strongly suggest that this isnotthecase:theearlypost‐compulsory‐schooltrajectoryfollowedbyayoungpersonplaysa rolealsoafter accounthasbeenmade fordiffer‐encesinfamilybackground.Inparticular,weobservegrowingso‐calledstate dependence among non‐completers having followed early tracksdominatedbyNEETactivities:earlyunemploymentshowsup inan in‐creasingriskofexperiencingunemploymentinadulthood;earlydisabil‐ity arrangements tend to continue in adulthood; and early inactivityinvolvesahighriskofcontinuingoutsidebotheducationandthelabourmarketalsoasayoungadult,withdisabilityarrangementsoftenbeingtheultimateoutcome.(Chapter7)However,wedonotclaimthatthereisacausalrelationshipbetweenearlyschoolandlabourmarketexperi‐encesandlateroutcomes.Thesameunderlyingcause,suchasadisabil‐ity,maywell affectboth thepathway throughupper secondaryeduca‐tion and future labour market prospects. Still, the strong relationshipidentified between the early trajectory followed and subsequent out‐comesmost likely also includes causal elements implying that, regard‐less of the underlying cause, evidence‐based information about youngpeople’spathwaysthatpredictsundesirableoutcomesmayserveasanimportantsourceforbettertargetedpoliciestowardsyouth.


Insum,ourreportpointstofourmajorresults:A first major finding is large cross‐country differences in terms of

non‐completionratesatdifferentageswithnon‐completionfromuppersecondary education continuing well into the thirties. In Finland andSweden, the non‐completion rate is comparatively low already among21‐year‐oldsandconvergestowards10%whenyoungpeoplearetraceduptoage31.InNorwayandespeciallyinDenmark,thenon‐completionrateamong21‐year‐olds ismuchhigherandhas,byage31,convergedtowards 20%. Indeed, completion from upper secondary school onlybeyondage21isespeciallyprevalentamongyoungDanes.

A second main finding emerging for all four countries is that, alt‐houghnon‐completionpredictsrisky labourmarketoutcomesinadult‐hood,employmentandstudyingisbyfarthedominantactivityoverthenexttenyearsorsoalsoamongthoseyoungpeoplewhofailtocompletean upper secondary degree by age 21. Hence, non‐completion whenaged21doesnotautomaticallyimplythattheyoungpersonisanearlyschool‐leaver or a school dropout having serious difficulties in copingwitheconomicandsociallife.

Athirdmajorresultisthatthedifferentpathwaysfollowedbyyoungnon‐completersstraightaftercompletingcompulsoryschool,arestrong‐lyrelatedtotheirlabourmarketoutcomesinadulthoodalsoaftertakinginto account differences in family background. This implies that alsoevidence concerning young people’s early school and labour marketexperiencescontainsvaluableinformationforpoliciestargetedatyouth.

Last,butnotleast,ourfindingsshowthatthedistributionofyouthin‐tostudyandemploymentactivitiesversusNEETactivitiesconvergesinadulthoodacrossthefourNordiccountries.Thissuggeststhatthemeritsof different upper secondary education systems should perhaps, firstandforemost,bejudgedbytheirimplicationsforskillsandincomefor‐mationratherthanbytheirmeritsintermsof“producing”NEETs.

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Sammanfattning

Ungaiåldern16–20årgöroftaolikavägvalnärdetgällerutbildningochplaneringinförsittframtidayrkesliv.Samtidigtsägsdettavaradentids‐periodilivetsomärdenmestkritiskamedtankepåsenarearbetsmark‐nadsutfall.Medandraord,devägarsomdeungahändelsevisväljerun‐derdeförstaårenefteravslutadgrundskolakommerhögstsannoliktattpåverkaderasframtidamöjligheterochutfallpåettavgörandesätt.Detcentralai föreligganderapportharvaritattundersökahurdessatidigavägvalserut,samtattutforskaderaskopplingtilldeungasarbetsmark‐nadsutfallivuxenlivet.

Ivårstudie följervi trekohorteravungdomar:de som fyllde16år1993, 1998 och 2003. Alla dessa ungdomar, som representerar totaltfyra nordiska länder –Danmark, Finland,Norge och Sverige, har följtsfram till år 2008, vilket innebär att den längsta uppföljningsperiodenomfattar15år.

I de nordiska länderna inleder en stor majoritet grundskoleeleverfortsatta studier, antingen direkt eller efter ettmellanår, och studerarmerellermindreoavbrutetframtill20årsålder,vanligtvisännulängre.Mångaungagöremellertidocksåenheltandravägval,vilkaoftakantasav riskfyllda faser såsom längre perioder utanför både utbildning ocharbetsmarknad.Ivåraanalyserharvianväntensåkalladklusterteknikförattgrupperadeungaiolikaklusterberoendepåvilkavägvaldegjortefteravslutadgrundskola.

Genom hela rapporten görs konsekvent en distinktionmellan ungasomhar fullföljt sina fortsatta studier efteravslutadgrundskola senastvidfyllda21år,ochungasomfortfarandeendasthargrundskoleexamensom21‐åringar.7Tyngdpunkten i rapporten liggerpåden senarekate‐

──────────────────────────7Ivårrapportavserfortsattastudierefteravslutadgrundskoladetsompåengelskakallasuppersecondary

educationochsommotsvararISCED3.Generelltkandennautbildningsnivåbetecknassomutbildningpåmellannivåefteravslutadutbildningpålägreochhögregrundnivå(=grundskola).Dennautbildningpåmellannivåäremellertidolikautformadocksåidenordiskaländernaochbeskrivsdessutommedolikamerellermindreofficiellatermer.IDanmarkanvändsnumeratermen”ungdomsuddannelse”.IFinlandtalarmanom”fortsattastudiereftergrundskolanidenallmänbildandegymnasieutbildningenochyrkesutbildningen”,medanmaninomutbildningsförvaltningentalaromandrastadietimotsatstillgrundnivå(=ISCED1&2).I


gorinavunga.Dessutomlyftervi framskillnadermellankönen, liksommellandetreundersöktaungdomskohorterna.

NärdetgällerdenordiskaländernakanDanmarkochSverigenärm‐ast beskrivas somvarandrasmotpoler i fråga omden fortsatta utbild‐ningen efter avslutad grundskola, särskilt yrkesutbildningen. Danmarkharettvälutvecklat system för lärlingsutbildningsomgerdeungaom‐fattandearbetsplatsförlagdpraktik,medanyrkesutbildningeniSverigeihuvudsak kan beskrivas som skolbaserad, även efter reformen somträdde ikraft2011.Dennaskillnad i ländernasutbildningssystemefteravslutadgrundskolaavspeglastydligt ideungas levnadsbanorframtill20årsålderochdärföräveniandelenungasomvidengivenålderfull‐följt sina studier efter avslutad grundskola. I Sverige fortsätter den ty‐piska unga att studera i tre år efter avslutad grundskola och andelenungasomintefullföljtsinafortsattastudiersom21‐åringarärsomhögst17%idetreungdomskohorterna.IDanmark,åandrasidan,ärmotsva‐randeandelungasåhögsom39%i1998årsungdomskohort(ochend‐ast något lägre i de andra två kohorterna). Situationen i Norge liknarmerdeniDanmarkäniSverige,medenandelungapåsomhögst32%somharenbartgrundskoleexamenfortfarandevid21årsålder.Finlandsermerut somSverigeänsomDanmarkellerNorge,medenandelpåknappt20%sominteännuvid21årsålderavlagtnågonexamenefteravslutadgrundskola.

Det är anmärkningsvärt att även när vi begränsar analysen till deunga som fortfarande som 21‐åringar inte avlagt någon examen efteravslutadgrundskolasåvisardetsigattenbetydandedelavdemfortsattstudera,menutanatt lyckasslutförasinastudierinomfemårefterav‐slutad grundskola. När vi gör en gemensam nordisk klusteranalys fördessa ungdomar finner vi att 58% av de finländska ungdomarna harfortsattsinastudierefteravslutadgrundskola,antingendirektellerefterett mellanår, men utan att ha avlagt examen som 21‐åringar. Motsva‐rande andel förDanmark är ca 62%, förNorge ungefär 71%och förSverigenästan76%.Dessaandelarvittnaromattävenomdehärung‐domarnaintelyckatsfullföljasinafortsattastudierännuvid21årsåldersåhardeoftast tillbringat störstadelen av tiden efter avslutad grund‐skola i utbildning.Den här andelen unga har dessutomökat över tid isamtligafyraländer,vilketframgårnärmanjämförsituationenidetreungdomskohorter som vår studie bygger på. Knappt 64% av de nor‐diskaungai1993årskohortsomfortfarandesom21‐åringarinteavlagt

Norgeanvändstermen”videregåendeavsluttendeutdanning”medanmaniSverigeanvänderbegreppet”utbildningpågymnasialnivå”.


någon examen efter avslutad grundskola hade fortsatt studera eftergrundskolanantingendirektellerefterettmellanår.Andelenhadeökattillnästan70%i2003årskohort.

Ennågotmerdetaljeradanalysavdessaungdomarutgåendefrånde‐ras huvudsakliga verksamhet efter tre eller färre år i fortsatta studierefter avslutad grundskola, utvisar att fortsatta studier är den övervä‐gandevanligasteaktiviteten:iDanmarkärca39%,iNorgeochSverigenästan37%ochiFinlandomkring35%avdessaungahuvudsakligeniutbildningunderdefemförstaårenefteravslutadgrundskola.Enannanviktiggruppbildardeungasombörjatarbetaiställetförattfullföljasinafortsattastudierefteravslutadgrundskola:avdedanskaungdomarsomfortfarandesom21‐åringarsaknarexamen från fortsattastudierdykernästan36%upp idenhär jobbdomineradekategorin,medanmotsva‐randeandelärknappt31%förFinland,närmare28%förNorgeochca25%förSverige.Menmedanviserentydligökningövertidavandelenunga som fortsätter i utbildning utan att avlägga examen, så förefallerdetintefinnasnågongemensamnordisktrendfördeungasomavbrutitsinafortsattastudierförarbete:iSverigevisarandelenungamedenbartgrundskoleexamen sombörjat jobba enökningöver tid,medan situat‐ionenärdenmotsattablanddedanskaårskullarna.Överlagtyderresul‐taten på att ungas vägval efter avslutad grundskola domineras av an‐tingenfortsattastudierellerjobbellerenkombinationavdessa.Dehärvägvalenärdemestframträdandeävenblanddeungdomarsomfortfa‐randesom21‐åringarsaknarexamenefteravslutadgrundskola.Dessu‐tomupprepassammamönsterisamtligafyranordiskaländersomingårivårstudie.

Restenavdeungasomfortfarandevid21årsåldersaknarexamenef‐ter avslutad grundskola tenderar att höra till den så kallade NEET‐gruppen, vilket innebär att de antingen är arbetslösa eller befinner sigheltutanförarbetskraften(=inaktiva, inklusiveungamedfunktionshin‐der).Andelen21‐åringarmedenbartgrundskoleexamensommestadelsvarit arbetslösa under de fem första åren efter avslutad grundskola ärnära 17% i Sverige, medan motsvarande andel är ca 12% i Finland,drygt9%iNorgemenunder5%iDanmark.Förtidspensioneringarfö‐rekommersällan;andelenärhögst(ca4%)förSverigeochlägst(endast1,3%)förDanmark.Däremotärandraformeravinaktivitetmycketvan‐ligt förekommande bland unga som fortfarande som21‐åringar saknarexamenefteravslutadgrundskola.AndelenärsärskilthögförNorgeellerca25%.FörDanmarkochFinlandstannarandelenstraxunder20%,ochförSverigeärdenca17%.


Dessa relativt stora skillnadermellan de nordiska ländernasNEET‐andelar minskar dock märkbart om andelen unga som huvudsakligenföljt NEET‐dominerade vägar efter avslutad grundskola relateras tillhelaungdomspopulationenochinte,somovan,tillpopulationenavungasom fortfarande som 21‐åringar saknar examen efter avslutad grund‐skola:ca10%avbådedanskaochnorskaungdomarkankarakteriserassom unga som har enbart grundskoleexamen på grund av att de i etttidigt skede efter avslutad grundskola hamnat utanför både utbildningoch arbetsliv. Motsvarande andel för Finland och Sverige är ca 6 %.Detta innebär att den betydligt lägre andelen danska och norska unga(jämförtmed finländska och svenska unga) som fullföljt sina fortsattastudier senast vid 21 års ålder, inte bör tolkas som att danska ochnorskaungauppvisarenklarthögreriskatthamnaienNEET‐situationefteravslutadgrundskolautansnararesomattdeharenstörretendensattfortsättaiutbildningellerbörjajobbautanattännusom21‐åringarhaavlagtexamenefteravslutadgrundskola.

Slutligenundersöktevideungasarbetsmarknadsutfallvid21,26re‐spektive31årsålder.Av21‐åringarmedexamenefteravslutadgrund‐skolavarca90%iantingenutbildningellerarbete.Sammaellerännustörreandelarnoteradesfördehögreåldrarna.Vid26årsåldervarmerän 67 % av de svenska ungdomar som avlagt examen efter avslutadgrundskola senast som 21‐åringar, sysselsatta jämfört med mellan 59och62%idetreövrigaländerna.Vid31årsålderhadeandelensyssel‐sattablanddessaungaökattillöver85%iDanmarkochSverigeochtillca76% iFinlandochNorge,medanandelensom fortfarandevar iut‐bildning hade vanligtvis sjunkit till runt 10 %. Omvänt var NEET‐andelenblanddessaungaiallafyraländerrelativtlåg,ca13%iNorgeochunder5%iDanmark.

Situationen ser helt annorlunda ut för de unga som ännu som 21‐åringar saknade examen efter avslutad grundskola, även om en påfal‐landestordelavocksådessaungdomarantingenstuderarellerarbetarivuxenålder.Vid31årsålderärdenhärandelennärmare84% fördedanskaungdomarsomfortfarandevid21årsålderhadeenbartgrund‐skoleexamen,medanmotsvarandeandelärca74%förSverigeochom‐kring 70% för Finland och Norge. Men i den här specifika ungdoms‐gruppenfinnerviocksåmångasomvid31årsålderärarbetslösa,erhål‐ler ersättning kopplat till funktionshinder eller befinner sig av andraorsaker utanför både utbildning och arbetsmarknad. Norge sticker utmedenmycketstorandelungautanförutbildningocharbetsliv,medanSverigekännetecknas av en stor andel somerhållernågon formaver‐sättningkopplattillfunktionshinder.Finlandåterharblanddessaunga


en jämförelsevis stor andel som är arbetslösa som unga vuxna, någotsom ihuvudsak speglardenhögaarbetslöshetenunder1990‐taletochsärskiltblanddemmedenbartgrundskoleexamen.

När vi istället relaterar dessa arbetsmarknadsutfall för unga somfortfarandesom21‐åringarsaknarexamenefteravslutadgrundskolatillhelaungdomspopulationen,förändrasdockåterigenskillnadernamellanländerna.Mest anmärkningsvärt är att trots den höga andelen danskaochnorskaungdomarsomfortfarandevid21årsåldersaknarexamenefteravslutadgrundskolasåärmångaavdemdefactosysselsattasomungavuxna.Vid31årsålderrepresenterarca27%avdendanskaung‐domspopulationensomtäcksavvårstudiesysselsattaungasomvid21årsålderhadeenbartgrundskoleexamen.MotsvarandeandelförNorgeäromkring19%,menendastca10%förFinlandochSverige.Denhärstoravariationeniandelaravspeglarväldetfaktumattländernauppvi‐sarväsentligaskillnader iantaletungasomfullföljersina fortsattastu‐dierförstefterattdefyllt21,ochiallsynnerhetattarbetsmarknadsut‐falletfördessaungaärhögstolikaidefyraländerna.IDanmarkverkardetfaktisktintespelasåstorrollommanfullföljersinafortsattastudiersom 21‐ eller 26‐åring,medan det däremot betyder en hel del om dufortfarande som 31‐åring saknar examen efter avslutad grundskola. ISverige, å andra sidan, är det av avgörande betydelse för arbetsmark‐nadsutfallet om du misslyckas med att fullfölja dina fortsatta studierinom normal tid. Finland och Norge placerar sig mellan dessa två ex‐tremfall.EttannatanmärkningsvärtresultatärattNEET‐andeleniung‐domspopulationenär i stortsettdensamma ide fyra länderna trotsdestoraskillnadernaiandelenungasomfortfarandevid21årsåldersak‐narexamenefteravslutadgrundskola.Sammantaget tyderdessaresul‐tat på att skillnadermellan länder i fråga om de ungas övergång frånskolatillarbetslivintenödvändigtvisäravavgörandebetydelseförlän‐dernasNEET‐grad.Dettatyderisinturpåattdeolikasystemenförfort‐sattastudierefteravslutadgrundskolabörsnarareutvärderaspåbasisavderaseffektpåkunskapsutvecklingenochdenlångsiktigaproduktivi‐teten,samtdekostnaderdegerupphovtill.

Detfinnsenomfattandelitteratursomstöderantagandetattskolre‐sultatoch i sistahandarbetsmarknadsutfall ärnära relaterade till denungas familjebakgrund. Också våra resultat stöder detta antagande.Följaktligenärdetavintresseattundersökaomsambandetvisermellantidigaochsenareutbildnings‐ocharbetsmarknadserfarenheteregentli‐genärenkopplingmellanfamiljebakgrundochsenarearbetsmarknads‐utfall.Våraresultat tyderpåattsåabsolut inteär fallet:devägvalsomungdomargörefteravslutadgrundskolaäravstorbetydelseocksåefter


attvikontrollerat förväsentligaskillnader ideungas familjebakgrund.Framför allt ser vi tilltagande så kallat situationsberoende (eng. state‐dependence)blandungasomietttidigtskedeefteravslutadgrundskolahamnat i en situation somdomineras avNEET‐aktiviteter. Tidiga erfa‐renheteravarbetslöshetvisarsigiformavenklartökadriskattbliar‐betslös somungvuxen.Ersättningarkopplade till funktionshinder ten‐derarattfortsättainivuxenlivet.Tidigaerfarenheteravandraformeravinaktivitetmedförökad risk att denunga stannar utanförbådeutbild‐ningocharbetsmarknadocksåsomungvuxen,varvidersättningtillföljdav funktionshinder ofta blir den slutliga lösningen. Därmed hävdar viemellertid inte att det förekommer ett kausalt sambandmellan tidigautbildnings‐ocharbetsmarknadserfarenheterochsenareutfall.Sammaunderliggandeorsak,såsomexempelvisfunktionshinder,kanmeränvälpåverkabådedeungasväggenomutbildningssystemetochderasfram‐tidaarbetsmarknadsutsikter.Likvälärdethögstsannoliktattdetstarkasambandsomvi finnermellandeungas tidigavägvalochsenareutfallsamtidigtavspeglarkausalaelement.Detta innebär i sin turatt,obero‐endeavdenunderliggandeorsaken,såkanempirisktframtageninform‐ationomungasvägvalsomtenderarattledatilloönskadeutfallanvän‐dassomviktigtbakgrundsmaterialdåmaneftersträvaratt föraenmermålinriktadungdomspolitik.

Sålundakanvårrapportsammanfattasiformavfyrahuvudresultat:Det första huvudresultatet pekar på stora skillnadermellande fyra

studeradenordiska ländernavadgällerungasomsaknarexamenefteravslutadgrundskola;skillnadernaärstoravidolikaåldrarochkvarstårocksåblandungavuxna.IFinlandochSverigeärandelenungameden‐bart grundskoleexamen relativt liten redan bland 21‐åringar och om‐kring10%bland31‐åringar.INorge,ochisynnerhetiDanmark,äran‐delen21‐åringarutanexamenefteravslutadgrundskolabetydligtstörreävenomdensjunkertillomkring20%för31‐åringar.Detattmanavslu‐tar sina fortsatta studier först efter fyllda 21 är särskilt vanligt blandungaiDanmark.

Enandrahuvudsakligslutsatssomdärtillgällersamtligafyraländerär att även om avsaknaden av examen efter avslutad grundskola ökarriskenförsämrearbetsmarknadsutfallivuxenålder,såärsysselsättningochutbildningdeheltdominerandeaktiviteternaändauppitrettioårs‐åldern också bland de ungdomar som har enbart grundskoleexamenfortfarande vid 21 års ålder. Enbart grundskoleexamen ännu som 21‐åringinnebärsålundainteattdenungakanautomatisktklassassomenpersonsomiett tidigtskedelämnatallutbildningbakomsigellersom


en person som avbrutit sina studier till följd av allvarliga ekonomiskaochsocialaproblem.

Ett tredje viktigt resultat är att de tidiga vägval som de ungdomargjort som fortfarande vid 21 års ålder saknar examen efter avslutadgrundskola är starkt relaterade till deras arbetsmarknadsutfall somungavuxnaocksåefterattvibeaktatskillnaderiungdomarnasfamilje‐bakgrund.Detta innebär att empiriska resultat gällande ungdomars ti‐digautbildnings‐ocharbetsmarknadserfarenheterkanbidramedvärde‐fullinformationnärdetgällerattutformaåtgärderriktademotunga.

Slutligen utvisar våra resultat att ungdomarna i de fyra studeradeländerna fördelar sig rätt olika mellan dels studier och sysselsättningochdelsNEET‐aktiviteter,menocksåattdessaskillnaderminskaribe‐tydande utsträckning när ungdomarna når vuxen ålder. Detta antyderatt fördelarna med olika utbildningssystem för fortsatta studier efteravslutadgrundskolabörkanskei förstahandutvärderasutgåendefrånhur de påverkar kunskaps‐ och inkomstbildningen snarare än i vilkenutsträckningde”producerar”NEET‐unga.

Appendix: Descriptions of national datasets used

Denmark

TheDanishdatasetusedintheprojectiscompiledfromregisterdataatStatistics Denmark. The dataset encompasses three cohorts of youngDanish residents. The first cohort contains all residents,whowere 16yearsold in1993,andtheyarefolloweduntil theyare31yearsold, in2008. The second cohort consists of Danish residents, who were 16years old in 1998. They are followedup to age 26, in 2008. The thirdcohortconsistsofDanishresidents,whowere16yearsoldin2003,andtheyarefolloweduntiltheyare21yearsold,in2008.

Statistics Denmark has supplied various kind of information fromregisters inStatisticsDenmark for theyoungpeople in these three co‐horts.Theresult is linkeddataconstructedforuse intheanalysespre‐sentedinthisreport.

Themain information used for the project is register‐based labourforce statistics (Registerbaseret Arbejdsstyrkestatistik – RAS) that as‐signeachDanishresidenttooneandonlyonestateintheDanishlabourmarketatoneparticularpointintime(theendofNovembereachyear).This statistic follows the international guidelines of the InternationalLabour Organization (ILO) for assessments of the attachment of thepopulationtothelabourmarket.TheILOguidelinesareprimarilyusedin relation to interviews,where each person answers questions abouttheattachmenttothelabourmarket.RASusestheguidelinestochoosetheappropriate labourmarketstate.TheDanishclassification isratherdetailed and presently contains 62 different categories, seehttp://www.dst.dk/da/Statistik/dokumentation/Times/ida‐databasen/ida‐personer/pstill.aspx.

Anothermainsourceofinformationisstatisticsoneducation.Thesestatisticscontainthecurrentandfinishededucationonadetailedbasis.We have also linked the young people in the three cohorts to infor‐mationonparentalbackground.Thisbackgroundincludestheeducationandtheincomeoftheparents(asobtainedfromtaxregisters).

http://www.dst.dk/da/Statistik/dokumentation/Times/ida%E2%80%90databasen/


Finland

Theproject uses the linkedemployer‐employeedata (FinnishLongitu‐dinalEmployer‐EmployeeDataFLEED)thatStatisticsFinlandhascreat‐ed forresearchuse.TheFLEEDdataconsistsofpersonsaged15to70livinginFinlandbetween1988and2011(excl.Åland).Thepersonshavebeenfollowedovertime,sothereisdataonthepersonforalltheyearsduringwhich the person has been alive, aged between 15 and 70 andresiding in Finland. The FLEED data includes information on the per‐son’s basic characteristics, family, living, employment relationships,periodsofunemployment,incomeandeducation.

The FLEED data is based on employment statistics that are annualstatisticsprovidingdatabyregiononthepopulation’seconomicactivityand employment. The population for the statistics is the permanentlyresidentpopulationinthecountryonthelastdayoftheyear.Thedataaremainlyderivedfromaround40administrativeregistersandstatisti‐caldatafiles.

Theproduceddatadescribethepopulation’smaintypeofactivity,oc‐cupation, status in occupation, number ofworkplaces, location ofwork‐place,andeducationandincomeofthepopulationandlabourforce.Thereferenceperiodofthestatisticsisthelastweekoftheyear,butthestatis‐tics also contain data accumulated during the statistical reference year(e.g.incomedata,monthsofemploymentandunemployment).

Thepopulationanddefinitionsof the employment statisticshave re‐mainedmoreorlessthesamesince1987,whenregularproductionofthestatisticswas started. However, the classifications used in the statisticshavechangedalongtheyears.Forexample,theStandardIndustrialClassi‐ficationwas amended in 1993, 2001 and 2007 and the Classification ofOccupationsin1995and2010.Thechangesintheclassificationshaveaneffectonthecomparabilityoftheyearsbecauseithasnotbeenpossibletobuildcompleteconversionkeysbetweenalltheclassifications.

Sources http://tilastokeskus.fi/tup/mikroaineistot/

me_kuvaus_henkilo_en.pdf

http://www.stat.fi/meta/til/tyokay_en.html

http://tilastokeskus.fi/tup/mikroaineistot/

http://www.stat.fi/meta/til/tyokay_en.html


Norway

TheNorwegiananalysesusedatafromFD‐Trygd,anadministrativeda‐tabasecompiledbyStatisticsNorway.Thedatabaseconsistsof severalwelfareandemploymentregistersattheindividuallevel,togetherwithdemographic information such as age, gender, parents’ education andincome,etc. Informationabouteducation isgatheredfromNUDB(Nas‐jonal Utdanningsdatabase). The different registers are linked togetherbyauniqueidentificationkey,whichmakesitpossibletofollowindivid‐ualsasthey“move”betweendifferentlabourmarketandwelfarestates,aswellastoandfromeducation.

The data used in this project encompasses all Norwegian residentswho have started an upper secondary education during the period1992–2008. Thismeans thatwe lack information about youthwho donotenrol inupper secondaryeducation in this timeperiod.Theenrol‐mentrateinNorwayisveryhigh–around96–97%ofeachyouthcohortenrolinuppersecondaryeducationthesameyeartheyfinishcompulso‐ryschool.Among thosewhodonothaveadirect transition fromcom‐pulsory to upper secondary school, almost 70% have enrolled withinfiveyearsaftercompletingcompulsoryschool(FalchandNyhus,2009).This means that the data covers practically the entire population ofNorwegianyouth,butthebias is likelytobe larger fortheyoungerco‐hortsastheyareobservedforfeweryears.TableA1showsthebiasforthethreeyouthcohortsusedinthisproject.

Table A1. Youth cohorts in the data and full population, Norway

Cohort of

16‐year‐olds

Number of youth in the

project data

Number of youth in full

population

Difference between data

and full population

1993 51,012 51,282 ‐270

1998 51,394 52,029 ‐635

2003 53,758 55,524 ‐1,766

Notes: The full population numbers are gathered from Statistics Norway. All numbers comprise

youth who turn 16 in 1993, 1998 or 2003 and who are resident in Norway the following five years.

Thefollowingregistersareusedinordertoclassifytheyouthintothefivemain activity categories: Ongoing education (Student); Employ‐ment (Employed); Maternity benefit and sickness benefit (Em‐ployed); Conscripts (Employed); Job seekers and occupationallyhandicapped(Unemployed);Rehabilitationandvocationalrehabilita‐tion allowance (Pensioner); Temporary disability benefits (Pension‐er); Disability pension (Pensioner); Social assistance (Other). In or‐der tomake thedatacomparable to theothercountries’data in this


project,we useDecember as our referencemonth. The exception isongoingeducation,whichismeasuredinOctobereachyear.

Sweden

TheSwedishdata isbasedonseveral registers fromStatisticsSweden.The major data source is LISA (Longitudinal integration database forhealth insurance and labour market studies), a longitudinal databasecoveringeducation,incomeandemployment.Thepopulationconsistsofall over 16‐year‐old nationally registered individuals during the years1960–2012. Thismeans that a large part of the Swedish population isfollowedovera longperiodof time. Informationon the indexpersons’biological siblings, half siblings on each parent’s side, spouses and allpersonsresidinginthehouseholdisaddedtothedatabase.Thedifferentregistersarelinkedtogetherbyauniqueidentificationkey,whichmakesitpossible to follow individualsas theymovebetweendifferent activi‐ties. The material also covers variables representing the individuals’demographic and socio‐economic status. These additional variablesmakeitpossibletoestimatetheeffectsoffailingorsucceedingwithvar‐ious upper secondary educations, taking into account the individuals’sex,countryofbirth,parents’levelofeducation,parents’levelofincome,etc.Thus, theeffectsof labourmarketchangeonyoung individuals’ la‐bourmarket careers can be pursued not only from amacro‐economicperspective,butalso fromadetailed,geographicaland longitudinalso‐cio‐economicperspective.

TheSwedishdatausedinthisprojectincludethefollowingmainreg‐isters:Longitudinalintegrationdatabaseforhealthinsuranceandlabourmarketstudies; themulti‐generationalregister; the incomeandwealthregister,theeducationregisterandthetotalpopulationregister.


Table A2. Summary of the number of young people in the four national datasets used

Total All three cohorts Cohort of 16‐year‐olds


Denmark 164,879 85,190 79,689 56,710 51,055 57,114

Finland 193,567 99,211 94,356 65,595 67,068 60,904

Norway 156,164 79,924 76,240 51,012 51,394 53,758

Sweden 290,257 149,713 140,544 90,611 92,495 107,151

Completers All three cohorts4 Cohort of 16‐year‐olds


Denmark 103,203 49,046 54,157 36,932 31,071 35,200

Finland 158,611 78,474 80,137 55,088 53,847 49,676

Norway 109,723 53,000 56,723 36,451 36,434 36,838

Sweden 243,763 123,438 120,325 77,498 76,790 89,475

Non‐completers All three cohorts Cohort of 16‐year‐olds


Denmark 61,676 36,144 25,532 19,778 19,984 21,914

Finland 34,956 20,737 14,219 10,507 13,221 11,228

Norway 46,441 26,924 19,517 14,561 14,960 16,920

Sweden 46,494 26,275 20,219 13,113 15,705 17,676

Youth unemployment and inactivityA comparison of school-to-work transitions and labour market outcomes

in four Nordic countries

Ved Stranden 18DK-1061 Copenhagen Kwww.norden.org

Young people follow highly different trajectories from age 16 up to age 20, a time period which is often argued to be the most critical in terms of their future labour market outcomes. The focus of this report is on investigating the look of these early pathways, as well as on exploring their link to labour market outcomes in adulthood. Results are reported and compared for four Nordic countries: Denmark, Finland, Norway and Sweden.

Youth unemployment and inactivity

TemaN

ord 2015:548

TemaNord 2015:548ISBN 978-92-893-4229-2 (PRINT)ISBN 978-92-893-4230-8 (PDF)ISBN 978-92-893-4231-5 (EPUB)ISSN 0908-6692

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ord 2015:548

TN2015548 omslag.indd 1 20-07-2015 12:48:57

youth unemployment and inactivity

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