DepartmentofSociology
HighlyEducatedSelf-EmployedPersonswithandwithoutMigrationBackgroundinaHighlyRegulatedEconomy. TheCaseofAustria
03/2017
Editorialteam:MirjamPotCorneliaSchadlersoz.univie.ac.at/forschung/working-papers
Highlyeducatedself-employedpersonswithandwithoutmigrationbackgroundinahighlyregulatedeconomy.
ThecaseofAustria.
SabrinaLaufer
SabrinaLauferreceivedaresearchawardbytheAustrianEconomicChambersin2015.Herresearchinterestsarefocusedontheexplorationofself-employmentinAustriaandsocialmobility.Sheisinterestedinapplyingtheoreticalconceptsanddevelopingpolicyrelevantanalysis.Whileshepreferstoworkwithquantitativemethods,sheregardsqual-itativemethodsasaninvaluablecomplement.Sheiscurrentlyworkingonthecomple-tionofherthesis‘Employmentchancesandrisksofself-employedpersonswithandwithoutmigrationbackgroundinAustria.Anempiricalstudyusingthemicrocensusandasupplementaryonlinesurvey.’paralleltoherjobatStatisticsAustriawhereshehasbeenemployedsince2009.Attheendof2008shefinishedherstudiesinSociology,Psy-chologyandPoliticalScienceinJena.
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Abstract
Fromaneconomicpointofviewself-employedpersons(withmigrationbackground)makevalu-ablecontributionstosociety,forinstanceasemployers.Fromasociologicalpointofviewitisin-teresting to evaluate the causesof (migrant) self-employment in timesof social andeconomicchange intransnationaleconomies.Thus,whatarethereasonsforself-employmentandwhichopportunitiesandrisksareinvolved?Whichsocialgroupsfaceadvantagesandwhichfacedisad-vantages?Basedonrepresentativedata,theAustrianmicrocensus,thispaperpresentsanover-viewof four typesof self-employmentbymigrationbackgroundbetween2004and2015. Fur-thermore,thearticlefocussesononetypebylogitregressionsforthereferenceyear2015.Sev-eral variables on different levels were tested. The results indicate that the likelihood of self-employmentamongpersonswithhigheducationandpost-industrialoccupations is thehighestformen,personsover40,part-timeworkers,personsworking fromhome,personsworkingonweekendsandhouseorapartmentowners.Hence,thefindingsoutlinealabourmarketsegmen-tationbycountryoforiginandgender,flexibilisationofworkandhighrelevanceofhomeowner-ship.Itishopedtoprovidecontentsforpolicymakersforthepurposeofbuildinginstrumentsforregulations.
Zusammenfassung
Aus ökonomischer Perspektive leisten selbständig tätige Personen (mitMigrationshintergrund)wertvolleBeiträgezurGesellschaft,zumBeispielalsArbeitgeberinnenundArbeitgeber.Aussozi-ologischerSichtistesinteressant,dieUrsachender(Migrantinnen-undMigranten-)Selbständig-keit inZeitensozialenundwirtschaftlichenWandels in transnationalenÖkonomienzuuntersu-chen.DaherstelltsichdieFrage,wassinddieGründefürdieSelbständigkeitundwelcheChancenundRisikengibtes?WelchesozialenGruppenhabenVorteileundwelchehabenNachteile?Aufder Grundlage repräsentativer Daten, demösterreichischenMikrozensus, präsentiert diese Ar-beiteinenÜberblickübervierTypenselbständig tätigerPersonenmitundohneMigrationshin-tergrundzwischen2004und2015.EinTypuswirdanhandvonlogistischenRegressionenfürdasReferenzjahr2015näheruntersucht.MehrereVariablen,aufverschiedenenEbenen,werdenge-testet.DieErgebnissezeigen,dassdieWahrscheinlichkeitselbständigzusein,unterPersonenmithoher Bildung und postindustriellen Berufen, am höchsten ist für:Männer, Personen über 40,Teilzeitbeschäftigte, Personen, die von zu Hause aus arbeiten, anWochenenden arbeiten undHaus-oderWohnungsbesitzerinnenund-besitzer.EszeigtsicheineArbeitsmarktsegmentierungnach Herkunftsland und Geschlecht, Arbeitsmarktflexibilisierung und hohe Relevanz von Haus-/Wohnungseigentum.DieseAnalysenkönneneinenBeitragzurBildungvonpolitischenEntschei-dungenleisten.
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Introduction
From an economic point of view self-employed persons (withmigration background1)
make valuable contributions to society. They are an essential social and economic re-
source. If self-employed2 – as various academic studies have pointed out – then they
makeacontributiontotheinternationalisationofthemiddleclassandcreationofjobs.
Fromasociologicalpointofviewitisinterestingtoevaluatethecausesof(migrant)self-
employmentintimesofeconomicchangeandrestructuringintransnationalandemerg-
ingeconomies.Therefore,thequestionariseswhatarethereasonsforself-employment
andwhich opportunities and risks are involved?Which social groups face advantages
andwhichfacedisadvantages?Previousstudiesinthisfieldhave,toalargeextent,re-
liedonqualitative researchmethods as self-employment is heterogeneous and there-
forenotaneasilycomparablephenomenon.Againstthisbackground,thispaperintends
tomakeacontributiontothefollowingresearchquestions,whichareinvestigatedusing
amixedmethodsdesign:Whattypesofself-employedpersonsarethere?Whichcharac-
teristicsinfluencewhetherapersonisself-employedoremployed?Arethesecharacter-
isticsrelatedtotheworkplace,household,personorregion?Furthermore,whatarethe
differencesbetweenpersonswith andwithoutmigrationbackground? The analysis of
thedeterminantsofself-employmentareofgreatimportancetogenerateknowledgeon
this specific segment of the labourmarket. Such information provides indications for
policymakersand,lastbutnotleast,furthersthedevelopmentoftheoryinthefield.
Starting from an interactive approach for the explanation of self-employment (mixed
embed-dedness),typesaretheoreticallyderivedand,forthefirsttime,alsoappliedem-
pirically.Onthebasisofmicrocensusdata,thedistributionoftypesovertimeisshown
whileonetypeisanalysedinmoredetailusinglogisticregressions.Theresultsindicate
that the likelihood of self-employment among personswith high education and post-
1 In this study, a person with migration background means she or both her parents are born outside of Austria. The term migrant is used concurrent to migration background. 2 In this study a self-employed person may have an employee or not, or is a freelancer (excluding economic branches of agriculture, forestry and fishing/public administration). Thus, the focus of the study are nearly all self-employed persons.
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industrialoccupations3ishighestformen,personsover40,part-timeworkers,persons
working from home, personsworking onweekends and house or apartment owners.
Theresultsbyregionrespectiveoftheircountryoforiginhavetobeobservedinamore
differentiatedway.Forinstance,womenfromthesecondgenerationorfromGermany
orfromaEU25countryorfromanon-Europeancountryhaveahighprobabilityofbeing
self-employed.
Inthemainpartofthispaper,IwillfirstreflectontheAustriancaseandthereasonsfor
analysingtheself-employmentstructure.Secondly,Iwillgiveabriefoverviewofthere-
searchon self-employment (forAustria and internationally) and thirdly, themethodo-
logicalsteps,theuseddataandthekeyfindingswillbepresented.Theresultssuggesta
labourmarketsegmentationbycountryoforiginandgender,flexibilisationofworkand
highrelevanceofhomeownership.Thisresearchmakesacontributiontotheoryonmi-
grant entrepreneurship by applying the typology of opportunity structures over time
andtheexplanationoffactorsinfluencingself-employmentofmigrantsandnatives.
Reasonsfordoingresearchonself-employmentinAustria
Why is researchonself-employment (still) importantandwhy isAustriaan interesting
countrytoexamine?Onereasonself-employmentisstillrelevantisthatthestrategyof
theEuropeanCommissionistoincreasetheself-employmentrateby2020(Europäische
Kommission, 2013). Policy makers need benchmarks and country specific knowledge
aboutthelabourmarketmechanismfordevelopinginstrumentstoregulatetheecono-
my. Another reason is that economies are changing due to globalisation. Self-
employment isanessentialemploymentfactor inpost-industrialsocietiesasoutsourc-
ing,fragmentingofmarketsandtheincreasingservicesectorarecausingtheriseof it.
Thereisashiftawayfromemploymentinlargefirmstoself-employmentinsmallones
(Volery, 2007). This studyaims to contribute toa greaterunderstandingabout the la-
bourmarketandthedriversofself-employmentinAustria.
3 Post-industrial occupations are, for instance, scientists.
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Austriaisaninterestingcaseasthelabourmarketishighlyregulatedandthecollective
paymentcommitmentisveryhigh(Haberfellner,2003).Oneexampleforregulationare
market-basedinstruments(activelabourmarketpolicy).Theseareusedtoinfluencethe
behaviour ofmarket participants (WKO, 2015). Another reason for doing research on
self-employmentinAustriaisthattheself-employmentrateandtheunemploymentrate
arerising(WKO,2016a,2016b).Nexttothis,theshareofpersonswithmigrationback-
ground and university degrees is higher than the one for persons without migration
background(18.6percentforpersonswithmigrationbackgroundvs.16.4percentfor
personswithoutmigrationbackground)(StatistikAustria,2015a).Incomparisontooth-
er member states, Austria has a low self-employment rate. Also in Austria the self-
employmentrateofpersonswithmigrationbackgroundintotalislowerthantherateof
personswithoutmigrationbackground.Theycanbefacedwithproblems,suchasexist-
ingstereotypes inpublicopinion, low income,ethnic labourmarketsegmentation,de-
qualification,marginalisationandresidentialsegregation(Asselinetal.,2006;Fassman,
1997;Krause&Liebig,2011;OECD,2013;Schmatz&Wetzel,2014).
Thesereasonsareacausetopaintadifferentiatedpictureaboutself-employedpersons
withandwithoutmigrationbackground.Furthermore,thesubgroupofhighlyeducated
personshave thehighest self-employment rate (aswill be shown later).Are theypre-
destinedtoincreasetheself-employmentrateinAustria?
Researchonself-employment
Self-employedmigrantshavegainedattention inAustria.The first systematic research
on themwas undertaken around themillennium (Haberfellner, Betz, Böse, & Riegler,
2000).Theycanbefacedwithdiverseproblems.Nexttoracistattitudes,publicopinion
isoftencharacterisedbystereotypesandassociatesmigrantenterpriseswithstructural
marginalisation. Visible self-employedmigrants are often the small andmedium sized
enterprises(SMEs)inpublicspaces,suchaskebabandpizzabusinesses.Thetrendofre-
centyears,resultingfromtheEUEasternenlargement,showsaheterogeneouspicture
ofthisself-employmentgroupinAustria(Haberfellner,2011).Studiesshowahighcon-
centrationofself-employedmigrantsinViennaandLowerAustria(Schmid,Mandl,Dorr,
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Staudenmayer,&Haberfellner, 2006). In total, thosewhoare self-employedandborn
outsideofAustriaaremorehighlyeducatedthanthoseborninAustria(OECD,2013).
Themostcloselyrelatedstudytothepresentoneisaboutdifferencesofimmigrantsand
nativesinSweden(Ohlsson,Broomé,&Bevelander,2012).Thekeyfindingsofthisstudy
are: the country of birth has little influence on the individual’s propensity to be self-
employed,butitismoreimportantthanthelabourmarketarea(Ohlssonetal.,2012,p.
420).Theauthorsconcludethatthelargestpercentageofvariancecanbeexplainedby
individual variables and not by the immigrant/ethnic background. Another study that
raisesattentiontoethnicorigin,locallabourmarketsandself-employmentsuggeststhat
futureresearchonimmigrantself-employmentshouldfocusonthemechanismbehind
the immigrant’s self-employment decision (Andersson, Hammarstedt, Hussain, &
Shukur,2013).Differenttypesofsurveysmightbehelpful tounderstand, for instance,
thecareerpathsoftheself-employedperson.
Research onmigrant entrepreneurship/self-employment shows uncertainty about the
causesthatdriveself-employment.It isstillunclearif it istheindividualorthecontext
levelthatmatters.4Thereisresearchaboutthepushandpullfactorsforcreatingabusi-
ness (inAustria) (Enzenhoferetal.,2007;Schmidetal.,2006).Qualitativeresearch5 in
Austriashowsadominationofthemotives‘self-realisation’,‘beingyourownboss’and
‘realisinganidea’(Schmidetal.,2006).Forself-employedpersonswithmigrationback-
grounddoingbusinessinlessprofitablebranches,suchasretailorgastronomy,itisas-
sumedthattheyarepushedintobusiness(push-factor).Itisnotclearifthisisthecase
forAustria (Schmidetal., 2006).However,problems for somepersonswithmigration
backgroundontheAustrianlabourmarketaredequalificationandlowincome(Schmatz
&Wetzel,2014;Stadler&Wiedenhofer-Galik,2011).Especiallyforthirdcountrynation-
alswho arewilling towork as a self-employee in a regulated trade6 Austria does not
provide full and automatic labourmarket access for immigrants. Dissimilar education
andworkbiographiesof immigrantsandnativesaremakingthedifference.Therefore,
4 A well elaborated classification of contexts is provided by Friederike Welter (Welter, 2011). 5 A quantitative study for Vienna shows that 14 per cent are pushed into self-employment, 41 per cent are pushed and pulled and 45 per cent are pulled (Schmatz & Wetzel, 2014). 6 The German term is ’reglementiertes Gewerbe’.
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immigrants see theneed toemploy amanagerwith the required skills (Schmidet al.,
2006).Additionally,theregulativeframeworkismostlydispersedandcomplex.Theas-
sessmentandrecognitionofforeignqualificationsinvolves,forinstance,fourministries
andthereareamultitudeofdifferentproceduresinplacedependingontheorigin,do-
mainandlevelofdegree(OECD,2012).
Theoreticalstartingpoint
The theoretical startingpoint of this research is the typologyof opportunity structure
developed by Kloosterman and Rath (Kloosterman& Rath, 2011). The theoretical ap-
proach behind their typology is calledmixed embeddedness and is an interactive ap-
proach.Interactiveinthiscontextmeansthatseveralvariablesfromdifferentlevelsare
atplaytogether.Thefirstinteractiveapproachwasdevelopedin1990.Waldingeretal.
took variables on the individual and the context level (market conditions, access to
ownership) into account (1990, p. 22). The interactive approach as proposed by
Waldinger et al. (1990) is limited and themixed embeddedness approach further the
approachfromWaldinger.Themainargumentofmixedembeddednessisthatthetype
ofwelfarestate(Esping-Andersen,1990)itselfhasanimpactontheself-employment(of
migrants).Thetypologyofopportunitystructures isavaluable instrumentfortworea-
sons: 1) tomeasure and compare types of self-employedpersons, and 2) to compare
themsystematicallyacrossdifferenttypesofwelfarestates.Inaddition,thetypologyof
opportunity structures opens up the possibility to show and compare economic
change(s)ofself-employmentinacountry(developmentovertime).
In1999thefirstarticleonmixedembeddednesswaspublished(Kloosterman,Vander
Leun,&Rath,1999),andsincethenKloostermanandRathhaveconstantlybeendevel-
opingthisapproach.Theirmainideaisthatcapitalistsocietiesarelinkedtothemarket,
andmarketsplaysacentralroleforinstanceforjobcreation(Kloosterman&Rath,2011,
p.92).Thedifferencebetweenthe interactivemodelofWaldingeretal.andKlooster-
man and Rath is that the latter includemigrants affecting the conditions of the host
country. Furthermore, they point out that migrants can use and expand opportunity
structurestoincludeinterestssuchasapplyingforfundingandimprovinginfrastructure.
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KloostermanandRathdevelopedGranovetter’sconceptofrelationalandstructuralem-
beddednessbyarticulatingthefactthatdifferentcapitalisticeconomiesproducediffer-
entopportunitystructuresandstimuli(Kloosterman&Rath,2011,p.103).Additionally,
theyproposedEsping-Andersen’sconceptandhisthreewelfareregimestoincludedif-
ferentvariablesonmicro,mesoandmacroleveltoexplainmigrantself-employment.
Opportunitystructuresaremeasuredbytwodimensions:growthpotentialandhuman
capital.Thegrowthpotential/marketrepresentsthedemandsideandhumancapitalthe
supplyside.Onthedemandsidechangesinurbaneconomies(outsourcing,fragmenting
ofmarkets,serviceeconomy)openupopportunitiesformigrantentrepreneurs.Onthe
supply side more highly educated migrants (especially from non-OECD countries) are
movingtoOECDcountries.Changesinimmigrationrules(e.g.EUenlargements)makeit
possible for highly educated people to immigrate.Modifications in the economy (e.g.
more post-industrial activities) increase the chances of social upwardmobility formi-
grantsthroughself-employment.Onefocusofthetheoreticalapproachistherelation-
ship between (migrant) entrepreneurship and social upwardmobility.7 The twomen-
tioneddimensions,namelyhumancapitalandgrowthpotential,allowtheidentification
ofmarketsegments.Humancapital isdivided into twocharacteristics:highthresholds
andlowthresholds,andgrowthpotentialisdividedintotwocharacteristics:stagnating
andexpandingmarkets.Fromthesefourcharacteristicsfourtypesofmarketsresult:1)
stagnating,high-skilledmarkets,2)vacancy-chainmarkets,3)post-industrial/high-skilled
marketsand4)post-industrial/low-skilledmarkets(Kloosterman&Rath,2011,p.93).8
Thetypologywasdevelopedformarketsandnotforindividuals.Theempiricalreachof
the mixed embeddedness approach in terms of quantitative evidence has not been
measuredbecausemeasurementwasnottheintentionoftheapproach.However,from
mypointofview, theapplicationof the typology is interesting tocomparechancesof
beingself-employedbythehighlyandnon-highlyeducated.Severalstepsareneededto
applythetypologytobeabletoempiricallyapplythemixedembeddednessapproach.
Firstly,thetypologyhastobetransformedtobeapplicable.Thestepstotransformthis
7 Kloosterman and Rath leave it open as to what they mean with social upward mobility. To sum-marise, in my opinion there is the need to calculate inter- and intergenerational mobility. 8 The types will be explained in more detail later.
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approachwillbepresentedlaterinthispaper.Secondly,mesoandmacrolevelcircum-
stances could be analysed to compare different regions or countries. These steps are
beyondthescopeofthispaper,butareneededtofullyapplytheapproach.
Withinthispapertheinfluenceofembeddednessfactors,forinstancetheethniccontext
(country of birth) and the regional business and public regulatory framework (labour
marketareasbyusingurbanisationdegrees)willbetested.Thelabourmarketsituation
of highly educated self-employed persons in the age range of 25 to 649 having post-
industrialoccupationswillbeanalysedbyusingmicrocensusdatafrom2015.Theanaly-
siswillbeconductedforwomenandmenseparatelybecausedifferencesoccur(forin-
stance,menhavehigherself-employmentratesthanwomen).
Methodanddata
Thestartingpointof thisstudy is thetheoreticalapproachofmixedembeddedness. It
provides two issues relevant for this research: 1) several independentvariableswhich
might explain self-employment ofmigrants, andmost importantly for this research 2)
thetypologyofopportunitystructure.
Iwillbeginwiththedeductionofvariables.Thevariableswerededucedconsecutivelyto
notoverloadthelogitregressionmodel.Foursuccessivepartstepswerefollowedbased
on the assumption that, next to the variables already included in the theoretical ap-
proach,contextvariablesarerelevant(Welter,2011).Therefore,thefirststepwasdedi-
cated to the deduction of determinants on self-employment from the theoretical ap-
proachwhile, inadditiontothat,twoqualitativemethodswereusedtoderivecontext
variables (expert interviews and explorative interview). In a second step expertswere
interviewed on self-employment of migrants. BetweenMarch andMay 2015 in total
nineexpertinterviews10wereconducted.Researchers,politiciansandconsultantsliving
inAustria,whoareworkingorhaveworkedonmigrantentrepreneurship issues,were
9 It is assumed that persons older than 25 have finished their studies. 10 One interview was with two experts at the same time. In another interview the expert was not talking about the influence of variables on self-employment. In total, eight experts discussed this topic.
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interviewed.All interviewswere transcribedwithATLAS.ti.Aftercoding the interviews
importantvariablesonmigrantself-employmentwereidentified.Aftertheidentification
ofrelevantvariablesfromtranscribedinterviewsthevariablesweredoublecheckedto
ensurethatcategoriessuggestedbyexpertswerenotmissed.Oneexplorativeinterview
wasundertakentoevaluatethesituationofaself-employedperson.Therefore,thethird
step included the deduction of variables from the explorative interview. Lastly, in a
fourthstep,theinterviewswerecheckedalsoregardingadditionalinterestingvariables
whichshouldbetakenintoaccountandwhichhavenotbeenidentifiedbythetheoreti-
cal approach, the experts or in the explorative interview. The following illustration
showsthesourceusedandthederivedindependentvariables(table1).
Source Variablename
Theoreticalapproach Countryoforigin
Migrationgeneration(first/secondgeneration)
Urbansurrounding(urban/non-Urban)
Expertinterviews Age
Householdcontext(numberofchildren,maritalstatus)
Explorativeinterview Workinghours
Sex
Secondemployment
Analysisbasis Homeownership(flat,house)
Workingfromhome
Workingonweekends
Table1:Useddatasourceandthederivedvariables
Intotal,elevendeterminantsofself-employmentweretheoreticallyandempiricallyde-
rived.The theoreticalapproachprovides the followingvariables: countryoforigin,mi-
grationgenerationandurbansurrounding.Besidesthesevariables, theexpertsnamed
thevariablesofageandhouseholdcontext(numberofchildren,maritalstatus). Inthe
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explorative interview thevariables addressingworkinghours, sexand secondemploy-
ment cameup. Additionally, to the already identified variables the analysis basis pro-
videsthevariablesofhomeownership,workingfromhomeandworkingonweekends.
Theempiricalbasisfortheanalysisisthemicrocensus.Datafrom2004to2015areused.
The reason for this timeframe is theavailabilityof thedataset (inMarch2016 theda-
tasetforthereferenceyear2015wasavailable)andthecharacteristics(from2004on-
wardthecountryoforiginisavailable).ThemicrocensusisAustria'slargestrepresenta-
tivesamplesurvey.Quarterlyabout22.500householdsarerandomlyselected.Thedata
base is thecentralpopulationregister.Thesampleplanof themicrocensuswasmodi-
fied in2004.Thesamplingerror forextrapolatedfrequenciesofpersonsremainedthe
sameovertheyears.Extrapolatedvaluesupto6.000persons(fromafluctuationrange
ofapproximatelyathirdofthevalue)areconsideredtobehighlyrandom.Valuesbelow
3.000(fromafluctuationrangeofapproximatelyhalfofthevalue)cannotbeinterpret-
edasstatisticallysignificant(Meraner,Gumprecht,&Kowarik,2015).
Secondly,thetransformationofthetypologyofopportunitystructureswillbepresent-
ed. The authors of the theoretical approachpropose twodimensions of the typology,
namelythemarketandhumancapital.Here,thesuggestionistotransformthemarket
dimensionintoanindividualdimensionusingtheoccupationalstatustomakethetypol-
ogyapplicable.Usingtheoccupationalstatushastwoadvantages:firstly,itisanindivid-
ual variable, and secondly the post-industrial class scheme of Esping-Andersen (1993)
canbeusedtoclassifyalloccupationstotheFordistandpost-industrialactivities.11The
occupationoftheself-employedpersonwillbemeasuredbytheInternationalStandard
ClassificationofOccupation(ISCO).BasedontheISCO2008one-digitcode,alloccupa-
tions will be coded into two dimensions: Fordist and post-industrial occupations
(Leiulfsrud,Bison,&Solheim,2010).Humancapitalwillbemeasuredbythehighested-
ucationandcodedintohigh(academicdegree)andnot-high(noacademicdegree)edu-
cation.12Table2presentsthetransformedtypology.
11 Fordist/industrial workers are, for instance, managers, skilled or unskilled production workers. Post-industrial activities are, for instance, scientists. 12 The term ‘not-high’ is used deliberately because it is supposed that the term ‘low’ is hierar-chical.
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Occupation
Fordist Post-industrial
EducationHigh Type1:high/Fordist Type2:high/post-industrial
Not-high Type3:not-high/Fordist Type4:not-high/post-industrial
Table2:Transformedtypologyofopportunitystructures
Typicalexamplesforthetypesare:Type1)(restaurant)managers,Type2)medicalprac-
titioners, building architects, lawyers, Type 3) (restaurant) managers, roofers, house
builders, and Type 4) shop supervisors, buyers, hairdressers, beauticians and related
workers.
Results
Threemain findings are of relevancewhen applying the transformed typology: 1) the
sharesofthetypesfromatimeperiodofelevenyears(2004to2015),2)thedevelop-
mentoftheproportionofthetypesovertime,and3)thelogitregressionofthedeter-
minantsonself-employmentofhighlyskilledpersonsforthereferenceyear2015.
Figure1demonstratesthesharesofself-employedpersonswithmigrationbackground
for the four typesover time.Not-highlyeducatedpersonswithpost-industrialoccupa-
tionshavethehighestincreasefrom2007to2015(2007:38.5percentand2015:47.9
percent).Duringthisseven-yearperiodthissegmenthasgrownbyalmost10percent.
Thesecond largestsharehavethepersonswithhigheducationandpost-industrialoc-
cupations(highestincreasefrom26.9percentin2009to29.9percentin2015).Thereis
nohighgrowth in this segment.PersonswithFordistoccupationsandmigrationback-
groundwithbothhighandnot-higheducationhavethelowestsharesin2015.Thede-
velopmentof thenon-highlyeducatedpersonswithFordistoccupationsandmigration
backgroundisinterestingbecausethisgrouphas31.6percentagepointsin2004andin
2015only20.1percent.Thissegmentisthusshrinkingby11.4percent.Comparedwith
personswithoutamigrationbackground,thissegmentshrinksevenmorestronglyinthe
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comparison between 2004 and 2015 for persons without migration background. In
2004,thisgrouprecorded41.1percentandin201523.9percent.Thiscorrespondstoa
shrinkageofminus17.2percent.
The proportion of type 2 does not grow. Only 6.9 percentage points of growth are
achieved forpersonswithoutmigrationbackgroundand zerogrowth forpersonswith
migrationbackground.Withregardtothedistributionofthefourtypesovertime,itbe-
comesclearthatthetype4‘not-highlyeducatedandpost-industrialoccupations’occu-
piesthelargestsharesince2007,asisthecaseforpersonswithmigrationbackground
(41.2per cent in2007and50.3per cent in2015).The secondhighest value,butonly
from2013,belongstotype2‘highlyeducatedandpost-industrialoccupations’(25.2per
centin2013and24.1percentin2015).Thevaluesfortype1‘highlyeducatedandFord-
ist’occupythelowestvalue(2.6percentin2004and1.7percentin2015).Thefollow-
ingfiguresillustratetheresultsformigrantsandnatives.
Figure1:Sharesofself-employedmigrantsbytypes2004to2015
0,0%
10,0%
20,0%
30,0%
40,0%
50,0%
60,0%
70,0%
80,0%
90,0%
100,0%
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Sharesofself-employedmigrantsbytypes2004to2015(inpercent)
Type1:high/fordist Type2:high/post-industrial Type3:not-high/fordist Type4:not-high/post-industrial
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Figure2:Sharesofself-employednativesbytypes2004to2015
Figures3and4showthedevelopmentovertimeoftheself-employmentrate13ofper-
sonswithandwithoutmigrationbackgroundfrom2004to2015.From2004to2007da-
tadoesnotincludemigrationbackground.Fortheseyearsonlypersonsbornoutsideof
Austriaarereferredtoasmigrants.Theself-employmentrateofmigrantswithhighed-
ucationandFordistoccupationisdecreasingfrom2004to2015(-6.7percent).Figure3
also shows that there is no significant increase of the self-employment rate for other
types.Theself-employmentrateofnativeswithhigheducationandFordistoccupation
13 The self-employment rate is an important concept for comparing self-employment of different groups and is defined as the percentage share of total employment accounted for the self-employed (Clark, 2014). The total employment consist of persons who are employed and unemployed. Addi-tionally, economic branches of agriculture, forestry and fishing/public administration are excluded from the scope.
0,0%
10,0%
20,0%
30,0%
40,0%
50,0%
60,0%
70,0%
80,0%
90,0%
100,0%
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Sharesofself-employednarvesbytypes2004to2015(inpercent)
Type1:high/fordist Type2:high/post-industrial Type3:not-high/fordist Type4:not-high/post-industrial
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isdecreasingfrom2004to2015(-8.5percent).Thisdecreaseishigherthanformigrants
oftype1.Aswellasforthemigrants,theself-employmentrateofothertypesisnotin-
creasingsignificantly.Apossiblereasonforthedecreaseoftheself-employmentrateof
type1 is thefinancialcrises.Thestagnatingself-employmentratesofothertypesmay
havetheircausessuchaslowincentivesforcreatingortakingoverabusiness.
Thegroupwiththehighestself-employmentratehashigheducationandpost-industrial
occupations.Forthisgroupthedifferencesbetweenpersonswithandwithoutmigration
backgroundaremarginal.In2015therateforbothpersonswithandwithoutmigration
backgroundwasaround20percent(seefigures3and4).
Figure3:Self-employmentrateofmigrantsbytypes2004to2015
0,0
5,0
10,0
15,0
20,0
25,0
30,0
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Self-employmentrateofmigrantsbytypes2004to2015
Type1:high/fordist Type2:high/post-industrial Type3:not-high/fordist Type4:not-high/post-industrial
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Figure4:Self-employmentrateofnativesbytypes2004to2015
After thisdescriptiveanalysis thegroupwith thehighest self-employmentquote (high
education/post-industrialoccupations)willbeanalysedby logitregressionsfortheref-
erenceyear2015.Thetestedvariablesareinfourlevels,namelyattheindividual,work,
spatial and household level. They are age, country of birth (including second genera-
tion),part-time,age,secondaryjob,workingfromhome,workingonweekends,popula-
tiondensity,homeownershipandmarried/children.Personsyoungerthan25wereex-
cludedfromthesamplebecauseitisassumedthatpersonsolderthan25havefinished
theirstudies.Thecalculationsarepresentedseparatelyformenandwomentoshowthe
different effects of the chosen variables. The dependent variable is self-employed or
employed(notself-employed).Self-employedpersonsmayormaynothaveemployees
ortheyarefreelancers.
0,0
5,0
10,0
15,0
20,0
25,0
30,0
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Self-employmentrateofnarvesbytypes2004to2015
Type1:high/fordist Type2:high/post-industrial Type3:not-high/fordist Type4:not-high/post-industrial
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Table3:Characteristicsofhighlyskilledindividualsage25-64withpost-industrialoccu-
pations
Characteristics on the individual levelAge (<40 years) 94.133 52,5% 16.657 29,7% 213.367 55,6% 29.359 31,6%Age (>40 years) 85.022 47,5% 39.460 70,3% 170.615 44,4% 63.422 68,4%Country of birthAustria 128.432 71,7% 42.813 76,3% 280.505 73,1% 67.414 72,7%Germany 13.211 7,4% 3.644 6,5% 23.643 6,2% 6.580 7,1%EU15 (without Austria and Germany) 8.265 4,6% 1.673 3,0% 14.098 3,7% 2.193 2,4%EU25 (enlargment countries 2004) 6.043 3,4% 2.168 3,9% 15.412 4,0% 4.706 5,1%EU2728 (enlargment countries 2007 and 2013) 3.971 2,2% 961 1,7% 10.497 2,7% 1.475 1,6%Ex-Yugoslavia/Turkey 5.378 3,0% 593 1,1% 10.181 2,7% 1.256 1,4%Second Generation 3.418 1,9% 552 1,0% 7.331 1,9% 1.729 1,9%Europe other 554 ,3% 705 1,3% 4.149 1,1% 1.602 1,7%Not Europe 9.885 5,5% 3.009 5,4% 18.166 4,7% 5.826 6,3%Characteristics on the work levelFull-time 153.274 85,6% 42.917 76,5% 270.622 70,5% 58.770 63,3%Part-time (<36 hours) 25.882 14,4% 13.200 23,5% 113.359 29,5% 34.011 36,7%No secondary job 161.735 90,3% 50.191 89,4% 351.283 91,5% 83.213 89,7%Secondary job 17.421 9,7% 5.926 10,6% 32.699 8,5% 9.568 10,3%Working from home (> 50% of the working time) 151.156 84,4% 34.432 61,4% 310.957 81,0% 57.577 62,1%Not working from home 28.000 15,6% 21.684 38,6% 73.024 19,0% 35.204 37,9%Not working on saturdays and/or sundays 102.922 57,4% 17.122 30,5% 224.745 58,5% 33.948 36,6%Working on saturdays and/or sundays (> once a month) 76.233 42,6% 38.995 69,5% 159.236 41,5% 58.833 63,4%Characteristics on the spatial levelNo high population density 90.899 50,7% 27.759 49,5% 191.945 50,0% 44.541 48,0%High population density 88.257 49,3% 28.358 50,5% 192.036 50,0% 48.240 52,0%Characteristics on the household levelNo ownership of flat(s) or house(s) 83.920 46,8% 20.845 37,1% 180.770 47,1% 36.390 39,2%Ownership of flat(s) or house(s) 95.236 53,2% 35.271 62,9% 203.211 52,9% 56.391 60,8%Not married and/or children (<18) 124.900 69,7% 41.168 73,4% 275.746 71,8% 66.642 71,8%Married and children (<18) 54.256 30,3% 14.949 26,6% 108.235 28,2% 26.139 28,2%Total 179.156 100,0% 56.117 100,0% 383.982 100,0% 92.781 100,0%
Women MenNot self- self-employed Not self- self-employed
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Table3showsthequantitiesoftheselectedvariablesbysexandemploymentstatusfor
highlyskilled individualsaged25to64withpost-industrialoccupations.14Thedistribu-
tionscanbedescribedasfollows:
1. Age: Self-employed persons are older than 40 years (women: 70.3 per cent;men:68.4percent).
2. Countryofbirth:Thehighestpercentageofself-employedpersonsareborninAustria from both genders. The second largest group was born in Germany(womenandmen).15
3. Part-time:Whenconsideringworkinghours,menaremorelikelytoworkpart-timethanwomen(women:23.5percent;men:36.7percent).16
4. Second job: 90per centof the self-employed (womenandmen)haveno sec-ondaryjob.
5. Working fromhome: 60per centof the self-employed (womenandmen) areworkingmorethan50percentfromhome.
6. Workingonweekends:Over60percent(women:69.5percent;men:63.4percent)areworkingonceormorethanonceamonthonweekends.
7. Populationdensity:Moreself-employedwomenthanmen live inareaswithahighpopulationdensity,whichmeansincities(women:54.2percent;men:50.5percent).
8. Homeownership:Morethan60percent(women:62.9percent;men:60.8percent)ownaflatorahouse.
9. Married/children: The majority of the self-employed are not married and/orhavenochildrenyoungerthan18years(women:73.4percent;men:71.8percent).
Theresultsforthelogisticregressionshowtheinfluenceonself-employmentseparately
forwomenandmen(seetable4and5).Forexample,intable4womenborninoneof
14Economicbranchesconsideredirrelevantforthestudyareexcluded(agriculture,forestryandfishing/publicadministration).15Extrapolatedvaluesupto6.000persons(fromafluctuationrangeofapproximatelyathirdofthevalue)areconsideredtobehighlyrandom.Valuesbelow3.000(fromafluctuationrangeofapproximatelyhalfofthevalue)cannotbeinterpretedasstatisticallysignificant(Meraner,Gum-precht,&Kowarik,2015).16Thisresultmaybeanexpressionofthe interestsofemployedpersonstowork less.22.9percentofallemployedmenand15.4percentofallemployedwomenwould liketoreducetheirworkinghours(StatistikAustria,2015b,p.43).Asaself-employeetheyhavethechoiceandobvi-ouslymenaremorelikelytoworklessthanwomen.Itwouldbeinterestingtoknowhowmuchmenearnincomparisontowomen.Iftheyearnmorethiswouldproperlyexplainwhymenworklesshoursthenwomen.
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the EU2517, Germany or non-European countries18, as well as the second generation,
have higher likelihoods of being self-employed. Also, women who are older than 40,
work part-time from home or onweekends, or own a flat or a house, have a higher
chancetobeself-employed.Incontrast,theresultsofthelogisticregressionformenare
differentforsomevariables(seetable5).Thevariableofbeingborn inEuropeother19
has a significant positive effect on self-employment for men. Being born in Ex-
Yugoslavia/Turkey20, as well as having a second job, lowers the chance to be self-
employedformen.Inaddition,thevariablebeingmarriedand/orhavingchildrenhasa
negativeeffectontheprobabilityofbeingself-employedformen.Similaritiesbetween
women andmen occur for the variables age, part-timework, homework,working on
weekend(s) and home ownership. Those variables have significant positive effects on
theprobabilityofbeingself-employed.Differencesoccurforwomenandmenseparated
bycountryoforigin.Thatmeanstheresultsaredifferentifdifferentiatedbygenderand
country of origin. For women from Germany, EU25 and second generation, self-
employmentisachance.Possiblereasonsforthehigherchancesofbeingself-employed
aretheglassceilingeffectsincompanies,thewish/needforflexibleworkinghours,the
wishtobetheirownbossorthewishtorealiseanidea.Intotal,highlyskilledmenwith
post-industrialoccupationshavehigherchancesofbeingself-employedthandowomen
ofthisscope.Nosignificanteffectsarevisibleforareaswithhighpopulationdensityfor
bothwomenandmen.
17TheEU25countriesarethosecountrieswhichjoinedtheEUin2004(Cyprus,CzechRepublic,Estonia,Hungary,Latvia,Lithuania,Malta,Poland,SlovakiaandSlovenia).18Thenon-EuropeancontinentsareAfrica,NorthAmerica,SouthAmerica,AsiaandOceania.19 The Europe other countries are mainly Switzerland and countries classified with “other Europe-an countries” in the microcensus. 20 These countries are taken together because all of them are in the tradition of the guest worker policy.
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Table4:Logisticregressionofself-employedhighlyskilledwomenaged25-64withpost-
industrialoccupationsinAustria
Characteristics on the individual levelAge (>40 years) 1,045 *** 1,068 *** ,985 *** ,990 *** ,949 ***Country of birthAustria Referenz Referenz Referenz Referenz ReferenzGermany ,433 *** ,458 *** ,461 *** ,503 ***EU15 (without Austria and Germany) -,118 n.s. -,046 n.s. -,052 n.s. -,035 n.s.EU25 (enlargment countries 2004) ,543 *** ,618 *** ,610 *** ,661 ***EU2728 (enlargment countries 2007 and 2013) -1,022 ** -,833 n.s. -,842 * -,789 n.s.Ex-Yugoslavia/Turkey ,024 n.s. ,021 n.s. ,003 *** ,063 n.s.Second Generation ,643 ** ,747 *** ,736 *** ,750 ***Europe other ,419 n.s. ,509 n.s. ,505 n.s. ,551 *Not Europe ,553 *** ,529 *** ,509 ** ,541 ***Characteristics on the work levelPart-time (<36 hours) ,544 *** ,548 *** ,525 ***Secondary job ,071 n.s. ,069 n.s. ,069 n.s.Working from home (> 50% of the working time) ,383 *** ,389 *** ,374 ***Working on saturdays and sundays (> once a month) ,453 *** ,454 *** ,456 ***Characteristics on the spatial levelHigh population density ,073 n.s. ,149 n.s.Characteristics on the household levelOwnership of flat(s) or house(s) ,213 **Married and children (<18) ,053 n.s.Constant -2,295 *** -2,394 *** -2,971 *** -3,007 *** -3,159 ***Observations 4.611 4.611 4.611 4.611 4.611degree of freeedom 1 9 13 14 162LogLikelihood 3885,687 3849,836 3755,451 3754,727 3749,525Cox & Snell R Square 0,033 0,04 0,06 0,06 0,061Nagelkerke R Square 0,056 0,069 0,102 0,102 0,104
Model D Model EModel A Model B Model C
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Table 5: Logistic regression of self-employed highly skilledmen aged 25-64with post-
industrialoccupationsinAustria
Conclusions
Toconclude,theaimofthispaperwastomakeacontributiontotheory,alsoincluding
genderdimension,bytransformingthetypologyofopportunitystructureandtheexpla-
nationoffactorsinfluencingself-employmentofmigrantsandnatives.Presentedtypes
Characteristics on the individual levelAge (>40 years) 1,021 *** 1,022 *** ,985 *** ,991 *** ,972 ***Country of birthAustria Referenz Referenz Referenz Referenz ReferenzGermany -,373 *** -,296 * -,297 * -,242 n.s.EU15 (without Austria and Germany) -,432 * -,395 n.s. -,400 n.s. -,381 n.s.EU25 (enlargment countries 2004) ,048 n.s. ,098 n.s. ,093 n.s. ,201 n.s.EU2728 (enlargment countries 2007 and 2013) -,602 n.s. -,421 n.s. -,434 n.s. -,419 n.s.Ex-Yugoslavia/Turkey -,847 *** -,836 *** -,848 *** -,724 **Second Generation -,344 n.s. -,419 n.s. -,425 n.s. -,419 n.s.Europe other ,983 ** 1,227 *** 1,232 *** 1,431 ***Not Europe -,147 n.s. -,242 n.s. -,259 n.s. -,126 n.s.Characteristics on the work levelPart-time (<36 hours) ,935 *** ,930 *** ,906 ***Secondary job -,389 *** -,388 *** -,375 ***Working from home (> 50% of the working time) ,660 *** ,660 *** ,654 ***Working on saturdays and sundays (> once a month) 1,034 *** 1,036 *** 1,029 ***Characteristics on the spatial levelHigh population density ,048 n.s. ,106 n.s.Characteristics on the household levelOwnership of flat(s) or house(s) ,258 ***Married and children (<18) -,278 ***Constant -1,734 *** -1,670 *** -2,547 *** -2,568 *** -2,667 ***Observations 4.452 4.452 4.452 4.452 4.452degree of freeedom 1 9 13 14 162LogLikelihood 4867,003 4838,44 4450,887 4450,509 4433,735Cox & Snell R Square 0,042 0,048 0,127 0,127 0,131Nagelkerke R Square 0,062 0,071 0,187 0,188 0,192
Model A Model B Model C Model D Model E
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ofself-employedpersonswithinthistypologyhavebeenappliedandanalysedbyusing
microcensusdataofthereferenceyears2004to2015.Themainquestionwashowthe
typologycanbeappliedandwhichvariablescanbederived.Additionally,expert inter-
viewswereusedtocontextualisethetopicandcontributetotheselectionofvariables
whichwereanalysed.Theyshowedthatbothvariablegroupsontheindividualandthe
context level are relevant, and they identified the individual level as being of greater
significance.
Given the points that the likelihoods are highest for highly skilled personswith post-
industrial occupations who are working part-time, are older than 40, working from
home,workingonweekendsandareownersofflat(s)and/orhouse(s),self-employment
inAustriaseemstobeachanceforflexibilityofworkingtimeandspace.Also,theresults
showthat,iftheyownaflatorahouse,thechanceofbeingself-employedishigherfor
bothmenandwomen.Isthisbecauseofahighsecuritybehaviourofthepersons?What
arethemechanismbehindtheself-employmentphenomena?Anotherconclusionisthat
thevariablesageandsexhaveahigherinfluenceonbeingself-employedthanthevaria-
ble countryof birth/migrationbackground.Whether the influenceof age (beingolder
than40)isanothersignforthehighsecuritybehaviourofthepersons,orwhetheritisa
resultofagelabourmarketdiscriminationcannotberatedwiththisresearch.
Thestudyshowsthatboththetransformation/applicationof thetypologyandthede-
tailedregressionanalysisgivedetailedinsightsonself-employmentinAustria.Thetrans-
formed typologymakesacontribution to theory,and theapplicationover timeshows
thegrowingandshrinkingsegmentsofself-employment.Ascanbeseen,twotypesare
ofhighrelevance (highlyandnot-highlyeducatedpersonswithpost-industrialoccupa-
tions). To increase the self-employment rate, the largest group (not-highly educated
withpost-industrialoccupations)andthegroupwiththehighestself-employmentrate
(highlyeducatedandpost-industrialoccupations)havetobeaddressedbypolicymak-
ers.
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