You Want to Vote Where Everybody Knows Your Name:

Anonymity, Expressive Engagement, and Turnout Among Young Adults*

by

Mark N. Franklin

Trinity College Connecticut

Prepared for delivery in the ECPR Joint Sessions of Workshops (Workshop #23: the Role of Political Discussion in Modern Democracies in a Comparative Perspective) Nicosia, April 25-30, 2006. (Revised version of a paper presented at the annual meeting of the American Political Science Association, Washington DC, September 2005.) • Thanks to Gary King for supplying me with district-level data for elections in the early 1990s, to Cees van der

Eijk and APSA panel participants for helpful comments, and to Diane Garner for suggesting the title.

You Want to Vote Where Everybody Knows Your Name:

Anonymity, Expressive Engagement, and Turnout Among Young Adults

ABSTRACT

Recent research has demonstrated that voting is a habit that is learned (or not) during a formative

period in the life of young adults. Learning to vote is costly, and it has been suggested that costs

depend on the extent to which young adults are engaged in social networks that mobilize them

politically and give their votes value. This paper develops the theoretical basis for the conjecture

and designs an indirect test that investigates the effect of length of residence on turnout in the

context of a model that focuses on the motivations of young adults to participate, including moti-

vations deriving from the electoral context, using survey and aggregate data for U.S. presidential

elections since 1960. Young adults respond to variations in the competitiveness of elections and

also to particularities of their social situation that apparently affect their susceptibility to the

mobilizing influence of family, friends, and acquaintances.

1

Recent research into voter turnout has repeatedly demonstrated the importance of generational

replacement in turnout change (Miller and Shanks 1996, Lyons and Alexander 2000; Putnam

2000, 2002; Blais et al. 2004; Franklin 2004). Turnout change, it appears, is led by the youngest

members of the electorate who, as they age, become set in their ways at a level to which their

turnout returns after any perturbation (cf. Plutzer 2002). So variations in turnout from election to

election are limited by the inertia of established cohorts, providing a baseline expectation for the

level of future turnout around which actual turnout varies under the influence of short-term

forces (Franklin 2004). The baseline can shift over time if new cohorts of voters differ in a

systematic way from their predecessor cohorts, creating long-term change (Putnam 2000;

Franklin 2004).

FIGURE 1 ABOUT HERE

These ideas can be illustrated using data from U.S. national election studies conducted

since 1960. Figure 1 shows the evolution of turnout in U.S. presidential elections by cohort

from 1960 to 2004, using three-cohort moving averages to locate the position of each

group of cohorts.1 As the graph clearly shows, turnout rises quite rapidly over the course of the

first few elections at which new cohorts are old enough to vote, but then flattens out (a

summary view is given in Table 1 below). As the figure also shows, falling turnout in the

1 Moving averages are required in order to smooth out irregularities due to sampling fluctuations when the

number of respondents in each electoral cohort are quite small, but moving averages also mute the

changes that would otherwise be seen from one cohort to the next. Of necessity, the plotted points average

the turnout for the incoming and previous two cohorts, so plotted changes in turnout for incoming cohorts

may be subject to a one-election delay if (as happened with the lowering of the voting age in 1972) devel-

opments affect only one of the three cohorts. See footnote 18 and Franklin (2004: 81-86) for further

discussion of these points.

2

Turnout of cohorts, percent

71

Figure 1 Evolution of U.S. turnout by Cohort, 1960-2004, in three-cohort moving averages

Source: American National Election Studies 1960-2004. Data corrected to observed turnout at each

election.

.

Election year1960 2004

27

(Three-cohort moving averages)

38

49

60

1952-60 cohorts

1956-64 cohorts

19601964-72

6

1972-8-84

-8s

4 cohorts

-68 cohorts

cohorts

1968-71984-92 cohorts cohorts 0

cohorts 1976cohorts

1980 8 cohorts

1992-00 cohort

1996-0.

1988-96 cohorts

1972 1984 1996

3

United States over the the period since 1960 came largely from successive reductions in the

initial turnout of new cohorts, starting with the 1968-76 group of cohorts. Most cohorts, if they

enter the electorate with lower turnout, retain a lower turnout level as they age (the turnout

trajectories of successive groups of cohorts are largely parallel).2 Until the cohorts of 1964-72

there seems to have been a sort of ceiling to which the turnout of successive cohorts appeared

to converge. A lower ceiling may have come into being for cohorts starting with the 1976-84

group of cohorts, though it is hard to be sure because later cohorts have presumably yet to reach

their peak turnout levels.3 Finally, the figure shows evidence of the effects of short-term forces

in the ripple-like deviations among all cohorts from smooth developmental trends.

Three questions are prompted by these patterns. (1) How do members of new cohorts,

whose turnout is initially so low, metamorphose only a few elections later into members of

established cohorts with much higher levels of turnout? (2) What is it that leads new generations

of voters to display levels of turnout that are systematically different from the turnout of earlier

generations? In particular, what happened to cohorts starting with the 1968-76 group of cohorts?

And (3) what causes the ripple-like parallel deviations from long-term trends? These questions

look very different, but they are in fact intimately connected, as we will see. The second and

third of them have been addressed in past research using aggregate-level data. That research

(Franklin 2004) showed that both the baseline level of turnout, set by the level at which new

cohorts enter the electorate, and the short-term deviations from that baseline, seen as ripples in

Figure 1, reflect differences in the competitiveness of elections. Whatever Anthony Downs

2 But note the extraordinary responsiveness of younger cohorts to the forces engendering high turnout in

the election of 2004. Those cohorts actually cross paths with earlier cohorts, which only return to about

their 1992 levels. 3 If a new ceiling was created after 1980, it may well have shifted again following the election of 2004.

4

(1957) might say, if the rewards of voting are conceived as the election of a government likely to

enact preferred policies, then individuals do apparently respond with their votes to variations in

the probability of being rewarded for those votes: more competitive elections yield higher

turnout.4 In this paper I will attempt to replicate those findings at the individual level, using

election studies conducted in the United States over the past half century together with relevant

aggregate data, but my primary purpose is to answer the first question, which relates to the

trajectory of turnout increase among young adults. How do young adults learn the habit of

voting? Why do more of them learn that habit in some circumstances than in others? And what

role is played in these processes by variations in the competitiveness of electoral contests?

Why vote?

The question why anyone would bother to vote, given that the chances of a single vote actually

affecting the outcome of a nationwide election are vanishingly small, was first raised by Downs

(1957) and elaborated by Riker and Ordershook (1968) who suggested that people must be

voting mainly as a function of civic virtue and in order to gain psychological benefits such as the

satisfaction of pulling their weight. Research using individual-level data has, since that time,

focused on explaining how civic virtue is acquired, an approach that evolved into the "resource"

approach to political participation (Verba and Nie 1972; Wolfinger and Rosenstone 1980; Verba,

4 These findings arise from analysis of aggregate levels of turnout in 22 established democracies over 50

years, which focused on variations over time in the rewards of voting. Costs were seen as relatively fixed

in any given country. The main source of variation in the costs of voting was found across countries

(Franklin 2004: 137-42). Using survey data, the research reported in this paper can employ measures that

register differences between individuals within the same country not only in terms of the rewards but also

in terms of the costs of voting.

5

Schlozman and Brady 1994).5 According to this approach, people vote because they have the

resources to do so, in terms of time, skill, money, and motivation. In due course this approach

was complemented by the "mobilization" approach (Rosenstone and Hansen 1993; Verba,

Schlozman and Brady 1994): people vote because they are motivated by others to do so (often an

additional distinction picks out campaign effects from among mobilizing influences). These two

approaches focus on the attributes of citizens and on things that happen to citizens, and so they

provide no basis for understanding why members of an electorate would pay attention to the

character of the election in which they are expected to vote. Yet, if turnout changes in response

to changes in electoral competitiveness, aspects of an election's character must somehow be

affecting the behavior of individuals.

A recent article suggests a possible mechanism. Hillygus (2005) finds that individuals

who had not planned to vote are hardly affected by conventional mobilizing efforts by parties

and candidates. However, they are affected by interacting with personal acquaintances.6 She

makes the point that past failures to find consistent effects of campaign exposure might result

from having failed to distinguish the electorate into those who are likely to vote and those who

are not (2005:64-65). Her distinction, it is true, relates to the expressed intention to vote, whereas

my concern is with the distinction between newer and more established electoral cohorts. Still,

the two ways of classifying the electorate overlap, as shown in Table 1 (which uses the same data

as employed in Figure 1 – data that will be described below). There we see that those not

planning to vote at the start of the election campaign – those most likely to be motivated by

5 Some distinguish political engagement from other resources (Verba, Schlozman and Brady 1994), but

this category overlaps with campaign processes that I wish to distinguish for reasons that will be

explained. 6 They are also affected by campaign advertising, but that is not relevant to my argument.

6

Table 1 Proportion not planning to vote at the start of the election campaign

and not reporting having voted, by electoral cohort, 1960-2000

Electoral cohort

Proportion not

planning to vote

Proportion not

voting

Facing first election 0.29 0.55

Facing second election 0.25 0.50

Facing third election 0.21 0.46

Facing fourth election 0.17 0.41

Facing fifth election 0.14 0.38

Facing sixth election or later 0.12 036

Source: American National Election Studies, 1960-2004, pre- and post-election waves.

7

personal contacts – are more than twice as numerous in younger cohorts. Because it helps to set

the scene, the table also includes a column showing the proportion later reporting not having

actually voted.7 In both columns the proportion of (intending) non-voters declines with lengthen-

ing time in the electorate, but this decline flattens out from the fourth election onwards, a change

in slope already noted in Figure 1. This observation will have relevance later in the paper.

TABLE 1 ABOUT HERE

The apparent importance of personal contacts among members of new cohorts is sugges-

tive of a group effort at getting out the vote, where the group consists not of the organization

assembled around a particular candidate but of ordinary people – the potential voter’s personal

friends and acquaintances. If getting out the vote is a group effort rather than an individual effort,

then a completely different calculus of voting applies than that suggested by Riker and Order-

shook. I will argue in the next section that, when voting is conceived as a social rather than as an

individual act, there are good theoretical reasons why the competitiveness of the election should

play an important role in determining how many of a group’s members will vote.

Furthermore, we will see that the same calculus of voting that helps to explain why

individuals would pay attention to an elections' character also helps to explain the process

whereby members of new electoral cohorts learn the habit of voting (or not) and metamorphose

into members of established cohorts.

7 The latter variable comes from the post-election wave of the same studies. Note that Hillygus’ measure

of whether respondents intend to vote was obtained in the April wave of a multi-wave panel study, where-

as the measure employed here was obtained in the August wave of successive two-wave election studies.

Some of those who would in April have intended not to vote might well change their minds by August,

reducing the relationship shown in Table 1 between cohort and intention to vote from what would have

been found in Hillygus' data.

8

Towards a theory of expressive engagement

Classic approaches to explaining why people vote have, as already mentioned, focused on the

resources that individuals have or acquire, and the mobilizing efforts to which they are exposed.

A rather different approach is based on the idea that voting has an expressive component

(Franklin, Niemi and Whitten 1994; Schuessler 2000): people vote in order to express who they

are and what matters to them. The expressive approach to why people vote has been elaborated

by Franklin (2004) to suggest that people vote in part so as to motivate the votes of others like

themselves, giving their own votes greater value to the extent that this objective is realized.8

Voting, on this view, is a social act with a very different calculus of costs and benefits than it

would have according to the individualistic calculus of rational choice theory. Building on the

work of Schelling (1978) and of Shepsle and Bonchek (1997), the basic intuition is that at least

some people see themselves as members of potentially winning coalitions of voters who need the

participation of all members of their group if their candidate is to win; a situation in which uncer-

tainty about the outcome of the election has the opposite effect to that expected by Riker and

Ordershook: every group member sees their vote as potentially decisive (Franklin 2004: 52).9

This approach, which I call the “expressive engagement” approach to understanding

electoral participation, links the expressive and mobilization approaches and focuses attention on

the importance of being embedded in social networks – a factor shown by Beck et al (2002) to be

8 Evidently it is the expressed intention of voting rather than the actual vote that would be the motivating

force; but someone who expresses the intention to vote for a particular party or candidate has already

decided who to vote for, a decision involving most of the costs of voting. The additional cost of actually

casting a ballot is small and perhaps incurred for the sake of credibility, if nothing else. 9 The same conclusion is reached by way of a different argument in an unpublished paper by Diermeier

and Van Mieghem (2002) who present a formal proof that uncertainty is a requirement for high turnout.

9

central to the process by which voting decisions are shaped (cf. Huckfeldt and Sprague 1987,

1991, 1995). Hillygus’ (2005) findings regarding personal contacts lend strong support to this

line of reasoning, suggesting that a crucial role is played by individuals who take the time and

trouble to advertise their intention of supporting a particular party or candidate, perhaps in the

hopes of motivating others to do the same.

This idea again raises the question first asked by Downs (1957): why would anyone

bother to do that? But now the question does not relate to an activity with minuscule consequen-

ces but instead to one whose consequences, though indeterminate, could possibly be quite large.

If members of an electoral coalition believe that their actions in advertising their intentions to

support a particular party or candidate could motivate others to do the same, then it would not be

ridiculous for them to suppose that their (expressed intention to) vote might just possibly make

the difference between winning and losing a close election.10 According to Franklin (2004:51),

…the calculus of voting is quite different for socially connected people. If each vote has a

motivating impact on other members of a group, then each vote effectively counts more than

once. People in social networks also incur costs of nonvoting because other members of their

group care whether they vote or not. By contrast, for those not involved in social networks, their

vote is only worth one single vote and, furthermore, they incur no social costs from freeloading.

So the benefits of voting and the costs of nonvoting are higher for socially connected people.

In this context, the question of whether the election is competitive becomes paramount.

The more competitive the election, in terms of the sizes of the electoral coalitions aligned on

10 Note that expressive engagement only partially overlaps with “discuss politics,” a variable missing

from too many election studies for it to be used in this research, or “tried to influence others” which

relates to a much more extensive intervention.

10

each side, the more incentive there is for each member of each coalition to do their best to

motivate their fellow members and potential members, because the more likely it is that their

efforts will be rewarded by an electoral victory for their party or candidate. The more the out-

come is seen to be a foregone conclusion for one side or the other, the less incentive there is for

either side to do this. Though there is ambivalence in the literature about the effectiveness of 'get

out the vote' campaigns (see Shaw 1999 for a review), I already noted that Hillygus (2005) has

found empirically that personal contacts can have considerable effects on individuals who were

not previously planning to vote.11

So variations in the competitiveness of elections could stimulate variations in the preval-

ence of expressive engagement, in turn leading to variations in electoral participation by young

adults. A highly competitive election would stimulate high levels of expressive engagement,

bringing more first time voters to the polls. A less competitive election, by lowering the motiva-

tion for expressive engagement, would lead to lower turnout. So one influence on turnout trends

would be trends in electoral competitiveness, just as has been found in aggregate-level research.

When we focus on the individual level, the question arises how does this work, exactly?

If features of an election's character act on individuals directly, then previous models of voting

behavior have been badly mis-specified in omitting measures of the character of elections as

independent variables. However, it is quite possible that an election's character is manifested at

the individual level by way of variables already included in most election studies. Competitive

elections should increase the political interest of citizens, motivating them to pay attention to the

election at hand, giving them a greater sense of party identification, and so on. Similarly,

11 Among those planning to vote at the start of the campaign she finds that conventional approaches by

parties and candidates are effective in reinforcing the intentions of would-be voters.

11

competitive elections should stimulate the efforts of those who would mobilize the votes of

others. These are all responses to competitive elections that are measured by variables included

in past individual-level studies.

Even if an election's character manifests itself by way of variables that are traditionally

included in models of individual-level electoral participation, there is nevertheless still a need to

take account of the newly discovered role of young adults. Previous research at the individual

level has generally assumed that everyone is affected in the same way by influences on whether

they vote or not. Some past research has investigated distinctions between citizens (see, for

example, Marsh 1991 and Perea 2002). But even those studies have ignored the tendency of

citizens to become set in their ways later in life. More recent of turnout among members of

different electoral cohorts have suggested that those who will be most affected by the character

of elections are those who are not yet set in their ways – members of new cohorts.12 If this

suggestion is correct, then models employed in previous research will have been mis-specified in

omitting interactions with respondents' age, even if it turns out that no similar problem arises

from the omission of variables defining each election's character.

On the basis of this logic, statistical models of electoral participation at the individual

level will look rather different than has been customary. Conventional models incorporate

independent variables concerned with resources, mobilization, and features of the campaign; and

generally take the form shown in equation 1:

Voting = ß0 + ß1X1 + ß2X2 + ß3X3 + e (Equation 1)

where the X1 variables measure the individual's resources of various kinds, the X2 variables

12 Note the very different early trajectories of successive sets of cohorts in Figure 1.

12

measure factors that facilitate or motivate the individual’s mobilization, and the X3 variables

measure aspects of the campaign, such as the extent to which it excites the potential voter’s

interest. In a model that takes account of expressive engagement, things are more complicated.

For one thing such models will need an additional set of independent variables (X4) to measure

aspects of the character of elections. For another it will be necessary to allow for different effects

on members of new cohorts than on members of established cohorts. This is not because being

engaged by personal acquaintances and friends mainly involves members of new cohorts. Ex-

pressive engagement involves not only those approached but also those who do the approaching.

Rather it is because members of established cohorts will tend to vote even in elections that fail to

motivate high electoral participation among members of new cohorts, as shown in Figure 1.

Evidently, the habit of voting generally overrides other motivations, which are primarily felt by

those who have not yet acquired this habit (or the corresponding habit of non-voting which

essentially takes individuals out of the pool of potential voters). For this reason all influences

that might affect the likelihood of voting need to be interacted with a variable that indicates

whether each individual is available to be mobilized or not.

So a properly specified model of electoral participation will include independent variables

relating to electoral competitiveness (X4) and have all the independent variables appearing twice,

once interacted with a new cohorts indicator and once without, as shown in Equation 2:

Voting = ß0 + ß1X1 +… + ß4X4 + New + New ( ß1X1 + … + ß4X4 ) + e (Equation 2)

Effectively the variables in this equation are doing two different things. The first set of X1

to X4 are measuring effects that apply to everyone, new or established. Though established voters

are largely set in the habit of voting, they are still subject to fluctuations in their likelihood of

voting, as we saw in Figure 1, and the un-interacted independent variables attempt to account for

13

these fluctuations. The second set of X1 to X4 – those that are interacted with the new cohorts

indicator – are trying to do something rather different: to account for the greater volatility of

young adults than older voters and for the rate of increase in participation among young adults as

they gain electoral experience. This component of the equation is concerned with the transition,

in Plutzer’s (2002) terminology, from habitual non-voting to habitual voting, a transition that by

definition involves rapidly increasing probabilities of voting (the years during which this

happens are sometimes referred to as “formative”). The variables involved in this transition

could, in principle, be quite different variables from those involved in the other process but, for

their effects to be intelligible, it would still be necessary that the variables occur within both the

interacted and un-interacted sets.13

A strong indication that conventional models of electoral participation are indeed mis-

specified is provided by the large role played in such models by respondents’ age. Though many

authors include the variable as though it had substantive meaning, it is actually an umbrella or

container concept that needs to be unpacked into its underlying components. There are, of

course, various things about people that change with age. Many of these things have effects on

13 To be able to interpret the import of an interaction term it is necessary that both components of the

interaction be included in the model along with the interaction itself. Note that in practice the interaction

effects are “multiplied out:” each individual variable within the set of parentheses is multiplied by the

new cohorts indicator before the model parameters are estimated. This method of specifying interaction

effects permits the analyst to determine whether the interaction effects are significantly different from the

corresponding un-interacted effects. An alternative way of specifying interactions with a dichotomy, used

in Table A.2 in the appendix, is to interact all variables with both sides of the dichotomy. This does not in

itself provide a test for significant differences between the effects, but does provide a full set of effects for

each group of respondents defined by the dichotomy – something that may be useful for some purposes

(see, for example, Table 4).

14

the likelihood that they will vote. People’s education sometimes increases, their income

generally goes up, their sense of efficacy often increases, their political knowledge and interest

may be enhanced. But all of these attributes have been measured in past election studies, and the

measures have been included in conventional models of electoral participation. If these attributes

supplied the reason why age was important then they would have replaced age as a predictor of

the likelihood of voting in any model that included them along with age. The fact that age still

plays a role in conventional models that contain these variables is a clear signal that something

else about age (perhaps more than one thing) remains undiscovered which, if it could be

identified and included in an electoral participation model, would indeed render age redundant as

a predictor of whether people cast a ballot.14

The central puzzle in voter turnout studies is to discover the mechanism that transforms

largely non-voting but highly responsive young adults into largely voting but relatively unres-

ponsive mature adults. Implicitly stated in the title to Erik Plutzer’s seminal article (2002), what

is it that turns a young adult into a habitual voter?15 The fact that models of individual-level

electoral participation continue to find a significant role for the age variable registers the fact that

past research has failed to unravel this puzzle, and the strength of the effects of age (generally

very strong) informs us of the extent of the failure.

14 Studies in the sociology of aging have long been concerned to eliminate the age variable in this way

(see, for example, Riley, Johnson and Foner 1972). In political science similar efforts have been made in

various subfields (see, for example, Converse 1976), but such efforts have been strangely lacking in

studies of electoral participation. 15 Plutzer does not answer his own implicit question, being concerned mainly to demonstrate that a

transition to habitual voting does take place, though he makes the same point about the unexplicated

effects of age. In this research I build on his insights to develop a properly specified model of turnout.

15

Expressive engagement and the social situation of young adults

A focus on this puzzle suggests the need to consider not only the possible rewards for voting, in

terms of the likelihood that the voter’s electoral coalition will win, but also the costs of voting, in

terms of how the transition to habitual voting for young adults might be affected by their social

situation. Because expressive engagement is expected to work in the context of politicized

groups of friends and acquaintances, young adults who are not embedded in politicized social

structures should have a harder time making the transition – their costs of learning the habit of

voting will be higher. Anything that makes it more difficult for young adults to be identified and

tagged in terms of likely partisanship will stand in the way of their being approached by like-

minded individuals, in turn reducing their incentives to master the intricacies of the voting act.

Moreover, as a separate factor, lack of social embeddedness will also make those intricacies

more opaque. An effective support group that is itself embedded in a community of voters

(perhaps a set of family members residing in the same household) will reduce the costs of voting

by providing a ready source of information and political advice. This is quite apart from the fact

that an effective political support group will also increase the benefits of the voting act, as

already explained.

On the basis of these ideas, changes in the likelihood of voting by young adults will not

only be conditioned by differences in the character of succeeding elections (changes in their

competitiveness) but also by differences in the social situations of the young adults themselves

(the ease with which they can be adopted by supportive networks of politicized individuals).

Ideally a test of the importance of social networks would involve the use of rich data,

such as employed by Hillygus (2005), that included extensive measures of the social and other

contacts that voters have during the course of an election campaign. Unfortunately, such data are

16

not common and certainly are not available in identical terms over a multiple-election period.

Yet measuring the effects of electoral competitiveness does require data that spans a number of

elections. At a single election, measures of that election's competitiveness will not vary. One

strong implication of Franklin 's (2004) study of voter turnout in established democracies is that

models of electoral participation involving only one election will suffer from missing variable

bias. So it is not appropriate to investigate social contacts and electoral competition in separate

analyses. Both are likely needed in a well-specified model of electoral participation.

Given the lack of suitable variables measuring the extent and impact of social contacts,

the present analysis employs two surrogate measures. The first is a measure of the length of time

respondents have lived in the same neighborhood.16 This is essentially a measure of the

opportunity that politically motivated individuals will have had to become aware of the young

adult and her political leanings. For members of new cohorts the variable generally indicates

whether, at the time of an election, they were still living in the parental home. Living in the

neighborhood where they grew up, many will already have an appropriate support group, and

others are likely to be identified and approached by those who might wish to help them over-

come the initial vote hurdle. By contrast, young adults who have left the parental home (whether

for educational, career, or romantic reasons, or simply to assert their independence) will be

16 Where this variable yielded missing values, answers to a question about how long respondents had

lived in the same household (suitably recoded) were substituted. The indicator is the same as that used by

Squire, Wolfinger, and Glass (1987) who employed it as an indicator of information about local politics.

It might be hard to distinguish these two aspects of the variable in most research designs, but our

expectation that the variable will be especially potent for young adults will, if confirmed, suggest that it is

engagement rather than information that is the key aspect. If voting was all about knowledge of local

politics, then moving to a new neighborhood later in life would have the same negative effect on the

probability of voting as for a young adult. This logic is reinforced by other findings (see footnote 33).

17

disadvantaged when the time comes to vote. Being new in their new communities they will

resemble more the atomized citizens of rational choice theorizing than the socially connected

ones described earlier, since they will not have the support network that would reduce the costs

and increase the benefits of voting. If their new community is a college campus they will be par-

ticularly disadvantaged, since few of their fellow students will be connected to social networks

with relevance to voting. In such circumstances, building a network of friends and acquaintances

will not often have the effects it would generally have in a less age-bounded community.

The second surrogate measure builds on the same logic by distinguishing voters into

those who reached voting age when this was still 21 and those who reached adulthood more

recently, after the voting age had been reduced to 18. It has been suggested (Franklin and

Wessels 2002; Franklin 2004) that a particularly intriguing implication of the responsiveness of

incoming cohorts to changes in the character of elections will have arisen from the lowering of

the voting age which, in the U.S., happened in time for the election of 1972. This reform will

have reduced by three years the average age at which young adults would need to be initiated

into the complexities of the voting act. Most people leave high school at about 18 years of age.

The years that follow are fraught with the problems of early adulthood. More importantly, those

are years in which young adults are only starting to establish the social networks that will

ultimately serve to guide their political choices and motivate their votes, as already discussed.

Initiation at a younger age will have increased the number of those facing their first election from

the confines of a college campus and, even among those who did not go to college, the reform

will have increased the number of those facing their first election soon after leaving the parental

home. The costs of learning to vote, high in any case, could only be raised by a reform that

brought forward the average person’s first election to a time shortly after leaving high school.

18

Franklin and Wessels (2002) argued that the socializing effect of failing to vote when

eligible would have had enduring effects on the electoral participation of voters who reached

adulthood in 1972 and later, as members of each cohort in turn were subjected to a more difficult

initiation into the intricacies of electoral politics, leading fewer of them to learn the habit of

voting and giving rise to a lower turnout ceiling, consistent with the pattern seen in Figure 1.17

Effectively, each post-1970 cohort would start its upward turnout trajectory from a lower base

than before the franchise extension, helping to explain their lower starting points in Figure 1.18

Length of residence and younger initiation are complementary in that both serve to

register costs of voting that are likely to be mitigated through access to an effective support

group. But while length of residence refers to the time of the survey, young initiation refers to a

time that, for most respondents, will be one or more elections in the past. The residual effect of

that past experience, if it is found, will validate the logic underlying the use of length of

residence as a surrogate for expressive engagement, just as finding effects of length of residence

will validate the findings from young initiation. Both effects would indicate that early adulthood

is a bad time to be facing one's first election, when childhood social connections are being

sundered and adult social connections are not yet in place.

17 Plutzer (2002) demonstrated that initial turnout rates of different groups of voters condition the ultimate

likelihood of voting for group members. Here his finding is used as grounds for supposing that the initial

turnout rates of different cohorts will condition the ultimate likelihood of voting for cohort members. 18 Following the franchise extension, the effect on each new cohort of a more costly initiation should be

the same, so the lower voting age cannot explain a progressive decline in the level of turnout at which

new cohorts enter the electorate. The apparently progressive decline in the initial turnout levels of

successive cohorts seen in Figure 1 is partly a consequence of using moving averages, which spread any

downward step over three elections. Variations after 1980 in the initial level of turnout for successive

cohorts give the appearance of random movements, up as well as down, likely due to other factors.

19

Hypotheses and data

Tests involving these two surrogate measures can be conducted using data from the American

National Election Studies fielded following presidential elections since 1960.19 These contain a

wide array of variables used in conventional models, including the length of time respondents

have lived in their present neighborhoods, and the variables have been rendered comparable

across election studies by the NES staff who maintain a cumulative file containing the resulting

data (a version including the 2004 component was released in October 2005 and is used here).

This cumulative dataset of course contains the birth year of each respondent, permitting

voters to be distinguished on the basis of the year in which they first became eligible to vote, and

assigned to corresponding electoral cohorts. Based on earlier research (Butler and Stokes 1975;

Franklin 2004) the cutting point adopted for distinguishing newer from more established elec-

toral cohorts is the passage from the 3rd to the 4th election that people experience as voting-age

adults (operationalized as aged under 33).20 As observed in Table 1, the chances that young

Americans will exercise their franchise increase rapidly over the course of the first four elections

at which they are old enough to vote. After that, shifts towards higher turnout are more gradual.

The primary hypothesis is that length of time in present neighborhood will, in a properly

specified model, show a strong positive effect on electoral participation among new voters but

much less so among established voters. There are also two subsidiary hypotheses. One is that

19 The number of available variables with relevance to turnout is much reduced before 1960. 20 No research has been done that would reveal whether the "immunization" process is a function of aging

or of the number of electoral contests a person has been exposed to. Butler and Stokes (1975),

investigating the British case, assumed the effect had to do with electoral experiences, but new cohorts do

not appear to metamorphose into established cohorts any earlier in the U.S. where elections are held much

more frequently. Various operationalizations were tried, and this one yielded the most robust findings.

20

those who entered the electorate following the lowering of the voting age will show a signifi-

cantly lower probability of voting than those who were not subjected to their first electoral

contest until after they were 21 years old.21 The other is that variations in electoral competitive-

ness will have significant effects. Voters (and especially members of new cohorts) will be more

responsive to expressive engagement (which is also liable to be more extensive) in the context of

more highly competitive elections.

The variables available for analysis are listed in Table 2, where they are divided into

categories according to the theoretical approach that each reflects. Each variable is accompanied

by its correlation with voting and by other information. Also listed are aggregate-level variables

measuring electoral competitiveness, together with linkage variables needed to create interactions

with new cohorts and to test the voting age hypothesis. The measures of competitiveness are those

that have been found important in aggregate-level research (Franklin and Evans 2001; Franklin

2004).22 The variables concerned are the closeness of the race (margin of victory) in the

congressional district where each respondent resides,23 and whether that district race is contested.

Additional features of the nationwide electoral contest were investigated, but were not found to be

21 This variable should not have a strong effect. Over 22 established democracies Franklin (2004) found

an average effect of 3.8 percent. Yet finding a significant effect, even if small, will serve to buttress a

confirmation of the primary hypothesis. 22 These variables were for the most part taken from ICPSR study # DA7757 which contains district-level

results up until 1990. For elections since 1990 the data were obtained from the web sites of Harvard's

Gary King and the Federal Elections Commission. 23 Of course voters react to the expected closeness of the district race but, in the absence of good polling

data for congressional districts, the actual result is employed as a surrogate for the best information that

could have been available to voters. To the extent that voters were reacting to less accurate information

this will result in error that will make it more difficult to confirm hypotheses – a conservative strategy.

21

Table 2 Individual level variables for explaining U.S. electoral participation

Variable Correlation with voting Notes Character of elections variables (From aggregate data)

District margin of victory (0-1=100%) -0.061*** Difference between winning and next candidateDistrict uncontested (0,1=yes) -0.050*** Whether district was uncontested Presidential margin of victory (0-1=16%) 0.021** Actual margin of victory in presidential race

Resource variables (From survey data)

Age (0-1=18-98 years old or more) 0.114 *** Rescaled Gender (0,1=male) 0.059 *** Recoded Race (0,1=white) 0.082 *** Recoded Education (0-1=college degree) 0.230 *** Rescaled Occupation (0-1=most status) 0.186 *** Rescaled Religion (0,1=protestant) 0.089 *** Recoded Home ownership (0,1=owned) 0.192 *** Recoded Income (0-1=highest) 0.239 *** Rescaled Efficacy (0-1=highest) 0.221 *** Rescaled

Mobilization variables (From survey data) Church attendence (0-1=weekly or more) 0.175 *** Rescaled Union member in household (0,1=yes) 0.058 *** Recoded Rural residence (1,0=rural) 0.066 *** Recoded Suburban residence (0,1=suburban) 0.049 *** Recoded Length of residence (0-1=20 years) 0.087 *** In neighborhood (in house if missing) rescaled

Campaign variables (From survey data) Contacted by major party (0,1=yes) 0.192 *** Recoded Strength of party ID (0-1=strong) 0.207 *** Rescaled Interested in public affairs (0-1=high) 0.317 *** Rescaled Interested in election (0-1=strong) 0.326 *** Rescaled Cared who won (0-1=much) 0.235 *** Rescaled Close presidential result expected (0,1=yes) 0.020 ** Recoded Importance of party differences (0-1=high) 0.196 *** Recoded Salience of house candidate (0-1=high) 0.329 *** Rescaled Tried to influence others (0,1=yes) 0.246 *** Recoded Affect towards major party (0-1=max) 0.034 *** Rescaled

Linkage variables (From date of birth) New cohort member (0,1=yes) -0.157*** Less than 33 years old Could vote at 18 (0,1=yes) -0.149*** Entered electorate in 1972 or later

Note: N=19,660 or more. Significant at *0.05; ** 0.01; *** 0.001, two tailed. Source: American National Election Studies, 1960-2004 post-election waves, with merged aggregate data

(see footnote 22).

22

significantly correlated with individual-level turnout.24

TABLE 2 ABOUT HERE

Campaign variables are distinguished from mobilization variables in Table 2 so as to

draw attention to the different expectations that apply to these variables when measures relating

to the character of elections are introduced into the analysis. Campaign variables may well carry

some influences from the character of elections if more competitive elections serve to stimulate

the activities and concerns that campaign variables measure.

All variables have been recoded where necessary to ensure that larger values correspond

to higher probabilities of voting (except in the case of aggregate-level variables whose values

have substantive meanings that call for negative correlations) and rescaled so that all of them

range from 0 to 1. Thus a 1-point shift in the value of any variable corresponds to a shift from the

minimum to the maximum value found in the data, permitting estimated effects to be given a

straightforward substantive interpretation that is comparable across variables.

The table provides some preliminary (and quite indirect) support for this paper's primary

hypothesis. If district-level measures of competitiveness influence turnout more than nationwide

measures do (as indicated by the correlations at the top of the table), this suggests variations in

expressive engagement from district to district according to the closeness of the race in specific

districts, with more competitive races generating more involvement by individuals, and more

expressive engagement, as only makes sense. Yet to be seen is whether such mobilizing efforts

have particularly strong effects on new cohorts, as hypothesized.

24 Indeed, the correlation between voting and the nationwide margin of victory in the presidential race,

included in Table 2 for illustrative purposes, is seen to be significant only at the 0.01 level despite the

enormous number of cases (N=19,660) and, moreover, to have the wrong sign. This anomalous finding

will play a role, later in the paper, in supporting our primary hypothesis.

23

I address this question by building a model of electoral participation as close as possible

to those used in past research (see Equation 1 above) and comparing that model with others

adapted to accommodate my own theoretical approach (Equation 2).

Findings

Table 3 shows the results of an analysis that attempts to classify respondents into those who

voted and those who did not on the basis of logistic regression analysis.25 Because the

coefficients that are produced by such an analysis are uninterpretable by mere mortals, they have

been converted in this table to first differences. Each coefficient shows the shift in the value of

the dependent variable that would result from a change of one unit in the corresponding

independent variable when all other independent variables are held at their mean values.26 So the

25 It might be supposed, by analogy with student-teacher research, that I should use a multi-level

modeling procedure to take account of the smaller N in the aggregate data employed. However, the

analogy is not warranted. This analysis contains no actor at the aggregate level and all effects are felt at

the individual level, including the effect of a competitive electoral situation. It is a mistake to think that

choice of model should necessarily depend on the level of aggregation at which data are collected. Had

the data on religious affiliation been acquired from aggregate level church records, the nature of the

influence would have been no different from the one estimated here. In the same way, it makes no

difference at what level competitiveness is measured. 26 The logistic regression coefficients from which these differences were calculated, along with their stan-

dard errors, are reported in an appendix. With so many independent variables, missing data is a problem,

reducing the number of cases by more than half with listwise deletion. So missing data on independent

variables was imputed by least squares estimation. An analysis with listwise deletion of missing data is

provided in the appendix (Table A.3, Model D1). It shows no notable differences in the effects of

substantively interesting variables. Though the effect of young initiation (voting at 18) is reduced, it

remains statistically significant, and a strong effect of this variable was not expected theoretically (see

footnote 21). Aggregate indicators lose their significance, but this might imply that their influences are

24

coefficients are interpreted in roughly the same way as b coefficients in OLS regression analysis.

Because each independent variable has been modified where necessary to yield values that range

from 0 to 1, the coefficient for each independent variable can be interpreted as the proportion

change in the likelihood of voting that would result from a shift in the value of that variable from

its minimum to its maximum observed value, controlling for all other variables in the model.

TABLE 3 ABOUT HERE

The table contains four models. Model A shows the effects of electoral competition in the

respondent's district, Model B is a conventional participation model containing individual-level

influences on the likelihood of voting. Model C adds these variables to Model A's aggregate-

level character of elections variables, and Model D adds interactions (any that proved statistically

significant) between these variables and a measure of whether respondents were members of new

cohorts (less than 33 years old). Other variables available in comparable terms across the U.S.

election studies (see Table 2) are omitted from Table 3 if they were found not to have significant

effects in preliminary versions of any of the four models.27

Model A shows a palpable effect of district marginality. Respondents living in a district

where the race was too close to call were 8 percent more likely to vote than those living in

districts where the challenger received virtually no support. If the district was uncontested, the

adequately indicated by campaign variables (see footnote 29). 27 The coefficients presented in Table 3 derive, however, from analyses that contain only the variables

shown there. The appendix contains a supplementary model (Model D2 in Table A.3) that includes voted

at previous election as an independent variable. Arguably this variable is called for theoretically, but it

was omitted from Model D because its presence renders age not significant, removing the opportunity to

use age as a diagnostic for adequate model specification (see below). In the appendix it is interacted with

(1-new) to avoid its displacing many of the effects of interest on new cohorts. Effects of substantive

importance are hardly changed by the presence of the quasi-lagged term.

25

Table 3 Differences in proportions voting that result from shifts from minimum to maximum in

independent variables when other such variables are held at their mean values Model A Model B Model C Model D 1st difference 1st difference 1st difference 1st difference New cohort member (0,1=aged under 33) -0.124**Character of election in each district

District margin of victory (0-1=100%) -0.080** -0.041* -0.037*District uncontested (0,1=yes) -0.059* -0.028* -0.036**

Individual level resource variables Age (0-1=18-98) 0.188*** 0.185*** 0.054Education (0 –1=College degree) 0.235*** 0.233*** 0.194***Occupation (0-1=high) 0.055*** 0.056*** 0.055***Home ownership (0,1=owner) 0.083*** 0.084*** 0.082***Income (0-1=highest) 0.138*** 0.133*** 0.138***Efficacy (0-1=highest) 0.081*** 0.080*** 0.078***

Individual level mobilization variables Church attendance (0-1=weekly) 0.109*** 0.110*** 0.140***Union member in household (0,1=yes) 0.038*** 0.037*** 0.038***Length of residence (0-1=20 yrs) 0.078*** 0.080*** 0.077***

Individual level campaign variables Contacted by major party (0,1=yes) 0.080*** 0.078*** 0.086***Strength of party ID (0-1=strong) 0.128*** 0.130*** 0.126***Interested in public affairs (0-1=high) 0.107*** 0.108*** 0.105***Interested in election (0-1=high) 0.133*** 0.133*** 0.130***Cared who won election (0,1=yes) 0.066*** 0.066*** 0.068***Close result expected (0,1=yes) 0.015* 0.015* 0.018*Importance of party differences (0-1=high) 0.039*** 0.039*** 0.039***Tried to influence others (0,1=yes) 0.059*** 0.059*** 0.060***

Individual level interactions with new cohorts New * Age 0.135**New * Education 0.115***New * Length of residence 0.131***New * Church attendance -0.066***New * Income -0.094***New * Contacted by major party -0.030***

Could vote at 18 (0,1=yes) -0.036*** Pseudo R2 0.004 0.254 0.255 0.262 Valid N 19660 19660 19660 19660

Note: Significant at *.05; **.01; ***.001 levels, one-tailed, based on robust standard errors clustered by year. See appendix for logistic regression coefficients and standard errors. Independent variables have had missing data imputed by least squares estimation. See appendix for analysis without missing data imputation.

Source: American National Election Studies, 1960-2004 post-election waves, with merged aggregate data (see footnote 22). See Appendix for logistic regression coefficients and robust standard errors.

26

chances of voting were reduced by almost a further 6 percent – 14 percent in all. Only about 5

percent of districts are uncontested over the period, and the effect is only barely significant; but

the level of significance increases with a more fully specified model (Model D), suggesting that

the effect is real, though small in relation to the amount of unexplained variance in Model A.28

Interestingly, these effects are much attenuated when individual-level predictors are

introduced in Models C and D. Evidently about half the impact of electoral competition is felt by

way of variables measured at the individual level. This finding provides support for my conten-

tion that expressive engagement plays an important role in turnout variations, even before we

look at the explicit test variables. Most voters (especially first-time voters) would not be aware of

the fact that they reside in a competitive district had they not been made aware of it by means of

some local information source. Few congressional races are given the sort of media attention that

would reach first-time voters. We know from Hillygus (2005) that political advertising is one

possible means, but it seems likely that additional means would be required. We will see in a

later section that the route by which the information is passed involves a number of campaign

variables which do not seem very likely to respond to political advertising (interest in public

affairs, interest in election, cared who won, or importance of party differences). Although the

evidence is not conclusive, such variables would seem more likely to respond to personal contac-

ting, which we know from Hillygus (2005) to have had important effects on first time voters.

Though the measure of electoral competition is attenuated in Models C and D, the effect

remains quite strong and is responsible for a difference in electoral participation of 4-7 percent

(depending on whether districts were contested) when districts with races that are too close to

28 The two variables are related to turnout at the 0.001 level of significance when taken separately, as

shown in Table 2.

27

call are compared to those where only one candidate receives significant support.29

Model D also shows that interactions with new cohorts are essential to a well-specified

model of electoral participation. Voters facing one of their first three elections behave differently

from more established voters. While church attendance, income, and being contacted by a major

party have less effect among members of new cohorts than among members of the electorate as

whole, other variables help to explain how members of new cohorts acquire the habit of voting.

A notable contribution is made by education, which for obvious reasons is more likely to

increase among new cohorts than in the general population and which serves to boost the turnout

of educated new cohort members by some 31 percent when the two relevant effects (0.194 and

0.115) are summed. Also important, however, is length of residence in the neighborhood. The

total effect of this last variable for new cohorts, at 20.8 percent (= 0.077 + 0.131), is second only

to that of education in overall importance. It is to the effects of this variable – the primary test

variable in the present study – that we now turn.

Social connections and expressive engagement

Because the effect of length of residence is estimated separately for new cohorts than for the

whole electorate, it can be seen that this variable has approaching three times the effect among

young adults than it has in the electorate as a whole (0.208, as calculated above, compared to

0.077). Young adults who had lived all their lives in the same neighborhood would be almost 21

percent more likely to vote than those who had recently moved there. I argued earlier that this

variable would acquire its role from the opportunity that long-time residents have had to become

29 However, there is every reason to suppose that the introduction of campaign variables beyond those available in this study would eliminate the direct effects of electoral context. Indeed, these variables prove not significant in the smaller dataset that results from eliminating cases with missing data on any variable (see Table A.3, Model D1 in the appendix).

28

enmeshed in social structures that expose them to expressive engagement on the part of acquain-

tances and friends – an engagement that in turn guides their party choice and adds value to their

vote. Model D shows that the effects concerned are substantial and positive, for members of new

cohorts, implying that young adults who are newly away from the parental home are in a very

bad situation to learn the habit of voting, as was hypothesized.

Of course, the effect of education is even greater and (for those who do obtain a college

degree) accounts for even higher turnout, suggesting an alternative route to at least moderately

high turnout. But the findings imply that the very highest probabilities of voting require both

education and the opportunities for mobilization that length of residence makes possible.

Notably, Model D shows no significant effect of age in the electorate taken as a whole.

Apparently the other variables included in the model do a good job of accounting for age-related

differences in the probability of voting among members of established cohorts. Among members

of new cohorts the age variable does show a significant effect, suggesting that the model could

yet be improved.30 Still, in isolating the effect as one applying just to new cohorts the model

performs better than traditional models did in accounting for age-related differences. We now

know that we should be looking specifically for corollaries of aging among young voters if we

want explicate its effects.

Finally, Model D shows a negative effect of 0.036 on the electoral participation of

individuals who first had the opportunity to vote at 18 years of age. This can be compared to the

average of 0.038 lower turnout found among cohorts coming of age since the lowering of the

voting age in 22 established democracies (Franklin 2004) and implies a gradual drop of 3.6

30 The effect of this variable is, however, only barely significant at the 0.01 level, and loses all statistical

significance in the model without missing data imputation (Table A.3, Model D1, in the appendix).

29

percent in overall turnout over the period (50-60 years) that it takes to replace the entire U.S.

electorate. However, the relevance of the effect to the argument in this paper is that it corrob-

orates the role ascribed to length of residence. Like length of residence, younger initiation into

electoral politics gains its theoretical importance by indicating the extent to which individuals

could have been exposed to the motivating and cost-cutting effects of expressive engagement.

Evidently, cohorts first faced with an election at the younger age found it harder to learn the

habit of voting than those initiated into electoral politics at the later age. The theoretical approach

set out earlier expects this to be due to differences in their likelihood of finding themselves

enmeshed in the social networks that would guide and encourage them in acquiring that habit.

Indirect effects of the character of elections

Why are the effects of electoral competition attenuated in Models C and D of Table 3? I asserted

earlier that this would be due to the mediating role of individual-level variables whose values

responded to variations in electoral competitiveness. Indeed, any overall assessment of the extent

to which the character of elections plays a role in electoral participation needs to take account of

the indirect effects of electoral competition transmitted by individual-level variables.

It should come as no surprise that variations in elections' character have indirect effects

by way of the campaign variables. It makes sense that, at the time of a more competitive election,

interest in politics goes up and so does the salience of the election at hand. It also makes sense

that groups and individuals should work harder to get out the vote in races where such efforts are

more likely to yield an electoral payoff. The extent of these indirect effects is suggested in Table

4, which summarizes a more detailed table supplied in the appendix to this paper. That table

(Table A.2) gives the effects on campaign variables of shifting each indicator of electoral

30

Table 4 Effects of electoral competitiveness on campaign variables, from OLS

regression analysis (summarized from Table A.2 in the appendix)

Intervening variables

Total effects of electoral

competition on

established cohorts

Total effects of

electoral competition

on new cohorts

Contacted by major party 0.076 0.236

Strength of partisanship -- 0.129

Interest in public affairs -- 0.116

Interest in election -- 0.144

Cared who won 0.059 0.130

Importance of party differences 0.124 0.128

Source: Table A.2 in the appendix (presented here as absolute values – see note 31).

31

competition from its minimum to its maximum observed value.31

TABLE 4 ABOUT HERE

The summary in Table 4 shows the extent to which each intervening variable would

change its value (distinguishing effects on new cohorts from effects on established cohorts) as a

consequence of such changes in the character of elections. As can be seen, effects are much more

extensive for new cohorts, reinforcing the message of aggregate-level findings that only citizens

facing one of their first few elections are truly responsive to changes in electoral context. For

new cohorts the effects of electoral competitiveness on campaign variables are strong. A shift in

electoral competitiveness from its minimum to its maximum would result in 'contacted by major

party' shifting through nearly a quarter of its range of possible values, and in 'strength of parti-

sanship,' 'interest in public affairs,' 'interest in the election,' 'cared who won,' and 'important party

differences' being shifted through between 12 and 14 percent of their ranges of possible values.32

31 Note that measures of electoral competition generally have an inverse relationship with turnout: in safe

seats, values of these variables are high while turnout is low. So the role of campaign characteristics as

intervening variables is indicated by the strength of the negative effects on them (the summary table

shows absolute values, so as to avoid confusion). The positive effect of district margin on strength of

partisanship among established cohorts in Table A.2, which would have been significant had I used a 2-

tailed test, is discussed in footnote 36. 32 Notice particularly the strong effects on 'contacted by major party.' These suggest extensive efforts to

get out the vote in districts with close races. It seems clear that parties understand the importance of

contacting young adults. These effects might seem to contradict Hilligus' finding of lesser effects of such

contacting for new voters. However, the effect in Table 4 is an effect on contacting by major parties, not

an effect of such contacting. Young voters are more likely to be contacted when the race in a district is

tight, as makes sense. Such efforts are, however, less successful for younger voters, as shown by the

interaction with new cohorts in Table 3's Model D, in line with Hilligus' (2005) findings.

32

Other effects on intervening variables are too small to have significant indirect effects.33

Applying these shifts to the effects of the variables in question, shown in Table 3’s Model

D, would result in a 1-8 percent change in participation for new cohorts, depending on the exact

mix of effects – enough (when taken with the 1-2 percent effects on established cohorts and 7

percent direct effects of district competitiveness) to have been responsible for the actual shifts of

up to 11 percent that have occurred in U.S. turnout since 1960.

Though included in Model D mainly to test a subsidiary hypothesis, and so as to ensure

that the model is well-specified, the effect of the lowering of the voting age, at -0.036, seems to

suggest that the overall fall in turnout in this country that has occurred since the middle 1960s

could readily be accounted for by the lowering of the voting age which, in the US, happened in

time for the election of 1972. However, the U.S. has also seen a considerable increase in the

average margin of victory in congressional district races during the same period, reason for

additional turnout decline. The total decline in U.S. turnout is thus over-explained by Model D,

suggesting that there would actually have been a rise in U.S. turnout but for the lowered voting

age and the reduced number of competitive congressional races.34 So this paper's findings

33 The complete absence of significant effects on the expectation of a close presidential race evidently

reflects the fact that all the significant effects of electoral competition involve district races. This

reinforces the impression that these findings have to do with the activities of contactors rather than with

the knowledge of the contacted (see footnote 16). If the effects were about knowledge, young adults

would surely more readily become informed about the Presidential race than about the local race. 34 During the thirty years since 1972, some three fifths of the U.S. electorate has been replaced with voters

who had their first electoral experience after turning 18. When the whole electorate has been replaced, the

effect of the reform will apparently have been a drop in turnout of 3.6 percent. As of the election of 2000

(leaving aside the 2004 contest whose extraordinary character has yet to be fully explained), the drop was

only three fifths of that, or 2.1 percent, but this is more than the total amount by which U.S. turnout had

declined since 1960 once appropriate corrections are made (McDonald and Popkin 2001).

33

resolve a longstanding paradox first pointed out by Brody (1978) and often mentioned since that

time (eg. Teixeira 1992; Rosenstone and Hansen 1993) arising from the fact that U.S. turnout has

been declining even while the population was becoming notably better educated.

Anonymity and turnout

This paper has employed a multiple election case study to provide an indirect test of the intuition

that new electoral cohorts gain the habit of voting partly as a consequence of the mobilizing

effect of expressive engagement among family, friends, and acquaintances. The powerful effect

of length of residence among new cohorts strongly suggests the importance of living in a locale

long enough to become known to those who will attempt to motivate one's vote.35 This finding is

reinforced by the effect of lowering the voting age which, it was hypothesized, would operate by

means of the same mechanism.

These findings are buttressed by the observed attenuation of district-level effects when

campaign variables are taken into account. Indeed, if we did not have a theory that called for

effects on new cohorts to result from activities of politicized individuals in specific neighbor-

hoods responding to electoral competition locally, we would be unable to account for what

appears to be the anomalous impact on individual-level electoral participation of district

measures of electoral competition rather than of nationwide measures in Tables 2 and 3. The fact

that half the effects of district-level competitiveness are subsumed by individual-level variables,

when those variables are introduced in Models C and D of Table 3, tells us that electoral

competition is influencing behavior at the local level, as called for by this theory.

35 Plutzer (2002) established that interstate relocations served as a major impediment to the acquisition of

habitual voting, a finding that fits nicely with those reported here.

34

The findings illustrate the critical importance of distinguishing effects for newer electoral

cohorts from effects for more established cohorts. Failure to make this distinction not only

prevents one from deducing the long-term implications for baseline turnout in future years, as

argued in previous research (Franklin 2004; Franklin, Lyons and Marsh 2004) but would also, in

this research, have made it impossible to confirm the conjecture that length of residence is a

fundamental aspect of the mechanism by which members of new cohorts are transformed into

habitual voters. Past research had shown no very strong effect of length of residence (see for

example Verba, Schlozman and Brady 1995:453). The present research finds length of residence

to be crucial – but only for members of new cohorts. Failure to focus on new cohorts would

result in failure to identify the importance of this variable.

The findings also establish the importance of electoral competitiveness in determining

whether members of new electoral cohorts will vote or not, confirming with individual-level U.S.

survey data the implications of earlier aggregate-level analyses that have profound implications

for our understanding of how and why the long-term baseline level of turnout evolves over time.

This paper's findings lay bare the ways in which electoral competitiveness manifests itself at the

individual level, largely by way of the traditional variables employed in past research. But the

fact that these effects are largely explicated does not make them less important. Taking account

at the individual level of aggregate-level processes of electoral competition helps us to under-

stand how long-term turnout change takes place.

There is much still to be learned about the process that turns young adults into habitual

voters. Building on an argument developed earlier, the age variable in interaction with new

cohorts provides something of a benchmark for the extent to which the transformation of new

electoral cohorts with low turnout into established electoral cohorts with higher turnout has been

35

explicated. Model D shows that a rise in turnout of 0.135 accounted for by new*age needs to be

accounted for in some more specific fashion. Still, at least the findings of this paper should help

focus future research on the real problem, identified by Plutzer (2002) as central, which is to

understand this process.

The findings also leave other unanswered questions. Though they dovetail nicely with

recent research (Beck et al. 2002; Plutzer 2002; Hillygus 2005), suggesting that length of

residence is a precondition that makes it easier for friends and acquaintances to shepherd young

adults into the habit of voting,36 still one would like to be able to 'connect the dots' by including

questions in future National Election Studies that ask whether individuals were made aware of

the vote intentions of acquaintances, family, and friends. New questions might also ask whether

respondents had themselves initiated the contacts that led them to being expressively engaged.

Such questions might help to determine whether learning to vote is ever a self-motivated matter,

rather than just a response to the mobilizing efforts of others.

The title of this paper is deliberately ambiguous on this score. Being known by name

could lead people to feel an obligation to those with whom they have connections, or the link

could (as I have presumed) go the other way. But, in either case, it is anonymity (or the lack of

it) that is important. For others to know who you are is apparently crucial if, as a new member of

the electorate, you are going to make the transition to habitual voting. Anonymity is also the

primary assumption responsible for the so-called "turnout paradox" (Grofman 1993) which arises

36 They also reinforce a suggestion made by Franklin (2004:166) that the importance of strength of

partisanship in conventional studies of electoral participation has been misconstrued. The positive effect

of margin of victory on strength of partisanship among established cohorts suggests that party ID may be

serving to mitigate the effects of low electoral competition rather than to boost to the effects of high

competition.

36

from the fact that people do vote even though, reasoning from first principles, they should have

had no incentive to do so.37 This paper's findings appear to confirm the intuition of Riker and

Ordershook (and of Downs before them) that anonymity would rob people of a motive to vote.

But anonymity, viewed as a condition rather than as an assumption, becomes a variable that

apparently helps to determine whether people will learn the habit of voting or not.

The anonymous individual indeed has less reason to vote, unless he or she has already

acquired the habit of voting. But the findings of this paper strongly suggest that a person whose

name is known, within a supportive network of family and friends (or acquaintances)

expressively engaged with one-another on the subject of their vote intentions, needs a very good

excuse for not voting.

APPENDIX

Table A.1 about here

Table A.2 about here

Table A.3 about here

37 The assumption concerned is that potential voters lack knowledge of what other potential voters will

do, an assumption that makes it irrational for individuals to take account of the rewards of voting (since

those rewards, if they are forthcoming, will be enjoyed whether the individual votes or not).

37

Table A.1 Logistic regression results (with robust standard errors) for Table 3

Model A Model B Model C Model D b s.e. b s.e. b s.e. b s.e. Constant 1.256 0.071 -3.888 0.182 -3.758 0.209 -3.122 0.280 New voter cohorts -0.770 0.276 District margin -0.397 0.164 -0.278 0.130 -0.255 0.126 District uncontested -0.302 0.153 -0.181 0.092 -0.236 0.101 Age 1.474 0.181 1.452 0.179 0.387 0.238 Education 1.559 0.176 1.544 0.178 1.304 0.175 Occupation 0.375 0.070 0.377 0.070 0.372 0.066 Home ownership 0.557 0.053 0.562 0.054 0.554 0.053 Income 0.963 0.069 0.933 0.066 0.970 0.098 Efficacy 0.552 0.076 0.544 0.075 0.533 0.072 Church attendance 0.727 0.072 0.740 0.072 0.842 0.075 Union member 0.269 0.053 0.262 0.056 0.237 0.061 Residence 0.605 0.194 0.618 0.189 0.515 0.172 Contacted by party 0.603 0.062 0.589 0.065 0.660 0.071 Strenth of party ID 0.833 0.046 0.841 0.047 0.824 0.046 Interest in public affairs 0.703 0.095 0.711 0.091 0.697 0.086 Interest in election 0.899 0.127 0.899 0.127 0.886 0.126 Cared who won 0.444 0.074 0.444 0.071 0.460 0.076 Close presidential race 0.102 0.062 0.103 0.061 0.123 0.062 Party differences 0.271 0.045 0.269 0.045 0.271 0.044 Tried to influence others 0.427 0.059 0.428 0.059 0.437 0.058 New*Age 1.522 0.643 New*Education 1.012 0.223 New*Residence 1.477 0.298 New*Church attendance -0.419 0.094 New*Income -0.569 0.171 New*Contacted -0.194 0.061 Could vote at 18 -0.247 0.067 Valid N 19660 19660 19660 19660 Pseudo R2 0.028 0.250 0.255 0.261

Note: Significance levels and coding of variables are given in Table 3 in the text of the paper. Robust

standard errors clustered by year.

Source: American National Election Studies, 1960-2004 post-election waves, with merged aggregate

data.

38

Table A.2 OLS regression results (with robust standard errors) for Table 4.

Effects on major party contacting

Effects on strength of party id

Effects on interest in public affairs

Character of elections variables b s.e. b s.e. b s.e.

Established * district margin of victory -0.076 0.030 * 0.077 0.011 0.028 0.021

New * district margin of victory -0.236 0.038 ** -0.129 0.015 *** -0.116 0.030 ***

Established * district unopposed n.s. n.s. -0.044 0.024 * New * district unopposed n.s. n.s. 0.019 0.052

Constant 0.312 0.023 ** 0.606 0.010 *** 0.608 0.017 ***

Total effects on established cohorts -0.076 n.s. -0.044Total effects on new cohorts -0.236 -0.129 -0.116 Adjusted R2 0.010 0.017 0.007 N 18344 17894 18945

Effects on interest in election

Effects on cared who won

Effects on cared who won

Character of elections variables b s.e. b s.e. b s.e.

Established * district margin of victory 0.010 0.019 0.043 0.024

0.077 0.023

New * district margin of victory -0.144 0.010 *** -0.130 0.032 *** 0.013 0.022

Established * district unopposed n.s. -0.059 0.031 * -0.124 0.032 **

New * district unopposed n.s. 0.007 0.036 -0.128 0.041 **

Constant 0.576 0.014 0.677 0.026 *** 0.601 0.022 ***

Total effects on established cohorts n.s. -0.059 -0.124Total effects on new cohorts -0.144 -0.130 -0.128Adjusted R2 0.010 0.006 0.004 N 19545 19545 19339 Note: Significant at *.05; **.01; ***.001 levels, one-tailed. n.s. = effect was not statistically significant at

the 0.05 level, one-tailed. Robust standard errors clustered by year.

Source: American National Election Studies, 1960-2004 post-election waves, with merged aggregate data.

39

Table A.3 Supplementary findings (Model D1 with listwise deletion of missing data,

Model D2 with vote at previous presidential election) with robust standard errors.

Model D1:

with listwise deletion Model D2:

with previous vote

1st

difference b s.e. 1st

difference b s.e. Constant -0.214 0.139 *** -3.296 0.223 *** (New-1)*voted at previous election 0.249 1.923 0.305 *** New voter cohorts -0.039 -0.284 0.261 -0.401 0.250 0.268 District margin -0.029 -0.214 0.139 -0.187 0.124 0.118 District uncontested -0.012 -0.090 0.120 -0.044 -0.324 0.098 *** Age 0.079 0.634 0.277 * -0.014 -0.112 0.298 Education 0.228 1.590 0.253 *** 0.140 1.093 0.206 *** Occupation 0.042 0.308 0.110 ** 0.042 0.336 0.068 *** Home ownership 0.064 0.455 0.065 *** 0.065 0.514 0.078 *** Income 0.124 0.933 0.115 *** 0.088 0.720 0.122 *** Efficacy 0.073 0.534 0.075 *** 0.066 0.522 0.089 *** Church attendance 0.126 0.905 0.093 *** 0.089 0.695 0.095 *** Union member 0.042 0.340 0.078 *** 0.021 0.179 0.065 ** Residence 0.098 0.914 0.179 *** 0.041 0.359 0.188 * Contacted by party 0.093 0.781 0.062 *** 0.061 0.542 0.060 *** Strength of party ID 0.108 0.761 0.088 *** 0.090 0.684 0.048 *** Interest in public affairs 0.079 0.567 0.109 *** 0.073 0.567 0.076 *** Interest in election 0.111 0.795 0.147 *** 0.099 0.785 0.117 *** Cared who won 0.067 0.470 0.074 *** 0.051 0.402 0.073 *** Close race expected 0.011 0.081 0.078 0.004 0.033 0.086 Party differences 0.030 0.221 0.050 *** 0.035 0.277 0.057 *** Tried to influence others 0.054 0.419 0.055 *** 0.052 0.445 0.065 *** New*Age 0.080 0.779 0.666 0.140 2.556 0.668 *** New*Education 0.069 0.601 0.179 *** 0.117 1.294 0.294 *** New*Residence 0.113 1.333 0.494 ** 0.115 -0.344 0.345 *** New*Income -0.077 -0.507 0.238 * -0.047 -0.246 0.175 * New*Church attendance -0.088 -0.578 0.151 *** -0.032 -0.246 0.115 * New*Contacted -0.031 -0.217 0.075 ** -0.006 -0.049 0.068 Could vote at 18 -0.025 -0.187 0.072 ** -0.029 -0.228 0.079 ** Valid N 10777 19660 Pseudo R2 0.250 0.325

Note: Significant at *.05; **.01; ***.001 levels, one-tailed. Robust standard errors clustered by year.

Source: American National Election Studies, 1960-2004 post-election waves, with merged aggregate data

(see footnote 22).

40

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