Abstract
Despite the growing literature on polarization, students of comparative politics have not yet been able to reach much assured understanding of how party polarization influences voter turnout in multiparty settings, which often put on offer both centrist, and divergent mainstream and niche party policies. I evaluate how politically sophisticated and unsophisticated citizens with different ideological preferences respond to high and increasing party polarization by employing individual- and party system-level data from 17 European multiparty democracies. I hypothesize that high levels of actual and perceived party polarization increase voter turnout, and policy seeking, sophisticated citizens are more likely to turn out when polarization in party policy offerings in the short run increases their utility from voting. The empirical analyses show that high party polarization increases both politically sophisticated and unsophisticated citizens’ propensities to turn out. However, such positive effect for the most part comes from the between- and within-party systems differences in actual party polarization, rather than how individual citizens perceive that. The implications of these findings with respect to strategic position taking incentives of political parties and the effects of the knowledge gap between sophisticated and unsophisticated citizens on political participation and democratic representation are discussed in the concluding section.
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Notes
Some post-election surveys do not provide information about political information (Slovenia 2008), union membership (Spain 2008), income (Latvia 2010), and vote shares of parties at the district level (Romania 2009).
France (2007) is not included in the sample due to the semi-presidential system and two-round elections. For the effects of electoral rules on political polarization, see Ezrow (2008), Dow (2011), Best and Dow (2015), McDonald and Moral (2015). Polish election in 2005 is also excluded due to the second round of the presidential election that took place shortly before the parliamentary election, which is likely to produce a coattail effect (Cox 1997; Clark and Golder 2006), thus to influence respondents’ polarization perceptions.
Post-election surveys examined in Models 1 and 2 are: Austria (2008), Croatia (2007), Czech Republic (2006, 2010), Denmark (2007), Estonia (2010), Finland (2007, 2011), Germany (2005, 2009), Greece (2009), Iceland (2007, 2009), Ireland (2007), Netherlands (2006, 2010), Norway (2005, 2009), Poland (2007), Portugal (2009), Slovakia (2010), Sweden (2006), Switzerland (2007).
The sample employed in Model 3 consists of the latter post-election surveys in Czech Republic, Denmark, Finland, Germany, Iceland, Ireland, Netherlands, Norway, Portugal, Sweden, and Switzerland.
CSES data provide validated voting records for only three post-election surveys in Norway (2005, 2009) and Sweden (2006). In such instances, the dependent variable is accordingly recoded, and the mean turnout rates in our data are closer to the observed turnout percentages. Overreporting of turnout with a sense of citizen duty may be a possible explanation for such observed differences between turnout rates (Gerber et al. 2008). Another possibility is that listwise deletion of observations with missing data might lead to higher observed turnout rates in our sample. Additional sensitivity checks for all models in Table 1 do not show a systematic relationship between perceived and actual party polarization and overreporting of turnout: Although predicted probabilities of turnout are expectedly lower to a small extent, the coefficients estimates do not change significantly when self-reported turnout data are employed.
Descriptive statistics in Table 3 in Appendix show that 23 post-election surveys in our sample have a mean actual party polarization of 3.59 with a standard deviation of 0.61.
While some European countries have constantly high or low party polarization, others reveal increasing or decreasing trends between consecutive elections. The mean change in actual party polarization is −0.11. The most substantial decrease in actual party polarization is about 0.8 points in Poland between 2005 and 2007, while party polarization reveals a positive trend between the consecutive elections in Denmark, Germany, Iceland, and Netherlands. Table 4 in Appendix shows the trends in all post-election surveys examined in this article.
An example might better illustrate the coding of these three measures of party polarization. For the German post-election surveys in 2005 and 2009, the respondents were asked to place six major parties on the traditional left-right continuum: Christian Democratic Union (6.4), Social Democratic Party (3.7), Free Democratic Party (5.8), Left Party (1.1), Alliance ’90/Greens (3.3), and Christian Social Union (7). Using the mean placements in parentheses, I computed the distance between the party groups to the left (i.e, Left, Alliance 90 and SPD), and to the right (i.e., FDP, CDU and CSU) of the party system center (in turn 2.7 and 6.4) to create the “actual party polarization” variable (3.7). The “change in actual party polarization” between 2009 and 2005 (Mean placements in 2005 were respectively 6.1, 3.6, 5.2, 1.2, 3.3, 6.5) is thus a substantial increase by 0.5 point (from 3.2 to 3.7). To reiterate, the measures entitled “perceived party polarization” in Model 1 and “perceived party polarization (difference)” in Models 2 and 3 take individual respondents placements of parties into account. For instance, if a respondent in the 2009 survey placed those parties respectively at 7, 3, 6, 1, 2 and 8, his perceived polarization variable score would be 5. I then calculated the difference between perceived and actual party polarization (1.3) and divided it by the standard deviation of this variable for the German post-election survey in 2009 (1.55) for standardization. Hence, the hypothetical respondent perceives party polarization as .8 standard deviations higher than the actual party polarization and has a “perceived party polarization (difference)” score of 0.8.
For a comparison of the measure of polarization employed here with other measures of polarization in previous literature and the sensitivity checks taking those measures as the primary party system-level independent variable, see Appendices C and E.
Some commonly employed measures in previous literature approximate the extremity, dispersion, or diversity of party policy offerings, rather than their polarization. See Best and Dow (2015) and McDonald and Moral (2015) for useful discussions about those interrelated but distinct concepts often used interchangeably in previous literature.
Factual knowledge items in the CSES surveys are usually not very cognitively demanding such as those about the length of electoral terms and the names of prominent elected officials. In surveys with lower mean scores for the unstandardized index, respondents are asked more demanding questions such as the relative share of public expenses across distinct policy domains (e.g., Denmark (2007), where the mean is −.4) or a series of knowledge items in a row (e.g., Norway (2005), where the mean is −1.3). However, survey means of the unstandardized variable can be as high as 1.3—e.g., Poland (2007).
Models A5 and A6 in Table 5 in Appendix relax this assumption and introduce an interaction term with education as another proxy for political sophistication.
Some citizens may rationalize ideological and policy positions of candidates (Campbell et al. 1960; Page and Brody 1972; Abramowitz 1978; Markus and Converse 1979). To my knowledge, there is no study to date with the exception of Jacoby and his colleagues’ (2010) that examines whether such perceptual bias is a function of political knowledge. Although the authors do not find a systematic difference between politically informed and uninformed respondents, because such pattern would constitute an important problem for the empirical analyses in this article, introducing an interaction term between political information and perceived polarization, rather than solely relying on compression effects in the logistic regression, is preferred.
In addition to political knowledge, the literature on projection bias suggests that citizens’ partisan attachments and ideological extremity condition their perceptions about parties and candidates’ policy or ideological stands. The correlations between perceived polarization (difference) and ideological extremity and strong partisan attachment are, however, 0.12 and 0.27 in turn.
Replication data and code are available online at https://dataverse.harvard.edu/dataverse/mertmoral.
Model 1 in Table 1, which takes perceived party polarization, rather than its difference from the actual party polarization, as the primary independent variable is reported for comparison purposes. Model 1 also provides empirical evidence supporting our major theoretical expectation regarding the positive effect of perceived party polarization on voter turnout in multiparty settings.
The marginal effect of perceived polarization is calculated by setting perceived polarization first to 0 and then to 1 to compute the (first) difference in predicted probabilities. 10,000 estimates are drawn from a multivariate normal distribution with the means of estimated coefficients and variances specified by the variance-covariance matrix from Model 2.
Four sets of robustness checks are presented in Table 5 in Appendix. Since comparative studies on political polarization suggest that electoral rules might affect the diversity and polarization in party policy offerings (Ezrow 2008; Dow 2011; McDonald and Moral 2015), two mixed party systems - Germany and Greece- were dropped from the samples employed in Models A1 and A2. The respondents who failed to place less than three of four largest parties, and those who misplaced left-wing parties to the right of right-wing parties are included in the samples employed in Models A3 and A4. In Models A5 and A6, perceived polarization is interacted with education as another proxy for political sophistication. Lastly, multilevel mixed-effects logistic regressions in Models A7 and A8 drop election fixed effects from model equations, and introduce random intercepts for each post-election survey and random coefficients for the actual party polarization and change in actual party polarization variables. Our conclusions that high perceived polarization and that high and increasing actual party polarization increase voter turnout are robust to such changes. In addition, four sensitivity checks reported in Table 6 in Appendix replace the measure of polarization employed in the empirical analyses in this article with other measures in previous literature—i.e., individual-level perceived polarization and aggregate-level party polarization in Crepaz (1990), weighted party system extremism in Dow (2011), and the measures of party polarization in Lachat (2008) and in Esteban and Ray (1994). Changing how we approximate party polarization does not alter the conclusions.
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Acknowledgements
Earlier versions of this paper were presented at the 111th Annual Meeting of the American Political Science Association and at the Comparative-American Politics Workshop in Binghamton University. I thank to the participants, Michael D. McDonald, Olga V. Shvetsova, Robin E. Best, three anonymous reviewers, and the Editor for helpful suggestions. Any remaining errors are, of course, my own.
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Moral, M. The Bipolar Voter: On the Effects of Actual and Perceived Party Polarization on Voter Turnout in European Multiparty Democracies. Polit Behav 39, 935–965 (2017). https://doi.org/10.1007/s11109-016-9386-0
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DOI: https://doi.org/10.1007/s11109-016-9386-0