breen educational expansion and social mobility
TRANSCRIPT
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EducationalExpansionandSocialMobilityintheTwentiethCentury
Abstract
Sociologistshavelongconsideredinequalityineducationalattainmenttobeamajor
cause of inequality between people in their chances of occupying a more
advantageousclass position. However, there is some disputeas to whetherornot
educational inequalityaccordingtosocialclassbackgrounddeclinedduringthe20th
century.Whatisnotindoubtisthemarkedexpansionofeducationintheadvanced
economies during this time, and several authors have pointed to educational
expansionasamechanismbywhich inequalities insocialmobilitychancesmaybe
reduced.Imeasurethemagnitudeofsuchaneffectandcompareitwiththeimpact
ofeducationalequalizationonsocialmobilityinBritain,SwedenandGermanyduring
the twentieth century. I find that in all three countries educational expansion has
hadapositiveeffectinpromotinggreatersocialmobility.
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EducationalExpansionandSocialMobilityintheTwentiethCentury
Sociologistsofstratificationand inequalityhavea longstanding interest intherole
of theeducationalsystem inhelping todetermine theoccupations that individuals
come to hold. The underlying assumption is that a weakening of the relationship
between social origins and educational attainment will lead to a weakening of the
relationship between origins and destinations. In the loglinear tradition of social
mobilityresearchthishasoftenbeenasserted,butthelinkbetweeneducationaland
occupationalmobilityhasneverbeenadequatelydemonstrated.Thefirstgoalofthis
paper, therefore, is to use simulations, based on loglinear models, to gauge the
impactof increasingeducational equalization on theorigindestination association.
The second goal is to illustrate the impact that the expansion of education, aside
from any equalization, may have on the relationship between social origins and
destinations. Under certain conditions, educational expansion alone may lead to a
weakeningofthisrelationship.Icalibratethesizeofthiseffectandcompareitwith
theimpactofeducationalequalizationinBritain,GermanyandSweden.
The paper begins with a review of recent research into the evolution of the
relationships between social origins and, on the one hand educational attainment
and, on the other, class destination. I then turn to the two mechanisms
equalization and a compositional effect by which changes in the educational
systembringaboutchanges in social fluidityand I illustratehow thesemightwork
via a simple fictitious example. Using data from Britain, Sweden and Germany I
quantify the impact of both of these mechanisms on the trend in social fluidity
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changes in educational stratification seems to be negligible' (page 21). In other
words, although educational attainment levels have everywhere increased, the
relative chances of continuing to further levels of the educational system among
peopleofdifferentsocialoriginshaveremainedgenerallyunchanged.
ShavitandBlossfeldsresultsechoed,toalargeextent,earlierfindingsfromtheUSA,
France,theNetherlands,Britainandelsewhere.1Inarecentreview,however,Breen
andJonsson(2005:226)reportedthat
SubsequentanalyseshaveclearlyshownequalizationinthecaseofGermany
(Henz&Maas1995,Jonssonetal.1996,Mller&Haun1994),France(Vallet
2004a), Italy (Shavit & Westerbeek 1998), and probably Norway (Lindbekk
1998), while the results for Sweden (Jonsson & Erikson 2000) and the
Netherlands(Siebenetal.2001)havebeencorroborated.
As well as studies of single nations, there have been at least two comparative
analyses of educational inequality with respect to social origins: these are Rijkens
(1999)PhDthesis,andtherecentpapersbyBreen,Luijkx,MllerandPollak(2009a,
2009b). These authors find a tendency for social origins to have a diminishing
influence on educational attainment over cohorts born during the first three
quarters of the twentieth century though, in the case of the latter papers, some
importantcrossnationalvariationsinthistrendarefound.
1
For
the
USA,
Featherman
and
Hauser
(1978);
for
France,
Garnier
and
Raffalovich
(1984);
for
the
Netherlands,Dronkers(1983)andforBritain,Halsey,HeathandRidge
(1980)andHeathandClifford
(1990).
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It is not immediately obvious why there should be such conflicting findings about
temporaltrends. It iscertainlytruethatdifferentstudiesusedifferentmeasuresof
social origins (for example, measures of occupational status or prestige or
categorical measures of social class membership and measures of parental
education)andemploydifferentstatisticalmodels,but it isneverthelesssomewhat
surprising that the basic pattern whatever it is is not robust to these kinds of
variations. All studies are, however, agreed that there was a massive increase in
formallevelsofeducationalattainmentinthecourseofthetwentiethcentury.
SocialFluidity
A common approach to the study of social reproduction is to examine the
relationship between the social class position held by an individual and the social
classthathisorherparentsoccupiedwhentherespondentwasgrowingup.There
are various ways that this relationship could be modeled, but much emphasis has
beengiven to theratioof theodds,amongrespondentsborn intooneclassorigin
compared with those born into another, of coming to occupy one social class
destinationratherthananother.Oddsratiosformedinthiswayaresometimessaid
to capture relative mobility chances or social fluidity. For analysts of social
mobility, education is one of the major channels through which intergenerational
class reproduction occurs (Ishida, Mller and Ridge 1995) and so educational
inequality is chiefly important because of how it might affect inequalities in social
mobility chances, or, in other words, how social fluidity might be driven by
educationalfluidity.
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Perhaps unsurprisingly, disagreements about temporal trends in social fluidity
parallel those about educational inequality. For example, Erikson and Goldthorpe
(1992:367)arguedforahighdegreeoftemporalstabilityinsocialfluidity,yettheir
analyseswerebasedontheproxyingofbirthcohortsbytheuseofagegroupsdrawn
fromasinglesurveypercountry.Indeed,fewstudieshaveanalyzedtrendsinfluidity
using a series of mobility tables collected over time (when a series is defined as
consistingofmorethantwoovertimeobservations),2andeven fewerhavedrawn
comparisons of trends between countries. The best known exceptions to this are
Ganzeboom,LuijkxandTreiman(1989:47)whoclaimedtodemonstratesubstantial
crossnationalandcrosstemporaldifferences in the extentof mobility,andBreen
and Luijkx (2004) who document significant variation in social fluidity among the
countriesofEuropeandafairlywidespreadtemporaltrendtowardsgreaterfluidity
intheclosingdecadesofthe20th
century.
Mosttemporalcomparisonshaveadoptedaperiodperspective,butasmallnumber
ofsinglecountrystudieshavedrawncomparisonsoverbirthcohorts:these include
Hout (1988, USA) and, more recently, Vallet (2004a, France), Mller and Pollak
(2004, Germany), and Breen and Jonsson (2007, Sweden). In all these cases,
repeated crosssectional surveys are used, so allowing for the possibility of
comparing period and cohort change in a way that cannot be done with a single
2ExceptionsareHout's(1988)workontheGeneralSocialSurvey(seealsoDiPreteandGrusky1990;
Hauser
and
Huang
1997),
the
work
of
Luijkx
and
Ganzeboom
(1989)
on
Dutch
data,
Jonssons
and
Mills(1993)analysisofSwedishandEnglishdata,andVallets(1999)comparisonsusingtheFrench
FQPsurveys.
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survey. These cohort based analyses show a gradual decline in the association
betweenclassoriginsanddestinationsduringthetwentiethcentury.3
Howeducationmightinfluencesocialmobility:(1)anexample
Following Breen and Jonsson (2007), there are two ways through which education
might cause social fluidity to change. The first, equalization, is a decline in the
association between class origins and educational attainment: this is what has
mainlyconcernedanalystsofsocialmobility.Thesecondprocess iscompositional:
if the origindestination association is weaker at higher levels of education, and if
educational expansion results in increasing shares of each cohort reaching higher
educational levels, then this compositional change will lead to a reduction in the
grossassociationbetweenoriginsanddestinations.Itisclearthatthecompositional
effect requires both educational expansion and the correct sort of threeway
interactionbetweenclassorigins,educationalqualificationsandclassdestinations.I
shallusethetermdifferentialassociationtorefertothecaseinwhichtheorigin
destination association tends to be weaker at higher levels of education. Such
differentialassociationmaybepresentwhen,forexample,higherqualificationsare
apowerfulsignalforemployersthatleaveslittleleewayforsocialnetworkeffects,or
whenthejobmarketsinwhichdegreeholdersoperateareparticularlymeritocratic.
Hout (1988) was the first to draw attention to this phenomenon and its possible
impact on fluidity and, subsequently, a weaker origindestination association at
3Therearegoodreasonsforsupposingthatchange influidity isbettercapturedasacohortthana
periodphenomen.Formostpeople,educationalattainmentisthemostimportantsingledeterminant
oftheirclassposition,andeducationisattainedduringchildhood,youthandearlyadulthood(or,as
Mller
and
Pollak
2004:
110
succinctly
state,
Educational
participation
and
class
inequality
in
education is a cohort phenomenon). Thus, changes in the distribution of educational attainment
affectspecificbirthcohortsandnottheentirepopulation(BreenandLuijkx2007).
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higher levels of education has been reported for France (Vallet 2004b), Sweden
(Erikson and Jonsson 1998) and Germany (Breen and Luijkx 2007). It is therefore
possiblethat,inthesecountries,anexpansionofhighereducationacrosscohortsled
to increasingfluidity. Ifthis isthecase,then itfollowsthatsocialmobilityanalysts
concern with only educational equalization is too restrictive, because educational
expansionitselfabouttheoccurrenceofwhichthereisnocontroversymayalso
havethecapacitytoweakentheassociationbetweenclassoriginsanddestinations.
Thesepossibilitiescanbe illustratedbymeansofthehypothetical2by2by2table
shown inTable1.Thesituationattime=1 isgivenonthe leftsideofthetable.The
toprows, labeled OEshow therelationshipbetweenclassorigins (middleclassor
workingclass)andeducational level(loworhigh)andtheoddsratio(OR)capturing
the association between these. Below that are the tables showing the origin
destinationdistributionandoddsratiosateachlevelofeducation(OD|E)and,below
them, the overall OD distribution, which is formed by adding the OD|E=low and
OD|E=hightables.Bydesigntheoddsratioisloweratthehighlevelofeducationto
capturedifferentialassociation.Therighthandpartof the table, labeledTime=2,
showstheeffectsofdifferentkindsofchangeintheorigineducationrelationship.
Case (a) deals with equalization alone, which in this case takes the form of a
reduction intheorigineducationoddsratio from itstime=1valueof1.5to1.31,
while preserving the marginal distributions of both origins and education. Keeping
the two partial origin destination associations unchanged (as I do throughout),
causestheoverallorigindestinationrelationshiptodeclinefrom4.14to4.03.This
is the effect of equalization. The next column, (b), shows the impact of expansion
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whendifferentialassociationholds.Thistimetheorigineducationoddsratioand
the origin distribution remain the same but the marginal distribution of education
shifts towards a larger share of people at the higher level. This causes the overall
oddsratiotodeclineto3.87.Finallycase(c)showstheimpactofbothprocesses.The
origineducationtablenowpreservesonlythemarginaldistributionoforiginsand
issubjecttoexactlythesameequalizationasincase(a)andthesameexpansionas
incase(b).Theorigindestinationassociationoddsratiointhiscaseis3.77.
[TABLE1HERE]
Howeducationmightinfluencesocialmobility:(2)formalderivation
TheoutcomesshowninTable1canbederivedformallyusingloglinearmodelsand
someelementaryresultsaboutconditionalprobabilities.Considerafourwaycross
tabulationofclassorigins(O,indexedbyj)byeducationalattainment(E,indexedby
k)bycurrentclasspositionordestination(D,indexedby l)bycohort(C,indexedby
i),withallthevariablestreatedascategorical.Aloglinearmodelingapproachwould
considertwotables:theEOCtable,whichpermitstheanalysisofthedistributionof
E, conditional on O and C, (E|OC), and the EOCD table, for the analysis of D
conditionalonO,EandC,(D|OEC).AnypairofmodelsforE|OCandD|OECimpliesa
set of estimated frequencies in the OEDC table and thus, by collapsing over the E
margin,asetoffrequenciesfortheODCtable.Inthiswayonecanassesstheeffect
ofdifferentmodelsforE|OCand/orD|OEConthetrendinODoverC.
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Wecanwritethejointprobabilitydistributionofthesefourvariablesastheproduct
ofconditionalprobabilitiesthatcapturethedependenciesamongthem:
),(),|(),,|(
),,,(
iCjOpriCjOkEprkEiCjOlDpr
lCkEjOiCprpijkl
=========
===== (1)
We always treat thejoint distribution of origins and cohorts, ),( iCjOpr == , as
exogenoussincetheOCmarginisfittedexactlyinallthemodelsconsideredhere.
Thethreewayprobabilitydistributionofcohortbyoriginsbydestinationsisarrived
atbysummingoverthelevelsofE:
==========k
lij iCjOpriCjOkEprkEiCjOlDprp ),(),|(),,|(. (2)
Specificmodelsoftheexactnatureofthedependencies in(1)willthusgiveriseto
differentjoint distributions of ODC via (2). It is intuitively clear that equalizing the
origineducation relationshipwill reduce theorigindestinationassociation, but
the consequences of the compositional effectare less immediately obvious.A log
linearmodelforthiseffectcanbewritten:
CE
ik
CO
ij
OE
jk
C
il
E
k
O
jijkf =. (3a)
OED
jkl
COE
ijk
CE
ik
CD
il
CO
ij
ED
kl
OD
jl
OEC
i
E
k
D
l
O
jijkl jkf =
(3b)
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Here f denotestheexpectedfrequenciesunderthemodel.Theeffectoforiginson
educationdoesnotvaryovercohortsandsothereisnoequalization:thisiscaptured
bytheabsenceofthetermCOE
ijk from(3a).However,Ehasanadditivedependence
onOandC (so thedistributionofeducation isallowed tochangeovercohorts).D
dependsonCandalsoonthejointEOdistribution(thisisthedifferentialassociation
effect).Inthiscase:
)()|()()()|(),()|(),|( CprCODprDOCprOCprOCDprCOprCEprEODprk
===
Thesameargumentcanbeappliedtologlinearmodelsforeducationalequalization
and for the combined equalization and compositional effects: in both cases they
implyadependenceoftheorigindestinationassociationoncohort.4
Iusetheforegoingresultsasthebasisofsimulationsoftheeffect,onthechangein
the Origin Destination odds ratios (i.e. social fluidity), of educational equalization
and of the compositional effect. The analysis is carried out using data on men in
GreatBritain,GermanyandSweden,forbirthcohortscoveringthefirsttwothirdsof
thetwentiethcentury.
4Theseresultscanbeobtainedonrequestfromtheauthor.Incaseaskepticalreaderthinksthatall
modelsgiverisetothethreewayODCdistribution,considerthecase inwhichEdependsadditively
onCandDdependsadditivelyonE.Then
==k ODprOCprCDprCOprCEprEDpr )|()()|(),()|()|( ,andnowtheODrelationshipdoesnotvarywithC.
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Data
ThesourcesofdataforthethreecountriesareshowninTable1.ForBritainthedata
come from theGeneralHouseholdSurvey (GHS) for theyears1973,19756,1979
1984,19871992.AlthoughtheGHShasbeenfieldedannually from1971onwards,
informationon theemploymentof therespondents father (orheadof the family)
wasnotcollected in1977or1978orafter1992,while informationon the lastjob
heldbythosenotcurrentlyworkingwasnotgathered in1985and1986.Iomitthe
1974 data because Goldthorpe and Mills (2004: 202), who have recently used the
GHS for mobility analysis (and who kindly provided the data), report that some
seriousproblemsexistwiththe1974data.
The German data, which cover the period 1976 to 2002, come mainly from the
Allbussurvey,butaresupplementedbyothersurveys.MllerandPollak(2004:85),
whokindlyprovidedthedata,writethatthesesurveysallusesimilarquestionnaires
and procedures to collect the data and they express their confidence that
cumulating these databases does not introduce systematic inconsistencies. To
preservecomparabilityovertime,theyreferonlytoGermansresidentintheformer
WestGermany.
TheSwedishdatasetisacompilationoftheannualsurveysoflivingconditions(ULF)
19761999, conducted by Statistics Sweden (Vogel et al. 1998). Each survey is
representativeoftheadultSwedishpopulation,aged1575(BreenandJonsson2007
formoredetail).
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[TABLE2HERE]
I analyze data for men (the reason for this is explained in the technical appendix)
and, as is conventional in mobility analysis, I confine attention to the working age
population.ForGermanyandSwedenthis ismenaged25 to64ateachsurvey. In
the British data the age range is narrower: 25 to 49, because, for most years,
respondents to the GHS aged 50 or over were not asked the occupation of their
father.
Class origins (O, for short) and destinations (D) are defined using the EGP class
schema(EriksonandGoldthorpe1992:ch.2)asfollows:
I Upper service class higher grade professionals, administrative and managerialworkers;
II Lower service class lower grade professionals, administrative and managerial
workers;
IIIRoutinenonmanualworkers;IVab Selfemployedandsmallemployers,
IVc Farmers,
V+VISkilledmanualworkers,techniciansandsupervisors,and
VIIab+III Semi and unskilled manual, agricultural, and lower grade routine non
manualworkers.
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These seven classesare used in the German case. Unfortunately the limitations of
the GHS force the use of a six, rather than seven, class classification for Britain,
because it is notpossible to distinguish between classes I and II or between these
andclassIVa(thatis,smallemployers):accordinglythefirstclassinBritainisI+II+IVa
while the third is IVb (the selfemployed without employees). In Sweden, on the
otherhand,the lasttwoclassescannotbedistinguished,soheretootherearesix,
ratherthanseven,classes.
Respondentseducationismeasuredbytheirhighestlevelofeducationalattainment
(education (E), for short) categorized using the CASMIN educational schema.
Categories1a,bandc,andalso2aandboftheoriginalscheme(Mller,Lttinger,
Knig,andKarle1989)havebeenamalgamated,givingfiveeducationalcategories:
1abc (compulsoryeducationonly),
2ab (secondaryintermediateeducation,vocationalandgeneral),
2c (fullsecondaryeducation),
3a (lowertertiaryeducation),and
3b (highertertiary).5
The exception here is Sweden where there are six educational categories because
thedistinctionhasbeenmadebetween1aband1c.
5Highertertiaryeducation,3b,meansthesuccessfulcompletion(withexamination)ofatraditional,
academically
oriented
university
education.
Lower
tertiary
education,
3a,
is
usually
characterized
by
a
shorterlengthofstudyandmorepracticallyorientedstudyprograms(e.g.technicalcollegediplomas,
socialworkeror,nonuniversityteachingcertificates).
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Birthcohortsaredefineddifferentlybecauseof thedifferentsurveydatesandage
ranges covered. So for Germany the cohorts are born 191221, 192230, 193139,
194048,194957,195866and196777andforBritain192427,192834,193541,
194248, 194955, 195662 and 196367. Thus the German data span a slightly
longer period than the British. Omitting cases with missing information on one or
more variables gives sample sizes of 18961 for Germany and 58125.5 for Great
Britain.ForGermanythedataareunweighteddatabutforBritaintheyareweighted
to correct for oversampling of Scottish respondents. For Sweden there are 24
annual surveys and they are grouped into six, 4yearly periods (197679; 8083; ...
9699).WithineachperiodIidentifytenfouryearagegroups(2528;2932...6164)
whichallowmetodefine15overlappingagecohorts.Theoldestcohortwasbornin
191218,theyoungestin196874.Thesamplesizeis33281.
Inall threedatasetsnoteverycohortcanbeobserved ineverysurvey: theoldest
andyoungestcohortsareobserved leastoften,while thecohortsborn around the
middleofthecenturyareobservedmostfrequently.Thismeansthatthere ismore
datainthemiddleoftheseriesandratherlittleattheextremessomethingwhich
shouldbekeptinmindwheninterpretingtheresults.6
6Thefocusofthispaperischangeinsocialfluidityacrossbirthcohortsbutthedatacomprisesamples
fromeachbirthcohortdrawn inoneormoreperiodsandthisraisesthequestionofwhetherthere
shouldbecontrols for period in the models fitted here. I have not done this because the need to
further crossclassify the data by period would have led to very sparse tables, especially in the
German case. But ignoring period effects can be justified by reference to the results of earlier
research which found that, once cohort effects are included in a model of fluidity, period effects
become largely insignificant.ForBritainandGermany,BreenandLuijkx (2007:112)write: (i)nboth
cases,
differences
between
periods
are
in
fact
the
result
of
cohort
replacement
and
Breen
and
Jonsson (2007: 1805) write similarly: period change disappears when we control for differences
betweenbirthcohorts.
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Modelsandresults
The existence of an educational equalization effect requires that the education
class origin association (EO) weakens over cohorts, while the compositional effect
requiresboththatthedistributionofeducationhasshiftedupwardsoversuccessive
birth cohorts expansion and that there exists a threeway interaction between
origins, education and current class position, or destination, such that the OD
associationisweakerathigherlevelsofeducation(differentialassociation).
Figure1showsthetrendovercohortsinclassdifferencesineducationalattainment
using the results of ordered logit models. In the figure each line refers to a class
originandshowshowthecoefficientsforthatclassevolveovercohorts,withclassI
alwaysactingasthereferencecategoryandhavingacoefficientofzero.Theoverall
impression is of a decline in class inequalities in Germany and Sweden but a
somewhat less clear picture in Great Britain. On the other hand, it appears that
among the older cohorts class differences were less marked in Britain and even
amongtheyoungestcohorttheyarestilllessthaninGermany.
Figure2showsthestrengthoftheassociationbetweenoriginsanddestinationsat
each educational level (educational categories 1ab and c for Sweden were
amalgamated for this figure). The parameters come from a logmultiplicative layer
effect model (Xie 1992) which gives a parsimonious account of the association
between origins and destinations across different educational levels. The
associationsaremeasuredrelativetothatinthelowesteducationallevel,whereitis
fixedat1.InSwedenandGermanythereisatendencyfortheassociationtoweaken
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athigher levels of education (though inGermany it isweakest at the lowerrather
than the upper tertiary level). In Britain too there is variation across educational
levelsbutthedifferencesarealittlelessmarked.
[FIGURE2HERE]
Figure3showstheexpansionofeducationamongmenoverthetwentiethcentury
by comparing the educational distributions of the second oldest and second
youngestcohorts ineachcountry.It isclearthatallthreecountrieshaveshownan
expansion,particularlymarked inBritain where the oldestcohortwas very heavily
clusteredatthelowesteducationallevel.
[FIGURE3HERE]
Figure 4 shows the trend in the gross association between class origins and class
destinationsinthethreecountries.7Forthepurposesofthefigure,theSwedishbirth
cohorts have been collapsed into seven to aid comparability. It is immediately
evident that the three countries display different patterns of change. In Sweden
therehasbeenaroughlyconstantdeclineintheorigindestinationassociationover
successivebirthcohorts:thisreplicatesfindingsofearlierstudiessuchasBreenand
Jonsson(2007).InGermany,aninitialstrengtheningwasfollowedbyasteepdecline,
commencingwiththethirdbirthcohort(born193139).Thislatterpatternisalready
wellknownfromearlierstudiesofGermansocialmobility(MllerandPollak2004).
7Herethetrendiscapturedusingthelogmultiplicativelayereffectmodel(Xie,1992).Innoneofthe
countries
does
this
fit
the
data
using
the
usual
p