Heterogeneity in Voting Behaviour · Determinants of voting behaviour are situated in the rest of...

Heterogeneity in Voting Behaviour Maxime Heroux-Legault

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Heterogeneity in Voting Behaviour

The literature on vote choice is diverse. It boasts many concurrent models upon which researchers can

draw to explain voting behaviour. Past research has proposed four main approaches to understanding

vote choice: The Columbia school focuses on social characteristics, the Michigan school focuses on party

identification and key issues, the spatial model focuses on ideological distance between voters and

parties and the valence model focuses on evaluations of the leaders and party competence at handling

consensual issues (Lazarsfeld et al. 1944; Berelson et al. 1954; Downs 1957; Campbell et al. 1960; Stokes

1963, 1992). More recent work focuses on the impact of other variables, such as emotions, political

sophistication, heuristics and economic voting in the voting calculus. (Marcus et al. 2000, Lau and

Redlawsk 2001, Luskin 1987, 1990, Lewis-Beck 2000)

With so many models, researchers are able to explain a large proportion of the variation in vote choice.

To do so, they increasingly rely on equations comprised of variables originating from the many models

above (Miller and Shanks 1996, Gidengil et al. 2012). One could consider such an achievement the

pinnacle of electoral studies. Yet, there are problems in the way research on vote choice has been

conducted. Fundamental theoretical questions have been eluded in favour of a never-ending race

towards the maximization of explanatory power.

The field suffers from a lack of theory. The proliferation of variables can lead to a kitchen-sink approach

to research and modeling. This does not mean that complex models which incorporate many variables

are wrong in principle. On the contrary, given the complexity of social life, it is almost certain that no

single variable or phenomena can explain vote choice on its own. However, using such models should

require more theoretical work than simply adding together variables originating from competing

models. For example, it needs to be explained how the spatial model and the valence model can coexist.

The first assumes that voters are informed and can choose parties based on their platform, while the


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second considers that voters are poorly informed and have to rely on summary evaluations of leaders

and party competence rather than the party platforms. Why would voters able to make decisions under

the downsian paradigm rely on leadership cues when they know what party will defend their interests

based on the policies it promotes? How can a voter without such information vote spatially at all? The

point is not that composite models are to be shirked, but rather that the manner in which the models

that comprise the composite relate to each other must be theoretically developed.

This theoretical inquiry is inspired by classic trade-offs featured in discussions of social research.

Przeworski and Teune (1970), for instance, highlight four goals of social science: generality, parsimony,

accuracy, and causality. Writing 45 years ago, they argued that generality and parsimony trump

accuracy. Since then, researchers have accomplished much. Political scientists now have parsimonious

models which are able to explain a large portion of the variation in voting decision. Given this

accomplishment, much of the work concerned with parsimony and generality has been largely

successful. It is now time for election scholars to turn their attention to the goal of accuracy. This has

already been discussed by some practitioners of electoral studies (Bartle, 2005) and follows an emerging

development in the philosophy of science to adopt scientific realism as a guide for scientific research

(Godfrey-Smith, 2003). Furthermore, King, Keohane and Verba have shown very limited support for the

general goal of parsimony (1993).

The main goal of the research is thus to study voting behaviour in more detail than is usually the case

when researchers rely on composite models such as the bloc recursive model. This paper will address

the puzzle discussed above, that is, that both the spatial and valence models are found to be significant

predictors of the vote even though the theoretical justifications for each model seems to contradict

those of the other. The spatial model argues that voters hold positions related to issues and know each

party’s positions on these issues, while the valence model explicitly denies this argument. It is likely the


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case that current results are explained by the fact that regression analyses average across all voters.

Identifying which voter characteristics have an effect on decision-making may help us identify which

voters rely on spatial judgments and which rely on valence judgments.

In the parlance of statistics, such characteristics would act as moderators. There are reasons to believe

that political sophistication may have an incidence on the propensity to think about politics in spatial or

valence terms. In this view, political behavior is the result of two distinct types of rationality, or a dual

rationality. Partial evidence for this can be found in previous work, though no work explicitly tests this

hypothesis.

This paper opens with a review of the literature on voting behavior. It then develops a theory that

explains why political sophistication determines whether an individual voter will rely more on the spatial

or valence model of voting. This is followed by a discussion of the empirical strategies employed to test

the predictions of the model of dual rationality, the execution of these strategies and a discussion of the

results.

The Literature on Vote Choice

Four principal models of vote choice have been advanced in the political science literature in the last

half-century. They are reviewed briefly. Afterwards, the literature on political sophistication is discussed

as well as how it relates to these models.

The researchers behind the Columbia model (Lazarsfeld et al. 1944) asserted that electoral behaviour

can mostly be explained by social characteristics. In its most parsimonious form, the Columbia model

rests upon the index of political predispositions (IPP). This index combines religion, region of residence

and the socio-economic status of the respondent. The authors established that social characteristics


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played a very important part in explaining the vote in the 1940 presidential election. The same trends

were identified in another study conducted in 1948 (Berelson et al. 1954).

The Michigan study tried to address one important question raised by the Columbia studies. Since social

groups are stable, the Columbia studies were unable to explain variation in election results over time.

The Michigan researchers’ task was thus to devise a model of voting that would be able to explain

changes from one election to another.

Their first contribution was to introduce the concept of the funnel of causality. Campbell et al. (1960)

conceptualized voting behaviour to be at the narrow end of the tunnel. Determinants of voting

behaviour are situated in the rest of the funnel, with the elements farther away from the vote being

closer to the top. Social characteristics, for example, are more distant from the vote than reactions to

the leader’s debate and as such would appear before effects of the debate in the funnel of causality.

This conceptualization lets the authors consider many variables that are both sociological and

psychological in nature. They use party identification as well as six attitudes to explain voting behaviour.

They are attitudes towards both party leaders, domestic and foreign policy as well as attitudes regarding

group-specific policies and the capacity of the parties to manage the country. These attitudes explain

the short-term variations observed across elections. Party identification, however, is a characteristic that

is enduring and grows stronger over time. Campbell et al. (1960) argued that party identification is a

stable orientation developed early in life, and that it is affective in nature. They also argue that party

identification affects voters’ perceptions. Thus, party identification has a direct effect on the vote and an

indirect effect since it affects voters’ perceptions of issues and the incumbent’s performance. The

authors show that these variables are more potent than social origins and even respondents’ own

prediction of their vote to predict how they will behave.


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A very different perspective is offered by the spatial model of voting. It assumes that voters are rational

beings who are motivated by their own self-interest (Downs 1957). This means that they can always

make a decision when presented with a set of alternatives, that these alternatives are ranked as better,

worse or equal to each other, that the preference ranking of alternatives is transitive, that a voter will

always choose the alternative which ranks higher and that, given the same set of alternatives, a voter

would always repeat the same choice.

From this set of propositions, one can deduce many behaviours that a rational voter should adopt. His or

her support for a party will be determined by the advantages gained from voting and constrained by the

cost of voting. The benefits of voting are a function of how close the voter is to the competing parties’

platform. The closer a voter is to a given party, the likelier it is that the voter will support this party. The

costs of voting include information costs and the time it takes to vote.

This description makes it possible to identify three key characteristics of the spatial model of voting.

First, under this model, politics is conflictual. Voters with opposite beliefs support parties which also

oppose each other. Politics is understood as a conflict between left and right generally, or between

conflicting positions regarding a specific issue. Second, in this model voters vote for a policy. They are

supposed to consider the platform of political parties and cast a vote in function of how well these

platforms benefit them. Other factors, such as party identification or appreciation of the party leaders,

should not affect the vote under the spatial model. Third, this model relies on a strong assumption of

voter competence. This model requires voters to hold positions of their own, be aware of the positions

of the parties and to be able to understand how proximate they are to the parties competing in the

election. For the model to even be viable, voters are required to be knowledgeable about politics.

The valence model was introduced by Donald Stokes (1963; 1992) in response to the spatial model. He

argued that voters often do not have specific policy positions. Likewise, Clarke et al. (2009: 12) argued


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that voters are “smart enough to know they aren’t smart enough” to make informed policy choices.

Proponents of the valence model argue that voters vote for a candidate or a party based on expectation

of their performance, rather than based on their proposed policies. Valence politics revolve around

consensual and technical issues where virtually all agree on the goal but are not really concerned about

the means of obtaining it. An excellent example of this is having a strong economy. Most voters are in

favour of a strong economy, but are often unaware of the finer points of economic theory. As such, they

do not have strong beliefs regarding which economic policy is optimal to encourage growth, limit

inflation, or create jobs. For this reason, they have difficulty using competing policy platforms as the

basis to make their electoral choice. Instead, valence voters make their voting decision by relying on

more easily accessible information such as their personal evaluation of the leader, whether they identify

with a party or not and which party they think is the best at handling consensual issues such as the

economy.

Like the spatial model, the valence model can be summarized with three defining characteristics. First,

unlike the spatial model, it advocates the idea of politics as revolving around consensus. This is because

the issues that matter in the valence model of voting are consensual. Virtually every voter seeks more

security, a stronger economy and less corruption in government. Elections centered on those issues are

thus not likely to oppose parties claiming to seek different goals. Rather, such elections will be

characterized by a large degree of consensus. These elections will instead be framed as a competition

between parties regarding who is the best to take on these consensual challenges. This leads us to the

second characteristic of the valence model. In this model what matters are not platforms or policies, but

rather perceptions of performance. The determinants of the vote in this model are thus different than

under spatial voting. In the valence model, evaluations of parties and leaders matter while knowledge of

policy positions do not. Third, the valence model is less demanding of voters than the spatial model. The

voters are not required to have positions of their own, or to know the parties’ positions. Indeed, since


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politics is consensual under the valence model, it is difficult to conceive of opposing positions. Instead,

voters are only required to devote enough attention to the campaign to develop some opinion of

parties’ performance when handling consensual issues – a much less demanding standard.

These models are numerous and varied. They rest on different assumptions and sets of theoretical

expectations. Recent work in the field of election studies has tried to combine them in order to

maximize explanatory power. This is illustrated by a model of vote choice devised by Miller and Shanks

(1996). Their model is interesting because it tries to reproduce the notion of the funnel of causality

(Campbell et al. 1960). It has the advantage of studying variables in the order in which they appear in

the funnel, and takes this into account to identify the total effects of variables involved in the voting

decision. It also mobilizes the variables made salient by the four models of vote choice discussed above.

This bloc recursive model has been used extensively by members of the Canadian Election Studies team

(Blais et al. 2002, Gidengil et al. 2012) to study vote choice in the Canadian context. Another group to

make use of many models (which they combine under the label “composite model”) leads the British

Electoral Study (BES). (Clarke et al. 2004, 2009, Whiteley et al., 2013). Their results are consistent across

elections. They found that the valence model explains most of the voting decision, followed by the

spatial model, with sociological models trailing behind.

However, several challenges arise when considering such models. The most important one regards the

challenge of theoretical compatibility. If these models all rest on different theories, assumptions and

disciplinary origins, can it simply be assumed that combining them in an additive regression model

makes theoretical sense, even if it performs well empirically?

A possible issue is that these models are mutually exclusive. The valence model was introduced in

opposition to the spatial model. The latter argued that voters are informed and choose candidates

based on the policies they defend, while the former argues that voters are not equipped to do this and


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that consensual issues drive politics. It seems strange, then, that both models would find confirmation

in standard models of vote choice.

A possible solution out of this paradox relies on the idea of heterogeneity. Regression estimates are

averaged across all respondents. The results obtained in recent studies of vote choice which show

support for both the valence and spatial models might support both models because in the aggregate,

voters use both. However, this does not mean that individual voters rely on both models equally. There

may be a category of voters who rely on the spatial model to a greater extent, while another category of

voters may instead rely more strongly on the valence model. Political sophistication may determine to

which subset an individual belongs.

The Literature on Political Sophistication

The concept of political sophistication has come a long way. Luskin (1987), for instance, argues that it is

present in an early form in Campbell et al. (1960) and Converse (1964). Under this view, political

sophistication includes knowledge about politics, but can also be understood as the capacity to create

links between many elements of politics and the ability to understand politics as an ideological

phenomenon. Under this view, the sophisticated are those at the apex of Converse’s (1964) ideological

hierarchy; those able to situate politicians and the policies they espouse in an ideological sense, for

instance as liberal or conservative, are at the top of the scale. Those in the third or second category,

who can relate issues to groups or contemporary debates, are in the middle of the scale, while

respondents who would be unable to discuss policies or issues would be among those with the least

political sophistication. Political sophistication is thus linked closely with the idea of political belief

systems. According to Luskin (1987), voters with a high degree of political sophistication show belief

systems of greater size, range, and constraint than voters with lower sophistication.


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However, in practice political science has redefined the measurement of the term. This is because using

a coding scheme such as Converse’s is very demanding. It requires an in-depth interview with a

respondent and then a qualitative assessment by the researcher of the respondent’s level of

sophistication based on the interview. This is a necessarily subjective appraisal which is extremely time-

consuming on the part of the researcher. It is also very time-consuming on the part of the respondent,

who has to engage in discussions about politics with the interviewer, a type of exchange which may be

more difficult now that most political science surveys are conducted over the phone or online rather

than in person. For this reason, Luskin (1987) recommends using three types of measures to tap political

sophistication: Active use (AU), recognition and understanding (RU) and information. He also

recommends using a composite of all these variables. To his surprise, the index based on pure

information performs even better than the composite.

Measures that depend on political information have since gained in importance, and their virtues have

been touted by, among others, Zaller (1992), Milner (2010) and Delli Carpini and Keeter (1996). They

argue that political knowledge is one of the best measures possible because it is objective. Regardless of

sophistication, voters can answer a question asking whether they are liberal or conservative. This is

because when provided with choices, even poorly sophisticated voters can provide an answer.

Questions regarding factual political knowledge, however, are objectively correct or wrong. For this

reason, they provide a better barometer of political sophistication than other questions. They also prove

resistant to attempts by respondents to appear more politically sophisticated than they actually are.

Schwarz and Schuman (1997) show that when asking questions about political knowledge before asking

about political interest, reported political interest is much lower than when this order is reversed.

Another strand of the literature on political sophistication focuses on how it develops. Intuitively, one

would think that education and exposure to the media would be among the prime conditions for the


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development of political sophistication. Yet, while these variables correlate with it, they seem to have

very weak effects on political sophistication. Luskin (1990) found that the most important determinants

of political sophistication are motivation (operationalized as political interest) and ability

(operationalized as intelligence). While education and exposure to the media are included in his model,

they have weak effects on political sophistication.

Highton (2009) proposed an interesting design to monitor the causal effect of college education on

political sophistication. He measured the degree of political sophistication of high school students, and

then measured it again after their college education was completed (or after a similar time period for

those who did not attend college). While he does find that the students who attended college have a

higher level of political sophistication on average than those students who did not, the gap between the

two groups did not increase while they were in college. In other words, the gap in political sophistication

between the two groups was the same before and after attending college, thus showing that political

sophistication is not affected by college education and determined relatively early in life. Highton argues

that important determinants of political sophistication are cognitive ability, parental characteristics, and

pre-adult political engagement.

Arceneaux et al. (2012) offered evidence which supports this argument. They assessed the impact of

genetics on political sophistication. They found that genetics account for 46% of the variance of interest

in politics and 60% of the variance of political knowledge. Their findings supported those of Higton

(2009). They show that political sophistication is a largely fundamental, pre-political construct.

This lends credibility to the hypothesis that there may be heterogeneous subsets of voters in the

population. If education and exposure to the media had a strong effect on political sophistication, then

one could expect that with rising education levels across the population and the ubiquity of news

coverage, political sophistication would be relatively homogeneous across the population. If this were to


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be believed, political sophistication would be a poor starting point to distinguish across groups of voters.

However, given that these variables have only weak effects on political sophistication, it seems likely

that such heterogeneity would at least be plausible.

An important point of contention in discussions of sophistication and voting behaviour concerns the

concept of correct voting. Scholars have realized that many voters have low levels of political

sophistication, and have become concerned that they may be unable to vote to the party that is the

most apt to defend their interests. In response to this concern, Sniderman et al. (1993) introduced the

idea that voters could rely on heuristics, that is, cognitive shortcuts that make it possible to make good

decisions even when lacking complete information. Lupia contributed to the argument (1994), showing

that unsophisticated voters can make the same decisions as sophisticated voters in the presence of

strong endorsement cues. However, this argument is not uncontroversial. Bartels (1996) found that in

American presidential elections, the correct voting hypothesis does not hold either at the individual or

the aggregate level. The debate is not close, however, as recent work argues that valence voters

successfully make use of heuristics to make their voting decision. (Clarke et al., 2009)

Political Sophistication and Heterogeneity in Voting Behaviour

Bartle (2005) is one of the few to have explicitly made the argument that studies of voting behaviour

should turn towards heterogeneity. He argued that models summarized by a single additive equation

are not sufficient to describe the causal complexity of the voting decision. He hypothesized that voters

may not all rely on similar reasoning to make their voting decision. He pointed out that if this is the case,

a single additive regression will lead to wrong results for both subsets of voters. He found that less

sophisticated voters place more weights on leader evaluations than other voters.

Boatright (2008) is concerned with the spatial model. He first identified spatial violators, that is, voters

who did not vote for the party closest to their own positions. He then analyzed what distinguishes this


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group from the rest of the sample. He found that these voters show below-average levels of political

knowledge, activism, and interest. This finding is consistent with the idea that political sophistication

determines how the voting decision is made. Yet, potential problems can be found in Boatright’s work.

First, it is probable that many apparent spatial voters are in fact not spatial voters. They could vote for a

given candidate not because they agree with the candidate’s policy position but rather because they like

the candidate, they identify with his or her party or because their social group generally endorses this

party. In other words, Boatright’s bivariate research design is unable to distinguish voters who support a

candidate because they share opinions on issues from voters who support a candidate with whom they

share opinions for other reasons. Conversely, some apparent violators may not vote for the closest party

because of party evaluations or leader evaluations, and not necessarily because they lack sophistication.

In other words, Boatright’s analysis is vulnerable to criticism because it ignores the other variables that

impact the voting decision. Compounding this problem is the fact that people who like a candidate or

identify with the party may misrepresent their ideological position in order to appear consistent to the

interviewer.

Lau and Redlawsk (2001) used a research design of their invention, the Dynamic Process Tracing

Environment (DPTE), to study the effect of political sophistication on decision-making. They found that

more sophisticated voters are more likely to rely on heuristics such as ideology and the endorsement

heuristic. They suggested that the less politically sophisticated would likely rely on partisan identification

and leader evaluations to a greater degree. However, they did not directly test this hypothesis. They also

noted that their research design necessarily includes a certain component of artificiality and that further

results from real elections would be welcome to confirm the validity of the results.

Kam (2005) uses an experimental design to study heterogeneity in voting behaviour. She found that the

less politically aware rely on party cues and not on an issue-relevant value. As political awareness


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increases, reliance on party cues drops and reliance on an issue-relevant value rises. Her findings

broadly support the hypotheses discussed here. However, it deserves to be noted that political

sophistication is not randomized in the research design, which limits the causal strength of the findings.

The findings also exclude important variables for the valence model such as perceptions of which party

and leader are the best to handle the issue under consideration. Finally, the experiment is about

supporting a given bill on one particular issue, rather than about supporting candidates in a more

complex electoral setting in which many issues are discussed simultaneously.

A more recent study has been conducted by Singh and Roy (2013). They found that more knowledgeable

individuals conduct a more thorough research of information, which they can then use to engage in

spatial voting to a greater extent than less sophisticated participants. This research thus goes in the

same direction as Kam’s but suffers from similar limitations, since they do not manipulate the

information available to participants and do not conduct the research in the context of a real election.

Up to this point, research on political sophistication and heterogeneity seems to support the idea that

more sophisticated voters are more likely to engage in spatial voting while less sophisticated voters

would resort to simpler heuristics associated with valence politics. However, several researchers

disagree with these findings. One of them is Cutler. (2002) He considered the effect of issues and leader

characteristics on sophisticated and less sophisticated voters. On average, he found that the

sophisticated are more strongly influenced by issues than unsophisticated voters. However, it deserves

to be noted that even the less sophisticated are influenced by some issues. Furthermore, he found that

all voters, regardless of sophistication, are similarly affected by leader characteristics.

Goren (2004) also obtained results which contradict the idea of heterogeneous subsets of voters. He

argued that while not all voters are sophisticated and able to relate particular issues to ideological

debates and constraints, the overwhelming majority of voters have values, and are able to relate these


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values to specific issues. Someone who espouses traditional family values, for instance, does not need to

know whether such values are liberal or conservative to oppose abortion and gay marriage. He tested

this hypothesis and found that the opinions of all voters are constrained similarly regardless of their

degree of sophistication.

Clarke et al. (2009) have also considered heterogeneity hypotheses. They found that sophisticated

voters are less likely to be moved by leader cues. Using a nonlinear model, they found that leader

effects are actually greater among people with modest levels of political sophistication, while they are

weaker at both ends of the sophistication scale. However, they ultimately rejected this finding because

it does not improve explanatory power and makes the models less parsimonious.

Whiteley et al. (2013) did something similar. They investigated the strength of leader effects in the

British referendum on alternative voting. This time, they found no effect of sophistication in either

direction. In a simple interaction, all voters reacted to the party leaders in the same way. However, in a

triple interaction they found that sophistication, knowledge of voter’s positions and leader evaluations

have a significant effect. This means is that while leader images have no differentiated effect of their

own across various sophistication levels, they do when knowledge of party leaders’ positions is factored

in.

While the above literature is suggestive, there is reason to believe that further research is needed. In

particular, the fact that there is no consensus in the literature is reason enough to motivate ongoing

investigations. It should also be noted that existing research contains important limitations which ought

to be corrected if one truly wants to integrate research on political sophistication, heterogeneity, and

models of voting. The above work is usually content to focus on one variable at a time rather than

specifying full models. This is a problem, as missing variables can lead to biased estimates. The


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subsequent analysis considers a full model of vote choice when investigating heterogeneity in models of

voting behaviour.

Hypotheses and Research Design

The hypothesis guiding the research supposes that different subsets of the population rely on different

rationales when casting their ballot. Political sophistication should constitute an important variable to

explain this heterogeneity. Informed voters are more likely to be aware of important political issues,

know where they stand and where the candidates and parties stand on these issues. As such, they are

more likely to exhibit the traits considered necessary to practice spatial voting. They are also less likely

to need to resort to cognitive shortcuts identified with valence politics such as party identification and

leader evaluations. (Clarke et al., 2009)

From the above expectation it is possible to formulate four distinct hypotheses. First, only the votes of

sophisticated voters should depend on their proximity to political parties. This is because the

unsophisticated are hypothesized to be unable to do so since they do not know where parties are

located on a left-right axis and how this relates to their own positions, if they hold any.

The three other hypotheses stipulate that unsophisticated voters should rely on variables associated

with the valence model to a greater extent than sophisticated voters. These variables are party

identification, evaluation of performance on the economy, and leader evaluations. The unsophisticated

should rely on these variables to a greater extent because they provide accessible cues that can be

easily followed to make their voting decisions. For the sophisticated that have access to more complex

and detailed information, the variables that belong to the valence model are not as useful. For this

reason, while they may use them in their voting decision to some degree, their impact will not be as

pronounced.


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The hypotheses are thus not completely symmetrical. Since the unsophisticated are supposed to be

unable to vote under the spatial model, the spatial model should have no impact at all in their voting

decision. The expectation is not as strong for sophisticated voters under the valence model. This is

because sophisticated voters have all the information needed to vote under the valence model. They

simply do not rely on it to the same extent as unsophisticated voters since other, more complex

information can guide their voting decision. As such, we expect the impact of valence variables to be

weaker among sophisticated voters, but not that it will be indistinguishable from zero.

To test the hypotheses, the paper relies on conditional logistic regressions (hereafter conditional logit).

The main advantage of conditional logits is that they allow a researcher to use both individual-specific

and alternative-specific variables in the same equation. An individual-specific variable is a variable that

characterizes a given individual, such as religion, race or gender. An alternative-specific variable

concerns the options given to the individual rather than the individual. For instance, such a variable

could be leader evaluations. In the context of electoral behaviour, this means that a researcher can

specify a different value for evaluations of each party leader for a given individual. This is extremely

useful for models of voting behaviour since conditional logits do not rely on one-on-one comparisons,

unlike multinomial logits. This means that a model of voting behaviour can be generalized and not be

limited to comparisons between two parties. A further advantage of conditional logits is that they can

take into account the decision-making process of individuals who have different choice sets. This

characteristic is important to study Canadian voting behaviour given the fact that party systems differ

across the country. In recent years, this has been true in Quebec given the presence of the Bloc

Quebecois, but the Reform Party and Social Credit have shown that this is not a recent anomaly, nor one

limited to the province of Quebec.


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The analysis relies on data from the 2011 CES. Many of the variables used in the models are taken

directly from the dataset and as such do not necessitate in-depth explanations. Some, however, have

been constructed and deserve details. One important variable represents spatial voting. This variable

measures the distance on the left-right spectrum between a given voter and a given political party. One

possible problem with this measure is that voters may attribute to their favorite party a position which is

close to theirs, which would overestimate the importance of ideological proximity when studying vote

choice. To offset this possible bias, the research design follows Cutler (2002) by using the average

perception of the position of a given party among knowledgeable independents instead of a particular

individual’s perception of this party’s position. Variables for the valence model were taken directly from

the dataset and did not need to be constructed. They consist of party identification, leader evaluations

and the party considered the best to manage the economy. The sophistication variable is a scale based

on eight questions monitoring knowledge about politics and runs from 0 to 1. The list of questions used

to construct this scale can be found in Appendix A. Finally, the analysis features several controls inspired

from sociodemographic and economic models of the vote, as well as earlier work on Canadian voting

behaviour (Gidengil et al., 2012). They include gender, age, catholicism, religiosity, atheism, French as a

first language, being married, education, as well as evaluations of the performance of the Canadian

economy over the last year.

Results

The analysis begins with a purely additive conditional logit. This means that heterogeneity is not yet part

of the model. The purpose of this step is simply to guarantee that the spatial and valence models

perform well and to establish a reference point from which the remainder of the analysis can be

evaluated. Results can be found in Table 1 and are reported using odds ratios.


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The first important conclusion from the conditional logit is the confirmation of the BES team’s oft-

repeated claim by the analysis. They have repeatedly found (Clarke et al. 2004, 2009, Whiteley et al.

2013) that the spatial and valence model outperform sociological models when trying to explain voting

behaviour. The results confirm this assertion. The variables associated with the spatial and valence

models are all significant and positive at the p=0.001 level1. This means that being close to a party

platform, liking its leader, thinking it is the best party to manage the economy and identifying with a

party all increase the probability of voting for this party.

On the other hand, none of the control variables are significant at the p=0.05 level. This means that

when the valence and spatial models are taken into account, other variables simply do not add much to

explanations of voting behaviour. This finding echoes the work of Roy and McGrane (forthcoming), who

find that the valence model on its own has an explanatory power similar to that of the bloc recursive

model traditionally used by the CES team. (Gidengil et al., 2012)

A second model including heterogeneous variables is specified. Four such variables are added to the

model. They each interact political knowledge with one of the main variables included in the first model.

Table 2 shows the results. The four variables that were included in the first model should now be

interpreted as the impact of these variables when sophistication is at 0. As expected, proximity voting is

not significantly different from 0 under this condition. Furthermore, it should be noted that the impact

of party identification and evaluations of performance regarding economic matters are much higher

among respondents who have low levels of sophistication. The impact of leader evaluations remains

unchanged.

This is confirmed by the interactive variables that were added to the model. The

ProximityXSophistication variable has an odds ratio above 1 and is significant, indicating that the

1 Note: The proximity variable is positive and significant regardless of whether one uses average position of parties

or a given individual’s perceived position of the party to construct the variable.


-19-

sophisticated rely more on spatial voting than the non-sophisticated. The Party

IdentificationXSophistication and Best on EconomyXSophistication variables having odds ratios

significantly smaller than 1 indicates that the impact of these variables on the voting decision is smaller

among sophisticated voters than among non-sophisticated voters. Finally, the last interactive variable

being not significant confirms that evaluations of leaders have homogenous effects on the voting

decision. Comparisons of the impact of each variable depending on degree of sophistication are

presented in figures 1 to 4.

Using the conditional impact of these variables as our starting point, we investigate whether

sophistication heterogeneity leads to changes in voting behaviour. This is especially important in light of

the literature on correct voting. Simulating the voting decision at the low and high end of the

sophistication variable can illuminate this debate. If the results are similar, then one can conclude that

voters make the same choice regardless of their level of sophistication. On the other hand, a lot of

variation would indicate that unsophisticated voters do not manage to make the decision they would

make if they were more informed.

All simulations below are conducted by manipulating political information from its minimum to its

maximum value. At the individual level, the importance of sophistication heterogeneity is impressive.

24% of voters change their vote when it is taken into account. This shows the huge impact sophistication

heterogeneity can have on individual voting decisions. Figure 5 summarizes the findings at the aggregate

level. It shows that the votes for the Conservative and the Green parties do not vary much once we take

the heterogeneous impact of sophistication into account. As the population becomes more

sophisticated, the vote for the Liberals and the Bloc decreases by 2 and 1 points respectively, while

votes for the NDP increase by 3 points. These results seem to indicate only minimal changes in the


-20-

aggregate. In other words, even though many individual voters change their vote, it seems that these

changes largely cancel out in the aggregate.

However, one should remember that even slight differences in votes can have considerable impacts in

the position of parties in the House of Commons thanks to regional disparity in electoral support and the

Canadian electoral system. For this reason, we simulate what these results would produce in terms of

seats in the House of Commons using an online tool developed by Bryan Breguet (2015). Results are

shown in Figure 6. The small differences in votes shown in Figure 5 have an important impact on the

composition of the House of Commons. With an unsophisticated electorate, the Liberals form the

official opposition, and the NDP and Bloc Québécois have an almost equal number of seats, at 46 and 43

respectively. The situation is quite different with a sophisticated electorate. In this situation, the NDP

forms the official opposition, while the Liberals are third. The Bloc loses 35 seats, as well as official party

status. In other words, while the heterogeneous impact of sophistication has a small effect on aggregate

vote choice, this small change in votes leads to important changes in the composition of the House of

Commons and Canadian politics. These results thus are more in line with those of Bartels (1996) than

Sniderman et al. (1993) and Lupia (1994). Indeed, our individual-level results in particular indicate a

bigger gap than in Bartels’ model, who found 10 points of variation due to sophistication. This difference

is due to the choice of variables interacted with political sophistication in the model. Bartels’ model used

exclusively socio-demographic variables, with which sophistication only interacts weakly. The variables

used in this paper have a more direct connection with sophistication, and as such their impact is

moderate more heavily by this variable.

The present paper started as an investigation of voter heterogeneity regarding sophistication. However,

it seems that this heterogeneity also has differentiated impacts on political parties. In other words, it

seems that some parties are favored by an electorate with low levels of sophistication, while other


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parties are advantaged when the electorate is sophisticated. While this finding was neither expected nor

hypothesized, we attempt to explain this finding in the next section.

Discussion

This paper’s theoretical inquiry was motivated by the apparent contradiction raised by proponents of

the spatial and valence models. In particular, the valence model was introduced to the literature as a

reaction against the spatial model, claiming that it inaccurately represents voters’ behaviour. (Stokes

1963) Nevertheless, while these models are theoretically opposed, they both find support in empirical

investigations of voters’ behaviour.

This paper proposed to explain this apparent contradiction by studying heterogeneity. It argued that

regressions may attribute both types of reasoning to all voters because regression results show averages

for the whole sample. If subsets of the population vote by using these models to varying degrees, then

models that do not inquire for heterogeneity may yield the apparent conclusion that all voters practice

both types of reasoning to the same extent. It was hypothesized that political sophistication would

determine to which extent a given voter relies on the spatial or valence models.

This hypothesis is supported by the analysis. Spatial voting only impacts the voting decision among the

sophisticated. We have also found that two variables belonging to the valence model, party

identification and perception of aptitude at managing the economy, have stronger effects among those

with low levels of sophistication. Only leader evaluations seem to have homogeneous effects across the

population.

In addition to helping resolve the theoretical tension between the spatial and valence model, the above

analysis has contributed to the debate on whether unsophisticated voters can vote correctly. The results

show that a quarter of Canadian voters would change their vote as sophistication increases from 0 to 1.


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This undercuts the optimistic belief that unsophisticated are able to vote as if they were informed by

relying on cognitive shortcuts.

We have further found that the spatial and valence models of voting impact different parties

heterogeneously. While this was not an expected finding, it is worthwhile to discuss it. It is possible that

some parties perform well under the spatial model but not under the valence model and vice versa.

Since the degree of sophistication determines the impact of either model, parties that perform well

under high degrees of sophistication would be favoured by the spatial model of voting, while parties

that perform well under low levels of sophistication would be favoured by the valence model of voting.

This explanation is plausible given the identity of the parties discussed above. The NDP is penalized

when votes depend on its reputation at managing the economy. It also cannot benefit from large

supplies of party identifiers. However, it is recognized for its platform and its ideological commitment to

it. On the other hand, the Liberals have a good record on the economy and a large proportion of

Canadians identify with the party. (Blais et al., 2002) However, one could describe Liberal policies as

being policies of brokerage rather than of ideological principles and commitment, which may penalize

the party when voters follow the spatial model of voting. One could argue that Conservatives have a

good economic record, enjoy a large section of supporters and hold distinct ideological commitments,

which may explain why their support does not seem to vary with degree of sophistication. One could say

the reverse about the Green party: with few supporters, an ambiguous platform, and no record to speak

of on the economy, they perform evenly under both models, though for reasons opposite to the

Conservatives. Finally, the Bloc Québécois has a platform that can be difficult to pinpoint on the left-

right axis given its nationalist focus and benefits from a large portion of identifiers in the general

population. It is thus possible to conclude tentatively that parties with strong, clear platforms will

benefit from a sophisticated electorate, while parties with a strong economic record and with whom the

population identifies will benefit from a less sophisticated electorate.


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The above discussion reveals fruitful avenues for future research. How can one explain that the impact

of leader evaluations on the vote is not affected by sophistication, unlike the other variables of the

model? A possibility would be that leader evaluations are endogenous to other variables, and simply

reflect the other priorities of the voter. For instance, a sophisticated voter may judge a leader based on

their platform, while an unsophisticated voter may do so based on whether they identify with their

party or not. If this is the case, evaluations of party leaders will seem to have homogeneous effects since

they operate at all levels of sophistication, even though they do so for different reasons.

Another important step is to broaden the analysis to other countries. While the argument is not specific

to Canada, it would be beneficial to show whether the heterogeneity observed in this study can be

replicated in other democracies. It would increase confidence in the results if they can be replicated

elsewhere. However, further benefits can be derived from extending the scope of analysis to other

countries. Doing so would extend the analysis of how political parties are affected by sophistication

heterogeneity, which would give more evidence to test our tentative argument regarding the

characteristics of the parties which benefit (or not) from a sophisticated electorate. Furthermore,

studying voting in other countries will highlight which national characteristics encourage and hinder

sophistication heterogeneity in voting behaviour.

Further research should also be conducted on the impact of sophistication on turnout and political

participation. Clarke et al. (2009) have found that the determinants of voting also determine turnout. If

this is true, then it is possible that sophistication heterogeneity also impacts political participation. This

may provide an answer for a longstanding problem in studies of political behaviour. Many researchers

wonder why political participation is decreasing while education is increasing in developed countries. A

possible answer would be that political parties do not offer what motivates a sophisticated public to

vote. If platforms are uninspired or too similar between competing parties, a sophisticated public which


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relies on the spatial model of voting will have no motivation to participate in elections. Sophistication

heterogeneity may not only affect for whom citizens vote, but also whether they vote at all.

Finally, the study of sophistication heterogeneity should also rely on experimental data. While

observational data is valuable, experimental data is important to ensure that the causal inferences we

make are valid and are not due to spurious or omitted variables. For this reason, the claim that voters

rely on varying models of voting due to political sophistication will be stronger if it can also be observed

in an experimental setting.


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Tables

Table 1: Additive Determinants of the Vote (Conditional Logit)

O.R. Std. Err.

Party Identification 4.47*** 0.57

Leader Evaluations 1.05*** 0.00

Best on Economy 1.88*** 0.26

Proximity 1.26*** 0.07

N(i)=3759

N(j)=896

Log-likelihood=-466.46

Legend

* : 0.05

**: 0.01

***: 0.001


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Controls for the Conditional Logit; Socio-demographic and Economic Variables

Liberal Party

O.R. Std. Err.

Age 1.02 0.01

Male 0.74 0.25

Catholic 1.12 0.48

Atheist 3.49 2.86

Religiosity 1.37 0.31

French 0.84 0.43

Married 0.75 0.26

Education 1.06 0.09

Economic Vote 1.16 0.29

Sophistication 0.74 0.75

Intercept 0.08 0.13

New Democratic Party

O.R. Std. Err.

Age 1.00 0.01

Male 0.97 0.31

Catholic 1.49 0.59

Atheist 0.75 0.54


French 1.29 0.61

Married 1.01 0.32

Education 0.97 0.07



Intercept 1.56 2.12

N(i)=3633

N(j)=865



-30-

Bloc Quebecois

O.R. Std. Err.

Age 1.01 0.02

Male 1.13 0.65

Catholic 1.54 1.72

Atheist 0.58 0.91


French 5.92 7.85

Married 0.75 0.47

Education 0.89 0.14



Intercept 0.27 0.77

Green Party

O.R. Std. Err.

Age 1.00 0.02

Male 1.74 0.88

Catholic 0.26 0.24

Atheist 0.57 0.68


French 0.54 0.54

Married 0.86 0.43

Education 1.04 0.13

Economic Vote 0.47* 0.17


Intercept 1.05 2.46

N(i)=3633

N(j)=865



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Table 2: Heterogeneous Determinants of the Vote (Conditional Logit)

O.R Std. Err.

Party Identification 13.26*** 7.19

Leader Evaluations 1.04* 0.02

Best on Economy 5.89** 3.36

Proximity 0.75 0.18

ProximityX Sophistication 2.34* 0.88

Party IdentificationX

Sophistication 0.17* 0.14

Leader EvaluationsX


Best on EconomyX

Sophistication 0.16* 0.14

N(i)=3759

N(j)=896


Legend

* : 0.05

**: 0.01

***: 0.001


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Controls for the Conditional Logit; Socio-demographic and Economic Variables

Liberal Party

O.R Std. Err.

Age 1.02 0.01

Male 0.73 0.25

Catholic 1.10 0.48

Atheist 3.75 3.11


French 0.83 0.44

Married 0.74 0.26

Education 1.06 0.09



Intercept 0.07 0.11

New Democratic Party

O.R Std. Err.

Age 1.00 0.01

Male 0.95 0.31

Catholic 1.40 0.56

Atheist 0.79 0.58


French 1.27 0.62

Married 0.95 0.31

Education 0.97 0.07



Intercept 3.95 5.65

N(i)=3759

N(j)=896



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Bloc Quebecois

O.R Std. Err.

Age 1.01 0.02

Male 1.11 0.64

Catholic 1.53 1.70

Atheist 0.65 1.02


French 5.70 7.54

Married 0.76 0.48

Education 0.88 0.14



Intercept 0.82 2.35

Green Party

O.R Std. Err.

Age 1.00 0.02

Male 1.72 0.88

Catholic 0.25 0.23

Atheist 0.68 0.83


French 0.53 0.54

Married 0.80 0.40

Education 1.03 0.13



Intercept 3.26 7.84

N(i)=3759

N(j)=896



-34-

Figures

Figure 1: Impact of Proximity on the Voting Decision in function of Sophistication

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

Unsophisticated Voters Sophisticated Voters

Impact of Proximity on the Voting Decision in

function of Sophistication


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Figure 2: Impact of Party Identification on the Voting Decision in function of Sophistication

0

2

4

6

8

10

12

14


Impact of Party Identification on the Voting

Decision in function of Sophistication


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Figure 3: Impact of Party Best on the Economy on the Voting Decision in function of Sophistication

0

1

2

3

4

5

6

7


Impact of Party Best on the Economy on the

Voting Decision in function of Sophistication


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Figure 4: Impact of Leader Evaluations on the Voting Decision depending on Sophistication

0

0.2

0.4

0.6

0.8

1

1.2


Impact of Leader Evaluations on the Economy on

the Voting Decision in function of Sophistication


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Figure 5: Impact of Sophistication Heterogeneity on aggregate votes

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

CPC LPC NDP Bloc Green

Vote for the main Canadian Parties in

function of Information Level

Unsophisticated Voters

Sophisticated Voters


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Figure 6: Impact of Sophistication Heterogeneity on the seat count

0

50

100

150

200

CPC LPC NDP Bloc Green

Impact of Sophistication

Heterogeneity on the seat count

Unsophisticated Voters

Sophisticated Voters


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Appendix A

The sophistication variable is calculated as the ratio of good answers in response to the following

questions:

1. If someone working has to take care of seriously ill relatives, how many weeks of compassionate

care benefits are paid?

2. If someone had to go to court and could not afford a lawyer, where would be the BEST place to

go for help?

3. Can people with low incomes receive a GST tax credit from the Canada Revenue Agency?

4. Can people who QUIT their job because they don't enjoy it receive employment insurance

benefits?

5. Which group uses a rainbow flag as their symbol?

6. Who is the founder of WikiLeaks?

7. In which of these provinces are the tar sands located?

8. Sierra Club Canada is an organization devoted to which cause?

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