1

Political communication on climate change in a comparative

perspective

Stefan Linde

Luleå University of Technology

Paper presented at ECPR General Conference in Montreal 2015

Correspondence with author: stefan.linde@ltu.se

Draft - please do not quote or cite without permission

1. Introduction

Climate change is now, perhaps more than ever, a highly politicized issue. Despite growing

scientific consensus (see e.g. IPCC 2013) climate change is in many countries a highly

partisan issue with representatives of different parties taking strongly different positions (e.g.

Fielding et al. 2012, McCright 2011). The politicization is further evident in an international

perspective where efforts to agree on comprehensive binding climate agreements have been

both painful and largely unsuccessful. The political nature of climate change has also been

found to extend beyond political elites to also affect individual attitudes. Through

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communications from political parties the partisan nature of climate change has been found to

affect public perceptions of climate science (McCright and Dunlap 2011), public concern for

climate change (Guber 2012, Tranter 2013), as well as public attitudes on climate policy

(Unsworth and Fielding 2014). As such, political communication fundamentally affect the

ways in which individuals form opinions about climate change.

While previous research has indicated the importance of political communication to public

climate change attitudes, the possibility to draw generalizable conclusions from these findings

is limited. First, previous research has failed to consider if, and how, the effects of political

communication vary in a cross-national perspective. From one perspective, cross-national

variations in party-system characteristics could e.g. be expected to influence the degree of

political polarization in a system and as such the importance of political cues to public attitude

formation (Hetherington 2001). From another perspective, the ‘international’ character of the

climate change debate (e.g. global news agencies) might though also cause national political

elites to lose influence over policy framing (Shehata and Hopmann 2012), potentially

reducing their influence on public attitudes. Presently, understanding of the effects of cross-

national variation is limited by a lack of country comparative studies. Second, previous

studies are also limited in the extent to which it considers how variations in individual

characteristics affect individual receptiveness to political communication. The influence of

political communication on public attitudes is e.g. commonly considered to be moderated by

factors such as political awareness (Classen and Highton 2009) and party attachment (Ray

2001). To more fully account for the impact of political communication on public climate

attitudes, a more nuanced picture of individual characteristics is needed.

This article aims to improve upon previous research by studying the relationship between

political communication and public climate policy attitudes in a comparative perspective.

Overall the article will investigate three main topics: 1) how political communication affects

public attitudes towards climate mitigation policies, 2) how this relationship is impacted by

characteristics of the party system and the parties within it, and 3) how the effect of political

communication varies between countries and individuals. By taking a comparative approach

the study can account for variations in party system characteristics and political culture.

Furthermore, to give a more nuanced picture of the effects of political polarization the study

also include measures of party unity, political awareness, and party attachment.

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After this introductory section the article continues as follows: First, I will give an

introduction to the study of political communication and public policy attitudes. This part is

ended by the formulation of a number of hypotheses that have guided the study. Second, the

methodological section describes the data collection process and the operationalization of the

variables. Next, the results section presents the results of an multiple regression analysis

where the dependent variable, Policy support, is regressed upon the main independent

variable, Party policy stance, and a number of interaction terms. Finally, the article is ended

by a discussion.

2. Theory

The aim of this article is to create a deeper understanding of how political communication

affects public attitudes towards climate mitigation policies, and of how this effect varies in-

between countries and individuals. Political communication and public opinion research

suggests that the impact of political communication will vary with a number of characteristics

associated with the party system and the parties within it. It has for example in several cases

been shown how the possibility for parties to cue their constituencies will be impacted by the

degree of dissent within parties in the system. Political polarization is e.g. in general

considered to impact the linkage between partisan cues and public attitudes by simplifying the

decision environment and thereby facilitating easier party-policy linkages. Besides system

characteristics, a number of individual level variables, notably political awareness and party

attachment, will also influence individual susceptibility to political communication. The

concept of political communication will together with each of the moderating factors be

elaborated further below.

Political communication

To get information about the surrounding world individuals in modern day societies are

largely reliant on anonymous sources (Converse 1964, Feldman 1984). These sources, the

political elite, consist of e.g. journalists, politicians, bureaucrats, and scientists. Information

retrieved from these sources is though rarely neutral or objective, but is rather heavily colored

by selection, stereotyping, and interpretation. The information obtained from these sources

has as a result been found to significantly impact the formation of public attitudes and beliefs

(Zaller 1992). For example, by the use of ideological cues and frames political parties can

fundamentally change how individuals perceive different issues. As such, information

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obtained from elite sources provides individuals not only with information about the

surrounding world, but also with interpretations of this information. What sources individuals

turn to is therefore of vital importance for what attitudes and beliefs the form about the world

(Ibid.).

One country in which the politicization of climate change been especially prominent is the

U.S. From what once was a highly consensual issue, or non-issue, in U.S. politics, climate

change has over the last couple of decades, like most other policy areas, become an all more

politicized topic (McCright 2011). The increasing divide between Republican and Democrat

elites has in turn generated an interest in studying how partisan communication affect public

attitude formation. Several studies have found that the more Republicans and Democrats have

grown apart on the issue, the more important has partisanship become to individual attitude

formation (Dunlap and McCright 2008). The increased importance of partisanship has for

example resulted in Democrat voters being more likely to hold views consistent with climate

science (McCright and Dunlap 2011), and to be more concerned about climate change

compared to their Conservative counterparts (Guber 2012). Much of the same effects have

also been found in Australian where, similar to the U.S., there is a clear divide on climate

change between the main political parties (Fielding et al. 2012). For example, Tranter (2013)

found that supporters of the liberal Coalition parties were much less likely to express concern

for climate change than those belonging to Labor or the Greens. Similarly, Unsworth and

Fielding (2014) found that party identity, if made salient, was an important predictor to public

support for climate change policy. Together, these studies indicate the importance of political

communication to public attitude formation.

Party system and party characteristics

The impact of political communication is not the same for all contexts and for all individuals,

but is conditional on individual, party, and party system characteristics. First, on party system

level, the degree of polarization among political parties has been found to impact the

importance of political communication for public attitude formation. A polarized political

climate is characterized by “high levels of ideological distance between parties and high

levels of homogeneity within parties” (Druckman, Peterson and Slothuus 2013:57). Political

polarization theory asserts that as the political parties in a system grow further apart on an

issue their respective ideological cues will become more distinct and thus more easily

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recognizable by their constituents. As a result, partisan voters will follow their preferred

parties’ movement, resulting in a polarizing effect. Conversely, when parties take on more

similar positions on an issue, i.e. increasing consensus, it will be more difficult for voters to

clearly distinguish between them, which in turn will lead to a mainstreaming effect among the

public (Zaller 1992). On an aggregate level, increased polarization on a policy issue means an

increase in ‘negative’ cues and therefore, under the assumption that these cues impact public

opinion, a decrease in the aggregate level of public support for that issue (Gabel and Scheve

2007).

Second, the impact of political communication is also dependent on the characteristics of the

political parties in a system. One such issue is the degree of unity within a party on an issue.

The failure of a party to agree internally on an issue will reduce its ability to effectively

communicate with its voters. Disagreement among party elites will increase the number of

contradictory messages sent to the public by different party leaders. Such an inconsistent

communication will in turn ‘muddle’ partisan cues, making it harder to effectively influence

public opinion. Internal dissent might also reduce the communicative capacity of a party by

reducing its willingness to openly discuss an issue in public (Ray 2003).

Individual characteristics

The impact of political communication will also vary with a number of individual

characteristics. First of these is political awareness, which is a measure of an individual’s

degree of interest for and attentiveness to politics. Individuals with a high degree of political

awareness will be more receptive to changes in the political environment, e.g. changing party

positions or increasing polarization, and will therefore be the able to quickly respond to these

changes. These individuals are though not gullible, but are, as a result a good understanding

of politics, well equipped to resist cues inconsistent with their own beliefs. Contrary,

individuals at the low end of the awareness spectrum are simultaneously inattentive to politics

and highly susceptible to persuasion (Zaller 1990). Political awareness has also been shown to

moderate the effect of political polarization. A number of studies have found how only the

most politically aware will pick up on increasing polarization while the less aware are unable

to identify any change. Thus, while increasing polarization might cause an increasing partisan

divide among the highly aware no such change will be found in other segments of the

population (Classen and Highton 2009).

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A second individual level characteristic is the degree of party attachment. Individuals with a

strong attachment to a party will be more prone to listen to communications by party leaders

and will also be more open to incorporating partisan cues. Individuals with a weaker party

attachment will instead be more open to alternative sources of communication for information

retrieval (Ray 2003). Individuals with a less strong party attachment will as such also be less

impacted by increasing polarization among the political parties. Instead, the effect of

polarization will be strongest among the most partisan voters (Ibid.).

Hypotheses

Given the theoretical presentation, a few hypotheses concerning the relationship between

political communication and public policy attitudes can be outlined. First, political

communication is expected to have a direct impact on public policy attitudes by biasing

individuals’ attitudes in the direction of their preferred party. For example, individuals

belonging to a Green party (i.e. positive stance on climate change) are expected to be more

supportive of climate mitigation policies than individuals belonging to parties with a more

negative stance.

H1: Partisan communication will bias individual policy attitudes either in a positive or

negative direction

Second, the impact of political communication is expected to be moderated by the degree of

political polarization in a system. With increasing degrees of polarization it should be easier

for individuals to differentiate between different parties. Therefore, when polarization

increases, partisan cues should become more important to public attitudes towards climate

mitigation policies.

H2. Polarization positively moderates the relationship between political communication and

public policy attitudes

Third, the effect of polarization should also vary with the degree of party unity. With

increasing dissent between political parties individuals voters will receive a greater number of

negative policy messages and will therefore, overall, be less inclined to support any policy.

The more united a party is internally, the more able will it be to cue its voters. Therefore, the

effects of party cues will increase as internal party unity increases.

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H3. Party unity positively moderates the relationship between political communication and

public policy attitudes

Fourth, the impact of political communication on public policy attitudes is expected to vary

with two individual level characteristics. The more politically aware individuals are the better

equipped they will be to identify difference between political parties. As such, political

awareness should increase the importance of party cues for individual policy attitudes.

Similarly, the impact of political communication should also increase with increasing levels

of party attachment. As individuals get more attached to their party, they will receive more

partisan cues and will also be more willing to internalize these cues. Party attachment should

therefore increase the importance of party positions to individual policy attitudes.

H4. Political awareness and party attachment will both, independently, positively moderates

the relationship between political communication and public policy attitudes

The next section gives an overview of the design of the study, the data collection process and

the operationalization of the variables.

3. Design and data

The aim of this study is to investigate the linkages between party communications and public

attitudes towards climate mitigation policies, as well as studying how this relationship varies

as a result of contextual and individual level characteristics. To do this, a cross-national study

combining the results of an expert survey and a public survey was designed. The surveys were

administered in four countries, Sweden, Norway, New Zealand, and Australia, over the course

of 2014-2015. By a most-different design the countries were selected on a basis of their

variation in political culture and dependence on natural resource extraction. For example,

while the political culture in Sweden and Norway share many similarities, Norway is

economically more dependent on natural resource extraction (oil) compared to Sweden. These

characteristics are both separately, and in combination, expected to affect how climate change

is discussed among political elites and the public in each country.

The expert survey was used to gauge measures related to the parties, such as party stance on

climate mitigation, internal party dissent, and the degree of polarization within the party

system. In the survey, the experts were asked to evaluate all parties in their own country (with

a seat in the national (federal) parliament) on a number of dimensions. The survey was sent to

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experts on political parties, national politics and climate change politics in the four countries.

About 80-100 surveys were sent to each country and in total about 20 respondents for

Sweden, Norway and Australia, while only 10 respondents for New Zealand. While the

response rate is not extraordinarily good, the number of respondents supersedes the

recommended amount of five respondents per country (Ray 1999). Since the quality of the

answers, and not their representativeness, is what is important to the study, the modest

response rate is not a major concern. To control the internal consistency (reliability) of the

experts’ ratings each party measure was controlled for influential outliers. For measures

including outliers the mean value was recalculated without the outliers and the two means was

compared. Only one measure, the degree of dissent within the Australian Country Liberal

party, was found to be significantly influenced by the existence of outliers (a change in of 0,5

or more was considered as significant). The measure was though kept, but could potentially

impact the interpretation of the results.

All individual level variables, such as policy support, party preferences, and political

awareness, were collected using the public survey. The survey was the same in all countries

(with exception of national adaptation to question wordings), and was administered roughly at

the same time in all countries (early spring 2015). The Swedish survey was an online survey

administered by the opinion laboratory, LORE, at the University of Gothenburg. The survey

was part of an ongoing panel, and some of the background variables had therefore been

collected at a previous instance. The surveys sent to Australia, New Zealand, and Norway

where administered by two private companies, CINT and SSI, specializing in public

surveying. Like the Swedish survey, these surveys were sent electronically. The surveys were

translated from Swedish by two separate translators for each language (i.e. Norwegian and

English), and the translations were then compared for any inconsistencies. The measurement

of the variables is further elaborated below.

The dependent variable, policy support, was measure using an aggregate index of three policy

variables. Using a seven-point scale (-3=completely against, 0=neither against nor for,

3=completely for), the respondents were asked to report their support or opposition for a tax

on CO2-emissions from individuals, from industry, or from energy producing companies. The

index showed a high degree of internal consistency (α=.944).

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The main independent variable, partisan communication, is operationalized as party stance on

climate change. This was measured by asking the experts to indicate the “party leadership’s

overall position on taking more forceful measures against climate change” on an 11-point

scale (0=Strongly opposed, 10=Strongly in favor). The mean expert rating is then used as the

measure of party positions. A second question asked the experts to evaluate the parties on “the

degree of dissent within the parties over climate policy”. Also this measure used an 11-point

scale (0=Complete party unity, 10=Extreme party dissent). The dissent measure was re-coded

in the analysis so that a high score represents more unity and a low score represents more

dissent (calculated as: 12 – dissent). To measure partisan polarization within a system, the

standard deviation of the expert party ratings was used. This measure was calculated for each

nation and not as an aggregate.

Two individual level variables was used to investigate how the effects of political

communication varies between individuals. First, Political awareness was measured with an

index combining measures of political interest and political discussion. Both these variables

are commonly used on their own to measure political awareness. The index showed a high

degree of internal consistency (α=.785). Party preference and party attachment was also

measured by two standardized questions. Party preference was measure by asking respondents

if they consider themselves attached to a particular party. Party attachment was measured on a

three point scale asking respondents how closely attached they felt to their preferred party

(very, somewhat, or not very attached).

Besides party affiliation and political awareness, a number of individual level control

variables found to be important both in general and in the case of environmental attitudes was

used. These included gender (dummy coding), income (quartiles), and education (low,

moderate, high). Dummy variables were also included to control for cross-national variations.

More information about the measurement of the control variables and the other variables can

be found in the appendix. The next section presents the results.

4. Results

To estimate the effect of party stance on individual policy support an OLS regression was

performed in four stages. In the models the individual level measures of policy support were

regressed on the expert estimates of party stance. To control for the moderating effect of party

system characteristics and individual level variables a number of interaction terms are

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included in the second, third and fourth part of the analysis. The interaction terms are entered

in model two. The last two stages of the analysis include the individual level control variables

for gender, income, and education, and the national control variables in the form of dummy

variables. The results of the analysis are presented in table one.

Table 1. Regressing individual policy support on party policy stance

Independent variables Model 11 Model 2

2 Model 3

3 Model 4

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Party stance 0,366(0,008)*** 0,552(0,090)*** 0,583(0,090)*** 0,415(0,094)**

Polarization 0,034(0,035)** 0,314(0,107)*** 0,278(0,106)*** 0,251(0,108)***

Party unity 0,021(0,014) 0,039(0,051) 0,079(0,051) -0,001(0,056)

Political awareness 0,123(0,025)*** -0,095(0,066)** -0,094(0,065)** -0,091(0,065)**

Party closeness 0,028(0,030)* -0,138(0,080)** -0,139(0,079)*** -0,134(0,079)***

Party stance x polarization -0,593(0,015)*** -0,524(0,015)*** -0,500(0,015)***

Party stance x unity -0,134(0,007) -0,251(0,007)* -0,068(0,007)

Party stance x awareness 0,390(0,009)*** 0,361(0,009)*** 0,361(0,009)***

Party stance x closeness 0,263(0,011)*** 0,269(0,011)*** 0,269(0,011)***

Female 0,036(0,038)** 0,035(0,038)**

Income quartiles -0,044(0,021)*** -0,051(0,022)***

Low education -0,023(0,102) -0,021(0,102)

High education 0,125(0,039)*** 0,126(0,039)***

Norway -0,031(0,049)*

New Zealand 0,036(0,051)**

Constant 1,824(0,178)*** 1,183(0,637) 1,139(0,636) 2,078(0,684)**

Adjusted R2 0,160 0,189 0,206 0,208

N 6053 6053 6053 6053

F 231,474*** 157,305*** 121,985*** 107,035***

Entries are standardized beta coefficients with standard errors in parenthesis. *=p<..05, **=p<.01, ***=p<.001.

1= Baseline predictors,

2=Interaction terms,

3=Control variables,

4=Country dummies

The first step in the analysis is to investigate the impact of political communication on public

policy attitudes. As shown in table 1, political parties do have an important and positive

influence on public attitudes towards climate mitigation policies. In all four models, the effect

of party stance on individual policy support is both strong and highly significant. Although

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the size of the coefficient varies some over the four models, the effect is not significantly

attenuated by the inclusion of the interaction terms or the control variables. Together with the

measure of party stance, model one includes the baseline effects of the variables used to

create the interaction terms. Although most of them are significant, only political awareness

seem to contribute to the model.

Unlike a regular linear regression with only main effects, the regression coefficients in a

model including interaction terms cannot be directly interpreted on its own. That is because

the regression coefficient of party position represents the effect of party positions on policy

support in the situation where all interaction terms are zero, which is a highly unlikely

scenario (Ray 2003). To fully account for the magnitude of party positions on individual

policy support, the effect of the interaction terms has to be summed up together with the

interaction effects1. With the use of the coefficients in table 1 and the mean values for the

interaction variables, the marginal effect of party stance on policy support can be calculated

for the ‘average’ individual2. Calculated this way, the effect of a one-unit increase in party

stance leads to a 2,867 point increase in policy support for the average individual.

The next step is to investigate the influence each of the interaction terms. In the second model

the interaction terms controlling for party, party system, and individual level characteristics

are included. These show how the effect of party positions on voter policy support not only is

direct, but that it also is conditional on both individual and party system characteristics. First,

the interaction effect of political polarization and party stance has a significant and negative

coefficient. This means that the more the parties in a system are polarized, the less important

are the parties’ stance to public attitude formation. The effect of polarization and its

interaction with party stance remains significant despite the addition of individual level

control variables. The effect is though slightly attenuated with the inclusion of the control

variables in model three and four. Second, looking at the characteristics of specific parties, the

interaction effect of party unity and party stance is insignificant throughout model 2-4. This

also holds true for the baseline effect of party unity which is insignificant in all models.

1 This is calculated as Policy support = β1(Party stance) + β2(Polarization) + β3(Party unity) + β4(Political

awareness) + β5(Party closeness)

2 ’Average’ here refers to an individual with the mean value for party stance and each of the interaction

variables

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Overall, this seems to indicate that party unity is unimportant to the influence of party stance

on individual policy support.

Model two also include the interaction terms for two individual level characteristics, political

awareness and party attachment. Looking first at the interaction between political awareness

and party stance we can see that it has a strongly significant and positive impact. This

indicates that the impact of party stance on public policy attitudes increases with increasing

political awareness. The coefficient of the interaction term is only slightly reduced with the

inclusion of the control variables, indicating a robust relationship. The inclusion of the

interaction term between political awareness and party stance also change the direction of

baseline effect of political awareness such that it becomes negative. Second, the interaction

term for party attachment and party stance is also significant and positive throughout model 2-

4. That is, the more closely attached an individual is to a party, the more important will the

party’s stance be to the individual’s policy attitudes.

In model three a number of individual level control variables are included. First, the dummy

variable included to control for gender is significant and positive, indicating that women’s

policy attitudes are slightly more impacted by party stance compared to men. Second, income

has a small significant negative effect on policy support, indicating how individuals with

higher income are less likely to support climate policy compared to those with lower income.

Third, of the dummy variables included to control for education only the High education has a

significant positive impact. This indicates that the likelihood of supporting climate mitigation

policies increases with increasing education.

Finally, model four includes the national control variables. Compared to the baseline

category, i.e. Australia, respondents in Norway are significantly less likely to support climate

policy while respondents in New Zealand are significantly more likely to do so. Inclusion of

the national control variables also changes the size of the coefficients of some of the other

independent variables, notably party stance, polarization, and the interaction of the two. To

avoid multicolliniarity only two of the three country dummies could be included in the model.

As a result it is hard to fully estimate the difference between all of the countries. To get a

better understanding of how the effects of political communication vary between different

political contexts, the effect of party stance to public policy support were plotted in a scatter

plot (Figure 1).

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Figure 1. Scatter plot of party policy stance and policy support. Fitted trend lines

representing correlation between parties and individuals for each country.

Figure 1 displays the fitted trend lines for each country. The results in the figure can be

understood as an interaction effect between the country variables and party policy stance

(excluding the effect of the interaction terms), where a steeper curve indicate a stronger

correlation between party stance and individual policy attitudes. The results indicates that the

effect of the parties’ policy stance do vary between countries. Comparatively, the effect of

party policy positions is the strongest in Sweden, whereas partisanship is much less important

in New Zealand. The difference between the countries is especially strong when comparing

parties with a more negative stance on climate policy.

5. Discussion

Overall, the results confirm most of the hypotheses. First, the position political parties take on

climate change does seem to be important for individual voters’ attitudes towards climate

mitigation polices. This effect is both strong and highly significant in all models. Second, the

effect of party positions varies with both party system (degree of polarization) and individual

level (political awareness and party attachment) characteristics. On the individual level,

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variations in political awareness and party attachment were found to significantly impact the

importance of party communications to individual policy attitudes. This discriminatory effect

indicates how different segments of the population base their policy attitudes in different

variables. There are though some unexpected findings. While political awareness and party

attachment, as expected, positively moderates the relationship between party stance and

policy support, the moderation effect of polarization is unexpectedly negative. Counter to the

hypothesized relationship, this indicates that the importance of political communication to

voter attitudes decreases as parties become more polarized in a system. Whether this negative

effect depends on measurement error or something else is hard to say. One possible

explanation is that the moderating effect of polarization on the relationship between party

stance and policy support in turn is moderated by another variable, e.g. political awareness

(Classen and Highton 2009). The moderating effect of polarization would thus be different in

different segments of the population, where for example highly aware individuals could be

more prone to follow party cues under a polarized climate compared to the less aware.

Third, and final, the impact of party positions on individual policy attitudes varies between

countries. Comparing the importance of party communication in different countries we can

see that there is a clear difference between the countries. One surprising finding here is that

party communications seem to be most important in Sweden, a country otherwise known as a

consensual country on climate change. Conversely, Australia, a country often described as

polarized on climate change (e.g. Fielding et al. 2012) seems to be much less partisan in

nature than Sweden. One possible explanation to this anomaly is that climate change is more

is more salient policy issue in Sweden as compared to the other countries. From this

perspective it would also be reasonable to assume that political communication would play a

more important role in public attitude formation. Overall, the findings indicate the importance

of considering individual as well as contextual variation when studying the impacts of

political communication on public attitudes.

One possible problem with interpreting the results is this study is the problem of endogeneity

and omitted variables (Gabel and Scheve 2007). It is for example possible that the causality in

the relationship between party stance and individual policy support runs in the opposite

direction of the hypothesized one (i.e. that public attitudes impact party stance). Similarly,

both variables might be driven by a third omitted variable. While the statistical approach used

in this study cannot control for causality, the results can be interpreted in light of previous

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studies which consistently have found that the causality mainly runs in the direction from

parties to voters (e.g. Gabel and Scheve 2007, Hellström 2008, Ray 2003). To confirm this

assumption, future studies should though control for causality, e.g. by the use of instrumental

variables or by using an experimental approach.

Appendix

Dependent variable

What is your position on the following policy proposals?

Q1: A carbon dioxide tax on fossil fuels used for private consumption?

Q2: A carbon dioxide tax on fossil fuels used by the industrial sector?

Q3: A carbon dioxide tax on fossil fuel producing industries?

Answers on a seven point scale: Completely disagree -3, -2, -1, Neither agree nor disagree 0,

+1, +2, Completely agree +3. The dependent variable is calculated as an index three policy

questions (Q1 + Q2 + Q3)/3.

Independent variables

Party stance

Over the course of 2014, what was the party leadership’s overall position on taking more

forceful measures against climate change? (0) Strongly opposed, (1)-(9), (10) Strongly in

favor

Polarization was measured as the standard deviation of expert replies to the party position

questions.

Party unity

Over the course of 2014, what was the degree of dissent over climate policy within each

party? (0) Complete party unity, (1)-(9), (10) Extreme party dissent

Political awareness

Generally speaking, how interested in politics are you? Very interested (1), somewhat

interested (2), not very interested (3), not interested at all (4)

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When you spend time with friends and family, to what extent do you usually discuss politics?

Never (1), rarely (2), neither rarely, nor often (3), often (4), always (5)

Party attachment

Generally speaking, do you consider yourself attached to one particular party? If so, which

one?

How closely attached are you to this party? Very closely (1), somewhat closely (2), not very

closely (3), Don’t know/Rather not say (4)

Control variables

Gender: dummy variable (1=female, 0=male)

Income: categorical (income percentiles)

Education: categorical (low, moderate, high)

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