Why Do Voters Change Their Mind during an Election Campaign? An Analysis of the Determinants of Campaign Volatility at the 2014 Belgian Federal Elections ()
1. Introduction
Since the 1970s, strong empirical evidence has accumulated demonstrating that voting behaviour is changing in Western Europe. While the 1950s and 1960s had been characterised by a high degree of electoral stability in most European democracies, the last four decades have been marked by an increasing electoral volatility ( Crewe & Denver, 1985 ; Dalton, McAllister, & Wattenberg, 2000 ; Drummond, 2006 ; Mair, 2005 ; Pedersen, 1979 ). One nowadays observes larger changes in vote shares between two consecutive electoral contests, which makes elections results much more unpredictable than in the past. This rising level of variability in elections outcomes seems to contradict Lipset and Rokkan’s hypothesis of a freezing of European party systems ( Lipset & Rokkan, 1967 ). In line with the indications provided by aggregate elections statistics, individual-level survey data unambiguously show that European voters tend to switch parties between successive elections more often than they did some decades ago ( Dalton et al., 2000 ).
This article is divided into four sections. The first part reviews different theories that are often referred to in the literature to account for campaign volatility. The second section presents the data and describes the operationalization of the dependent and independent variables. The third part is dedicated to the empirical testing of our hypotheses and deals with the results of our bivariate and multivariate analyses. The final section contains some concluding remarks on the implications of our findings as well as some suggestions for further research.
2. Theoretical Framework
In their seminal study on electoral change in Western Europe between 1885 and 1985, Bartolini and Mair (1990) hypothesize that institutional incentives for tactical voting lead to higher levels of inter-election volatility. They suggest a causal mechanism linked to changes in the viability of parties, which can occur between two consecutive elections. A party does experience a change in viability when its ability (real or perceived) to win seats or to affect the process of government formation changes between two successive elections ( Bartolini & Mair, 1990 ). The explanation for why strategic incentives can stimulate vote switching is straightforward. In systems that provide no incentive for strategic voting, electors can switch from one party to another for substantive reasons, namely shifts in their own political opinions or changes in parties’ policies or platforms from one election to the next. In countries where the electoral system provides strategic incentives, voters can switch parties not only for these substantive reasons, but also for tactical reasons related to changes in the viability of parties between two successive elections. Thus, there are good reasons to expect the level of volatility to be higher in systems that provide strategic incentives. According to Bartolini and Mair, rational voters who factor tactical considerations into their vote decision should be more likely than sincere voters to change parties from one election to the next. For instance, if a strategic voter thinks that the party he/she voted for in the previous elections has become less capable of winning seats or influencing government formation, he/she will probably decide to abandon that party and choose a more viable party option. In contrast, if a sincere voter believes that the party he/she previously endorsed has become less competitive, he/she will probably remain loyal to that party regardless of the efficacy of his/her vote in terms of seat allocation or coalition formation. Admittedly, Bartolini and Mair’s argument appears to be quite convincing from a theoretical standpoint, but it must be pointed out that the results of their analysis did not provide empirical evidence in support of their hypothesis.
Hypothesis 1: The higher the perceived coalition potential of the party the respondent planned to vote for at the start of the campaign, the more stable will be the vote intention.
Even though the cognitive mobilization hypothesis has received some empirical support in the above mentioned literature, its validity is questioned by recent work. Indeed, a large number of studies conducted in the last two decades clearly demonstrate that political sophistication does not contribute to volatility, but to stability. Less educated and poorly informed citizens are often found to be more prone than sophisticated voters to switch parties between two successive elections and to alter their vote intention during a campaign ( Albright, 2009 ; Boy & Dupoirier, 1990 ; Jaffre & Chiche, 1997 ; Marthaler, 2008 ; Muxel, 2009 ; Tiberj, 2015 ; Walgrave et al., 2010 ). These recent findings largely concord with the traditional floating voter hypothesis ( Berelson et al., 1963 ; Lazarsfeld et al., 1968 ).
Hypothesis 2: Political sophistication decreases campaign volatility.
Using data from national elections studies in five countries (Australia, Canada, the Netherlands, the United Kingdom and the United States), Dalton and Weldon (2005) also observed that distrust in parties induced higher levels of electoral volatility. Similarly, in her study on the sources of voter’s volatility at the 2007 French presidential and parliamentary elections, Muxel (2009) noticed that political disaffection was one of the main catalysts of vote switching. Electors with a low degree of trust in the French political system were more prone than other voters to change parties between two successive elections ( Muxel, 2009 ). In the Belgian case as well, political dissatisfaction has been found to trigger party switching. Dassonneville (2012) showed that external political efficacy strongly correlated with both inter-election volatility and campaign volatility during the 2009 regional elections. Furthermore, trust in local and national institutions as well as external political efficacy emerged as good predictors of vote switching in the 2012 Belgian local elections ( Dassonneville, Hooghe, &Marien, 2014 ).
Rather than focussing on long-term attitudes linked to general disaffection such as trust in parties, satisfaction with democracy or external political efficacy, Soderlund (2008) examined whether or not voter’s volatility could be explained by a short-term attitude, namely retrospective evaluations of party performances. He demonstrated that the probability of vote switching was strongly influenced by retrospective evaluations of performances of the party the respondent had voted for in the previous elections. Citizens tended to remain loyal to the party they had previously voted for if they thought that it had done a good job during the inter-election period, and conversely, voters were inclined to change parties if they considered that their previously endorsed party had performed poorly ( Soderlund, 2008 ). Remarkably, the relationship between perceived party performances and vote switching remained robust even after controlling for the variables associated with general dissatisfaction with politics. According to Soderlund, this finding seems to indicate that shifts in voting behaviour should be interpreted as the products of rational judgments about past performances instead of being seen as symptoms of political frustration. This also means that disappointment about a particular party does not necessarily translate into general dissatisfaction with the political system, which contradicts Zelle’s frustrated floating voter hypothesis ( Soderlund, 2008 ). In their analysis of the determinants of party switching in 36 elections held in 22 advanced democracies, Dassonneville, Blais and Dejaeghere (2015) came to the same conclusion as that drawn by Soderlund. They pointed out that dissatisfaction with the party previously voted for significantly increased the probability of changing parties. By contrast, a general feeling of political dissatisfaction did not significantly affect the likelihood of vote switching. In sum, party switchers were not frustrated about politics in general, but they clearly were disappointed about the performances of the party they had voted for in the previous elections ( Dassonneville et al., 2015 ).
Even though retrospective evaluation of party performances is claimed to be a good predictor of electoral volatility, we cannot include this “short-term” explanatory variable in our analysis because of the absence of data thereon3. Consequently, we devote our attention to “long-term” attitudes that allow to measure voter’s level of political satisfaction. In previous work, researchers have mentioned four “long-term” attitudes influencing the probability of vote switching: affect towards the favourite party, trust in political actors and institutions, satisfaction with democracy and external political efficacy ( Dalton & Weldon, 2005 ; Dassonneville, 2012 ; Zelle, 1995 ). In the present article, we include in our model these four indicators of political satisfaction in order to test the validity of the frustrated floating voter hypothesis.
Hypothesis 3: Political satisfaction decreases campaign volatility.
Finally, voter’s ideological profile is often argued to be one of the main determinants of electoral volatility. Scholars state that ideological extremeness reduces the probability of switching from one party to another between two successive elections as well as during the campaign ( Crow, 2005 ; Dassonneville, 2012 ; Lisi, 2010 ; Van Der Meer et al., 2015 ). Voters with a radical ideological profile (i.e. those who place themselves to the far left or to the far right on the left-right axis) usually display a high degree of stability in their political opinions and tend to report strong partisan attachments. Hence, they are expected to remain loyal to the same party elections after elections ( Crow, 2005 ; Dassonneville, 2012 ; Lisi, 2010 ; Van Der Meer et al., 2015 ). By contrast, citizens with a moderate ideological profile (i.e. those who place themselves close to the ideological centre) are thought to be less committed to a particular party and much more ambivalent to the different political alternatives that are available on the electoral market. As a consequence, they should be more inclined to change parties between two consecutive electoral contests and to switch their vote intention during the weeks preceding the elections. In line with these expectations, some recent studies have shown that the level of volatility was the highest among voters with moderate ideological orientations ( Crow, 2005 ; Dassonneville, 2012 ; Lisi, 2010 ; Van Der Meer et al., 2015 ).
Hypothesis 4: Ideological extremeness decreases campaign volatility.
3. Data and Operationalization
Our study draws on data from the 2014 PartiRep Belgian Voter Survey which was conducted among a random sample of eligible voters from the two biggest regions of the country, namely Flanders and Wallonia4. This dataset contains individual-level information on respondents’ political attitudes and voting choices in the federal, regional and European elections of May 25. The PartiRep survey had a two wave panel design; it consisted of a pre-electoral wave and a post-electoral wave. The pre-electoral wave took place between March 20 and May 17 and consisted of face-to-face interviews. It resulted in a total of 2019 interviews (1018 in Wallonia and 1001 in Flanders). The post-elec- toral wave with telephone interviews was conducted between the end of May and the end of June. A total of 1528 respondents (702 in Wallonia and 826 in Flanders) participated in this second wave.
Our dependent variable, campaign volatility, can only be operationalized by means of panel survey data that allow to compare respondent’s vote intention at the start of the campaign with his/her actual voting choice on Election Day. The panel design of the PartiRep survey enables us to determine whether or not respondents changed their mind during the campaign. In the pre-electoral interview, they were asked to indicate which party they intended to vote for at the federal elections, and in the post-electoral interview, they were asked to mention which party they had eventually chosen on Election Day. By comparing the vote intention reported in the pre-electoral wave with the actual electoral behaviour reported in the post-electoral wave, we can distinguish between two groups of respondents: stable voters and campaign switchers. Stable voters are those respondents who reported a vote intention for a given party at the beginning of the campaign and who eventually cast a ballot for that party in the federal elections. Campaign switchers are those who expressed a vote intention in favour of a given party at the launch of the campaign but who then cast a vote for another party at the federal elections. The variable “campaign volatility” is dichotomous; it takes the value 1 for campaign switchers and the value 0 for stable voters.
Table 1 indicates that about a third (32.8%) of the respondents reported having changed their vote intention during the months preceding the 2014 federal elections. Interestingly, this level of campaign volatility turns out to have been relatively high when compared to figures observed in other Western countries such as Canada, Germany, Sweden, Switzerland or the United States ( Blais, 2004 ; Granberg & Holmberg, 1991 ; Lachat, 2007 ).
The present study aims to identify the factors that can account for stability and change of vote intentions during the 2014 Belgian federal election campaign. As explained above (see section “Theoretical framework”), our hypotheses focus on four potential predictors of campaign volatility: strategic considerations, political sophistication, political satisfaction and ideological extremeness. Hypothesis 1 posits that a voter can decide to switch his/her vote intention due to tactical considerations related to his/her perception about the coalition potential of the party he/she intended to vote for at the launch of the campaign. In order to test this hypothesis, we include in our model the variable “Perceived coalition potential of the party the respondent planned to vote for in the pre-electoral wave” as an independent variable. In the pre-electoral interview, respondents were asked to evaluate how much of a chance the party they intended to vote for had of joining the federal governmental coalition after the elections. They as-
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Table 1. Proportion of campaign switchers in the 2014 Belgian federal elections.
sessed this coalition potential on an 11-point scale where 0 meant “The party has no chance of entering the governmental coalition” and 10 meant “The party has a very good chance of entering the governmental coalition”.
The second explanatory factor, political sophistication, is a broad and complex concept which encompasses two distinct dimensions: cognitive skills and interest in politics ( Lachat, 2007 ). Hence, political sophistication can be operationalized by means of a wide range of indicators such as political knowledge, internal political efficacy, political interest, the degree of campaign attention, media exposure or political participation ( Dassonneville, 2012 ; Lachat, 2007 ). In our analysis, we make use of three distinct indicators for measuring voter’s level of sophistication, namely political knowledge, political interest and campaign attention. We construct an index of political knowledge that corresponds to the respondent’ score on five political knowledge questions asked in the PartiRep survey. This score takes values ranging from 0 (“no political knowledge at all”) to 5 (“high political knowledge”). The variable “political interest” consists of the self-reported level of interest in politics on an 11-point scale where 0 means “no interest at all” and 10 means “Very much interest”. In order to measure the degree of campaign attention, respondents were asked to indicate how often they had paid attention to political information in the media (newspapers, TV and radio) during the campaign. Respondents gave an answer on a 4-point scale where 0 means “Never”, 1 “One or several time(s) a month”, 2 “One or several time(s) a week” and 3 “Every day”.
The third explanatory factor, political satisfaction, also encompasses many distinct dimensions and, as a result, it can be operationalized by means of a large number of indicators ( Soderlund, 2008 ; Zelle, 1995 ). Our model incorporates four independent variables designed to assess respondent’s level of political satisfaction: political trust, affect towards the preferred party, satisfaction with democracy and external political efficacy. Political trust is measured through the average score for self-reported degree of trust in a series of institutions and political actors: the justice, the police, media, political parties, the regional government, the regional parliament, the federal government, the federal parliament, social movements, politicians, and the European Union. For each of these 11 institutions, respondents gave a value on an 11-point scale where 0 means “No trust at all” and 10 means “Complete trust”. In order to assess affect directed to the favourite party, we look at respondent’ self-reported degree of affection for each political party on an 11-point sympathy scale. The highest sympathy score given by the respondent to any one out of all Belgian parties represents his/her level of affection for his/her preferred party. Satisfaction with democracy consists of respondent’ self-reported degree of satisfaction with the Belgian democratic process on a 4-point scale where 0 means “not satisfied at all” and 3 means “highly satisfied”. The variable “external political efficacy” is constructed by means of the average score on 14 items that deal with the feeling of external political efficacy (see these items in Appendix). This average score may take values ranging from 0 (“low political efficacy”) to 4 (“high political efficacy”).
The last independent variable, “ideological extremeness”, is constructed on the basis of the respondent’s left-right self-placement on an 11-point scale where 0 means “the left” and 10 means “the right”. For each respondent, we calculated the distance between his/her self-reported position on the left-right axis and the ideological centre (i.e. the position 5 on that axis). Thus, the level of ideological extremeness is ranging from 0 (when the position 5 was reported) to 5 (when the position 0 or 10 was reported).
In addition to these socio-demographic characteristics, we also control for party identification, which is argued to form a barrier against voter’s volatility. In their seminal book The American Voter, Campbell et al. (1960) stressed the stabilizing effect of partisanship on electoral behaviour by showing that voters who identified with a particular party almost invariably remained loyal to that party election after election. By contrast, independents were found to be considerably more inclined to switch parties from one election to another ( Campbell et al., 1960 ). In line with these early findings, a large number of recent studies clearly demonstrate that voters who report no partisan attachment are much more volatile than party identifiers (e.g. Blumenstiel & Plischke, 2015 ; Crow, 2005 ; Dalton, 2013 ; Dassonneville & Dejaeghere, 2014 ; Granberg & Holmberg, 1991 ; Lachat, 2007 ; Lisi, 2010 ; Soderlund, 2008 ).
4. Results
To start with, we perform some bivariate analyses. First, we try to determine whether campaign volatility is triggered by strategic considerations. We do so by comparing how stable voters and campaign switchers evaluated the coalition potential of the party for which they expressed a vote intention at the beginning of the campaign. As can be read from Table 2, the results of this comparison lend support for hypothesis 1. At the start of the campaign, stable voters thought that the party they intended to support had a relatively good chance of joining the federal governmental coalition after the elections (mean perceived coalition potential = 7.06 out of 10). Campaign switchers, on the other hand, considered that the party they planned to vote for at the launch of the campaign displayed a lower chance of gaining office (mean perceived coalition potential = 5.48 out of 10). The difference between stable voters and switchers in terms of perceived coalition potential is statistically significant.
Second, we investigate the relationship between political sophistication and campaign volatility, by looking at differences between stable voters and switchers with respect to their levels of political knowledge, political interest and campaign attention. As can be seen in Table 3, campaign switchers are less interested in politics, less attentive to political information and less knowledgeable about the political system, which is in line with our expectations. For each of these three variables, the difference between the two groups of respondents reaches the conventional level of statistical significance. Thus, hypothesis 2 can be totally confirmed.
Third, we examine whether or not there is a link between political disaffection and campaign volatility. We make use of four different indicators in order to compare the average level of political satisfaction of switchers with that of stable voters. The results of this comparison (reported in Table 4) give credit to hypothesis 3, as they clearly show that compared to stable voters, campaign switchers exhibit a lower level of satis-
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Table 2. Strategic considerations and campaign volatility in the 2014 Belgian federal elections.
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Table 3. Political sophistication and campaign volatility in the 2014 Belgian federal elections.
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Table 4. Political satisfaction and campaign volatility in the 2014 Belgian federal elections.
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Table 5. Ideological extremeness and campaign volatility in the 2014 Belgian federal elections.
faction with democracy, a lower degree of trust in institutions and political actors, a lower level of external political efficacy and a lower degree of affection for their favourite party. These differences between stable voters and switchers are statistically significant for each of the four indicators.
Finally, we attempt to determine whether ideological extremeness significantly correlates with campaign volatility. To this end, we compare the average degree of ideological extremeness of switchers with that of stable voters (see Table 5). Results seem to confirm our hypothesis 4, since the average ideological profile of switchers proves to be more moderate than that of stable voters. The difference between the two groups of respondents in terms of ideological extremeness achieves statistical significance.
After having conducted these preliminary bivariate analyses, we carry out a multivariate analysis; we regress campaign volatility on all the independent and control variables. Given that the dependent variable is dichotomous, we perform a binary logistic regression in order to test our hypotheses. The results of our multivariate analysis are displayed in Table 6. At first glance, it appears that most coefficients are in the expected direction.
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Table 6. The determinants of campaign volatility in the 2014 Belgian federal elections (binary logistic regression).
Coefficients are unstandardized regression coefficients.* p < 0.05; **p < 0.01; ***p < 0.001.
her vote preference and to shift to another party that seems to have a better chance of gaining office. Since log odds coefficients of a binary logistic regression are quite hard to interpret, Figure 1 graphically presents the estimated effect of the perceived coalition potential of the party the respondent planned to vote for on the probability of campaign volatility. The graph shows that a high perceived coalition potential decreases the likelihood of changing one’s vote intention in the last weeks before the election.
Similarly, the hypothesis that shifts in vote intentions can be attributed to political disaffection (H3) is partially confirmed, since two out of the four indicators of political
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Note: Predictions with all covariates set at their sample means. Predictions are based on estimates presented in Table 6.
Figure 1. Predicted probability of campaign volatility by perceived coalition potential of the party the respondent planned to vote for at the start of the campaign.
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Note: Predictions with all covariates set at their sample means. Predictions are based on estimates presented in Table 6.
Figure 2. Predicted probability of campaign volatility by level of political interest.
As evident from Table 6, regression results lend no support for the hypothesis that voters with a radical ideological profile are less likely than moderate voters to change their mind in the last weeks before Election Day (H4). Admittedly, the effect of ideological extremeness on campaign volatility is in the expected negative direction, but it is far from achieving statistical significance.
Regarding the control variables, results indicate that party identification significantly reduces the probability of switching one’s vote intention during the campaign. Voters who report no partisan attachment are much more inclined than party identifiers to change their mind in the weeks preceding the elections. Moreover, one may observe that two socio-demographic characteristics, gender and age, significantly influence
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Note: Predictions with all covariates set at their sample means. Predictions are based on estimates presented in Table 6.
Figure 3. Predicted probability of campaign volatility by level of external political efficacy.
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Note: Predictions with all covariates set at their sample means. Predictions are based on estimates presented in Table 6.
Figure 4. Predicted probability of campaign volatility by degree of affection for the favourite party.
5. Conclusion
Appendix
Coding details of the independent variables
Gender: Male = 0; female = 1
Age: In years calculated by distracting the reported year of birth from 2014 (the year that survey was conducted in).
Level of education: Respondent’s level of education is a categorical variable coded as follows. No degree or elementary school degree = 0; unfinished high school degree = 1; finished high school degree = 2; higher education or university degree = 3.
Party identification: Party id is a dummy variable; it takes the value 1 for respondents who feel close to a particular party and the value 0 for other voters.
Perceived coalition potential of the party the respondent planned to vote for in wave 1: In the pre-electoral interview conducted at the start of the campaign, respondents were asked to evaluate how much of a chance the party they planned to vote for had of joining the federal government after the elections. They gave a value on an 11-point scale where 0 meant “No chance of entering the federal coalition” and 10 meant “A very good chance of entering the federal coalition”.
Political interest: Self-reported level of interest in politics on an 11-point scale where 0 means “no interest at all” and 10 means “very much interest”.
Political knowledge: Respondent’ score on five knowledge questions asked in the PartiRep survey. Scores were thus ranging from 0 (“no knowledge”) to 5 (“high knowledge”).
Campaign attention: The survey questionnaire allows us to assess the level of campaign attention, as it contains the following question: How often did you pay attention to political information in the media (newspapers, radio and TV) during the election campaign? Four options were offered to respondents: never (coded 1); one or several time(s) a month (coded 1); one or several time(s) a week (coded 2); every day (coded 3).
Ideological extremeness: This variable is constructed on the basis of the respondent’s left-right self-placement on an 11-point scale where 0 means “the left” and 10 means “the right”. For each respondent, we calculated the distance between his/her self-reported position on the left-right continuum and the ideological centre (i.e. the value 5 on that continuum). Hence, the variable “ideological extremeness” takes values ranging from 0 (when 5 was reported) to 5 (when 0 or 10 was reported).
Political trust: This variable consists of the respondent’s average score for self-reported level of trust in a series of political actors and institutions: the justice, the police, media, political parties, the regional government, the regional parliament, the federal government, the federal parliament, social movements, politicians, and the European Union. For each institution, respondents gave a score on an 11-point scale where 0 meant “No trust at all” and 10 meant “Complete trust”.
Affection for the favourite party: Respondents were asked to indicate their degree of affection for each political party on an 11-point sympathy scale. The highest score given by a respondent to any one out of all parties represents his/her degree of affection for his/her favourite party.
Satisfaction with democracy: Self-reported level of satisfaction with the democratic process on a 4-point scale with values ranging from 0 (“not satisfied at all”) to 3 (“highly satisfied”).
External political efficacy: This variable consists of the respondent’s average score on 14 items dealing with external political efficacy.
・ During the election campaign, parties make many promises, but eventually, nothing happens anyway.
・ An average citizen may have an impact on politics and what the government is doing.
・ Voting makes no sense; parties do what they want anyway.
・ Political parties offer clear and differentiated electoral platforms.
・ In my country, politicians are capable of solving problems.
・ International politics is capable of solving problems.
・ If a sufficient number of people like me give their opinion, politicians will take these opinions into account.
・ Elections cannot influence policies anymore.
・ Influencing politicians makes no sense, since they cannot do something.
・ MPs’ opinions do reflect what voters think.
・ Politicians are ready to lie to us, when this can serve their own interests.
・ If a politician acts in accordance with his/her values and his/her ideas, his/her political career has little chance of being successful.
・ I believe that politicians really care about people’s well-being.
・ Virtually all politicians are ready to forget the promises they have made, if this allows them to get more power.
For each of these 14 statements, respondents gave an answer on a 5-point scale where 0meant “totally agree” and 4 meant “totally disagree”. These scores were converted to so that all low scores meant “low external political efficacy” and all high scores meant “high external political efficacy”. We then calculated the average score taking values ranging from 0 (“low external political efficacy”) to 4 (“high external political efficacy”).
1In this section, we review not only specific studies on campaign switching, but also the rich literature on inter-election switching. Although there is, at first glance, no logical connexion between the two types of volatility, some scholars have noticed that the mechanisms accounting for campaign switching did not differ fundamentally from the mechanisms underlying inter-election switching (e.g. Dassonneville, 2012 ; Lachat, 2007 ; Van Der Meer et al., 2015 ). Hence, the good predictors of inter-election volatility, which have been identified in previous work, can be regarded as potential predictors of campaign volatility.
2As explained earlier, two types of tactical voting can be distinguished: seat-maximizing and government- maximizing voting. In our analysis, we will not examine seat-maximizing voting. We will focus on government-maximizing voting and its effect on campaign volatility.
3In the Parti Rep survey questionnaire, respondents were not asked to evaluate the past performances of the party they had voted for in the previous elections.
4There are three regions in Belgium: Flanders, Wallonia and Brussels. In the present article, Brussels is left out of our analysis, since Brussels citizens were not interviewed in the 2014 PartiRep Belgian Voter Survey. This panel survey was only conducted in the two other regions.
5For the coding details of the control variables, see Appendix.