breen educational expansion and social mobility

8/13/2019 Breen Educational Expansion and Social Mobility

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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

breen educational expansion and social mobility

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