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7/27/2019 Explaining Turnout Decline in Britain, 1964-2005; Party Identification and the Political Context.pdf
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Explaining Turnout Decline in Britain, 1964-2005: Party Identification and the PoliticalContextAuthor(s): Oliver HeathSource: Political Behavior, Vol. 29, No. 4 (Dec., 2007), pp. 493-516Published by: Springer
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7/27/2019 Explaining Turnout Decline in Britain, 1964-2005; Party Identification and the Political Context.pdf
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Polit Behav (2007) 29:493-516
DOI 10.1007/s 11109-007-9039-4
ORIGINAL PAPER
Explaining Turnout Decline in Britain, 1964-2005:
Party Identification and the Political Context
Oliver Heath
Published online: 21 August2007
? SpringerScience+BusinessMedia, LLC 2007
Abstract Turnoutdecline in Britain s greater han it firstappearssince changesin
the social compositionof the electorate have had a positive impacton turnout.This
paper finds that whereas a weakening in the strength of party identification is
associated with the long-term decline, the political context influences short-term
variation.Partisandealignment s also changingthe dynamicsof the determinants f
turnout.Since non-identifiersare more strongly influencedby the political context
than strongidentifiers,and there are now more non-identifiers hanpreviously, the
politicalcontext is becominga moreimportant actor in determiningwhetherpeoplevote or not.
Keywords Turnout . Party identification . Political context
As in many other maturedemocracies, there has been growing concern in Britain
aboutdeclining levels of electoralparticipation.This concern came to a head in the
2001 General Election when turnout ell by an unprecedented12 percentagepoints
from 1997 to just 59.6%, and reached its lowest level since full adult franchise.Recent research, both in the UK and elsewhere, has devoted considerable
attention to this phenomenon,and three main argumentshave been put forward n
order to explain it. Broadly speaking these relate to socialisation effects and the
impact of generationalchange (Miller 1992; Wattenberg2002; Clarke et al. 2004;Franklin 2004), partisan dealignment and the weakening of party identification
(Wattenberg2000, 2002; Dalton et al. 2000), and (decreased) mobilisation by
political parties (Rosenstoneand Hansen 1993).
Although nterlinked, ach of these theoriesoffersverydifferent nterpretationsor
thecauses of turnout hangeand,by implication, he natureof therelationshipbetween
O. Heath(F?)
Departmentf Government,niversityf Essex,Colchester 04 3SQ,UKe-mail:[email protected]
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494 Polit Behav (2007) 29:493-516
voters and parties. Accounts that emphasise the impact of generationalchangedominate the literature.Franklin's(2004) socialisation thesis posits thatvoting is a
habit whichis learned or not)in the firstfew elections thatanindividual s eligible to
vote in. Theelectoralcontext stimulatesnew votersto eitherparticipate rnot,andthis
leaves a 'footprint'on their futureparticipation.Turnoutdecline is thus primarilya
function of new cohortsentering he electorateand old cohorts eaving it.However, 'generation effects' are very difficult to empirically verify. Age,
cohort, and period are all co-linear which makes identificationimpossible unless
some simplifying assumptionsare made. For example, if age and cohort (year of
birth) are known, period (time of survey) is a given, or if cohort and period are
known, age is a given etc. Thus much previous researchon this subjecthas been
rathersuggestive. Analysis of the generationalbasis for turnoutdecline has tended
to rely on the constructionof 'psuedo panels' to illustratethe relativedifference in
levels of reportedturnout between different age cohorts over time. Clarke et al.
(2004) and Franklin(2004) adoptthis techniqueand arguethat modem day youngcohorts display much lower turnout han their olden day equivalents.The problemwith this approach s that it is not able to distinguishbetween the individual level
ageing processes that arerepeatedlyfound to have a positive impacton turnout,or
period effects, which may have short-term(ratherthan permanent)effects and
influence everyone (more or less) equally. But, perhapsmore fundamentally,the
main problem with accounts such as this is that they provide somewhat
deterministicexplanationsof political behaviour,which are unable to take account
of suddenchanges,
such as we observed in 2001 when there were over 5 million
fewer votes cast than in 1997.1Changesof this scale obviously cannot be the result
of generational replacement alone, so we must begin to look for additional
explanationsof turnoutchange elsewhere.
The second account of turnoutchange relates to the role of partyidentification
and partisandealignment. Since the work of Campbell et al. (1960, 1966) partyidentificationhas been a key featurein explanationsof why people vote, and since
its introduction o the British context by Butlerand Stokes (1969) it has repeatedlybeen found to be one of the most important predictorvariables for explaining
turnout(see Heath et al. 1985; Clarke et al. 2004). Althoughthere are conceptualambiguities surrounding he precise meaning of party identification,two broad
theories dominate the literature.Firstly,in its originalconception,it is firmlybased
in social psychology and can be regardedas a stable formof self-identification. t is
acquiredthrough early-life socialisationexperiences (Campbellet al. 1960; Butler
and Stokes 1969) and is strengthenedover time throughthe constantrepetitionof
voting andparticipating n the electoralprocess (Converse 1969, 1976). As such it
exerts a powerfullong-termforce on voting behaviour.By reducing he information
and decision making costs, partisanloyalties transform he act of voting from a
strictly instrumental ationalcalculationto a matterof habitborneout of a sense ofloyalty. This interpretationhas some similarities with the socialisation thesis of
generational replacement, and some scholars have suggested that partisan
1In 2001 there were 25,554,856 votes cast whereas in 1997 there30,496,924. PippaNorris TheBritish
ParliamentaryConstituencyDatabase 1992-2001.
1 Springer
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Polit Behav (2007) 29:493-516 495
dealignment contains a generational component (Clarke et al. 2004). However,
more recently this socialisationinterpretation as come underattack,and since the
1980s there has been a rise in the popularityof more rationalapproachesto the
studyof party dentification.Accordingto Fiorina(1981) party dentificationcan be
considereda weighted averageof past evaluationsof political parties,and follows
Downs' (1957) partydifferential erm,which states thatretrospectiveevaluationsofpolitical parties are a rationalway of calculating future expectations in decidingwhichpartyto vote for. It is continuallyupdated,andrepresentsa 'running ally' of
past evaluations. This line of thinking has been developed by, inter alia, Stokes
(1992), Achen (2002), Stewartand Clarke(1998) andClarkeet al. (2004). Although
differing n detail,theircore argument s thatpartyID is notjust the productof earlylife socialisation but responds to the macro political context and is sensitive to
political cues. It is updated bothin terms of directionandintensity)by information
relatingto evaluations of party political behaviour and variationsin the economy
(Clarkeet al. 2004: 28).
Lastly, the role of mobilisation has been emphasised by Rosenstoneand Hansen
(1993). This takesvarious orms,ranging rommobilisationby parties knockingup),civil rightsandcommunityorganisations o mobilisationby thepolitical contextand
the structureof electoralcompetition.Rosenstone andHansen(1993: 161) contend
that"people participaten electoralpolitics because someoneencouragesor inspiresthemto takepart",andso turnoutdecline is, accordingto them,mainlythe resultof
decreased mobilisation. This rather broad definition of mobilisation essentially
containstwo components.The firstrelatesprimarily o campaigneffects by politicalparties,specifically face to face campaigning.They arguethata move from labour
intensive door-to-doorcampaigning, o money intensive advertisingcampaignshas
had a negative impact on turnout(ibid 217-218). The second point relates to the
impactof the structure f electoralcompetitionand factorsthatmay stimulatepeopleto participate.Accordinglyturnout s likely to be higherin elections that areclosely
fought, since each vote counts (see also Denver and Hands 1974, 1985; Pattie and
Johnston2001; Clarkeet al. 2004; Franklin2004). However,since there hasbeen no
uniformdeclineinthecompetitivenessof elections inBritain,andthe electoralcontext
changesfrom election to election,thisfactorappearsunlikelyto explainthelong-termturnoutdecline observedover the last few decades,although t couldexplaina sudden
droplike, for example, in 2001.
Althougheach of these theories has received some empirical support,there has
been little attemptto simultaneouslymodel theirrelative importance n relation to
each other in order to explain their unique impact on the dynamics of turnout
change. Previous research on turnout has thus tended to provide only partialaccounts of why people vote. This is partly because two different, yet not
incompatible,methodologicalperspectiveshave dominated he analysisof turnout.2
2 Therehavebeen many studiesthat examine the individual evel determinants f turnoutat one pointin
time (Clarkeet al. 2004: 237-260; Whiteleyet al. 2001) and from an over time perspective(Miller 1992;Abramsonand Aldrich1981).There have also beenmanystudies thatexaminethe aggregate evel impactof thepoliticalcontextat theconstituency evel (Whiteleyet al. 2001; Denver andHands1974, 1985)andat the national level over time (Clarkeet al. 2004: 261-268; Franklin2004). However, therehave been
very few attemptsto synthesise these two approaches ogetherto explain turnoutchange.
ISpringer
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496 PolitBehav 2007)29:493-516
The first uses cross-sectional survey data taken at one point in time to examine
individual level factors which explain voting in terms of social class location,sense
of political efficacy andparty dentificationetc. (see Heath et al. 2001; Verba et al.
1995). The second uses aggregatelevel data to examine the political context, such
as the expected closeness of the contest, the ideological difference between the
parties and the level of campaign spending and mobilisation (see Whiteley et al.2001; Pattie and Johnston 1998; Denver and Hands 1974, 1985). By considering
only time series aggregatedata there is the risk of ecological fallacy or spuriouscorrelation.However, by consideringonly cross-sectional data it is only possible to
discriminate between people within elections, not people across elections. This
meansit is not possible to examine factors thatmay influenceeverybody n the same
way, such as the expected closeness of the contest.
Notableexceptionsthat have attempted o integrate hese two approaches nclude
Rosenstone and Hansen (1993), Heath and Taylor (1999), Pattie and Johnston
(2001), and Franklin(2004). Rosenstone and Hansen (1993) comparethe relative
impact of individual-level factors and contextual-level factors on turnoutchange,but since theiranalysis is only based on two periods(the 1960s vs. the 1980s) their
results are unable to uncoverpreciselyhow thepoliticalcontextshapesand interacts
with individual characteristics.Similarly,PattieandJohnston(2001) combine over
time aggregatelevel analysis with individuallevel survey analysis from 1992 and
1997 to try andexplain turnoutdecline between the two elections. And, in perhapsthe most comprehensive attemptso far, Franklin(2004: Chapter6) examines the
impactof the electoral context on individual turnout
using pooledcross sectional
survey data from Germany,but he does not model the impact of this on turnout
change. Rather,his chapterson turnoutchange are all based on aggregatedata.By
building on this previous research, and extending the number of elections under
investigation, this paper integrates these two approaches by modelling both
individual evel factorsand contextual evel factorssimultaneously. n doing so it is
able to test the impact of both short-termcontextualfactors and long-term socio-
compositionalfactorson turnoutchange, and examine the interplaybetween them.
Data and Methods
In this paperI synthesisethese two methodologicaland theoreticalperspectivesand
analyse a nested model of electoral behaviour that examines individuals within
years.To do this I use pooled cross-sectionaldata fromthe BritishElection Studies
1964-2005 (see Appendix for details). This is the longest time series data on
political behaviour available in the UK and covers 12 elections and consists of
32,085 interviews. By using this approachI am able to pay particularattentionto
compositionalchanges thathave takenplace in the distributionof the sociologicaland attitudinalcharacteristicsof the electorate.Compositioneffects of this type are
rarely consideredin studies of turnout,which is a severe drawback(althoughsee
Heath and Taylor 1999). Concentrating olely on the effects of variables without
taking into account their compositional distribution in the electorate can be
particularlymisleading since in very high turnoutelections approaching100%,no
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Polit Behav (2007) 29:493-516 497
variables will have significanteffects since everyone will vote. To make sense of
turnoutchange it is therefore necessary to model compositional changes in the
electorate,as employedin this paper,rather han ust concentratingon the effects of
variables to see if they have changed or not.
Of course it is possible that, as the composition of a factorchanges, so does its
effect.3 If this is the case then the assumptionof parametricuniformityover timemay not be valid, and modelling the effect of compositional changes may be
misleading. To test for this possibility I thereforespecify a number of interaction
terms between the independentvariables and year. Broadly speaking the results
show thatthere is no systematicparametricvariationover time, certainlynone that
is related to the composition of the variable.4 The assumption of parametric
uniformityis thereforefairly robust.
Turnout 1950-2005
Turnout levels in Britain have dramaticallyfallen over the last 50 years, from
around80%in the 1950s to around60%in the 2000s (Fig. 1). Fromthe equationof
the regression line we can see that on average turnout has fallen by about
3Forexample,the salience of class in determining urnoutmay weaken as society becomesmoremiddle
class. However, it is also possible that the effect of class may be stronger n some years thanin others
withoutany generaltendencyto change.If this is the case thenthe source of the variation s unlikelyto be
due to long-termforces and may be the result of particular hort-term actors, possibly relatingto the
politicalcontext. Underthese circumstances he assumptionof parametricuniformity s still broadlyvalid
but it may be necessaryto try and specify additional nteraction erms in orderto explain the differingeffects from year to year.
4 Including he interactionbetween class andyeardoes not resultin an improvementn the fit to the data
(Z2 change eq 7.4, df = 11, p = .767). This suggests that the working class have not become
disproportionatelyess likely to vote with Labour's shift to the right(Budgeet al. 2001). However,there
have been some modestchanges in the odds of voting over time by tenure(X2change eq 24.3; df = 10;
p = .007), and rathergreaterchanges by Franchise(X2changeeq 32.7; df = 8, p < .0005) partyID (X2
changeeq 42.5; df = 11,p < .0005) andage (Q2changeeq 34.4; df = 11;p < .0005). The changes bytenureare
relatively unimportantince it is
onlyin 2005 that
significantdeviationsareobserved
(whentheeffect was stronger han n otheryears).Thechangesby Franchisearealso modest(theeffect is somewhat
weaker in 1970 and 1975 andis somewhatstronger n 1987) suggestingthatthere is little structureo the
variation.In both instances, without sound theoretical ustificationfor including additional interaction
terms,the assumptionof parametrichomogeneityis thereforeupheld.The changes by age and partyID
aresomewhat more interesting.There are significantdifferencesin the effect of the age variable n 2001
and 2005 (the two elections with particularlyow turnout).In both these elections the effect of the ageterm was stronger han usual(meaningthatthe oddsof votingincreasemorerapidlywith eachyearof ageor thatyoung people were even less likely to vote in relation to old people thanusual). Thereare also
significantdifferencesin the effect of the partyID variable n 1983 andOctober1974, when the effect of
partyID was somewhat weaker than normal(meaning that strong identifiers were not so much more
likelyto vote than non identifiers than at other
times),and in 2001, when the effect of
partyID was
somewhatstronger han normal(meaningthat weak identifierswere even less likely to vote thanstrongidentifiers hanat othertimes). These short-term hangessuggestthatthe effect of age andpartyID maybe related to the political context (Franklin 2004). Since there has been no long-term change, and
moreover,since we can be surethatthechangesthathave takenplace are not relatedto the distribution f
the variable n the population, here is no reason to relaxthe assumptionof parametrichomogeneity(as a
general principle)at this point. However,we will return o these points in the second partof the paperwhen we considerthe political context.
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498 Polit Behav (2007) 29:493-516
90-
85
80-
0 75
70
. 65
60
55 - y = -0.2894x+ 646.31
R2 = 0.6186
50
1945 1955 1965 1975 1985 1995 2005 2015
Fig. 1 Turnout in Britain, 1950-2005 (official results). Source: 1945-1997 from Heath and Taylor
(1999: 165);FromElectoralcommission 2001 and 2005 reports http://www.electoralcommission.org.uk/
election-data/index.cfm)
0.29 percentagepointsa year, althoughfrom the dispersionof thepointsaround his
line we can see that the decline has not been uniform and in some years it dropped
considerably more than expected, whereas in other years it actually increased.
However,overall, it is evident that a trendof long-termdecline has takenplace. The
R2 of 62% shows that notwithstanding he short-termresidual variation,a linearmodel of decline providesa good fit to the data. This result is notjust dependenton
unusualstartor endpoints,and is robustto the exclusion of any particular lection.5
This holds even when as many as four elections are randomlyomitted at a time.
Indeed, even if the two highest turnout elections of 1950 and 1951 and the two
lowest turnoutelections of 2001 and 2006 arediscountedfromthe analysis,there is
still a significant long-term decline in levels of turnout.6Moreover, specifying a
linear trendover time providesa far betterfit to the data thana non-lineartrend.A
regressionusing the natural ogarithmof years passed since 1949 accountsfor only
47% of the variation,suggesting that this does not provide such a good fit to thedata. Although the trend of turnoutdecline is most pronouncedsince the 1950s,
there is also significantevidence of a longer term general downward trend since
1929 (the firstelection in which women were eligible to vote). On average, since
1929, turnouthas fallen by 0.14 points a year.7There is thus evidence of two distinctphenomena:a general long-termtrendof
decline, particularly since the 1950s, accompanied by short-term fluctuation
(residual variation).To understand he dynamics of turnoutchange it is therefore
5 Bootstrapping eveals that theseresults are robustto the exclusion of any particular lection, and arein
fact strongerwhen some elections are omitted.6 Linear regression of turnoutdecline 1955-1997: % turnout= 77.7 - 0.08 year (one sided t test
significantat 0.1 level).
7 Linear regression of turnout decline 1929-2006: % turnout= 79.7 - 0.14 year (one sided t test
significantat 0.01 level).
4Springer
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Polit Behav (2007) 29:493-516 499
necessaryto exploreboth these phenomenaandanalysethe factorswhich determine
each of them. Only by doing this is it possible to get a clear idea of how much
secular decline has takenplace over and above the short-termvariation rom which
turnout evels can easily bounce back. I arguethat long-termchanges in the socio-
psychological compositionof the populationareresponsiblefor the seculardecline,
and short-termchanges in the political context are responsible for the residualvariation. The firstpartof this papertherefore examines structural hanges in the
composition of the electorate,paying particularattentionto hypotheses of turnout
changederivedfrom generationaldifferences andpartisandealignment.The second
partof thispaperthenexamines the short-term actors which may cause the residual
variationaround he long-termdecline and considers the political context. In doingso I address he interplaybetween these factorsand theirimplicationsfor the future.
Social Change and Turnout
Demographic actors such as social class, housingtenure,age, genderandeducation
have been found to have modest associations with turnoutat the individual level in
Britain(Swaddleand Heath 1989; PattieandJohnston1998; Whiteley et al. 2001),
althougha very strongeffect elsewhere,particularlyn the UnitedStates (Verbaand
Nie 1972;Verba et al. 1995). In general,people with high socioeconomic status are
more likely to turn out thanthose with low status.Accordingto Verbaet al. (1995)socioeconomic status acts as a civic resource that facilitates
participation byreducingthe costs associatedwith understandingpolitics in general and the policy
positionsof the parties.Similarlyhousingtenurehas also been found to have a more
direct effect on voting by reducingthe costs of registration Brians 1997).As in manyother advanced ndustrialdemocracies, n the last 50 yearsthere have
been substantialchanges in the socio-economic composition of the electorate in
Britain which would appear to favour higher levels of turnout. The class
composition of the British population has gone througha major transformation,with the workingclass shrinkingand the Salariatexpanding.8The averagelevel of
home ownership s also much higherthanit used to be, andthe average age of theelectorate is older.9
Social changeof this type is often consideredto represent omethingof a paradoxin relationto levels of turnout.Since the middle class are more likely to vote than
the working class, and there are more middle class people in Britain today than
previously,it would seem logical all otherthingsbeing equal that turnout hould be
higher.The fact that it isn't means thatthe positive impactof these social changesmust be outweighed by the negative impact of othervariables.
This brings us to arguments about generational change. However, since, as
previously mentioned, there are identification problems when age, period and
8 If respondentdoes not have social class then social class of spouse is used as a proxy.
9 After 1992theaverageage of peopleon the electoralregisterwas substantiallyolderthan t was before.
However,rather hanreflectinga suddendemographic hangethis is probablymorelikely due to council
tax avoidance,which meant that in the 1990s many people, particularlyhe young,did not sign up to the
electoralregister.
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500 Polit Behav (2007) 29:493-516
generationare considered simultaneously,it is thereforenecessary to make some
simplifying assumptions.To this end I draw on Franklin's (2004) socialisation
thesis which providesthe most plausibleaccountof why different cohortsmay turn
out at differentrates. Franklinsuggests that differentgenerationsor cohorts exhibit
different rates of turnoutdepending upon the characterof elections they were
exposed to when they were firstpolitically socialised. People coming of age in lowturnoutelections are likely to vote at lower rates throughout heir adult life than
people coming of age in high turnoutelections.
Therefore,ratherthan measuringcohort directlyI follow Franklinand measure
turnoutat the first election that each electoral cohort was eligible to vote in. For
example, people born between 1938 and 1943 were first eligible to vote in 1964,when turnoutwas 77.1%, so each person in this cohort scores 77.1 on the cohort
variable, people born in 1944 and 1945 were first eligible to vote in 1966, when
turnoutwas 75.8%,andso score75.8, andpeople bornbetween 1946 and 1952 were
firsteligible to vote in 1970 when turnoutwas 72.0% etc. This is repeatedfor eachelectoral cohort bornbetween 1904 and 1987. The measurethus tells us whetheror
not respondentswere socialised in relatively high turnoutelections.
Although this approachsolves the identificationproblem, since the electoral
cohort variable is not collinear with age andperiod, it possibly underestimates he
effect of generation.It is a theoreticalconstructrather hanan empiricalconstruct,
and as such theremaybe additionaldifferencesbetween generations hat it does not
take into account (for example in strengthof party identification).Moreover, the
measurementof the theoryis not perfecteither.In his originalformulationFranklin
suggests that socialisation takes place over a relatively long period-he cites three
elections-but the measure used here is based on exposure to just one election
(otherwise it would mean droppingthe first two and last two elections from the
series which wouldbe too heavy a price to pay). This meansthe expectedeffects of
the variable are likely to be somewhat weaker than Franklin would suppose.
However, despitethese limitations t still providesa potentially mportant ource of
turnoutchange, and at least allows us to consider the possible impacton turnoutof
generationalchanges, even if these are not captured n theirentirety.Franklinalso
arguesthat the extension of the franchise had
important long-term implicationssince people who reached the age of maturitybefore full franchisewas extended
were in a sense socialised into the act of not voting.10 The proportionof the
electorate who came of age before full franchisewas implementedhas decreased
from 23% in 1964 to less than 1%in 1997 and almost nothingthereafter.
Lastly, over the last few decades there has been a substantialdecline in the
strengthof party identification(see also Crewe et al. 1977; Dalton 2000; Clarke
et al. 2004). This phenomenon s notjust limited to Britainor the United States.In
an analysis of 19 advanced democracies, Dalton (2000) finds a similar trend in
practicallyevery country,and in the United States a similardealignmenthas beenfound to have a substantial mpacton turnoutdecline (Abramsonand Aldrich 1981;
10Therehavebeen various amendments o the franchise n Britainover the last 100 yearsor so. In 1918
women over 30 were given the vote for the firsttime, and all men over 21 were eligible to vote (priorto
that there were propertyrequirements or men). In 1928 full adult franchise as we know it today was
establishedwhen the age of maturity or women was reducedso that it was the same as for men.
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Polit Behav (2007) 29:493-516 501
Rosenstone and Hansen 1993; Wattenberg2000; althoughsee Franklin2004 for a
counterargument).
Model Specification
To untanglethe impactof these differenttrendsandestablish theiruniqueimpacton
turnoutI specify a dynamicmodel which takes into accountcompositionalchangesin the electorate over time. To do this I examine a series of logistic regressionmodels. (Since turnoutis a binary variable, coded 1 for voted and 0 for did not
vote)." The logistic model examines individualsnested in years and whethertheyvoted or not. The firstmodel containsonly dummytermsfor eachelection year.The
magnitudesof these coefficients indicate the level of observed variation n reportedturnout n relationto the baseline figurein 1964, andcan be viewed as unexplained
year effects. The subsequent models each control for the composition of an
additionalsociological factor: model 2 also controls for age, sex, social class and
tenure;model 3 and 4 control for the generationalterms of full franchise (this is
interactedwith sex since priorto 1928 women did not have equal voting rights)and
electoral cohort(turnoutat firstelection thatpersonwas eligible to vote).12Finally,model 5 controlsfor partyidentification.13By controllingfor age, electoralcohort
and year in this way we are able to untangle the independent impact of age,
generationandperiodwhich have provedso problematic o differentiatebetween in
previousstudies on turnout.Thus the full
specificationfor the final model is:
Pr(Voting) = fn(Bo+ B1 1966 + B2 1970 + B3 1974F+ B4 19740 + B5 1979
+ B6 1983 + B7 1987 + B8 1992 + B9 1997 + B102001 + B112005
+ B12Age + B13Class+ B14Male+ B15Tenure+ B16Franchise
+ B17Franchise Male + B18Electoralcohort+ B19Party D) (1)
The extent to which controllingfor these factors influencesthe magnitudeof the
coefficients for the yearly dummyterms reveals the extent to which variation n, for
" Turnout s measuredby whetherrespondentsreportedhavingvoted in the election, or not.The base isall those on the electoralregister.Reported urnoutconsistentlyoverestimatesactualturnoutor validated
turnout. Swaddle and Heath (1989: 539) suggest that four main reasons account for this discrepancy:
misreportingby survey respondents,responsebias, failure to trace all movers, and redundancy n the
electoralregister.However,Heath andTaylor(1999) show a fairlyconstantrelationshipbetween official
turnoutandreported urnoutacross the years,with the latter racking he formeralbeit at a higher evel. If
the relationshipbetween the two measuresis constant, then this will affect the constant term in the
regressionsbut will not affect the parameter stimatesof interest.12 Electoralcohortsare definedby the first GeneralElection that an individualwas eligible to vote in and
the aggregateturnout n this election is computedfor each individual n that cohort. The rangeof valuesfor electoralcohort are centred on zero. People bornbefore 1904 (who were thus eligible to vote beforefull franchise was implemented)score zero. The dummyterm for Franchise hus tells us whetherpeoplebornbefore full franchise was implemented urnoutdifferentlyfrom those bornafter,and the interaction
with sex tells us whetherthis was different for women (who did not have the vote) and men.
13 Partyidentification s measuredusing the standard our point scale (0 = None; 1 = Not very strong;2 = Fairly strong;3 = Very strong).
ISpringer
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502 Polit Behav (2007) 29:493-516
example the age distributionof the electorate,influences turnoutchange. When we
control for age we hold the age distributionof the populationconstant over time. If
year effects then become largerwhen we control for age we can conclude thatthe
change in the distribution of the variable in question had a positive impact on
turnout evels, and similarly, if year effects become smaller we can conclude that
the variable had a negative effect. The addition of factors by blocs thus adds adynamic component to the model that shows how variation in the independentvariables over time influences variation n levels of turnout.
Results
Table 1 shows the parameter stimatesfor five models. Since the sample size is so
large it is appropriateo use robuststandard rrors n the analyses. The first model
contains only the dummy terms (or unexplainedperiod effects) for each election,with 1964 set as the reference category. The second model also includes age, sex
(1 = Male, 0 = Female), class (coded 1 for working class and 0 for other) and
housing tenure (code 1 for home owner and 0 for renter/other)as explanatory
variables,the third model also includes franchise(coded 1 for came of age before
full franchise,0 for post-fullfranchise)and franchise nteractedwith sex, the fourth
model also includes electoral cohort and the fifth model includes strengthof partyidentification.
From Model 5 we can see thatholding everythingelse constant,the log odds of
voting increase with each year of age (b = 0.02), are significantly lower for the
workingclass than the middle class (b = -0.32), and significantlyhigherfor home
owners than for renters (b = 0.49). There are also clear generation effects. The
franchise term and franchise interactedwith sex term are both highly significant,
althoughthe sex term by itself is not. This implies that women who came of agebefore full franchise was extended were much less likely to vote in subsequentelections than women who came of age with equal rights(b = -0.86), whereas men
were unaffectedby the extension of the franchise to women (b = -0.86 + 0.88 =
0.02).The second measure of
generational change,electoral
cohort,is also
significant.In line with Franklin'sthesis, people who came of age in high turnout
elections are also morelikely to vote in subsequentelections thanpeople socialised
in low turnoutelections, althoughthe magnitudeof the effect is small (b = 0.01).
Finally,we can see that the log odds of voting are muchhigherfor those with a very
strong partyidentification hanfor those with no identificationat all (b = 0.64).
However, in orderto understand he determinants f turnoutchangeit is of much
more interestto examine the impactthatcontrollingfor each of these variableshas
on the magnitudeof the coefficientsfor each of the election yeardummyterms. The
parameter stimates from Model 1 show thatreported urnoutwas significantlyandsubstantially ower in each of the subsequentelections after 1964. Forexample, the
log odds of someonevoting in the 2005 election were much lower than the log odds
of someone voting in the 1964 election (-0.75). However, when we control for the
compositionof age, class and tenure(that s whenwe hold the age distribution f the
electorate etc. constantover time) Model 2 shows that the predicted log odds of
SSpringer
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Table 1 Reportedturnout over time and the impact of social change, 1964-2005, log odds (with robust standard
Model 1: year Model 2: +demogs Model 3: +franchise Model
b Robust SE b Robust SE b Robust SE b
1964
1966 -0.45*** 0.00 -0.45*** 0.01 -0.47*** 0.01 -0.47*
1970 -0.59*** 0.00 -0.57*** 0.00 -0.60*** 0.01 -0.59*
1974 -0.10*** 0.00 -0.11*** 0.00 -0.16*** 0.02 -0.16*
1975 -0.32*** 0.00 -0.32*** 0.00 -0.38*** 0.02 -0.37*
1979 -0.29*** 0.00 -0.30*** 0.01 -0.38*** 0.03 -0.37*
1983 -0.47*** 0.00 -0.54*** 0.01 -0.62*** 0.03 -0.61*
1987 -0.25*** 0.00 -0.36*** 0.01 -0.45*** 0.03 -0.44*
1992 -0.17*** 0.00 -0.26*** 0.01 -036*** 0.04 -0.35*
1997 -0.45*** 0.00 -0.63*** 0.02 -0.74*** 0.04 -0.72*2001 -0.81*** 0.00 -1.07*** 0.03 -1.19*** 0.04 -1.16*
2005 -0.75*** 0.00 -1.03*** 0.03 -1.15*** 0.04 -1.12*
Age 0.02*** 0.00 0.02*** 0.00 0.02**
Working class -0.29*** 0.02 -0.29*** 0.02 -0.29*
Male 0.01 0.03 -0.03 0.03 -0.03
Tenure 0.46*** 0.06 0.46*** 0.06 0.45**
Franchise -0.89*** 0.15 -0.87*
Franchiseby male 0.83*** 0.12 0.83**
Electoral cohort 0.01**
Party ID
Constant 2.08 0.00 1.14 0.10 1.15 0.10 1.17
aQ
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Table 1 continued
Model 1: year Model 2: +demogs Model 3: +franchise Model 4
b Robust SE b Robust SE b Robust SE b
z2222
(df=
11)958
(df=
15) 1,032 (df = 17) 1,041Nagelkerke R2 .01 .05 .06 .06
(N = 31,188)
***Significant at p = .001
**Significant at p = .01
*Significant at p = .05
CD
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Polit Behav (2007) 29:493-516 505
voting in 2005 are even lower thanthe log odds that we initially observed (-1.03
compared o -0.75). Controlling or franchise(Model 3) also has a similareffect; in
each case the magnitude of the coefficient for the dummy terms since 1964
increases.This shows thatchangesin the distributionof these social variableswould
have had a positive impact on levels of turnoutceteris paribus, and that if the
present day electorate had the same social composition as the electorate in 1964thenturnout n the 2000s would have been considerably ower than it actuallywas.
Controllingfor electoral cohort (model 4) has practicallyno impacton the yeareffects: hardlyany of the dummytermschange in magnitude (althoughwhere theydo change it is in the expected direction).This suggests that Franklin'sfootprint
hypotheses,as operationalisedhere, is not well equippedto explain turnoutchange,
although it has merit in other respects. Somewhat contraryto received wisdom,
generationalchanges have on aggregatethereforehad a positive impacton turnout.The replacement n the electorateof women politically socialised before 1928, who
were much less likely to vote thanmen, with women socialised after 1928, who had
more or less the same likelihood of voting as men means that ratherthanlosing a
civic generationwe have in fact gained a fully franchisedgeneration.Since these social changes would have had a positive impact on turnout,to
explainthe generaldecline it is thusnecessaryto search for explanationselsewhere.
To do this I first consider the impact of partisan dealignment. Controlling for
partisanshipmodel 5) has a substantial mpacton the magnitudeof the coefficients
for each of the different election dummy terms. From Model 4 we can see that,without
controllingfor
partisanship, eported urnoutwas
significantlyower thanin
1964 in each of the subsequentelections. However, when partisanship s added to
the model, reportedturnout s no longer significantlylower in 1974 or 1992 and,moreimportantly, he magnitudeof the dummyterms aregreatlyreducedacrossthe
board.Forexample,the magnitudeof the coefficientfor 2005 decreases from -1.12
in model 4 to -0.72 in model 5, when partyID is added to the equation.It is possible to get a clearer idea of the magnitude of all these changes by
transforming he log odds into probabilities,which are slightly easier to interpret.14
14This is done using the following function:Pv= (elogxo+logxi)/(1 + elogxo+logxi), wherelog xo refersto
the constant(1964) term and log xi refers to the dummyterm for a particularelection year. Thus, the
probability of voting in 2005 (calculated from the log odds presented in Model 1 in Table 1) is
e2.08-0.75/1 e2.08-0.75 - 3.79/4.79 = 0.79. Or, put another way reported turnout among survey
respondentswas 79% (Table 2). This correspondsto our observed known value from the surveyestimates. We can then calculate the level of turnout n each year assumingthat variousdemographicvariableshadstayedthe same since 1964by comparing he magnitudeof the coefficient for each dummyterm afterwe control for age, sex, class and tenureetc. (Model 2) to the constant1964 term in Model 1.
This implicitlyholds demographicvariablesat the samedistributionas in 1964 and allows us to see what
turnoutwould have looked like in subsequentyears had therebeen no change. Thus, the probabilityof
voting in 2005, controlling for demographics(calculatedfrom the log odds presentedin Model 2 in
Table 1) is e2.08-1.03/ + e2.08-1.03= 2.83/3.83 = 0.74. Or, put anotherway, had the age, class and
tenureetc. distributionof thepopulationbeen the samein 2005 as it was in 1964 reported urnoutamongsurvey respondentswould have been 74%,or 5 percentagepoints lower than what we actuallyobserved.
These calculations are repeatedfor each block wise step.
6LSpringer
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506 PolitBehav 2007)29:493-516
Table 2 presentsthe full results. We can see thatthe observedprobabilityof votingin 2005 is 0.79 (Model 1). Controllingfor demographics(Model 2) reduces the
predictedprobabilityof voting in 2005 to 0.74, controllingfor franchise(Model 3)reducesit even further o 0.72, controllingfor electoral cohort(Model4) leaves the
predicted probability of voting unchanged on 0.72. From this we can see that
holding demographic changes in the social and generational composition of theelectorate constantovertime, the predicted evel of reported urnout n 2005 (Model
4) is some 7 percentage points lower than the observed level of 79% (Model 1).Fromthis we can inferthat,otherthingsbeing equal, social changeboosted turnout
by about 7 percentagepoints,or that the 'real' decline in levels of turnout s in fact
7 percentagepoints greaterthanwhat it looks like on the surfacewhen we fail to
take into account social change.
Controlling for party ID (Model 5) greatly reduces the magnitude of this
decline. In real terms without controllingfor party identificationreportedturnout
fell from 89% in 1964 to 72% in 2005-a decline of 17 percentage points;however controlling for party ID reportedturnoutin 2005 was 80%-a decline
of just 9 percentage points from 1964. This finding contrasts with Franklin's
(2004: 164) claim that party ID does not generate high turnout.However, party
dealignmentis clearly not the whole story. Even controllingfor party ID turnout
was still substantiallylower in 2005 than it was in 1964, so there are clearlyadditional sources of turnoutchange that we need to consider. But the generaltrend of decline is greatly reduced: plotting predicted turnout from model 4
against yearreveals the linear trend of decline since 1964 in 'real terms' is
-0.30 percentage points per year (with an R2 of .61), but when we take partyidentificationinto account the average rate of decline falls to just -0.13 points
per year (with an R2 Ofjust .25). This suggests firstly, that partisan dealignmentaccounts fairly well for any secular decline, and secondly, that the remainingsources of variation probably do not follow a linear function since the R2 is
extremely low.
Short-term Factors: Political Context and Turnout
The above analysis suggests that,if party dentificationhad not decreased n Britain
over the last 40 yearsthenit is doubtfulwhetherthere would have been any generaldecline in levels of turnout.However, this does not mean that turnoutwould not
have variedfrom election to election. Previous researchhas shownthatthe political
context-particularly the expected closeness of the race-influences turnout evels
(Rosenstone and Hansen 1993; Pattie and Johnston 2001; Clarke et al. 2004;Franklin2004). Butbecause thepoliticalcontextchangesfrom electionto election it
cannot be expected to explain any general decline (cf. Rosenstone and Hansen1993). However, it can account for residual variationand explain why turnoutwas
particularlyhigh in some years and particularly ow in others.
Figure 2 shows the perceived ideological difference between the parties over
time (2 = A great deal of difference; 1 = Some difference; 0 = Not much
SSpringer
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Polit Behav (2007) 29:493-516 507
Table 2 Predictedreportedturnoutover time andthe impactof social change, 1964-2005,
probabilities
Model Model 2 Model 3 Model 4 Model 5
1 year +demogs +franchise +electoral +partyID
cohort
1964 89 89 89 89 89
1966 84 84 83 83 83
1970 82 82 82 82 82
1974 88 88 87 87 89
1975 85 85 85 85 86
1979 86 86 85 85 88
1983 83 82 81 81 85
1987 86 85 84 84 88
1992 87 86 85 85 88
1997 84 81 79 80 84
2001 78 73 71 71 79
2005 79 74 72 72 80
difference).'5 The differences between the Conservative and Labour party were
perceived by the electorate to be at their greatest during the 1980s, and at their
narrowestduring he 1970s andin the late 1990s/early2000s.'6 Even thoughthereis
a considerableamount of individuallevel variation, his does not mean thatpeoplewho think that there is a great deal of difference between the parties in 2001, for
example are somehow wrong. Rather,responses to the question are likely to bedeterminedby what the respondentviews as the salient issue, which will varyfrom
person to person. In this respect the perceived ideological difference is a more
useful measurethana more 'objective' measure based on manifesto content. From
Fig. 2 we can see that the perceivedideological difference between the partieshas a
non-linear association with time. This means there is no evidence of either a
uniformincrease or decrease since the 1960s.
In similarfashion,the expected closeness of the contest varies from one election
to thenext, and theexpectedgap atT1 is a very poorpredictorof the expectedgapat
T2. For example the contest in 1992 was expected to be very close (the meandifference in the polls was in fact 0.4 percentagepoints) whereasin 1997 the polls
put Labour 16 percentage points ahead (Fig. 3).Of course, not everyone may react to these stimuli in the same way. From
analysis in the firstpartof the papertherewas some evidence thatthe age variable
15 In the 2001 and 2005 surveythe questionon the perceived ideological difference was asked in the
mailbackpartof the survey.Non responsesare set to the mean for the year in question.16 This fits well with conventionalaccountsof the difference between the parties.In the 1970s andlate
1990sHaroldWilson andTony Blairrespectively,steered he LabourPartyawayfromthe Left andcloser
to the Centreground, n bothcases reducing he gap between the two mainparties.By contrast, he 1980s
was characterisedby sharpconflictbetweenMrs.Thatcher'sbrandof neo-conservative iberalismon the
one hand,and Labour'smilitant eft on theother.This, combinedwith the narrowwidth of theconfidence
intervals,suggeststhat on the whole the electorateunderstood airlywell the ideological platformsof thetwo majorpartiesand how they differed from each other, and that there was not much divergence in
opinion.
IL Springer
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508 Polit Behav (2007) 29:493-516
1.80 -
00 1.60 -
C 1.40 t
O 1.20
I I1970 1980 1990 2000
Fig. 2 Partydifferential:perceived deological differencebetween ConservativeandLabour,1964-2001
(0 = not much difference, 1 = some difference,2 = a lot of difference),N = 32,085
and party ID behave differently in different electoral contexts. Since party
identification structures ndividual behaviour and makes it relatively stable andpredictable,it is possible that short-termfactors may have a stronger impact on
those with weaker identificationsince their decision to vote is less ingrained.We
would thereforeexpect the impact of partyID to be greaterin electoral contests
where there is less at stake. To test thishypothesisit is necessaryto fit aninteraction
term between partyidentificationand the perceiveddifference between the parties.
Similarly,Franklin uggests thatyoung people are also morelikely to be influenced
by the politicalcontextthanold people who have become stuck in theirways, so this
interaction erms is also included as a control.There areproblemsof identification f
the model contains dummy terms for all the election years and aggregate levelelection variables since period effects are largely the result of the characterof the
election variables.The finalmodel thereforeonly includesthe dummytermsfor the
years that are significantafter all the otherindependentvariables arecontrolled for
(these are 1966, 1970, 2001 and2005). The equationfor the finalregressionmodel
can be expressedas:
Pr(Voting)=fn(Bo + B1Age + B2Class+ B3Male+ B4Tenure
+ B5Electoral ohort+ B6Franchise+ B7Franchise Male
+ B8Party D+ B9Ideologicaldifference+ B10Expectedpolldifference
+ BI Previouspolldifference+ B12 deologicaldifference Party D
+ B13 deologicaldifference* NewVoter)
(2)
l Springer
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Polit Behav (2007) 29:493-516 509
20.00 -
a) * *
S15.00-
()
0
V)a) *t
S10.00
1,)
"00
t'. 5.00 -
xw, *
O*
O*
0.00-
1970 1980 1990 2000
Fig. 3 Expectedcloseness of the race: meangapbetweenConservativeandLabourparty n finalopinion
polls 1964-2005. Source: 1965-1997 from Heath andTaylor(1999: 178);2001, 2005 fromall published
polls (http://www.mori.com/polls/trends/voting-allpub-trends.shtml)
whereBo
is theconstant,
B1-B8
are the individual evelparameters
romequation1,and B9-B13are the parametersassociatedwith the political context.
Table 3 presents the results from the final model. Overall the model performs
quite well-particularly for the purpose of explaining change over time. The
dummy terms for the elections in 1966, 1970, 2001 and 2005 are still significant,
meaning that there are still some unexplained period effects that the model is not
able to account for. Althoughthis should be treatedwith caution,it is also possiblethat these additionalsources of variationmay be somewhatparticularisticn nature,
meaningthatthey cannoteasily be modelled. Forexample, in 1970 the election was
held duringthe summerholidays when many people were away. However, the factthat the final model managesto reduce the magnitudeof these coefficients,and none
of the otherdummytermsare significantmeans that the model is fairly well able to
capture the dynamics of turnoutchange in Britain over the last 40 years. For
example, in 2001 the coefficient for the 'real' decline (when only demographicsare
included in the model) is -0.725. This is reduced is to -0.584 when partyidentification is included, and -0.300 when the political context variables are
included.
From Table 3 the firstthingto notice is thatthe political context variableshave a
significantimpact on turnout.The log odds of voting increase when there is a bigideological difference between theparties(b = 0.33) anddecreasewhen the election
is expected to be a landslide (b = -0.02). The closeness of the race from the
previous election is also significant, suggesting that the decision to vote is
influencedby bothretrospectiveandprospectiveperceptionsaboutthe closeness of
the race. The interactionterm between party ID and the perceived ideological
L Springer
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510 Polit Behav (2007) 29:493-516
Table 3 Reported urnoutandthe impactof the politicalcontext, log odds (withrobust standard rrors)
b RobustSE
1966 -0.23*** 0.02
1970 -0.41*** 0.03
2001 -0.30*** 0.052005 -0.46*** 0.05
Age 0.01*** 0.00
Workingclass -0.30*** 0.03
Male -0.05 0.03
Tenure 0.47*** 0.07
Electoral cohort 0.01*** 0.00
Franchise -0.79*** 0.14
Franchiseby male 0.88*** 0.14
PartyID 0.68*** 0.05
Partydifferential 0.33*** 0.07
Expectedcloseness of race -0.02*** 0.00
Previouscloseness of race -0.01* 0.00
Partydifferentialby partyID -0.06* 0.03
Partydifferentialby new voter -0.10** 0.03
Constant 0.02 0.13
z22,500 (df = 17)
NagelkerkeR2 .132N= 31,188
***Significantat p = .001
**Significantatp = .01
*Significantatp = .05
distance betweenthe partiesis significantandnegative,meaningthatthe difference
between the parties is a more important predictorof reportedturnoutfor non-
identifiers hanit is forstrong
identifiers.17imilarly
the interactioneffect between
new voters andthe difference betweenthe parties s significant,meaningthatyoung
people are more influenced by the political context than old people (see also
Franklin2004). The other individuallevel variablesare much the same as before
and so need no furtherdiscussion here.
We can get a clearer idea of how these factorsinfluence turnout evels by usingthe regression equationto predict turnout n each year (Table 4).18Replacing the
sample means with the corresponding1964 means for demographicvariables,we
can see that,for example, predicted urnout n 2005 would have been 6.0 percentage
17 The interactionbetweenparty dentificationandtheexpectedcloseness of the contest is not significantbut this result is not surprisinggiven the data constraintsof having only 12 level 2 datapoints.
18 On the whole the predictionsslightly over estimatethe observedlevel of reported urnout by about
2 percentage points), but otherwise they capture the dynamics of turnoutchange over time fairly
accurately.From Table 4 we can see thatpredictedturnout n 1964 was 90.3%andpredictedturnout n
2005 was 81.7%,(a decline of 8.6 percentagepointswhich is not far off the 10 point observeddecline).
L Springer
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PolitBehav 2007)29:493-516 511
Table4 Summarympact f theindependentariablesnturnouthangeoverime,percentages
Year Observed Predicted Impactof social Impactof party Impactof political
reported reported change on turnout ID on turnout context on turnout
turnout turnout (% points) (% points) (% points)
1964 88.9 90.3 0.0 0.0 0.0
1966 83.6 85.7 0.1 -0.2 -2.4
1970 81.5 84.4 0.3 -0.5 -1.5
1974 87.9 88.9 0.7 -1.4 -0.8
1975 85.3 87.8 0.8 -1.5 -1.8
1979 85.6 87.9 1.3 -2.7 -1.0
1983 83.3 85.3 2.0 -3.7 -3.4
1987 86.1 88.0 2.3 -3.4 -1.2
1992 87.1 89.9 2.1 -2.9 0.4
1997 83.6 86.6 3.6 -4.0 -3.4
2001 78.0 80.6 5.9 -6.9 -5.8
2005 79.1 81.7 6.0 -6.7 -3.2
points lower thanit actuallywas (81.7 - 75.6 = 6.0), meaningthat,all otherthings
being equal, social change has had a positive impact of 6.0 percentagepoints on
turnout levels over this time period. By contrastpartisan dealignmenthas had a
negativeimpactof 6.7 percentagepointsandthepoliticalcontexthas hada negative
impactof 3.2 percentagepoints. Whereasthe impactof social change and partisandealignmenthas been more or less cumulative over the last 40 years, the impactof
the political context varies much more from election to election. This suggests that
partisandealignmentis responsiblefor the seculardecline in turnoutover the last
40 years and the political context is responsible for the short-termvariation. The
secular decline has therefore been somewhat less than the overall decline. For
example, in 2001 when turnoutfell off an apparentcliff, we can attributeabout
6.9 percentagepoints of the drop to long-term secular decline and 5.8 percentage
points to short-term variation. Bearing in mind that the baseline 1964 election
witnessed a fairly tightrace with clear ideological waterbetweenthe parties,we cansee that the elections that deviated most from the long-term patternof generaldecline since then (1966, 1979, 1983, 1997, 2001, 2005) are the ones that on
average had the least competitive electoral contests with the least difference
between the parties(as illustratedby the high impact of the political context).Variation in levels of turnout over time can thus be attributed o two distinct
processes.The firstis compositionaland refers to the generaldecline in the strengthof party identificationin the electorate since 1964. The second is contextual and
refers to the natureof the political contest.This varies fromyear to yearand is able
to accountfor muchof the residualvariation n levels of turnout rom the long-termtrend of generaldecline. Whereas to a certain extent partyidentificationstructures
individual behaviour and makes it relatively stable and predictable,the politicalcontext is muchmore volatile. In some sense then,these two determinants f turnout
SSpringer
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512 PolitBehav 2007)29:493-516
pull at each otherin oppositedirections,and the decline of the firstsuggests thatthe
latter is thereforebecoming more important.This is supportedby the significanceof the interaction ermbetweenpartyID and
ideological difference. Whereas for strong identifiers the difference between the
parties hardlymakes any difference to their probabilityof voting (0.94 if a good
deal of difference;0.92 if not muchdifference),for non-identifiers he probabilityofvoting is greaterwhen there is a good deal of difference between the partiesthan
when there is not muchdifference(0.76 compared o 0.60). Since non-identifiersare
more influenced than strong identifiersby short-term actors, and since there are
now more non-identifiers hanpreviously,de facto short-termactors areassuminga
greaterrole in determining urnout evels thanwas the case in the 1960s.This canbe
illustratedby imputingthe sample means for partyID from each election into the
regression equationand varying the level of perceived partydifference between a
hypotheticallow of 0 and a hypothetical high of 2, while holding all other values
constant (at their 1964 levels). Varying the ideological difference between the
parties has only a slight impact on the predictedlevel of turnout n 1964, with a
predictedreported urnoutof 88.3%when there is no differencebetween the partiesand 91.5% when there is a substantialdifferencebetween the parties,giving a rangeof 3.2 percentage points (Table 5). In 2005 this range is somewhat larger at
7.1 percentagepoints.
Conclusion
Previous researchhas tended to examine turnoutchange as either a function of
individuals or as a functionof elections. Both these approachesappearto be miss-
specified. Although Franklin(2004) makes an importantcontributionby drawingattentionaway from individualisticaccountsof turnout o highlightthe role played
by the electoral context, he goes too far in the opposite direction, stating that
"turnout s an aggregate-levelconcept" (ibid 167). Althoughturnout s influenced
by the political context, its impact is mediatedby how individualsrespond to it.
Different individualsrespond
in differentways,
so thecomposition
of different
groupsis important or understandinghe impactof the election. By modelling the
joint impact on turnout of individual factors and macro factors relating to the
structureof the nationalpolitical contest, the paperexamines how the dynamicsof
voting are changing over time. The political context has a significant impact on
individual's willingness to turnout to vote, even when we control for individual
level attributes.However, individualsrespondto politicalcues at the macro level in
different ways, and to understandwhy people vote (or not) we therefore need to
understandhow theirbehaviourrelatesto the widerpolitical context. In this respect
turnoutcannotbe fully understoodpurely with reference to individuals'attributes,but neither can it be understoodpurely with referenceto the political context.
To explain turnoutchange it is necessaryto firstknow what one is attempting o
explain. This paper arguesthat there are two distinctphenomenaat work. The first
relates to partisan alignment (or the strengthof party identification).In countries
where this is high (such as in Malta) turnout s likely to be high and will not vary
SSpringer
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Polit Behav (2007) 29:493-516 513
Table 5 Predictedreported
turnoutand the changing impact
of partydifferential,1964-2005,
percentages
Year When party When party Rangedifferential= 0 differential= 2
1964 88.3 91.5 3.2
1966 85.4 89.4 3.9
1970 82.7 87.3 4.61974 86.6 90.5 3.8
1975 86.6 90.4 3.9
1979 84.9 89.4 4.5
1983 84.2 88.9 4.8
1987 83.9 88.8 4.9
1992 84.2 89.0 4.8
1997 84.2 89.0 4.8
2001 78.1 84.6 6.5
2005 75.4 82.5 7.1
much from election to election. In countries where it is lower but stable (such as in
Denmark)turnout s likely to be correspondingly ower and will vary accordingto
the political context (both up and down but no general decline). However, in
countries where party identification is declining (such as in Britain, the United
States and many others) turnout will decline over the long-term, and become
increasingly nfluencedby the structureof short-term orces relatingto the politicalcontext.
There is no doubt that this process has significant mplicationsfor representative
democracy. Party-basedrepresentativedemocracy implies that political represen-tatives articulateand express the political interests and preferencesof the peoplewho have elected them (Key 1964; Dalton 2000). In this light, the strongerthe
alignmentbetweenthe public andparties,the greaterclaim partieshave to speakon
the behalf of theirelectors. However, as Dalton and Wattenberg 2000: 278) state,whereas "partiesused to ensure that elections were judgements on broad policychoices thatwould guide governmentaction-this function has become less clear".
There are not only fewer people voting than previously, but those people who do
vote are now more likely to belong to the growingband of non-identifiers or weak
identifiers) hanstrongidentifiers.For these people the act of voting is not so much
of a judgmenton broadpolicy platforms,but a response to more narrow concerns
related to short-term actors associatedwith the political context. Thus the politicalcontext is becoming more important.This also helps to provide a context for
understandingwhy short-termfactors such as the 'personalisationof politics',
leadershipeffects andcampaigneffects appear o be gaining importance n terms ofexplaining vote choice and the decision to vote. When partyID is high turnout s
high and so individual level variables will not differentiateeffectively between
those who vote and those who don't (since almost everyone will vote). However,when partyID is low turnout s correspondingly ower and there is more room for
other factors to come into play.
L Springer
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514 Polit Behav (2007) 29:493-516
The paperthus sheds light on why people participate,how electoralparticipationrelates to the political processandin some sense, whatparticipation ctuallymeans,
andwhatcan be inferred andwhatcannot)from bothhigh levels of turnoutand low
levels of turnout.I show that individuals need both resources and motivation to
participate n politics. People have the resourcesto participatemore so now than
ever before, but this in itself is not enough to ensure high levels of electoralparticipation.Turnouthas not declined because it has become more difficult to vote,
but because the attachments between political parties and the electorate have
become much weaker over time. If this is not re-energisedthen baseline levels of
turnoutwill continue to decline, no matter how easy it is to vote or how close an
election is expected to be.
Acknowledgements I would like to thank David Sanders, Paul Whiteley, Anthony Heath, David
Denver,JohnBartle,MichaelLewis-Beck, JouniKuha and threeanonymousreviewers for theirhelpfulcommentsandsuggestions.I am also gratefulto the ESRC(PTA-026-27-0486)and the BritishAcademyfor researchfunding.
Appendix
BritishGeneralElection Study, 2005
The 2005 BritishGeneralElection Study was fundedby the ESRC. The studywas
carried outby University
of Essex andUniversity
of Dallas at Texas. Thesamplewas drawn from the Postcode Address file. The fieldwork was carried out by
National Centrefor Social Research. The surveyconsisted of two waves. The first
wave took place before the election. It had a response rate of 61% and achieved
3,589 interviews. The second wave took place immediatelyafter the election. It had
a response rate of 88% (of Wave 1) and achieved 2,959 interviews. In addition a
top-upsurveywas also carriedout which had a responserate of 54% and achieved
1,202 interviews. The data used in the papercomes from the post election panel,which has a valid samplesize of 3,431 respondentson the electoralregister.Further
details are available at the BES website (http://www.essex.ac.uk/bes).
British General Election Study, 2001
The 2001 British GeneralElection Studywas fundedby the ESRC. The studywas
carried out by Universityof Essex and Universityof Dallas at Texas. The samplewas drawnfrom the Postcode Addressfile. The fieldworkwas carriedout by NOP.
The surveyconsisted of two waves. The firstwave took place before the election. It
had a responserate of 53% and achieved 3,220 interviews. The second wave tookplace immediatelyafter the election. It had a responserate of 74% (of Wave 1) and
achieved 2,359 interviews. In additiona top-upsurvey was also carriedout which
had a responserate of 47% andachieved 681 interviews.The data used in the paper
comes from the post election panel, which has a valid sample size of 2,081
SSpringer
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Polit Behav (2007) 29:493-516 515
respondentson the electoral register. Furtherdetails are available in Clarke et al.
(2004: 329-336).
BritishGeneralElection Study, 1997
The 1997 British GeneralElection Studywas fundedby the ESRC and the GatsbyCharitableFoundation,and the Commission for Racial Equality. The study was
carriedout by CREST. The samplewas drawn from the Postcode Addressfile. The
fieldwork was carried out by Social and CommunityPlanningResearchin May to
June 1997. The issued sample was 6,540, of which 5,814 were eligible addresses.
There were 3,615 interviews giving a responserate of 63%. Furtherdetails of the
survey are given in Heathet al. (2001: 170).
BritishElections, 1963-1992
The combinedBritishGeneral Election studydataset,1963-1992 was compiled bythe Data Archive, University of Essex. The original studies were carriedout byNuffield College, 1963-1970, University of Essex, 1974-1979, and Nuffield
College, 1983-1992. The samples were drawn from the Electoral Register. The
achievedsamplesizes were 2,009 (1963); 1,769 (1964); 1,874 (1966); 1,843 (1970);
2,462 (1974F); 2,365 (19740); 1,893 (1979); 3,955 (1983);3826
(1987); 3534(1992). Furtherdetails are available in Heath et al. (1994: 302-308).
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